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Early diagnosis is crucial to slowing the progression of Alzheimer's disease (AD), so it is urgent to find an effective diagnostic method for AD. This study intended to investigate whether the transfer learning approach of deep Q-network (DQN) could effectively distinguish AD patients using local metrics of resting-state functional magnetic resonance imaging (rs-fMRI) as features. This study included 1310 subjects from the Consortium for Reliability and Reproducibility (CoRR) and 50 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) GO/2. The amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF) and percent amplitude of fluctuation (PerAF) were extracted as features using the Power 264 atlas. Based on gender bias in AD, we searched for transferable similar parts between the CoRR feature matrix and the ADNI feature matrix, resulting in the CoRR similar feature matrix served as the source domain and the ADNI similar feature matrix served as the target domain. A DQN classifier was pre-trained in the source domain and transferred to the target domain. Finally, the transferred DQN classifier was used to classify AD and healthy controls (HC). A permutation test was performed. The DQN transfer learning achieved a classification accuracy of 86.66% (p < 0.01), recall of 83.33% and precision of 83.33%. The findings suggested that the transfer learning approach using DQN could be an effective way to distinguish AD from HC. It also revealed the potential value of local brain activity in AD clinical diagnosis., (© 2024 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.)

A growing body of evidence indicates the existence of abnormal local and long-range functional connection patterns in patients with alcohol use disorder (AUD). However, it has yet to be established whether AUD is associated with abnormal interhemispheric and intrahemispheric functional connection patterns. In the present study, we analysed resting-state functional magnetic resonance imaging data from 55 individuals with AUD and 32 healthy nonalcohol users. For each subject, whole-brain functional connectivity density (FCD) was decomposed into ipsilateral and contralateral parts. Correlation analysis was performed between abnormal FCD and a range of clinical measurements in the AUD group. Compared with healthy controls, the AUD group exhibited a reduced global FCD in the anterior and middle cingulate gyri, prefrontal cortex and thalamus, along with an enhanced global FCD in the temporal, parietal and occipital cortices. Abnormal interhemispheric and intrahemispheric FCD patterns were also detected in the AUD group. Furthermore, abnormal global, contralateral and ipsilateral FCD data were correlated with the mean amount of pure alcohol and the severity of alcohol addiction in the AUD group. Collectively, our findings indicate that global, interhemispheric and intrahemispheric FCD may represent a robust method to detect abnormal functional connection patterns in AUD; this may help us to identify the neural substrates and therapeutic targets of AUD., (© 2024 The Authors. Addiction Biology published by John Wiley & Sons Ltd on behalf of Society for the Study of Addiction.)

To model behavioral and neural correlates of language comprehension in naturalistic environments, researchers have turned to broad-coverage tools from natural-language processing and machine learning. Where syntactic structure is explicitly modeled, prior work has relied predominantly on context-free grammars (CFGs), yet such formalisms are not sufficiently expressive for human languages. Combinatory categorial grammars (CCGs) are sufficiently expressive directly compositional models of grammar with flexible constituency that affords incremental interpretation. In this work, we evaluate whether a more expressive CCG provides a better model than a CFG for human neural signals collected with functional magnetic resonance imaging (fMRI) while participants listen to an audiobook story. We further test between variants of CCG that differ in how they handle optional adjuncts. These evaluations are carried out against a baseline that includes estimates of next-word predictability from a transformer neural network language model. Such a comparison reveals unique contributions of CCG structure-building predominantly in the left posterior temporal lobe: CCG-derived measures offer a superior fit to neural signals compared to those derived from a CFG. These effects are spatially distinct from bilateral superior temporal effects that are unique to predictability. Neural effects for structure-building are thus separable from predictability during naturalistic listening, and those effects are best characterized by a grammar whose expressive power is motivated on independent linguistic grounds., (© 2023 The Authors. Cognitive Science published by Wiley Periodicals LLC on behalf of Cognitive Science Society (CSS).)

One approach to understanding how the human cognitive system stores and operates with quantifiers such as "some," "many," and "all" is to investigate their interaction with the cognitive mechanisms for estimating and comparing quantities from perceptual input (i.e., nonsymbolic quantities). While a potential link between quantifier processing and nonsymbolic quantity processing has been considered in the past, it has never been discussed extensively. Simultaneously, there is a long line of research within the field of numerical cognition on the relationship between processing exact number symbols (such as "3" or "three") and nonsymbolic quantity. This accumulated knowledge can potentially be harvested for research on quantifiers since quantifiers and number symbols are two different ways of referring to quantity information symbolically. The goal of the present review is to survey the research on the relationship between quantifiers and nonsymbolic quantity processing mechanisms and provide a set of research directions and specific questions for the investigation of quantifier processing., (© 2023 The Authors. Cognitive Science published by Wiley Periodicals LLC on behalf of Cognitive Science Society (CSS).)

Heart failure (HF) is a complex clinical syndrome with multiple interactions between the failing myocardium and cerebral (dys-)functions. Bi-directional feedback interactions between the heart and the brain are inherent in the pathophysiology of HF: (i) the impaired cardiac function affects cerebral structure and functional capacity, and (ii) neuronal signals impact on the cardiovascular continuum. These interactions contribute to the symptomatic presentation of HF patients and affect many co-morbidities of HF. Moreover, neuro-cardiac feedback signals significantly promote aggravation and further progression of HF and are causal in the poor prognosis of HF. The diversity and complexity of heart and brain interactions make it difficult to develop a comprehensive overview. In this paper a systematic approach is proposed to develop a comprehensive atlas of related conditions, signals and disease mechanisms of the interactions between the heart and the brain in HF. The proposed taxonomy is based on pathophysiological principles. Impaired perfusion of the brain may represent one major category, with acute (cardio-embolic) or chronic (haemodynamic failure) low perfusion being sub-categories with mostly different consequences (i.e. ischaemic stroke or cognitive impairment, respectively). Further categories include impairment of higher cortical function (mood, cognition), f brain stem function (sympathetic over-activation, neuro-cardiac reflexes). Treatment-related interactions could be categorized as medical, interventional and device-related interactions. Also interactions due to specific diseases are categorized. A methodical approach to categorize the interdependency of heart and brain may help to integrate individual research areas into an overall picture. [ABSTRACT FROM AUTHOR]

Problematic gaming in adolescents is associated with neural alterations in structural and functional imaging studies. Especially frontal regions, associated with cognitive control functions, as well as temporoparietal areas, responsible for attention processes and self-concepts, and frontolimbic and subcortical regions, connected to emotion regulation and reward processing, are affected. The differences provide a further explanation for addictive disorders and emphasize the importance of interventions that address executive and cognitive-affective deficits., (© 2021 The Authors. Addiction Biology published by John Wiley & Sons Ltd on behalf of Society for the Study of Addiction.)

Stimulant drug-paired cues can acquire the ability to activate mesocorticolimbic pathways and lead to new bouts of drug use. Studies in laboratory animals suggest that these effects are augmented by progressively greater drug use histories, impulsive personality traits, and acute drug ingestion. As a preliminary test of these hypotheses in humans, we exposed cocaine users (n = 14) and healthy volunteers (n = 10) to cocaine-related videos during two functional magnetic resonance imaging (fMRI) sessions, once following acute administration of placebo and once following d-amphetamine (0.3 mg/kg, p.o.). Across sessions, cocaine users showed larger cocaine cue-induced responses than healthy controls in the associative striatum and midbrain. Among the cocaine users, larger drug cue-induced responses during the placebo session were correlated with higher Barratt Impulsiveness Scale (BIS-11) nonplanning scores (associative striatum) and greater lifetime use of stimulant drugs (limbic, associative, and sensorimotor striatum). The administration of d-amphetamine did not augment the cue-induced activations, but, in cocaine users, drug cue-induced striatal activations were more widespread following prolonged cocaine cue exposure. Together, these effects of past and present drug use might aggravate the risk for stimulant drug use problems., (© 2021 Society for the Study of Addiction.)

How does the human brain link relational concepts to perceptual experience? For example, a speaker may say "the cup to the left of the computer" to direct the listener's attention to one of two cups on a desk. We provide a neural dynamic account for both perceptual grounding, in which relational concepts enable the attentional selection of objects in the visual array, and for the generation of descriptions of the visual array using relational concepts. In the model, activation in neural populations evolves dynamically under the influence of both inputs and strong interaction as formalized in dynamic field theory. Relational concepts are modeled as patterns of connectivity to perceptual representations. These generalize across the visual array through active coordinate transforms that center the representation of target objects in potential reference objects. How the model perceptually grounds or generates relational descriptions is probed in 104 simulations that systematically vary the spatial and movement relations employed, the number of feature dimensions used, and the number of matching and nonmatching objects. We explain how sequences of decisions emerge from the time- and state-continuous neural dynamics, how relational hypotheses are generated and either accepted or rejected, followed by the selection of new objects or the generation of new relational hypotheses. Its neural realism distinguishes the model from information processing accounts, its capacity to autonomously generate sequences of processing steps distinguishes it from deep neural network accounts. The model points toward a neural dynamic theory of higher cognition., (© 2021 The Authors. Cognitive Science published by Wiley Periodicals LLC on behalf of Cognitive Science Society (CSS).)

Objectives: Progressive supranuclear palsy-Richardson syndrome (PSP-RS) is characterized by symmetrical parkinsonism with postural instability and frontal dysfunction. This study aims to use the whole brain structural connectome (SC) to gain insights into the underlying disconnectivity which may be implicated in the clinical features of PSP-RS., Methods: Sixteen patients of PSP-RS and 12 healthy controls were recruited. Disease severity was quantified using PSP rating scale (PSPRS), and mini-mental scale was applied to evaluate cognition. Thirty-two direction diffusion MRIs were acquired and used to compute the structural connectome of the whole brain using deterministic fiber tracking. Group analyses were performed at the edge-wise, nodal, and global levels. Age and gender were used as nuisance covariates for all the subsequent analyses, and FDR correction was applied., Results: Network-based statistics revealed a 34-edge network with significantly abnormal edge-wise connectivity in the patient group. Of these, 25 edges were cortical connections, of which 68% were frontal connections. Abnormal deep gray matter connections were predominantly comprised of connections between structures of the basal ganglia. The characteristic path length of the SC was lower in PSP-RS, and nodal analysis revealed abnormal degree, strength, local efficiency, betweenness centrality, and participation coefficient in several nodes., Conclusions: Significant alterations in the structural connectivity of the whole brain connectome were observed in PSP-RS. The higher degree of abnormality observed in nodes belonging to the frontal lobe and basal ganglia substantiates the predominant frontal dysfunction and parkinsonism observed in PSP-RS. The findings of this study support the concept that PSP-RS may be a network-based disorder., (© 2020 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Patients with substance use disorders (SUD) are at high risk to die by suicide. So far, the neurobiology of the suicide-SUD association has not been elucidated. This study aimed to identify potential pharmacological targets among hub genes from brain gene co-expression networks of individuals with SUD in a suicidal and non-suicidal context. Post-mortem samples from the prefrontal cortex of 79 individuals were analyzed. Individuals were classified into the following groups: suicides with SUD (n = 28), suicides without SUD (n = 23), nonsuicides with SUD (n = 9), nonsuicides without SUD (n = 19). Gene expression profiles were evaluated with the Illumina HumanHT-12 v4 array. Co-expression networks were constructed in WGCNA using the differentially expressed genes found in the comparisons: (a) suicides with and without SUD and (b) nonsuicides with and without SUD. Hub genes were selected for drug-gene interaction testing in the DGIdb database. Among drugs interacting with hub genes in suicides we found MAOA inhibitors and dextromethorphan. In the nonsuicide individuals, we found interactions with eglumegad and antipsychotics (olanzapine, clozapine, loxapine). Modafinil was found to interact with genes in both suicides and nonsuicides. These drugs represent possible candidate treatments for patients with SUD with and without suicidal behavior and their study in each context is encouraged., (© 2021 Wiley Periodicals LLC.)

Objective: To assess hemispheric differences in the duration of focal onset seizures and its association with clinical and demographic factors., Methods: A retrospective analysis was performed on adult patients with drug-resistant unifocal epilepsy, who underwent intracranial EEG recording between 01/2006 and 06/2016. Seizure duration was determined based on the subdural and/or stereo-EEG (sEEG) recordings. Hemispheric differences in seizure duration were statistically evaluated with regard to clinical and demographic data., Results: In total, 69 patients and 654 focal onset seizures were included. The duration of seizures with left-hemispheric onset (n = 297) was by trend longer (91.88 ± 93.92 s) than of right-hemispheric seizures (n = 357; 71.03 ± 68.53 s; p = .193). Significant hemispheric differences in seizures duration were found in temporal lobe seizures (n = 225; p = .013), especially those with automotor manifestation (n = 156; p = .045). A prolonged duration was also found for left-hemispheric onset seizures with secondary generalized commencing during waking state (n = 225; p = .034), but not during sleep. A similar hemispheric difference in seizure duration was found in female patients (p = .040), but not in men., Conclusions: Hemispheric differences in seizure duration were revealed with significantly longer durations in case of left-hemispheric seizure onset. The observed differences in seizure duration might result from brain asymmetry and add new aspects to the understanding of seizure propagation and termination., (© 2020 The Authors. Acta Neurologica Scandinavica published by John Wiley & Sons Ltd.)

Objectives: Common wisdom in paleoanthropology is that Neandertals had bigger brains than recent humans. Here we tested the hypothesis that there is no difference in brain size between Neandertals and recent humans while accounting for methodological variation and the makeup of both the Neandertal and recent human samples., Materials and Methods: We examined endocranial volume (ECV) derived from virtually reconstructed endocasts of 11 Neandertals, six of which had associated femoral head diameters (FHD). Our recent human comparative dataset consisted of virtually measured ECV and associated FHD from 94 recent humans from the Robert J. Terry Anatomical Collection (63 male, 31 female). ECV of Neandertals and recent humans was compared using bootstrap resampling, repeating the analysis for two groupings of Neandertals (all and classic) and for three groupings of recent humans (all, males, and females). To examine brain size scaling, we completed an ordinary least squares regression of log (ECV) against log (FHD) for Neandertals and recent humans., Results: The results of the bootstrap resampling analyses indicated that Neandertals only had significantly larger ECV when compared with recent human females. The regression between ECV and FHD suggested that Neandertals fall within the range of variation for larger humans., Discussion: Our results demonstrate that Neandertals do not have uniquely large brains when compared with recent humans. Their brain size falls in the large end of the recent human range of variation, but does not exceed it. These results have implications for future research on Neandertal encephalization., (© 2020 Wiley Periodicals LLC.)

Objectives: Seizures are a prominent feature of anti-N-methyl-d-aspartate receptor (anti-NMDAR) encephalitis. Nearly half of brain magnetic resonance image (MRI) results are abnormal. The aim of our study was to evaluate the associations between seizures and brain MRI results in patients with anti-NMDAR encephalitis., Methods: Patients with anti-NMDAR encephalitis were enrolled between January 2015 and December 2018. The patients included were divided into normal and abnormal MRI groups. Seizure outcomes and modified Rankin Scale scores at the 1-year follow-up were assessed. Seizure characteristics and outcomes were compared between groups., Results: Of 35 patients with anti-NMDAR encephalitis, 28 patients (80%) had reported seizures in the acute phase. Patients with abnormal MRI findings more frequently had focal seizures than patients with normal MRI findings (72.7% vs 17.6%, P < .01). The incidence of patients treated with 2 or more antiepileptic drugs was higher in the normal MRI group than in the abnormal MRI group (100% vs 45.4%, P < .01). The onset-immunotherapy time was shorter in the abnormal MRI group than in the normal MRI group (P < .05). There were no statistically significant differences in seizure outcomes between the normal and abnormal MRI groups (P > .05)., Conclusions: Focal seizures were most common in patients with abnormal MRI lesions. In the acute stage of the disease, the abnormal MRI group was more likely than the normal MRI group to achieve seizure control. Abnormal MRI findings did not affect the overall good prognosis of patients with anti-NMDAR encephalitis with seizures., (© 2020 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

The article presents a commentary on the role of phosphatidylethanol in assessing postmortem ethanol intake in autopsies. The author highlights the use of the ethanol compound as a biomarker in determining alcohol consumption in an autopsied person's brain and serum blood level. The author also offers the detailed information on the research conducted on the effectiveness of phosphatidylethanol in autopsies.

Aim: To study brain-sparing physiological responses in a rodent model of birth asphyxia which reproduces the asphyxia-defining systemic hypoxia and hypercapnia., Methods: Steady or intermittent asphyxia was induced for 15-45 minutes in anaesthetized 6- and 11-days old rats and neonatal guinea pigs using gases containing 5% or 9% O 2 plus 20% CO 2 (in N 2 ). Hypoxia and hypercapnia were induced with low O 2 and high CO 2 respectively. Oxygen partial pressure (PO 2 ) and pH were measured with microsensors within the brain and subcutaneous ("body") tissue. Blood lactate was measured after asphyxia., Results: Brain and body PO 2 fell to apparent zero with little recovery during 5% O 2 asphyxia and 5% or 9% O 2 hypoxia, and increased more than twofold during 20% CO 2 hypercapnia. Unlike body PO 2 , brain PO 2 recovered rapidly to control after a transient fall (rat), or was slightly higher than control (guinea pig) during 9% O 2 asphyxia. Asphyxia (5% O 2 ) induced a respiratory acidosis paralleled by a progressive metabolic (lact)acidosis that was much smaller within than outside the brain. Hypoxia (5% O 2 ) produced a brain-confined alkalosis. Hypercapnia outlasting asphyxia suppressed pH recovery and prolonged the post-asphyxia PO 2 overshoot. All pH changes were accompanied by consistent shifts in the blood-brain barrier potential., Conclusion: Regardless of brain maturation stage, hypercapnia can restore brain PO 2 and protect the brain against metabolic acidosis despite compromised oxygen availability during asphyxia. This effect extends to the recovery phase if normocapnia is restored slowly, and it is absent during hypoxia, demonstrating that exposure to hypoxia does not mimic asphyxia., (© 2020 The Authors. Acta Physiologica published by John Wiley & Sons Ltd on behalf of Scandinavian Physiological Society.)

During competitive interactions, such as predator-prey or team sports, the outcome of one's actions is dependent on both their own choices and those of their opponents. Success in these rivalries requires that individuals choose dynamically and unpredictably, often adopting a mixed strategy. Understanding the neural basis of strategic decision making is complicated by the fact that it recruits various cognitive processes that are often shared with non-strategic forms of decision making, such as value estimation, working memory, response inhibition, response selection, and reward processes. Although researchers have explored neural activity within key brain regions during mixed-strategy games, how brain activity differs in the context of strategic interactions versus non-strategic choices is not well understood. We developed a novel behavioral paradigm to dissociate choice behavior during mixed-strategy interactions from non-strategic choices, and we used task-based functional magnetic resonance imaging (fMRI) to contrast brain activation. In a block design, participants competed in the classic mixed-strategy game, "matching pennies," against a dynamic computer opponent designed to exploit predictability in players' response patterns. Results were contrasted with a non-strategic task that had comparable sensory input, motor output, and reward rate; thus, differences in behavior and brain activation reflect strategic processes. The mixed-strategy game was associated with activation of a distributed cortico-striatal network compared to the non-strategic task. We propose that choosing in mixed-strategy contexts requires additional cognitive demands present to a lesser degree during the control task, illustrating the strength of this design in probing function of cognitive systems beyond core sensory, motor, and reward processes., (© 2019 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.)

New Findings: What is the central question of this study? Does habitual resistance and endurance exercise modify dynamic cerebral autoregulation? What is the main finding and its importance? To the authors' knowledge, this is the first study to directly assess dynamic cerebral autoregulation in resistance-trained individuals, and potential differences between exercise training modalities. Forced oscillations in blood pressure were induced by repeated squat-stands, from which dynamic cerebral autoregulation was assessed using transfer function analysis. These data indicate that dynamic cerebral autoregulatory function is largely unaffected by habitual exercise type, and further document the systemic circulatory effects of regular exercise., Abstract: Regular endurance and resistance exercise produce differential but desirable physiological adaptations in both healthy and clinical populations. The chronic effect of these different exercise modalities on cerebral vessels' ability to respond to rapid changes in blood pressure (BP) had not been examined. We examined dynamic cerebral autoregulation (dCA) in 12 resistance-trained (mean ± SD, 25 ± 6 years), 12 endurance-trained (28 ± 9 years) and 12 sedentary (26 ± 6 years) volunteers. The dCA was assessed using transfer function analysis of forced oscillations in BP vs. middle cerebral artery blood velocity (MCAv), induced via repeated squat-stands at 0.05 and 0.10 Hz. Resting BP and MCAv were similar between groups (interaction: both P ≥ 0.544). The partial pressure of end-tidal carbon dioxide ( P ETC O 2 ) was unchanged (P = 0.561) across squat-stand manoeuvres (grouped mean for absolute change +0.6 ± 2.3 mmHg). Gain and normalized gain were similar between groups across all frequencies (both P ≥ 0.261). Phase showed a frequency-specific effect between groups (P = 0.043), tending to be lower in resistance-trained (0.63 ± 0.21 radians) than in endurance-trained (0.90 ± 0.41, P = 0.052) and -untrained (0.85 ± 0.38, P = 0.081) groups at slower frequency (0.05 Hz) oscillations. Squat-stands induced mean arterial pressure perturbations differed between groups (interaction: P = 0.031), with greater changes in the resistance (P < 0.001) and endurance (P = 0.001) groups compared with the sedentary group at 0.05 Hz (56 ± 13 and 49 ± 11 vs. 35 ± 11 mmHg, respectively). The differences persisted at 0.1 Hz between resistance and sedentary groups (49 ± 12 vs. 33 ± 7 mmHg, P < 0.001). These results indicate that dCA remains largely unaltered by habitual endurance and resistance exercise with a trend for phase to be lower in the resistance exercise group at lower fequencies., (© 2019 The Authors. Experimental Physiology © 2019 The Physiological Society.)

The article presents a study which examines the natural endocast of Australopithecus africanus "Taung" in the context of Raymond Dart's perspectives based on his unpublished observations and illustrations from 1925-1929. It explores several issues related to the identities of lunate sulcus and luci and sutures to give light to the concept of A. africanus. Dart asserts that Taung's brain was reorganized globally and that it was closer to brain of Pithecanthropus compared to the living apes.

Many eating-related psychological constructs have been proposed to explain obesity and overeating. However, these constructs, including food addiction, disinhibition, hedonic hunger, emotional eating, binge eating and the like all have similar definitions, emphasizing loss of control over intake. As questionnaires measuring the constructs correlate strongly (r > 0.5) with each other, we propose that these constructs should be reconsidered to be part of a single broad phenotype: uncontrolled eating. Such an approach enables reviewing and meta-analysing evidence obtained with each individual questionnaire. Here, we describe robust associations between uncontrolled eating, body mass index (BMI), food intake, personality traits and brain systems. Reviewing cross-sectional and longitudinal data, we show that uncontrolled eating is phenotypically and genetically intertwined with BMI and food intake. We also review evidence on how three psychological constructs are linked with uncontrolled eating: lower cognitive control, higher negative affect and a curvilinear association with reward sensitivity. Uncontrolled eating mediates all three constructs' associations with BMI and food intake. Finally, we review and meta-analyse brain systems possibly subserving uncontrolled eating: namely, (i) the dopamine mesolimbic circuit associated with reward sensitivity, (ii) frontal cognitive networks sustaining dietary self-control and (iii) the hypothalamus-pituitary-adrenal axis, amygdala and hippocampus supporting stress reactivity. While there are limits to the explanatory and predictive power of the uncontrolled eating phenotype, we conclude that treating different eating-related constructs as a single concept, uncontrolled eating, enables drawing robust conclusions on the relationship between food intake and BMI, psychological variables and brain structure and function., (© 2019 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.)

Aims To understand processes placing individuals at risk for stimulant (amphetamine and cocaine) use disorder. Design Longitudinal study. Setting University of California, San Diego Department of Psychiatry, CA, USA. Participants Occasional stimulant users (OSU; n = 184) underwent a baseline clinical interview and a functional magnetic resonance imaging (fMRI) session. On the basis of a follow-up clinical interview completed 3 years later, OSU ( n = 147) were then categorized as problem stimulant users (PSU: n = 36; those who developed stimulant use disorders in the interim) or desisted stimulant users (DSU: n = 74; those who stopped using). OSU who did not meet criteria for PSU or DSU ( n = 37) were included in dimensional analyses. Measurements fMRI blood oxygen level-dependent (BOLD) contrast percentage signal change from baseline collected during a Paper-Scissors-Rock task was examined during three decision-making conditions, those resulting in: (1) wins, (2) ties and (3) losses. These data were used as dependent variables in categorical analyses comparing PSU and DSU, as well as dimensional analyses including interim drug use as predictors, controlling for baseline drug use. Findings PSU exhibited lower anterior cingulate, middle insula, superior temporal, inferior parietal, precuneus and cerebellum activation than DSU across all three conditions (significant brain clusters required > 19 neighboring voxels to exceed F(1,108) = 5.58, P < 0.01 two-tailed; all Cohen's d > 0.83). Higher interim marijuana use was linked to lower pre-central and superior temporal activation during choices resulting in wins (> 19 neighboring voxels to exceed t = 2.61, P < 0.01 two-tailed; R2 change > 0.11). Conclusions Individuals who transition from stimulant use to stimulant use disorder appear to show alterations in neural processing of stimulus valuation and outcome monitoring, patterns also evident in chronic stimulant use disorder. Attenuated anterior cingulate and insular processing may constitute a high-risk neural processing profile, which could be used to calculate risk scores for individuals experimenting with stimulants. [ABSTRACT FROM AUTHOR]

Cerebral small vessel disease (CSVD) is an important cause of stroke, cognitive impairment, and other diseases, and its early quantitative evaluation can significantly improve patient prognosis. Magnetic resonance imaging (MRI) is an important method to evaluate the occurrence, development, and severity of CSVD. However, the diagnostic process lacks quantitative evaluation criteria and is limited by experience, which may easily lead to missed diagnoses and misdiagnoses. With the development of artificial intelligence technology based on deep learning, the extraction of high-dimensional features in imaging can assist doctors in clinical decision-making, and it has been widely used in brain function and mental disorders, and cardiovascular and cerebrovascular diseases. This paper summarizes the global research results in recent years and briefly describes the application of deep learning in evaluating CSVD signs in MRI imaging, including recent small subcortical infarcts, lacunes of presumed vascular origin, vascular white matter hyperintensity, enlarged perivascular spaces, cerebral microbleeds, brain atrophy, cortical superficial siderosis, and cortical cerebral microinfarct., (© 2024 The Author(s). CNS Neuroscience & Therapeutics published by John Wiley & Sons Ltd.)

Tasks, tools, and techniques that we perform, use, and acquire, define the elements of expertise which we value as the hallmarks of goal‐driven behavior. Somehow, the creation of tools enables us to define new tasks, or is it that the envisioning of new tasks drives us to invent new tools? Or maybe it is that new tools engender new techniques which then result in new tasks? This jumble of issues will be explored and discussed in this diverse collection of papers. Individually, few of the papers are related to each other by topic or by techniques of analysis. Collectively, all focus on tasks performed using tools and discuss the techniques of tool use which enable differences in performance and expertise across individuals, societies, and (even) species. [ABSTRACT FROM AUTHOR]

In this paper, brain tumors are detected and diagnosed using machine learning approaches in brain magnetic resonance imaging (MRI), which has many real time clinical applications. Noise variations in brain images are detected and removed using index filter, which is proposed in this paper. Brain images devoid of noise content are in spatial domain format, which are not suitable for further feature extraction process. Hence, there is a need for converting all the spatial pixels into multi orientation pixels. In this paper, Gabor transform is used for spatial into multi oriented image conversion. The noise filtered images are transformed into multi orientation‐based brain image using Gabor transform method. Then, the hybrid features which are the integration of statistical and texture features (GLCM, gray level co‐occurrence matrix, and LDP, local derivative pattern), are computed from this transformed brain image. These computed features are classified using extreme machine learning (EML) approach, which categorizes the source brain image as normal or abnormal. Then, the segmented tumor regions are diagnosed using co‐active adaptive neuro fuzzy inference system (CANFIS) classifier, which classifies the segmented regions as mild or severe. The proposed tumor detection and diagnosis methods are applied and tested on the brain images which are available as open access dataset. The performance of the proposed brain tumor detection method is analyzed in terms of sensitivity, specificity, and accuracy with classification rate. [ABSTRACT FROM AUTHOR]

In this paper, an additive margin network with adaptive feature recalibration, AMNets, for handling a wide range of visual tasks, is proposed. The new AMNets consists of three improvements on convolutional neural networks: (1) squeeze‐and‐excitation mechanism was embedded into the the residual block of single layer to improve the performance of the classification, (2) softmax loss was replaced by the additive margin softmax loss to minimize intra‐class variance and maximize inter‐class variance, and (3) Adam optimizer was exploited to update iteratively the network parameters. Experiments on the Brain Stroke CT Image Dataset show that our additive margin network is quite effective to improve state‐of‐the‐art algorithms. Network algorithms have been extensively used in medical image field to pursuit a more accuracy of disease recognition. This paper proposes AMNets, an additive margin network with adaptive feature recalibration for handling a wide range of visual tasks in medicine. [ABSTRACT FROM AUTHOR]

The uncontrolled growth of cells in brain regions leads to the tumor regions and these abnormal tumor regions are scanned by magnetic resonance imaging (MRI) technique as an image. This paper proposes random forest classifier based Glioma brain tumor detection and segmentation methodology using feature optimization technique. The texture features are derived from brain MRI image and these derived feature set are now optimized by ant colony optimization algorithm. These optimized set of features are trained and classified using random forest classification method. This classifier classifies the brain MRI image into Glioma or non‐Glioma image based on the optimized set of features. Furthermore, energy‐based segmentation method is applied on the classified Glioma image for segmenting the tumor regions. The proposed methodology for Glioma brain tumor stated in this paper achieves 97.7% of sensitivity, 96.5% of specificity, and 98.01% of accuracy. [ABSTRACT FROM AUTHOR]

Abstract: Cognitive modeling is the effort to understand the mind by implementing theories of the mind in computer code, producing measures comparable to human behavior and mental activity. The community of cognitive modelers has traditionally met twice every 3 years at the International Conference on Cognitive Modeling (ICCM). In this special issue of topiCS, we present the best papers from the ICCM meeting. (The full proceedings are available on the ICCM website.) These best papers represent advances in the state of the art in cognitive modeling. Since ICCM was for the first time also held jointly with the Society for Mathematical Psychology, we use this preface to also reflect on the similarities and differences between mathematical psychology and cognitive modeling. [ABSTRACT FROM AUTHOR]

Alzheimer's disease, often known as dementia, is a severe neurodegenerative disorder that causes irreversible memory loss by destroying brain cells. People die because there is no specific treatment for this disease. Alzheimer's is most common among seniors 65 years and older. However, the progress of this disease can be reduced if it can be diagnosed earlier. Recently, artificial intelligence has instilled hope in the diagnosis of Alzheimer's disease by performing sophisticated analyses on extensive patient datasets, enabling the identification of subtle patterns that may elude human experts. Researchers have investigated various deep learning and machine learning models to diagnose this disease at an early stage using image datasets. In this paper, a new Deep learning (DL) methodology is proposed, where MRI images are fed into the model after applying various pre‐processing techniques. The proposed Alzheimer's disease detection approach adopts transfer learning for multi‐class classification using brain MRIs. The MRI Images are classified into four categories: mild dementia (MD), moderate dementia (MOD), very mild dementia (VMD), and non‐dementia (ND). The model is implemented and extensive performance analysis is performed. The finding shows that the model obtains 97.31% accuracy. The model outperforms the state‐of‐the‐art models in terms of accuracy, precision, recall, and F‐score. [ABSTRACT FROM AUTHOR]

Background: Right hemisphere communication disorders are neither consistently labelled nor adequately defined. Labels associated with right hemisphere brain damage (RHD) are broad and fail to capture the essence of communication challenges needed for stroke‐related service provisions. Determination of rehabilitation needs and best‐practice guidelines for the education, management and functional improvement of communication disorders after RHD are all predicated on an apt diagnostic label and disorder characteristics. Aims: In this paper apragmatism is proposed as a potential communication‐specific diagnostic label for the impairments in communication that occur after RHD. In particular, the researchers aimed: (1) to establish an operational definition of apragmatism; and (2) to describe the linguistic, paralinguistic and extralinguistic communication deficits under the umbrella term apragmatism. Methods & Procedures: An international collaborative of researchers with expertise in RHD followed a multilevel approach to consider the utility of apragmatism as a diagnostic label. Adopting the relational approach to concept mapping, the researchers engaged in a series of group meetings to complete four levels of mapping: (1) identify and review, (2) define, (3) expert discussion and (4) label determination. Main Contribution: Apragmatism was established as a suitable diagnostic label for the impairments in communication associated with RHD. The paper offers an operational definition and description of the linguistic, paralinguistic and extralinguistic features of apragmatism through evidence summaries and examples from people with RHD retrieved from the RHDBank. Conclusions & Implications: The adoption of the term apragmatism offers an opportunity to capture the hallmark of RHD communication deficits. The use of the term is recommended when referencing the pragmatic language impairments in this population. Apragmatism, which may co‐occur with or be exacerbated by cognitive impairments, can interfere with the ability to interpret and convey intended meaning and impact the lives of right hemisphere stroke survivors and their families. What this paper adds: What is already known on the subject: RHD results in a heterogeneous group of deficits that range in cognitive–communicative complexity. Many of the deficits are subsumed under pragmatics. For example, adults with RHD may demonstrate tangential or verbose communication, insensitivity to others' needs and feelings, prosodic changes, minimal gesture use and facial expression, and more. While descriptions of pragmatic impairments pervade the literature, there is no consistently used diagnostic label. The clinical consequences of this absence include difficulty with inter‐ and intra‐disciplinary communication about these patients, difficulty consolidating findings across research studies, and challenges in communicating about these pragmatic changes with patients, families and other stakeholders. What this paper adds to existing knowledge: The term apragmatism is proposed as a diagnostic label to consistently describe pragmatic communication changes after RHD. Apragmatism is characterized using three components of pragmatics: linguistic, paralinguistic and extralinguistic. Descriptions and examples of these three components are provided with supplemental transcripts retrieved from the RHDBank. What are the potential or actual clinical implications of this work?: Adoption of the term apragmatism by speech and language therapists and other medical and rehabilitation professionals has the potential to provide consistency in describing the abilities and challenges experienced by people following a right hemisphere stroke. Such improvements may help drive the development of evidence‐based assessments and treatments for this population. [ABSTRACT FROM AUTHOR]

The March 2024 issue of JCPP Advances features two neuroimaging studies that investigate links between early environmental risk factors for mental health problems, brain development and psychopathology in children and young adults. The papers provide new insights into how adverse environments and negative experiences in childhood increase risk for depression and mental health problems, and how this may or may not be mediated, or moderated, by individual differences in the brain. [ABSTRACT FROM AUTHOR]

Liver, an important regulator of metabolic homeostasis, is critical for healthy brain function. In particular, age‐related neurodegenerative diseases seriously reduce the quality of life for the elderly. As population aging progresses rapidly, unraveling the mechanisms that effectively delay aging has become critical. Appropriate exercise is reported to improve aging‐related cognitive impairment. Whereas current studies focused on exploring the effect of exercise on the aging brain itself, ignoring the persistent effects of peripheral organs on the brain through the blood circulation. The aim of this paper is to summarize the communication and aging processes of the liver and brain and to emphasize the metabolic mechanisms of the liver–brain axis about exercise ameliorating aging‐related neurodegenerative diseases. A comprehensive understanding of the potential mechanisms about exercise ameliorating aging is critical for improving adaptation to age‐related brain changes and formulating effective interventions against age‐related cognitive decline. [ABSTRACT FROM AUTHOR]

Background: Education outside the classroom (EOtC) is considered beneficial to children's physical and mental health. Especially, stress resilience has been linked to nature experience., Aims: This study experimentally explored the effects of pupils' autonomy support (AUT) and physical activity (PA) on their biological stress responses and brain development in EOtC., Sample: The study comprised 48 fifth and sixth graders., Methods: The intervention consisted of one day/week taught in a forest over one school year. Structural magnetic resonance imaging (MRI) was conducted at the beginning and the end of the school year, functional MRI under a stress condition at the end. Regions of interest were amygdala, hippocampus and the anterior cingulate cortex (ACC). All other measures were obtained at the beginning, at mid-term and at the end of the school year. PA was measured using accelerometry. Cortisol levels were obtained three times during the examined school days. AUT was measured with a paper-based survey. Data were analysed using Bayesian multivariate models., Results: EOtC students exhibit more efficient regulation of biological stress-reactivity and show a reduction of cortisol over the day associated with light PA in the forest. Cortisol is further associated with amygdala activation in the stress condition. Cerebral structural change is best explained by age; however, AUT has a positive direct effect on the maturation of the ACC, which is stronger in EOtC., Conclusions: Our results support the idea that autonomy supportive teaching fosters cerebral maturation and that EOtC can have a positive effect on biological stress regulation., (© 2022 The Authors. British Journal of Educational Psychology published by John Wiley & Sons Ltd on behalf of British Psychological Society.)

Purpose: To make an adaptable, head shaped radionuclide phantom to simulate molecular imaging of the brain using clinical acquisition and reconstruction protocols. This will allow the characterization and correction of scanner characteristics, and improve the accuracy of clinical image analysis, including the application of databases of normal subjects. Methods: A fused deposition modeling 3D printer was used to create a head shaped phantom made up of transaxial slabs, derived from a simulated MRI dataset. The attenuation of the printed polylactide (PLA), measured by means of the Hounsfield unit on CT scanning, was set to match that of the brain by adjusting the proportion of plastic filament and air (fill ratio). Transmission measurements were made to verify the attenuation of the printed slabs. The radionuclide distribution within the phantom was created by adding 99mTc pertechnetate to the ink cartridge of a paper printer and printing images of gray and white matter anatomy, segmented from the same MRI data. The complete subresolution sandwich phantom was assembled from alternate 3D printed slabs and radioactive paper sheets, and then imaged on a dual headed gamma camera to simulate an HMPAO SPECT scan. Results: Reconstructions of phantom scans successfully used automated ellipse fitting to apply attenuation correction. This removed the variability inherent in manual application of attenuation correction and registration inherent in existing cylindrical phantom designs. The resulting images were assessed visually and by count profiles and found to be similar to those from an existing elliptical PMMA phantom. Conclusions: The authors have demonstrated the ability to create physically realistic HMPAO SPECT simulations using a novel head-shaped 3D printed subresolution sandwich method phantom. The phantom can be used to validate all neurological SPECT imaging applications. A simple modification of the phantom design to use thinner slabs would make it suitable for use in PET. [ABSTRACT FROM AUTHOR]

The acquired immobility response during the "forced swim test (FST)" is not a rodent model of depression, but the test has some validity in predicting a compound's antidepressant potential. Nevertheless, 60% of the about 600 papers that were published annually the past 2 years label the rodent's immobility response as depression‐like behaviour, but the relative contribution per country is changing. When the Editors‐in‐Chief of 5 journals publishing most FST papers were asked for their point of view on labelling immobility as depression‐like behaviour and despair, they responded that they primarily rely on the reviewers regarding scientific merit of the submission. One Editor informs authors of the recent NIMH notice (https://grants.nih.gov/grants/guide/notice‐files/NOT‐MH‐19‐053.html) which encourages investigators to use animal models "for" addressing neurobiological questions rather than as model "of" specific mental disorders. The neurobiological questions raised by use of the FST fall in two categories. First, research on the role of endocrine and metabolic factors, with roots in the 1980s, and with focus on the bottom‐up action of glucocorticoids on circuits processing salient information, executive control and memory consolidation. Second, recent findings using novel technological and computational advances that have allowed great progress in charting top‐down control in the switch from active to passive coping with the inescapable stressor executed by neuronal ensembles of the medial prefrontal cortex via the peri‐aquaductal grey. It is expected that combining neural top‐down and endocrine bottom‐up approaches will provide new insights in the role of stress‐coping and adaptation in pathogenesis of mental disorders. [ABSTRACT FROM AUTHOR]

Magnetic resonance imaging (MRI) is becoming increasingly important in precision radiotherapy owing to its excellent soft‐tissue contrast and versatile scan options. Many recent advances in MRI have been shown to be promising for MRI‐guided radiotherapy and for improved treatment outcomes. This paper summarizes these advances into six sections: MRI simulators, MRI‐linear accelerator hybrid machines, MRI‐only workflow, four‐dimensional MRI, MRI‐based radiomics, and magnetic resonance fingerprinting. These techniques can be implemented before, during, or after radiotherapy for various precision radiotherapy applications, such as tumor delineation, tumor motion management, treatment adaptation, and clinical decision making. For each of these techniques, this paper describes its technical details and discusses its clinical benefits and challenges. [ABSTRACT FROM AUTHOR]

By employing a firm‐level linked employer–employee dataset for Danish manufacturing firms, this paper investigates whether offshoring is complementary to, or a substitute for, research and development (R&D) activities. Offshoring is instrumented with world export supply to circumvent the inherent endogenous nature of the firm's decision to offshore. Results suggest that firms with increased offshoring do in fact tend to engage in further R&D activities at home. Moreover, they also tend to reallocate R&D resources toward product R&D, possibly at the expense of process R&D. [ABSTRACT FROM AUTHOR]

How to collect relevance judgment has long been an important problem in Information Retrieval (IR). A popular method is to collect relevance judgment in a point‐wise manner, in which assessors examine and give an absolute relevance score for each item independently of the others. As an alternative, pair‐wise relevance judgment, also named preference judgment, allows an assessor to compare two items side‐by‐side and express their preference for one over the other. Previous work has explored the differences between these two paradigms of relevance judgments from many different aspects. Most of these works are conducted through explicit/implicit feedback. However, few works investigate the underlying neurological mechanisms of the two paradigms. In this paper, we conduct a lab study to investigate and compare point‐wise and pair‐wise relevance judgment in image search scenarios. We study the neurological mechanisms of the two paradigms through an event‐related potential (ERP) analysis of the users' brain signals while viewing images during a search process. We have obtained several observations, such as search engine users tend to pay more attention to preferred items in the point‐wise paradigm but unpreferred items in the pair‐wise paradigm. Furthermore, we test the adoption of brain signals as implicit feedback for predicting pair‐wise relevance judgment, highlighting the feasibility of leveraging brain signals to understand users' relevance judgments. [ABSTRACT FROM AUTHOR]

This article presents information on certain features of the short research papers presented at the interdisciplinary conference "Adolescent Brain Development: Vulnerabilities and Opportunities," which was held at The Lighthouse Conference Center in New York from September 18 to 20, 2003. It is informed that these research papers reflect on several research programs on adolescent vulnerabilities.

Depression is a serious public health problem, and adolescence is an 'age of risk' for the onset of Major Depressive Disorder. Recently, we and others have proposed neuroimmune network models that highlight bidirectional communication between the brain and the immune system in both mental and physical health, including depression. These models draw on research indicating that the cellular actors (particularly monocytes) and signaling molecules (particularly cytokines) that orchestrate inflammation in the periphery can directly modulate the structure and function of the brain. In the brain, inflammatory activity heightens sensitivity to threats in the cortico‐amygdala circuit, lowers sensitivity to rewards in the cortico‐striatal circuit, and alters executive control and emotion regulation in the prefrontal cortex. When dysregulated, and particularly under conditions of chronic stress, inflammation can generate feelings of dysphoria, distress, and anhedonia. This is proposed to initiate unhealthy, self‐medicating behaviors (e.g. substance use, poor diet) to manage the dysphoria, which further heighten inflammation. Over time, dysregulation in these brain circuits and the inflammatory response may compound each other to form a positive feedback loop, whereby dysregulation in one organ system exacerbates the other. We and others suggest that this neuroimmune dysregulation is a dynamic joint vulnerability for depression, particularly during adolescence. We have three goals for the present paper. First, we extend neuroimmune network models of mental and physical health to generate a developmental framework of risk for the onset of depression during adolescence. Second, we examine how a neuroimmune network perspective can help explain the high rates of comorbidity between depression and other psychiatric disorders across development, and multimorbidity between depression and stress‐related medical illnesses. Finally, we consider how identifying neuroimmune pathways to depression can facilitate a 'next generation' of behavioral and biological interventions that target neuroimmune signaling to treat, and ideally prevent, depression in youth and adolescents. [ABSTRACT FROM AUTHOR]

Several obstacles limit the efficacy of brain tumour treatment, most notably the blood‐brain barrier (BBB), which prevents the brain uptake of the majority of accessible medicines due to tight junctions. The presence of glutathione (GSH) receptors on the BBB surface has been demonstrated in numerous papers; consequently, products containing glutathione as a targeting ligand coupled with nanoliposomes are used to enhance drug delivery across the BBB. Here, the 5% pre‐inserted PEG2000‐GSH PEGylated liposomal doxorubicin was conducted according to 2B3‐101 being tested in clinical trials. In addition, PEGylated nanoliposomal doxorubicin connected to the spacer‐GSH targeting ligand (GSGGCE) and the PEG3400 was conducted using post‐insertion method. Next, in vivo biodistribution of the produced formulations was tested on healthy mice to see if GSGGCE, as the targeted ligand, could cross the BBB compared to 5% pre‐inserted PEG2000‐GSH and Caelyx®. Compared to the pre‐inserted formulation and Caelyx®, the post‐inserted formulations' concentration was lower in the heart and higher in brain tissues, resulting in boosting the brain concentration of accumulated doxorubicin with fewer possible side effects, including cardiotoxicity. In comparison to the pre‐insertion procedure, the post‐insertion method is easier, faster, and more cost‐effective. Moreover, employing PEG3400 and the post‐insertion approach in the PEG3400‐GSGGCE liposomal formulations was found to be effective in crossing the BBB. [ABSTRACT FROM AUTHOR]

Many aspects of chemistry and biology are mediated by electromagnetic field (EMF) interactions. The central nervous system (CNS) is particularly sensitive to EMF stimuli. Studies have explored the direct effect of different EMFs on the electrical properties of neurons in the last two decades, particularly focusing on the role of voltage‐gated ion channels (VGCs). This work aims to systematically review published evidence in the last two decades detailing the effects of EMFs on neuronal ion channels as per the PRISM guidelines. Following a predetermined exclusion and inclusion criteria, 22 papers were included after searches on three online databases. Changes in calcium homeostasis, attributable to the voltage‐gated calcium channels, were found to be the most commonly reported result of EMF exposure. EMF effects on the neuronal landscape appear to be diverse and greatly dependent on parameters, such as the field's frequency, exposure time, and intrinsic properties of the irradiated tissue, such as the expression of VGCs. Here, we systematically clarify how neuronal ion channels are particularly affected and differentially modulated by EMFs at multiple levels, such as gating dynamics, ion conductance, concentration in the membrane, and gene and protein expression. Ion channels represent a major transducer for EMF‐related effects on the CNS. [ABSTRACT FROM AUTHOR]

The determination of death by neurological criteria (brain death) is practiced in at least 80 countries, though it is a matter of continuing controversy. At the same time, the brain is central to human life, thinking, and behavior; however, a growing "neurocentrism" or a brain-focused image of human identity became established in most Western and in many non-Western societies and acts as a forceful ideology. This paper seeks a broader theoretical and sociocultural basis to approaching death bioethically by analyzing criticisms aimed at a neurologically focussed vision of human life, and then turning these towards the brain death criteria exposed to the criticism. The overall critique of the "neuro-self" has scope to offer alternative perspectives to the contested issues in brain-death criteria. Specifically, the paper examines two major shortcomings of a narrow brain view of life and culture. First, it considers the reduction of the individual to the brain: this is the crux of the neurological way of determining death, and is a way that is seemingly context-independent and culturally neutral. Second, it considers how dimensions of society and culture for humans are detached from the brain and have little impact on clinical practice and thinking in brain-death criteria; however, a deeper exploration reveals that they actually have direct relevance and that social and cultural factors have greater contributions to make to the current debates., (© 2022 John Wiley & Sons Ltd.)

To provide instructive clues for clinical practice and further research of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) infection, we analyzed the existing literature on viral neuroinvasion of SARS‐CoV‐2 in coronavirus disease 2019 (COVID‐19) patients. To date, SARS‐CoV‐2 has been detected in the cerebrospinal fluid (CSF) or brain parenchyma in quite a few patients, which provide undeniable evidence for the neuroinvasive potential of this novel coronavirus. In contrast with the cerebrum and cerebellum, the detection rate of SARS‐CoV‐2 was higher in the olfactory system and the brainstem, both of which also showed severe microgliosis and lymphocytic infiltrations. As compared with the number of patients who underwent viral testing in the central nervous system (CNS), the number of patients showing positive results seems very small. However, it seems too early to conclude that the neuroinvasion of SARS‐CoV‐2 is rare in COVID‐19 patients because the detection methods or sampling procedures in some studies may not be suitable or sufficient to reveal the CNS infection induced by neurotropic viruses. Moreover, the primary symptoms and/or causes of death were distinctly different among examined patients, which probably caused more conspicuous pathological changes than those due to the direct infection that usually localized to specific brain areas. Unfortunately, most autopsy studies did not provide sufficient details about neurological symptoms or suspected diagnoses of the examined patients, and the documentation of neuropathological changes was often incomplete. Given the complex pathophysiology of COVID‐19 and the characteristics of neurotropic viruses, it is understandable that any study of the CNS infection may inevitably have limitations. Highlights: We analyzed the papers on CSF testing and brain autopsies in COVID‐19 patients.SARS‐CoV‐2 has been detected in the CSF or brain parenchyma in a few patients.The detection rate of SARS‐CoV‐2 is high in the olfactory system and the brainstem.Some detection methods are not sufficient to reveal the CNS infection of SARS‐CoV‐2.Symptoms or death causes of examined patients are not often provided in some papers.It cannot be simply concluded that viral neuroinvasion is rare in COVID‐19 patients. [ABSTRACT FROM AUTHOR]

Ethical deliberations are unfolding for potentially controversial organoid‐entities such as brain organoids and embryoids. Much of the ethical deliberation centers on the questionable moral status of such organoid‐entities. However, while such work is important and appropriate, ethical deliberations may become too exclusively rooted in moral status and potentially overshadow other relevant moral dilemmas. The ethical discussion on organoid models can benefit from insights brought forth by both Judith Jarvis Thomson and Don Marquis in how they attempted to advance the abortion debate. To discuss other abortion ethical issues more fully, both Thomson and Marquis assumed differing moral status positions of the conceptus and followed lines of reasoning based on these moral status assumptions. We suggest a similar approach with controversial organoid‐entities like brain organoids and embryoids. To avoid overshadowing or overlooking other relevant ethical issues, ethicists ought to first assume an organoid‐entity moral status position (such as a high moral status or no moral status) and explore any possible arguments that may result from such a position. While we ought not to copy the content of Thomson and Marquis' arguments exactly for organoid‐entities, it is worthwhile to translate their arguments' overarching structures. This paper explores the relevant insights of Thomson and Marquis, how they can be translated into the organoid ethics debate, and what possible lines of inquiry may be worth exploring based on particular moral status assumptions. [ABSTRACT FROM AUTHOR]

Zebrafish brain imaging is very important for the study of brain disease and regeneration. We scanned the adult zebrafish brain before and after skull removal and monitored the recovery process of a head wound by polarization‐sensitive optical coherence tomography (PS‐OCT) in this paper. We analyzed the structure and polarization characteristics of the brain and skull in PS‐OCT images, and found their internal microstructure can be clearly identified with the polarization information. Further, we estimated the pigment distribution of the skull area and found that the density of pigment in skull is a critical factor of affecting zebrafish brain in vivo polarization imaging. Our results demonstrated that more features of brain can be displayed by introducing the polarization information, and proved high‐resolution PS‐OCT will play a great potential role in studying the zebrafish brain and skull. [ABSTRACT FROM AUTHOR]