The Common Neural Basis of Autobiographical Memory, Prospection, Navigation, Theory of Mind, and the Default Mode: A Quantitative Meta-analysis

Abnormalities of regional brain activity in patients with asymptomatic internal carotid artery occlusion: a resting-state fMRI study

BACKGROUND

Asymptomatic internal carotid artery occlusion (aICAO) disrupts cerebral blood flow and can impair brain function. While previous research has primarily focused on abnormal functional connectivity between brain networks or regions in aICAO patients, less is known about specific regional brain activity alterations. This study investigated changes in local brain activity and their associations with cognitive function in patients with aICAO.

METHODS

A total of 26 unilateral patients with aICAO without MRI lesions and 25 matched healthy controls (HCs) underwent resting-state functional magnetic resonance imaging and neuropsychological assessment. Local brain activity in patients with aICAO was investigated using percentage amplitude of fluctuation (PerAF) and degree centrality (DC). The association between the abnormal regional brain activity in patients with aICAO and cognitive function was also explored.

RESULTS

Compared with HCs, patients with aICAO showed decreased PerAF in the ipsilateral (occlusion side, right) superior temporal gyrus (temporal pole), ipsilateral inferior frontal gyrus (triangular part). In addition, decreased DC was detected in the ipsilateral cuneus of patients with aICAO, while increased DC was observed in the contralateral (opposite to occlusion side, left) precuneus and contralateral inferior frontal gyrus (triangular part) among patients with aICAO. Furthermore, the DC value of contralateral precuneus in aICAO group was negatively correlated with Montreal Cognitive Assessment (MoCA) (r = -0.612, p = 0.002), Forward Digit Span Test (FDST) (r = -0.677, p = 0.001), and Backward Digit Span Test (BDST) (r = -0.531, p = 0.011) scores.

CONCLUSIONS

Our findings revealed abnormal local spontaneous brain activity within brain regions associated with cognitive functions in patients with unilateral aICAO. Notably, some of these abnormalities correlated with their cognitive impairments. This study contributes to the understanding of potential neural mechanisms underlying cognitive dysfunction in unilateral aICAO patients.

The impact of cognitive bias modification of interpretation on hostile attribution bias, reactive aggression and neural mechanisms

Hostile Attribution Bias (HAB) has been demonstrated to exert adverse impacts on reactive aggression (RA). Consequently, it is essential to investigate its prevention strategies and the brain-level alterations induced by these strategies. Cognitive Bias Modification of Interpretation (CBMI) has exhibited potential in modifying HAB. The current objective of this research is to explore its influence on individuals' hostile attributions bias and reactive aggression, and conduct an exploratory study on the underlying brain change mechanisms associated with behavioral alterations. The college students with high HAB and aggression levels were randomly assigned to a trained group and a control group. The trained group participated in a one-month-long CBM-I program, whereas the control group completed one-month-long reading tasks. The results indicated significant HAB and reactive aggression reductions within the trained group. In the trained group, the resting-state functional connectivity (rs-FC) between the anterior medial prefrontal cortex (amPFC) and the calcarine exhibited a remarkable increase, and this augmentation was positively correlated with the decrease in HAB. In contrast, no significant changes were detected in the control group after training. Our results suggest that the CBM-I has an effect on ameliorating individuals' hostile attributions bias and reactive aggression and has exploratorily uncovered the corresponding changes at the brain level.

Self-related thought alterations associated with intrinsic brain dysfunction in mild cognitive impairment

The subjective experience of self-awareness is attributed to the human capacity for introspective thought during periods of mind-wandering. However, how this cognitive function is impacted in individuals with mild cognitive impairment (MCI) still needs to be better understood. To address this gap, we investigated alterations in self-referential thinking in a cohort of 30 MCI patients, comparing them to 60 healthy old-aged and 60 healthy younger controls. MCI patients exhibited a notable decline in overall cognitive function, as evidenced by significantly lower scores on the Montreal Cognitive Assessment (MoCA), with particular deficits in Memory subscore and Memory Index Score (MIS). Employing the Amsterdam Resting-State Questionnaire (ARSQ) to assess mind-wandering, we observed diminished self-related thoughts relating to personal past experiences and future thinking among MCI patients. Notably, using high-density electroencephalography (hdEEG) microstate analysis, we detected reduced neural activity for microstate C associated with self-related thoughts in MCI patients and healthy older relative to healthy younger controls, and an increase in neural activity for microstate A in MCI patients compared to healthy older and younger controls. This aberrant temporal activity was localized within brain regions implicated in episodic autobiographical memory and the default mode network. Our results highlight a link between impaired mind-wandering ability and dysfunction within the intrinsic neural networks of MCI patients, underscoring its implications for disruptions in the sense of self within this clinical population.

The Journey of the Default Mode Network: Development, Function, and Impact on Mental Health

The Default Mode Network has been extensively studied in recent decades due to its central role in higher cognitive processes and its relevance for understanding mental disorders. This neural network, characterized by synchronized and coherent activity at rest, is intrinsically linked to self-reflection, mental exploration, social interaction, and emotional processing. Our understanding of the DMN extends beyond humans to non-human animals, where it has been observed in various species, highlighting its evolutionary basis and adaptive significance throughout phylogenetic history. Additionally, the DMN plays a crucial role in brain development during childhood and adolescence, influencing fundamental cognitive and emotional processes. This literature review aims to provide a comprehensive overview of the DMN, addressing its structural, functional, and evolutionary aspects, as well as its impact from infancy to adulthood. By gaining a deeper understanding of the organization and function of the DMN, we can advance our knowledge of the neural mechanisms that underlie cognition, behavior, and mental health. This, in turn, can lead to more effective therapeutic strategies for a range of neuropsychiatric conditions.

Effects of Continuous Positive Airway Pressure on Neuroimaging Biomarkers and Cognition in Adult Obstructive Sleep Apnea: A Randomized Controlled Trial

Rationale: Obstructive sleep apnea (OSA) is associated with cognitive impairment. The effects of continuous positive airway pressure (CPAP) on neuroimaging biomarkers and cognitive performance among middle-aged patients with OSA and normal cognition remain unclear. Objectives: To investigate the effects of CPAP therapy over 12 months on neuroimaging biomarkers and cognitive performance. Methods: In this multicenter, randomized clinical trial, we randomly assigned 148 participants with normal cognition and an apnea-hypopnea index ⩾15/h into two groups: patients receiving CPAP with best supportive care (BSC); and patients receiving BSC alone. The primary endpoint was Montreal Cognitive Assessment (MoCA) score at 6 months after enrollment. The secondary endpoints were intranetwork functional connectivity (FC) of default mode network (DMN) and cortical thickness assessed by functional and structural magnetic resonance imaging, other neuroimaging biomarkers, and neurobehavioral tests. Measurements and Main Results: Between 2017 and 2021, 148 patients were recruited from five hospitals. Linear mixed models showed that there was no significant difference in MoCA scores at 6 months between the CPAP and BSC groups (difference, -0.04; 95% confidence interval [CI], -0.72 to 0.65; P = 0.91). However, there were significant differences in the FC of DMN (difference, -13.73; 95% CI, -23.40 to -4.06; P = 0.01) and cortical thickness (difference, -0.06 mm; 95% CI, -0.10 to -0.01 mm; P = 0.02) between CPAP and BSC groups at 6 months after treatment. No serious adverse events occurred. Conclusions: CPAP improved cortical thickness and FC of DMN, suggesting that patients with OSA may recover from brain atrophic processes after CPAP treatment. However, no improvement in MoCA was found. Clinical trial registered with www.clinicaltrials.gov (NCT02886156).

Neural network localization in Parkinson's disease with impulse control disorders

Background

There is a huge heterogeneity of magnetic resonance imaging findings in Parkinson's disease (PD) with impulse control disorders (ICDs) studies. Here, we hypothesized that brain regions identified by structural and functional imaging studies of PD with ICDs could be reconciled in a common network.

Methods

In this study, an initial systematic literature review was conducted to collect and evaluate whole-brain functional and structural magnetic resonance imaging studies related to PD with ICDs. We subsequently utilized the Human Connectome Project (HCP) dataset (n = 1,093) and a novel functional connectivity network mapping (FCNM) technique to identify a common brain network affected in PD with ICDs.

Results

A total of 19 studies with 25 contrasts, incorporating 345 individuals with PD and ICDs, and 787 individuals with PD without ICDs were included in the analysis. By using the HCP dataset and a novel FCNM technique, we ultimately identified that the aberrant neural networks predominantly involve the default mode network (middle and inferior temporal gyrus, anterior cingulate cortex, angular gyrus) and subcortical network (caudate nucleus).

Conclusion

This study suggests that the heterogeneous neuroimaging findings in PD with ICDs can be attributed to shared abnormalities in the default mode and subcortical networks. These dysfunctions are associated with impaired self-regulation, decision-making, and heightened impulsivity in PD with ICDs. Our findings integrate diverse neuroimaging results from previous studies, providing a clearer understanding of the neurobiological mechanisms underlying PD with ICDs at a network level.

Cognitive reserve and aging: Impacts on theory of mind and executive functions

AIM

This study examines the effects of cognitive reserve (CR) on Executive Functions (EF) and Theory of Mind (ToM). While CR is suggested to mitigate age-related cognitive decline, its relationship with social cognition remains limited and inconsistent in the literature. It was hypothesized that the effect of CR on ToM might be indirect, mediated by EF and working memory.

METHODS

225 cognitively healthy participants were included. CR was measured with the Cognitive Reserve Index Questionnaire, EF with verbal fluency and the Stroop Test, and WM using digit span tasks. Structural Equation Modeling was used to analyze the relationships among CR, EF, WM, and SC, controlling for age and gender.

RESULTS

CR was significantly associated with both RMET and FPRT performances. Mediation analysis revealed the direct effects of CR on RMET performance, while the effects on FPRT performance were mediated by executive functions. WM had a partial mediating effect on EF and ToM, but did not directly influence FPRT. Education was most strongly associated with RMET performance, while leisure activities were linked to FPRT performance.

CONCLUSION

These findings suggest that CR indirectly supports ToM by enhancing EF and highlight the importance of interventions aimed at strengthening executive control to support social cognition in aging.

Two long-axis dimensions of hippocampal-cortical integration support memory function across the adult lifespan

The hippocampus is a complex structure critically involved in numerous behavior-regulating systems. In young adults, multiple overlapping spatial modes along its longitudinal and transverse axes describe the organization of its functional integration with neocortex, extending the traditional framework emphasizing functional differences between sharply segregated hippocampal subregions. Yet, it remains unknown whether these modes (i.e. gradients) persist across the adult human lifespan, and relate to memory and molecular markers associated with brain function and cognition. In two independent samples, we demonstrate that the principal anteroposterior and second-order, mid-to-anterior/posterior hippocampal modes of neocortical functional connectivity, representing distinct dimensions of macroscale cortical organization, manifest across the adult lifespan. Specifically, individual differences in topography of the second-order gradient predicted episodic memory and mirrored dopamine D1 receptor distribution, capturing shared functional and molecular organization. Older age was associated with less distinct transitions along gradients (i.e. increased functional homogeneity). Importantly, a youth-like gradient profile predicted preserved episodic memory - emphasizing age-related gradient dedifferentiation as a marker of cognitive decline. Our results underscore a critical role of mapping multidimensional hippocampal organization in understanding the neural circuits that support memory across the adult lifespan.

Neural signatures of recollection are sensitive to memory quality and specific event features

Episodic memories reflect a bound representation of multimodal features that can be recollected with varying levels of precision. Recent fMRI investigations have demonstrated that the precision and content of information retrieved from memory engage a network of posterior medial temporal and parietal regions co-activated with the hippocampus. Yet, comparatively little is known about how memory content and precision affect common neural signatures of memory captured by electroencephalography (EEG), where recollection has been associated with changes in event-related potential (ERP) and oscillatory measures of neural activity. Here, we used a multi-feature paradigm previously reported in Cooper & Ritchey (2019) with continuous measures of memory, in conjunction with scalp EEG, to characterize the content and quality of information that drives ERP and oscillatory markers of episodic memory. A common signature of memory retrieval in left posterior regions, called the late positive component (LPC), was sensitive to overall memory quality and also to precision of recollection for spatial features. Analysis of oscillatory markers during recollection revealed that alpha/beta desynchronization was modulated by overall memory quality and also by individual features in memory. Importantly, we found evidence of a relationship between these two neural markers of memory retrieval, suggesting that they may represent complementary aspects of the recollection experience. These findings demonstrate how time-sensitive and dynamic processes identified with EEG correspond to overall episodic recollection, and also to the retrieval of precise features in memory.

Disentangling the role of executive function and episodic memory in older adults' performance on dynamic theory of mind tasks

Theory of mind is a core social cognitive ability, and declines over the lifespan. Prior work examining the mechanisms underlying older adults' theory of mind deficits has yielded heterogenous results. One reason for this might be a general reliance on static, rather than dynamic, stimuli. Because dynamic measures may best capture everyday theory of mind engagement, the current study examined whether executive function and/or episodic memory - the primary mechanisms examined in prior work - predicted older adults' static and dynamic theory of mind performance. In Study 1, 153 older adults completed traditional static measures of theory of mind (false belief task, Reading the Mind in the Eyes) and a dynamic theory of mind measure that captured multiple domains of theory of mind (e.g. inferring beliefs, understanding emotions). They also completed comprehensive measures of executive function and episodic memory. Episodic memory, but not executive function, predicted theory of mind performance across tasks. In Study 2, 124 different older adults completed two novel dynamic tasks, and the same cognitive measures from Study 1. The first dynamic task was similar to the Study 1, but was relatively unfamiliar. In the second task, older adults made continuous (e.g. dynamic) awkwardness ratings while watching a video. This task reduces ceiling effects, a frequent limitation of theory of mind research. Replicating the results in Study 1, episodic memory, but not executive function, predicted older adults' performance on both tasks. Together, these findings suggest that episodic memory ability predicts older adults' static and dynamic theory of mind performance.

Why friendship and loneliness affect our health

Humans, like all monkeys and apes, have an intense desire to be social. The human social world, however, is extraordinarily complex, depends on sophisticated cognitive and neural processing, and is easily destabilized, with dramatic consequences for our mental and physical health. To show why, I first summarize descriptive aspects of human friendships and what they do for us, then discuss the cognitive and neurobiological processes that underpin them. I then summarize the growing body of evidence suggesting that our mental as well as our physical health and wellbeing are best predicted by the number and quality of close friend/family relationships we have, with five being the optimal number. Finally, I review neurobiological evidence that both number of friends and loneliness itself are correlated with the volume of certain key brain regions associated with the default mode neural network and its associated gray-matter processing units.

Music-Evoked Nostalgia Activates Default Mode and Reward Networks Across the Lifespan

Nostalgia is a mixed emotion that is often evoked by music. Nostalgic music may induce temporary improvements in autobiographical memory in individuals with cognitive decline. However, the neural mechanism underlying music-evoked nostalgia and its associated memory improvements is unclear. With the ultimate goal of understanding how nostalgia-evoking music may help retrieve autobiographical memories in individuals with cognitive impairment, we first sought to understand the neural underpinnings of these processes in healthy younger and older adults. Methodological constraints, including the lack of personally tailored and experimentally controlled stimuli, have impeded our understanding of this mechanism. Here, we utilized an innovative machine-learning-based method to construct three categories of songs, all matched for musical features: (1) personalized nostalgic, (2) familiar non-nostalgic, and (3) unfamiliar non-nostalgic. In 57 participants (29 aged 18-35; 28 aged 60 and older), we investigated the functional neural correlates of music-evoked nostalgia using fMRI. Four main findings emerged: (1) Listening to nostalgic music, more than familiar non-nostalgic or unfamiliar music, was associated with bilateral activity in the default mode network, salience network, reward network, medial temporal lobe, and supplementary motor regions, (2) Psychophysiological interaction (PPI) models indicated that listening to nostalgic music involved increased functional connectivity of self-referential (posteromedial cortex) and affect-related regions (insula), (3) Older adults had stronger BOLD signals than younger adults in nostalgia-related regions during nostalgic listening, (4) While the BOLD response to nostalgic music in younger adults was associated with trait-level factors of nostalgia proneness and cognitive ability, the response in older adults was related to affective responses to the music. Overall, our findings serve as a foundation for understanding the neural basis of music-evoked nostalgia and its potential use in future clinical interventions.

Arousal threshold reveals novel neural markers of sleep depth independently from the conventional sleep stages

Reports of sleep-specific brain activity patterns have been constrained by assessing brain function as it related to the conventional polysomnographic sleep stages. This limits the variety of sleep states and underlying activity patterns that one can discover. The current study used all-night functional MRI sleep data and defined sleep behaviorally with auditory arousal threshold (AAT) to characterize sleep depth better by searching for novel neural markers of sleep depth that are neuroanatomically localized and temporally unrelated to the conventional stages. Functional correlation values calculated in a four-min time window immediately before the determination of AAT were entered into a linear mixed effects model, allowing multiple arousals across the night per subject into the analysis, and compared to models with sleep stage to determine the unique relationships with AAT. These unique relationships were for thalamocerebellar correlations, the relationship between the right language network and the right "default-mode network dorsal medial prefrontal cortex subsystem," and the relationship between thalamus and ventral attention network. These novel neural markers of sleep depth would have remained undiscovered if the data were merely analyzed with the conventional sleep stages.

Effects of insecure attachment on fMRI resting state functional connectivity in poly drug use disorder

BACKGROUND

Insecure adult attachment has previously been linked to more severe psychopathology and to alterations within neuronal connectivity on a structural as well as functional level. Little is known about the resting state functional connectivity (rs-FC) of the attachment system in patients suffering from poly-drug use disorder (PUD).

METHODS

The present study investigated rs-FC at two measuring points (t1: ROI-to-ROI; t2: seed-to-voxel) in a sample of PUD patients (n = 33; Age: M = 30y; SD = 8y; Female = 15%). Adult attachment was measured with the German version of the Experiences in Close Relationships Scale (ECR-RD8). Furthermore, insecure attachment was correlated with depressive symptoms (ADS), trait anxiety (STAI) and general psychopathology (BSI-53).

RESULTS

More insecure attachment was associated with increased trait anxiety, depressive and general psychiatric symptom burden in patients. Furthermore, we observed time-stable links between insecure adult attachment and increased rs-FC between the left lateral parietal default mode network (DMN LP) and bilateral parts of the salience network, as well as decreased rs-FC between DMN LP and medial parts of the DMN.

DISCUSSION

Implications of the present study are highlighting the association between attachment security and brain areas related to affect regulation.

Suicidal Behaviour Prior to First Episode Psychosis: Wider and More Widespread Grey-Matter Alterations

INTRODUCTION

The prodromal phase preceding the onset of First Episode Psychosis (FEP) is associated with an increased risk of Suicidal Behaviors (SBs). The aim of this study was to identify specific structural brain abnormalities linked to SBs that occur prior to the onset of FEP.

METHODS

Voxel-based morphometry analyses were used to investigate differences in brain Grey Matter (GM) volume using the CAT12 toolbox within SPM12. Covariates, including gender, age, handedness, intracranial volume, depression severity, and global cognitive functioning, were controlled for as confounding factors.

RESULTS

Significant reductions in GM were observed in the left superior temporal gyrus, dorsal posterior cingulate cortex, precuneus, cuneus, anterior cerebellum (p-FWE corrected < 0.05, k > 50) as well as in the right amygdala (0.96 ± 0.06 vs. 1.01 ± 0.05; F = 4.78; p < 0.05) and left amygdala (0.97 ± 0.06 vs. 1.02 ± 0.05; F = 8.97; p = 0.01).

CONCLUSIONS

History of SB prior to the onset of the psychotic disorder was related to wider and more widespread brain GM alterations. The regions identified are involved in cognitive and emotional processes such as emotional regulation, social cognition, perseverative thinking, and pain tolerance. These findings suggest that structural brain abnormalities related to SB occurring before FEP onset may serve as early biomarkers for identifying individuals at increased risk of suicide.

An Explainable Unified Framework of Spatio-Temporal Coupling Learning With Application to Dynamic Brain Functional Connectivity Analysis

Time-series data such as fMRI and MEG carry a wealth of inherent spatio-temporal coupling relationship, and their modeling via deep learning is essential for uncovering biological mechanisms. However, current machine learning models for mining spatio-temporal information usually overlook this intrinsic coupling association, in addition to poor explainability. In this paper, we present an explainable learning framework for spatio-temporal coupling. Specifically, this framework constructs a deep learning network based on spatio-temporal correlation, which can well integrate the time-varying coupled relationships between node representation and inter-node connectivity. Furthermore, it explores spatio-temporal evolution at each time step, providing a better explainability of the analysis results. Finally, we apply the proposed framework to brain dynamic functional connectivity (dFC) analysis. Experimental results demonstrate that it can effectively capture the variations in dFC during brain development and the evolution of spatio-temporal information at the resting state. Two distinct developmental functional connectivity (FC) patterns are identified. Specifically, the connectivity among regions related to emotional regulation decreases, while the connectivity associated with cognitive activities increases. In addition, children and young adults display notable cyclic fluctuations in resting-state brain dFC.

Cognitive and psychiatric relevance of dynamic functional connectivity states in a large (N > 10,000) children population

Children's brains dynamically adapt to the stimuli from the internal state and the external environment, allowing for changes in cognitive and mental behavior. In this work, we performed a large-scale analysis of dynamic functional connectivity (DFC) in children aged 9~11 years, investigating how brain dynamics relate to cognitive performance and mental health at an early age. A hybrid independent component analysis framework was applied to the Adolescent Brain Cognitive Development (ABCD) data containing 10,988 children. We combined a sliding-window approach with k-means clustering to identify five brain states with distinct DFC patterns. Interestingly, the occurrence of a strongly connected state with the most within-network synchrony and the anticorrelations between networks, especially between the sensory networks and between the cerebellum and other networks, was negatively correlated with cognitive performance and positively correlated with dimensional psychopathology in children. Meanwhile, opposite relationships were observed for a DFC state showing integration of sensory networks and antagonism between default-mode and sensorimotor networks but weak segregation of the cerebellum. The mediation analysis further showed that attention problems mediated the effect of DFC states on cognitive performance. This investigation unveils the neurological underpinnings of DFC states, which suggests that tracking the transient dynamic connectivity may help to characterize cognitive and mental problems in children and guide people to provide early intervention to buffer adverse influences.

The neural correlates of guilt highlight preclinical manifestations between bipolar and major depressive disorders

BACKGROUND

Over 25 % of bipolar disorder (BD) patients are misdiagnosed with major depressive disorder (MDD). An urgent need exists for a biomarker to differentiate BD from MDD. Various manifestations and intensities of maladaptive guilt processing might uniquely contribute to the pathogenesis of BD compared to MDD.

METHOD

This study adopted a first-person perspective guilt-provoking functional magnetic resonance imaging (fMRI) task, respectively induced by painful and ambiguous scenarios in 111 individuals: 35 with remitted MDD, 38 with remitted bipolar I disorder (BD-I), and 38 matched controls.

RESULTS

A significant interaction between group and sense of agency in predicting guilt ratings for ambiguous, rather than painful, scenarios. The association between sense of agency and guilt was significant in MDD but not in BD-I patients or controls. Activation in the dorsomedial prefrontal cortex (dmPFC), pregenual anterior cingulate cortex (pgACC), and right inferior parietal lobule (IPL) was higher in BD-I than MDD subjects in response to ambiguous scenarios, whereas these were comparable to painful ones. The correlation between guilt ratings and activation in the dorsal anterior cingulate cortex (dACC) to ambiguous scenarios was significant in MDD, but not in BD-I or controls. The results of the multivariate pattern classification analysis showed that in the ambiguous scenarios, the accuracy of using brain activation patterns in the dmPFC, pgACC, and IPL to distinguish between participants with MDD and BD-I was 70.0 %, 71.5 %, and 68.7 %, respectively. An additional test of the classification model, employing a combined mask of the three ROIs to distinguish between the two mood disorders in ambiguous scenarios, achieved an accuracy of 78.6 % and an AUC value of 0.84.

CONCLUSIONS

Subjective reports and neural correlates of guilt in ambiguous social situations, as well as a sense of agency, could provide to be a potential biomarker to help distinguish between BD-I and MDD even in the remitted stage.

Cerebellar contribution to emotion regulation and its association with medial frontal GABA level

As a tactic to regulate emotions, distancing involves changing perspectives to alter the psychological distance from stimuli that elicit emotional reactions. Using magnetic resonance spectroscopy and functional magnetic resonance imaging, this study aimed to examine (i) whether the neural correlates of emotion upregulation via distancing differ across emotional valence (i.e. emotional responses toward positive and negative pictures), and (ii) whether the gamma-aminobutyric acid (GABA) concentration in the medial prefrontal cortex (MPFC), one of the crucial areas of emotion regulation, is correlated with brain activity related to either negative or positive emotion upregulation. Thirty-four healthy Japanese adults participated in this study. Compared to the condition involving positive emotion upregulation, negative emotion upregulation induced increased activation in the MPFC, left temporoparietal junction, bilateral anterior insula, pre-supplementary motor area, and bilateral cerebellum. In contrast, when comparing positive emotion upregulation with negative emotion upregulation, no significant activation was found. Right cerebellar activity during negative emotion upregulation was positively correlated with GABA concentration in the MPFC. These findings provide evidence of cerebellar involvement in the upregulation of negative emotion via distancing and its association with the prefrontal GABA concentration.

A double dissociation between semantic and spatial cognition in visual to default network pathways

Processing pathways between sensory and default mode network (DMN) regions support recognition, navigation, and memory but their organisation is not well understood. We show that functional subdivisions of visual cortex and DMN sit at opposing ends of parallel streams of information processing that support visually mediated semantic and spatial cognition, providing convergent evidence from univariate and multivariate task responses, intrinsic functional and structural connectivity. Participants learned virtual environments consisting of buildings populated with objects, drawn from either a single semantic category or multiple categories. Later, they made semantic and spatial context decisions about these objects and buildings during functional magnetic resonance imaging. A lateral ventral occipital to fronto-temporal DMN pathway was primarily engaged by semantic judgements, while a medial visual to medial temporal DMN pathway supported spatial context judgements. These pathways had distinctive locations in functional connectivity space: the semantic pathway was both further from unimodal systems and more balanced between visual and auditory-motor regions compared with the spatial pathway. When semantic and spatial context information could be integrated (in buildings containing objects from a single category), regions at the intersection of these pathways responded, suggesting that parallel processing streams interact at multiple levels of the cortical hierarchy to produce coherent memory-guided cognition.

Neural processing of sad and happy autobiographical memories in women with depression and borderline personality disorder

Patients with major depressive disorder (MDD) and borderline personality disorder (BPD) are reported to have disrupted autobiographical memory (AM). Using functional magnetic resonance imaging we investigated behavioral and neural processing of the recall of emotional (sad and happy) memories in 30 MDD, 18 BPD, and 34 healthy control (HC) unmedicated women. The behavioral results showed that the MDD group experienced more sadness than the HC after the sad recall, while BPD participants experienced less happiness than HC after the happy recall. The fMRI results for sad AMs, compared to happy AMs, elicited greater activation in multiple brain regions (i.e., medial prefrontal cortex, posterior cingulate cortex, insula) linked to self-related information, emotional processing, and semantic recollection across all groups. Functional connectivity analysis revealed a significant main effect of group between the occipital cortex and precuneus and between occipital cortex and posterior cingulate cortex. The effect was driven by stronger connectivity between the occipital cortex and precuneus in the clinical groups taken together than in the HC. Our results suggest a need for stronger coordination between visual imagery and contextual recall for vivid memory retrieval in these clinical groups.

Stepwise pathways from the olfactory cortex to central hub regions in the human brain

The human brain is organized as a hierarchical global network. Functional connectivity research reveals that sensory cortices are connected to corresponding association cortices via a series of intermediate nodes linked by synchronous neural activity. These sensory pathways and relay stations converge onto central cortical hubs such as the default-mode network (DMN). The DMN regions are believed to be critical for representing concepts and, hence, language acquisition and use. Although prior research has established that major senses are placed at a similar distance from the DMN-five to six connective steps-it is still unknown how the olfactory system functionally connects to the large-scale cortical hubs of the human brain. In this study, we investigated the connective distance from olfactory seed areas to the DMN. The connective distance involves a series of three to four intermediate steps. Furthermore, we parcellated the olfactory cortical subregions and found evidence of two distinct olfactory pathways. One emerges from the anterior olfactory nucleus and olfactory tubercle; it involves early access to the orbitofrontal cortex, known for processing reward and multisensory signals. The other emerges from the frontal and temporal regions of the piriform cortex, involving the anterior insula, intermediate frontal sulcus, and parietal operculum. The results were confirmed in a replication cohort. Our results provide evidence that olfaction has unique early access to the central cortical networks via dual pathways.

Early Infant Prefrontal Cortical Microstructure Predicts Present and Future Emotionality

BACKGROUND

High levels of infant negative emotionality (NE) and low positive emotionality (PE) predict future emotional and behavioral problems. The prefrontal cortex (PFC) supports emotional regulation, with each PFC subregion specializing in specific emotional processes. Neurite orientation dispersion and density imaging estimates microstructural integrity and myelination via the neurite density index (NDI) and dispersion via the orientation dispersion index (ODI), with potential to more accurately evaluate microstructural alterations in the developing brain. Yet, no study has used these indices to examine associations between PFC microstructure and concurrent or developing infant emotionality.

METHODS

We modeled PFC subregional NDI and ODI at 3 months with caregiver-reported infant NE and PE at 3 months (n = 61) and at 9 months (n = 50), using multivariable and subsequent bivariate regression models.

RESULTS

The most robust statistically significant findings were positive associations among 3-month rostral anterior cingulate cortex (ACC) ODI and caudal ACC NDI and concurrent NE, a positive association between 3-month lateral orbitofrontal cortex ODI and prospective NE, and a negative association between 3-month dorsolateral PFC ODI and concurrent PE. Multivariate models also revealed that other PFC subregional microstructure measures, as well as infant and caregiver sociodemographic and clinical factors, predicted infant 3- and 9-month NE and PE.

CONCLUSIONS

Greater NDI and ODI, reflecting greater microstructural complexity, in PFC regions supporting salience perception (rostral ACC), decision making (lateral orbitofrontal cortex), action selection (caudal ACC), and attentional processes (dorsolateral PFC) might result in greater integration of these subregions with other neural networks and greater attention to salient negative external cues, thus higher NE and/or lower PE. These findings provide potential infant cortical markers of future psychopathology risk.

The future, before, and after: Bayesian and multivariate analyses reveal shared and unique neural mechanisms of imagining and remembering the same unique event

Research shows that the brain regions that subserve our ability to remember the past are also involved in imagining the future. Given this similarity in brain activity, it remains unclear how brain activity distinguishes imagination from memory. In the current work, we scanned participants using functional magnetic resonance imaging before and after they performed a highly unique and elaborate activity wherein they went skydiving for the first time in their lives. Multivariate pattern analysis, Bayesian inference, and a tightly controlled experimental design were used to identify the neural activity that differentiates between memory and imagination of the same events. The results showed that large swaths of the default mode network exhibited identical patterns of activity in recollection and imagination; several frontal areas were involved in imagination (but not in recollection). Representational similarity analysis revealed that the left ventral precuneus exhibited different patterns of memory and imagination. Further examination revealed that this subarea may be especially important for recollection of specific episodes. These results advance our understanding of how the critical distinction between the past and future might be manifested in the brain.

A Deep Dynamic Causal Learning Model to Study Changes in Dynamic Effective Connectivity During Brain Development

OBJECTIVE

Brain dynamic effective connectivity (dEC), characterizes the information transmission patterns between brain regions that change over time, which provides insight into the biological mechanism underlying brain development. However, most existing methods predominantly capture fixed or temporally invariant EC, leaving dEC largely unexplored.

METHODS

Herein we propose a deep dynamic causal learning model specifically designed to capture dEC. It includes a dynamic causal learner to detect time-varying causal relationships from spatio-temporal data, and a dynamic causal discriminator to validate these findings by comparing original and reconstructed data.

RESULTS

Our model outperforms established baselines in the accuracy of identifying dynamic causalities when tested on the simulated data. When applied to the Philadelphia Neurodevelopmental Cohort, the model uncovers distinct patterns in dEC networks across different age groups. Specifically, the evolution process of brain dEC networks in young adults is more stable than in children, and significant differences in information transfer patterns exist between them.

CONCLUSION

This study highlights the brain's developmental trajectory, where networks transition from undifferentiated to specialized structures with age, in accordance with the improvement of an individual's cognitive and information processing capability.

SIGNIFICANCE

The proposed model consists of the identification and verification of dynamic causality, utilizing the spatio-temporal fusing information from fMRI. As a result, it can accurately detect dEC and characterize its evolution over age.

Altered Hippocampal Subfields Functional Connectivity in Benign Paroxysmal Positional Vertigo Patients With Residual Dizziness: A Resting-State fMRI Study

OBJECTIVE

To explore alterations in functional connectivity (FC) focusing on hippocampal subfields in benign paroxysmal positional vertigo (BPPV) patients with residual dizziness (RD) after successful canalith repositioning procedure (CRP).

METHODS

We conducted resting-state functional magnetic resonance imaging (fMRI) on 95 BPPV patients, comprising 50 patients with RD and 45 without. Seed-to-voxel and seed-to-seed analyses were employed to examine changes in FC between the two groups. The hippocampal subfields, including the bilateral dentate gyrus (DG), cornu ammonis (CA), entorhinal cortex (EC), subiculum, and hippocampal amygdalar transition area (HATA) were selected as seeds. Additionally, we assessed the relationship between abnormal FC and clinical symptoms.

RESULTS

Seed-to-voxel analysis indicated that, compared to non-RD patients, those with RD exhibited decreased FC between the right DG and right parietal operculum cortex, right HATA and right precuneus, left HATA and left precuneus, left EC and cerebellar vermis 8/-crus 1, and between the left subiculum and left angular gyrus. Conversely, we observed increased FC between the left CA and left lingual gyrus, as well as between the right CA and right fusiform gyrus in RD patients. Furthermore, these variations in FC were significantly correlated with clinical features including the duration of RD and scores on the Hamilton Anxiety Scale and Dizziness Handicap Inventory.

CONCLUSION

BPPV patients with RD exhibited altered FC between hippocampal subfields and brain regions associated with spatial orientation and navigation, vestibular and visual processing, and emotional regulation. These findings offer novel insights into the pathophysiological mechanisms in BPPV patients with RD following successful CRP.

Distinct patterns of connectivity with the motor cortex reflect different components of sensorimotor learning

Sensorimotor learning is supported by multiple competing processes that operate concurrently, making it a challenge to elucidate their neural underpinnings. Here, using human functional MRI, we identify 3 distinct axes of connectivity between the motor cortex and other brain regions during sensorimotor adaptation. These 3 axes uniquely correspond to subjects' degree of implicit learning, performance errors and explicit strategy use, and involve different brain networks situated at increasing levels of the cortical hierarchy. We test the generalizability of these neural axes to a separate form of motor learning known to rely mainly on explicit processes and show that it is only the Explicit neural axis, composed of higher-order areas in transmodal cortex, that predicts learning in this task. Together, our study uncovers multiple distinct patterns of functional connectivity with motor cortex during sensorimotor adaptation, the component processes that these patterns support, and how they generalize to other forms of motor learning.

How sturdy is your memory palace? Reliable room representations predict subsequent reinstatement of placed objects

Our autobiographical experiences typically occur within the context of familiar spatial locations. When we encode these experiences into memory, we can use our spatial map of the world to help organize these memories and later retrieve their episodic details. However, it is still not well understood what psychological and neural factors make spatial contexts an effective scaffold for storing and accessing memories. We hypothesized that spatial locations with distinctive and stable neural representations would best support the encoding and robust reinstatement of new episodic memories. We developed a novel paradigm that allowed us to quantify the within-participant reliability of a spatial context ("room reliability") prior to memory encoding, which could then be used to predict the degree of successful re-activation of item memories. To do this, we constructed a virtual reality (VR) "memory palace", a custom-built environment made up of 23 distinct rooms that participants explored using a head-mounted VR display. The day after learning the layout of the environment, participants underwent whole-brain fMRI while being presented with videos of the rooms in the memory palace, allowing us to measure the reliability of the neural activity pattern associated with each room. Participants were taken back to VR and asked to memorize the locations of 23 distinct objects randomly placed within each of the 23 rooms, and then returned to the scanner as they recalled the objects and the rooms in which they appeared. We found that our room reliability measure was predictive of object reinstatement across cortex, and further showed that this was driven not only by the group-level reliability of a room across participants, but also the idiosyncratic reliability of rooms within each participant. Together, these results showcase how the quality of the neural representation of a spatial context can be quantified and used to 'audit' its utility as a memory scaffold for future experiences.

The neural basis underlying the association between parents' socioeconomic status and depressive symptoms among college students

Objective

Depression is increasingly prevalent among adolescents, with parents' socioeconomic status (SES) serving as significant predictors. Understanding the link between parents' SES and college students' depressive symptoms is of paramount concern. However, the neural basis linking the association between parents' SES and students' depressive symptoms still remains to be explored. In order to address this issue, this study aims to investigate the relationship between parents' SES and students' depressive symptoms, and the role of brain functional connectivity (FC) pattern in this relationship.

Methods

In this study, a total of 363 college students without a history of mental or neurological disorders underwent depressive symptoms assessment and resting-state functional magnetic resonance imaging scans. We used a connectome-based predictive modeling (CPM) approach to identify neural biomarkers of depressive symptoms.

Results

The results indicate that there is a negative correlation between parents' SES and students' depression tendencies (Father's education level and SDS: r  = -0.119, p < 0.05; Mother's education level and SDS: r  = -0.117, p < 0.05), suggesting that students whose parents have a higher educational level are less likely to suffer from depression. Furthermore, a FC pattern that can significantly predict depressive symptoms outside of the body was identified (r  = 0.13, p < 0.005), with most of the FCs belonging to the default mode network (DMN) and ventral attention network (VAN). Additionally, the FC pattern associated with depressive symptoms mediate the relationship between parents' SES and depressive symptoms.

Conclusion

Therefore, we believe that improving the education levels of parents may have a practical effect in reducing depressive symptoms among adolescents.

Characterization of changes in the resting-state intrinsic network in patients with diabetic peripheral neuropathy

Diabetic peripheral neuropathy (DPN) is the most common complication of type 2 diabetes mellitus (T2DM) and is often accompanied by a variety of cognitive and emotional deficits, but the neurologic mechanisms underlying these deficits have not been fully elucidated. Therefore, this study aimed to use independent component analysis to explore the changes in the characteristics within the intrinsic network and to reveal patterns of interactions between networks in patients with DPN. Forty-one patients with T2DM who showed DPN, 37 patients with T2DM who did not show DPN (NDPN group), and 43 healthy controls (HC) underwent a neuropsychological assessment and resting-state functional magnetic resonance imaging examinations to examine the patterns of intra- and inter-network variations in the patients with T2DM at different clinical stages (with and without DPN). The relationships of intra- and inter-network functional connectivity (FC) with clinical/cognitive variables were also examined. In comparison with the NDPN group and HC, patients with DPN showed decreased FC within the visual network and sensorimotor network (SMN). Moreover, in comparison with the HC group, patients with DPN showed decreased FC within the anterior default mode network and increased FC within the basal ganglia network. Inter-network analysis showed decreased FC between the SMN and salience network in patients with DPN relative to the NDPN and HC groups. The decreased FC within the bilateral paracentral lobule (BA 6) of SMN was associated with Color Trails Test part 1 scores (r = -0.302, P = 0.007) and disease duration (r = -0.328, P = 0.003) in all patients with T2DM. In conclusion, the results revealed that patients with DPN have abnormal FC in multiple resting-state intrinsic networks in addition to the SMN, and that decreased FC between the SMN and salience network may be involved in the neural basis of abnormal sensorimotor function in patients with DPN.

Dynamic multilayer networks reveal mind wandering

Introduction

Mind-wandering is a highly dynamic phenomenon involving frequent fluctuations in cognition. However, the dynamics of functional connectivity between brain regions during mind-wandering have not been extensively studied.

Methods

We employed an analytical approach aimed at extracting recurring network states of multilayer networks built using amplitude envelope correlation and imaginary phase-locking value of delta, theta, alpha, beta, or gamma frequency band. These networks were constructed based on electroencephalograph (EEG) data collected while participants engaged in a video-learning task with mind-wandering and focused learning conditions. Recurring multilayer network states were defined via clustering based on overlapping node closeness centrality.

Results

We observed similar multilayer network states across the five frequency bands. Furthermore, the transition patterns of network states were not entirely random. We also found significant differences in metrics that characterize the dynamics of multilayer network states between mind-wandering and focused learning. Finally, we designed a classification algorithm, based on a hidden Markov model using state sequences as input, that achieved a 0.888 mean area under the receiver operating characteristic curve for within-participant detection of mind-wandering.

Discussion

Our approach offers a novel perspective on analyzing the dynamics of EEG data and shows potential application to mind-wandering detection.

Personality traits vary in their association with brain activity across situations

Human cognition supports complex behaviour across a range of situations, and traits (e.g. personality) influence how we react in these different contexts. Although viewing traits as situationally grounded is common in social sciences, often studies attempting to link brain activity to human traits examine brain-trait associations in a single task, or, under passive conditions like wakeful rest. These studies, often referred to as brain wide association studies (BWAS) have recently become the subject of controversy because results are often unreliable even with large sample sizes. Although there are important statistical reasons why BWAS yield inconsistent results, we hypothesised that the situation in which brain activity is measured will impact the power in detecting a reliable link to specific traits. We performed a state-space analysis where tasks from the Human Connectome Project (HCP) were organized into a low-dimensional space based on how they activated different large-scale neural systems. We examined how individuals' observed brain activity across these different contexts related to their personality. We found that for multiple personality traits, stronger associations with brain activity emerge in some tasks than others. These data highlight the importance of context-bound views for understanding how brain activity links to trait variation in human behaviour.

Retinotopic coding organizes the interaction between internally and externally oriented brain networks

The human brain seamlessly integrates internally generated thoughts with incoming sensory information, yet the networks supporting internal (default network, DN) and external (dorsal attention network, dATN) processing are traditionally viewed as antagonistic. This raises a crucial question: how does the brain integrate information between these seemingly opposed systems? Here, using precision neuroimaging methods, we show that these internal/external networks are not as dissociated as traditionally thought. Using densely-sampled 7T fMRI data, we defined individualized whole-brain networks from participants at rest and calculated the retinotopic preferences of individual voxels within these networks during an visual mapping task. We show that while the overall network activity between the DN and dATN is independent at rest, considering a latent retinotopic code reveals a complex, voxel-scale interaction stratified by visual responsiveness. Specifically, the interaction between the DN and dATN at rest is structured at the voxel-level by each voxel's retinotopic preferences, such that the spontaneous activity of voxels preferring similar visual field locations is more anti-correlated than that of voxels preferring different visual field locations. Further, this retinotopic scaffold integrates with the domain-specific preferences of subregions within these networks, enabling efficient, parallel processing of retinotopic and domain-specific information. Thus, DN and dATN are not independent at rest: voxel-scale interaction between these networks preserves and encodes information in both positive and negative BOLD responses, even in the absence of visual input or task demands. These findings suggest that retinotopic coding may serve as a fundamental organizing principle for brain-wide communication, providing a new framework for understanding how the brain balances and integrates internal cognition with external perception.

The recursive grammar of mental time travel

One apparent feature of mental time travel is the ability to recursively embed temporal perspectives across different times: humans can remember how we anticipated the future and anticipate how we will remember the past. This recursive structure of mental time travel might be formalized in terms of a 'grammar' that is reflective of but more general than linguistic notions of absolute and relative tense. Here, I provide a foundation for this grammatical framework, emphasizing a bounded (rather than unbounded) recursive function that supports mental time travel to a limited temporal depth and to actual and possible scenarios. Anticipated counterfactual thinking, for instance, entails three levels of mental time travel to a possible scenario ('in the future, I will reflect on how my past self could have taken a different future action') and is centrally implicated in complex human decision-making. This perspective calls for further research into the mechanisms, ontogeny, functions and phylogeny of recursive mental time travel, and revives the question of links with other recursive forms of thinking such as theory of mind. This article is part of the theme issue 'Elements of episodic memory: lessons from 40 years of research'.

Aberrant activity at rest of the associative striatum in schizophrenia: Meta-analyses of the amplitude of low frequency fluctuations

Schizophrenia is a severe psychiatric disorder associated with brain alterations at rest. Amplitude of low-frequency fluctuations (ALFF) and its fractional version (fALFF) have been widely used to investigate alterations in spontaneous brain activity in schizophrenia. However, results are still inconsistent. Furthermore, while these measurements are similar, they showed some differences, and no meta-analysis has been yet performed to compare them in schizophrenia. Thus, we conducted systematic research in five databases and in the grey literature to find articles investigating fALFF and/or ALFF alterations in schizophrenia. Two separate meta-analyses were performed using the SDM-PSI software to identify fALFF and ALFF alterations separately. Then, a conjunction analysis was conducted to determine congruent results between the two approaches. We found that patients with schizophrenia showed altered fALFF activity in the left insula/putamen, the right paracentral lobule and the left middle occipital gyrus compared to healthy individuals. Patients with schizophrenia exhibited ALFF alterations in the bilateral putamen, the bilateral caudate nucleus, the bilateral inferior frontal gyrus, the right precuneus, the right precentral gyrus, the left postcentral gyrus, the right posterior cingulate gyrus, compared to healthy controls. ALFF increased activity in the left putamen was higher in drug-naïve patients and was correlated with positive symptoms. The conjunction analysis revealed a spatial convergence between fALFF and ALFF studies in the left putamen. This left putamen cluster is part of the associative striatum. Its alteration in schizophrenia provides additional support to the influential aberrant salience hypothesis of psychosis.

Resting-state EEG microstates predict mentalizing ability as assessed by the Reading the Mind in the Eyes test

Microstates analysis of electroencephalography (EEG) has gained increasing attention among researchers and clinicians as a valid tool for investigating temporal dynamics of large-scale brain networks with a millisecond time resolution. Although microstates analysis has been widely applied to elucidate the neurophysiological basis of various cognitive functions in both clinical and non-clinical samples, its application in relation to socio-affective processing has been relatively under-researched. Therefore, the main aim of the current study was to investigate the relationship between EEG microstates and mentalizing (i.e., the ability to understand the mental states of others). Eighty-two participants (thirty-six men; mean age: 24.28 ± 7.35 years; mean years of education: 15.82 ± 1.77) underwent a resting-state EEG recording and performed the Reading the Mind in the Eyes Test (RMET). The parameters of the microstates were then calculated using Cartool v. 4.09 software. Our results showed that the occurrence of microstate map C was independently and positively associated with the RMET total score and contributed to the prediction of mentalizing performance, even when controlling for potential confounding variables (i.e., age, sex, education level, tobacco and alcohol use). Since microstate C is involved in self-related processes, our findings may reflect the link between self-awareness of one's own thoughts/feelings and the enhanced ability to recognize the mental states of others at the neurophysiological level. This finding extends the functions traditionally attributed to microstate C, i.e. mind-wandering, self-related thoughts, prosociality, and emotional and interoceptive processing, to include mentalizing ability.

Top-down attention shifts behavioral and neural event boundaries in narratives with overlapping event scripts

Understanding and remembering the complex experiences of everyday life relies critically on prior schematic knowledge about how events in our world unfold over time. How does the brain construct event representations from a library of schematic scripts, and how does activating a specific script impact the way that events are segmented in time? We developed a novel set of 16 audio narratives, each of which combines one of four location-relevant event scripts (restaurant, airport, grocery store, and lecture hall) with one of four socially relevant event scripts (breakup, proposal, business deal, and meet cute), and presented them to participants in an fMRI study and a separate online study. Responses in the angular gyrus, parahippocampal gyrus, and subregions of the medial prefrontal cortex (mPFC) were driven by scripts related to both location and social information, showing that these regions can track schematic sequences from multiple domains. For some stories, participants were primed to attend to one of the two scripts by training them to listen for and remember specific script-relevant episodic details. Activating a location-related event script shifted the timing of subjective event boundaries to align with script-relevant changes in the narratives, and this behavioral shift was mirrored in the timing of neural responses, with mPFC event boundaries (identified using a hidden Markov model) aligning to location-relevant rather than socially relevant boundaries when participants were location primed. Our findings demonstrate that neural event dynamics are actively modulated by top-down goals and provide new insight into how narrative event representations are constructed through the activation of temporally structured prior knowledge.

Meditation and interoception: a conceptual framework for the narrative and experiential self

The concept of the self is complex and there is no consensus on what the self is. However, there are emerging patterns in the literature that point to two different selves, the narrative and experiential self. The narrative self refers to a conceptual or representational knowledge of the self that extends across time and manifests in self-reflection and personality assessments. The experiential self refers to first-person perception, moment-to-moment awareness, embodiment, and a sense of agency. These two selves are reliably linked to two distinct neural circuits, the default mode network (DMN) and the insula and salience network (SN). One of the consistent themes in the meditative and mindfulness literature is a change in the perspective of the self. In this paper, I will review how meditation alters those neural circuits providing a plausible mechanism that can explain the changes in the self. I also propose a rudimentary conceptual framework to account for some of the mixed results found throughout meditation literature.

Cortical hubs of highly superior autobiographical memory

Highly Superior Autobiographical Memory (HSAM) is a rare form of enhanced memory in which individuals demonstrate an extraordinary ability to remember details of their personal lives with high levels of accuracy and vividness. Neuroimaging studies have identified brain regions - specifically, midline areas within the default network - associated with remembering events from one's past. Extending this research on the neural underpinnings of autobiographical memory, the present study utilizes graph theory analyses to compare functional brain connectivity in a cohort of HSAM (n = 12) and control participants (n = 29). We perform seed-based analysis in resting-state fMRI data to assess how specific cortical regions within the autobiographical memory network are differentially connected in HSAM individuals. Additionally, we apply a whole-brain connectivity analysis to identify differences in brain hub-network topology associated with enhanced autobiographical memory. Seed-based results show converging patterns of increased connectivity in HSAM across midline areas. Whole-brain analysis also reveals enhanced connectivity across medial prefrontal and posterior cingulate cortex in HSAM individuals. Together, these results extend prior research, highlighting cortical hubs within the default network associated with enhanced autobiographical memory.

Decoding ruminative reflection in healthy individuals: The role of triple network connectivity

Ruminative reflection has been linked to enhanced executive control in processing internally represented emotional information, suggesting it may serve as an adaptive strategy for emotion regulation. Investigating the neural substrates of reflection can deepen our understanding of its adaptive properties. This study used network-based statistic (NBS)-Predict methodology to identify resting state functional connectivity (FC)-based predictors of ruminative reflection in a healthy sample. Our results showed that reflection in healthy subjects was predicted by FC within and between the default mode network (DMN), fronto-parietal network (FPN), and salience network (SN). Notably, FC within the FPN and SN, as well as between the FPN and DMN, contributed more significantly to the predictive model. These results underscore the greater influence of FPN and SN connectivity in predicting reflection, providing empirical evidence that increased executive control over internal emotional representations is integral to adaptive reflective processes. Moreover, the triple-network model, particularly the FPN-DMN coupling, emerges as a crucial predictor of ruminative reflection, highlighting the importance of coordinating self-relevant and goal-directed processing in reflective mechanisms. These identified connectivity fingerprints may offer insights into the role of reflective processes in facilitating recovery from depression.

Symptomatology after damage to the angular gyrus through the lenses of modern lesion-symptom mapping

Brain-behavior relationships are complex. For instance, one might know a brain region's function(s) but still be unable to accurately predict deficit type or severity after damage to that region. Here, I discuss the case of damage to the angular gyrus (AG) that can cause left-right confusion, finger agnosia, attention deficit, and lexical agraphia, as well as impairment in sentence processing, episodic memory, number processing, and gesture imitation. Some of these symptoms are grouped under AG syndrome or Gerstmann's syndrome, though its exact underlying neuronal systems remain elusive. This review applies recent frameworks of brain-behavior modes and principles from modern lesion-symptom mapping to explain symptomatology after AG damage. It highlights four major issues for future studies: (1) functionally heterogeneous symptoms after AG damage need to be considered in terms of the degree of damage to (i) different subdivisions of the AG, (ii) different AG connectivity profiles that disconnect AG from distant regions, and (iii) lesion extent into neighboring regions damaged by the same infarct. (2) To explain why similar symptoms can also be observed after damage to other regions, AG damage needs to be studied in terms of the networks of regions that AG functions with, and other independent networks that might subsume the same functions. (3) To explain inter-patient variability on AG symptomatology, the degree of recovery-related brain reorganisation needs to account for time post-stroke, demographics, therapy input, and pre-stroke differences in functional anatomy. (4) A better integration of the results from lesion and functional neuroimaging investigations of AG function is required, with only the latter so far considering AG function in terms of a hub within the default mode network. Overall, this review discusses why it is so difficult to fully characterize the AG syndrome from lesion data, and how this might be addressed with modern lesion-symptom mapping.

The "limbic network," comprising orbitofrontal and anterior temporal cortex, is part of an extended default network: Evidence from multi-echo fMRI

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.

Unveiling altered connectivity between cognitive networks and cerebellum in schizophrenia

Cognitive functioning is a crucial aspect in schizophrenia (SZ), and when altered it has devastating effects on patients' quality of life and treatment outcomes. Several studies suggested that they could result from altered communication between the cortex and cerebellum. However, the neural correlates underlying these impairments have not been identified. In this study, we investigated resting state functional connectivity (rsFC) in SZ patients, by considering the interactions between cortical networks supporting cognition and cerebellum. In addition, we investigated the relationship between SZ patients' rsFC and their symptoms. We used fMRI data from 74 SZ patients and 74 matched healthy controls (HC) downloaded from the publicly available database SchizConnect. We implemented a seed-based connectivity approach to identify altered functional connections between specific cortical networks and cerebellum. We considered ten commonly studied resting state networks, whose functioning encompasses specific cognitive functions, and the cerebellum, whose involvement in supporting cognition has been recently identified. We then explored the relationship between altered rsFC values and Positive and Negative Syndrome Scale (PANSS) scores. The SZ group showed increased connectivity values compared with HC group for cortical networks involved in attentive processes, which were also linked to PANSS items describing attention and language-related processing. We also showed decreased connectivity between cerebellar regions, and increased connectivity between them and attentive networks, suggesting the contribution of cerebellum to attentive and affective deficits. In conclusion, our findings highlighted the link between negative symptoms in SZ and altered connectivity within the cerebellum and between the same and cortical networks supporting cognition.

ℛSCZ: A Riemannian schizophrenia diagnosis framework based on the multiplexity of EEG-based dynamic functional connectivity patterns

Abnormal electrophysiological (EEG) activity has been largely reported in schizophrenia (SCZ). In the last decade, research has focused to the automatic diagnosis of SCZ via the investigation of an EEG aberrant activity and connectivity linked to this mental disorder. These studies followed various preprocessing steps of EEG activity focusing on frequency-dependent functional connectivity brain network (FCBN) construction disregarding the topological dependency among edges. FCBN belongs to a family of symmetric positive definite (SPD) matrices forming the Riemannian manifold. Due to its unique geometric properties, the whole analysis of FCBN can be performed on the Riemannian geometry of the SPD space. The advantage of the analysis of FCBN on the SPD space is that it takes into account all the pairwise interdependencies as a whole. However, only a few studies have adopted a FCBN analysis on the SPD manifold, while no study exists on the analysis of dynamic FCBN (dFCBN) tailored to SCZ. In the present study, I analyzed two open EEG-SCZ datasets under a Riemannian geometry of SPD matrices for the dFCBN analysis proposing also a multiplexity index that quantifies the associations of multi-frequency brainwave patterns. I adopted a machine learning procedure employing a leave-one-subject-out cross-validation (LOSO-CV) using snapshots of dFCBN from (N-1) subjects to train a battery of classifiers. Each classifier operated in the inter-subject dFCBN distances of sample covariance matrices (SCMs) following a rhythm-dependent decision and a multiplex-dependent one. The proposed ℛSCZ decoder supported both the Riemannian geometry of SPD and the multiplexity index DC reaching an absolute accuracy (100 %) in both datasets in the virtual default mode network (DMN) source space.

Default mode network dynamics: An integrated neurocircuitry perspective on social dysfunction in human brain disorders

Our intricate social brain is implicated in a range of brain disorders, where social dysfunction emerges as a common neuropsychiatric feature cutting across diagnostic boundaries. Understanding the neurocircuitry underlying social dysfunction and exploring avenues for its restoration could present a transformative and transdiagnostic approach to overcoming therapeutic challenges in these disorders. The brain's default mode network (DMN) plays a crucial role in social functioning and is implicated in various neuropsychiatric conditions. By thoroughly examining the current understanding of DMN functionality, we propose that the DMN integrates diverse social processes, and disruptions in brain communication at regional and network levels due to disease hinder the seamless integration of these social functionalities. Consequently, this leads to an altered balance between self-referential and attentional processes, alongside a compromised ability to adapt to social contexts and anticipate future social interactions. Looking ahead, we explore how adopting an integrated neurocircuitry perspective on social dysfunction could pave the way for innovative therapeutic approaches to address brain disorders.

Unveiling Promising Neuroimaging Biomarkers for Schizophrenia Through Clinical and Genetic Perspectives

Schizophrenia is a complex and serious brain disorder. Neuroscientists have become increasingly interested in using magnetic resonance-based brain imaging-derived phenotypes (IDPs) to investigate the etiology of psychiatric disorders. IDPs capture valuable clinical advantages and hold biological significance in identifying brain abnormalities. In this review, we aim to discuss current and prospective approaches to identify potential biomarkers for schizophrenia using clinical multimodal neuroimaging and imaging genetics. We first described IDPs through their phenotypic classification and neuroimaging genomics. Secondly, we discussed the applications of multimodal neuroimaging by clinical evidence in observational studies and randomized controlled trials. Thirdly, considering the genetic evidence of IDPs, we discussed how can utilize neuroimaging data as an intermediate phenotype to make association inferences by polygenic risk scores and Mendelian randomization. Finally, we discussed machine learning as an optimum approach for validating biomarkers. Together, future research efforts focused on neuroimaging biomarkers aim to enhance our understanding of schizophrenia.

Neural correlates of individual differences in moral identity and its positive moral function

Moral identity is an important moral variable which has positive moral functions, such as contributing to prosocial behaviours, reducing antisocial behaviours, and resisting the risk factors of antisocial behaviours. However, little is known about the neural correlates of moral identity and the neural basis of the effect of moral identity on the risk factors of antisocial behaviours, including moral disengagement. In this study, we explored these issues in 142 college students by estimating the regional homogeneity (ReHo) through resting-state functional magnetic resonance imaging (fMRI). The whole-brain correlation analyses found that higher internalized moral identity was correlated with higher ReHo in the precuneus. Furthermore, the ReHo in the precuneus was negatively correlated with moral disengagement, suggesting positive moral functions of the neural mechanisms of moral identity. These findings deepen our understanding of individual differences in moral identity and provide inspiration for the education of moral identity and the intervention for moral disengagement from the perspective of the brain.

Theory of mind in epilepsy

Epilepsy is characterized by recurrent, chronic, and unprovoked seizures. Epilepsy has a significant negative impact on a patient's quality of life even if seizures are well controlled. In addition to the distress caused by seizures, patients with epilepsy (PwE) may suffer from cognitive impairment with serious social consequences such as poor interpersonal relationships, loss of employment, and reduced social networks. Pathological changes and functional connectivity abnormalities observed in PwE can disrupt the neural network responsible for the theory of mind. Theory of mind is the ability to attribute mental states to other people (intentions, beliefs, and emotions). It is a complex aspect of social cognition and includes cognitive and affective constructs. In recent years, numerous studies have assessed the relationship between social cognition, including the theory of mind, in PwE, and suggested impairment in this domain. Interventions targeting the theory of mind can be potentially helpful in improving the quality of life of PwE.

Brain mechanisms discriminating enactive mental simulations of running and plogging

Enactive cognition emphasizes co-constructive roles of humans and their environment in shaping cognitive processes. It is specifically engaged in the mental simulation of behaviors, enhancing the connection between perception and action. Here we investigated the core network of brain regions involved in enactive cognition as applied to mental simulations of physical exercise. We used a neuroimaging paradigm in which participants (N = 103) were required to project themselves running or plogging (running while picking-up litter) along an image-guided naturalistic trail. Using both univariate and multivariate brain imaging analyses, we find that a broad spectrum of brain activation discriminates between the mental simulation of plogging versus running. Critically, we show that self-reported ratings of daily life running engagement and the quality of mental simulation (how well participants were able to imagine themselves running) modulate the brain reactivity to plogging versus running. Finally, we undertook functional connectivity analyses centered on the insular cortex, which is a key region in the dynamic interplay between neurocognitive processes. This analysis revealed increased positive and negative patterns of insular-centered functional connectivity in the plogging condition (as compared to the running condition), thereby confirming the key role of the insular cortex in action simulation involving complex sets of mental mechanisms. Taken together, the present findings provide new insights into the brain networks involved in the enactive mental simulation of physical exercise.

Sisterhood predicts similar neural processing of a film

Relationships between humans are essential for how we see the world. Using fMRI, we explored the neural basis of homophily, a sociological concept that describes the tendency to bond with similar others. Our comparison of brain activity between sisters, friends and acquaintances while they watched a movie, indicate that sisters' brain activity is more similar than that of friends and friends' activity is more similar than that of acquaintances. The increased similarity in brain activity measured as inter-subject correlation (ISC) was found both in higher-order brain areas including the default-mode network (DMN) and sensory areas. Increased ISC could not be explained by genetic relation between sisters neither by similarities in eye-movements, emotional experiences, and physiological activity. Our findings shed light on the neural basis of homophily by revealing that similarity in brain activity in the DMN and sensory areas is the stronger the closer is the relationship between the people.