Obesity is associated with alterations in anatomical connectivity of frontal-corpus callosum.

Obesity has been linked to abnormal frontal function, including the white matter fibers of anterior portion of the corpus callosum, which is crucial for information exchange within frontal cortex. However, alterations in white matter anatomical connectivity between corpus callosum and cortical regions in patients with obesity have not yet been investigated. Thus, we enrolled 72 obese and 60 age-/gender-matched normal weight participants who underwent clinical measurements and diffusion tensor imaging. Probabilistic tractography with connectivity-based classification was performed to segment the corpus callosum and quantify white matter anatomical connectivity between subregions of corpus callosum and cortical regions, and associations between corpus callosum-cortex white matter anatomical connectivity and clinical behaviors were also assessed. Relative to normal weight individuals, individuals with obesity exhibited significantly greater white matter anatomical connectivity of corpus callosum-orbitofrontal cortex, which was positively correlated with body mass index and self-reported disinhibition of eating behavior, and lower white matter anatomical connectivity of corpus callosum-prefrontal cortex, which was significantly negatively correlated with craving for high-calorie food cues. The findings show that alterations in white matter anatomical connectivity between corpus callosum and frontal regions involved in reward and executive control are associated with abnormal eating behaviors.

Gyral and sulcal connectivity in the human cerebral cortex.

The rapid evolution of image acquisition and data analytic methods has established in vivo whole-brain tractography as a routine technology over the last 20 years. Imaging-based methods provide an additional approach to classic neuroanatomical studies focusing on biomechanical principles of anatomical organization and can in turn overcome the complexity of inter-individual variability associated with histological and tractography studies. In this work we propose a novel, reliable framework for determining brain tracts resolving the anatomical variance of brain regions. We distinguished 4 region types based on anatomical considerations: (i) gyral regions at borders between cortical communities; (ii) gyral regions within communities; (iii) sulcal regions at invariant locations across subjects; and (iv) other sulcal regions. Region types showed strikingly different anatomical and connection properties. Results allowed complementing the current understanding of the brain's communication structure with a model of its anatomical underpinnings.

Brainnetome atlas of preadolescent children based on anatomical connectivity profiles.

During the preadolescent period, when the cerebral thickness, curvature, and myelin are constantly changing, the brain's regionalization patterns underwent persistent development, contributing to the continuous improvements of various higher cognitive functions. Using a brain atlas to study the development of these functions has attracted much attention. However, the brains of children do not always have the same topological patterns as those of adults. Therefore, age-specific brain mapping is particularly important, serving as a basic and indispensable tool to study the normal development of children. In this study, we took advantage of longitudinal data to create the brain atlas specifically for preadolescent children. The resulting human Child Brainnetome Atlas, with 188 cortical and 36 subcortical subregions, provides a precise period-specific and cross-validated version of the brain atlas that is more appropriate for adoption in the preadolescent period. In addition, we compared and illustrated for regions with different topological patterns in the child and adult atlases, providing a topologically consistent reference for subsequent research studying child and adolescent development.

Whole-Brain Wiring Diagram of Oxytocin System in Adult Mice.

Oxytocin (Oxt) neurons regulate diverse physiological responses via direct connections with different neural circuits. However, the lack of comprehensive input-output wiring diagrams of Oxt neurons and their quantitative relationship with Oxt receptor (Oxtr) expression presents challenges to understanding circuit-specific Oxt functions. Here, we establish a whole-brain distribution and anatomic connectivity map of Oxt neurons, and their relationship with Oxtr expression using high-resolution 3D mapping methods in adult male and female mice. We use a flatmap to describe Oxt neuronal expression in four hypothalamic domains including under-characterized Oxt neurons in the tuberal nucleus (TU). Oxt neurons in the paraventricular hypothalamus (PVH) broadly project to nine functional circuits that control cognition, brain state, and somatic visceral response. In contrast, Oxt neurons in the supraoptic (SO) and accessory (AN) nuclei have limited central projection to a small subset of the nine circuits. Surprisingly, quantitative comparison between Oxt output and Oxtr expression showed no significant correlation across the whole brain, suggesting abundant indirect Oxt signaling in Oxtr-expressing areas. Unlike output, Oxt neurons in both the PVH and SO receive similar monosynaptic inputs from a subset of the nine circuits mainly in the thalamic, hypothalamic, and cerebral nuclei areas. Our results suggest that PVH-Oxt neurons serve as a central modulator to integrate external and internal information via largely reciprocal connection with the nine circuits while the SO-Oxt neurons act mainly as unidirectional Oxt hormonal output. In summary, our Oxt wiring diagram provides anatomic insights about distinct behavioral functions of Oxt signaling in the brain.SIGNIFICANCE STATEMENT Oxytocin (Oxt) neurons regulate diverse physiological functions from prosocial behavior to pain sensation via central projection in the brain. Thus, understanding detailed anatomic connectivity of Oxt neurons can provide insight on circuit-specific roles of Oxt signaling in regulating different physiological functions. Here, we use high-resolution mapping methods to describe the 3D distribution, monosynaptic input and long-range output of Oxt neurons, and their relationship with Oxt receptor (Oxtr) expression across the entire mouse brain. We found Oxt connections with nine functional circuits controlling cognition, brain state, and somatic visceral response. Furthermore, we identified a quantitatively unmatched Oxt-Oxtr relationship, suggesting broad indirect Oxt signaling. Together, our comprehensive Oxt wiring diagram advances our understanding of circuit-specific roles of Oxt neurons.

Anatomical and functional coupling between the dorsal and ventral attention networks.

Studies have indicated that the dorsal attention network (DAN) and the ventral attention network (VAN) functionally interact via several fronto-parietal connector hubs. However, the anatomical connectivity profiles of these connector hubs, and the coupling between the anatomical and functional connectivities of them, are still unknown. In the present study, we found that functional connector hubs anatomically bridged the DAN and VAN based on multimodal magnetic resonance imaging data from the Human Connectome Project (HCP) Consortium and an independent Chinese cohort. The three hubs had unique anatomical connectivity patterns with the attention sub-networks. For each connector hub, the pattern of anatomical connectivity resembled the functional one. Finally, the strength of the anatomical connectivity of these connector hubs was positively associated with the functional connectivity at the group- and individual-levels. Our findings help to better understand the anatomical mechanisms underlying the functional interactions between the DAN and the VAN.

Anatomical connectivity and efficacy of electro-therapy for seizure control: A SANTE's single-center regression analyses.

OBJECTIVE: To assess based on a single-center data from a multicenter trial (Stimulation of the Anterior Nucleus for the Thalamus for Epilepsy (SANTE)), the role of anatomical connectivity and other factors (e.g., stimulating electrode placement) on efficacy of electro-therapy of the anterior thalamic nuclei (ATN), a node in Papez network, on pharmaco-resistant seizures. DATA SOURCE: Adults with at least 6 seizures /month were enrolled in this trial. Percent seizure reduction was compared between subjects with seizures emerging inside Papez's network (IPN) to those with seizures outside it (OPN). Statistical analyses were performed on the first year of the trial. RESULTS: Data from 11 subjects were analyzed. At Year 1, median seizure reduction was 80.5% (-100% to -40.3%) in 8/11 subjects with seizures IPN, vs. 52.8% (-61.4% to -23.7%) for 3/11 subjects with seizures OPN (2-sided Wilcoxon p = 0.08). At year 7, 3/11 subjects with seizures IPN had been seizure free for several years vs. 0/11 subjects with seizures OPN. Addition of 4 subjects from a pilot trial with nearly identical protocol to SANTE's, increased to 12/15 the number of subjects with seizures IPN. A 2-sided Fisher's exact test applied to seizure frequency reduction in the 12/15 cohort compared to the 3/15 with seizures OPN, showed significant (p = 0.04) differences in efficacy at the 70% seizure reduction rate. Median quality of life (QOL) scores for subjects with seizures IPN improved by 81% vs. 53% for subjects with seizures OPN. No other factors (e.g., current intensity) had a statistically significant effect on efficacy. CONCLUSIONS: Degree of anatomical connectivity between stimulation targets and epileptogenic networks (ENs) plays an important role in therapeutic efficacy. This may be explained by the minimization of signal attenuation inherent in impulse transmission in nervous tissue partly as a function of fiber tract length, tissue anisotropy, and number of synaptic relays between stimulation target and epileptogenic networks.

Hierarchy of Connectivity-Function Relationship of the Human Cortex Revealed through Predicting Activity across Functional Domains.

Many studies showed that anatomical connectivity supports both anatomical and functional hierarchies that span across the primary and association cortices in the cerebral cortex. Even though a structure-function relationship has been indicated to uncouple in the association cortex, it is still unknown whether anatomical connectivity can predict functional activations to the same degree throughout the cortex, and it remains unclear whether a hierarchy of this connectivity-function relationship (CFR) exists across the human cortex. We first addressed whether anatomical connectivity could be used to predict functional activations across different functional domains using multilinear regression models. Then, we characterized the CFR by predicting activity from anatomical connectivity throughout the cortex. We found that there is a hierarchy of CFR between sensory-motor and association cortices. Moreover, this CFR hierarchy was correlated to the functional and anatomical hierarchies, respectively, reflected in functional flexibility and the myelin map. Our results suggest a shared hierarchical mechanism in the cortex, a finding which provides important insights into the anatomical and functional organizations of the human brain.

Comparison of resting-state functional connectivity in marmosets with tracer-based cellular connectivity.

Resting-state functional MRI (RS-fMRI) is widely used to assess how strongly different brain areas are connected. However, this connection obtained by RS-fMRI, which is called functional connectivity (FC), simply refers to the correlation of blood oxygen level-dependent (BOLD) signals across time it has yet to be quantified how accurately FC reflects cellular connectivity (CC). In this study, we elucidated this relationship using RS-fMRI and quantitative tracer data in marmosets. In addition, we also elucidated the effects of distance between two brain regions on the relationship between FC and CC across seed region. To calculate FC, we used full correlation approach that is considered to reflect not only direct (monosynaptic connections) but also indirect pathways (polysynaptic connections). Our main findings are that: (1) overall FC obtained by RS-fMRI was highly correlated with tracer-based CC, but correlation coefficients varied remarkably across seed regions; (2) the strength of FC decreased with increase in the distance between two regions; (3) correlation coefficients between FC and CC after regressing out the effects of the distance between two regions still varied across seed regions, but some regions have strong correlations. These findings suggest that although FC reflects the strength of monosynaptic pathways, it is strongly affected by the distance between regions.

Anterior Intraparietal Area: A Hub in the Observed Manipulative Action Network.

Current knowledge regarding the processing of observed manipulative actions (OMAs) (e.g., grasping, dragging, or dropping) is limited to grasping and underlying neural circuitry remains controversial. Here, we addressed these issues by combining chronic neuronal recordings along the anteroposterior extent of monkeys' anterior intraparietal (AIP) area with tracer injections into the recorded sites. We found robust neural selectivity for 7 distinct OMAs, particularly in the posterior part of AIP (pAIP), where it was associated with motor coding of grip type and own-hand visual feedback. This cluster of functional properties appears to be specifically grounded in stronger direct connections of pAIP with the temporal regions of the ventral visual stream and the prefrontal cortex, as connections with skeletomotor related areas and regions of the dorsal visual stream exhibited opposite or no rostrocaudal gradients. Temporal and prefrontal areas may provide visual and contextual information relevant for manipulative action processing. These results revise existing models of the action observation network, suggesting that pAIP constitutes a parietal hub for routing information about OMA identity to the other nodes of the network.

Correlated Gene Expression and Anatomical Communication Support Synchronized Brain Activity in the Mouse Functional Connectome.

Cognition and behavior depend on synchronized intrinsic brain activity that is organized into functional networks across the brain. Research has investigated how anatomical connectivity both shapes and is shaped by these networks, but not how anatomical connectivity interacts with intra-areal molecular properties to drive functional connectivity. Here, we present a novel linear model to explain functional connectivity by integrating systematically obtained measurements of axonal connectivity, gene expression, and resting-state functional connectivity MRI in the mouse brain. The model suggests that functional connectivity arises from both anatomical links and inter-areal similarities in gene expression. By estimating these effects, we identify anatomical modules in which correlated gene expression and anatomical connectivity support functional connectivity. Along with providing evidence that not all genes equally contribute to functional connectivity, this research establishes new insights regarding the biological underpinnings of coordinated brain activity measured by BOLD fMRI.SIGNIFICANCE STATEMENT Efforts at characterizing the functional connectome with fMRI have risen exponentially over the last decade. Yet despite this rise, the biological underpinnings of these functional measurements are still primarily unknown. The current report begins to fill this void by investigating the molecular underpinnings of the functional connectome through an integration of systematically obtained structural information and gene expression data throughout the rodent brain. We find that both white matter connectivity and similarity in regional gene expression relate to resting-state functional connectivity. The current report furthers our understanding of the biological underpinnings of the functional connectome and provides a linear model that can be used to streamline preclinical animal studies of disease.

Corresponding anatomical and coactivation architecture of the human precuneus showing similar connectivity patterns with macaques.

The precuneus (PCun) is one of the most expanded areas of the association cortex and plays an important role in integrating information from different modalities. However, whether the functional architecture of PCun is shared by humans and macaques is an open question. We used both anatomical connectivity and task-dependent coactivation patterns to parcellate the human PCun and consistently identified three subregions in the human PCun using two independent datasets. Two subregions were located in the dorsal PCun and one subregion was located in the ventral PCun. This parcellation scheme for the PCun was supported by identifying the subregion-specific networks and by functional characterization. Then, the absolute and relative gray matter volume of precuneus in human and macaque was calculated and significantly smaller absolute and relative gray matter volume in macaque was identified. Next, three macaque PCun subregions were defined based on our tractographic atlas. Finally, the whole brain anatomical connectivity patterns and connectivity fingerprints with 17 predefined homologous target brain areas were mapped for each PCun subregion and revealed that the PCun shares similar anatomical connectivity patterns in humans and macaques. The similar anatomical connectivity patterns of PCun were validated by an independent in-house dataset. Our findings demonstrated that anatomical connectivity patterns can reflect the functional architecture of the PCun in humans and that the functional architecture of the PCun is similar in humans and macaques.

Parcellation of Macaque Cortex with Anatomical Connectivity Profiles.

The macaque model has been widely used to investigate the brain mechanisms of specific cognitive functions and psychiatric disorders. However, a detailed functional architecture map of the macaque cortex in vivo is still lacking. Here, we aimed to construct a new macaque cortex atlas based on its anatomical connectivity profiles using in vivo diffusion MRI. First, we defined the macaque cortical seed areas using the NeuroMaps atlas. Then, we applied the anatomical connectivity patterns-based parcellation approach to parcellate the macaque cortex into 80 subareas in each hemisphere, which were approximately symmetric between the two hemispheres. In each hemisphere, we identified 14 subareas in the frontal cortex, 9 subareas in the somatosensory cortex, 13 subareas in the parietal cortex, 16 subareas in the temporal cortex, 16 subareas in the occipital cortex, and 12 subareas in the limbic system. Finally, the graph-based network analyses of the anatomical network based on newly constructed macaque cortex atlas identified seven hub areas including bilateral ventral premotor cortex, bilateral superior parietal lobule, right medial precentral gyrus, and right precuneus. This newly constructed macaque cortex atlas may facilitate studies of the structure and functions of the macaque brain in the future.

Organization of cortico-cortical pathways supporting memory retrieval across subregions of the left ventrolateral prefrontal cortex.

Functional magnetic resonance imaging (fMRI) evidence indicates that different subregions of ventrolateral prefrontal cortex (VLPFC) participate in distinct cortical networks. These networks have been shown to support separable cognitive functions: anterior VLPFC [inferior frontal gyrus (IFG) pars orbitalis] functionally correlates with a ventral fronto-temporal network associated with top-down influences on memory retrieval, while mid-VLPFC (IFG pars triangularis) functionally correlates with a dorsal fronto-parietal network associated with postretrieval control processes. However, it is not known to what extent subregional differences in network affiliation and function are driven by differences in the organization of underlying white matter pathways. We used high-angular-resolution diffusion spectrum imaging and functional connectivity analysis in unanesthetized humans to address whether the organization of white matter connectivity differs between subregions of VLPFC. Our results demonstrate a ventral-dorsal division within IFG. Ventral IFG as a whole connects broadly to lateral temporal cortex. Although several different individual white matter tracts form connections between ventral IFG and lateral temporal cortex, functional connectivity analysis of fMRI data indicates that these are part of the same ventral functional network. By contrast, across subdivisions, dorsal IFG was connected with the midfrontal gyrus and correlated as a separate dorsal functional network. These qualitative differences in white matter organization within larger macroanatomical subregions of VLPFC support prior functional distinctions among these regions observed in task-based and functional connectivity fMRI studies. These results are consistent with the proposal that anatomical connectivity is a crucial determinant of systems-level functional organization of frontal cortex and the brain in general.

Linking macroscale graph analytical organization to microscale neuroarchitectonics in the macaque connectome.

Macroscale connectivity of the mammalian brain has been shown to display several characteristics of an efficient communication network architecture. In parallel, at the microscopic scale, histological studies have extensively revealed large interregional variation in cortical neural architectonics. However, how these two "scales" of cerebrum organization are linked remains an open question. Collating and combining data across multiple studies on the cortical cytoarchitecture of the macaque cortex with information on macroscale anatomical wiring derived from tract tracing studies, this study focuses on examining the interplay between macroscale organization of the macaque connectome and microscale cortical neuronal architecture. Our findings show that both macroscale degree as well as the topological role in the overall network are related to the level of neuronal complexity of cortical regions at the microscale, showing (among several effects) a positive overall association between macroscale degree and metrics of microscale pyramidal complexity. Macroscale hub regions, together forming a densely interconnected "rich club," are noted to display a high level of neuronal complexity, findings supportive of a high level of integrative neuronal processes to occur in these regions. Together, we report on cross-scale observations that jointly suggest that a region's microscale neuronal architecture is tuned to its role in the global brain network.

How local excitation-inhibition ratio impacts the whole brain dynamics.

The spontaneous activity of the brain shows different features at different scales. On one hand, neuroimaging studies show that long-range correlations are highly structured in spatiotemporal patterns, known as resting-state networks, on the other hand, neurophysiological reports show that short-range correlations between neighboring neurons are low, despite a large amount of shared presynaptic inputs. Different dynamical mechanisms of local decorrelation have been proposed, among which is feedback inhibition. Here, we investigated the effect of locally regulating the feedback inhibition on the global dynamics of a large-scale brain model, in which the long-range connections are given by diffusion imaging data of human subjects. We used simulations and analytical methods to show that locally constraining the feedback inhibition to compensate for the excess of long-range excitatory connectivity, to preserve the asynchronous state, crucially changes the characteristics of the emergent resting and evoked activity. First, it significantly improves the model's prediction of the empirical human functional connectivity. Second, relaxing this constraint leads to an unrealistic network evoked activity, with systematic coactivation of cortical areas which are components of the default-mode network, whereas regulation of feedback inhibition prevents this. Finally, information theoretic analysis shows that regulation of the local feedback inhibition increases both the entropy and the Fisher information of the network evoked responses. Hence, it enhances the information capacity and the discrimination accuracy of the global network. In conclusion, the local excitation-inhibition ratio impacts the structure of the spontaneous activity and the information transmission at the large-scale brain level.

Morphological covariance in anatomical MRI scans can identify discrete neural pathways in the brain and their disturbances in persons with neuropsychiatric disorders.

We hypothesize that coordinated functional activity within discrete neural circuits induces morphological organization and plasticity within those circuits. Identifying regions of morphological covariation that are independent of morphological covariation in other regions therefore may therefore allow us to identify discrete neural systems within the brain. Comparing the magnitude of these variations in individuals who have psychiatric disorders with the magnitude of variations in healthy controls may allow us to identify aberrant neural pathways in psychiatric illnesses. We measured surface morphological features by applying nonlinear, high-dimensional warping algorithms to manually defined brain regions. We transferred those measures onto the surface of a unit sphere via conformal mapping and then used spherical wavelets and their scaling coefficients to simplify the data structure representing these surface morphological features of each brain region. We used principal component analysis (PCA) to calculate covariation in these morphological measures, as represented by their scaling coefficients, across several brain regions. We then assessed whether brain subregions that covaried in morphology, as identified by large eigenvalues in the PCA, identified specific neural pathways of the brain. To do so, we spatially registered the subnuclei for each eigenvector into the coordinate space of a Diffusion Tensor Imaging dataset; we used these subnuclei as seed regions to track and compare fiber pathways with known fiber pathways identified in neuroanatomical atlases. We applied these procedures to anatomical MRI data in a cohort of 82 healthy participants (42 children, 18 males, age 10.5 ± 2.43 years; 40 adults, 22 males, age 32.42 ± 10.7 years) and 107 participants with Tourette's Syndrome (TS) (71 children, 59 males, age 11.19 ± 2.2 years; 36 adults, 21 males, age 37.34 ± 10.9 years). We evaluated the construct validity of the identified covariation in morphology using DTI data from a different set of 20 healthy adults (10 males, mean age 29.7 ± 7.7 years). The PCA identified portions of structures that covaried across the brain, the eigenvalues measuring the magnitude of the covariation in morphology along the respective eigenvectors. Our results showed that the eigenvectors, and the DTI fibers tracked from their associated brain regions, corresponded with known neural pathways in the brain. In addition, the eigenvectors that captured morphological covariation across regions, and the principal components along those eigenvectors, identified neural pathways with aberrant morphological features associated with TS. These findings suggest that covariations in brain morphology can identify aberrant neural pathways in specific neuropsychiatric disorders.

MEG source reconstruction based on identification of directed source interactions on whole-brain anatomical networks.

We present an MEG source reconstruction method that simultaneously reconstructs source amplitudes and identifies source interactions across the whole brain. In the proposed method, a full multivariate autoregressive (MAR) model formulates directed interactions (i.e., effective connectivity) between sources. The MAR coefficients (the entries of the MAR matrix) are constrained by the prior knowledge of whole-brain anatomical networks inferred from diffusion MRI. Moreover, to increase the accuracy and robustness of our method, we apply an fMRI prior on the spatial activity patterns and a sparse prior on the MAR coefficients. The observation process of MEG data, the source dynamics, and a series of the priors are combined into a Bayesian framework using a state-space representation. The parameters, such as the source amplitudes and the MAR coefficients, are jointly estimated from a variational Bayesian learning algorithm. By formulating the source dynamics in the context of MEG source reconstruction, and unifying the estimations of source amplitudes and interactions, we can identify the effective connectivity without requiring the selection of regions of interest. Our method is quantitatively and qualitatively evaluated on simulated and experimental data, respectively. Compared with non-dynamic methods, in which the interactions are estimated after source reconstruction with no dynamic constraints, the proposed dynamic method improves most of the performance measures in simulations, and provides better physiological interpretation and inter-subject consistency in real data applications.

Determination of the posterior boundary of Wernicke's area based on multimodal connectivity profiles.

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

Insight and psychosis: Functional and anatomical brain connectivity and self-reflection in Schizophrenia.

Impaired insight into illness, associated with worse treatment outcome, is common in schizophrenia. Insight has been related to the self-reflective processing, centred on the medial frontal cortex. We hypothesized that anatomical and functional routes to and from the ventromedial prefrontal cortex (vmPFC) would differ in patients according to their degree of impaired insight. Forty-five schizophrenia patients and 19 healthy subjects performed a self-reflection task during fMRI, and underwent diffusion tensor imaging. Using dynamic causal modelling we observed increased effective connectivity from the posterior cingulate cortex (PCC), inferior parietal lobule (IPL), and dorsal mPFC (dmPFC) towards the vmPFC with poorer insight and decrease from vmPFC to the IPL. Stronger connectivity from the PCC to vmPFC during judgment of traits related to self was associated with poorer insight. We found small-scale significant changes in white matter integrity associated with clinical insight. Self-reflection may be influenced by synaptic changes that lead to the observed alterations in functional connectivity accompanied by the small-scale but measurable alterations in anatomical connections. Our findings may point to a neural compensatory response to an impairment of connectivity between self-processing regions. Similarly, the observed hyper-connectivity might be a primary deficit linked to inefficiency in the component cognitive processes that lead to impaired insight. We suggest that the stronger cognitive demands placed on patients with poor insight is reflected in increased effective connectivity during the task in this study.

Post-treatment alterations in white matter integrity in PTSD: Effects on symptoms and functional connectivity a secondary analysis of an RCT.

Post-traumatic stress disorder (PTSD) has been linked to altered communication within the limbic system, including reduced structural connectivity in the uncinate fasciculus (UNC; i.e., decreased fractional anisotropy; FA) and reduced resting-state functional connectivity (RSFC) between the hippocampus and ventromedial prefrontal cortex (vmPFC). Previous research has demonstrated attenuation of PTSD symptoms and alterations in RSFC following exposure-based psychotherapy. However, the relationship between changes in structural and functional connectivity patterns and PTSD symptoms following treatment remains unclear. To investigate this, we conducted a secondary analysis of data from a randomized clinical trial of intensive exposure therapy, evaluating alterations in UNC FA, hippocampus-vmPFC RSFC, and PTSD symptoms before (pre-treatment), 7 days after (post-treatment), and 30 days after (follow-up) the completion of therapy. Our results showed that post-treatment changes in RSFC were positively correlated with post-treatment and follow-up changes in UNC FA and that post-treatment changes in UNC FA were positively correlated with post-treatment and follow-up changes in PTSD symptoms. These findings suggest that early changes in functional connectivity are associated with sustained changes in anatomical connectivity, which in turn are linked to reduced PTSD symptom severity.