Pain is often comorbid with emotional disorders such as anxiety and depression. Hyperexcitability of the anterior cingulate cortex has been implicated in pain and pain-related negative emotions that arise from impairments in inhibitory gamma-aminobutyric acid neurotransmission. This review primarily aims to outline the main circuitry (including the input and output connectivity) of the anterior cingulate cortex and classification and functions of different gamma-aminobutyric acidergic neurons; it also describes the neurotransmitters/neuromodulators affecting these neurons, their intercommunication with other neurons, and their importance in mental comorbidities associated with chronic pain disorders. Improving understanding on their role in pain-related mental comorbidities may facilitate the development of more effective treatments for these conditions. However, the mechanisms that regulate gamma-aminobutyric acidergic systems remain elusive. It is also unclear as to whether the mechanisms are presynaptic or postsynaptic. Further exploration of the complexities of this system may reveal new pathways for research and drug development.

A unified theory of emotion and motivation is updated in which motivational states are states in which instrumental goal-directed actions are performed to obtain anticipated rewards or avoid punishers, and emotional states are states that are elicited when the (conditioned or unconditioned) instrumental reward or punisher is or is not received. This advances our understanding of emotion and motivation, for the same set of genes and associated brain systems can define the primary or unlearned rewards and punishers such as a sweet taste or pain, and the brain systems that learn to expect rewards or punishers and that therefore produce motivational and emotional states. It is argued that instrumental actions under the control of the goal are important for emotion, because they require an intervening emotional state in which an action is learned or performed to obtain the goal, that is, the reward, or to avoid the punisher. The primate including human orbitofrontal cortex computes the reward value, and the anterior cingulate cortex is involved in learning the action to obtain the goal. In contrast, when the instrumental response is overlearned and becomes a habit with stimulus-response associations, emotional states may be less involved. In another route to output, the human orbitofrontal cortex has effective connectivity to the inferior frontal gyrus regions involved in language and provides a route for declarative reports about subjective emotional states to be produced. Reasoning brain systems provide alternative strategies to obtain rewards or avoid punishers and can provide different goals for action compared to emotional systems.

Percheron acute artery occlusion is a rare type of acute cerebral infarction.

An elderly male presented with sudden-onset near-memory and sensory impairments for 5 days. Upon admission, based on symptoms, signs, magnetic resonance imaging, and computed tomography findings, a diagnosis of Percheron syndrome was made. Subsequently, anti-platelet therapy, lipid-lowering treatment, cerebral circulation enhancement (such as the administration of calcium channel blockers to improve cerebral blood flow), and neurotrophic support (such as the use of drugs like citicoline to protect nerve cells) were immediately implemented, along with additional symptomatic treatments. The patient's symptoms were alleviated, following which he was discharged.

The diagnosis of acute occlusion of the Percheron artery requires rich clinical expertise and accurate imaging tools. Timely intervention and effective follow-up hold significant implications for optimizing patient recovery.

Though cortical changes in frontotemporal dementia (FTD) are well-documented, the cerebellum's role, closely linked to these areas, remains unclear.

To provide evidence on cerebellar involvement in FTD across clinical, genetic, imaging, neuropathological, and neurophysiological perspectives. Additionally, we sought evidence supporting the application of cerebellar non-invasive brain stimulation (NIBS) in FTD for both diagnostic and therapeutic purposes.

We performed a literature review using MEDLINE (via PubMed), Scopus, and Web of Science databases.

We emphasized the involvement of specific cerebellar regions which differentiate each FTD subtypes and may account for some of the characteristic symptoms. Furthermore, we highlighted peculiarities in FTD genetic alterations. Finally, we outlined neurophysiological evidence supporting a role for the cerebellum in FTD pathogenesis.

The cerebellum is critically involved in the FTD spectrum. Moreover, it can be speculated that cerebellar modulation, as already shown in other neurodegenerative disorders, could restore the interneuronal intracortical circuits typically impaired in FTD patients, providing clinical improvements and fundamental outcome measures in clinical trials.

A key question is how new semantic representations are formed in the human brain and how this may benefit from the hippocampal episodic memory system. Here, we describe the major effective connectivity between the hippocampal memory system and the anterior temporal lobe (ATL) semantic memory system in humans. Then, we present and model a theory of how semantic representations may be formed in the human ATL using slow associative learning in semantic attractor networks that receive inputs from the hippocampal episodic memory system. The hypothesis is that if one category of semantic representations is being processed for several seconds, then a slow short-term memory trace associative biologically plausible learning rule will enable all the components during that time to be associated together in a semantic attractor network. This benefits from the binding of components provided by the hippocampal episodic memory system. The theory is modeled in a four-layer network for view-invariant visual object recognition, followed by a semantic attractor network layer that utilizes a temporal trace associative learning rule to form semantic categories based on the inputs that occur close together in time, using inputs from the hippocampal system or from the world.

Key questions for understanding hippocampal function in memory and navigation in humans are the type and source of visual information that reaches the human hippocampus. We measured bidirectional pairwise effective connectivity with functional magnetic resonance imaging between 360 cortical regions while 956 Human Connectome Project participants viewed scenes, faces, tools, or body parts. We developed a method using deterministic dynamical graphs to define whole cortical networks and the flow in both directions between their cortical regions over timesteps after signal is applied to V1. We revealed that a ventromedial cortical visual "Where" network from V1 via the retrosplenial and medial parahippocampal scene areas reaches the hippocampus when scenes are viewed. A ventrolateral "What" visual cortical network reaches the hippocampus from V1 via V2-V4, the fusiform face cortex, and lateral parahippocampal region TF when faces/objects are viewed. There are major implications for understanding the computations of the human vs rodent hippocampus in memory and navigation: primates with their fovea and highly developed cortical visual processing networks process information about the location of faces, objects, and landmarks in viewed scenes, whereas in rodents the representations in the hippocampal system are mainly about the place where the individual is located and self-motion between places.

A growing body of evidence suggests that the link between the cardiac autonomic nervous system (ANS) and the central nervous system (CNS) is crucial to the onset and development of major depressive disorder (MDD), affecting perception, cognition, and emotional processing. The bottom-up heart-brain communication pathway plays a significant role in this process. Previous studies have shown that slow-frequency oscillations of peripheral signals (e.g., respiration, stomach) can influence faster neural activities in the CNS via phase-amplitude coupling (PAC). However, the understanding of heart-brain coupling remains limited. Additionally, while MDD patients exhibit altered brain activity patterns, little is known about how heart rate variability (HRV) affects brain oscillations. Therefore, we used PAC to investigate heart-brain coupling and its association with depression. We recorded MEG and ECG data from 55 MDD patients (35 females) and 52 healthy subjects (28 females) at rest and evaluated heart-brain PAC at a broadband level. The results showed that the low-frequency component of HRV (HRV-LF) significantly modulated MEG alpha power (10 Hz) in humans. Compared with the healthy group, the MDD group exhibited more extensive heart-brain coupling cortical networks, including the pars triangularis. LF-alpha coupling was observed in the bilateral insula in both groups. Notably, results revealed a significantly increased sympathetic-dominated HRV-LF modulation effect on left insula alpha oscillations, along with increased depressive severity. These findings suggest that MDD patients may attempt to regulate their internal state through enhanced heart-brain modulation, striving to restore normal physiological and psychological balance.

Irritable Bowel Syndrome (IBS) is a prevalent condition characterized by dysregulated brain-gut interactions. Despite its widespread impact, the brain mechanism of IBS remains incompletely understood, and there is a lack of objective diagnostic criteria and biomarkers. This study aims to investigate brain network alterations in IBS patients using the functional connectivity strength (FCS) method and to develop a support vector machine (SVM) classifier for distinguishing IBS patients from healthy controls (HCs).

Thirty-one patients with IBS and thirty age and sex-matched HCs were enrolled in this study and underwent resting-state functional magnetic resonance imaging (fMRI) scans. We applied FCS to assess global brain functional connectivity changes in IBS patients. An SVM-based machine - learning approach was then used to evaluate whether the altered FCS regions could serve as fMRI-based markers for classifying IBS patients and HCs.

Compared to the HCs, patients with IBS showed significantly increased FCS in the left medial orbitofrontal cortex (mOFC) and decreased FCS in the bilateral cingulate cortex/precuneus (PCC/Pcu) and middle cingulate cortex (MCC). The machine-learning model achieved a classification accuracy of 91.9% in differentiating IBS patients from HCs.

These findings reveal a unique pattern of FCS alterations in brain areas governing pain regulation and emotional processing in IBS patients. The identified abnormal FCS features have the potential to serve as effective biomarkers for IBS classification. This study may contribute to a deeper understanding of the neural mechanisms of IBS and aid in its diagnosis in clinical practice.

The aim of this study was to investigate the relationship between obesity (OB) progression and brain structural changes.

T1-weighted magnetic resonance images were acquired from 258 participants with overweight (OW) or OB and 74 participants with normal weight. Participants with OW or OB were divided into four groups according to BMI grades. Two-sample t tests compared disparities between the four subgroups and the participants with normal weight. We used causal structural covariance networks to examine the progressive impact of OB on brain structure.

With increasing BMI values, reductions in gray matter volume originated in the left caudate nucleus, medial orbitofrontal cortex, and left insula and expanded to the right hippocampus and left lateral orbitofrontal cortex and then to the right parahippocampal gyrus, left precuneus, and left dorsolateral prefrontal cortex (p < 0.05, false discovery rate corrected). The left caudate nucleus and medial orbitofrontal cortex are the primary hubs of the directional network, exhibiting positive causality to the right hippocampus and left dorsolateral prefrontal cortex. Moreover, the right hippocampus is identified as an important transition hub.

These findings suggest that changes in gray matter volume in individuals with OB may originate from reward/motivation processing regions, subsequently progressing to inhibitory control/learning memory regions, providing a new reference direction for clinical intervention and treatment of OB.

Inferring large-scale brain networks from functional magnetic resonance imaging (fMRI) provides more detailed and richer connectivity information, which is critical for gaining insight into brain structure and function and for predicting clinical phenotypes. However, as the number of network nodes increases, most existing methods suffer from the following limitations: (1) Traditional shallow models often struggle to estimate large-scale brain networks. (2) Existing deep graph structure learning models rely on downstream tasks and labels. (3) They rely on sparse postprocessing operations. To overcome these limitations, this paper proposes a novel framework for revealing large-scale functional brain connectivity networks through graph contrastive structure learning, called BGCSL.

Unlike traditional supervised graph structure learning methods, this framework does not rely on labeled information. It consists of two important modules: sparse graph structure learner and graph contrastive learning (GCL). It employs dynamic augmentation in GCL to train a sparse graph structure learner, enabling it to capture the intrinsic structure of the data.

We conducted extensive experiments on 12 synthetic datasets and 2 public functional magnetic resonance imaging datasets, demonstrating the effectiveness of our proposed framework. In the synthetic datasets, particularly in cases where node features are insufficient, BGCSL still maintains state-of-the-art performance. More importantly, on the ABIDE-I and HCP-rest datasets, BGCSL improved the downstream task performance of GCN-based models, including the original GCN, dGCN, and ContrastPool, to varying degrees.

Our proposed method holds significant potential as a valuable reference for future large-scale brain network estimation and representation and is conducive to supporting the exploration of more fine-grained biomarkers.

The human brain demonstrates an exceptional adaptability, which encompasses the ability to regulate emotions, exhibit cognitive flexibility, and generate behavioral responses, all supported by neuroplasticity. Brain-computer interfaces (BCIs) employ adaptive algorithms and machine learning techniques to adapt to variations in the user's brain activity, allowing for customized interactions with external devices. Older adults may experience cognitive decline, which could affect the ability to learn and adapt to new technologies such as BCIs, but both (human brain and BCI) demonstrate adaptability in their responses. The human brain is skilled at quickly switching between tasks and regulating emotions, while BCIs can modify signal-processing algorithms to accommodate changes in brain activity. Furthermore, the human brain and BCI participate in knowledge acquisition; the first one strengthens cognitive abilities through exposure to new experiences, and the second one improves performance through ongoing adjustment and improvement. Current research seeks to incorporate emotional states into BCI systems to improve the user experience, despite the exceptional emotional regulation abilities of the human brain. The implementation of BCIs for older adults could be more effective, inclusive, and beneficial in improving their quality of life. This review aims to improve the understanding of brain-machine interfaces and their implications for mental health in older adults.

Early-life adversity during pre- and early post-natal phases can impact brain development and lead to maladaptive changes in executive function related behaviors. This increases the risk for a range of psychopathologies and physical diseases. Importantly, exposure to adversities during these periods is also linked to alterations in the orbito-frontal cortex (OFC) which is a key player in these executive functions. The OFC thus appears to be a central node in this association between early life stress and disease risk. Gaining a clear, and detailed understanding of the association between early life stress, OFC function, and executive function, as well as the underlying mechanisms mediating this association is relevant to inform potential therapeutic interventions. In this paper, we begin by reviewing evidence linking early life adversities to 1) alterations in behaviors regulated by the OFC and 2) changes in OFC anatomy and function. We then present insights into the underlying mechanisms for these changes, stemming from early life adversity models, and highlight important future directions for this line of research.

We examined the long-term causal effects of an evidence-based parenting program delivered in infancy on children's emotion regulation and resting-state functional connectivity (rs-fc) during middle childhood. Families were referred to the study by Child Protective Services (CPS) as part of a diversion from a foster care program. A low-risk group of families was also recruited. CPS-involved families were randomly assigned to receive the target (Attachment and Biobehavioral Catch-up, ABC) or a control intervention (Developmental Education for Families, DEF) before infants turned 2. Both interventions were home-based, manualized, and 10-sessions long. During middle childhood, children underwent a 6-min resting-state functional MRI scan. Amygdala seed-based rs-fc analysis was completed with intervention group as the group-level predictor of interest. Fifty-seven children (NABC = 21; NDEF = 17; NCOMP = 19; Mage = 10.02 years, range = 8.08-12.14) were scanned successfully. The DEF group evidenced negative left amygdala↔OFC connectivity, whereas connectivity was near zero in the ABC and comparison groups (ABCvsDEF: Cohen's d = 1.17). ABC may enhance high-risk children's regulatory neurobiology outcomes ∼8 years after the intervention was completed.

The objective of this study was to investigate underlying mechanisms of long-term effective weight loss after laparoscopic sleeve gastrectomy (LSG) and effects on the medial orbitofrontal cortex (mOFC) and cognition.

A total of 18 individuals with obesity (BMI ≥ 30 kg/m2) underwent LSG. Clinical data, cognitive scores, and brain magnetic resonance imaging scans were evaluated before LSG and 12 months after LSG. We employed voxel-based morphometry analysis and seed-based resting-state functional connectivity (RSFC) analysis to assess LSG-induced structural and functional changes in mOFC. Partial correlation analysis and univariate and multivariate linear regression models were used to explore associations among biochemical indexes, neuroimaging, cognition, and weight loss.

No significant improvement in general cognition was found after LSG. Decreases in gray matter volume of the bilateral mOFC and increases in RSFC of the right mOFC were observed 12 months after LSG. Weight loss was associated with RSFC, general cognitive scores, and triglyceride changes. Multivariate linear regression model revealed gray matter volume of the left mOFC and working memory scores at baseline explained 55.2% of the variation in weight loss.

These findings suggest that mOFC imaging and cognitive scores could serve as biomarkers for predicting persistent weight loss after LSG, which provides a solid foundation for a potential target for neuromodulation research.

Bipolar disorder (BD), a severe neuropsychiatric condition, often appears during adolescence. Traditional diagnostic methods, which primarily rely on clinical interviews and single-modal magnetic resonance imaging (MRI) techniques, may have limitations in accuracy. This study aimed to improve adolescent BD diagnosis by integrating behavioral assessments with multimodal MRI. We hypothesized that this combination would enhance diagnostic accuracy for at-risk adolescents.

A retrospective cohort of 309 participants, including patients with BD, offspring of patients with BD (with and without subthreshold symptoms), non-BD offspring with subthreshold symptoms, and healthy control participants, was analyzed. Behavioral attributes were integrated with MRI features from T1-weighted, resting-state functional MRI, and diffusion tensor imaging. Three diagnostic models were developed using GLMNET multinomial regression: a clinical diagnosis model based on behavioral attributes, an MRI-based model, and a comprehensive model integrating both datasets.

The comprehensive model achieved a prediction accuracy of 0.83 (95% CI, 0.72-0.92), significantly higher than the clinical (0.75) and MRI-based (0.65) models. Validation with an external cohort showed high accuracy (0.89, area under the curve = 0.95). Structural equation modeling revealed that clinical diagnosis (β = 0.487, p < .0001), parental BD history (β = -0.380, p < .0001), and global function (β = 0.578, p < .0001) significantly affected brain health, while psychiatric symptoms showed only a marginal influence (β = -0.112, p = .056).

This study highlights the value of integrating multimodal MRI with behavioral assessments for early diagnosis in at-risk adolescents. Combining neuroimaging enables more accurate patient subgroup distinctions, facilitating timely interventions and improving health outcomes. Our findings suggest a paradigm shift in BD diagnostics, advocating for incorporating advanced imaging techniques in routine evaluations.

Bipolar disorder (BD) involves altered reward processing and decision-making, with inconsistencies across studies. Here, we integrated hierarchical Bayesian modelling with magnetoencephalography (MEG) to characterise maladaptive belief updating in this condition. First, we determined if previously reported increased learning rates in BD stem from a heightened expectation of environmental changes. Additionally, we examined if this increased expectation speeds up belief updating in decision-making, associated with modulation of rhythmic neural activity within the prefrontal, orbitofrontal, and anterior cingulate cortex (PFC, OFC, ACC). Twenty-two euthymic BD and 27 healthy control (HC) participants completed a reward-based motor decision-making task in a volatile setting. Hierarchical Bayesian modelling revealed BD participants anticipated greater environmental volatility, resulting in a more stochastic mapping from beliefs to actions and paralleled by lower win rates and a reduced tendency to repeat rewarded actions than HC. Despite this, BD individuals adjusted their expectations of action-outcome contingencies more slowly, but both groups invigorated their actions similarly. On a neural level, while healthy individuals exhibited an alpha-beta suppression and gamma increase during belief updating, BD participants showed dampened effects, extending across the PFC, OFC, and ACC regions. This was accompanied by an abnormally increased beta-band directed information flow in BD. Overall, the results suggest euthymic BD individuals anticipate environmental change without adequately learning from it, contributing to maladaptive belief updating. Alterations in frequency-domain amplitude and functional connectivity within the PFC, OFC, and ACC during belief updating underlie the computational effects and could serve as potential indicators for predicting relapse in future research.

To investigate the alterations in spontaneous brain activity and the similarities and differences between monocular deprivation amblyopia and binocular deprivation amblyopia.

Twenty children with binocular deprivation amblyopia, 26 children with monocular deprivation amblyopia and 20 healthy controls underwent resting-state functional magnetic resonance imaging. The evaluation of altered spontaneous brain activity was conducted using fractional amplitude of low-frequency fluctuations (fALFF). One-way analysis of variance was employed to analyze fALFF values among the three groups. Additionally, the relationship between fALFF values and best corrected visual acuity (BCVA) was analyzed via correlation analysis.

Compared to healthy controls, children with binocular deprivation amblyopia presented increased fALFF values in the left medial superior frontal gyrus, left middle frontal gyrus, left anterior cingulate cortex, left postcentral gyrus and bilateral precentral gyrus, and decreased fALFF values in the right fusiform gyrus. Compared to healthy controls, children with monocular deprivation amblyopia presented increased fALFF values in the right lingual gyrus, right superior frontal gyrus, right middle frontal gyrus, left superior temporal gyrus, triangular part of the left inferior frontal gyrus and bilateral middle temporal gyrus, and decreased fALFF values in the right precuneus. Compared with monocular deprivation amblyopia, fALFF values of binocular deprivation amblyopia were decreased in the triangular part of the left inferior frontal gyrus, right lingual gyrus and right cuneus, and increased in the left precentral gyrus and left postcentral gyrus. No significant correlations were found between the fALFF values of identified regions and the BCVA of amblyopic eyes for either type of amblyopia.

Children with deprivation amblyopia presented alterations in spontaneous activity in multiple brain regions, and these alterations differed between monocular amblyopia and binocular amblyopia. These abnormal spontaneous activities may reflect dysfunctions and compensation related to amblyopia.

Chronic cortisol overexposure plays a significant role in the development of neuropathological changes associated with neuropsychiatric and neurodegenerative disorders. The hippocampus, the primary target of cortisol, may exhibit characteristic regional responses due to its internal heterogeneity. In this study, we explored structural and functional alterations of hippocampal (HP) subfields in Cushing's disease (CD), an endogenous model of chronic cortisol overexposure.

Utilizing structural and resting-state functional magnetic resonance imaging data from 169 participants (86 patients with CD and 83 healthy control participants [HCs]) recruited from a single center, we investigated specific structural changes in HP subfields and explored the functional connectivity alterations driven by these structural abnormalities. We also analyzed potential associative mechanisms between these changes and biological attributes, neuropsychiatric representations, cognitive function, and gene expression profiles.

Compared with HCs, patients with CD exhibited significant bilateral volume reductions in multiple HP subfields. Notably, volumetric decreases in the left HP body and tail subfields were significantly correlated with cortisol levels, Montreal Cognitive Assessment scores, and quality of life measures. Disrupted connectivity between the structurally abnormal HP subfields and the ventromedial prefrontal cortex may impair reward-based decision making and emotional regulation, with this dysconnectivity being linked to structural changes in right HP subfields. Another region that exhibited dysconnectivity was located in the left pallidum and putamen. Gene expression patterns associated with synaptic components may underlie these macrostructural alterations.

Our findings elucidate the subfield-specific effects of chronic cortisol overexposure on the hippocampus, enhancing understanding of shared neuropathological traits linked to cortisol dysregulation in neuropsychiatric and neurodegenerative disorders.

Two key series of discoveries about the hippocampus are described. One is the discovery of hippocampal spatial view cells in primates. This discovery opens the way to a much better understanding of human episodic memory, for episodic memory prototypically involves a memory of where people or objects or rewards have been seen in locations "out there" which could never be implemented by the place cells that encode the location of a rat or mouse. Further, spatial view cells are valuable for navigation using vision and viewed landmarks, and provide for much richer, vision-based, navigation than the place to place self-motion update performed by rats and mice who live in dark underground tunnels. Spatial view cells thus offer a revolution in our understanding of the functions of the hippocampus in memory and navigation in humans and other primates with well-developed foveate vision. The second discovery describes a computational theory of the hippocampal-neocortical memory system that includes the only quantitative theory of how information is recalled from the hippocampus to the neocortex. It is shown how foundations for this research were the discovery of reward neurons for food reward, and non-reward, in the primate orbitofrontal cortex, and representations of value including of monetary value in the human orbitofrontal cortex; and the discovery of face identity and face expression cells in the primate inferior temporal visual cortex and how they represent transform-invariant information. This research illustrates how in order to understand a brain computation, a whole series of integrated interdisciplinary discoveries is needed to build a theory of the operation of each neural system.

Anticipatory brain activity makes it possible to predict the occurrence of expected situations. However, events such as traffic accidents are statistically unpredictable and can generate catastrophic consequences. This study investigates the brain activity and effective connectivity associated with anticipating and processing such unexpected, unavoidable accidents. We asked 161 participants to ride a motorcycle simulator while recording their electroencephalographic activity. Of these, 90 participants experienced at least one accident while driving. We conducted both within-subjects and between-subjects comparisons. During the pre-accident period, the right inferior parietal lobe (IPL), left anterior cingulate cortex (ACC), and right insula showed higher activity in the accident condition. In the post-accident period, the bilateral orbitofrontal cortex, right IPL, bilateral ACC, and middle and superior frontal gyrus also showed increased activity in the accident condition. We observed greater effective connectivity within the nodes of the limbic network (LN) and between the nodes of the attentional networks in the pre-accident period. In the post-accident period, we also observed greater effective connectivity between networks, from the ventral attention network (VAN) to the somatomotor network and from nodes in the visual network, VAN, and default mode network to nodes in the frontoparietal network, LN, and attentional networks. This suggests that activating salience-related processes and emotional processing allows the anticipation of accidents. Once an accident has occurred, integration and valuation of the new information takes place, and control processes are initiated to adapt behavior to the new demands of the environment.

Autism spectrum disorder (ASD) has proven to be highly enigmatic due to the diversity of its underlying genetic causes and the huge variability in symptom presentation. Uncovering common phenotypes across people with ASD and pre-clinical models allows us to better understand the influence on brain function of the many different genetic and cellular processes thought to contribute to ASD aetiology. One such feature of ASD is the convergent evidence implicating abnormal functioning of the medial prefrontal cortex (mPFC) across studies. The mPFC is a key part of the 'social brain' and may contribute to many of the changes in social behaviour observed in people with ASD. Here we review recent evidence for mPFC involvement in both ASD and social behaviours. We also highlight how pre-clinical mouse models can be used to uncover important cellular and circuit-level mechanisms that may underly atypical social behaviours in ASD. This article is part of the Special Issue on "PFC circuit function in psychiatric disease and relevant models".

The study of brain gyrification may provide useful information on the cytoarchitecture and connectivity of the brain. One of the methods that have been developed to estimate brain gyrification, known as surface ratio (SR), has not yet been studied in schizophrenia. Here we aimed to assess whether SR could provide new insights on the brain structure of schizophrenia patients and the severity of symptoms. We also computed a more established brain gyrification measure, namely absolute mean curvature (AMC). We analyzed 63 magnetic resonance images, 25 from schizophrenia patients with treatment-resistant auditory verbal hallucinations (SCH-H), 18 from schizophrenia patients without hallucinations (SCH-NH), and 20 from healthy controls (HC). The SR measure revealed that SCH-H patients had a more folded orbitofrontal cortex than SCH-NH patients and HC. Gyrification in this region was also negatively associated with positive symptoms, specifically with the delusions and conceptual disorganization items, only in the SCH-H group. Regarding the AMC measure, we identified two areas where HC showed more gyrification than SCH-H patients, but no relationships arose with symptoms. The hypergyrification of the orbitofrontal cortex displayed by SCH-H patients, as captured by the SR measure, suggests aberrant and/or excessive wiring in these patients, which in turn could give rise to auditory verbal hallucinations. Alternatively, we comment on potential compensatory mechanisms that may better explain the negative association between orbitofrontal gyrification and positive symptomatology. The SR measure captured the most relevant differences and associations, making it a promising biomarker in schizophrenia.

A key question for understanding the function of the hippocampus in memory is how information is recalled from the hippocampus to the neocortex. This was investigated in a neuronal network model of the hippocampal system in which "What" and "Where" neuronal firing rate vectors were applied to separate neocortical modules, which then activated entorhinal cortex "What" and "Where" modules, then the dentate gyrus, then CA3, then CA1, then the entorhinal cortex, and then the backprojections to the neocortex. A rate model showed that the whole system could be trained to recall "Where" in the neocortex from "What" applied as a retrieval cue to the neocortex, and could in principle be trained up towards the theoretical capacity determined largely by the number of synapses onto any one neuron divided by the sparseness of the representation. The trained synaptic weights were then imported into an integrate-and-fire simulation of the same architecture, which showed that the time from presenting a retrieval cue to a neocortex module to recall the whole memory in the neocortex is approximately 100 ms. This is sufficiently fast for the backprojection synapses to be trained onto the still active neocortical neurons during storage of the episodic memory, and this is needed for recall to operate correctly to the neocortex. These simulations also showed that the long loop neocortex-hippocampus-neocortex that operates continuously in time may contribute to complete recall in the neocortex; but that this positive feedback long loop makes the whole dynamical system inherently liable to a pathological increase in neuronal activity. Important factors that contributed to stability included increased inhibition in CA3 and CA1 to keep the firing rates low; and temporal adaptation of the neuronal firing and of active synapses, which are proposed to make an important contribution to stabilizing runaway excitation in cortical circuits in the brain.

With the increased availability and sophistication of digital devices in the last decade, young people have become mainstream mobile phone users. Heavy mobile phone dependence causes affective problems (depression, anxiety) and loss of attention on current activities, leading to more cluttered thoughts. Problematic mobile phone use has been found to increase the occurrence of mind wandering, but the neural mechanism underlying this relationship remains unclear. The current study aims to investigate the neural mechanism between mobile phone use and mind wandering. University students from datasets (ongoing research project named Gene-Brain-Behavior project, GBB) completed psychological assessments of mobile phone addiction and mind wandering and underwent resting-state functional connectivity (FC) scanning. FC matrix was constructed to further conduct correlation and mediation analyses. Students with high mobile phone addiction scores were more likely to have high mind wandering scores. FC among the default mode, motor, frontoparietal, basal ganglia, limbic, medial frontal, visual association, and cerebellar networks formed the neural basis of mind wandering. FC between the frontoparietal and motor networks, between the default mode network and cerebellar network, and within the cerebellar network mediated the relationship between mobile phone addiction and mind wandering. The findings confirm that mobile phone addiction is a risk factor for increased mind wandering and reveal that FC in several brain networks underlies this relationship. They contribute to research on behavioral addiction, education, and mental health among young adults.

Different cortical systems to the hippocampus were activated using fMRI during different types of episodic memory task. For object with scene location episodic memory, the activations were high in cortical systems involved in spatial processing, including the ventromedial visual and medial parahippocampal system. These activations for the medial parahippocampal system were higher in the right hemisphere. The activations in the face and object processing ventrolateral visual cortical stream regions FFC, PIT, V8 and TE2p were higher in the object-location in scene task than the reward-location task, and were higher in the right hemisphere. For reward-location in scene episodic memory, activations were also high in the ventromedial visual cortical spatial stream to the hippocampus, but were also selectively high in storage in key reward cortical regions (ventromedial prefrontal 10r, 10v, 10d; pregenual anterior cingulate d32, p24, p32, s32; and medial orbitofrontal cortex reward-related pOFC, 11l, OFC). For word-pair episodic memory, activations were lower in the ventromedial visual and medial parahippocampal spatial cortical stream, and were higher in language-related regions in Broca's area (44, 45, 47l), and were higher in the left hemisphere for these regions and for the many highly connected inferior frontal gyrus regions in the left hemisphere. Further, effective connectivity analyses during the episodic memory tasks showed that the direction of connectivity for these systems was from early visual cortical regions V2-V4 to the ventromedial visual cortical regions VMV1-3 and VVC for spatial scene processing; was from the pregenual anterior cingulate and orbitofrontal cortex reward systems to the hippocampal system; and was from the FFC/V8/PIT system to TE2p in the visual inferior temporal visual cortex, which has connectivity to lateral parahippocampal TF, which in turn has forward effective connectivity to the hippocampus.

Sarcopenia presenting a critical challenge in population-aging healthcare. The elucidation of the interplay between brain structure and sarcopenia necessitates further research. The aim of this study is to explore the casual association between brain structure and sarcopenia. Linkage disequilibrium score regression (LDSC) was conducted to estimate the genetic correlations; MR was then performed to explore the causal relationship between Brain imaging-derived phenotypes (BIDPs) and three sarcopenia-related traits: handgrip strength, walking pace, and appendicular lean mass (ALM). The main analyses were conducted using the inverse-variance weighted method. Moreover, weighted median and MR-Egger were conducted as sensitivity analyses. Genetic association between 6.41% of BIDPs and ALM was observed, and 4.68% of BIDPs exhibited causal MR association with handgrip strength, 2.11% of BIDPs were causally associated with walking pace, and 2.04% of BIDPs showed causal association with ALM. Volume of ventromedial hypothalamus was associated with increased odds of handgrip strength (OR: 1.18, 95% CI: 1.02 to 1.37) and ALM (OR: 1.05, 95% CI: 1.01 to 1.09). Mean thickness of G-pariet-inf-Angular was associated with decreased odds of handgrip strength (OR: 0.83, 95% CI: 0.70 to 0.97) and walking pace (OR: 0.97, 95% CI: 0.93 to 0.99). As part of the brain structure forward causally influences sarcopenia, which may provide new perspectives for the prevention of sarcopenia and offer valuable insights for further research on the brain-muscle axis.

Resting-state functional magnetic resonance imaging (fMRI) investigations have provided a view of the default network (DN) as composed of a specific set of frontal, parietal, and temporal cortical regions. This spatial topography is typically defined with reference to an influential network parcellation scheme that designated the DN as one of seven large-scale networks (Yeo et al., 2011). However, the precise functional organization of the DN is still under debate, with studies arguing for varying subnetwork configurations and the inclusion of subcortical regions. In this vein, the so-called limbic network-defined as a distinct large-scale network comprising the bilateral temporal poles, ventral anterior temporal lobes, and orbitofrontal cortex-is of particular interest. A large multi-modal and multi-species literature on the anatomical, functional, and cognitive properties of these regions suggests a close relationship to the DN. Notably, these regions have poor signal quality with conventional fMRI acquisition, likely obscuring their network affiliation in most studies. Here, we leverage a multi-echo fMRI dataset with high temporal signal-to-noise and whole-brain coverage, including orbitofrontal and anterior temporal regions, to examine the large-scale network resting-state functional connectivity of these regions and assess their associations with the DN. Consistent with our hypotheses, our results support the inclusion of the majority of the orbitofrontal and anterior temporal cortex as part of the DN and reveal significant heterogeneity in their functional connectivity. We observed that left-lateralized regions within the temporal poles and ventral anterior temporal lobes, as well as medial orbitofrontal regions, exhibited the greatest resting-state functional connectivity with the DN, with heterogeneity across DN subnetworks. Overall, our findings suggest that, rather than being a functionally distinct network, the orbitofrontal and anterior temporal regions comprise part of a larger, extended default network.

Resilience to emotional disorders is critical for adolescent mental health, especially following childhood abuse. Yet, brain signatures of resilience remain undetermined due to the differential susceptibility of the brain's emotion processing system to environmental stresses. Analyzing brain's responses to angry faces in a longitudinally large-scale adolescent cohort (IMAGEN), we identified two functional networks related to the orbitofrontal and occipital regions as candidate brain signatures of resilience. In girls, but not boys, higher activation in the orbitofrontal-related network was associated with fewer emotional symptoms following childhood abuse, but only when the polygenic burden for depression was high. This finding defined a genetic-dependent brain (GDB) signature of resilience. Notably, this GDB signature predicted subsequent emotional disorders in late adolescence, extending into early adulthood and generalizable to another independent prospective cohort (ABCD). Our findings underscore the genetic modulation of resilience-brain connections, laying the foundation for enhancing adolescent mental health through resilience promotion.

The occurrence mechanism of intracerebral hemorrhage remains unclear. Several recent studies have highlighted the close relationship between environmental senses and intracerebral hemorrhage, but the mechanisms of causal mediation are inconclusive. We aimed to investigate the causal relationships and potential mechanisms between environmental senses and intracerebral hemorrhage. Multiple Mendelian randomization methods were used to identify a causal relationship between environmental senses and intracerebral hemorrhage. Gut microbiota and brain imaging phenotypes were used to find possible mediators. Enrichment and molecular interaction analyses were used to identify potential mediators and molecular targets. No causal relationship between temperature and visual perception with intracerebral hemorrhage was found, whereas long-term noise was identified as a risk factor for intracerebral hemorrhage (OR 2.95, 95% CI: 1.25 to 6.93, PIVW = 0.01). The gut microbiota belonging to the class Negativicutes and the order Selenomonadales and the brain image-derived phenotypes ICA100 node 54, edge 803, edge 1149, and edge 1323 played mediating roles. "Regulation of signaling and function in synaptic organization" is the primary biological pathway of noise-induced intracerebral hemorrhage, and ARHGAP22 may be the critical gene. This study emphasized the importance of environmental noise in the prevention, disease management, and underlying biological mechanisms of intracerebral hemorrhage.

Table tennis training has been employed as an exercise treatment to enhance cognitive brain functioning in patients with mental illnesses. However, research on its underlying mechanisms remains limited. In this study, we investigated functional and structural changes in large-scale brain regions between 20 table tennis players (TTPs) and 21 healthy controls (HCs) using 7-Tesla magnetic resonance imaging (MRI) techniques. Compared with those of HCs, TTPs exhibited significantly greater fractional anisotropy (FA) and axial diffusivity (AD) values in multiple fiber tracts. We used the locations with the most significant structural changes in white matter as the seed areas and then compared static and dynamic functional connectivity (sFC and dFC). Brodmann 11, located in the orbitofrontal cortex, showed altered dFC values to large-scale brain regions, such as the occipital lobe, thalamus, and cerebellar hemispheres, in TTPs. Brodmann 48, located in the temporal lobe, showed altered dFC to the parietal lobe, frontal lobe, cerebellum, and occipital lobe. Furthermore, the AD values of the forceps minor (Fmi) and right anterior thalamic radiations (ATRs) were negatively correlated with useful field of view (UFOV) test scores in TTPs. Our results suggest that table tennis players exhibit a unique pattern of dynamic neural activity, this provides evidence for potential mechanisms through which table tennis interventions can enhance attention and other cognitive functions.

Teratological research shows that both prenatal stress and prenatal substance exposure have a significant impact on neurodevelopmental outcomes in children. Using human research, the purpose of this narrative review is to explore the degree to which these exposures may represent complex prenatal and postnatal risks for the development of cognition and behavior in children. An understanding of the HPA axis and its function during pregnancy as well as the types and operationalization of prenatal stress provide a context for understanding the direct and indirect mechanisms by which prenatal stress affects brain and behavior development. In turn, prenatal substance exposure studies are evaluated for their importance in understanding variables that indicate a potential interaction with prenatal stress including reactivity to novelty, arousal, and stress reactivity during early childhood. The similarities and differences between prenatal stress exposure and prenatal substance exposure on neurodevelopmental outcomes including arousal and emotion regulation, cognition, behavior, stress reactivity, and risk for psychopathology are summarized. Further considerations for teratological studies of prenatal stress and/or substance exposure include identifying and addressing methodological challenges, embracing the complexity of pre-and postnatal environments in the research, and the importance of incorporating parenting and resilience into future studies.

The primate including the human hippocampus implicated in episodic memory and navigation represents a spatial view, very different from the place representations in rodents. To understand this system in humans, and the computations performed, the pathway for this spatial view information to reach the hippocampus was analysed in humans. Whole-brain effective connectivity was measured with magnetoencephalography between 30 visual cortical regions and 150 other cortical regions using the HCP-MMP1 atlas in 21 participants while performing a 0-back scene memory task. In a ventromedial visual stream, V1-V4 connect to the ProStriate region where the retrosplenial scene area is located. The ProStriate region has connectivity to ventromedial visual regions VMV1-3 and VVC. These ventromedial regions connect to the medial parahippocampal region PHA1-3, which, with the VMV regions, include the parahippocampal scene area. The medial parahippocampal regions have effective connectivity to the entorhinal cortex, perirhinal cortex, and hippocampus. In contrast, when viewing faces, the effective connectivity was more through a ventrolateral visual cortical stream via the fusiform face cortex to the inferior temporal visual cortex regions TE2p and TE2a. A ventromedial visual cortical 'Where' stream to the hippocampus for spatial scenes was supported by diffusion topography in 171 HCP participants at 7 T.

The cingulate gyrus (CG), a brain structure above the corpus callosum, is recognised as part of the limbic system and plays numerous vital roles. However, its full functional capacity is yet to be understood. In recent years, emerging evidence from imaging modalities, supported by electrical cortical stimulation (ECS) findings, has improved our understanding. To our knowledge, there is a limited number of systematic reviews of the cingulate function studied by ECS. We aim to parcellate the CG by reviewing ECS studies.

We searched PubMed and Embase for studies investigating CG using ECS. A total of 30 studies met the inclusion criteria. We evaluated the ECS responses across the cingulate subregions and summarised the reported findings.

We included 30 studies (totalling 887 patients, with a mean age of 31.8±9.8 years). The total number of electrodes implanted within the cingulate was 3028 electrode contacts; positive responses were obtained in 941 (31.1%, median percentages, 32.3%, IQR 22.2%-64.3%). The responses elicited from the CG were as follows. Simple motor (8 studies, 26.7 %), complex motor (10 studies, 33.3%), gelastic with and without mirth (7 studies, 23.3%), somatosensory (9 studies, 30%), autonomic (11 studies, 36.7 %), psychic (8 studies, 26.7%) and vestibular (3 studies, 10%). Visual and speech responses were also reported. Despite some overlap, the results indicate that the anterior cingulate cortex is responsible for most emotional, laughter and autonomic responses, while the middle cingulate cortex controls most complex motor behaviours, and the posterior cingulate cortex (PCC) regulates visual, among various other responses. Consistent null responses have been observed across different regions, emphasising PCC.

Our results provide a segmental mapping of the functional properties of CG, helping to improve precision in the surgical planning of epilepsy.

Cerebral small vessel disease (CSVD) is a prevalent vascular disorder that has been consistently associated with vascular cognitive impairment (VCI). The diagnosis of CSVD continues to rely on magnetic resonance imaging (MRI). Epidemiological data indicate that the characteristic MRI features of CSVD, including white matter hyperintensity (WMH) and lacunar infarction, are very common among individuals over 40 years of age in community studies. This prevalence poses a significant burden on many low- and middle-income families. The amygdala plays a crucial role in integrating sensory and associative information to regulate emotional cognition. Although many previous studies have linked alterations in the amygdala to various diseases, such as depression, there has been little research on CSVD-associated alterations in the amygdala due to the complexity of CSVD. In this paper, we summarize the various imaging features of CSVD and discuss the correlation between amygdala changes and VCI. We also explore how new neuroimaging methods can assess amygdala changes early, laying a foundation for future comprehensive exploration of the pathogenesis of CSVD.

We develop further here the only quantitative theory of the storage of information in the hippocampal episodic memory system and its recall back to the neocortex. The theory is upgraded to account for a revolution in understanding of spatial representations in the primate, including human, hippocampus, that go beyond the place where the individual is located, to the location being viewed in a scene. This is fundamental to much primate episodic memory and navigation: functions supported in humans by pathways that build 'where' spatial view representations by feature combinations in a ventromedial visual cortical stream, separate from those for 'what' object and face information to the inferior temporal visual cortex, and for reward information from the orbitofrontal cortex. Key new computational developments include the capacity of the CA3 attractor network for storing whole charts of space; how the correlations inherent in self-organizing continuous spatial representations impact the storage capacity; how the CA3 network can combine continuous spatial and discrete object and reward representations; the roles of the rewards that reach the hippocampus in the later consolidation into long-term memory in part via cholinergic pathways from the orbitofrontal cortex; and new ways of analysing neocortical information storage using Potts networks.

Recent work has identified a critical role for the hippocampus in reward-sensitive behaviors, including motivated memory, reinforcement learning, and decision-making. Animal histology and human functional neuroimaging have shown that brain regions involved in reward processing and motivation are more interconnected with the ventral/anterior hippocampus. However, direct evidence examining gradients of structural connectivity between reward regions and the hippocampus in humans is lacking. The present study used diffusion MRI (dMRI) and probabilistic tractography to quantify the structural connectivity of the hippocampus with key reward processing regions in vivo. Using a large sample of subjects (N = 628) from the human connectome dMRI data release, we found that connectivity profiles with the hippocampus varied widely between different regions of the reward circuit. While the dopaminergic midbrain (ventral tegmental area) showed stronger connectivity with the anterior versus posterior hippocampus, the ventromedial prefrontal cortex showed stronger connectivity with the posterior hippocampus. The limbic (ventral) striatum demonstrated a more homogeneous connectivity profile along the hippocampal long axis. This is the first study to generate a probabilistic atlas of the hippocampal structural connectivity with reward-related networks, which is essential to investigating how these circuits contribute to normative adaptive behavior and maladaptive behaviors in psychiatric illness. These findings describe nuanced structural connectivity that sets the foundation to better understand how the hippocampus influences reward-guided behavior in humans.

Connectivity maps are now available for the 360 cortical regions in the Human Connectome Project Multimodal Parcellation atlas. Here we add function to these maps by measuring selective fMRI activations and functional connectivity increases to stationary visual stimuli of faces, scenes, body parts and tools from 956 HCP participants. Faces activate regions in the ventrolateral visual cortical stream (FFC), in the superior temporal sulcus (STS) visual stream for face and head motion; and inferior parietal visual (PGi) and somatosensory (PF) regions. Scenes activate ventromedial visual stream VMV and PHA regions in the parahippocampal scene area; medial (7m) and lateral parietal (PGp) regions; and the reward-related medial orbitofrontal cortex. Body parts activate the inferior temporal cortex object regions (TE1p, TE2p); but also visual motion regions (MT, MST, FST); and the inferior parietal visual (PGi, PGs) and somatosensory (PF) regions; and the unpleasant-related lateral orbitofrontal cortex. Tools activate an intermediate ventral stream area (VMV3, VVC, PHA3); visual motion regions (FST); somatosensory (1, 2); and auditory (A4, A5) cortical regions. The findings add function to cortical connectivity maps; and show how stationary visual stimuli activate other cortical regions related to their associations, including visual motion, somatosensory, auditory, semantic, and orbitofrontal cortex value-related, regions.

Generative Artificial Intelligence foundation models (for example Generative Pre-trained Transformer - GPT - models) can generate the next token given a sequence of tokens. How can this 'generative AI' be compared with the 'real' intelligence of the human brain, when for example a human generates a whole memory in response to an incomplete retrieval cue, and then generates further prospective thoughts? Here these two types of generative intelligence, artificial in machines and real in the human brain are compared, and it is shown how when whole memories are generated by hippocampal recall in response to an incomplete retrieval cue, what the human brain computes, and how it computes it, are very different from generative AI. Key differences are the use of local associative learning rules in the hippocampal memory system, and of non-local backpropagation of error learning in AI. Indeed, it is argued that the whole operation of the human brain is performed computationally very differently to what is implemented in generative AI. Moreover, it is emphasized that the primate including human hippocampal system includes computations about spatial view and where objects and people are in scenes, whereas in rodents the emphasis is on place cells and path integration by movements between places. This comparison with generative memory and processing in the human brain has interesting implications for the further development of generative AI and for neuroscience research.

To explore the structural and functional changes in cognition-related brain regions in patients with chronic low back pain (CLBP) at earlier ages, and explore the impact of the interaction between CLBP and age on the brain.

Seventy-six patients with CLBP were recruited and divided into "younger" age group (20-29 years, YA), "middle" age group (30-39 years, MA), and "older" age group (40-49 years, OA). All patients underwent functional magnetic resonance imaging (fMRI) as well as clinical psychological and pain-related symptoms assessments.

Structural analysis showed that patients in OA group had lower gray matter (GM) volumes in the orbitofrontal cortex (OFC) bilaterally and the right superior frontal gyrus (SFG) compared to YA group. The resting-state brain activity analysis showed that amplitude of low-frequency fluctuation (ALFF) values in the bilateral postcentral gyrus and left ventral medial prefrontal cortex (mPFC) were significantly different in the OA group. The functional connectivity (FC) in the right ventral dorsolateral prefrontal cortex (DLPFC) and the right insula was significantly decreased in the OA group compared to the YA and MA groups. Likewise, the FC in the left caudal parahippocampal gyrus (PHG) and left inferior parietal lobule (IPL) were significantly lower in the MA and OA groups compared to the YA group. In addition, both the structural properties and the FC values of these brain regions were significantly correlated with age.

This preliminary study concludes that CLBP affects the aging process. The synergistic effects of CLBP and aging accelerate the functional and structural decline of certain areas of the brain, which not only affects pain processing, but are also may be associated with cognitive declines.