Functional topography of the thalamocortical system in human

Hyperactivity of the medial thalamus in patients with photophobia-associated migraine

OBJECTIVE

To examine cerebral functional alterations associated with sensory processing in patients with migraine and constant photophobia.

BACKGROUND

Migraine is a common headache disorder that presents with photophobia in many patients during attacks. Furthermore, some patients with migraine experience constant photophobia, even during headache-free intervals, leading to a compromised quality of life.

METHODS

This prospective, case-control study included 40 patients with migraine (18 male and 22 female) who were recruited at an eye hospital and eye clinic. The patients were divided into two groups: migraine with photophobia group, consisting of 22 patients (10 male and 12 female) with constant photophobia, and migraine without photophobia group, consisting of 18 patients (eight male and 10 female) without constant photophobia. We used 18F-fluorodeoxyglucose and positron emission tomography to compare cerebral glucose metabolism between the two patient groups and 42 healthy participants (16 men and 26 women).

RESULTS

Compared with the healthy group, both the migraine with photophobia and migraine without photophobia groups showed cerebral glucose hypermetabolism in the bilateral thalamus (p < 0.05, family-wise error-corrected). Moreover, the contrast of migraine with photophobia minus migraine without photophobia patients showed glucose hypermetabolism in the bilateral medial thalamus (p < 0.05, family-wise error-corrected).

CONCLUSIONS

The medial thalamus may be associated with the development of continuous photophobia in patients with migraine.

A Prelimbic Cortex-Thalamus Circuit Bidirectionally Regulates Innate and Stress-Induced Anxiety-Like Behavior

Anxiety-related disorders respond to cognitive behavioral therapies, which involved the medial prefrontal cortex (mPFC). Previous studies have suggested that subregions of the mPFC have different and even opposite roles in regulating innate anxiety. However, the specific causal targets of their descending projections in modulating innate anxiety and stress-induced anxiety have yet to be fully elucidated. Here, we found that among the various downstream pathways of the prelimbic cortex (PL), a subregion of the mPFC, PL-mediodorsal thalamic nucleus (MD) projection, and PL-ventral tegmental area (VTA) projection exhibited antagonistic effects on anxiety-like behavior, while the PL-MD projection but not PL-VTA projection was necessary for the animal to guide anxiety-related behavior. In addition, MD-projecting PL neurons bidirectionally regulated remote but not recent fear memory retrieval. Notably, restraint stress induced high-anxiety state accompanied by strengthening the excitatory inputs onto MD-projecting PL neurons, and inhibiting PL-MD pathway rescued the stress-induced anxiety. Our findings reveal that the activity of PL-MD pathway may be an essential factor to maintain certain level of anxiety, and stress increased the excitability of this pathway, leading to inappropriate emotional expression, and suggests that targeting specific PL circuits may aid the development of therapies for the treatment of stress-related disorders.

Changes in Spatiotemporal Dynamics of Default Network Oscillations between 19 and 29 Years of Age

The exploration of functional resting-state brain developmental parameters and measures can help to improve scientific, psychological, and medical applications. The present work focussed on both traditional approaches, such as topographical power analyses at the signal space level, and advanced approaches, such as the exploration of age-related dynamics of source space data. The results confirmed the expectation that the third life decade would show a kind of stability in oscillatory signal and source-space-related parameters. However, from a source dynamics perspective, different frequency ranges appear to develop quite differently, as reflected in age-related sequential network communication profiles. Among other discoveries, the left anterior cingulate source location could be shown to reduce bi-directional network communication in the lower alpha band, whereas it differentiated its uni- and bidirectional communication dynamics to sub-cortical and posterior brain locations. Higher alpha oscillations enhanced communication dynamics between the thalamus and particularly frontal areas. In conclusion, resting-state data appear to be, at least in part, functionally reorganized in the default mode network, while quantitative measures, such as topographical power and regional source activity, did not correlate with age in the third life decade. In line with other authors, we suggest the further development of a multi-perspective approach in biosignal analyses.

Not Just a Mood Disorder─Is Depression a Neurodevelopmental, Cognitive Disorder? Focus on Prefronto-Thalamic Circuits

Depression is one of the most burdensome psychiatric disorders, affecting hundreds of millions of people worldwide. The disease is characterized not only by severe emotional and affective impairments, but also by disturbed vegetative and cognitive functions. Although many candidate mechanisms have been proposed to cause the disease, the pathophysiology of cognitive impairments in depression remains unclear. In this article, we aim to assess the link between cognitive alterations in depression and possible developmental changes in neuronal circuit wiring during critical periods of susceptibility. We review the existing literature and propose a role of serotonin signaling during development in shaping the functional states of prefrontal neuronal circuits and prefronto-thalamic loops. We discuss how early life insults affecting the serotonergic system could be important in the alterations of these local and long-range circuits, thus favoring the emergence of neurodevelopmental disorders, such as depression.

A three-dimensional model of neural activity and phenomenal-behavioral patterns

How phenomenal experience and behavior are related to neural activity in physiology and psychopathology represents a fundamental question in neuroscience and psychiatry. The phenomenal-behavior patterns may be deconstructed into basic dimensions, i.e., psychomotricity, affectivity, and thought, which might have distinct neural correlates. This work provides a data overview on the relationship of these phenomenal-behavioral dimensions with brain activity across physiological and pathological conditions (including major depressive disorder, bipolar disorder, schizophrenia, attention-deficit/hyperactivity disorder, anxiety disorders, addictive disorders, Parkinson's disease, Tourette syndrome, Alzheimer's disease, and frontotemporal dementia). Accordingly, we propose a three-dimensional model of neural activity and phenomenal-behavioral patterns. In this model, neural activity is organized into distinct units in accordance with connectivity patterns and related input/output processing, manifesting in the different phenomenal-behavioral dimensions. (1) An external neural unit, which involves the sensorimotor circuit/brain's sensorimotor network and is connected with the external environment, processes external inputs/outputs, manifesting in the psychomotor dimension (processing of exteroception/somatomotor activity). External unit hyperactivity manifests in psychomotor excitation (hyperactivity/hyperkinesia/catatonia), while external unit hypoactivity manifests in psychomotor inhibition (retardation/hypokinesia/catatonia). (2) An internal neural unit, which involves the interoceptive-autonomic circuit/brain's salience network and is connected with the internal/body environment, processes internal inputs/outputs, manifesting in the affective dimension (processing of interoception/autonomic activity). Internal unit hyperactivity manifests in affective excitation (anxiety/dysphoria-euphoria/panic), while internal unit hypoactivity manifests in affective inhibition (anhedonia/apathy/depersonalization). (3) An associative neural unit, which involves the brain's associative areas/default-mode network and is connected with the external/internal units (but not with the environment), processes associative inputs/outputs, manifesting in the thought dimension (processing of ideas). Associative unit hyperactivity manifests in thought excitation (mind-wandering/repetitive thinking/psychosis), while associative unit hypoactivity manifests in thought inhibition (inattention/cognitive deficit/consciousness loss). Finally, these neural units interplay and dynamically combine into various neural states, resulting in the complex phenomenal experience and behavior across physiology and neuropsychiatric disorders.

Aberrant dynamic functional connectivity of thalamocortical circuitry in major depressive disorder

Thalamocortical circuitry has a substantial impact on emotion and cognition. Previous studies have demonstrated alterations in thalamocortical functional connectivity (FC), characterized by region-dependent hypo- or hyper-connectivity, among individuals with major depressive disorder (MDD). However, the dynamical reconfiguration of the thalamocortical system over time and potential abnormalities in dynamic thalamocortical connectivity associated with MDD remain unclear. Hence, we analyzed dynamic FC (dFC) between ten thalamic subregions and seven cortical subnetworks from resting-state functional magnetic resonance images of 48 patients with MDD and 57 healthy controls (HCs) to investigate time-varying changes in thalamocortical FC in patients with MDD. Moreover, dynamic laterality analysis was conducted to examine the changes in functional lateralization of the thalamocortical system over time. Correlations between the dynamic measures of thalamocortical FC and clinical assessment were also calculated. We identified four dynamic states of thalamocortical circuitry wherein patients with MDD exhibited decreased fractional time and reduced transitions within a negative connectivity state that showed strong correlations with primary cortical networks, compared with the HCs. In addition, MDD patients also exhibited increased fluctuations in functional laterality in the thalamocortical system across the scan duration. The thalamo-subnetwork analysis unveiled abnormal dFC variability involving higher-order cortical networks in the MDD cohort. Significant correlations were found between increased dFC variability with dorsal attention and default mode networks and the severity of symptoms. Our study comprehensively investigated the pattern of alteration of the thalamocortical dFC in MDD patients. The heterogeneous alterations of dFC between the thalamus and both primary and higher-order cortical networks may help characterize the deficits of sensory and cognitive processing in MDD.

Longitudinal Development of Thalamocortical Functional Connectivity in 22q11.2 Deletion Syndrome

BACKGROUND

The 22q11.2 deletion syndrome (22qDel) is a genetic copy number variant that strongly increases risk for schizophrenia and other neurodevelopmental disorders. Disrupted functional connectivity between the thalamus and the somatomotor/frontoparietal cortex has been implicated in cross-sectional studies of 22qDel, idiopathic schizophrenia, and youths at clinical high risk for psychosis. Here, we used a novel functional atlas approach to investigate longitudinal age-related changes in network-specific thalamocortical functional connectivity (TCC) in participants with 22qDel and typically developing (TD) control participants.

METHODS

TCC was calculated for 9 functional networks derived from resting-state functional magnetic resonance imaging scans collected from 65 participants with 22qDel (63.1% female) and 69 demographically matched TD control participants (49.3% female) ages 6 to 23 years. Analyses included 86 longitudinal follow-up scans. Nonlinear age trajectories were characterized with generalized additive mixed models.

RESULTS

In participants with 22qDel, TCC in the frontoparietal network increased until approximately age 13, while somatomotor TCC and cingulo-opercular TCC decreased from age 6 to 23. In contrast, no significant relationships between TCC and age were found in TD control participants. Somatomotor connectivity was significantly higher in participants with 22qDel than in TD control participants in childhood, but lower in late adolescence. Frontoparietal TCC showed the opposite pattern.

CONCLUSIONS

22qDel is associated with aberrant development of functional network connectivity between the thalamus and cortex. Younger individuals with 22qDel have lower frontoparietal connectivity and higher somatomotor connectivity than control individuals, but this phenotype may normalize or partially reverse by early adulthood. Altered maturation of this circuitry may underlie elevated neuropsychiatric disease risk in this syndrome.

Functional connectome hierarchy of thalamus impacts fatigue in acute stroke patients

This study aimed to explore the topographic features of thalamic subregions, functional connectomes and hierarchical organizations between thalamus and cortex in poststroke fatigue patients. We consecutively recruited 121 acute ischemic stroke patients (mean age: 59 years) and 46 healthy controls matched for age, sex, and educational level. The mean age was 59 years (range 19-80) and 38% of acute stroke patients were females. Resting-state functional and structural magnetic resonance imaging were conducted on all participants. The fatigue symptoms were measured using the Fatigue Severity Scale. The thalamic functional subdivisions corresponding to the canonical functional network were defined using the winner-take-all parcellation method. Thalamic functional gradients were derived using the diffusion embedding analysis. The results suggested abnormal functional connectivity of thalamic subregions primarily located in the temporal lobe, posterior cingulate gyrus, parietal lobe, and precuneus. The thalamus showed a gradual increase from the medial to the lateral in all groups, but the right thalamus shifted more laterally in poststroke fatigue patients than in non- poststroke fatigue patients. Poststroke fatigue patients also had higher gradient scores in the somatomotor network and the right medial prefrontal and premotor thalamic regions, but lower values in the right lateral prefrontal thalamus. The findings suggested that poststroke fatigue patients had altered functional connectivity and thalamocortical hierarchical organizations, providing new insights into the neural mechanisms of the thalamus.

Organization of thalamocortical structural covariance and a corresponding 3D atlas of the mouse thalamus

For information from sensory organs to be processed by the brain, it is usually passed to appropriate areas of the cerebral cortex. Almost all of this information passes through the thalamus, a relay structure that reciprocally connects to the vast majority of the cortex. The thalamus facilitates this information transfer through a set of thalamocortical connections that vary in cellular structure, molecular profiles, innervation patterns, and firing rates. Additionally, corticothalamic connections allow for intracortical information transfer through the thalamus. These efferent and afferent connections between the thalamus and cortex have been the focus of many studies, and the importance of cortical connectivity in defining thalamus anatomy is demonstrated by multiple studies that parcellate the thalamus based on cortical connectivity profiles. Here, we examine correlated morphological variation between the thalamus and cortex, or thalamocortical structural covariance. For each voxel in the thalamus as a seed, we construct a cortical structural covariance map that represents correlated cortical volume variation, and examine whether high structural covariance is observed in cortical areas that are functionally relevant to the seed. Then, using these cortical structural covariance maps as features, we subdivide the thalamus into six non-overlapping regions (clusters of voxels), and assess whether cortical structural covariance is associated with cortical connectivity that specifically originates from these regions. We show that cortical structural covariance is high in areas of the cortex that are functionally related to the seed voxel, cortical structural covariance varies along cortical depth, and sharp transitions in cortical structural covariance profiles are observed when varying seed locations in the thalamus. Subdividing the thalamus based on structural covariance, we additionally demonstrate that the six thalamic clusters of voxels stratify cortical structural covariance along the dorsal-ventral, medial-lateral, and anterior-posterior axes. These cluster-associated structural covariance patterns are prominently detected in cortical regions innervated by fibers projecting out of their related thalamic subdivisions. Together, these results advance our understanding of how the thalamus and the cortex couple in their volumes. Our results indicate that these volume correlations reflect functional organization and structural connectivity, and further provides a novel segmentation of the mouse thalamus that can be used to examine thalamic structural variation and thalamocortical structural covariation in disease models.

The role of the primary sensorimotor system in generalized epilepsy: Evidence from the cerebello-cerebral functional integration

The interaction between cerebellum and cerebrum participates widely in function from motor processing to high-level cognitive and affective processing. Because of the motor symptom, idiopathic generalized epilepsy (IGE) patients with generalized tonic-clonic seizure have been recognized to associate with motor abnormalities, but the functional interaction in the cerebello-cerebral circuit is still poorly understood. Resting-state functional magnetic resonance imaging data were collected for 101 IGE patients and 106 healthy controls. The voxel-based functional connectivity (FC) between cerebral cortex and the cerebellum was contacted. The functional gradient and independent components analysis were applied to evaluate cerebello-cerebral functional integration on the voxel-based FC. Cerebellar motor components were further linked to cerebellar gradient. Results revealed cerebellar motor functional modules were closely related to cerebral motor components. The altered mapping of cerebral motor components to cerebellum was observed in motor module in patients with IGE. In addition, patients also showed compression in cerebello-cerebral functional gradient between motor and cognition modules. Interestingly, the contribution of the motor components to the gradient was unbalanced between bilateral primary sensorimotor components in patients: the increase was observed in cerebellar cognitive module for the dominant hemisphere primary sensorimotor, but the decrease was found in the cerebellar cognitive module for the nondominant hemisphere primary sensorimotor. The present findings suggest that the cerebral primary motor system affects the hierarchical architecture of cerebellum, and substantially contributes to the functional integration evidence to understand the motor functional abnormality in IGE patients.

Subcortical influences on the topology of cortical networks align with functional processing hierarchies

fMRI of the human brain reveals spatiotemporal patterns of functional connectivity (FC), forming distinct cortical networks. Lately, subcortical contributions to these configurations are receiving renewed interest, but investigations rarely focus explicitly on their effects on cortico-cortical FC. Here, we employ a straightforward multivariable approach and graph-theoretic tools to assess subcortical impact on topological features of cortical networks. Given recent evidence showing that structures like the thalamus and basal ganglia integrate input from multiple networks, we expect increased segregation between cortical networks after removal of subcortical effects on their FC patterns. We analyze resting state data of young and healthy participants (male and female; N = 100) from the human connectome project. We find that overall, the cortical network architecture becomes less segregated, and more integrated, when subcortical influences are accounted for. Underlying these global effects are the following trends: 'Transmodal' systems become more integrated with the rest of the network, while 'unimodal' networks show the opposite effect. For single nodes this hierarchical organization is reflected by a close correspondence with the spatial layout of the principal gradient of FC (Margulies et al., 2016). Lastly, we show that the limbic system is significantly less coherent with subcortical influences removed. The findings are validated in a (split-sample) replication dataset. Our results provide new insight regarding the interplay between subcortex and cortical networks, by putting the integrative impact of subcortex in the context of macroscale patterns of cortical organization.

Characterizing functional modules in the human thalamus: coactivation-based parcellation and systems-level functional decoding

The human thalamus relays sensory signals to the cortex and facilitates brain-wide communication. The thalamus is also more directly involved in sensorimotor and various cognitive functions but a full characterization of its functional repertoire, particularly in regard to its internal anatomical structure, is still outstanding. As a putative hub in the human connectome, the thalamus might reveal its functional profile only in conjunction with interconnected brain areas. We therefore developed a novel systems-level Bayesian reverse inference decoding that complements the traditional neuroinformatics approach towards a network account of thalamic function. The systems-level decoding considers the functional repertoire (i.e., the terms associated with a brain region) of all regions showing co-activations with a predefined seed region in a brain-wide fashion. Here, we used task-constrained meta-analytic connectivity-based parcellation (MACM-CBP) to identify thalamic subregions as seed regions and applied the systems-level decoding to these subregions in conjunction with functionally connected cortical regions. Our results confirm thalamic structure-function relationships known from animal and clinical studies and revealed further associations with language, memory, and locomotion that have not been detailed in the cognitive neuroscience literature before. The systems-level decoding further uncovered large systems engaged in autobiographical memory and nociception. We propose this novel decoding approach as a useful tool to detect previously unknown structure-function relationships at the brain network level, and to build viable starting points for future studies.

Aberrant cortico-thalamo-cerebellar network interactions and their association with impaired cognitive functioning in patients with schizophrenia

Evidence indicating abnormal functional connectivity (FC) among the cortex, thalamus, and cerebellum in schizophrenia patients has increased. However, the role of the thalamus and cerebellum when integrated into intrinsic networks and how those integrated networks interact in schizophrenia patients are largely unknown. We generated an integrative network map by merging thalamic and cerebellar network maps, which were parcellated using a winner-take-all approach, onto a cortical network map. Using cognitive networks, the default mode network (DMN), the dorsal attention network (DAN), the salience network (SAL), and the central executive network (CEN) as regions of interest, the FC of 48 schizophrenia patients was compared with that of 57 healthy controls (HCs). The association between abnormal FC and cognitive impairment was also investigated in patients. FC was lower between the SAL-CEN, SAL-DMN, and DMN-CEN and within-CEN in schizophrenia patients than in HCs. Hypoconnectivity between the DMN-CEN was correlated with impaired cognition in schizophrenia patients. Our findings broadly suggest the plausible role of the thalamus and cerebellum in integrative intrinsic networks in patients, which may contribute to the disrupted triple network and cognitive dysmetria in schizophrenia.

Thalamo-cortical and cerebello-cortical functional connectivity in development

The thalamus is a critical relay center for neural pathways involving sensory, motor, and cognitive functions, including cortico-striato-thalamo-cortical and cortico-ponto-cerebello-thalamo-cortical loops. Despite the importance of these circuits, their development has been understudied. One way to investigate these pathways in human development in vivo is with functional connectivity MRI, yet few studies have examined thalamo-cortical and cerebello-cortical functional connectivity in development. Here, we used resting-state functional connectivity to measure functional connectivity in the thalamus and cerebellum with previously defined cortical functional networks in 2 separate data sets of children (7-12 years old) and adults (19-40 years old). In both data sets, we found stronger functional connectivity between the ventral thalamus and the somatomotor face cortical functional network in children compared with adults, extending previous cortico-striatal functional connectivity findings. In addition, there was more cortical network integration (i.e. strongest functional connectivity with multiple networks) in the thalamus in children than in adults. We found no developmental differences in cerebello-cortical functional connectivity. Together, these results suggest different maturation patterns in cortico-striato-thalamo-cortical and cortico-ponto-cerebellar-thalamo-cortical pathways.

Thermoregulation and thermal sensation during whole-body water immersion at different water temperatures in healthy individuals: A scoping review

BACKGROUND

Severe thermal discomfort may increase risk of drowning due to hypothermia or hyperthermia from prolonged exposure to noxious water temperatures. The importance of using a behavioral thermoregulation model with thermal sensation may predict the thermal load that the human body receives when exposed to various immersive water conditions. However, there is no thermal sensation "gold standard" model specific for water immersion. This scoping review aims to present a comprehensive overview regarding human physiological and behavioral thermoregulation during whole-body water immersion and explore the feasibility for an accepted defined sensation scale for cold and hot water immersion.

METHODS

A standard literary search was performed on PubMed, Google Scholar, and SCOPUS. The words "Water Immersion," "Thermoregulation," "Cardiovascular responses" were used either as independent searched terms and MeSH terms (Medical Subject Headings) or in combination with other text words. The inclusion criteria for clinical trials terms to thermoregulatory measurements (core or skin temperature), whole-body immersion, 18-60 years old and healthy individuals. The prementioned data were analyzed narratively to achieve the overall study objective.

RESULTS

Twenty-three published articles fulfilled the review inclusion/exclusion criteria (with nine measured behavioral responses). Our outcomes illustrated a homogenous thermal sensation in a variety of water temperatures ranges, that was strongly associated with thermal balance, and observed different thermoregulatory responses. This scoping review highlights the impact of water immersion duration on human thermoneutral zone, thermal comfort zone, and thermal sensation.

CONCLUSION

Our findings enlighten the significance of thermal sensation as a health indicator for establishing a behavioral thermal model applicable for water immersion. This scoping review provides insight for the needed development of subjective thermal model of thermal sensation in relation to human thermal physiology specific to immersive water temperature ranges within and outside the thermal neutral and comfort zone.

Medio-dorsal thalamic dysconnectivity in chronic knee pain: A possible mechanism for negative affect and pain comorbidity

The reciprocal interaction between pain and negative affect is acknowledged but pain-related alterations in brain circuits involved in this interaction, such as the mediodorsal thalamus (MDThal), still require a better understanding. We sought to investigate the relationship between MDThal circuitry, negative affect and pain severity in chronic musculoskeletal pain. For these analyses, participants with chronic knee pain (CKP, n = 74) and without (n = 36) completed magnetic resonance imaging scans and questionnaires. Seed-based MDThal functional connectivity (FC) was compared between groups. Within CKP group, we assessed the interdependence of MDThal FC with negative affect. Finally, post hoc moderation analysis explored whether burden of pain influences affect-related MDThal FC. The CKP group showed altered MDThal FC to hippocampus, ventromedial prefrontal cortex and subgenual anterior cingulate. Furthermore, in CKP group, MDThal connectivity correlated significantly with negative affect in several brain regions, most notably the medial prefrontal cortex, and this association was stronger with increasing pain burden and absent in pain-free controls. In conclusion, we demonstrate mediodorsal thalamo-cortical dysconnectivity in chronic pain with areas linked to mood disorders and associations of MDThal FC with negative affect. Moreover, burden of pain seems to enhance affect sensitivity of MDThal FC. These findings suggest mediodorsal thalamic network changes as possible drivers of the detrimental interplay between chronic pain and negative affect.

Thalamocortical contributions to cognitive task activity

Thalamocortical interaction is a ubiquitous functional motif in the mammalian brain. Previously (Hwang et al., 2021), we reported that lesions to network hubs in the human thalamus are associated with multi-domain behavioral impairments in language, memory, and executive functions. Here, we show how task-evoked thalamic activity is organized to support these broad cognitive abilities. We analyzed functional magnetic resonance imaging (MRI) data from human subjects that performed 127 tasks encompassing a broad range of cognitive representations. We first investigated the spatial organization of task-evoked activity and found a basis set of activity patterns evoked to support processing needs of each task. Specifically, the anterior, medial, and posterior-medial thalamus exhibit hub-like activity profiles that are suggestive of broad functional participation. These thalamic task hubs overlapped with network hubs interlinking cortical systems. To further determine the cognitive relevance of thalamic activity and thalamocortical functional connectivity, we built a data-driven thalamocortical model to test whether thalamic activity can be used to predict cortical task activity. The thalamocortical model predicted task-specific cortical activity patterns, and outperformed comparison models built on cortical, hippocampal, and striatal regions. Simulated lesions to low-dimensional, multi-task thalamic hub regions impaired task activity prediction. This simulation result was further supported by profiles of neuropsychological impairments in human patients with focal thalamic lesions. In summary, our results suggest a general organizational principle of how the human thalamocortical system supports cognitive task activity.

Perspectives for the application of neurogenetic research in programming Neurorehabilitation

Certain genetic variants underlie the proper functioning of the nervous system. They affect the nervous system in all aspects - molecular, systemic, cognitive, computational and sensorimotor. The greatest changes in the nervous system take place in the process of its maturation in the period of psychomotor development, as well as during neurorehabilitation, the task of which is to rebuild damaged neuronal pathways, e.g. by facilitating movement or training cognitive functions. Certain genetic polymorphisms affect the effectiveness of the processes of reconstruction or restoration of neural structures, which is clearly reflected in the effects of neurorehabilitation. This review presents the perspectives for the application of neurogenetic research in programming neurorehabilitation by determining the relationship of as many as 16 different genetic polymorphisms with specific functions of importance in rehabilitation. Thanks to this broad view, it may be possible to predict the effectiveness of rehabilitation on the basis of genetic testing, which would significantly contribute to the development of personalized medicine and to the optimal management of medical services in healthcare systems.

Thalamo-cortical inter-subject functional correlation during movie watching across the adult lifespan

An increasing number of studies have shown that the functional interactions between the thalamus and cerebral cortices play an important role in cognitive function and are influenced by age. Previous studies have revealed age-related changes in the thalamo-cortical system within individuals, while neglecting differences between individuals. Here, we characterized inter-subject functional correlation (ISFC) between the thalamus and several cortical brain networks in 500 healthy participants aged 18–87 years old from the Cambridge Centre for Aging and Neuroscience (Cam-CAN) cohort using movie-watching state fMRI data. General linear models (GLM) were performed to assess age-related changes in ISFC of thalamo-cortical networks and the relationship between ISFC and fluid intelligence. We found significant age-related decreases in ISFC between the posterior thalamus (e.g., ventral posterior nucleus and pulvinar) and the attentional network, sensorimotor network, and visual network (FDR correction with p &lt; 0.05). Meanwhile, the ISFC between the thalamus (mainly the mediodorsal nucleus and ventral thalamic nuclei) and higher-order cortical networks, including the default mode network, salience network and control network, showed complex changes with age. Furthermore, the altered ISFC of thalamo-cortical networks was positively correlated with decreased fluid intelligence (FDR correction with p &lt; 0.05). Overall, our results provide further evidence that alterations in the functional integrity of the thalamo-cortical system might play an important role in cognitive decline during aging.

Dynamic and stationary brain connectivity during movie watching as revealed by functional MRI

Spatially remote brain regions show synchronized activity as typically revealed by correlated functional MRI (fMRI) signals. An emerging line of research has focused on the temporal fluctuations of connectivity; however, its relationships with stationary connectivity have not been clearly illustrated. We examined dynamic and stationary connectivity when the participants watched four different movie clips. We calculated point-by-point multiplication between two regional time series to estimate the time-resolved dynamic connectivity, and estimated the inter-individual consistency of the dynamic connectivity time series. Widespread consistent dynamic connectivity was observed for each movie clip, which also showed differences between the clips. For example, a cartoon movie clip, Wall-E, showed more consistent of dynamic connectivity with the posterior cingulate cortex and supramarginal gyrus, while a court drama clip, A Few Good Men, showed more consistent of dynamic connectivity with the auditory cortex and temporoparietal junction, which might suggest the involvement of specific brain processing for different movie contents. In contrast, the stationary connectivity as measured by the correlations between regional time series was highly similar among the movie clips, and showed fewer statistically significant differences. The patterns of consistent dynamic connectivity could be used to classify different movie clips with higher accuracy than the stationary connectivity and regional activity. These results support the functional significance of dynamic connectivity in reflecting functional brain changes, which could provide more functionally relevant information than stationary connectivity.

Cognitive outcome is related to functional thalamo-cortical connectivity after pediatric stroke

The thalamus has complex connections with the cortex and is involved in various cognitive processes. Despite increasing interest in the thalamus and the underlying thalamo-cortical interaction, little is known about thalamo-cortical connections after pediatric arterial ischemic stroke. Therefore, the aim of this study was to investigate thalamo-cortical connections and their association with cognitive performance after arterial ischemic stroke.

Twenty patients in the chronic phase after pediatric arterial ischemic stroke (≥ 2 years after diagnosis, diagnosed &lt;16 years; aged 5–23 years, mean 15.1 years) and twenty healthy controls matched for age and sex were examined in a cross-sectional study design. Cognitive performance (selective attention, inhibition, working memory, and cognitive flexibility) was evaluated using standardized neuropsychological tests. Resting-state functional magnetic resonance imaging was used to examine functional thalamo-cortical connectivity. Lesion masks were integrated in the preprocessing pipeline to ensure that structurally damaged voxels did not influence functional connectivity analyses.

Cognitive performance (selective attention, inhibition and working memory) was significantly reduced in patients compared to controls. Network analyses revealed significantly lower thalamo-cortical connectivity for the motor, auditory, visual, default mode network, salience, left/right executive and dorsal attention network in patients compared to controls. Interestingly, analyses revealed as well higher thalamo-cortical connectivity in some subdivisions of the thalamus for the default mode network (medial nuclei), motor (lateral nuclei), dorsal attention (anterior nuclei), and the left executive network (posterior nuclei) in patients compared to controls. Increased and decreased thalamo-cortical connectivity strength within the same networks was, however, found in different thalamic sub-divisions. Thus, alterations in thalamo-cortical connectivity strength after pediatric stroke seem to point in both directions, with stronger as well as weaker thalamo-cortical connectivity in patients compared to controls. Multivariate linear regression, with lesion size and age as covariates, revealed significant correlations between cognitive performance (selective attention, inhibition, and working memory) and the strength of thalamo-cortical connectivity in the motor, auditory, visual, default mode network, posterior default mode network, salience, left/right executive, and dorsal attention network after childhood stroke.

Our data suggest that the interaction between different sub-nuclei of the thalamus and several cortical networks relates to post-stroke cognition. The variability in cognitive outcomes after pediatric stroke might partly be explained by functional thalamo-cortical connectivity strength.

Neural network of bipolar disorder: Toward integration of neuroimaging and neurocircuit-based treatment strategies

Bipolar disorder (BD) is a complex psychiatric disorder characterized by dysfunctions in three domains including emotional processing, cognitive processing, and psychomotor dimensions. However, the neural underpinnings underlying these clinical profiles are not well understood. Based on the reported data, we hypothesized that (i) the core neuropathology in BD is damage in fronto-limbic network, which is associated with emotional dysfunction; (ii) changes in intrinsic brain network, such as sensorimotor network, salience network, default-mode network, central executive network are associated with impaired cognition function; and (iii) beyond the dopaminergic-driven basal ganglia-thalamo-cortical motor circuit modulated by other neurotransmitter systems, such as serotonin (subcortical-cortical modulation), the sensorimotor network and related motor function modulated by other non-motor networks such as the default-mode network are involved in psychomotor function. In this review, we propose a neurocircuit-based clinical characteristics and taxonomy to guide the treatment of BD. We draw on findings from neuropsychological and neuroimaging studies in BD and link variations in these clinical profiles to underlying neurocircuit dysfunctions. We consider pharmacological, psychotherapy, and neuromodulatory treatments that could target those specific neurocircuit dysfunctions in BD. Finally, it is suggested that the methods of testing the neurocircuit-based taxonomy and important limitations to this approach should be considered in future.

Use of machine learning in predicting the efficacy of repetitive transcranial magnetic stimulation on treating depression based on functional and structural thalamo-prefrontal connectivity: A pilot study

Repetitive transcranial magnetic stimulation (rTMS) is a noninvasive, safe, and efficacious treatment for major depressive disorder (MDD). However, the antidepressant efficacy of rTMS greatly varies across individual patients. Thus, markers that can be used to predict the outcome of rTMS treatment at the individual level must be identified. Thalamo-cortical connectivity was abnormal in patients with MDD, and was normalized after rTMS treatment. In the current study, we investigated whether the resting-state functional and structural thalamo-cortical connectivity could be utilized to predict the rTMS treatment efficacy by employing support vector machine regression analysis. Results showed that the Hamilton Depression Scale scores of patients with MDD decreased after rTMS treatment. The functional connectivity of mediodorsal nucleus with prefrontal cortex predicted the rTMS treatment improvement, whereas the functional connectivity of other thalamic nuclei with cerebral cortex did not predict the treatment efficacy. The brain areas that contributed the most to the prediction were dorsal lateral prefrontal cortex, ventral lateral, and orbital and medial prefrontal areas. The improvement in the outcome of rTMS treatment could also be predicted by the thalamo-prefrontal structural connectivity. No statistically significantly difference in thalamo-cortical connectivity was observed between early improvers and early non-improvers. These results suggested that the thalamo-prefrontal connectivity can predict the rTMS treatment improvement. This study highlighted the crucial role of the thalamo-prefrontal connectivity as a neuroimaging marker in the treatment of depression via rTMS.

Tracing the psychopathology of bipolar disorder to the functional architecture of intrinsic brain activity and its neurotransmitter modulation: a three-dimensional model

Bipolar disorder (BD) shows complex alterations in psychomotor, affective, and thought dimensions, as described by Kraepelin in his fundamental model of manic-depressive illness. In turn, the expression of behavioral/phenomenological dimensions is traceable to intrinsic brain activity. We reported a data overview on intrinsic brain functioning and its changes in BD. Accordingly, we proposed a three-dimensional model of the relationship between brain functioning and behavioral/phenomenological patterns, along with its application to BD. In this model, intrinsic brain activity is organized in distinct units in accordance to connectivity patterns and related setting of input/output processing, underlying the different behavioral/phenomenological dimensions. An external unit (mainly involving the sensorimotor network) is connected with the external environment and sets the exteroceptive input/somatomotor output processing, underlying the psychomotor dimension. An internal unit (mainly involving the salience network) is connected to the internal/body environment and sets the interoceptive input/visceromotor output processing, underlying the affective dimension. Finally, an associative unit (mainly involving the default-mode network) is not connected with the environment and sets the processing of associative inputs/outputs, underlying the thought dimension. In each unit, neurotransmitter signaling couples the subcortical-cortical loop, which modulates the network activity levels, in turn setting input/output processing and related expression levels of the behavioral/phenomenological dimension. Different combinations in neurotransmitter signaling favor network balancing into distinct functional brain states, which manifest in different combinations of excitation or inhibition in psychomotricity, affectivity, and thought, resulting in the manic, depressive, and mixed states of BD. Our working model might provide a coherent framework for tracing the complex BD psychopathology to core functional brain alterations.

Rapid GFAP and Iba1 expression changes in the female rat brain following spinal cord injury

Evidence suggests that rapid changes to supporting glia may predispose individuals with spinal cord injury (SCI) to such comorbidities. Here, we interrogated the expression of astrocyte- and microglial-specific markers glial fibrillary acidic protein (GFAP) and ionized calcium binding adaptor molecule 1 (Iba1) in the rat brain in the first 24 hours following SCI. Female Sprague-Dawley rats underwent thoracic laminectomy; half of the rats received a mild contusion injury at the level of the T10 vertebral body (SCI group), the other half did not (Sham group). Twenty-four hours post-surgery the amygdala, periaqueductal grey, prefrontal cortex, hypothalamus, lateral thalamus, hippocampus (dorsal and ventral) in rats were collected. GFAP and Iba1 mRNA and protein levels were measured by real-time quantitative polymerase chain reaction and Western blot. In SCI rats, GFAP mRNA and protein expression increased in the amygdala and hypothalamus. In contrast, gene and protein expression decreased in the thalamus and dorsal hippocampus. Interestingly, Iba1 transcripts and proteins were significantly diminished only in the dorsal and ventral hippocampus, where gene expression diminished. These findings demonstrate that as early as 24 hours post-SCI there are region-specific disruptions of GFAP and Iba1 transcript and protein levels in higher brain regions. All procedures were approved by the University of Technology Sydney Institutional Animal Care and Ethics Committee (UTS ACEC13-0069).

Deep brain stimulation of anteromedial globus pallidus internus improved OCD rather than tics in a Gilles de la Tourette syndrome patient

A 32-year-old gentleman with refractory Gilles de la Tourette syndrome went on a DBS procedure on anteromedial globus pallidus internus. At the most suitable adjustment, the OCD component of his disease improved almost completely while his tics remained unchanged which was in contrast with other previous studies. Moreover, variations in symptoms were seen in response to different adjustments. We discuss that these variations and fluctuations in the therapeutic outcomes may be due to differences in physiological conditions of tic- or OCD-specified pathways and areas including distinct stimulation threshold and occurrence of neuroplasticity in neural circuits which may determine the responsiveness of each pathway or circuit to a specific stimulus. At last, we suggest that pathways and circuits should be targeted for DBS rather than single components; as these components may be involved in multiple pathways, related to different pathophysiological states.

Probabilistic mapping of thalamic nuclei and thalamocortical functional connectivity in idiopathic generalised epilepsy

It is well established that abnormal thalamocortical systems play an important role in the generation and maintenance of primary generalised seizures. However, it is currently unknown which thalamic nuclei and how nuclear‐specific thalamocortical functional connectivity are differentially impacted in patients with medically refractory and non‐refractory idiopathic generalised epilepsy (IGE). In the present study, we performed structural and resting‐state functional magnetic resonance imaging (MRI) in patients with refractory and non‐refractory IGE, segmented the thalamus into constituent nuclear regions using a probabilistic MRI segmentation method and determined thalamocortical functional connectivity using seed‐to‐voxel connectivity analyses. We report significant volume reduction of the left and right anterior thalamic nuclei only in patients with refractory IGE. Compared to healthy controls, patients with refractory and non‐refractory IGE had significant alterations of functional connectivity between the centromedian nucleus and cortex, but only patients with refractory IGE had altered cortical connectivity with the ventral lateral nuclear group. Patients with refractory IGE had significantly increased functional connectivity between the left and right ventral lateral posterior nuclei and cortical regions compared to patients with non‐refractory IGE. Cortical effects were predominantly located in the frontal lobe. Atrophy of the anterior thalamic nuclei and resting‐state functional hyperconnectivity between ventral lateral nuclei and cerebral cortex may be imaging markers of pharmacoresistance in patients with IGE. These structural and functional abnormalities fit well with the known importance of thalamocortical systems in the generation and maintenance of primary generalised seizures, and the increasing recognition of the importance of limbic pathways in IGE.

More Than Just Static: Dynamic Functional Connectivity Changes of the Thalamic Nuclei to Cortex in Parkinson's Disease With Freezing of Gait

Background: The thalamus is not only a key relay node of the thalamocortical circuit but also a hub in the regulation of gait. Previous studies of resting-state functional magnetic resonance imaging (fMRI) have shown static functional connectivity (FC) between the thalamus and the cortex are disrupted in Parkinson's disease (PD) patients with freezing of gait (FOG). However, temporal dynamic FC between the thalamus and the cortex has not yet been characterized in these patients.

Methods: Fifty PD patients, including 25 PD patients with FOG (PD-FOG) and 25 PD patients without FOG (PD-NFOG), and 25 healthy controls (HC) underwent resting-state fMRI. Seed-voxel-wise static and dynamic FC were calculated between each thalamic nuclei and other voxels across the brain using the 14 thalamic nuclei in both hemispheres as regions of interest. Associations between altered thalamic FC based on significant inter-group differences and severity of FOG symptoms were also examined in PD-FOG.

Results: Both PD-FOG and PD-NFOG showed lower static FC between the right lateral posterior thalamic nuclei and right inferior parietal lobule (IPL) compared with HC. Altered FC dynamics between the thalamic nuclei and several cortical areas were identified in PD-FOG, as shown by temporal dynamic FC analyses. Specifically, relative to PD-NFOG or HC, PD-FOG showed greater fluctuations in FC between the left intralaminar (IL) nuclei and right IPL and between the left medial geniculate and left postcentral gyrus. Furthermore, the dynamics of FC between the left pulvinar anterior nuclei and left inferior frontal gyrus were upregulated in both PD-FOG and PD-NFOG. The dynamics of FC between the right ventral lateral nuclei and left paracentral lobule were elevated in PD-NFOG but were maintained in PD-FOG and HC. The quantitative variability of FC between the left IL nuclei and right IPL was positively correlated with the clinical scales scores in PD-FOG.

Conclusions: Dynamic FC between the thalamic nuclei and relevant associative cortical areas involved in sensorimotor integration or cognitive function was disrupted in PD-FOG, which was reflected by greater temporal fluctuations. Abnormal dynamic FC between the left IL nuclei of the thalamus and right IPL was related to the severity of FOG.

Bridging large-scale cortical networks: Integrative and function-specific hubs in the thalamus

The thalamus is critical for the brain's integrative hub functions; however, the localization and characterization of the different thalamic hubs remain unclear. Using a voxel-level network measure called functional connectivity overlap ratio (FCOR), we examined the thalamus' association with large-scale resting-state networks (RSNs) to elucidate its connector hub roles. Connections to the core-neurocognitive networks were localized in the anterior and medial parts, such as the anteroventral and mediodorsal nuclei areas. Regions functionally connected to the sensorimotor network were distinctively located around the lateral pulvinar nucleus but to a limited extent. Prominent connector hubs include the anteroventral, ventral lateral, and mediodorsal nuclei with functional connections to multiple RSNs. These findings suggest that the thalamus, with extensive connections to most of the RSNs, is well placed as a critical integrative functional hub and could play an important role for functional integration facilitating brain functions associated with primary processing and higher cognition.

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Multiple large-scale cortical networks converged in the thalamus

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Neurocognitive associated hub existed in the anterior and medial region

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Control-processing hub localized in the intermediate thalamus

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Sensorimotor network was located around the lateral pulvinar nucleus

Mapping thalamocortical functional connectivity with large-scale brain networks in patients with first-episode psychosis

Abnormal thalamocortical networks involving specific thalamic nuclei have been implicated in schizophrenia pathophysiology. While comparable topography of anatomical and functional connectivity abnormalities has been reported in patients across illness stages, previous functional studies have been confined to anatomical pathways of thalamocortical networks. To address this issue, we incorporated large-scale brain network dynamics into examining thalamocortical functional connectivity. Forty patients with first-episode psychosis and forty healthy controls underwent T1-weighted and resting-state functional magnetic resonance imaging. Independent component analysis of voxelwise thalamic functional connectivity maps parcellated the cortex into thalamus-related networks, and thalamic subdivisions associated with these networks were delineated. Functional connectivity of (1) networks with the thalamus and (2) thalamic subdivision seeds were examined. In patients, functional connectivity of the salience network with the thalamus was decreased and localized to the ventrolateral (VL) and ventroposterior (VP) thalamus, while that of a network comprising the cerebellum, temporal and parietal regions was increased and localized to the mediodorsal (MD) thalamus. In patients, thalamic subdivision encompassing the VL and VP thalamus demonstrated hypoconnectivity and that encompassing the MD and pulvinar regions demonstrated hyperconnectivity. Our results extend the implications of disrupted thalamocortical networks involving specific thalamic nuclei to dysfunctional large-scale brain network dynamics in schizophrenia pathophysiology.

Global hippocampal and selective thalamic nuclei atrophy differentiate chronic TBI from Non-TBI

Traumatic brain injury (TBI) may increase susceptibility to neurodegenerative diseases later in life. One neurobiological parallel between chronic TBI and neurodegeneration may be accelerated aging and the nature of atrophy across subcortical gray matter structures. The main aim of the present investigation is to evaluate and rank the degree that subcortical gray matter atrophy differentiates chronic moderate-severe TBI from non-TBI participants by evaluating morphometric differences between groups. Forty individuals with moderate-severe chronic TBI (9.23 yrs from injury) and 33 healthy controls (HC) underwent high resolution 3D T1-weighted structural magnetic resonance imaging. Whole brain volume was classified into white matter, cortical and subcortical gray matter structures with hippocampi and thalami further segmented into subfields and nuclei, respectively. Extensive atrophy was observed across nearly all brain regions for chronic TBI participants. A series of multivariate logistic regression models identified subcortical gray matter structures of the hippocampus and thalamus as the most sensitive to differentiating chronic TBI from non-TBI participants (McFadden R² = .36, p < .001). Further analyses revealed the pattern of hippocampal atrophy to be global, occurring across nearly all subfields. The pattern of thalamic atrophy appeared to be much more selective and non-uniform, with largest between-group differences evident for nuclei bordering the ventricles. Subcortical gray matter was negatively correlated with time since injury (r = -.31, p = .054), while white matter and cortical gray matter were not. Cognitive ability was lower in the chronic TBI group (Cohen's d = .97, p = .003) and correlated with subcortical structures including the pallidum (r² = .23, p = .038), thalamus (r² = .36, p = .007) and ventral diencephalon (r² = .23, p = .036). These data may support an accelerated aging hypothesis in chronic moderate-severe TBI that coincides with a similar neuropathological profile found in neurodegenerative diseases.

Corticothalamic Pathways From Layer 5: Emerging Roles in Computation and Pathology

Large portions of the thalamus receive strong driving input from cortical layer 5 (L5) neurons but the role of this important pathway in cortical and thalamic computations is not well understood. L5-recipient "higher-order" thalamic regions participate in cortico-thalamo-cortical (CTC) circuits that are increasingly recognized to be (1) anatomically and functionally distinct from better-studied "first-order" CTC networks, and (2) integral to cortical activity related to learning and perception. Additionally, studies are beginning to elucidate the clinical relevance of these networks, as dysfunction across these pathways have been implicated in several pathological states. In this review, we highlight recent advances in understanding L5 CTC networks across sensory modalities and brain regions, particularly studies leveraging cell-type-specific tools that allow precise experimental access to L5 CTC circuits. We aim to provide a focused and accessible summary of the anatomical, physiological, and computational properties of L5-originating CTC networks, and outline their underappreciated contribution in pathology. We particularly seek to connect single-neuron and synaptic properties to network (dys)function and emerging theories of cortical computation, and highlight information processing in L5 CTC networks as a promising focus for computational studies.

Individualized diagnosis of major depressive disorder via multivariate pattern analysis of thalamic sMRI features

BACKGROUND

Magnetic resonance imaging (MRI) studies have found thalamic abnormalities in major depressive disorder (MDD). Although there are significant differences in the structure and function of the thalamus between MDD patients and healthy controls (HCs) at the group level, it is not clear whether the structural and functional features of the thalamus are suitable for use as diagnostic prediction aids at the individual level. Here, we were to test the predictive value of gray matter density (GMD), gray matter volume (GMV), amplitude of low-frequency fluctuations (ALFF), and fractional amplitude of low-frequency fluctuations (fALFF) in the thalamus using multivariate pattern analysis (MVPA).

METHODS

Seventy-four MDD patients and 44 HC subjects were recruited. The Gaussian process classifier (GPC) was trained to separate MDD patients from HCs, Gaussian process regression (GPR) was trained to predict depression scores, and Multiple Kernel Learning (MKL) was applied to explore the contribution of each subregion of the thalamus.

RESULTS

The primary findings were as follows: [1] The balanced accuracy of the GPC trained with thalamic GMD was 96.59% (P < 0.001). The accuracy of the GPC trained with thalamic GMV was 93.18% (P < 0.001). The correlation between Hamilton Depression Scale (HAMD) score targets and predictions in the GPR trained with GMD was 0.90 (P < 0.001, r2 = 0.82), and in the GPR trained with GMV, the correlation between HAMD score targets and predictions was 0.89 (P < 0.001, r2 = 0.79). [2] The models trained with ALFF and fALFF in the thalamus failed to discriminate MDD patients from HC participants. [3] The MKL model showed that the left lateral prefrontal thalamus, the right caudal temporal thalamus, and the right sensory thalamus contribute more to the diagnostic classification.

CONCLUSIONS

The results suggested that GMD and GMV, but not functional indicators of the thalamus, have good potential for the individualized diagnosis of MDD. Furthermore, the thalamus shows the heterogeneity in the structural features of thalamic subregions for predicting MDD. To our knowledge, this is the first study to focus on the thalamus for the prediction of MDD using machine learning methods at the individual level.

Regional glucose metabolic decreases with ageing are associated with microstructural white matter changes: a simultaneous PET/MR study

PURPOSE

Human ageing is associated with a regional reduction in cerebral neuronal activity as assessed by numerous studies on brain glucose metabolism and perfusion, grey matter (GM) density and white matter (WM) integrity. As glucose metabolism may impact energetics to maintain myelin integrity, but changes in functional connectivity may also alter regional metabolism, we conducted a cross-sectional simultaneous FDG PET/MR study in a large cohort of healthy volunteers with a wide age range, to directly assess the underlying associations between reduced glucose metabolism, GM atrophy and decreased WM integrity in a single ageing cohort.

METHODS

In 94 healthy subjects between 19.9 and 82.5 years (mean 50.1 ± 17.1; 47 M/47F, MMSE ≥ 28), simultaneous FDG-PET, structural MR and diffusion tensor imaging (DTI) were performed. Voxel-wise associations between age and grey matter (GM) density, RBV partial-volume corrected (PVC) glucose metabolism, white matter (WM) fractional anisotropy (FA) and mean diffusivity (MD), and age were assessed. Clusters representing changes in glucose metabolism correlating significantly with ageing were used as seed regions for tractography. Both linear and quadratic ageing models were investigated.

RESULTS

An expected age-related reduction in GM density was observed bilaterally in the frontal, lateral and medial temporal cortex, striatum and cerebellum. After PVC, relative FDG uptake was negatively correlated with age in the inferior and midfrontal, cingulate and parietal cortex and subcortical regions, bilaterally. FA decreased with age throughout the entire brain WM. Four white matter tracts were identified connecting brain regions with declining glucose metabolism with age. Within these, relative FDG uptake in both origin and target clusters correlated positively with FA (0.32 ≤ r ≤ 0.71) and negatively with MD (- 0.75 ≤ r ≤  - 0.41).

CONCLUSION

After appropriate PVC, we demonstrated that regional cerebral glucose metabolic declines with age and that these changes are related to microstructural changes in the interconnecting WM tracts. The temporal course and potential causality between ageing effects on glucose metabolism and WM integrity should be further investigated in longitudinal cohort PET/MR studies.

Classification of Adolescent Major Depressive Disorder Via Static and Dynamic Connectivity

This paper introduces an approach for classifying adolescents suffering from MDD using resting-state fMRI. Accurate diagnosis of MDD involves interviews with adolescent patients and their parents, symptom rating scales based on Diagnostic and Statistical Manual of Mental Disorders (DSM), behavioral observation as well as the experience of a clinician. Discovering predictive biomarkers for diagnosing MDD patients using functional magnetic resonance imaging (fMRI) scans can assist the clinicians in their diagnostic assessments. This paper investigates various static and dynamic connectivity measures extracted from resting-state fMRI for assisting with MDD diagnosis. First, absolute Pearson correlation matrices from 85 brain regions are computed and they are used to calculate static features for predicting MDD. A predictive sub-network extracted using sub-graph entropy classifies adolescent MDD vs. typical healthy controls with high accuracy, sensitivity and specificity. Next, approaches utilizing dynamic connectivity are employed to extract tensor based, independent component based and principal component based subject specific attributes. Finally, features from static and dynamic approaches are combined to create a feature vector for classification. A leave-one-out cross-validation method is used for the final predictor performance. Out of 49 adolescents with MDD and 33 matched healthy controls, a support vector machine (SVM) classifier using a radial basis function (RBF) kernel using differential sub-graph entropy combined with dynamic connectivity features classifies MDD vs. healthy controls with an accuracy of 0.82 for leave-one-out cross-validation. This classifier has specificity and sensitivity of 0.79 and 0.84, respectively.

Thalamo-cortical networks in subtypes of migraine with aura patients

Background

We searched for differences in resting-state functional connectivity (FC) between brain networks and its relationship with the microstructure of the thalamus between migraine with pure visual auras (MA), and migraine with complex neurological auras (MA+), i.e. with the addition of at least one of sensory or language symptom.

Methods

3T MRI data were obtained from 20 patients with MA and 15 with MA + and compared with those from 19 healthy controls (HCs). We collected resting state data among independent component networks. Diffusivity metrics of bilateral thalami were calculated and correlated with resting state ICs-Z-scores.

Results

As compared to HCs, both patients with MA and MA + disclosed disrupted FC between the default mode network (DMN) and the right dorsal attention system (DAS). The MA + subgroup had lower microstructural metrics than both HCs and the MA subgroup, which correlated negatively with the strength of DMN connectivity. Although the microstructural metrics of MA patients did not differ from those of HCs, these patients lacked the correlation with the strength of DAS connectivity found in HCs.

Conclusions

The present findings suggest that, as far as MRI profiles are concerned, the two clinical phenotypes of migraine with aura have both common and distinct morpho-functional features of nodes in the thalamo-cortical network.

Characterizing resting-state networks in Parkinson's disease: A multi-aspect functional connectivity study

PURPOSE

Resting-state functional magnetic resonance imaging (Rs-fMRI) can be used to investigate the alteration of resting-state brain networks (RSNs) in patients with Parkinson's disease (PD) when compared with healthy controls (HCs). The aim of this study was to identify the differences between individual RSNs and reveal the most important discriminatory characteristic of RSNs between the HCs and PDs.

METHODS

This study used Rs-fMRI data of 23 patients with PD and 18 HCs. Group independent component analysis (ICA) was performed, and 23 components were extracted by spatially overlapping the components with a template RSN. The extracted components were used in the following three methods to compare RSNs of PD patients and HCs: (1) a subject-specific score based on group RSNs and a dual-regression approach (namely RSN scores); (2) voxel-wise comparison of the RSNs in the PD patient and HC groups using a nonparametric permutation test; and (3) a hierarchical clustering analysis of RSNs in the PD patient and HC groups.

RESULTS

The results of RSN scores showed a significant decrease in connectivity in seven ICs in patients with PD compared with HCs, and this decrease was particularly striking on the lateral and medial posterior occipital cortices. The results of hierarchical clustering of the RSNs revealed that the cluster of the default mode network breaks down into the three other clusters in PD patients.

CONCLUSION

We found various characteristics of the alteration of the RSNs in PD patients compared with HCs. Our results suggest that different characteristics of RSNs provide insights into the biological mechanism of PD.

Frequency-specific alternations in the moment-to-moment BOLD signals variability in schizophrenia

Variability of neuronal activity is considered as the fundamental mechanism for the flexible and optimal brain function. Moreover, different frequency neuro signal is related to specific function. While little is currently known regarding changes in spontaneous BOLD variability of schizophrenia. The current study used resting-state fMRI data from 53 chronic schizophrenic subjects and 67 healthy subjects to investigate this issue. The data-driven method was used to measure the BOLD variability (MSSD: mean square successive difference) in two different frequency bands respectively (slow-5: 0.01-0.027 Hz; slow-4:0.027-0.073 Hz). Schizophrenic subjects exhibited decreased BOLD variability in thalamus region, sensorimotor and visual networks, and increased BOLD variability in salience network compared to matched healthy controls. Moreover, the interaction effects between frequency and group were observed in thalamus and right dorsolateral prefrontal cortex (DLPFC). These findings identified that altered BOLD variability is frequency dependent in schizophrenia. Importantly, the severity of patients' negative symptom was related to the increased BOLD variability of DLPFC within slow-4 frequency band, highlighting the evidence that abnormal BOLD variability of frontal cortex is likely to have effects on the pathophysiology of negative symptom in schizophrenia.

A connectome-based approach to assess motor outcome after neonatal arterial ischemic stroke

Objective

Studies of motor outcome after Neonatal Arterial Ischemic Stroke (NAIS) often rely on lesion mapping using MRI. However, clinical measurements indicate that motor deficit can be different than what would solely be anticipated by the lesion extent and location. Because this may be explained by the cortical disconnections between motor areas due to necrosis following the stroke, the investigation of the motor network can help in the understanding of visual inspection and outcome discrepancy. In this study, we propose to examine the structural connectivity between motor areas in NAIS patients compared to healthy controls in order to define the cortical and subcortical connections that can reflect the motor outcome.

Methods

Thirty healthy controls and 32 NAIS patients with and without Cerebral Palsy (CP) underwent MRI acquisition and manual assessment. The connectome of all participants was obtained from T1‐weighted and diffusion‐weighted imaging.

Results

Significant disconnections in the lesioned and contra‐lesioned hemispheres of patients were found. Furthermore, significant correlations were detected between the structural connectivity metric of specific motor areas and manuality assessed by the Box and Block Test (BBT) scores in patients.

Interpretation

Using the connectivity measures of these links, the BBT score can be estimated using a multiple linear regression model. In addition, the presence or not of CP can also be predicted using the KNN classification algorithm. According to our results, the structural connectome can be an asset in the estimation of gross manual dexterity and can help uncover structural changes between brain regions related to NAIS.

Concurrent brain parcellation and connectivity estimation via co-clustering of resting state fMRI data: A novel approach

Connectional topography mapping has been gaining widespread attention in human brain imaging studies. However, existing methods might not effectively utilize the information from neuroimaging data, thus hindering the understanding of the underlying connectional organization in the brain and uncovering the optimal clustering number from the data. In this study, we propose a novel method for the automated construction of inherent functional connectivity topography in a data‐driven manner by leveraging the power of co‐clustering‐based on resting state fMRI (rs‐fMRI) data. We propose the co‐clustering‐based method not only for concurrently parcellating two interconnected brain regions of interest (ROIs) under consideration into functionally homogenous subregions, but also for estimating the connectivity between these subregions from the two brain ROIs. In particular, we first model the connectional topography mapping as a co‐clustering‐based bipartite graph partitioning problem for constructing the inherent functional connectivity topography between the two interconnected brain ROIs. We also adopt an objective criterion, that is, silhouette width index measuring clustering quality, for determining the optimal number of clusters. The proposed method has been validated for mapping thalamocortical connectional topography based on rs‐fMRI data of 57 subjects. Validation results have demonstrated that our method identified the optimal solution with five pairs of mutually connected subregions of the thalamocortical system from the rs‐fMRI data, and could yield more meaningful, interpretable, and homogenous connectional topography than existing methods. The proposed method was further validated by the high symmetry of the mapped connectional topography between two hemispheres.

Temporal Lobe Epilepsy Shows Distinct Functional Connectivity Patterns in Different Thalamic Nuclei

Background: The thalamus, as a key relay of neuronal information flow between subcortical structures and cortical networks, has been implicated in focal limbic seizures propagation, awareness maintenance, and seizure-related cognitive deficits. However, the specific functional alterations between different thalamic nuclei and subcortical-cortical systems in temporal lobe epilepsy (TLE) remain largely unknown. Methods: We examined thalamic functional connectivity (FC) in 26 TLE patients and 30 healthy controls matched for sex, age, and education. The anterior (ANT), ventral posterior medial, and central lateral nuclei of thalamus were employed to establish whole-brain seed-to-voxel thalamic FC maps. Secondary Pearson's correlation analysis was conducted to assess associations between the abnormal thalamic FC and the memory performance in TLE. Results: Seed-based FC analyses revealed typical distinct FC patterns within each thalamic nuclei in both controls and TLE patients. The TLE showed significantly decreased FC between different thalamic nuclei and subcortical-cortical networks, including the limbic structures, midbrain, sensorimotor network, medial prefrontal cortex, temporal-occipital fusiform gyrus, and cerebellum. Verification analyses yielded similar patterns of thalamic FC changes in TLE. Importantly, the decreased FC between the ANT and hippocampal pathway was correlated with the poorer memory performance of TLE. Conclusion: These findings suggest that the distinct thalamocortical FC patterns are damaged to some extent in TLE patients. Importantly, the specific pathology of the ANT-hippocampal pathway in TLE may be a potential factor that contributes to memory deficits. Our study may pave the way for improved treatments and cognitive function by directly targeting different thalamocortical circuits for TLE.

Bridging the Gap? Altered Thalamocortical Connectivity in Psychotic and Psychedelic States

Psychiatry has a well-established tradition of comparing drug-induced experiences to psychotic symptoms, based on shared phenomena such as altered perceptions. The present review focuses on experiences induced by classic psychedelics, which are substances capable of eliciting powerful psychoactive effects, characterized by distortions/alterations of several neurocognitive processes (e.g., hallucinations). Herein we refer to such experiences as psychedelic states. Psychosis is a clinical syndrome defined by impaired reality testing, also characterized by impaired neurocognitive processes (e.g., hallucinations and delusions). In this review we refer to acute phases of psychotic disorders as psychotic states. Neuropharmacological investigations have begun to characterize the neurobiological mechanisms underpinning the shared and distinct neurophysiological changes observed in psychedelic and psychotic states. Mounting evidence indicates changes in thalamic filtering, along with disturbances in cortico-striato-pallido-thalamo-cortical (CSPTC)-circuitry, in both altered states. Notably, alterations in thalamocortical functional connectivity were reported by functional magnetic resonance imaging (fMRI) studies. Thalamocortical dysconnectivity and its clinical relevance are well-characterized in psychotic states, particularly in schizophrenia research. Specifically, studies report hyperconnectivity between the thalamus and sensorimotor cortices and hypoconnectivity between the thalamus and prefrontal cortices, associated with patients' psychotic symptoms and cognitive disturbances, respectively. Intriguingly, studies also report hyperconnectivity between the thalamus and sensorimotor cortices in psychedelic states, correlating with altered visual and auditory perceptions. Taken together, the two altered states appear to share clinically and functionally relevant dysconnectivity patterns. In this review we discuss recent findings of thalamocortical dysconnectivity, its putative extension to CSPTC circuitry, along with its clinical implications and future directions.

Parcellation of the thalamus by using a dual-segment method based on resting-state functional connectivity: An application on autism spectrum disorder

BACKGROUND

Evidence suggests thalamus is a key "information relay" center and all cortical areas receive inputs from the thalamus and each of the main nuclei of thalamus connects a single one or a few cortical areas. The traditional "winner-takes-all" thalamus parcellation method was then proposed based on this assumption. However, this method is based on the structural segments of the cortex which is not suitable for the functional parcellation of the thalamus.

METHOD

Here we proposed a dual-segment method for thalamus functional parcellation based on the resting-state fMRI data. The traditional "winner-takes-all" and the proposed dual-segment methods were both applied to the dataset of 76 healthy controls (HCs) and 34 subjects with autism spectrum disorder.

RESULTS

The results showed that the thalamus was subdivided into two sub-regions by using the dual-segment method: one is located in the dorsomedial part of thalamus which connects the high-level cognitive cortical regions; the other is located in the ventrolateral part of thalamus which connects the low-level sensory cortical areas. The functional connectivity strength between thalamus sub-regions and the corresponding cortical regions based on the dual-segment method was higher than that of results from the traditional "winner-takes-all" method. The thalamo-cortical functional connectivity based on our proposed method also showed higher classification ability to distinguish subjects with autism spectrum disorder from HCs.

CONCLUSION

Our study will provide a new method for functional thalamus parcellation which might help understand the sub-regions functions of thalamus in neuroscience studies.

Dynamic Temporospatial Patterns of Functional Connectivity and Alterations in Idiopathic Generalized Epilepsy

The dynamic profile of brain function has received much attention in recent years and is also a focus in the study of epilepsy. The present study aims to integrate the dynamics of temporal and spatial characteristics to provide comprehensive and novel understanding of epileptic dynamics. Resting state fMRI data were collected from eighty-three patients with idiopathic generalized epilepsy (IGE) and 87 healthy controls (HC). Specifically, we explored the temporal and spatial variation of functional connectivity density (tvFCD and svFCD) in the whole brain. Using a sliding-window approach, for a given region, the standard variation of the FCD series was calculated as the tvFCD and the variation of voxel-wise spatial distribution was calculated as the svFCD. We found primary, high-level, and sub-cortical networks demonstrated distinct tvFCD and svFCD patterns in HC. In general, the high-level networks showed the highest variation, the subcortical and primary networks showed moderate variation, and the limbic system showed the lowest variation. Relative to HC, the patients with IGE showed weaken temporal and enhanced spatial variation in the default mode network and weaken temporospatial variation in the subcortical network. Besides, enhanced temporospatial variation in sensorimotor and high-level networks was also observed in patients. The hyper-synchronization of specific brain networks was inferred to be associated with the phenomenon responsible for the intrinsic propensity of generation and propagation of epileptic activities. The disrupted dynamic characteristics of sensorimotor and high-level networks might potentially contribute to the driven motion and cognition phenotypes in patients. In all, presently provided evidence from the temporospatial variation of functional interaction shed light on the dynamics underlying neuropathological profiles of epilepsy.

Functional Subdivisions of Magnocellular Cell Groups in Human Basal Forebrain: Test-Retest Resting-State Study at Ultra-high Field, and Meta-analysis

The heterogeneous neuronal subgroups of the basal forebrain corticopetal system (BFcs) have been shown to modulate cortical functions through their cholinergic, gamma-aminobutyric acid-ergic, and glutamatergic projections to the entire cortex. Although previous studies suggested that the basalo-cortical projection system influences various cognitive functions, particularly via its cholinergic component, these studies only focused on certain parts of the BFcs or nearby structures, leaving aside a more systematic picture of the functional connectivity of BFcs subcompartments. Moreover, these studies lacked the high-spatial resolution and the probability maps needed to identify specific subcompartments. Recent advances in the ultra-high field 7T functional magnetic resonance imaging (fMRI) provided potentially unprecedented spatial resolution of functional MRI images to study the subdivision of the BFcs. In this study, the BF space containing corticopetal cells was divided into 3 functionally distinct subdivisions based on functional connection to cortical regions derived from fMRI. The overall functional connection of each BFcs subdivision was examined with a test-retest study. Finally, a meta-analysis was used to study the related functional topics of each BF subdivision. Our results demonstrate distinct functional connectivity patterns of these subdivisions along the rostrocaudal axis of the BF. All three compartments have shown consistent segregation and overlap at specific target regions including the hippocampus, insula, thalamus, and the cingulate gyrus, suggesting functional integration and separation in BFcs.

fMRI volume classification using a 3D convolutional neural network robust to shifted and scaled neuronal activations

Deep-learning methods based on deep neural networks (DNNs) have recently been successfully utilized in the analysis of neuroimaging data. A convolutional neural network (CNN) is a type of DNN that employs a convolution kernel that covers a local area of the input sample and moves across the sample to provide a feature map for the subsequent layers. In our study, we hypothesized that a 3D-CNN model with down-sampling operations such as pooling and/or stride would have the ability to extract robust feature maps from the shifted and scaled neuronal activations in a single functional MRI (fMRI) volume for the classification of task information associated with that volume. Thus, the 3D-CNN model would be able to ameliorate the potential misalignment of neuronal activations and over-/under-activation in local brain regions caused by imperfections in spatial alignment algorithms, confounded by variability in blood-oxygenation-level-dependent (BOLD) responses across sessions and/or subjects. To this end, the fMRI volumes acquired from four sensorimotor tasks (left-hand clenching, right-hand clenching, auditory attention, and visual stimulation) were used as input for our 3D-CNN model to classify task information using a single fMRI volume. The classification performance of the 3D-CNN was systematically evaluated using fMRI volumes obtained from various minimal preprocessing scenarios applied to raw fMRI volumes that excluded spatial normalization to a template and those obtained from full preprocessing that included spatial normalization. Alternative classifier models such as the 1D fully connected DNN (1D-fcDNN) and support vector machine (SVM) were also used for comparison. The classification performance was also assessed for several k-fold cross-validation (CV) schemes, including leave-one-subject-out CV (LOOCV). Overall, the classification results of the 3D-CNN model were superior to that of the 1D-fcDNN and SVM models. When using the fully-processed fMRI volumes with LOOCV, the mean error rates (± the standard error of the mean) for the 3D-CNN, 1D-fcDNN, and SVM models were 2.1% (± 0.9), 3.1% (± 1.2), and 4.1% (± 1.5), respectively (p = 0.041 from a one-way ANOVA). The error rates for 3-fold CV were higher (2.4% ± 1.0, 4.2% ± 1.3, and 10.1% ± 2.0; p < 0.0003 from a one-way ANOVA). The mean error rates also increased considerably using the raw fMRI 3D volume data without preprocessing (26.2% for the 3D-CNN, 75.0% for the 1D-fcDNN, and 75.0% for the SVM). Furthermore, the ability of the pre-trained 3D-CNN model to handle shifted and scaled neuronal activations was demonstrated in an online scenario for five-class classification (i.e., four sensorimotor tasks and the resting state) using the real-time fMRI of three participants. The resulting classification accuracy was 78.5% (± 1.4), 26.7% (± 5.9), and 21.5% (± 3.1) for the 3D-CNN, 1D-fcDNN, and SVM models, respectively. The superior performance of the 3D-CNN compared to the 1D-fcDNN was verified by analyzing the resulting feature maps and convolution filters that handled the shifted and scaled neuronal activations and by utilizing an independent public dataset from the Human Connectome Project.

The anterior and medial thalamic nuclei and the human limbic system: tracing the structural connectivity using diffusion-weighted imaging

The limbic system is a phylogenetically old, behaviorally defined system that serves as a center for emotions. It controls the expression of anger, fear, and joy and also influences sexual behavior, vegetative functions, and memory. The system comprises a collection of tel-, di-, and mesencephalic structures whose components have evolved and increased over time. Previous animal research indicates that the anterior nuclear group of the thalamus (ANT), as well as the habenula (Hb) and the adjacent mediodorsal nucleus (MD) each play a vital role in the limbic circuitry. Accordingly, diffusion imaging data of 730 subjects obtained from the Human Connectome Project and the masks of six nuclei (anterodorsal, anteromedial, anteroventral, lateral dorsal, Hb, and MD) served as seed regions for a direct probabilistic tracking to the rest of the brain using diffusion-weighted imaging. The results revealed that the ANT nuclei are part of the limbic and the memory system as they mainly connect via the mammillary tract, mammillary body, anterior commissure, fornix, and retrosplenial cortices to the hippocampus, amygdala, medio-temporal, orbito-frontal and occipital cortices. Furthermore, the ANT nuclei showed connections to the mesencephalon and brainstem to varying extents, a pattern rarely described in experimental findings. The habenula—usually defined as part of the epithalamus—was closely connected to the tectum opticum and seems to serve as a neuroanatomical hub between the visual and the limbic system, brainstem, and cerebellum. Finally, in contrast to experimental findings with tracer studies, directly determined connections of MD were mainly confined to the brainstem, while indirect MD fibers form a broad pathway connecting the hippocampus and medio-temporal areas with the mediofrontal cortex.

Common and specific dimensions of internalizing disorders are characterized by unique patterns of brain activity on a task of emotional cognitive control

Alterations in neural systems underlying cognitive control are well-documented across individuals with various internalizing disorders. The current study examined how individual differences in underlying traits related to internalizing disorders influence brain activation, as assessed by fMRI, when cognitive control must be exerted to make a decision about the emotional valence (positive, negative) of a task-relevant word displayed concurrently with a task-irrelevant emotional face. Taking a bi-factor model approach, fifty-five middle-aged female participants were characterized on symptom level on a common internalizing latent factor representing shared symptoms across anxiety and depression, as well as on specific factors remaining after taking the common internalizing factor into account: low positive affect, anxious arousal, and anxious apprehension. Contrasting activation on trials requiring higher vs. lower control revealed that higher levels of the Common Internalizing factor are associated with less deactivation of regions of the default mode network. Higher levels of the Low Positive Affect-specific factor are associated with less differentiation in engagement of portions of the fronto-parietal control network, while higher levels of the Anxious Arousal-specific factor are associated with less of a differentiation in activation of the thalamus. No effects were observed for level of the Anxious Apprehension-specific factor. These results suggest that prior findings of alterations in default mode activity associated with depression may not be specific to depressive symptoms per se but may characterize internalizing symptoms more generally. In addition, they suggest that reduced engagement of cognitive control regions may be more associated with low positive affect than depressive symptoms more generally.