Search

Resting-state functional connectivity (rsFC) is an emerging means of understanding the neurobiology of combat-related post-traumatic stress disorder (PTSD). However, most rsFC studies to date have limited focus to cognitively related intrinsic connectivity networks (ICNs), have not applied data-driven methodologies or have disregarded the effect of combat exposure. In this study, we predicted that group independent component analysis (GICA) would reveal group-wise differences in rsFC across 50 active duty service members with PTSD, 28 combat-exposed controls (CEC), and 25 civilian controls without trauma exposure (CC). Intranetwork connectivity differences were identified across 11 ICNs, yet combat-exposed groups were indistinguishable in PTSD vs CEC contrasts. Both PTSD and CEC demonstrated anatomically diffuse differences in the Auditory Vigilance and Sensorimotor networks compared to CC. However, intranetwork connectivity in a subset of three regions was associated with PTSD symptom severity among executive (left insula; ventral anterior cingulate) and right Fronto-Parietal (perigenual cingulate) networks. Furthermore, we found that increased temporal synchronization among visuospatial and sensorimotor networks was associated with worse avoidance symptoms in PTSD. Longitudinal neuroimaging studies in combat-exposed cohorts can further parse PTSD-related, combat stress-related or adaptive rsFC changes ensuing from combat.

Why is psychiatry unable to define clinically useful biomarkers? We explore this question from the vantage of data and decision science and consider biomarkers as a form of phenotypic data that resolves a well-defined clinical decision. We introduce a framework that systematizes different forms of phenotypic data and further introduce the concept of decision model to describe the strategies a clinician uses to seek out, combine, and act on clinical data. Though many medical specialties rely on quantitative clinical data and operationalized decision models, we observe that, in psychiatry, clinical data are gathered and used in idiosyncratic decision models that exist solely in the clinician's mind and therefore are outside empirical evaluation. This, we argue, is a fundamental reason why psychiatry is unable to define clinically useful biomarkers: because psychiatry does not currently quantify clinical data, decision models cannot be operationalized and, in the absence of an operationalized decision model, it is impossible to define how a biomarker might be of use. Here, psychiatry might benefit from digital technologies that have recently emerged specifically to quantify clinically relevant facets of human behavior. We propose that digital tools might help psychiatry in two ways: first, by quantifying data already present in the standard clinical interaction and by allowing decision models to be operationalized and evaluated; second, by testing whether new forms of data might have value within an operationalized decision model. We reference successes from other medical specialties to illustrate how quantitative data and operationalized decision models improve patient care.

Magnetic resonance imaging (MRI) studies of panic disorder (PD) have discovered various damaged brain regions, with heterogeneous results across studies. The present study used meta-analytic approaches to discover gray matter (GM) changes consistently detected in PD and to characterize the functional and connectivity profiles of these regions. In the present study we first conducted an activation likelihood estimation (ALE) meta-analysis of eight eligible whole-brain VBM studies. Then, meta-analytic connectivity modeling analyses (MACMs) were used to provide co-atrophy and co-activation profiles across all the experiments stored in BrainMap. Lastly, the co-atrophied and co-activated regions were analyzed using functional decoding to reveal their functions. Lower gray matter volume was found in the bilateral dorsomedial prefrontal cortex (DMPFC), left dorsolateral prefrontal cortex (DLPFC), right insula, right superior temporal gyrus (STG), right middle temporal gyrus (MTG) and right superior orbital frontal cortex (OFC). Significant co-atrophies were found in the STG, DMPFC and OFC and co-activations were found between the left DLPFC and bilateral DMPFC. Decreased gray matter volume in STG, OFC, DLPFC and DMPFC and their co-atrophy and co-activation patterns indicate the damaged higher cognitive functions in PD and suggest that cortical regions are important structural imaging biomarkers in PD.

Contains fulltext : 187792.pdf (Publisher’s version ) (Closed access) Despite the common conception of the dorsal premotor cortex (PMd) as a single brain region, its diverse connectivity profiles and behavioral heterogeneity argue for a differentiated organization of the PMd. A previous study revealed that the right PMd is characterized by a rostro-caudal and a ventro-dorsal distinction dividing it into five subregions: rostral, central, caudal, ventral and dorsal. The present study assessed whether a similar organization is present in the left hemisphere, by capitalizing on a multimodal data-driven approach combining connectivity-based parcellation (CBP) based on meta-analytic modeling, resting-state functional connectivity, and probabilistic diffusion tractography. The resulting PMd modules were then characterized based on multimodal functional connectivity and a quantitative analysis of associated behavioral functions. Analyzing the clusters consistent across all modalities revealed an organization of the left PMd that mirrored its right counterpart to a large degree. Again, caudal, central and rostral modules reflected a cognitive-motor gradient and a premotor eye-field was found in the ventral part of the left PMd. In addition, a distinct module linked to abstract cognitive functions was observed in the rostro-ventral left PMd across all CBP modalities, implying greater differentiation of higher cognitive functions for the left than the right PMd. 12 p.

Schizophrenia is a devastating brain disorder that disturbs sensory perception, motor action, and abstract thought. Its clinical phenotype implies dysfunction of various mental domains, which has motivated a series of theories regarding the underlying pathophysiology. Aiming at a predictive benchmark of a catalogue of cognitive functions, we developed a bottom-up machine-learning strategy and provide a proof of principle in a multi-site clinical dataset (n=324). Existing neuroscientific knowledge on diverse cognitive domains was first condensed into neuro-topographical maps. We then examined how the ensuing meta-analytic cognitive priors can distinguish patients and controls using brain morphology and intrinsic functional connectivity. Some affected cognitive domains supported well-studied directions of research on auditory evaluation and social cognition. However, rarely suspected cognitive domains also emerged as disease-relevant, including self-oriented processing of bodily sensations in gustation and pain. Such algorithmic charting of the cognitive landscape can be used to make targeted recommendations for future mental health research.

Background Better understanding of the neurobiology of posttraumatic stress disorder (PTSD) may be critical to developing novel, effective therapeutics. Here, we conducted a data-driven investigation using a well-established, graph-based topological measure of nodal strength to determine the extent of functional dysconnectivity in a cohort of active duty U.S. Army soldiers with PTSD compared to controls. Methods A total of 102 participants with (n = 50) or without PTSD (n = 52) completed functional magnetic resonance imaging at rest and during symptom provocation using subject-specific script imagery. Vertex/voxel global brain connectivity with global signal regression (GBCr), a measure of nodal strength, was calculated as the average of its functional connectivity with all other vertices/voxels in the brain gray matter. Results In contrast to resting state, where there were no group differences, we found a significantly higher GBCr during symptom provocation, in PTSD participants compared to controls, in areas within the right hemisphere, including anterior insula, caudal-ventrolateral prefrontal, and rostral-ventrolateral parietal cortices. Overall, these clusters overlapped with the ventral and dorsal salience networks. Post hoc analysis showed increased GBCr in these salience clusters during symptom provocation compared to resting state. In addition, resting-state GBCr in the salience clusters predicted GBCr during symptom provocation in PTSD participants but not in controls. Conclusion In PTSD, increased connectivity within the salience network has been previously hypothesized, based primarily on seed-based connectivity findings. The current results strongly support this hypothesis using whole-brain network measure in a fully data-driven approach. It remains to be seen in future studies whether these identified salience disturbances would normalize following treatment.

Background In soldiers with posttraumatic stress disorder, symptom provocation was found to induce increased connectivity within the salience network, as measured by functional magnetic resonance imaging and global brain connectivity with global signal regression (GBCr). However, it is unknown whether these GBCr disturbances would normalize following effective posttraumatic stress disorder treatment. Methods Sixty-nine US Army soldiers with (n = 42) and without posttraumatic stress disorder (n = 27) completed functional magnetic resonance imaging at rest and during symptom provocation using subject-specific script imagery. Then, participants with posttraumatic stress disorder received six weeks (12 sessions) of group cognitive processing therapy or present-centered therapy. At week 8, all participants repeated the functional magnetic resonance imaging scans. The primary analysis used a region-of-interest approach to determine the effect of treatment on salience GBCr. A secondary analysis was conducted to explore the pattern of GBCr alterations posttreatment in posttraumatic stress disorder participants compared to controls. Results Over the treatment period, present-centered therapy significantly reduced salience GBCr ( p = .02). Compared to controls, salience GBCr was high pretreatment (present-centered therapy, p = .01; cognitive processing therapy, p = .03) and normalized post-present-centered therapy ( p = .53) but not postcognitive processing therapy ( p = .006). Whole-brain secondary analysis found high GBCr within the central executive network in posttraumatic stress disorder participants compared to controls. Post hoc exploratory analyses showed significant increases in executive GBCr following cognitive processing therapy treatment ( p = .01). Conclusion The results support previous models relating cognitive processing therapy to central executive network and enhanced cognitive control while unraveling a previously unknown neurobiological mechanism of present-centered therapy treatment, demonstrating treatment-specific reduction in salience connectivity during trauma recollection.

The human left inferior parietal lobule (LIPL) plays a pivotal role in many cognitive functions and is an important node in the default mode network (DMN). Although many previous studies have proposed different parcellation schemes for the LIPL, the detailed functional organization of the LIPL and the exact correspondence between the DMN and LIPL subregions remain unclear. Mounting evidence indicates that spontaneous fluctuations in the brain are strongly associated with cognitive performance at the behavioral level. However, whether a consistent functional topographic organization of the LIPL during rest and under task can be revealed remains unknown. Here, they used resting-state functional connectivity (RSFC) and task-related coactivation patterns separately to parcellate the LIPL and identified seven subregions. Four subregions were located in the supramarginal gyrus (SMG) and three subregions were located in the angular gyrus (AG). The subregion-specific networks and functional characterization revealed that the four anterior subregions were found to be primarily involved in sensorimotor processing, movement imagination and inhibitory control, audition perception and speech processing, and social cognition, whereas the three posterior subregions were mainly involved in episodic memory, semantic processing, and spatial cognition. The results revealed a detailed functional organization of the LIPL and suggested that the LIPL is a functionally heterogeneous area. In addition, the present study demonstrated that the functional architecture of the LIPL during rest corresponds with that found in task processing.

Background Task-based functional magnetic resonance imaging (fMRI) studies of adult attention-deficit/hyperactivity disorder (ADHD) have revealed various ADHD-related dysfunctional brain regions, with heterogeneous findings across studies. Here, we used novel meta-analytic data-driven approaches to characterize the function and connectivity profile of ADHD-related dysfunctional regions consistently detected across studies. Methods We first conducted an activation likelihood estimation meta-analysis of 24 task-based fMRI studies in adults with ADHD. Each ADHD-related dysfunctional region resulting from the activation likelihood estimation meta-analysis was then analyzed using functional decoding based on ~7500 fMRI experiments in the BrainMap database. This approach allows mapping brain regions to functions not necessarily tested in individual studies, thus suggesting possible novel functions for those regions. Additionally, ADHD-related dysfunctional regions were clustered based on their functional coactivation profiles across all the experiments stored in BrainMap (meta-analytic connectivity modeling). Results ADHD-related hypoactivation was found in the left putamen, left inferior frontal gyrus (pars opercularis), left temporal pole, and right caudate. Functional decoding mapped the left putamen to cognitive aspects of music perception/reproduction and the left temporal lobe to language semantics; both these regions clustered together on the basis of their meta-analytic functional connectivity. Left inferior gyrus mapped to executive function tasks; right caudate mapped to both executive function tasks and music-related processes. Conclusions Our study provides meta-analytic support to the hypothesis that, in addition to well-known deficits in typical executive functions, impairment in processes related to music perception/reproduction and language semantics may be involved in the pathophysiology of adult ADHD.

The nature of the relationship between structure and function is a fundamental question in neuroscience, especially at the macroscopic neuroimaging level. Although mounting studies have revealed that functional connectivity reflects structural connectivity, whether similar structural and functional connectivity patterns can reveal corresponding similarities in the structural and functional topography remains an open problem. In our current study, we used the right inferior parietal lobule (RIPL), which has been demonstrated to have similar anatomical and functional connectivity patterns at the subregional level, to directly test the hypothesis that similar structural and functional connectivity patterns can inform the corresponding topography of this area. In addition, since the association between the RIPL regions and particular functions and networks is still largely unknown, post-hoc functional characterizations and connectivity analyses were performed to identify the main functions and cortical networks in which each subregion participated. Anatomical and functional connectivity-based parcellations of the RIPL have consistently identified five subregions. Our functional characterization using meta-analysis-based behavioral and connectivity analyses revealed that the two anterior subregions (Cl1 and Cl2) primarily participate in interoception and execution, respectively; whereas the posterior subregion (Cl3) in the SMG primarily participates in attention and action inhibition. The two posterior subregions (Cl4, Cl5) in the AG were primarily involved in social cognition and spatial cognition, respectively. These results indicated that similar anatomical and functional connectivity patterns of the RIPL are reflected in corresponding structural and functional topographies. The identified cortical connectivity and functional characterization of each subregion may facilitate RIPL-related clinical research. Hum Brain Mapp 37:4316-4332, 2016. © 2016 Wiley Periodicals, Inc.

Contains fulltext : 168978.pdf (Publisher’s version ) (Closed access) Human neuroimaging methods have provided a number of means by which the connectivity structure of the human brain can be inferred. For instance, correlations in blood-oxygen-level-dependent (BOLD) signal time series are commonly used to make inferences about "functional connectivity". Correlations across samples in structural morphometric measures, such as voxel-based morphometry (VBM) or cortical thickness (CT), have also been used to estimate connectivity, putatively through mutually trophic effects on connected brain areas. In this study, we have compared seed-based connectivity estimates obtained from four common correlational approaches: resting-state functional connectivity (RS-fMRI), meta-analytic connectivity modeling (MACM), VBM correlations, and CT correlations. We found that the two functional approaches (RS-fMRI and MACM) had the best agreement. While the two structural approaches (CT and VBM) had better-than-random convergence, they were no more similar to each other than to the functional approaches. The degree of correspondence between modalities varied considerably across seed regions, and also depended on the threshold applied to the connectivity distribution. These results demonstrate some degrees of similarity between connectivity inferred from structural and functional covariances, particularly for the most robust functionally connected regions (e.g., the default mode network). However, they also caution that these measures likely capture very different aspects of brain structure and function. 21 p.

Within the object recognition-related ventral visual stream, the human fusiform gyrus (FG), which topographically connects the striate cortex to the inferior temporal lobe, plays a pivotal role in high-level visual/cognitive functions. However, though there are many previous investigations of distinct functional modules within the FG, the functional organization of the whole FG in its full functional heterogeneity has not yet been established. In the current study, a replicable functional organization of the FG based on distinct anatomical connectivity patterns was identified. The FG was parcellated into medial (FGm), lateral (FGl), and anterior (FGa) regions using diffusion tensor imaging. We validated the reasonability of such an organizational scheme from the perspective of resting-state whole brain functional connectivity patterns and the involvement of functional subnetworks. We found corroborating support for these three distinct modules, and suggest that the FGm serves as a transition region that combines multiple stimuli, the FGl is responsible for categorical recognition, and the FGa is involved in semantic understanding. These findings support two organizational functional transitions of the ventral temporal gyrus, a posterior/anterior direction of visual/semantic processing, and a media/lateral direction of high-level visual processing. Our results may facilitate a more detailed study of the human FG in the future. Hum Brain Mapp 37:3003-3016, 2016. © 2016 Wiley Periodicals, Inc.

Background Repetitive transcranial magnetic stimulation (rTMS) has the potential to treat brain disorders by modulating the activity of disease-specific brain networks, yet the rTMS frequencies used are delivered in a binary fashion – excitatory (>1 Hz) and inhibitory (≤1 Hz). Objective To assess the effective connectivity of the motor network at different rTMS stimulation rates during positron-emission tomography (PET) and confirm that not all excitatory rTMS frequencies act on the motor network in the same manner. Methods We delivered image-guided, supra-threshold rTMS at 3 Hz, 5 Hz, 10 Hz, 15 Hz and rest (in separate randomized sessions) to the primary motor cortex (M1) of the lightly anesthetized baboon during PET imaging. Each rTMS/PET session was analyzed using normalized cerebral blood flow (CBF) measurements. Path analysis – using structural equation modeling (SEM) – was employed to determine the effective connectivity of the motor network at all rTMS frequencies. Once determined, the final model of the motor network was used to assess any differences in effective connectivity at each rTMS frequency. Results The exploratory SEM produced a very well fitting final network model ( χ 2 = 18.04, df = 21, RMSEA = 0.000, p = 0.647, TLI = 1.12) using seven nodes of the motor network. 5 Hz rTMS produced the strongest path coefficients in four of the seven connections, suggesting that this frequency is the optimal rTMS frequency for stimulation the motor network (as a whole); however, the premotor cerebellum connection was optimally stimulated at 10 Hz rTMS and the supplementary motor area caudate connection was optimally driven at 15 Hz rTMS. Conclusion(s) We have demonstrated that 1) 5 Hz rTMS revealed the strongest path coefficients (i.e. causal influence) on the nodes of the motor network, 2) stimulation at "excitatory" rTMS frequencies did not produce increased CBF in all nodes of the motor network, 3) specific rTMS frequencies may be used to target specific none-to-node interactions in the stimulated brain network, and 4) more research needs to be performed to determine the optimum frequency for each brain circuit and/or node.

Major depressive disorder (MDD) involves impairment in cognitive and interpersonal functioning. The right temporoparietal junction (RTPJ) is a key brain region subserving cognitive-attentional and social processes. Yet, findings on the involvement of the RTPJ in the pathophysiology of MDD have so far been controversial. Recent connectivity-based parcellation data revealed a topofunctional dualism within the RTPJ, linking its anterior and posterior part (aRTPJ/pRTPJ) to antagonistic brain networks for attentional and social processing, respectively. Comparing functional resting-state connectivity of the aRTPJ and pRTPJ in 72 MDD patients and 76 well-matched healthy controls, we found a seed (aRTPJ/pRTPJ) × diagnosis (MDD/controls) interaction in functional connectivity for eight regions. Employing meta-data from a large-scale neuroimaging database, functional characterization of these regions exhibiting differentially altered connectivity with the aRTPJ/pRTPJ revealed associations with cognitive (dorsolateral prefrontal cortex, parahippocampus) and behavioral (posterior medial frontal cortex) control, visuospatial processing (dorsal visual cortex), reward (subgenual anterior cingulate cortex, medial orbitofrontal cortex, posterior cingulate cortex), as well as memory retrieval and social cognition (precuneus). These findings suggest that an imbalance in connectivity of subregions, rather than disturbed connectivity of the RTPJ as a whole, characterizes the connectional disruption of the RTPJ in MDD. This imbalance may account for key symptoms of MDD in cognitive, emotional, and social domains. Hum Brain Mapp 37:2931-2942, 2016. © 2016 Wiley Periodicals, Inc.

Psychopathy is a disorder of high public concern because it predicts violence and offense recidivism. Recent brain imaging studies suggest abnormal brain activity underlying psychopathic behavior. No reliable pattern of altered neural activity has been disclosed so far. This study sought to identify consistent changes of brain activity in psychopaths and to investigate whether these could explain known psychopathology. First, we used activation likelihood estimation (p < 0.05, corrected) to meta-analyze brain activation changes associated with psychopathy across 28 functional magnetic resonance imaging studies reporting 753 foci from 155 experiments. Second, we characterized the ensuing regions functionally by employing meta-data of a large-scale neuroimaging database (p < 0.05, corrected). Psychopathy was consistently associated with decreased brain activity in the right laterobasal amygdala, the dorsomedial prefrontal cortex, and bilaterally in the lateral prefrontal cortex. A robust increase of activity was observed in the fronto-insular cortex on both hemispheres. Data-driven functional characterization revealed associations with semantic language processing (left lateral prefrontal and fronto-insular cortex), action execution and pain processing (right lateral prefrontal and left fronto-insular), social cognition (dorsomedial prefrontal cortex), and emotional as well as cognitive reward processing (right amygdala and fronto-insular cortex). Aberrant brain activity related to psychopathy is located in prefrontal, insular, and limbic regions. Physiological mental functions fulfilled by these brain regions correspond to disturbed behavioral patterns pathognomonic for psychopathy. Hence, aberrant brain activity may not just be an epiphenomenon of psychopathy but directly related to the psychopathology of this disorder.

BACKGROUND: Better understanding of the neurobiology of posttraumatic stress disorder (PTSD) may be critical to developing novel, effective therapeutics. Here, we conducted a data-driven investigation using a well-established, graph- based topological measure of nodal strength to determine the extent of functional dysconnectivity in a cohort of active duty US Army soldiers with PTSD compared to controls. METHODS: 102 participants with (n=50) or without PTSD (n=52) completed functional magnetic resonance imaging (fMRI) at rest and during symptom provocation using subject-specific script imagery. Vertex/voxel global brain connectivity with global signal regression (GBCr), a measure of nodal strength, was calculated as the average of its functional connectivity with all other vertices/voxels in the brain gray matter. RESULTS: In contrast to during resting-state, where there were no group differences, we found a significantly higher GBCr, in PTSD participants compared to controls, in areas within the right hemisphere, including anterior insula, caudal- ventrolateral prefrontal, and rostral-ventrolateral parietal cortices. Overall, these clusters overlapped with the ventral and dorsal salience networks. Post hoc analysis showed increased GBCr in these salience clusters during symptom provocation compared to resting-state. In addition, resting-state GBCr in the salience clusters predicted GBCr during symptom provocation in PTSD participants but not in controls. CONCLUSION: In PTSD, increased connectivity within the salience network has been previously hypothesized, based primarily on seed-based connectivity findings. The current results strongly support this hypothesis using whole-brain network measure in a fully data-driven approach. It remains to be seen in future studies whether these identified salience disturbances would normalize following treatment.

Parcellation of the human brain into fine-grained units by grouping voxels into distinct clusters has been an effective approach for delineating specific brain regions and their subregions. Published neuroimaging studies employing coordinate-based meta-analyses have shown that the activation foci and their corresponding behavioral categories may contain useful information about the anatomical-functional organization of brain regions. Inspired by these developments, we proposed a new parcellation scheme called meta-analytic activation modeling-based parcellation (MAMP) that uses meta-analytically obtained information. The raw meta data, including the experiments and the reported activation coordinates related to a brain region of interest, were acquired from the Brainmap database. Using this data, we first obtained the "modeled activation" pattern by modeling the voxel-wise activation probability given spatial uncertainty for each experiment that featured at least one focus within the region of interest. Then, we processed these "modeled activation" patterns across the experiments with a K-means clustering algorithm to group the voxels into different subregions. In order to verify the reliability of the method, we employed our method to parcellate the amygdala and the left Brodmann area 44 (BA44). The parcellation results were quite consistent with previous cytoarchitectonic and in vivo neuroimaging findings. Therefore, the MAMP proposed in the current study could be a useful complement to other methods for uncovering the functional organization of the human brain.

Historically, the human frontal pole (FP) has been considered as a single architectonic area. Brodmann's area 10 is located in the frontal lobe with known contributions in the execution of various higher order cognitive processes. However, recent cytoarchitectural studies of the FP in humans have shown that this portion of cortex contains two distinct cytoarchitectonic regions. Since architectonic differences are accompanied by differential connectivity and functions, the frontal pole qualifies as a candidate region for exploratory parcellation into functionally discrete sub-regions. We investigated whether this functional heterogeneity is reflected in distinct segregations within cytoarchitectonically defined FP-areas using meta-analytic co-activation based parcellation (CBP). The CBP method examined the co-activation patterns of all voxels within the FP as reported in functional neuroimaging studies archived in the BrainMap database. Voxels within the FP were subsequently clustered into sub-regions based on the similarity of their respective meta-analytically derived co-activation maps. Performing this CBP analysis on the FP via k-means clustering produced a distinct 3-cluster parcellation for each hemisphere corresponding to previously identified cytoarchitectural differences. Post-hoc functional characterization of clusters via BrainMap metadata revealed that lateral regions of the FP mapped to memory and emotion domains, while the dorso- and ventromedial clusters were associated broadly with emotion and social cognition processes. Furthermore, the dorsomedial regions contain an emphasis on theory of mind and affective related paradigms whereas ventromedial regions couple with reward tasks. Results from this study support previous segregations of the FP and provide meta-analytic contributions to the ongoing discussion of elucidating functional architecture within human FP.

Previous work has shown that the hippocampus is smaller in the brains of individuals suffering from major depressive disorder (MDD) than those of healthy controls. Moreover, right hippocampal volume specifically has been found to predict the probability of subsequent depressive episodes. This study explored the utility of right hippocampal volume as an endophenotype of recurrent MDD (rMDD). We observed a significant genetic correlation between the two traits in a large sample of Mexican American individuals from extended pedigrees (ρg = -0.34, p = 0.013). A bivariate linkage scan revealed a significant pleiotropic quantitative trait locus on chromosome 18p11.31-32 (LOD = 3.61). Bivariate association analysis conducted under the linkage peak revealed a variant (rs574972) within an intron of the gene SMCHD1 meeting the corrected significance level (χ(2) = 19.0, p = 7.4 × 10(-5)). Univariate association analyses of each phenotype separately revealed that the same variant was significant for right hippocampal volume alone, and also revealed a suggestively significant variant (rs12455524) within the gene DLGAP1 for rMDD alone. The results implicate right-hemisphere hippocampal volume as a possible endophenotype of rMDD, and in so doing highlight a potential gene of interest for rMDD risk.

Post-traumatic stress disorder (PTSD) is presumably the result of life threats and conditioned fear. However, the neurobiology of fear fails to explain the impact of traumas that do not entail threats. Neuronal function, assessed as glucose metabolism with (18)fluoro-deoxyglucose positron emission tomography, was contrasted in active duty, treatment-seeking US Army Soldiers with PTSD endorsing either danger- (n = 19) or non-danger-based (n = 26) traumas, and was compared with soldiers without PTSD (Combat Controls, n = 26) and Civilian Controls (n = 24). Prior meta-analyses of regions associated with fear or trauma script imagery in PTSD were used to compare glucose metabolism across groups. Danger-based traumas were associated with higher metabolism in the right amygdala than the control groups, while non-danger-based traumas associated with heightened precuneus metabolism relative to the danger group. In the danger group, PTSD severity was associated with higher metabolism in precuneus and dorsal anterior cingulate and lower metabolism in left amygdala (R(2 )= 0.61). In the non-danger group, PTSD symptom severity was associated with higher precuneus metabolism and lower right amygdala metabolism (R(2 )= 0.64). These findings suggest a biological basis to consider subtyping PTSD according to the nature of the traumatic context.

Much of what we assume about the functional topography of the hippocampus was derived from a single case study over half a century ago. Given advances in the imaging sciences, a new era of discovery is underway, with potential to transform our understanding of healthy processing as well as our ability to treat disorders. We employed coactivation based parcellation, a meta-analytic approach, and ultra-high field, high-resolution functional and structural neuroimaging to characterize the neurofunctional topography of the hippocampus. Data revealed strong support for an evolutionarily preserved topography along the long-axis. Specifically, the left hippocampus was segmented into three distinct clusters: an emotional processing cluster supported by structural and functional connectivity to the amygdala and parahippocampal gyrus, a cognitive operations cluster, with functional connectivity to the anterior cingulate and inferior frontal gyrus, and a posterior perceptual cluster with distinct structural connectivity patterns to the occipital lobe coupled with functional connectivity to the precuneus and angular gyrus. The right hippocampal segmentation was more ambiguous, with plausible 2- and 5-cluster solutions plausible. Segmentations shared connectivity with brain regions known to support the correlated processes. This represents the first neurofunctional topographic model of the hippocampus using a robust, bias-free, multi-modal approach.

The inferior frontal junction (IFJ) area, a small region in the posterior lateral prefrontal cortex (LPFC), has received increasing interest in recent years due to its central involvement in the control of action, attention, and memory. Yet, both its function and anatomy remain controversial. Here, we employed a meta-analytic parcellation of the left LPFC to show that the IFJ can be isolated based on its specific functional connections. A seed region, oriented along the left inferior frontal sulcus (IFS), was subdivided via cluster analyses of voxel-wise whole-brain co-activation patterns. The ensuing clusters were characterized by their unique connections, the functional profiles of associated experiments, and an independent topic mapping approach. A cluster at the posterior end of the IFS matched previous descriptions of the IFJ in location and extent and could be distinguished from a more caudal cluster involved in motor control, a more ventral cluster involved in linguistic processing, and 3 more rostral clusters involved in other aspects of cognitive control. Overall, our findings highlight that the IFJ constitutes a core functional unit within the frontal lobe and delineate its borders. Implications for the IFJ’s role in human cognition and the organizational principles of the frontal lobe are discussed.

Adolescence is a period of developmental flux when brain systems are vulnerable to influences of early substance use, which in turn relays increased risk for substance use disorders. Our study intent was to assess adolescent regional cerebral blood flow (rCBF) as it relates to current and future alcohol use. The aim was to identify brain-based predictors for initiation of alcohol use and onset of future substance use disorders.Quantitative rCBF was assessed in 100 adolescents (age 12-15). Prospective behavioral assessments were conducted annually over a three-year follow-up period to characterize onset of alcohol initiation, future drinking patterns and use disorders. Comparisons amongst use groups (i.e., current-, future-, and non-alcohol using adolescents) identified rCBF associated with initiation of alcohol use. Regression by future drinking patterns identified rCBF predictive of heavier drinking. Survival analysis determined whether or not baseline rCBF predicted later development of use disorders.Baseline rCBF was decreased to the parietal cortex and increased to mesolimbic regions in adolescents currently using alcohol as well as those who would use alcohol in the future. Higher baseline rCBF to the left fusiform gyrus and lower rCBF to the right inferior parietal cortex and left cerebellum was associated with future drinking patterns as well as predicted the onset of alcohol and substance use disorders in this cohort.Variations in resting rCBF to regions within reward and default mode or control networks appear to represent trait markers of alcohol use initiation and are predictive of future development of use disorders.

Persistent developmental stuttering is a neurological disorder that commonly manifests as a motor problem. Cognitive theories, however, hold that poorly developed cognitive skills are the origins of stuttering. Working memory (WM), a multicomponent cognitive system that mediates information maintenance and manipulation, is known to play an important role in speech production, leading us to postulate that the neurophysiological mechanisms underlying stuttering may be associated with a WM deficit. Using functional magnetic resonance imaging, we aimed to elucidate brain mechanisms in a phonological WM task in adults who stutter and controls. A right-lateralized compensatory mechanism for a deficit in the rehearsal process and neural disconnections associated with the central executive dysfunction were found. Furthermore, the neural abnormalities underlying the phonological WM were independent of memory load. This study demonstrates for the first time the atypical neural responses to phonological WM in PWS, shedding new light on the underlying cause of stuttering.

Meta-analytic techniques for mining the neuroimaging literature continue to exert an impact on our conceptualization of functional brain networks contributing to human emotion and cognition. Traditional theories regarding the neurobiological substrates contributing to affective processing are shifting from regional- towards more network-based heuristic frameworks. To elucidate differential brain network involvement linked to distinct aspects of emotion processing, we applied an emergent meta-analytic clustering approach to the extensive body of affective neuroimaging results archived in the BrainMap database. Specifically, we performed hierarchical clustering on the modeled activation maps from 1,747 experiments in the affective processing domain, resulting in five meta-analytic groupings of experiments demonstrating whole-brain recruitment. Behavioral inference analyses conducted for each of these groupings suggested dissociable networks supporting: (1) visual perception within primary and associative visual cortices, (2) auditory perception within primary auditory cortices, (3) attention to emotionally salient information within insular, anterior cingulate, and subcortical regions, (4) appraisal and prediction of emotional events within medial prefrontal and posterior cingulate cortices, and (5) induction of emotional responses within amygdala and fusiform gyri. These meta-analytic outcomes are consistent with a contemporary psychological model of affective processing in which emotionally salient information from perceived stimuli are integrated with previous experiences to engender a subjective affective response. This study highlights the utility of using emergent meta-analytic methods to inform and extend psychological theories and suggests that emotions are manifest as the eventual consequence of interactions between large-scale brain networks.

The human pulvinar is the largest thalamic area in terms of size and cortical connectivity. Although much is known about regional pulvinar structural anatomy, relatively little is known about pulvinar functional anatomy in humans. Cooccurrence of experimentally induced brain activity is a traditional metric used to establish interregional brain connectivity and forms the foundation of functional neuroimaging connectivity analyses. Because functional neuroimaging studies report task-related coactivations within a standardized space, meta-analysis of many whole-brain studies can define the brain's interregional coactivation across many tasks. Such an analysis can also detect and define variations in functional coactivations within a particular region. Here we use coactivation profiles reported in ∼ 7,700 functional neuroimaging studies to parcellate and define the pulvinar's functional anatomy. Parcellation of the pulvinar's coactivation profile identified five clusters per pulvinar of distinct functional coactivation. These clusters showed a high degree of symmetry across hemispheres and correspondence with the human pulvinar's cytoarchitecture. We investigated the functional coactivation profiles of each resultant pulvinar cluster with meta-analytic methods. By referencing existent neuroimaging and lesion-deficit literature, these profiles make a case for regional pulvinar specialization within the larger human attention-controlling network. Reference to this literature also informs specific hypotheses that can be tested in subsequent studies in healthy and clinical populations.

Past neuroimaging studies have focused on identifying specialized functional brain systems for processing different components of reading, such as orthography, phonology, and semantics. More recently, a few experiments have been performed to look into the integration and interaction of distributed neural systems for visual word recognition, suggesting that lexical processing in alphabetic languages involves both ventral and dorsal neural pathways originating from the visual cortex. In the present functional magnetic resonance imaging study, we tested the multiple pathways model with Chinese character stimuli and examined how the neural systems interacted in reading Chinese. Using dynamic causal modeling, we demonstrated that visual word recognition in Chinese engages the ventral pathway from the visual cortex to the left ventral occipitotemporal cortex, but not the dorsal pathway from the visual cortex to the left parietal region. The ventral pathway, however, is linked to the superior parietal lobule and the left middle frontal gyrus (MFG) so that a dynamic neural network is formed, with information flowing from the visual cortex to the left ventral occipitotemporal cortex to the parietal lobule and then to the left MFG. The findings suggest that cortical dynamics is constrained by the differences in how visual orthographic symbols in writing systems are linked to spoken language. Hum Brain Mapp 36:2580–2591, 2015. © 2015 Wiley Periodicals, Inc.

The baboon provides a model of photosensitive, generalized epilepsy. This study compares cerebral blood flow responses during intermittent light stimulation (ILS) between photosensitive (PS) and healthy control (CTL) baboons using H 2 15 O-PET. We examined effective connectivity associated with visual stimulation in both groups using structural equation modeling (SEM). Eight PS and six CTL baboons, matched for age, gender and weight, were classified on the basis of scalp EEG findings performed during the neuroimaging studies. Five H 2 15 O-PET studies were acquired alternating between resting and activation (ILS at 25 Hz) scans. PET images were acquired in 3D mode and co-registered with MRI. SEM demonstrated differences in neural connectivity between PS and CTL groups during ILS that were not previously identified using traditional activation analyses. First-level pathways consisted of similar posterior-to-anterior projections in both groups. While second-level pathways were mainly lateralized to the left hemisphere in the CTL group, they consisted of bilateral anterior-to-posterior projections in the PS baboons. Third- and fourth-level pathways were only evident in PS baboons. This is the first functional neuroimaging study used to model the photoparoxysmal response (PPR) using a primate model of photosensitive, generalized epilepsy. Evidence of increased interhemispheric connectivity and bidirectional feedback loops in the PS baboons represents electrophysiological synchronization associated with the generation of epileptic discharges. PS baboons demonstrated decreased model stability compared to controls, which may be attributed to greater variability in the driving response or PPRs, or to the influence of regions not included in the model.

Despite its 0.5-1% lifetime prevalence in men and its general societal relevance, neuroimag- ing investigations in pedophilia are scarce. Preliminary findings indicate abnormal brain structure and function. However, no study has yet linked structural alterations in pedophiles to both connectional and functional properties of the aberrant hotspots. The relationship between morphological alterations and brain function in pedophilia as well as their contribution to its psychopathology thus remain unclear. First, we assessed bimodal connectivity of structurally altered candidate regions using meta- analytic connectivity modeling (MACM) and resting-state correlations employing openly accessible data. We compared the ensuing connectivity maps to the activation likelihood estimation (ALE) maps of a recent quantitative meta-analysis of brain activity during processing of sexual stimuli. Second, we functionally characterized the structurally altered regions employing meta-data of a large-scale neuroi- maging database. Candidate regions were functionally connected to key areas for processing of sexual stimuli. Moreover, we found that the functional role of structurally altered brain regions in pedophilia relates to nonsexual emotional as well as neurocognitive and executive functions, previously reported to be impaired in pedophiles. Our results suggest that structural brain alterations affect neural net- works for sexual processing by way of disrupted functional connectivity, which may entail abnormal sexual arousal patterns. The findings moreover indicate that structural alterations account for common affective and neurocognitive impairments in pedophilia. The present multimodal integration of brain structure and function analyses links sexual and nonsexual psychopathology in pedophilia. Hum Brain

The role of the amygdala in emotion recognition is well established, and amygdala volume and emotion recognition performance have each been shown separately to be highly heritable traits, but the potential role of common genetic influences on both traits has not been explored. The authors investigated the pleiotropic influences of amygdala volume and emotion recognition performance.In a sample of randomly selected extended pedigrees (N=858), the authors used a combination of univariate and bivariate linkage to investigate pleiotropy between amygdala volume and emotion recognition performance and followed up with association analysis.The authors found a pleiotropic region for amygdala volume and emotion recognition performance on chromosome 4q26 (LOD score=4.40). Association analysis conducted in the region underlying the bivariate linkage peak revealed a variant meeting the corrected significance level (Bonferroni-corrected p=5.01×10(-5)) within an intron of PDE5A (rs2622497, p=4.4×10(-5)) as being jointly influential on both traits. PDE5A has been implicated previously in recognition-memory deficits and is expressed in subcortical structures that are thought to underlie memory ability, including the amygdala.This study extends our understanding of the shared etiology between the amygdala and emotion recognition by showing that the overlap between amygdala volume and emotion recognition performance is due at least in part to common genetic influences. Moreover, this study identifies a pleiotropic locus for the two traits and an associated variant, which localizes the genetic signal even more precisely. These results, when taken in the context of previous research, highlight the potential utility of PDE5 inhibitors for ameliorating emotion recognition deficits in individuals suffering from mental or neurodegenerative illness.

The posterior medial cortex (PMC) is particularly poorly understood. Its neural activity changes have been related to highly disparate mental processes. We therefore investigated PMC properties with a data-driven exploratory approach. First, we subdivided the PMC by whole-brain coactivation profiles. Second, functional connectivity of the ensuing PMC regions was compared by task-constrained meta-analytic coactivation mapping (MACM) and task-unconstrained resting-state correlations (RSFC). Third, PMC regions were functionally described by forward/reverse functional inference. A precuneal cluster was mostly connected to the intraparietal sulcus, frontal eye fields, and right temporo-parietal junction; associated with attention and motor tasks. A ventral posterior cingulate cortex (PCC) cluster was mostly connected to the ventromedial prefrontal cortex and middle left inferior parietal cortex (IPC); associated with facial appraisal and language tasks. A dorsal PCC cluster was mostly connected to the dorsomedial prefrontal cortex, anterior/posterior IPC, posterior midcingulate cortex, and left dorsolateral prefrontal cortex; associated with delay discounting. A cluster in the retrosplenial cortex was mostly connected to the anterior thalamus and hippocampus. Furthermore, all PMC clusters were congruently coupled with the default mode network according to task-constrained but not task-unconstrained connectivity. We thus identified distinct regions in the PMC and characterized their neural networks and functional implications.

Over 90 percent of patients with Parkinson's disease experience speech‐motor impairment, namely, hypokinetic dysarthria characterized by reduced pitch and loudness. Resting‐state functional connectivity analysis of blood oxygen level‐dependent functional magnetic resonance imaging is a useful measure of intrinsic neural functioning. We utilized resting‐state functional connectivity modeling to analyze the intrinsic connectivity in patients with Parkinson's disease within a vocalization network defined by a previous meta‐analysis of speech (Brown et al., 2009). Functional connectivity of this network was assessed in 56 patients with Parkinson's disease and 56 gender‐, age‐, and movement‐matched healthy controls. We also had item 5 and 18 of the UPDRS, and the PDQ‐39 Communication subscale available for correlation with the voice network connectivity strength in patients. The within‐group analyses of connectivity patterns demonstrated a lack of subcortical–cortical connectivity in patients with Parkinson's disease. At the cortical level, we found robust (homotopic) interhemispheric connectivity but only inconsistent evidence for many intrahemispheric connections. When directly contrasted to the control group, we found a significant reduction of connections between the left thalamus and putamen, and cortical motor areas, as well as reduced right superior temporal gyrus connectivity. Furthermore, most symptom measures correlated with right putamen, left cerebellum, left superior temporal gyrus, right premotor, and left Rolandic operculum connectivity in the voice network. The results reflect the importance of (right) subcortical nodes and the superior temporal gyrus in Parkinson's disease, enhancing our understanding of the neurobiological underpinnings of vocalization impairment in Parkinson's disease. Hum Brain Mapp 36:1951–1962, 2015. © 2015 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc..

Wernicke's area is one of the most important language regions and has been widely studied in both basic research and clinical neurology. However, its exact anatomy has been controversial. In this study, we proposed to address the anatomy of Wernicke's area by investigating different connectivity profiles. First, the posterior superior temporal gyrus (STG), traditionally called "Wernicke's area", was parcellated into three component subregions with diffusion MRI. Then, whole-brain anatomical connectivity, resting-state functional connectivity (RSFC) and meta-analytic connectivity modeling (MACM) analyses were used to establish the anatomical, resting-state and task-related coactivation network of each subregion to identify which subregions participated in the language network. In addition, behavioral domain analysis, meta-analyses of semantics, execution speech, and phonology and intraoperative electrical stimulation were used to determine which subregions were involved in language processing. Anatomical connectivity, RSFC and MACM analyses consistently identified that the two anterior subregions in the posterior STG primarily participated in the language network, whereas the most posterior subregion in the temporoparietal junction area primarily participated in the default mode network. Moreover, the behavioral domain analyses, meta-analyses of semantics, execution speech and phonology and intraoperative electrical stimulation mapping also confirmed that only the two anterior subregions were involved in language processing, whereas the most posterior subregion primarily participated in social cognition. Our findings revealed a convergent posterior anatomical border for Wernicke's area and indicated that the brain's functional subregions can be identified on the basis of its specific structural and functional connectivity patterns.

Background Although case-control approaches are beginning to disentangle schizophrenia’s complex polygenic burden, other methods will likely be necessary to fully identify and characterize risk genes. Endophenotypes, traits genetically correlated with an illness, can help characterize the impact of risk genes by providing genetically relevant traits that are more tractable than the behavioral symptoms that classify mental illness. Here, we present an analytic approach for discovering and empirically validating endophenotypes in extended pedigrees with very few affected individuals. Our approach indexes each family member’s risk as a function of shared genetic kinship with an affected individual, often referred to as the coefficient of relatedness. To demonstrate the utility of this approach, we search for neurocognitive and neuroanatomic endophenotypes for schizophrenia in large unselected multigenerational pedigrees. Methods A fixed-effects test within the variance component framework was performed on neurocognitive and cortical surface area traits in 1606 Mexican-American individuals from large, randomly ascertained extended pedigrees who participated in the Genetics of Brain Structure and Function study. As affecteds were excluded from analyses, results were not influenced by disease state or medication usage. Results Despite having sampled just 6 individuals with schizophrenia, our sample provided 233 individuals at various levels of genetic risk for the disorder. We identified three neurocognitive measures (digit-symbol substitution, facial memory, and emotion recognition) and six medial temporal and prefrontal cortical surfaces associated with liability for schizophrenia. Conclusions With our novel analytic approach, one can discover and rank endophenotypes for schizophrenia, or any heritable disease, in randomly ascertained pedigrees.

Item does not contain fulltext The degree to which genetic factors influence brain connectivity is beginning to be understood. Large-scale efforts are underway to map the profile of genetic effects in various brain regions. The NIH-funded Human Connectome Project (HCP) is providing data valuable for analyzing the degree of genetic influence underlying brain connectivity revealed by state-of-the-art neuroimaging methods. We calculated the heritability of the fractional anisotropy (FA) measure derived from diffusion tensor imaging (DTI) reconstruction in 481 HCP subjects (194/287 M/F) consisting of 57/60 pairs of mono- and dizygotic twins, and 246 siblings. FA measurements were derived using (Enhancing NeuroImaging Genetics through Meta-Analysis) ENIGMA DTI protocols and heritability estimates were calculated using the SOLAR-Eclipse imaging genetic analysis package. We compared heritability estimates derived from HCP data to those publicly available through the ENIGMA-DTI consortium, which were pooled together from five-family based studies across the US, Europe, and Australia. FA measurements from the HCP cohort for eleven major white matter tracts were highly heritable (h(2)=0.53-0.90, p

Neuroimaging evidence suggests that executive functions (EF) depend on brain regions that are not closely tied to specific cognitive demands but rather to a wide range of behaviors. A multiple-demand (MD) system has been proposed, consisting of regions showing conjoint activation across multiple demands. Additionally, a number of studies defining networks specific to certain cognitive tasks suggest that the MD system may be composed of a number of sub-networks each subserving specific roles within the system. We here provide a robust definition of an extended MDN (eMDN) based on task-dependent and task-independent functional connectivity analyses seeded from regions previously shown to be convergently recruited across neuroimaging studies probing working memory, attention and inhibition, i.e., the proposed key components of EF. Additionally, we investigated potential sub-networks within the eMDN based on their connectional and functional similarities. We propose an eMDN network consisting of a core whose integrity should be crucial to performance of most operations that are considered higher cognitive or EF. This then recruits additional areas depending on specific demands.

The neural systems of lexical tone processing have been studied for many years. However, previous findings have been mixed with regard to the hemispheric specialization for the perception of linguistic pitch patterns in native speakers of tonal language. In this study, we performed two activation likelihood estimation (ALE) meta-analyses, one on neuroimaging studies of auditory processing of lexical tones in tonal languages (17 studies), and the other on auditory processing of lexical information in non-tonal languages as a control analysis for comparison (15 studies). The lexical tone ALE analysis showed significant brain activations in bilateral inferior prefrontal regions, bilateral superior temporal regions and the right caudate. While the control ALE analysis showed significant cortical activity in the left inferior frontal gyrus and left temporo-parietal regions. However, we failed to obtain significant differences from the contrast analysis between two auditory conditions, which might be caused by the limited number of studies available for comparison. Although the current study lack evidence to argue for a lexical tone specific activation pattern, our results provide clues and directions for future investigations on this topic, more and more sophisticated methods are needed to explore this question in more depth as well.

Highlights • Developed and validated an overt continuous speech paradigm for use in fMRI. • The speech paradigm successfully identified the neural circuit of speech production. • The speech paradigm is effective in mapping disordered motor speech. • The fMRI paradigm will be useful for studying normal and disordered speech., We developed a task paradigm whereby subjects spoke aloud while minimizing head motion during functional MRI (fMRI) in order to better understand the neural circuitry involved in motor speech disorders due to dysfunction of the central nervous system. To validate our overt continuous speech paradigm, we mapped the speech production network (SPN) in typical speakers (n = 19, 10 females) and speakers with hypokinetic dysarthria as a manifestation of Parkinson disease (HKD; n = 21, 8 females) in fMRI. We then compared it with the SPN derived during overt speech production by 15O-water PET in the same group of typical speakers and another HKD cohort (n = 10, 2 females). The fMRI overt connected speech paradigm did not result in excessive motion artifacts and successfully identified the same brain areas demonstrated in the PET studies in the two cohorts. The SPN derived in fMRI demonstrated significant spatial overlap with the corresponding PET derived maps (typical speakers: r = 0.52; speakers with HKD: r = 0.43) and identified the components of the neural circuit of speech production belonging to the feedforward and feedback subsystems. The fMRI study in speakers with HKD identified significantly decreased activity in critical feedforward (bilateral dorsal premotor and motor cortices) and feedback (auditory and somatosensory areas) subsystems replicating previous PET study findings in this cohort. These results demonstrate that the overt connected speech paradigm is feasible during fMRI and can accurately localize the neural substrates of typical and disordered speech production. Our fMRI paradigm should prove useful for study of motor speech and voice disorders, including stuttering, apraxia of speech, dysarthria, and spasmodic dysphonia.

Neuroscience literature increasingly suggests a conceptual self composed of interacting neu- ral regions, rather than independent local activations, yet such claims have yet to be investigated. We, thus, combined task-dependent meta-analytic connectivity modeling (MACM) with task-independent resting-state (RS) connectivity analysis to delineate the neural network of the self, across both states. Given psychological evidence implicating the self's interdependence on social information, we also delineated the neural network underlying conceptual other-processing. To elucidate the relation between the self-/other-networks and their function, we mined the MACM metadata to generate a cognitive-behavioral profile for an empirically identified region specific to conceptual self, the prege- nual anterior cingulate (pACC), and conceptual other, posterior cingulate/precuneus (PCC/PC). Min- ing of 7,200 published, task-dependent, neuroimaging studies, using healthy human subjects, yielded 193 studies activating the self-related seed and were conjoined with RS connectivity analysis to delin- eate a differentiated self-network composed of the pACC (seed) and anterior insula, relative to other functional connectivity. Additionally, 106 studies activating the other-related seed were conjoined with RS connectivity analysis to delineate a differentiated other-network of PCC/PC (seed) and angular gyrus/temporoparietal junction, relative to self-functional connectivity. The self-network seed related to emotional conflict resolution and motivational processing, whereas the other-network seed related

The human dorsomedial prefrontal cortex (dmPFC) has been implicated in various complex cognitive processes, including social cognition. To unravel its functional organization, we assessed the dmPFC's regional heterogeneity, connectivity patterns, and functional profiles. First, the heterogeneity of a dmPFC seed, engaged during social processing, was investigated by assessing local differences in whole-brain coactivation profiles. Second, functional connectivity of the ensuing dmPFC clusters was compared by task-constrained meta-analytic coactivation mapping and task-unconstrained resting-state correlations. Third, dmPFC clusters were functionally profiled by forward/reverse inference. The dmPFC seed was thus segregated into 4 clusters (rostroventral, rostrodorsal, caudal-right, and caudal-left). Both rostral clusters were connected to the amygdala and hippocampus and associated with memory and social cognitive tasks in functional decoding. The rostroventral cluster exhibited strongest connectivity to the default mode network. Unlike the rostral segregation, the caudal dmPFC was divided by hemispheres. The caudal-right cluster was strongly connected to a frontoparietal network (dorsal attention network), whereas the caudal-left cluster was strongly connected to the anterior midcingulate cortex and bilateral anterior insula (salience network). In conclusion, we demonstrate that a dmPFC seed reflecting social processing can be divided into 4 separate functional modules that contribute to distinct facets of advanced human cognition.

Research on how lexical tone is neuroanatomically represented in the human brain is central to our understanding of cortical regions subserving language. Past studies have exclusively focused on tone perception of the spoken language, and little is known as to the lexical tone processing in reading visual words and its associated brain mechanisms. In this study, we performed two experiments to identify neural substrates in Chinese tone reading. First, we used a tone judgment paradigm to investigate tone processing of visually presented Chinese characters. We found that, relative to baseline, tone perception of printed Chinese characters were mediated by strong brain activation in bilateral frontal regions, left inferior parietal lobule, left posterior middle/medial temporal gyrus, left inferior temporal region, bilateral visual systems, and cerebellum. Surprisingly, no activation was found in superior temporal regions, brain sites well known for speech tone processing. In activation likelihood estimation (ALE) meta-analysis to combine results of relevant published studies, we attempted to elucidate whether the left temporal cortex activities identified in Experiment one is consistent with those found in previous studies of auditory lexical tone perception. ALE results showed that only the left superior temporal gyrus and putamen were critical in auditory lexical tone processing. These findings suggest that activation in the superior temporal cortex associated with lexical tone perception is modality-dependent.

The superior parietal lobule (SPL) plays a pivotal role in many cognitive, perceptive, and motor-related processes. This implies that a mosaic of distinct functional and structural subregions may exist in this area. Recent studies have demonstrated that the ongoing spontaneous fluctuations in the brain at rest are highly structured and, like coactivation patterns, reflect the integration of cortical locations into long-distance networks. This suggests that the internal differentiation of a complex brain region may be revealed by interaction patterns that are reflected in different neuroimaging modalities. On the basis of this perspective, we aimed to identify a convergent functional organization of the SPL using multimodal neuroimaging approaches. The SPL was first parcellated based on its structural connections as well as on its resting-state connectivity and coactivation patterns. Then, post hoc functional characterizations and connectivity analyses were performed for each subregion. The three types of connectivity-based parcellations consistently identified five subregions in the SPL of each hemisphere. The two anterior subregions were found to be primarily involved in action processes and in visually guided visuomotor functions, whereas the three posterior subregions were primarily associated with visual perception, spatial cognition, reasoning, working memory, and attention. This parcellation scheme for the SPL was further supported by revealing distinct connectivity patterns for each subregion in all the used modalities. These results thus indicate a convergent functional architecture of the SPL that can be revealed based on different types of connectivity and is reflected by different functions and interactions.

Noninvasive markers of brain function could yield biomarkers in many neurological disorders. Disease models constrained by coordinate-based meta-analysis are likely to increase this yield. Here, we evaluate a thalamic model of temporal lobe epilepsy that we proposed in a coordinate-based meta-analysis and extended in a diffusion tractography study of an independent patient population. Specifically, we evaluated whether thalamic functional connectivity (resting-state fMRI-BOLD) with temporal lobe areas can predict seizure onset laterality, as established with intracranial EEG. Twenty-four lesional and non-lesional temporal lobe epilepsy patients were studied. No significant differences in functional connection strength in patient and control groups were observed with Mann-Whitney Tests (corrected for multiple comparisons). Notwithstanding the lack of group differences, individual patient difference scores (from control mean connection strength) successfully predicted seizure onset zone as shown in ROC curves: discriminant analysis (two-dimensional) predicted seizure onset zone with 85% sensitivity and 91% specificity; logistic regression (four-dimensional) achieved 86% sensitivity and 100% specificity. The strongest markers in both analyses were left thalamo-hippocampal and right thalamo-entorhinal cortex functional connection strength. Thus, this study shows that thalamic functional connections are sensitive and specific markers of seizure onset laterality in individual temporal lobe epilepsy patients. This study also advances an overall strategy for the programmatic development of neuroimaging biomarkers in clinical and genetic populations: a disease model informed by coordinate-based meta-analysis was used to anatomically constrain individual patient analyses., Highlights • A thalamic disease model informed connectivity analyses in temporal lobe epilepsy. • No patient vs. control group differences in thalamic connection strength were observed. • Yet thalamic functional connection strength predicted seizure onset laterality. • Lack of group difference should not deter constrained assessment in individuals. • Meta-analytic disease models successfully guide individual patient biomarker development.

Individuals with a family history of substance use disorder (FH+) show impaired frontal white matter as indicated by diffusion tensor imaging (DTI). This impairment may be due to impaired or delayed development of myelin in frontal regions, potentially contributing to this population's increased risk for developing substance use disorders. In this study, we examined high angular resolution DTI and proton magnetic resonance spectroscopy data from the anterior corona radiata were collected in 80 FH+ and 34 FH- youths (12.9 ± 1.0 years old). White matter integrity indices included fractional anisotropy (FA), N-acetylaspartate (NAA), and total choline (tCho). Lower FA suggests decreased myelination. Decreased NAA coupled with higher tCho suggests impaired build-up and maintenance of cerebral myelin and consequently greater breakdown of cellular membranes. We found FH+ youths had lower FA (P < 0.0001) and NAA (P = 0.017) and higher tCho (P = 0.04). FH density (number of parents and grandparents with substance use disorders) was negatively correlated with FA (P < 0.0001) and NAA (P = 0.011) and positively correlated with tCho (P = 0.001). FA was independently predicted by both FH density (P = 0.006) and NAA (P = 0.002), and NAA and tCho were both independent predictors of FH density (P < 0.001). Our finding of lower frontal FA in FH+ youths corresponding to lower NAA and increased tCho is consistent with delayed or impaired development of frontal white matter in FH+ youths. Longitudinal studies are needed to determine how these differences relate to substance use outcomes.

Spatial normalization—applying standardized coordinates as anatomical addresses within a reference space—was introduced to human neuroimaging research nearly 30 years ago. Over these three decades, an impressive series of methodological advances have adopted, extended, and popularized this standard. Collectively, this work has generated a methodologically coherent literature of unprecedented rigor, size, and scope. Large-scale online databases have compiled these observations and their associated meta-data, stimulating the development of meta-analytic methods to exploit this expanding corpus. Coordinate-based meta-analytic methods have emerged and evolved in rigor and utility. Early methods computed cross-study consensus, in a manner roughly comparable to traditional (nonimaging) meta-analysis. Recent advances now compute coactivation-based connectivity, connectivity-based functional parcellation, and complex network models powered from data sets representing tens of thousands of subjects. Meta-analyses of human neuroimaging data in large-scale databases now stand at the forefront of computational neurobiology.

The right temporoparietal junction (rTPJ) is frequently associated with different capacities that to shift attention to unexpected stimuli (reorienting of attention) and to understand others' (false) mental state [theory of mind (ToM), typically represented by false belief tasks]. Competing hypotheses either suggest the rTPJ representing a unitary region involved in separate cognitive functions or consisting of subregions subserving distinct processes. We conducted activation likelihood estimation (ALE) meta-analyses to test these hypotheses. A conjunction analysis across ALE meta-analyses delineating regions consistently recruited by reorienting of attention and false belief studies revealed the anterior rTPJ, suggesting an overarching role of this specific region. Moreover, the anatomical difference analysis unravelled the posterior rTPJ as higher converging in false belief compared with reorienting of attention tasks. This supports the concept of an exclusive role of the posterior rTPJ in the social domain. These results were complemented by meta-analytic connectivity mapping (MACM) and resting-state functional connectivity (RSFC) analysis to investigate whole-brain connectivity patterns in task-constrained and task-free brain states. This allowed for detailing the functional separation of the anterior and posterior rTPJ. The combination of MACM and RSFC mapping showed that the posterior rTPJ has connectivity patterns with typical ToM regions, whereas the anterior part of rTPJ co-activates with the attentional network. Taken together, our data suggest that rTPJ contains two functionally fractionated subregions: while posterior rTPJ seems exclusively involved in the social domain, anterior rTPJ is involved in both, attention and ToM, conceivably indicating an attentional shifting role of this region.

Individuals with a family history of substance use disorders (FH+) are at a greater risk of developing substance use disorders than their peers with no such family histories (FH−) and this vulnerability is proportional to the number of affected relatives (FH density). The risk for developing substance use disorders peaks during adolescence to early adulthood in the general population, and that is thought to be related to delayed maturation of frontocortical and frontostriatal functional circuits. We hypothesized that FH+ youth and young adults have impaired myelination of frontocortical and frontostriatal white matter tracts. We examined fractional anisotropy (FA) data in 80 FH+ and 34 FH− youths (12.9±1.0 years) and in 25 FH+ and 30 FH− young adults (24.3±3.4 years). FH+ youths had lower FA values in both frontocortical and frontostriatal tracts as well as parietocortical tracts including the anterior, superior and posterior corona radiata and the superior frontal-occipital fasciculus. Moreover, FA values in these tracts were negatively correlated with FH density. FH+ adults had lower FA values in two frontocortical tracts: the genu of the corpus callosum and anterior corona radiata and also significant negative correlations between FA and FH density in these same tracts. In both groups, lower FA values corresponded to higher radial diffusivity suggesting reduced axonal myelination. We interpreted our findings as evidence for impaired myelination of frontal white matter that was proportional to FH density. Our data suggest that deficits may partially resolve with age, paralleling an age-related decline in risk for developing substance use disorders.