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• The semantic network supports mathematical processing. • Brain activation within the semantic network plays a domain-general role in mathematical processing, this role is similar to that in other domains. • Functional connectivity between the semantic and visuospatial networks also plays a domain-specific role, exclusively contributing to mathematical processing. The role of the visuospatial network in mathematical processing has been established, but the role of the semantic network in mathematical processing remains poorly understood. The current study compared different types of inductive reasoning with the functional magnetic resonance imaging (fMRI) technique to investigate the role of the semantic network in mathematical processing and whether the role is domain-general or domain-specific. 32 undergraduate students were recruited to complete tasks involving numerical, geometrical, situational, and verbal inductive reasoning, as well as arithmetical computation. The intensity and pattern analysis of brain activation found that all types of inductive reasoning elicited greater and similar activation than arithmetical computation in the semantic network, mainly including the left middle temporal gyrus, inferior frontal gyrus, angular gyrus, and dorsomedial prefrontal cortex. Furthermore, the intensity and patterns analysis of functional connectivity found that numerical inductive reasoning elicited stronger and dissimilar connectivity between the semantic and visuospatial networks than other types of inductive reasoning and arithmetical computation. These findings suggest that the semantic network not only plays a domain-general role but also exhibits domain-specific interactions with the visuospatial network in mathematical processing. [ABSTRACT FROM AUTHOR]

• Spindle-related brain activation in the right middle temporal gyrus was significantly increased during N2 compared with N3. • Enhanced right middle temporal spindle-related brain activation in N2 negatively correlated with N2 sleep duration. • Utilized simultaneous EEG-fMRI to compare spindle-related brain activation between sleep stage N2 and N3 in two independent samples. The association between spindle metrics and sleep architecture differs during N2 vs. N3 sleep, the underlying neural mechanism is not clearly illustrated. Here, we tested the discrepancy in spindle-related brain activation between N2 and N3 within healthy college students (dataset 1: n = 27, 59 % females, median age 23 years), using simultaneous electroencephalography-functional magnetic resonance imaging (EEG-fMRI). To assess the replicability of the finding, we repeated the analysis among normal adults (independent dataset 2: n = 30, 50 % females, median age 32 years). The finding from dataset 1 indicated significantly increased blood-oxygen level-dependent signal in the right middle temporal gyrus during N2 compared with N3, which was well replicated in dataset 2. Furthermore, correlation analysis was performed to explore the association between this spindle-related brain activation and N2, N3 sleep duration during EEG-fMRI. We conducted the correlation analysis in N2 and N3, respectively. The negative association between spindle-related brain activation in the right middle temporal gyrus and sleep duration was only observed in N2. Our findings emphasize the unique role of spindle-related brain activation in the right middle temporal gyrus during N2 in shortening N2 sleep duration. [ABSTRACT FROM AUTHOR]

• No significant changes were found after right mesial temporal lobe seizures (mTLS). • Left mTLS are associated with a prolonged deafferentiation of the affected regions. • Left mTLS are associated with widespread disorganization of cortical activity. Focal epilepsies disrupt long-range networks with seizure recurrence driving both regional and global alterations in connectivity networks. While prior studies have focused on the interictal consequences, limited data exist on the direct aftermath of focal seizures. We hypothesize that mesial temporal lobe seizures lead to enduring cortical disorganization. The aim was to assess the effects of a mesial temporal lobe seizure on cortical activity and understand how the side of seizure onset influences these consequences. In this retrospective study, high-resolution EEG of patients with mesial temporal lobe epilepsy (mTLE) were analyzed. Groups of patients were identified based on the side of seizure onset. We compared relative powers in different frequency bands between interictal (prior to the seizure) and late postictal (one hour following the seizure) periods. Network-based statistics were employed to compare functional connectivity at source level between periods. Twenty-three patients were included (13 left and 10 right mesial temporal lobe seizures). In patients with left mTLE, we observed a post-seizure increase in the relative spectral power in the delta band (p = 0.001) and a decrease in the relative spectral power in the alpha band (p = 0.013) over the left temporofrontal regions. We isolated a subnetwork that presented a decrease in connectivity strength in alpha band, primarily involving long-range left hemisphere connections (p = 0.042). We also identified a subnetwork that presented a decrease in connectivity strength in theta band, primarily involving interhemispheric connections (p = 0.039). No significant post-seizure changes were found in patients with right mTLE. Left mesial temporal lobe seizures appear to be associated with lasting and widespread disorganization of cortical activity. We propose that the postictal state is associated with a prolonged functional deafferentation of the affected region in patients with left mTLE. This leads to a widespread disorganization of the functional networks, which may be associated with cognitive impairments and promote the progression of epilepsy. Further studies are required to fully understand the functional repercussions. [Display omitted] [ABSTRACT FROM AUTHOR]

• We delineate fundamental neurophysiological mechanisms for how people can act intentionally. • We show that the ability to foresee the effects of action is a role of a theta activity. • There is bi-directional communication between temporo-frontal cortices is essential. • The results conceptually broaden the relevance of theta band activity. The ability to plan and carry out goal-directed behavior presupposes knowledge about the contingencies between movements and their effects. Ideomotor accounts of action control assume that agents integrate action-effect contingencies by creating action-effect bindings, which associate movement patterns with their sensory consequences. However, the neurophysiological underpinnings of action-effect binding are not yet well understood. Given that theta band activity has been linked to information integration, we thus studied action-effect integration in an electrophysiological study with N = 31 healthy individuals with a strong focus on theta band activity. We examined how information between functional neuroanatomical structures is exchanged to enable action planning. We show that theta band activity in a network encompassing the insular cortex (IC), the anterior temporal lobe (ATL), and the inferior frontal cortex (IFC) supports the establishment of action-effect bindings. All regions revealed bi-directional effective connectivities, indicating information transfer between these regions. The IC and ATL create a loop for information integration and the conceptual abstraction of it. The involvement of anterior regions of the IFC, particularly during the acquisition phase of the action-effect, likely reflects episodic control mechanisms in which a past event defines a "template" of what action-effect is to be expected. Taken together, the current findings connect well with major cognitive concepts. Our study suggests a functional relevance of theta band activity in an IC-ATL-IFC network, which in turn implies that basic ideomotor action-effect integration is implemented through theta band activity and effective connectivities between temporo-frontal structures. [ABSTRACT FROM AUTHOR]

• Resting state neural activity is near-critical across all cortical subsystems. • Resting state behaves as an equilibrium system over long timescale. • Subtle fine-tuning of criticality is modulated by cognitive tasks. • Engaged subsystems selectively shift to criticality during perceptual tasks. The constantly evolving world necessitates a brain that can swiftly adapt and respond to rapid changes. The brain, conceptualized as a system performing cognitive functions through collective neural activity, has been shown to maintain a resting state characterized by near-critical neural dynamics, positioning it to effectively respond to external stimuli. However, how near-criticality is dynamically modulated during task performance remains insufficiently understood. In this study, we utilized the prototypical Ising Hamiltonian model to investigate the modulation of near-criticality in neural activity at the cortical subsystem level during perceptual tasks. Specifically, we simulated 2D-Ising models in silico using structural MRI data and empirically estimated the system's state in vivo using functional MRI data. We first replicated previous findings that the resting state is typically near-critical as captured by the Ising model. Importantly, we observed heterogeneous changes in criticality across cortical subsystems during a naturalistic movie-watching task, with visual and auditory regions fine-tuned closer to criticality. A more fine-grained analysis of the ventral temporal cortex during an object recognition task further revealed that only regions selectively responsive to a specific object category were tuned closer to criticality when processing that object category. In conclusion, our study provides empirical evidence from the domain of perception supporting the cognitive critical brain hypothesis that modulating the criticality of subsystems within the brain's hierarchical and modular organization may be a fundamental mechanism for achieving diverse cognitive functions. [ABSTRACT FROM AUTHOR]

• The frontal pole (FP), ventromedial prefrontal cortex (vmPFC) and inferior frontal gyrus (IFG) were commonly activated in visual-art-induced aesthetic experiences. • Bilateral superior temporal gyrus (STG) and striatal areas were commonly activated in music appreciation. • Activation Network Modelling (ANM) further showed that visual art and music engaged quite distinct brain networks. • Our findings support the domain-specific view of aesthetic appreciation and challenge the notion that there is a general "common neural currency" for aesthetic experiences across domains. Aesthetic experiences are characterized by a conscious, emotionally and hedonically rewarding perceptions of a stimulus's aesthetic qualities and are thought to arise from a unique combination of cognitive and affective processes. To pinpoint neural correlates of aesthetic experiences, in the present study, we performed a series of meta-analyses based on the existing functional Magnetic Resonance Imaging (fMRI) studies of art appreciation in visual art (34 experiments, 692 participants) and music (34 experiments, 718 participants). The Activation Likelihood Estimation (ALE) analyses showed that the frontal pole (FP), ventromedial prefrontal cortex (vmPFC), and inferior frontal gyrus (IFG) were commonly activated in visual-art-induced aesthetic experiences, whilst bilateral superior temporal gyrus (STG) and striatal areas were commonly activated in music appreciation. Additionally, task-independent Resting-state Functional Connectivity (RSFC), task-dependent Meta-analytical Connectivity Modelling (MACM) analyses, as well as Activation Network Modeling (ANM) further showed that visual art and music engaged quite distinct brain networks. Our findings support the domain-specific view of aesthetic appreciation and challenge the notion that there is a general "common neural currency" for aesthetic experiences across domains. [ABSTRACT FROM AUTHOR]

• Migraine patients demonstrated significantly lower scores on the MOCA test. • Hippocampal subfields were correlated with cognitive performance in migraine patients. • Hippocampal changes may shed light on potential dementia risks in migraine patients. The etiology of cognitive decline linked to migraine remains unclear, with a growing recurrence rate and potential increased dementia risk among sufferers. Cognitive dysfunction has recently gained attention as a significant problem among migraine sufferers that can be related to alterations in hippocampal function and structure. This study explores hippocampal subfield connectivity and volume changes in migraine patients. We recruited 90 individuals from Alanya University's Neurology Department, including 49 migraine patients and 41 controls, for functional and anatomical imaging. Using the CONN toolbox and FreeSurfer, we assessed functional connectivity and subfield volumes, respectively. Montreal Cognitive Assessment (MOCA) was used to assess cognition in the entire sample. As a result, migraine patients exhibited significantly lower MOCA scores compared to controls (p <.001). Also, we found significant differences in hippocampal subfields between migraine patients and control groups in terms of functional connectivity after adjusting for years of education; here we showed that the left CA3 showed higher connectivity with right MFG and right occipitolateral cortex. Furthermore, the connectivity of left fimbria with the left temporal lobe and hippocampus and the connectivity of the right hippocampal-tail with right insula, heschl's gyrus, and frontorbital cortex were lower in the migraineurs. Additionally, volumes of specific hippocampal subfields were significantly lower in the migraineurs (whole hippocampus p = 0.004, whole hippocampus head p = 0.003, right CA1 head p = 0.006, and right HATA p = 0.005) compared to controls. In conclusion, these findings indicate that migraine-associated cognitive impairment involves significant functional and structural brain changes, particularly in the hippocampus, which may heighten dementia risk. This pioneering study unveils critical hippocampal alterations linked to cognitive function in migraine sufferers, underscoring the potential for these changes to impact dementia development. [ABSTRACT FROM AUTHOR]

• Dynamic ReHo of IPL mediated the relationship between sex and mental rotation. • The genetic and molecular mechanism of sex difference in mental rotation. • Serial mediation models between genes, transporters/receptors, brain biomarkers. Sex differences in mental rotation are a well-documented phenomenon in cognitive research, with implications for the differing prevalence of neuropsychiatric disorders such as autism spectrum disorder (ASD), Alzheimer's disease (AD) and major depressive disorder (MDD) between the sexes. Despite extensive documentation, the biological mechanism underpinning these differences remain elusive. This study aimed to elucidate neural, genetic, and molecular bases of these disparities in mental rotation by integrating data from multimodal magnetic resonance imaging (MRI), transcriptomic and receptor/transporter. We first calculated the dynamic regional homogeneity (dReHo), gray matter volume (GMV) and fractional anisotropy (FA) in voxel-wise manner and parceled them into 246 brain regions based on Brainnetome Atlas. Subsequent analyses involved Pearson Correlations to examine the association between mental rotation performance and dReHo/GMV/FA and two-sample t -tests to delineate gender differences in these indices. Based on the above results, further mediation analysis was conducted to explore the relationship between sex, brain biomarkers and mental rotation. In addition, transcriptome-neuroimaging association analysis and correlation analysis between brain biomarkers and neurotransmitter receptor/transporter distribution were also performed to uncover genetic and molecular mechanisms contributing to the observed sex differences in mental rotation. We found correlations between mental rotation performance and dReHo, GMV and FA of the inferior parietal lobule (IPL) and superior temporal gyrus (STG) and sex effects on these brain biomarkers. Notably, the dReHo of the left IPL mediated the relationship between sex and mental rotation. Further correlation analysis revealed that the proton-coupled oligopeptide transporter PEPT2 (SLC15A2) and interleukin 17 receptor D (IL17RD) were associated with sex-related t-statistic maps and mental rotation-related r-statistic maps of dReHo. Moreover, γ-aminobutyric acid subtype A (GABA A) receptor availability was correlated with the r-statistic of dReHo, while norepinephrine transporter (NET) availability was correlated with its t-statistic. Serial mediation models revealed the indirect effect of these genes on the r-statistic maps through the transporter/receptor and t-statistic maps. Our findings provide novel insights into the biological mechanism underlying sex differences in mental rotation, identifying potential biomarkers for cognitive impairment and explaining variations in prevalence of certain mental disorders between the sexes. These results highlight the necessity of considering sex in research on mental health disorders. [ABSTRACT FROM AUTHOR]

• Hallucinations, including both auditory and visual types, are often associated with alterations in brain structure, particularly in language-related areas. • Significant positive correlations were found between hallucination scores and brain volume in regions previously linked to volume reductions in patients with hallucinations. • Participants with high hallucination proneness for both auditory and visual experiences exhibited higher brain volumes in language areas compared to those experiencing hallucinations rarely or never. • These findings challenge existing models and suggest a need for further research into the complex relationship between brain structure and auditory and visual hallucination experiences. • The results suggest that higher brain volumes in language areas may contribute to hallucination susceptibility in healthy individuals, contrasting the volume reductions seen in patients. Hallucinations, including both auditory and visual forms, are often associated with alterations in brain structure, particularly in specific language-related cortical areas. Existing models propose different frameworks for understanding the relationship between brain volume and hallucination proneness, but practical evidence supporting these models is limited. This study investigated the relationship between hallucination proneness and brain volume in language-related cortical regions, specifically the superior temporal gyrus and Broca's area. A total of 68 participants, primarily university students, completed the Launay-Slade Hallucination Scale (LSHS) to assess hallucination proneness for both auditory and visual experiences. Structural MRI scans were used to measure brain volume in the targeted regions. The results indicated significant positive correlations between LSHS scores and brain volume in the superior temporal gyrus and Broca's area regions previously linked to volume reductions in patients with clinically diagnosed hallucinations. Participants reporting high hallucination proneness for both auditory and visual hallucinations exhibited higher brain volumes in these language areas compared to those experiencing hallucinations rarely or never. These findings challenge existing models by suggesting that higher brain volumes in language-related cortical areas may be associated with increased proneness to both auditory and visual hallucinations in non-clinical populations. This contrasts with the volume reductions seen in patients with clinical hallucinations and highlights the need for further research into the complex interplay between brain structure and hallucinatory experiences. [ABSTRACT FROM AUTHOR]

• We examine how decision-making power influences neural responses to persuasive messages in a partnership investment scenario. • Investors with dominant decision-making power show increased intra-brain functional connectivity in the mentalizing network during persuasive message processing. • Decision-making power significantly modulates how different message types affect interpersonal neural synchronization during persuasion. • This study corroborates the power-responsibility hypothesis, suggesting that decision-making power enhances investors' processing of persuasive messages. Partnership investment is a common form of business where investors have different levels of power and need to persuade each other to reach a consensus. This study investigated the neural mechanisms underlying the impact of decision-making power on persuasive communication in partnership investment, aiming to provide neural evidence to test two competing hypotheses: the power-responsibility hypothesis and the power-overconfidence hypothesis. Using functional near-infrared spectroscopy (fNIRS), we recorded brain activity from persuader-receiver dyads as they engaged in a partnership investment task. Behavioral results showed that receivers' decisions were more affected by persuaders' persuasive messages when receivers had dominant decision-making power. Neurally, the functional connectivity (FC) between the left and right temporo-parietal junctions (lTPJ and rTPJ) of the receiver was significantly increased by their decision-making power. Additionally, we identified four pairs of interpersonal neural synchronization (INS) that exhibited significant enhancement when persuaders used numeric persuasion rather than non-numeric persuasion: lTPJ-rTPJ, left superior temporal gyrus (lSTG)-rTPJ, left middle temporal gyrus (lMTG)-rTPJ, and medial prefrontal cortex (mPFC)-lTPJ. The decision-making power amplified the INS difference in the last three pairs. Furthermore, using a support vector machine (SVM) algorithm, the INS could accurately predict receivers' adoption of persuasive messages when they held dominant decision-making power. Finally, we found that FC at lTPJ-rTPJ and INS at lSTG-rTPJ were positively associated with receivers' adoption of persuasive messages as well. Our study clarifies how decision-making power alters the way individuals process persuasive messages in partnership investment, providing insights into the neural basis of persuasion in group decision-making contexts and supporting the power-responsibility hypothesis. [ABSTRACT FROM AUTHOR]

• We have successfully developed a novel SPECT ligand 123/125I-AD-DRK for cheaper diagnostic nuclear medicine imaging of AD and/or non-AD tauopathies. • 123/125I-AD-DRK can bind to amyloid and tau aggregates deposited in postmortem brains from the patients with AD and PSP, respectively. • 123/125I-AD-DRK can visualize mature amyloid and tau aggregates in the living brains of APP23 and rTg4510 mice, respectively. Non-invasive determination of amyloid-β peptide (Aβ) and tau deposition are important for early diagnosis and therapeutic intervention for Alzheimer's disease (AD) and non-AD tauopathies. In the present study, we investigated the capacity of a novel radioiodinated compound AD-DRK (123/125I-AD-DRK) with 50% inhibitory concentrations of 11 nM and 2 nM for Aβ and tau aggregates, respectively, as a single photon emission computed tomography (SPECT) ligand in living brains. In vitro and ex vivo autoradiography with 125I-AD-DRK was performed in postmortem human and two transgenic (Tg) mice lines with either fibrillar Aβ or tau accumulation, APP23 and rTg4510 mice. SPECT imaging of 123I-AD-DRK was performed in APP23 mice to investigate the ability of AD-DRK to visualize fibrillar protein deposition in the living brain. In-vitro autoradiogram of 125I-AD-DRK showed high specific radioactivity accumulation in the temporal cortex and hippocampus of AD patients and the motor cortex of progressive supranuclear palsy (PSP) patients enriched by Aβ and/or tau aggregates. Ex-vivo autoradiographic images also demonstrated a significant increase in 125I-AD-DRK binding in the forebrain of both APP23 and rTg450 mice compared to their corresponding non-Tg littermates. SPECT imaging successfully captured Aβ deposition in the living brain of aged APP23 mice. The present study developed a novel high-contrast SPECT agent for assisting the diagnosis of AD and non-AD tauopathies, likely benefiting from its affinity for both fibrillar Aβ and tau. [ABSTRACT FROM AUTHOR]

• Pseudoword trials required higher control energy than word trials in reading network areas without auditory input. • Incongruent trials required higher control energy than congruent trials in reading network areas without auditory input. • The left fusiform gyrus required higher control energy in conditions with visual inputs. • The left superior temporal gyrus (STG) required higher control energy in conditions with auditory input. • The left STG, but not the left fusiform gyrus, showed interaction effect between orthographic similarity and modality. Neuroimaging studies have identified functional and structural brain circuits that support reading. However, much less is known about how reading-related functional dynamics are constrained by white matter structure. Network control theory proposes that cortical brain dynamics are linearly determined by the white matter connectome, using control energy to evaluate the difficulty of the transition from one cognitive state to another. Here we apply this approach to linking brain dynamics with reading ability and disability in school-age children. A total of 51 children ages 8.25 -14.6 years performed an in-scanner rhyming task in visual and auditory modalities, with orthographic (spelling) and phonological (rhyming) similarity manipulated across trials. White matter structure and fMRI activation were used conjointly to compute the control energy of the reading network in each condition relative to a null fixation state. We then tested differences in control energy across trial types, finding higher control energy during non-word trials than word trials, and during incongruent trials than congruent trials. ROI analyses further showed a dissociation between control energy of the left fusiform and superior temporal gyrus depending on stimulus modality, with higher control energy for visual modalities in fusiform and higher control energy for auditory modalities in STG. Together, this study highlights that control theory can explain variations on cognitive demands in higher-level abilities such as reading, beyond what can be inferred from either functional or structural MRI measures alone. [ABSTRACT FROM AUTHOR]

• Novel method MQGA enhances quantitative analysis of brain network hubs. • MQGA uses betweenness centrality, degree centrality, and participation coefficient to comprehensively characterize provincial nodes and connector nodes. • Optimal hub node index found at 4 % sparsity, improving hub identification accuracy. • Removing connector hubs impacts network integrity more than removing provincial hubs. • Higher hub stability observed in healthy controls compared to disease groups. Recent advancements in large-scale network studies have shown that connector hubs and provincial hubs are vital for coordinating complex cognitive tasks by facilitating information transfer between and within specialized modules. However, current methods for identifying these hubs often lack standardized measurement criteria, hindering quantitative analysis. This study proposes a novel computational method utilizing multi-graph theoretical index calculations to quantitatively analyze hub attributes in brain networks. Using benchmark network, random simulation network (N = 100), resting fMRI data from the ADHD-200 NYU dataset (HC = 110, ADHD = 146), and the Peking dataset (HC = 120, ADHD = 83), we introduce the Multi-criteria Quantitative Graph Analysis (MQGA) method, which employs betweenness centrality, degree centrality, and participation coefficient to determine the connector (con) hub index and provincial (pro) hub index. The method's accuracy, reliability, and stability were validated through correlation analysis of hub indices and labels, vulnerability tests, and consistency analysis across subjects. Results indicate that as network sparsity increases, the con hub index increases while the pro hub index decreases, with the optimal hub node index at 4 % sparsity. Vulnerability tests revealed that removing con nodes had a greater impact on network integrity than removing pro nodes. Both con and pro exhibited stability in consistency analyses, but con was more stable. The stability of hub scores in disease groups was significantly lower than in the healthy control group. High con values were found in the precuneus, postcentral gyrus, and precentral gyrus, whereas high pro values were identified in the precentral gyrus, postcentral gyrus, superior parietal lobule, precuneus, and superior temporal gyrus. This approach enhances the accuracy and sensitivity of hub node identification, facilitating precise comparisons and producing consistent, replicable results, advancing our understanding of brain network hub nodes, their roles in cognitive processes, and their implications for brain disease research. [ABSTRACT FROM AUTHOR]

Functional near-infrared spectroscopy (fNIRS) is increasingly used to study brain function in infants, but the development and standardization of analysis techniques for use with infant fNIRS data have not paced other technical advances. Here we quantify and compare the effects of different methods of analysis of infant fNIRS data on two independent fNIRS datasets involving 6–9-month-old infants and a third simulated infant fNIRS dataset. With each, we contrast results from a traditional, fixed-array analysis with several functional channel of interest (fCOI) analysis approaches. In addition, we tested the effects of varying the number and anatomical location of potential data channels to be included in the fCOI definition. Over three studies we find that fCOI approaches are more sensitive than fixed-array analyses, especially when channels of interests were defined within-subjects. Applying anatomical restriction and/or including multiple channels in the fCOI definition does not decrease and in some cases increases sensitivity of fCOI methods. Based on these results, we recommend that researchers consider employing fCOI approaches to the analysis of infant fNIRS data and provide some guidelines for choosing between particular fCOI approaches and settings for the study of infant brain function and development.

• Only the right STS could specifically decode attentional orienting triggered by social but not non-social cues. • The right STS/STG could decode attentional orienting across different social but not non-social cues. • The right STS/STG might serve as a unified and dedicated neural locus for various social attention behaviors. Humans appear to be endowed with the ability to readily share attention with interactive partners through the utilization of social direction cues, such as eye gaze and biological motion (BM). Here, we investigated the specialized brain mechanism underlying this fundamental social attention ability by incorporating different types of social (i.e., BM, gaze) and non-social (arrow) cues and combining functional magnetic resonance imaging (fMRI) with a modified central cueing paradigm. Using multi-voxel pattern analysis (MVPA), we found that although gaze- and BM-mediated attentional orienting could be decoded from neural activity in a wide range of brain areas, only the right anterior and posterior superior temporal sulcus (aSTS and pSTS) could specifically decode attentional orienting triggered by social but not non-social cues. Critically, cross-category MVPA further revealed that social attention could be decoded across BM and gaze cues in the right STS and the right superior temporal gyrus (STG). However, these regions could not decode attentional orienting across social and non-social cues. These findings together provide evidence for the existence of a specialized social attention module in the human brain, with the right STS/STG being the critical neural site dedicated to social attention. [ABSTRACT FROM AUTHOR]

• fMRI assessed neural correlates of understanding expected and unexpected actions. • Mirror neuron system brain regions responded to expected actions. • The mirror neuron system and mentalizing system function in concert for unexpected actions. • Functional coupling of both networks and other brain regions occurs only during unexpected actions. • Action expectancy is an important factor affecting action representation. Action understanding involves two distinct processing levels that engage separate neural mechanisms: perception of concrete kinematic information and recognition of abstract action intentions. The mirror neuron system and the mentalizing system have both been linked to concrete action and abstract information processing, but their specific roles remain debatable. Here, we conducted a functional magnetic resonance imaging study with 26 participants who passively observed expected and unexpected actions. We performed whole-brain activation, region of interest, and effective connectivity analyses to investigate the neural correlates of these actions. Whole-brain activation analyses revealed that expected actions were associated with increased activation in the left medial superior frontal gyrus, while unexpected actions were linked to heightened activity in the left supramarginal gyrus, left superior parietal lobule, right inferior temporal gyrus, and left middle frontal gyrus. Region of interest analyses demonstrated that the left ventral premotor cortex exhibited greater activation during the observation of expected actions compared to unexpected actions, while the left inferior frontal gyrus, left superior parietal lobule, and left precuneus showed stronger activation during the observation of unexpected actions. Effective connectivity was observed between the left ventral premotor cortex and the left angular gyrus, left intraparietal sulcus, left dorsal premotor cortex, and left ventromedial prefrontal cortex with the middle frontal gyrus when observing unexpected, but not expected, actions. These findings suggest that expected actions are primarily processed by the mirror neuron system, whereas unexpected actions engage both the mirror neuron system and the mentalizing system, with these systems playing complementary roles in the understanding of unexpected actions. [ABSTRACT FROM AUTHOR]

• Our work offer valuable insights into decompose the dynamic cognitive-neural mechanism processing of the interpersonal emotion regulation (IER). • Our findings reveal that the left middle temporal gyrus and ventrolateral prefrontal cortex serve as pivotal regions for enhancing one's tendency and efficiency in utilizing IER, while also augmenting its regulatory effects. • The findings hold significant clinical implications, providing a foundation for future clinicians to precisely target specific brain regions in individuals with impaired social context, encompassing those afflicted with social anxiety disorder, and depression disorder. Interpersonal emotion regulation (IER) is a crucial ability for effectively recovering from negative emotions through social interaction. It has been emphasized that the empathy network, cognitive control network, and affective generation network sustain the deployment of IER. However, the temporal dynamics of functional connectivity among these networks of IER remains unclear. This study utilized IER task-fMRI and sliding window approach to examine both the stationary and dynamic functional connectivity (dFC) of IER. Fifty-five healthy participants were recruited for the present study. Through clustering analysis, four distinct brain states were identified in dFC. State 1 demonstrated situation modification stage of IER, with strong connectivity between affective generation and visual networks. State 2 exhibited pronounced connectivity between empathy network and both cognitive control and affective generation networks, reflecting the empathy stage of IER. Next, a 'top-down' pattern is observed between the connectivity of cognitive control and affective generation networks during the cognitive control stage of state 3. The affective response modulation stage of state 4 mainly involved connections between empathy and affective generation networks. Specifically, the degree centrality of the left middle temporal gyrus (MTG) mediated the association between one's IER tendency and the regulatory effects in state 2. The betweenness centrality of the left ventrolateral prefrontal cortex (VLPFC) mediated the association between one's IER efficiency and the regulatory effects in state 3. Altogether, these findings revealed that dynamic connectivity transitions among empathy, cognitive control, and affective generation networks, with the left VLPFC and MTG playing dominant roles, evident across the IER processing. [ABSTRACT FROM AUTHOR]

• The general language network of the early deaf brain revealed by meta-analysis. • The left IFG and pMTG robustly participate in supramodal language processing. • More activation in the left calcarine gyrus and the right caudate in deaf individuals. • Cross-modal plasticity and age of sign language acquisition shape language network. • An overall left-lateralized pattern of language with regional lateralization shifts. This meta-analysis summarizes evidence from 44 neuroimaging experiments and characterizes the general linguistic network in early deaf individuals. Meta-analytic comparisons with hearing individuals found that a specific set of regions (in particular the left inferior frontal gyrus and posterior middle temporal gyrus) participates in supramodal language processing. In addition to previously described modality-specific differences, the present study showed that the left calcarine gyrus and the right caudate were additionally recruited in deaf compared with hearing individuals. In addition, this study showed that the bilateral posterior superior temporal gyrus is shaped by cross-modal plasticity, whereas the left frontotemporal areas are shaped by early language experience. Although an overall left-lateralized pattern for language processing was observed in the early deaf individuals, regional lateralization was altered in the inferior frontal gyrus and anterior temporal lobe. These findings indicate that the core language network functions in a modality-independent manner, and provide a foundation for determining the contributions of sensory and linguistic experiences in shaping the neural bases of language processing. [ABSTRACT FROM AUTHOR]

• This study investigates musicians' and nonmusicians' consonant and dissonant perceptions. • Behavioral results show that (non)-/musicians used different features in consonant judgments. • ERP results show similar N1/P2 effects in midline and left-lateralized electrodes. • Musicians' fMRI reveals functional connectivity between MPFC and left auditory cortex. • Spatiotemporal searchlight RSA results show the locus of musicians' N1 in MPFC and auditory cortex, P2 in dACC. The perception of two (or more) simultaneous musical notes, depending on their pitch interval(s), could be broadly categorized as consonant or dissonant. Previous literature has suggested that musicians and non-musicians adopt different strategies when discerning music intervals: while musicians rely on the frequency ratios between the two fundamental frequencies, such as "perfect fifth" (3:2) as consonant and "tritone" (45:32) as dissonant intervals; non-musicians may rely on the presence of 'roughness' or 'beats', generated by the difference of fundamental frequencies, as the key elements of 'dissonance'. The separate Event-Related Potential (ERP) differences in N1 and P2 along the midline electrodes provided evidence congruent with such 'separate reliances'. To replicate and to extend, in this study we reran the previous experiment, and separately collected fMRI data of the same protocol (with sparse sampling modifications). The behavioral and EEG results largely corresponded to our previous finding. The fMRI results, with the joint analyses by univariate, psycho-physiological interaction, and representational similarity analysis (RSA) approaches, further reinforce the involvement of central midline-related brain regions, such as ventromedial prefrontal and dorsal anterior cingulate cortex, in consonant/dissonance judgments. The final spatiotemporal searchlight RSA provided convincing evidence that the medial prefrontal cortex, along with the bilateral superior temporal cortex, is the joint locus of midline N1 and dorsal anterior cingulate cortex for the P2 effect (for musicians). Together, these analyses reaffirm that musicians rely more on experience-driven knowledge for consonance/dissonance perception; but also demonstrate the advantages of multiple analyses in constraining the findings from both EEG and fMRI. [ABSTRACT FROM AUTHOR]

• Sentence comprehension does rely on overall verbal short-term memory (vSTM) capacity. • Increases in syntactic complexity reduce the influence of vSTM on correct comprehension of the sentence, suggesting a language-specific resource. • Lesions in the left anterior temporal lobe increase the difficulties to resolve increasingly complex syntactic structure, which is a language-specific competence. Sentence comprehension requires the integration of linguistic units presented in a temporal sequence based on a non-linear underlying syntactic structure. While it is uncontroversial that storage is mandatory for this process, there are opposing views regarding the relevance of general short-term-/working-memory capacities (STM/WM) versus language specific resources. Here we report results from 43 participants with an acquired brain lesion in the extended left hemispheric language network and resulting language deficits, who performed a sentence-to-picture matching task and an experimental task assessing phonological short-term memory. The sentence task systematically varied syntactic complexity (embedding depth and argument order) while lengths, number of propositions and plausibility were kept constant. Clinical data including digit-/ block-spans and lesion size and site were additionally used in the analyses. Correlational analyses confirm that performance on STM/WM-tasks (experimental task and digit-span) are the only two relevant predictors for correct sentence-picture-matching, while reaction times only depended on age and lesion size. Notably increasing syntactic complexity reduced the correlational strength speaking for the additional recruitment of language specific resources independent of more general verbal STM/WM capacities, when resolving complex syntactic structure. The complementary lesion-behaviour analysis yielded different lesion volumes correlating with either the sentence-task or the STM-task. Factoring out STM measures lesions in the anterior temporal lobe correlated with a larger decrease in accuracy with increasing syntactic complexity. We conclude that overall sentence comprehension depends on STM/WM capacity, while increases in syntactic complexity tax another independent cognitive resource. [ABSTRACT FROM AUTHOR]

• We explored brain correlates of self-objectification and related emotional response. • Neural activity was recorder in 25 women exposed to objectifying interactions. • Being objectified increased activity in cortical and subcortical brain regions. • Self-objectification tendency and shame response increased activity in the caudate. • Importance of neuroscientific perspective for understanding toxic social dynamic. Female Sexual Objectification refers to perceiving and treating women based on their body appearance. This phenomenon may serve as a precursor for dysfunctional behaviors, particularly among females prone to self -objectification and experiencing shame emotions. Understanding this challenging trajectory by disclosing its neural consequences may be crucial for comprehending extreme psychopathological outcomes. However, investigations in this sense are still scarce. The present study explores the neural correlates of female participants' experiences of being objectified and their relationship with self-objectification, emotional responses and individual dispositions in self-esteem, emotion regulation abilities and self-conscious emotion proneness. To this aim, 25 female participants underwent an fMRI experimental session while they were exposed to interpersonal encounters with objectifying or non-objectifying men. Participants' experienced emotions and levels of attention shifted toward their bodies (self-objectification) was reported after each interaction. The results revealed increased brain activity in objectifying contexts, impacting cortical (frontal, occipital and temporal cortex) and subcortical regions (thalamus, and hippocampus) involved in visual, emotion, and social processing. Remarkably, the inferior temporal gyrus emerged as a crucial neural hub associated in opposite ways with self-esteem and the self-conscious emotion of shame, highlighting its role in self-referential processing during social dynamics. This study points out the importance of adopting a neuroscientific perspective for a deeper understanding of sexual objectification, and to shed light on its possible neural consequences. [ABSTRACT FROM AUTHOR]

• PD, MSA, and HC patients present distinctly different patterns of association across the clinical symptomatology - cortical excitability - neuroimaging network. • A wide range of associations centered around RMT were found in the HC group, which were disrupted in PD and MSA patient populations. • The joint metric involving ICF and the FC between the right M1 and left temporal middle gyrus can facilitate early differentiation of PD and MSA. Due to a high degree of symptom overlap in the early stages, with movement disorders predominating, Parkinson's disease (PD) and multiple system atrophy (MSA) may exhibit a similar decline in motor areas, yet they differ in their spread throughout the brain, ultimately resulting in two distinct diseases. Drawing upon neuroimaging analyses and altered motor cortex excitability, potential diffusion mechanisms were delved into, and comparisons of correlations across distinct disease groups were conducted in a bid to uncover significant pathological disparities. We recruited thirty-five PD, thirty-seven MSA, and twenty-eight matched controls to conduct clinical assessments, electromyographic recording, and magnetic resonance imaging scanning during the "on medication" state. Patients with neurodegeneration displayed a widespread decrease in electrophysiology in bilateral M1. Brain function in early PD was still in the self-compensatory phase and there was no significant change. MSA patients demonstrated an increase in intra-hemispheric function coupled with a decrease in diffusivity, indicating a reduction in the spread of neural signals. The level of resting motor threshold in healthy aged showed broad correlations with both clinical manifestations and brain circuits related to left M1, which was absent in disease states. Besides, ICF exhibited distinct correlations with functional connections between right M1 and left middle temporal gyrus in all groups. The present study identified subtle differences in the functioning of PD and MSA related to bilateral M1. By combining clinical information, cortical excitability, and neuroimaging intuitively, we attempt to bring light on the potential mechanisms that may underlie the development of neurodegenerative disease. [ABSTRACT FROM AUTHOR]

• We show stable representations of time and space in right parietal areas. • Memory traces for time and space can be decoded without direct perception. • Results reinforce the idea of duration-selective coding in the right IPS. • The right IPS might form the basis for time-space-interferences. Time and space form an integral part of every human experience, and for the neuronal representation of these perceptual dimensions, previous studies point to the involvement of the right-hemispheric intraparietal sulcus and structures in the medial temporal lobe. Here we used multi-voxel pattern analysis (MVPA) to investigate long-term memory traces for temporal and spatial stimulus features in those areas. Participants were trained on four images associated with short versus long durations and with left versus right locations. Our results demonstrate stable representations of both temporal and spatial information in the right posterior intraparietal sulcus. Building upon previous findings of stable neuronal codes for directly perceived durations and locations, these results show that the reactivation of long-term memory traces for temporal and spatial features can be decoded from neuronal activation patterns in the right parietal cortex. [ABSTRACT FROM AUTHOR]

The complexity of fMRI signals quantifies temporal dynamics of spontaneous neural activity, which has been increasingly recognized as providing important insights into cognitive functions and psychiatric disorders. However, its heritability and structural underpinnings are not well understood. Here, we utilize multi-scale sample entropy to extract resting-state fMRI complexity in a large healthy adult sample from the Human Connectome Project. We show that fMRI complexity at multiple time scales is heritable in broad brain regions. Heritability estimates are modest and regionally variable. We relate fMRI complexity to brain structure including surface area, cortical myelination, cortical thickness, subcortical volumes, and total brain volume. We find that surface area is negatively correlated with fine-scale complexity and positively correlated with coarse-scale complexity in most cortical regions, especially the association cortex. Most of these correlations are related to common genetic and environmental effects. We also find positive correlations between cortical myelination and fMRI complexity at fine scales and negative correlations at coarse scales in the prefrontal cortex, lateral temporal lobe, precuneus, lateral parietal cortex, and cingulate cortex, with these correlations mainly attributed to common environmental effects. We detect few significant associations between fMRI complexity and cortical thickness. Despite the non-significant association with total brain volume, fMRI complexity exhibits significant correlations with subcortical volumes in the hippocampus, cerebellum, putamen, and pallidum at certain scales. Collectively, our work establishes the genetic basis and structural correlates of resting-state fMRI complexity across multiple scales, supporting its potential application as an endophenotype for psychiatric disorders. • fMRI complexity at multiple time scales is heritable across most brain regions. • fMRI complexity is related to surface area (SA) and cortical myelination (CM). • SA-complexity correlations mainly relate to common genetic and environmental effects. • CM-complexity correlations are primarily associated with environmental correlations. • fMRI complexity at certain scales relates to the volumes of some subcortical areas. [ABSTRACT FROM AUTHOR]

The medial temporal lobe (MTL) consists of several regions thought to be involved in learning and memory. However, the degree of functional specialization among these regions remains unclear. Previous studies have demonstrated effects of both content and processing stage, but findings have been inconsistent. In particular, studies have suggested that the perirhinal cortex is more involved in object processing than spatial processing, while other regions such as the parahippocampal cortex have been implicated in spatial processing. In this study, functional magnetic resonance imaging (fMRI) optimized for the MTL region was used to probe MTL activation during intentional encoding of object identities or positions. A region of interest analysis showed that object encoding evoked stronger activation than position encoding in bilateral perirhinal cortex, temporopolar cortex, parahippocampal cortex, hippocampus and amygdala. Results also indicate an unexpected significant correlation in activation level between anterior and posterior portions in both the left parahippocampal cortex and left hippocampus. Exploratory analysis did not show any regional content effects during preparation and rehearsal stages. These results provide additional evidence for functional specialization within the MTL, but were less clear regarding the specific nature of content specificity in these regions.

• Environmental exposures are linked to cognitive outcomes like attention deficits. • Home radon exposure has seldom been studied for its effects aside from cancer. • We assessed links between home radon exposure and neural dynamics serving attention. • Youths with greater radon exposure showed atypical attention network recruitment. • Radon exposure also robustly modulated expected neurodevelopmental trajectories. Radon is a naturally occurring gas that contributes significantly to radiation in the environment and is the second leading cause of lung cancer globally. Previous studies have shown that other environmental toxins have deleterious effects on brain development, though radon has not been studied as thoroughly in this context. This study examined the impact of home radon exposure on the neural oscillatory activity serving attention reorientation in youths. Fifty-six participants (ages 6–14 years) completed a classic Posner cuing task during magnetoencephalography (MEG), and home radon levels were measured for each participant. Time-frequency spectrograms indicated stronger theta (3–7 Hz, 300–800 ms), alpha (9–13 Hz, 400–900 ms), and beta responses (14–24 Hz, 400–900 ms) during the task relative to baseline. Source reconstruction of each significant oscillatory response was performed, and validity maps were computed by subtracting the task conditions (invalidly cued – validly cued). These validity maps were examined for associations with radon exposure, age, and their interaction in a linear regression design. Children with greater radon exposure showed aberrant oscillatory activity across distributed regions critical for attentional processing and attention reorientation (e.g., dorsolateral prefrontal cortex, and anterior cingulate cortex). Generally, youths with greater radon exposure exhibited a reverse neural validity effect in almost all regions and showed greater overall power relative to peers with lesser radon exposure. We also detected an interactive effect between radon exposure and age where youths with greater radon exposure exhibited divergent developmental trajectories in neural substrates implicated in attentional processing (e.g., bilateral prefrontal cortices, superior temporal gyri, and inferior parietal lobules). These data suggest aberrant, but potentially compensatory neural processing as a function of increasing home radon exposure in areas critical for attention and higher order cognition. [ABSTRACT FROM AUTHOR]

• Venous arch structures of hippocampus are shown using high resolution SWI at 7T. • Hippocampal venous density is calculated to characterize hippocampal oxygen utilization. • χ vein in BVR and IVV are used to assess oxygen consumption in MTL and hippocampus. • Increased χ vein in IVV are found with age. Mapping the small venous vasculature of the hippocampus in vivo is crucial for understanding how functional changes of hippocampus evolve with age. Oxygen utilization in the hippocampus could serve as a sensitive biomarker for early degenerative changes, surpassing hippocampal tissue atrophy as the main source of information regarding tissue degeneration. Using an ultrahigh field (7T) susceptibility-weighted imaging (SWI) sequence, it is possible to capture oxygen-level dependent contrast of submillimeter-sized vessels. Moreover, the quantitative susceptibility mapping (QSM) results derived from SWI data allow for the simultaneous estimation of venous oxygenation levels, thereby enhancing the understanding of hippocampal function. In this study, we proposed two potential imaging markers in a cohort of 19 healthy volunteers aged between 20 and 74 years. These markers were: 1) hippocampal venous density on SWI images and 2) venous susceptibility (Δ χ vein) in the hippocampus-associated draining veins (the inferior ventricular veins (IVV) and the basal veins of Rosenthal (BVR) using QSM images). They were chosen specifically to help characterize the oxygen utilization of the human hippocampus and medial temporal lobe (MTL). As part of the analysis, we demonstrated the feasibility of measuring hippocampal venous density and Δ χ vein in the IVV and BVR at 7T with high spatial resolution (0.25 × 0.25 × 1 mm3). Our results demonstrated the in vivo reconstruction of the hippocampal venous system, providing initial evidence regarding the presence of the venous arch structure within the hippocampus. Furthermore, we evaluated the age effect of the two quantitative estimates and observed a significant increase in Δ χ vein for the IVV with age (p = 0.006, r2 = 0.369). This may suggest the potential application of Δ χ vein in IVV as a marker for assessing changes in atrophy-related hippocampal oxygen utilization in normal aging and neurodegenerative diseases such as AD and dementia. [ABSTRACT FROM AUTHOR]

• Seven brain regions show both reduced cortical thickness and abnormal QSM levels in AD patients. • We observed significant correlations across AD patients between region-specific cortical thickness and network topology. • Decreased correlation between QSM value and structural network efficiency in AD patients at individual level across brain regions with reduced cortical thickness and aberrant QSM value. Aberrant susceptibility due to iron level abnormality and brain network disconnections are observed in Alzheimer's disease (AD), with disrupted iron homeostasis hypothesized to be linked to AD pathology and neuronal loss. However, whether associations exist between abnormal quantitative susceptibility mapping (QSM), brain atrophy, and altered brain connectome in AD remains unclear. Based on multi-parametric brain imaging data from 30 AD patients and 26 healthy controls enrolled at the China-Japan Friendship Hospital, we investigated the abnormality of the QSM signal and volumetric measure across 246 brain regions in AD patients. The structural and functional connectomes were constructed based on diffusion MRI tractography and functional connectivity, respectively. The network topology was quantified using graph theory analyses. We identified seven brain regions with both reduced cortical thickness and abnormal QSM (p < 0.05) in AD, including the right superior frontal gyrus, left superior temporal gyrus, right fusiform gyrus, left superior parietal lobule, right superior parietal lobule, left inferior parietal lobule, and left precuneus. Correlations between cortical thickness and network topology computed across patients in the AD group resulted in statistically significant correlations in five of these regions, with higher correlations in functional compared to structural topology. We computed the correlation between network topological metrics, QSM value and cortical thickness across regions at both individual and group-averaged levels, resulting in a measure we call spatial correlations. We found a decrease in the spatial correlation of QSM and the global efficiency of the structural network in AD patients at the individual level. These findings may provide insights into the complex relationships among QSM, brain atrophy, and brain connectome in AD. [ABSTRACT FROM AUTHOR]

• We investigated the structural connectome asymmetry of autism spectrum disorder. • Atypical asymmetry patterns were observed in sensory and default-mode regions. • Atypical asymmetry was associated with altered network communication efficiency. • Communication symptoms and nonverbal intelligence were associated with asymmetry. Autism spectrum disorder is a common neurodevelopmental condition that manifests as a disruption in sensory and social skills. Although it has been shown that the brain morphology of individuals with autism is asymmetric, how this differentially affects the structural connectome organization of each hemisphere remains under-investigated. We studied whole-brain structural connectivity-based brain asymmetry in individuals with autism using diffusion magnetic resonance imaging obtained from the Autism Brain Imaging Data Exchange initiative. By leveraging dimensionality reduction techniques, we constructed low-dimensional representations of structural connectivity and calculated their asymmetry index. Comparing the asymmetry index between individuals with autism and neurotypical controls, we found atypical structural connectome asymmetry in the sensory and default-mode regions, particularly showing weaker asymmetry towards the right hemisphere in autism. Network communication provided topological underpinnings by demonstrating that the inferior temporal cortex and limbic and frontoparietal regions showed reduced global network communication efficiency and decreased send-receive network navigation in the inferior temporal and lateral visual cortices in individuals with autism. Finally, supervised machine learning revealed that structural connectome asymmetry could be used as a measure for predicting communication-related autistic symptoms and nonverbal intelligence. Our findings provide insights into macroscale structural connectome alterations in autism and their topological underpinnings. [ABSTRACT FROM AUTHOR]

• We propose a novel imaging method to study gait-related brain function. • We used a dual-injection paradigm and for each participant acquired two static FDG-PET scans. • There was a gait-related increase in glucose metabolism in discrete locomotor brain regions during walking relative to standing. • Our methods reduce participant burden making repeated study visits redundant. • Our methods could be employed in neurodegenerative disorders adversely affecting gait. Gait is an excellent indicator of physical, emotional, and mental health. Previous studies have shown that gait impairments in ageing are common, but the neural basis of these impairments are unclear. Existing methodologies are suboptimal and novel paradigms capable of capturing neural activation related to real walking are needed. In this study, we used a hybrid PET/MR system and measured glucose metabolism related to both walking and standing with a dual-injection paradigm in a single study session. For this study, 15 healthy older adults (10 females, age range: 60.5-70.7 years) with normal cognition were recruited from the community. Each participant received an intravenous injection of [18F]-2-fluoro-2-deoxyglucose (FDG) before engaging in two distinct tasks, a static postural control task (standing) and a walking task. After each task, participants were imaged. To discern independent neural functions related to walking compared to standing, we applied a bespoke dose correction to remove the residual 18F signal of the first scan (PET STAND) from the second scan (PET WALK) and proportional scaling to the global mean, cerebellum, or white matter (WM). Whole-brain differences in walking-elicited neural activity measured with FDG-PET were assessed using a one-sample t-test. In this study, we show that a dual-injection paradigm in healthy older adults is feasible with biologically valid findings. Our results with a dose correction and scaling to the global mean showed that walking, compared to standing, increased glucose consumption in the cuneus (Z = 7.03), the temporal gyrus (Z = 6.91) and the orbital frontal cortex (Z = 6.71). Subcortically, we observed increased glucose metabolism in the supraspinal locomotor network including the thalamus (Z = 6.55), cerebellar vermis and the brainstem (pedunculopontine/mesencephalic locomotor region). Exploratory analyses using proportional scaling to the cerebellum and WM returned similar findings. Here, we have established the feasibility and tolerability of a novel method capable of capturing neural activations related to actual walking and extended previous knowledge including the recruitment of brain regions involved in sensory processing. Our paradigm could be used to explore pathological alterations in various gait disorders. [ABSTRACT FROM AUTHOR]

For sentence comprehension, information carried by semantic relations between constituents must be combined with other information to decode the constituent structure of a sentence, due to atypical and noisy situations of language use. Neural correlates of decoding sentence structure by semantic information have remained largely unexplored. In this functional MRI study, we examine the neural basis of semantic-driven syntactic parsing during sentence reading and compare it with that of other types of syntactic parsing driven by word order and case marking. Chinese transitive sentences of various structures were investigated, differing in word order, case making, and agent-patient semantic relations (i.e., same vs. different in animacy). For the non-canonical unmarked sentences without usable case marking, a semantic-driven effect triggered by agent-patient ambiguity was found in the left inferior frontal gyrus opercularis (IFGoper) and left inferior parietal lobule, with the activity not being modulated by naturalness factors of the sentences. The comparison between each type of non-canonical sentences with canonical sentences revealed that the non-canonicity effect engaged the left posterior frontal and temporal regions, in line with previous studies. No extra neural activity was found responsive to case marking within the non-canonical sentences. A word order effect across all types of sentences was also found in the left IFGoper, suggesting a common neural substrate between different types of parsing. The semantic-driven effect was also observed for the non-canonical marked sentences but not for the canonical sentences, suggesting that semantic information is used in decoding sentence structure in addition to case marking. The current findings illustrate the neural correlates of syntactic parsing with semantics, and provide neural evidence of how semantics facilitates syntax together with other information., Competing Interests: Declaration of competing interest None., (Copyright © 2024. Published by Elsevier Inc.)

The neural architecture of semantic knowledge comprises two key structures: (i) A set of widely dispersed regions, located adjacent to the sensorimotor cortices, serve as spokes that represent various modality-specific and context-dependent contents. (ii) The anterior-temporal lobe (ATL) serves as a hub that computes the nonlinear mappings required to transform modality-specific information into pan-modality, multifaceted concepts. Little is understood regarding whether neural dynamics between the hub and spokes might flexibly alter depending on the nature of a concept and how it impinges upon behaviour. Using fMRI, we demonstrate for the first time that the ATL serves as a 'pivot' which dynamically forms flexible long-range networks with cortical modules specialised for different domains (in the present case, the knowledge about actions and places). In two experiments, we manipulated semantic congruity and asked participants to recognise visually presented items. In Experiment 1 (dual-object displays), the ATL increased its functional coupling with the bilateral frontoparietal action-sensitive system when the objects formed a pair that permitted semantically meaningful action. In Experiment 2 (objects embedded in a scene), the ATL augmented its coupling with the retrosplenial cortex of the place-sensitive system when the objects and scene formed a semantically coherent ensemble. Causative connectivity revealed that, while communication between the hub and spokes was bidirectional, the hub's directional impact on spokes dwarfed the strength of the inverse spoke-to-hub connectivity. Furthermore, the size of behavioural congruity effects co-varied with the strength of neural coupling between the ATL hub and action- / place-related spokes, evident both at the within -individual level (the behavioural fluctuation across scanning runs) and between -individual level (the behavioural variation of between participants). Together, these findings have important implications for understanding the machinery that links neural dynamics with semantic cognition. • Object recognition recruits the anterior temporal lobe (ATL), regardless of tasks and stimuli • Processing semantic congruity about action and place recruits respective domain-specific regions • Neural dynamics between the ATL and action/place-specific regions co-varies with behavioural congruity effects • Semantic knowledge requires a division of labour between domain-general (ATL) and domain-specific regions [ABSTRACT FROM AUTHOR]

In this study we propose a deformation-based framework to jointly model the influence of aging and Alzheimer's disease (AD) on the brain morphological evolution. Our approach combines a spatio-temporal description of both processes into a generative model. A reference morphology is deformed along specific trajectories to match subject specific morphologies. It is used to define two imaging progression markers: 1) a morphological age and 2) a disease score. These markers can be computed regionally in any brain region. The approach is evaluated on brain structural magnetic resonance images (MRI) from the ADNI database. The model is first estimated on a control population using longitudinal data, then, for each testing subject, the markers are computed cross-sectionally for each acquisition. The longitudinal evolution of these markers is then studied in relation with the clinical diagnosis of the subjects and used to generate possible morphological evolutions. In the model, the morphological changes associated with normal aging are mainly found around the ventricles, while the Alzheimer's disease specific changes are located in the temporal lobe and the hippocampal area. The statistical analysis of these markers highlights differences between clinical conditions even though the inter-subject variability is quite high. The model is also generative since it can be used to simulate plausible morphological trajectories associated with the disease. Our method quantifies two interpretable scalar imaging biomarkers assessing respectively the effects of aging and disease on brain morphology, at the individual and population level. These markers confirm the presence of an accelerated apparent aging component in Alzheimer's patients but they also highlight specific morphological changes that can help discriminate clinical conditions even in prodromal stages. More generally, the joint modeling of normal and pathological evolutions shows promising results to describe age-related brain diseases over long time scales. [ABSTRACT FROM AUTHOR]

Recent behavioural evidence shows that visual displays of two individuals interacting are not simply encoded as separate individuals, but as an interactive unit that is 'more than the sum of its parts'. Recent functional magnetic resonance imaging (fMRI) evidence shows the importance of the posterior superior temporal sulcus (pSTS) in processing human social interactions, and suggests that it may represent human-object interactions as qualitatively 'greater' than the average of their constituent parts. The current study aimed to investigate whether the pSTS or other posterior temporal lobe region(s): 1) Demonstrated evidence of a dyadic information effect - that is, qualitatively different responses to an interacting dyad than to averaged responses of the same two interactors, presented in isolation, and; 2) Significantly differentiated between different types of social interactions. Multivoxel pattern analysis was performed in which a classifier was trained to differentiate between qualitatively different types of dyadic interactions. Above-chance classification of interactions was observed in 'interaction selective' pSTS-I and extrastriate body area (EBA), but not in other regions of interest (i.e. face-selective STS and mentalizing-selective temporo-parietal junction). A dyadic information effect was not observed in the pSTS-I, but instead was shown in the EBA; that is, classification of dyadic interactions did not fully generalise to averaged responses to the isolated interactors, indicating that dyadic representations in the EBA contain unique information that cannot be recovered from the interactors presented in isolation. These findings complement previous observations for congruent grouping of human bodies and objects in the broader lateral occipital temporal cortex area. • pSTS and EBA classify between different dynamic interactions. • EBA is sensitive to (uniquely) dyadic interaction information. • These findings support previous evidence for grouping of interacting people/objects in LOTC. [ABSTRACT FROM AUTHOR]

Research on how the brain construes meaning during language use has prompted two conflicting accounts. According to the 'grounded view', word understanding involves quick reactivations of sensorimotor (embodied) experiences evoked by the stimuli, with simultaneous or later engagement of multimodal (conceptual) systems integrating information from various sensory streams. Contrariwise, for the 'symbolic view', this capacity depends crucially on multimodal operations, with embodied systems playing epiphenomenal roles after comprehension. To test these contradictory hypotheses, the present magnetoencephalography study assessed implicit semantic access to grammatically constrained action and non-action verbs (n = 100 per category) while measuring spatiotemporally precise signals from the primary motor cortex (M1, a core region subserving bodily movements) and the anterior temporal lobe (ATL, a putative multimodal semantic hub). Convergent evidence from sensor- and source-level analyses revealed that increased modulations for action verbs occurred earlier in M1 (∼130–190 ms) than in specific ATL hubs (∼250–410 ms). Moreover, machine-learning decoding showed that trial-by-trial classification peaks emerged faster in M1 (∼100–175 ms) than in the ATL (∼345–500 ms), with over 71% accuracy in both cases. Considering their latencies, these results challenge the 'symbolic view' and its implication that sensorimotor mechanisms play only secondary roles in semantic processing. Instead, our findings support the 'grounded view', showing that early semantic effects are critically driven by embodied reactivations and that these cannot be reduced to post-comprehension epiphenomena, even when words are individually classified. Briefly, our study offers non-trivial insights to constrain fine-grained models of language and understand how meaning unfolds in neural time. [ABSTRACT FROM AUTHOR]

The extent to which brains respond similarly to a specific stimulus, across a small group of individuals, has been previously found to predict out-of-sample aggregate preference for that stimulus. However, the location in the brain where neural similarity predicts out-of-sample preference remains unclear. In this article, we attempt to identify the neural substrates in three functional magnetic resonance imaging (fMRI) studies. Two fMRI studies (N = 40 and 20), using previously broadcasted TV commercials, show that spatiotemporal neural similarity at temporal lobe and cerebellum predict out-of-sample preference and recall. A follow-up fMRI study (N = 28) with previously unseen movie-trailers replicated the predictive effect of neural similarity. Moreover, neural similarity provided unique information on out-of-sample preference above and beyond in-sample preference. Overall, the findings suggest that neural similarity at temporal lobe and cerebellum – traditionally associated with sensory integration and emotional processing – may reflect the level of engagement with video stimuli. Image 1 • Neural similarity during video watching predicts preference, but it is unclear exactly which brain areas are predictive. • Three fMRI studies involving TV ads and movie-trailers found robust predictive effects at temporal lobe and cerebellum. • These areas are associated with sensory integration and emotional processing. • No such effect was found in brain areas associated with perception and valuation. • Neural similarity offers unique information on population preference on top of neural activation and individual preference. [ABSTRACT FROM AUTHOR]

More than two decades of functional magnetic resonance imaging (fMRI) of the human brain have succeeded to identify, with a growing level of precision, the neural basis of multiple cognitive skills within various domains (perception, sensorimotor processes, language, emotion and social cognition ...). Progress has been made in the comprehension of the functional organization of localized brain areas. However, the long time required for fMRI acquisition limits the number of experimental conditions performed in a single individual. As a consequence, distinct brain localizations have mostly been studied in separate groups of participants, and their functional relationships at the individual level remain poorly understood. To address this issue, we report here preliminary results on a database of fMRI data acquired on 78 individuals who each performed a total of 29 experimental conditions, grouped in 4 cross-domains functional localizers. This protocol has been designed to efficiently isolate, in a single session, the brain activity associated with language, numerical representation, social perception and reasoning, premotor and visuomotor representations. Analyses are reported at the group and at the individual level, to establish the ability of our protocol to selectively capture distinct regions of interest in a very short time. Test-retest reliability was assessed in a subset of participants. The activity evoked by the different contrasts of the protocol is located in distinct brain networks that, individually, largely replicate previous findings and, taken together, cover a large proportion of the cortical surface. We provide detailed analyses of a subset of regions of relevance: the left frontal, left temporal and middle frontal cortices. These preliminary analyses highlight how combining such a large set of functional contrasts may contribute to establish a finer-grained brain atlas of cognitive functions, especially in regions of high functional overlap. Detailed structural images (structural connectivity, micro-structures, axonal diameter) acquired in the same individuals in the context of the ARCHI database provide a promising situation to explore functional/structural interdependence. Additionally, this protocol might also be used as a way to establish individual neurofunctional signatures in large cohorts. • Presentation of functional localizers and large database to be presented and diffused in the community (soon available in HBP). • Detailed functional description of intermixed correlates of language and social cognition along the temporal lobe. • Detailed functional description of intermixed correlates of numerical, motor and visuospatial cognition within the temporal lobe. • Subject level analysis for protocol robustness. [ABSTRACT FROM AUTHOR]

Memory formation transforms experiences into durable engrams. The stabilization critically depends on processes during and after learning, and involves hippocampal-medial prefrontal interactions that appear to be mediated by the nucleus reuniens of the thalamus in rodents, which corresponds to the human medioventral thalamus. How this region contributes to durable memory formation in humans is, however, unclear. Furthermore, the anterior-, lateral dorsal-, and mediodorsal nuclei appear to promote mnemonic function as well. We hypothesized that durable memory formation is associated with increases in thalamo-cortical interactions during encoding and consolidation. Thirty-three human subjects underwent fMRI while studying picture-location associations. To assess consolidation, resting-state brain activity was measured after study and was compared to a pre-study baseline. Memory was tested on the same day and 48 h later. While "weak" memories could only be remembered at the immediate test, "durable" memories persisted also after the delay. We found increased coupling of the medioventral-, adjacent anterior-, lateral dorsal-, and mediodorsal thalamus with the hippocampus and surrounding medial temporal lobe, as well as with anterior and posterior midline regions related to durable memory encoding. The medioventral and lateral dorsal thalamus showed increased connectivity with posterior medial and parietal cortex from baseline to post-encoding rest, positively scaling with the proportion of durable memories formed across subjects. Additionally, the lateral dorsal thalamus revealed consolidation-related coupling with the inferior temporal, retrosplenial, and medial prefrontal cortex. We suggest that thalamo-cortical cross-talk strengthens mnemonic representations at initial encoding, and that cortical coupling of specific thalamic subregions supports consolidation thereafter. • Thalamo-cortical interactions support memory encoding. • Medioventral and lateral dorsal thalamic connectivity supports consolidation. • Thalamo-cortical effects are specifically linked to durable memory formation. [ABSTRACT FROM AUTHOR]

The Human Connectome Project (HCP) has a 7T component that aims to study the human brain's organization and function with high spatial and temporal resolution fMRI and diffusion-weighted acquisitions. For whole brain applications at 7T, a major weakness however remains the heterogeneity of the radiofrequency transmission field ( B 1 + ), which prevents from achieving an optimal signal and contrast homogeneously throughout the brain. In this work, we use parallel transmission (pTX) Universal Pulses (UP) to improve the flip angle homogeneity and demonstrate their application to highly accelerated multi-band EPI (MB5 and GRAPPA2, as prescribed in the 7T HCP protocol) sequence, but also to acquire at 7T B 1 + -artefact-free T 1 - and T 2 -weighted anatomical scans used in the pre-processing pipeline of the HCP protocol. As compared to typical implementations of pTX, the proposed solution is fully operator-independent and allows "plug and play" exploitation of the benefits offered by multi-channel transmission. Validation in five healthy adults shows that the proposed technique achieves a flip angle homogeneity comparable to that of a clinical 3 T system. Compared to standard single-channel transmission, the use of UPs at 7T yielded up to a two-fold increase of the temporal signal-to-noise ratio in the temporal lobes as well as improved detection of functional connectivity in the brain regions most strongly affected by B 1 + inhomogeneity. [ABSTRACT FROM AUTHOR]

Abstract Does the human brain elicit patterns of activity associated with the meaning of words in the absence of conscious awareness? Do such non-conscious semantic representations generalize across languages? This study aimed to address these questions using fMRI-based multivariate pattern analysis (MVPA) in a masked word paradigm. Animal and non-animal words were visually presented in two different languages (i.e. Spanish and Basque). Words were presented very briefly and were masked. On each trial, participants identified the semantic category and provided a visibility rating of the word. A support vector machine (SVM) was used to decode word category from multivoxel patterns of BOLD responses in seven canonical semantic regions of a left-lateralized network that were prespecified based on a previous meta-analysis. We show that the semantic category of non-conscious words (i.e. associated with null visual experience and chance-level discrimination performance) can be significantly decoded from BOLD response patterns. For Spanish, such discriminative patterns of BOLD responses were consistently found in inferior parietal lobe, dorsomedial prefrontal cortex, inferior frontal gyrus and posterior cingulate gyrus. While for Basque, these were found in ventromedial temporal lobe and posterior cingulate gyrus. All of the areas identified have previously been associated with semantic processing in studies involving animals-tools and animals-artifacts contrasts. In conscious trials, such patterns were found to be distributed over all seven regions of the semantic network in both Spanish and Basque. However, we found no evidence of across-language generalization. These results demonstrate that even in the absence of conscious awareness and lack of behavioural sensitivity to the words, putative semantic brain areas carry information related to the meanings of the words. The generalization of semantic representations across languages, however, may require deeper conscious semantic access. Highlights • Masked words were visually presented in Spanish and Basque. • SVM classifiers were used to decode the semantic category from BOLD activity patterns. • The category of non-conscious words can be decoded in key substrates of the semantic network. • Across-language generalization of semantic representations may however require conscious access. [ABSTRACT FROM AUTHOR]

Abstract Human listeners can quickly and easily recognize different sound sources (objects and events) in their environment. Understanding how this impressive ability is accomplished can improve signal processing and machine intelligence applications along with assistive listening technologies. However, it is not clear how the brain represents the many sounds that humans can recognize (such as speech and music) at the level of individual sources, categories and acoustic features. To examine the cortical organization of these representations, we used patterns of fMRI responses to decode 1) four individual speakers and instruments from one another (separately, within each category), 2) the superordinate category labels associated with each stimulus (speech or instrument), and 3) a set of simple synthesized sounds that could be differentiated entirely on their acoustic features. Data were collected using an interleaved silent steady state sequence to increase the temporal signal-to-noise ratio, and mitigate issues with auditory stimulus presentation in fMRI. Largely separable clusters of voxels in the temporal lobes supported the decoding of individual speakers and instruments from other stimuli in the same category. Decoding the superordinate category of each sound was more accurate and involved a larger portion of the temporal lobes. However, these clusters all overlapped with areas that could decode simple, acoustically separable stimuli. Thus, individual sound sources from different sound categories are represented in separate regions of the temporal lobes that are situated within regions implicated in more general acoustic processes. These results bridge an important gap in our understanding of cortical representations of sounds and their acoustics. Highlights • We decoded auditory object, sound category and acoustic representations in fMRI. • Speakers and instruments were decoded (within category) in separable clusters in STL. • Speech and music sounds were decoded from each other in larger bilateral STL clusters. • These clusters fell within areas that represent acoustically separable tone patterns. • Category specific areas exist within more general acoustic processing regions. [ABSTRACT FROM AUTHOR]

Abstract The ability to make predictions is thought to facilitate language processing. During language comprehension such predictions appear to occur at multiple levels of linguistic representations (i.e. semantic, syntactic and lexical). The neural mechanisms that define the network sensitive to linguistic predictability have yet to be adequately defined. The purpose of the present study was to explore the neural network underlying predictability during the normal reading of connected text. Predictability values for different linguistic information were obtained from a pre-existing text corpus. Forty-one subjects underwent simultaneous eye-tracking and fMRI scans while reading these select paragraphs. Lexical, semantic, and syntactic predictability measures were then correlated with functional activation associated with fixation onset on the individual words. Activation patterns showed both positive and negative correlations to lexical, semantic, and syntactic predictabilities. Conjunction analysis revealed regions specific to or shared between each type of predictability. The regions associated with the different predictability measures were largely separate. Results suggest that most linguistic predictions are graded in nature, activating components of the existing language system. A number of regions were also found to be uniquely associated with full lexical predictability, most notably the anterior temporal lobe and the inferior posterior temporal cortex. Highlights • Lexical, semantic and syntactic prediction are central to language comprehension. • These predictabilities are associated with largely separate regions of the brain. • Linguistic prediction may be graded in nature according to predicted value. • Full lexical prediction appears to require ATL and IPTL. [ABSTRACT FROM AUTHOR]

Abstract Brain atrophy as measured from structural MR images, is one of the primary imaging biomarkers used to track neurodegenerative disease progression. In diseases such as frontotemporal dementia or Alzheimer's disease, atrophy can be observed in key brain structures years before any clinical symptoms are present. Atrophy is most commonly captured as volume change of key structures and the shape changes of these structures are typically not analysed despite being potentially more sensitive than summary volume statistics over the entire structure. In this paper we propose a spatiotemporal analysis pipeline based on Large Diffeomorphic Deformation Metric Mapping (LDDMM) to detect shape changes from volumetric MRI scans. We applied our framework to a cohort of individuals with genetic variants of frontotemporal dementia and healthy controls from the Genetic FTD Initiative (GENFI) study. Our method, take full advantage of the LDDMM framework, and relies on the creation of a population specific average spatiotemporal trajectory of a relevant brain structure of interest, the thalamus in our case. The residuals from each patient data to the average spatiotemporal trajectory are then clustered and studied to assess when presymptomatic mutation carriers differ from healthy control subjects. We found statistical differences in shape in the anterior region of the thalamus at least five years before the mutation carrier subjects develop any clinical symptoms. This region of the thalamus has been shown to be predominantly connected to the frontal lobe, consistent with the pattern of cortical atrophy seen in the disease. Graphical abstract Image 1 Highlights • Clustering shape parametrisation allows local shape analysis. • Thalamic shape changes appear 5 years before onset of fronto temporal dementia. • Shape changes seem to occur before volume changes. • Pre-symptomatic shape changes in thalamus are dorsofrontal, where connecting to temporal lobes. [ABSTRACT FROM AUTHOR]

• AD patients exhibit brain dysregulation in emotion, cognition and decision regions. • Alterations in regions like left ITG, STG, ORBsup, etc., may indicate anxious depression. • Predictive model differentiated anxious from non-anxious MDD with an AUC of 0.802. Anxious depression is a common subtype of major depressive disorder (MDD) associated with adverse outcomes and severely impaired social function. It is important to clarify the underlying neurobiology of anxious depression to refine the diagnosis and stratify patients for therapy. Here we explored associations between anxiety and brain structure/function in MDD patients. A total of 260 MDD patients and 127 healthy controls underwent three-dimensional T1-weighted structural scanning and resting-state functional magnetic resonance imaging. Demographic data were collected from all participants. Differences in gray matter volume (GMV), (fractional) amplitude of low-frequency fluctuation ((f)ALFF), regional homogeneity (ReHo), and seed point-based functional connectivity were compared between anxious MDD patients, non-anxious MDD patients, and healthy controls. A random forest model was used to predict anxiety in MDD patients using neuroimaging features. Anxious MDD patients showed significant differences in GMV in the left middle temporal gyrus and ReHo in the right superior parietal gyrus and the left precuneus than HCs. Compared with non-anxious MDD patients, patients with anxious MDD showed significantly different GMV in the left inferior temporal gyrus, left superior temporal gyrus, left superior frontal gyrus (orbital part), and left dorsolateral superior frontal gyrus; fALFF in the left middle temporal gyrus; ReHo in the inferior temporal gyrus and the superior frontal gyrus (orbital part); and functional connectivity between the left superior temporal gyrus(temporal pole) and left medial superior frontal gyrus. A diagnostic predictive random forest model built using imaging features and validated by 10-fold cross-validation distinguished anxious from non-anxious MDD with an AUC of 0.802. Patients with anxious depression exhibit dysregulation of brain regions associated with emotion regulation, cognition, and decision-making, and our diagnostic model paves the way for more accurate, objective clinical diagnosis of anxious depression. [ABSTRACT FROM AUTHOR]

• STEM teaching pedagogies are crucial for learning. • We examined brain synchronization based on fNIRS between teachers and students under three STEM teaching pedagogies, including traditional, storytelling, storyboarding. • Our results demonstrated that story-based teaching and storyboarding can improve STEM learning efficacy at the neural level. • Students' prior knowledge showed no different effects on learning process under three STEM teaching pedagogies. Early STEM education is crucial for later learning. This novel study utilised fNIRS to examine how STEM teaching methods (i.e., traditional, storytelling, storyboarding) affect neural activity synchronisation between teachers and students. Our results showed that left and right inferior frontal gyrus (IFG) for storytelling teaching versus traditional teaching, superior temporal gyrus for storyboard teaching versus traditional teaching, and left angular gyrus for storyboard and storytelling teaching were significant different in brain synchronisation. In the storytelling teaching condition, left supramarginal gyrus brain synchrony was found to improve STEM learning outcomes. In the storyboard teaching condition, IFG brain synchrony correlated positively with STEM learning improvement. The findings confirmed that story-based teaching and storyboarding can improve STEM learning efficacy at the neural level and unscored the significant role of neural synchronization as a predictor of learning outcomes. [ABSTRACT FROM AUTHOR]

• Within 100 and 150 ms, face-selective regions (LO-faces, IP-faces, FG-faces, pSTS-faces) begin to discriminate facial expressions. • As early as ∼100 ms, LO-faces and IP-faces represent categorical rather than image level information of facial expressions. • LO-faces and IP-faces have exhibit better performance in discriminating facial expressions when compared to FG-faces and pSTS-faces. The ability of humans to discern facial expressions in a timely manner typically relies on distributed face-selective regions for rapid neural computations. To study the time course in regions of interest for this process, we used magnetoencephalography (MEG) to measure neural responses participants viewed facial expressions depicting seven types of emotions (happiness, sadness, anger, disgust, fear, surprise, and neutral). Analysis of the time-resolved decoding of neural responses in face-selective sources within the inferior parietal cortex (IP-faces), lateral occipital cortex (LO-faces), fusiform gyrus (FG-faces), and posterior superior temporal sulcus (pSTS-faces) revealed that facial expressions were successfully classified starting from ∼100 to 150 ms after stimulus onset. Interestingly, the LO-faces and IP-faces showed greater accuracy than FG-faces and pSTS-faces. To examine the nature of the information processed in these face-selective regions, we entered with facial expression stimuli into a convolutional neural network (CNN) to perform similarity analyses against human neural responses. The results showed that neural responses in the LO-faces and IP-faces, starting ∼100 ms after the stimuli, were more strongly correlated with deep representations of emotional categories than with image level information from the input images. Additionally, we observed a relationship between the behavioral performance and the neural responses in the LO-faces and IP-faces, but not in the FG-faces and lpSTS-faces. Together, these results provided a comprehensive picture of the time course and nature of information involved in facial expression discrimination across multiple face-selective regions, which advances our understanding of how the human brain processes facial expressions. [ABSTRACT FROM AUTHOR]

Abstract The controlled semantic cognition framework proposes that the ventral anterior temporal lobes (vATL) in the left and right hemisphere function as an integrated hub region supporting transmodal semantic representations. The clinical evidence for the transmodal function of vATL is largely based on studies of semantic dementia patients with severe anomia, who also show impaired performance on nonverbal tasks that involve the retrieval of knowledge about objects and their prototypical use, such as the production of tool use pantomimes. Yet, evidence from patients with apraxia and functional neuroimaging studies in healthy adults does not implicate vATL in pantomime production. We, therefore, compared semantic retrieval of object-action associations for overt verb and pantomime production from picture and word stimuli. Our results show that, independent of stimulus modality, the retrieval of object-action associations for verb, but not pantomime, production is related to activity in bilateral vATL. Bilateral vATL activation was also observed for meaningless verbal responses that did not require the retrieval of object-action associations. Taken together, our results suggest that bilateral vATL is not engaged in the retrieval of object-action associations per se, but rather supports semantic representations that are functionally specialized for language. These findings have implications for the semantic cognition framework and our understanding of the dependence of conceptual knowledge on language. Highlights • Investigates engagement of transmodal semantic hub for nonverbal behaviour. • Compares behaviour and brain activation underlying verb and pantomime production. • Semantic control network activated for verb and pantomime production. • Semantic hub only engaged during verb but not pantomime production. • Results suggests that semantic hub is specialized for language. [ABSTRACT FROM AUTHOR]

Abstract To understand the spatial organization as well as long- and short-range connections of the human brain at microscopic resolution, 3D reconstruction of histological sections is important. We approach this challenge by reconstructing series of unstained histological sections of multi-scale (1.3 μ m and 64 μ m) and multi-modal 3D polarized light imaging (3D-PLI) data. Since spatial coherence is lost during the sectioning procedure, image registration is the major step in 3D reconstruction. We propose a non-rigid registration method which comprises of a novel multi-modal similarity metric and an improved regularization scheme to cope with deformations inevitably introduced during the sectioning procedure, as well as a rigid registration approach using a robust similarity metric for improved initial alignment. We also introduce a multi-scale feature-based localization and registration approach for mapping of 1.3 μ m sections to 64 μ m sections and a scale-adaptive method that can handle challenging sections with large semi-global deformations due to tissue splits. We have applied our registration method to 126 consecutive sections of the temporal lobe of the human brain with 64 μ m and 1.3 μ m resolution. Each step of the registration method was quantitatively evaluated using 10 different sections and manually determined ground truth, and a quantitative comparison with previous methods was performed. Visual assessment of the reconstructed volumes and comparison with reference volumes confirmed the high quality of the registration result. Highlights • Robust and accurate non-rigid registration based on a physical deformation model. • 3D reconstruction of high-resolution and ultra-high resolution 3D-PLI data. • Novel similarity metric using the canonical form of correlation transform and different regularizers. • Scale-adaptive non-rigid registration to cope with large semi-global deformations. • Feature-based localization and registration of ultra-high resolution 3D-PLI data. [ABSTRACT FROM AUTHOR]

Studies of autobiographical memory retrieval often use photographs to probe participants' memories for past events. Recent neuroimaging work has shown that viewing photographs depicting events from one's own life evokes a characteristic pattern of brain activity across a network of frontal, parietal, and medial temporal lobe regions that can be readily distinguished from brain activity associated with viewing photographs from someone else's life (Rissman, Chow, Reggente, and Wagner, 2016). However, it is unclear whether the neural signatures associated with remembering a personally experienced event are distinct from those associated with recognizing previously encountered photographs of an event. The present experiment used a novel functional magnetic resonance imaging (fMRI) paradigm to investigate putative differences in brain activity patterns associated with these distinct expressions of memory retrieval. Eighteen participants wore necklace-mounted digital cameras to capture events from their everyday lives over the course of three weeks. One week later, participants underwent fMRI scanning, where on each trial they viewed a sequence of photographs depicting either an event from their own life or from another participant's life and judged their memory for this event. Importantly, half of the trials featured photographic sequences that had been shown to participants during a laboratory session administered the previous day. Multi-voxel pattern analyses assessed the sensitivity of two brain networks of interest—as identified by a meta-analysis of prior autobiographical and laboratory-based memory retrieval studies—to the original source of the photographs (own life or other's life) and their experiential history as stimuli (previewed or non-previewed). The classification analyses revealed a striking dissociation: activity patterns within the autobiographical memory network were significantly more diagnostic than those within the laboratory-based network as to whether photographs depicted one's own personal experience (regardless of whether they had been previously seen), whereas activity patterns within the laboratory-based memory network were significantly more diagnostic than those within the autobiographical memory network as to whether photographs had been previewed (regardless of whether they were from the participant's own life). These results, also apparent in whole-brain searchlight classifications, provide evidence for dissociable patterns of activation across two putative memory networks as a function of whether real-world photographs trigger the retrieval of firsthand experiences or secondhand event knowledge. [ABSTRACT FROM AUTHOR]

In this study, we investigated the time course and neural correlates of the retrieval process underlying visual working memory. We made use of a rare dataset in which the same task was recorded using both scalp electroencephalography (EEG) and Electrocorticography (ECoG), respectively. This allowed us to examine with great spatial and temporal detail how the retrieval process works, and in particular how the medial temporal lobe (MTL) is involved. In each trial, participants judged whether a probe face had been among a set of recently studied faces. With a method that combines hidden semi-Markov models and multivariate pattern analysis, the neural signal was decomposed into a sequence of latent cognitive stages with information about their durations on a trial-by-trial basis. Analyzed separately, EEG and ECoG data yielded converging results on discovered stages and their interpretation, which reflected 1) a brief pre-attention stage, 2) encoding the stimulus, 3) retrieving the studied set, and 4) making a decision. Combining these stages with the high spatial resolution of ECoG suggested that activity in the temporal cortex reflected item familiarity in the retrieval stage; and that once retrieval is complete, there is active maintenance of the studied face set in the decision stage in the MTL. During this same period, the frontal cortex guides the decision by means of theta coupling with the MTL. These observations generalize previous findings on the role of MTL theta from long-term memory tasks to short-term memory tasks. [ABSTRACT FROM AUTHOR]