Integrative and Network-Specific Connectivity of the Basal Ganglia and Thalamus Defined in Individuals

Cognitive Brain Networks and Enlarged Perivascular Spaces: Implications for Symptom Severity and Support Needs in Children with Autism

Background/Objectives: The severity of autism spectrum disorder (ASD) is clinically assessed through a comprehensive evaluation of social communication deficits, restricted interests, repetitive behaviors, and the level of support required (ranging from level 1 to level 3) according to DSM-5 criteria. Along with its varied clinical manifestations, the neuroanatomy of ASD is characterized by heterogeneous abnormalities. Notably, brain MRI of children with ASD often reveals an increased number of perivascular spaces (PVSs) compared to typically developing children. Our recent findings indicate that enlarged PVSs (ePVSs) are more common in younger male patients with severe ASD and that specific ePVS locations are significantly associated with ASD symptoms. Methods: In this study, we mapped ePVSs across key regions of three major cognitive networks-the Default Mode Network (DMN), the combined Central Executive/Frontoparietal Network (CEN/FPN), and the Salience Network (SN)-in 36 individuals with different symptom severities and rehabilitation needs due to ASD. We explored how the number, size, and location of PVSs in these networks are related to specific ASD symptoms and the overall need for rehabilitation and support. Results: Our results suggest that ePVSs in the DMN, CEN/FPN, and SN are strongly correlated with the severity of certain ASD symptoms, including verbal deficits, stereotypies, and sensory disturbances. We found a mild association between ePVSs and the level of support needed for daily living and quality of life. Conclusions: Dysfunction in cognitive networks associated with the presence of ePVSs has a significant impact on the severity of ASD symptoms. However, the need for assistance may also be influenced by other comorbid conditions and dysfunctions in smaller, overlapping brain networks.

The human brainstem's red nucleus was upgraded to support goal-directed action

The red nucleus, a large brainstem structure, coordinates limb movement for locomotion in quadrupedal animals. In humans, its pattern of anatomical connectivity differs from that of quadrupeds, suggesting a different purpose. Here, we apply our most advanced resting-state functional connectivity based precision functional mapping in highly sampled individuals (n = 5), resting-state functional connectivity in large group-averaged datasets (combined n ~ 45,000), and task based analysis of reward, motor, and action related contrasts from group-averaged datasets (n > 1000) and meta-analyses (n > 14,000 studies) to precisely examine red nucleus function. Notably, red nucleus functional connectivity with motor-effector networks (somatomotor hand, foot, and mouth) is minimal. Instead, connectivity is strongest to the action-mode and salience networks, which are important for action/cognitive control and reward/motivated behavior. Consistent with this, the red nucleus responds to motor planning more than to actual movement, while also responding to rewards. Our results suggest the human red nucleus implements goal-directed behavior by integrating behavioral valence and action plans instead of serving a pure motor-effector function.

Deficit of satellite oligodendrocytes of neurons in the rostral part of the head of the caudate nucleus in schizophrenia

Increasing evidence implicates compromised myelin integrity and oligodendrocyte abnormalities in the dysfunction of neuronal networks in schizophrenia. We previously reported a deficiency of myelinating oligodendrocytes (OL), oligodendrocyte progenitors (OP) and satellite oligodendrocytes of neurons (Sat-OL) in the prefrontal cortex and the inferior parietal cortex - cortical hubs of the frontoparietal cognitive network and default mode network (DMN) altered in schizophrenia. Deficiency of OL and OP was also detected in the head of the caudate nucleus (HCN), which accumulates cortical projections from the associative cortex and is the central node of these networks. However, the number of Sat-Ol per neuron in schizophrenia has not been studied in the HCN. In the current study we estimated the number of Sat-Ol per neuron in the rostral part of the HCN in schizophrenia (n = 18) compared to healthy controls (n = 18) in the same section collection that was previously used to study the number Ol and OP. We found a significant decrease of the number of Sat-Ol per neuron (- 50%, p < 0.001) in schizophrenia as compared to normal controls. Considering that the rostral part of the HCN is an individual network-specific projection zone of the DMN, the deficit of Sat-Ol found in schizophrenia may be related to the dysfunctional DMN-HCN connections, which has been repeatedly described in schizophrenia. The dramatic decrease of the number of Sat-Ol per neuron may be partially related to a pronounced excess of dopamine concentration in the rostral part of the HCN in schizophrenia.

Functional Neuroanatomy of Tics: A Brain Network Perspective

Tourette syndrome is defined by motor and vocal tics, yet our understanding of the pathophysiology of tics remains limited. Functional MRI (fMRI) can localize brain function related to the clinical phenomenology of tics. Here, we review extant fMRI studies examining brain activity during the premonitory urge, tic release, and tic suppression. Results are placed in the context of large-scale functional networks, given recent advancements in understanding the brain's functional network organization. During tic-related phenomena, brain activity follows consistent patterns involving specific networks, largely centered around the cingulo-opercular action mode network. This network-level framework provides a novel avenue for targeted-treatment methods.

Variation in brain aging: A review and perspective on the utility of individualized approaches to the study of functional networks in aging

Healthy aging is associated with cognitive decline across multiple domains, including executive function, memory, and attention. These cognitive changes can often influence an individual's ability to function and quality of life. However, the degree to which individuals experience cognitive decline, as well as the trajectory of these changes, exhibits wide variability across people. These cognitive abilities are thought to depend on the coordinated activity of large-scale networks. Like behavioral effects, large variation can be seen in brain structure and function with aging, including in large-scale functional networks. However, tracking this variation requires methods that reliably measure individual brain networks and their changes over time. Here, we review the literature on age-related cognitive decline and on age-related differences in brain structure and function. We focus particularly on functional networks and the individual variation that exists in these measures. We propose that novel individual-centered fMRI approaches can shed new light on patterns of inter- and intra-individual variability in aging. These approaches may be instrumental in understanding the neural bases of cognitive decline.

Efficacy and safety of high-dose and personalized TBS on post-stroke cognitive impairment: A randomized controlled trial

BACKGROUND

Cognitive impairments are prevalent among stroke patients, impacting independent living. While intermittent theta burst stimulation (iTBS) shows potential for rehabilitation, the efficacy of the commonly-used doses remains unsatisfactory.

OBJECTIVE

To investigate the efficacy, dose-dependent effect, and safety of high-dose iTBS targeting the individualized frontoparietal cognitive network (FCN) for post-stroke cognitive recovery.

METHODS

In a randomized, sham-controlled, three-arm trial, patients with post-stroke cognitive impairment (PSCI) received 15 days of high-dose (3600 pulses/day), standard low-dose (1200 pulses/day) as an active control, or sham iTBS targeting the individualized FCN, alongside cognitive training. Primary outcome measured changes in global cognition via the Montreal Cognitive Assessment (MoCA). Secondary measures included MoCA response rates and score changes in the Wechsler Memory Scale, Wechsler Adult Intelligence Scale, and Mini-Mental State Examination.

RESULTS

Of forty-five randomized participants, forty-one (8 women; mean [SD] age, 58.63 [8.64] years) were analyzed. Personalized targeting improved focality by 33.0 % over the standard F3 target in E-field analysis. Both high-dose and standard low-dose groups showed significant improvements in MoCA. Importantly, the high-dose group demonstrated superior cognitive recovery over both the active control group (estimated difference = 2.50, p = 0.0339, 95 % CI = 0.15-4.84) and the sham control group (estimated difference = 4.29, p = 0.0001, 95 % CI = 1.99-6.60), indicating a superior effect of high-dose stimulation for cognitive recovery. Similar high-dose and dose-dependent effects were observed in other secondary outcomes, suggesting consistent effects on the memory, intelligence, and mental state. No serious adverse events occurred.

CONCLUSIONS

This study highlights the efficacy and safety of high-dose iTBS targeting the individualized FCN for post-stroke cognitive recovery.

The brain's action-mode network

The brain is always intrinsically active, using energy at high rates while cycling through global functional modes. Awake brain modes are tied to corresponding behavioural states. During goal-directed behaviour, the brain enters an action-mode of function. In the action-mode, arousal is heightened, attention is focused externally and action plans are created, converted to goal-directed movements and continuously updated on the basis of relevant feedback, such as pain. Here, we synthesize classical and recent human and animal evidence that the action-mode of the brain is created and maintained by an action-mode network (AMN), which we had previously identified and named the cingulo-opercular network on the basis of its anatomy. We discuss how rather than continuing to name this network anatomically, annotating it functionally as controlling the action-mode of the brain increases its distinctiveness from spatially adjacent networks and accounts for the large variety of the associated functions of an AMN, such as increasing arousal, processing of instructional cues, task general initiation transients, sustained goal maintenance, action planning, sympathetic drive for controlling physiology and internal organs (connectivity to adrenal medulla), and action-relevant bottom-up signals such as physical pain, errors and viscerosensation. In the functional mode continuum of the awake brain, the AMN-generated action-mode sits opposite the default-mode for self-referential, emotional and memory processing, with the default-mode network and AMN counterbalancing each other as yin and yang.

Individual variability in cortical representations of tonic pain

When people experience pain in everyday situations, the experience is often long-lasting and fluctuating. However, pain research predominantly focuses on artificial brief and repeated singular painful events. Here, we aimed to approximate clinically relevant pain in 152 sessions from 38 participants who underwent four sessions each. We applied variable levels of contact heat pain to the forearm using a thermode. Participants were asked to continuously rate their pain experience through a potentiometer device. In a whole-brain approach, we related the dynamic fluctuations of cortical activity and connectivity to the time courses of pain. We also explored the variability of cortical processing across participants. In an individual approach, we compared the cortical processing pattern of each individual with the overall group findings. The results revealed a large discrepancy between the group results that are usually reported in publications and the 4-session individual processing patterns: the group findings corroborated previous work localising tonic pain encoding to the secondary somatosensory cortex. By contrast, this region was shadowed by a variety of activity patterns across individuals, represented by a low spatial correlation between group statistics and individual results. The current findings challenge the usefulness and applicability of group results. They do not inform us how pain is processed in the brain as none of the participants exhibited the processing pattern of the group statistics. Therapies to relieve pain that rely on the modulation of brain regions will fail unless they are adapted to an individual's unique pain processing characteristics.

Representing Brain-Behavior Associations by Retaining High-Motion Minoritized Youth

BACKGROUND

Population neuroscience datasets provide an opportunity for researchers to estimate reproducible effect sizes for brain-behavior associations because of their large sample sizes. However, these datasets undergo strict quality control to mitigate sources of noise, such as head motion. This practice often excludes a disproportionate number of minoritized individuals.

METHODS

We used motion-ordering and motion-ordering+resampling (bagging) to test whether these methods preserve functional magnetic resonance imaging (fMRI) data in the Adolescent Brain Cognitive Development (ABCD) Study (N = 5733). For the 2 methods, brain-behavior associations were computed as the partial Spearman's rank correlations (Rs) between functional connectivity and cognitive performance (NIH Cognition Toolbox) as well as externalizing and internalizing psychopathology (Child Behavior Checklist) while adjusting for participant sex assigned at birth and head motion.

RESULTS

Black and Hispanic youth exhibited excess head motion relative to data collected from White youth and were discarded disproportionately when conventional approaches were used. Motion-ordering and bagging methods retained more than 99% of Black and Hispanic youth. Both methods produced reproducible brain-behavior associations across low-/high-motion racial/ethnic groups based on motion-limited fMRI data.

CONCLUSIONS

The motion-ordering and bagging methods are 2 feasible approaches that can enhance sample representation for testing brain-behavior associations and that result in reproducible effect sizes in diverse populations.

Intrinsic brain functional connectivity mediates the relationship between psychological resilience and cognitive decline in ageing

Ageing individuals often experience cognitive decline and intrinsic functional connectivity (FC) changes. Psychological resilience, a personality trait that reflects the capacity to adapt and cope with age-related challenges, plays a key role in mitigating cognitive decline. In this study involving 101 older adults, we investigated how psychological resilience influences cognitive decline measured by processing speed. Particularly, we obtained resting-state functional magnetic resonance imaging (fMRI) to assess how intrinsic FC, represented by degree centrality, modulates the relationship between resilience and processing speed. Our results indicated while psychological resilience positively predicted processing speed, this relationship was mainly driven by education. Additionally, the degree centrality of both thalamus and caudate negatively correlated with processing speed and resilience. Notably, the degree centrality of both thalamus and caudate significantly mediated the relationship between resilience and processing speed. These findings suggest that psychological resilience could protect against age-related cognitive decline via its influence on FC in the thalamus and caudate, highlighting these areas as potential intervention targets for reducing cognitive decline in ageing people.

Somatosensory-Thalamic Functional Dysconnectivity Associated With Poststroke Motor Function Rehabilitation: A Resting-State fMRI Study

BACKGROUND

The thalamus plays a pivotal role in functional brain networks, yet its contribution to motor function recovery following stroke remains elusive. We aim to explore changes in thalamocortical functional connectivity poststroke and its correlation with motor function.

METHODS

Thirty-nine subacute ischemic stroke patients and 32 healthy individuals underwent resting-state functional magnetic resonance imaging (MRI). The Fugl-Meyer Assessment (FMA) was employed to evaluate upper and lower extremity motor function before and 1 year after stroke rehabilitation. The ipsilesional thalamus and contralesional thalamus were parceled into functional regions of interest (ROIs) based on connectivity with six cortical ROIs: prefrontal, motor, temporal, posterior parietal, somatosensory, and occipital cortex. Functional connectivity between each cortical ROI and its corresponding thalamic ROI was calculated and compared between groups. Differences identified in the ROI-to-ROI analysis were further investigated through seed-to-voxel whole-brain connectivity analyses to pinpoint thalamic dysconnectivity. Correlations with upper and lower extremity motor function were also analyzed.

RESULTS

Significant changes in thalamocortical functional connectivity were observed after stroke in ROI-to-ROI analysis, with bilateral somatosensory-thalamic connectivity decreased and ipsilesional temporal-thalamic and bilateral occipital-thalamic connectivity increased. Seed-to-voxel analysis localized ipsilesional thalamic hypoconnectivity to the ipsilesional rolandic operculum and ipsilesional precentral gyrus. Ipsilesional somatosensory-thalamic connectivity was positively correlated with baseline upper extremity FMA scores and negatively correlated with upper extremity motor function change rate at 1-year postdischarge.

CONCLUSIONS

This study provides new insights into the role of the thalamus in motor function recovery after stroke, offering preliminary evidence for its potential as a therapeutic target in poststroke rehabilitation.

Group-to-individual generalizability and individual-level inferences in cognitive neuroscience

Much of cognitive neuroscience research is focused on group-averages and interindividual brain-behavior associations. However, many theories core to the goal of cognitive neuroscience, such as hypothesized neural mechanisms for a behavior, are inherently based on intraindividual processes. To accommodate this mismatch between study design and theory, research frequently relies on an implicit assumption that group-level, between-person inferences extend to individual-level, within-person processes. The assumption of group-to-individual generalizability, formally referred to as ergodicity, requires that a process be both homogenous within a population and stationary within individuals over time. Our goal in this review is to assess this assumption and provide an accessible introduction to idiographic science (study of the individual) for the cognitive neuroscientist, ultimately laying a foundation for increased focus on the study of intraindividual processes. We first review the history of idiographic science in psychology to connect this longstanding literature with recent individual-level research goals in cognitive neuroscience. We then consider two requirements of group-to-individual generalizability, pattern homogeneity and stationarity, and suggest that most processes in cognitive neuroscience do not meet these assumptions. Consequently, interindividual findings are inappropriate for the intraindividual inferences that many theories are based on. To address this challenge, we suggest precision imaging as an ideal path forward for intraindividual study and present a research framework for complementary interindividual and intraindividual study.

Volumetric Assessment and Graph Theoretical Analysis of Thalamic Nuclei in Essential Tremor

INTRODUCTION

Essential tremor (ET) is a neurological disorder primarily characterized by upper limb action tremor. It is widely recognized that the thalamus is implicated in ET pathophysiology, playing a central role in treatment approaches. This study aimed to explore thalamic morphology, assessing macrostructural changes and intrinsic thalamic networks in ET patients.

METHODS

A total of 109 ET (41 with and 68 without resting tremor) and 81 healthy controls (HC) were enrolled in the study. An automatic probabilistic segmentation of thalamic nuclei was employed on T1-weighted MRI images using FreeSurfer 7.4. Subsequently, volumetric data were extracted, and graph theoretical analysis was applied on the cortical-thalamic nuclei network, assessing global and local network properties.

RESULTS

No significant differences were observed in the volume of thalamic nuclei between ET patients and HC. ET patients exhibited significant alterations in the global thalamic network, suggesting a less efficient brain network in comparison with HC. ET patients also showed local alterations of thalamic network such as lower eccentricity and path length in the ventral nuclei and reduced efficiency in the pulvinar, indicating a less interconnected network. No significant differences were observed between ET patients with and without rest tremor.

CONCLUSION

Our study demonstrates reduced global and local efficiency of brain networks in ET patients, suggesting impaired communication and interconnection between brain regions. These findings confirm the involvement of the ventral lateral and pulvinar nuclei as key regions in tremor pathophysiology in ET patients, supporting the targeting of these regions for therapeutic approaches.

Using precision approaches to improve brain-behavior prediction

Predicting individual behavioral traits from brain idiosyncrasies has broad practical implications, yet predictions vary widely. This constraint may be driven by a combination of signal and noise in both brain and behavioral variables. Here, we expand on this idea, highlighting the potential of extended sampling 'precision' studies. First, we discuss their relevance to improving the reliability of individualized estimates by minimizing measurement noise. Second, we review how targeted within-subject experiments, when combined with individualized analysis or modeling frameworks, can maximize signal. These improvements in signal-to-noise facilitated by precision designs can help boost prediction studies. We close by discussing the integration of precision approaches with large-sample consortia studies to leverage the advantages of both.

Evidence for convergence of distributed cortical processing in band-like functional zones in human entorhinal cortex

The wide array of cognitive functions associated with the hippocampus is supported through interactions with the cerebral cortex. However, most of the direct cortical input to the hippocampus originates in the entorhinal cortex, forming the hippocampal-entorhinal system. In humans, the role of the entorhinal cortex in mediating hippocampal-cortical interactions remains unknown. In this study, we used precision neuroimaging to examine the distributed cortical anatomy associated with the human hippocampal-entorhinal system. Consistent with animal anatomy, our results associate different subregions of the entorhinal cortex with different parts of the hippocampus long axis. Furthermore, we find that the entorhinal cortex comprises three band-like zones that are associated with functionally distinct cortical networks. Importantly, the entorhinal cortex bands traverse the proposed human homologs of rodent lateral and medial entorhinal cortices. Finally, we show that the entorhinal cortex is a major convergence area of distributed cortical processing and that the topography of cortical networks associated with the anterior medial temporal lobe mirrors the macroscale structure of high-order cortical processing.

Distributed associations among white matter hyperintensities and structural brain networks with fluid cognition in healthy aging

White matter hyperintensities (WMHs) are associated with age-related cognitive impairment and increased risk of Alzheimer's disease. However, the manner by which WMHs contribute to cognitive impairment is unclear. Using a combination of predictive modeling and network neuroscience, we investigated the relationship between structural white matter connectivity and age, fluid cognition, and WMHs in 68 healthy adults (18-78 years). Consistent with previous work, WMHs were increased in older adults and exhibited a strong negative association with fluid cognition. Extending previous work, using predictive modeling, we demonstrated that age, WMHs, and fluid cognition were jointly associated with widespread alterations in structural connectivity. Subcortical-cortical connections between the thalamus/basal ganglia and frontal and parietal regions of the default mode and frontoparietal networks were most prominent. At the network level, both age and WMHs were negatively associated with network density and communicability, and positively associated with modularity. Spatially, WMHs were most prominent in arterial zones served by the middle cerebral artery and associated lenticulostriate branches that supply subcortical regions. Finally, WMHs overlapped with all major white matter tracts, most prominently in tracts that facilitate subcortical-cortical communication and are implicated in fluid cognition, including the anterior thalamic-radiations and forceps minor. Finally, results of mediation analyses suggest that whole-brain WMH load influences age-related decline in fluid cognition. Thus, across multiple levels of analysis, we showed that WMHs were increased in older adults and associated with altered structural white matter connectivity and network topology involving subcortical-cortical pathways critical for fluid cognition.

The promise of precision functional mapping for neuroimaging in psychiatry

Precision functional mapping (PFM) is a neuroimaging approach to reliably estimate metrics of brain function from individual people via the collection of large amounts of fMRI data (hours per person). This method has revealed much about the inter-individual variation of functional brain networks. While standard group-level studies, in which we average brain measures across groups of people, are important in understanding the generalizable neural underpinnings of neuropsychiatric disorders, many disorders are heterogeneous in nature. This heterogeneity often complicates clinical care, leading to patient uncertainty when considering prognosis or treatment options. We posit that PFM methods may help streamline clinical care in the future, fast-tracking the choice of personalized treatment that is most compatible with the individual. In this review, we provide a history of PFM studies, foundational results highlighting the benefits of PFM methods in the pursuit of an advanced understanding of individual differences in functional network organization, and possible avenues where PFM can contribute to clinical translation of neuroimaging research results in the way of personalized treatment in psychiatry.

Connectome-based fingerprinting: reproducibility, precision, and behavioral prediction

Functional magnetic resonance imaging-based functional connectivity enables the non-invasive mapping of individual differences in brain functional organization to individual differences in a vast array of behavioral phenotypes. This flexibility has renewed the search for neuroimaging-based biomarkers that exhibit reproducibility, prediction, and precision. Functional connectivity-based measures that share these three characteristics are key to achieving this goal. Here, we review the functional connectome fingerprinting approach and discuss its value, not only as a simple and intuitive conceptualization of the "functional connectome" that provides new insights into how the connectome is altered in association with psychiatric symptoms, but also as a straightforward and interpretable method for indexing the reproducibility of functional connectivity-based measures. We discuss how these advantages provide new avenues for strengthening reproducibility, precision, and behavioral prediction for functional connectomics and we consider new directions toward discovering better biomarkers for neuropsychiatric conditions.

Cross-species striatal hubs: Linking anatomy to resting-state connectivity

Corticostriatal connections are essential for motivation, cognition, and behavioral flexibility. There is broad interest in using resting-state functional magnetic resonance imaging (rs-fMRI) to link circuit dysfunction in these connections with neuropsychiatric disorders. In this paper, we used tract-tracing data from non-human primates (NHPs) to assess the likelihood of monosynaptic connections being represented in rs-fMRI data of NHPs and humans. We also demonstrated that existing hub locations in the anatomical data can be identified in the rs-fMRI data from both species. To characterize this in detail, we mapped the complete striatal projection zones from 27 tract-tracer injections located in the orbitofrontal cortex (OFC), dorsal anterior cingulate cortex (dACC), ventromedial prefrontal cortex (vmPFC), ventrolateral PFC (vlPFC), and dorsal PFC (dPFC) of macaque monkeys. Rs-fMRI seeds at the same regions of NHP and homologous regions of human brains showed connectivity maps in the striatum mostly consistent with those observed in the tracer data. We then examined the location of overlap in striatal projection zones. The medial rostral dorsal caudate connected with all five frontocortical regions evaluated in this study in both modalities (tract-tracing and rs-fMRI) and species (NHP and human). Other locations in the caudate also presented an overlap of four frontocortical regions, suggesting the existence of different locations with lower levels of input diversity. Small retrograde tracer injections and rs-fMRI seeds in the striatum confirmed these cortical input patterns. This study sets the ground for future studies evaluating rs-fMRI in clinical samples to measure anatomical corticostriatal circuit dysfunction and identify connectional hubs to provide more specific treatment targets for neurological and psychiatric disorders.

Precision Functional Mapping to Advance Developmental Psychiatry Research

Many psychiatric conditions have their roots in early development. Individual differences in prenatal brain function (which is influenced by a combination of genetic risk and the prenatal environment) likely interact with individual differences in postnatal experience, resulting in substantial variation in brain functional organization and development in infancy. Neuroimaging has been a powerful tool for understanding typical and atypical brain function and holds promise for uncovering the neurodevelopmental basis of psychiatric illness; however, its clinical utility has been relatively limited thus far. A substantial challenge in this endeavor is the traditional approach of averaging brain data across groups despite individuals varying in their brain organization, which likely obscures important clinically relevant individual variation. Precision functional mapping (PFM) is a neuroimaging technique that allows the capture of individual-specific and highly reliable functional brain properties. Here, we discuss how PFM, through its focus on individuals, has provided novel insights for understanding brain organization across the life span and its promise in elucidating the neural basis of psychiatric disorders. We first summarize the extant literature on PFM in normative populations, followed by its limited utilization in studying psychiatric conditions in adults. We conclude by discussing the potential for infant PFM in advancing developmental precision psychiatry applications, given that many psychiatric disorders start during early infancy and are associated with changes in individual-specific functional neuroanatomy. By exploring the intersection of PFM, development, and psychiatric research, this article underscores the importance of individualized approaches in unraveling the complexities of brain function and improving clinical outcomes across development.

Ventral Striatum is Preferentially Correlated with the Salience Network Including Regions in Dorsolateral Prefrontal Cortex

The ventral striatum (VS) receives input from the cerebral cortex and is modulated by midbrain dopaminergic projections in support of processing reward and motivation. Here we explored the organization of cortical regions linked to the human VS using within-individual functional connectivity MRI in intensively scanned participants. In two initial participants (scanned 31 sessions each), seed regions in the VS were preferentially correlated with distributed cortical regions that are part of the Salience (SAL) network. The VS seed region recapitulated SAL network topography in each individual including anterior and posterior midline regions, anterior insula, and dorsolateral prefrontal cortex (DLPFC) - a topography that was distinct from a nearby striatal seed region. The region of DLPFC linked to the VS is positioned adjacent to regions associated with domain-flexible cognitive control. The full pattern was replicated in independent data from the same two individuals and generalized to 15 novel participants (scanned 8 or more sessions each). These results suggest that the VS forms a cortico-basal ganglia loop as part of the SAL network. The DLPFC is a neuromodulatory target to treat major depressive disorder. The present results raise the possibility that the DLPFC may be an effective neuromodulatory target because of its preferential coupling to the VS and suggests a path toward further personalization.

Structure-function coupling in highly sampled individual brains

Structural connectivity (SC) between distant regions of the brain support synchronized function known as functional connectivity (FC) and give rise to the large-scale brain networks that enable cognition and behavior. Understanding how SC enables FC is important to understand how injuries to SC may alter brain function and cognition. Previous work evaluating whole-brain SC-FC relationships showed that SC explained FC well in unimodal visual and motor areas, but only weakly in association areas, suggesting a unimodal-heteromodal gradient organization of SC-FC coupling. However, this work was conducted in group-averaged SC/FC data. Thus, it could not account for inter-individual variability in the locations of cortical areas and white matter tracts. We evaluated the correspondence of SC and FC within three highly sampled healthy participants. For each participant, we collected 78 min of diffusion-weighted MRI for SC and 360 min of resting state fMRI for FC. We found that FC was best explained by SC in visual and motor systems, as well as in anterior and posterior cingulate regions. A unimodal-to-heteromodal gradient could not fully explain SC-FC coupling. We conclude that the SC-FC coupling of the anterior-posterior cingulate circuit is more similar to unimodal areas than to heteromodal areas.

Functional connectivity across the human subcortical auditory system using an autoregressive matrix-Gaussian copula graphical model approach with partial correlations

The auditory system comprises multiple subcortical brain structures that process and refine incoming acoustic signals along the primary auditory pathway. Due to technical limitations of imaging small structures deep inside the brain, most of our knowledge of the subcortical auditory system is based on research in animal models using invasive methodologies. Advances in ultrahigh-field functional magnetic resonance imaging (fMRI) acquisition have enabled novel noninvasive investigations of the human auditory subcortex, including fundamental features of auditory representation such as tonotopy and periodotopy. However, functional connectivity across subcortical networks is still underexplored in humans, with ongoing development of related methods. Traditionally, functional connectivity is estimated from fMRI data with full correlation matrices. However, partial correlations reveal the relationship between two regions after removing the effects of all other regions, reflecting more direct connectivity. Partial correlation analysis is particularly promising in the ascending auditory system, where sensory information is passed in an obligatory manner, from nucleus to nucleus up the primary auditory pathway, providing redundant but also increasingly abstract representations of auditory stimuli. While most existing methods for learning conditional dependency structures based on partial correlations assume independently and identically Gaussian distributed data, fMRI data exhibit significant deviations from Gaussianity as well as high-temporal autocorrelation. In this paper, we developed an autoregressive matrix-Gaussian copula graphical model (ARMGCGM) approach to estimate the partial correlations and thereby infer the functional connectivity patterns within the auditory system while appropriately accounting for autocorrelations between successive fMRI scans. Our results show strong positive partial correlations between successive structures in the primary auditory pathway on each side (left and right), including between auditory midbrain and thalamus, and between primary and associative auditory cortex. These results are highly stable when splitting the data in halves according to the acquisition schemes and computing partial correlations separately for each half of the data, as well as across cross-validation folds. In contrast, full correlation-based analysis identified a rich network of interconnectivity that was not specific to adjacent nodes along the pathway. Overall, our results demonstrate that unique functional connectivity patterns along the auditory pathway are recoverable using novel connectivity approaches and that our connectivity methods are reliable across multiple acquisitions.

The Middle Managers: Thalamic and Cholinergic Contributions To Coordinating Top-Down And Bottom-Up Processing

Methodological advances have facilitated extensive revision of traditional views of thalamic and cholinergic contributions to cognition and behavior. Increasing attention to the integrative capabilities of the thalamus highlights its role beyond a simple sensory relay, recognizing its complex connectivity and role in orchestrating different phases of attention. Correspondingly, modern conceptualizations position the cholinergic system as key in integrating sensory information with attention and goals. These theoretical developments have occurred largely in parallel, but have large conceptual overlap. We review this overlap, including evidence from animal, patient, neuroimaging, and computational studies, and suggest thalamo-cholinergic cognition plays a key role in coordinating stable and flexible attention.

Psilocybin desynchronizes the human brain

A single dose of psilocybin, a psychedelic that acutely causes distortions of space-time perception and ego dissolution, produces rapid and persistent therapeutic effects in human clinical trials1-4. In animal models, psilocybin induces neuroplasticity in cortex and hippocampus5-8. It remains unclear how human brain network changes relate to subjective and lasting effects of psychedelics. Here we tracked individual-specific brain changes with longitudinal precision functional mapping (roughly 18 magnetic resonance imaging visits per participant). Healthy adults were tracked before, during and for 3 weeks after high-dose psilocybin (25 mg) and methylphenidate (40 mg), and brought back for an additional psilocybin dose 6-12 months later. Psilocybin massively disrupted functional connectivity (FC) in cortex and subcortex, acutely causing more than threefold greater change than methylphenidate. These FC changes were driven by brain desynchronization across spatial scales (areal, global), which dissolved network distinctions by reducing correlations within and anticorrelations between networks. Psilocybin-driven FC changes were strongest in the default mode network, which is connected to the anterior hippocampus and is thought to create our sense of space, time and self. Individual differences in FC changes were strongly linked to the subjective psychedelic experience. Performing a perceptual task reduced psilocybin-driven FC changes. Psilocybin caused persistent decrease in FC between the anterior hippocampus and default mode network, lasting for weeks. Persistent reduction of hippocampal-default mode network connectivity may represent a neuroanatomical and mechanistic correlate of the proplasticity and therapeutic effects of psychedelics.

Heritability of functional gradients in the human subcortico-cortical connectivity

The human subcortex plays a pivotal role in cognition and is widely implicated in the pathophysiology of many psychiatric disorders. However, the heritability of functional gradients based on subcortico-cortical functional connectivity remains elusive. Here, leveraging twin functional MRI (fMRI) data from both the Human Connectome Project (n = 1023) and the Adolescent Brain Cognitive Development study (n = 936) datasets, we construct large-scale subcortical functional gradients and delineate an increased principal functional gradient pattern from unimodal sensory/motor networks to transmodal association networks. We observed that this principal functional gradient is heritable, and the strength of heritability exhibits a heterogeneous pattern along a hierarchical unimodal-transmodal axis in subcortex for both young adults and children. Furthermore, employing a machine learning framework, we show that this heterogeneous pattern of the principal functional gradient in subcortex can accurately discern the relationship between monozygotic twin pairs and dizygotic twin pairs with an accuracy of 76.2% (P < 0.001). The heritability of functional gradients is associated with the anatomical myelin proxied by MRI-derived T1-weighted/T2-weighted (T1w/T2w) ratio mapping in subcortex. This study provides new insights into the biological basis of subcortical functional hierarchy by revealing the structural and genetic properties of the subcortical functional gradients.

Human striatal association megaclusters

The striatum receives projections from multiple regions of the cerebral cortex consistent with the role of the basal ganglia in diverse motor, affective, and cognitive functions. Within the striatum, the caudate receives projections from association cortex, including multiple distinct regions of prefrontal cortex. Building on recent insights about the details of how juxtaposed cortical networks are specialized for distinct aspects of higher-order cognition, we revisited caudate organization using within-individual precision neuroimaging initially in two intensively scanned individuals (each scanned 31 times). Results revealed that the caudate has side-by-side regions that are coupled to at least five distinct distributed association networks, paralleling the organization observed in the cerebral cortex. We refer to these spatial groupings of regions as striatal association megaclusters. Correlation maps from closely juxtaposed seed regions placed within the megaclusters recapitulated the five distinct cortical networks, including their multiple spatially distributed regions. Striatal association megaclusters were explored in 15 additional participants (each scanned at least 8 times), finding that their presence generalizes to new participants. Analysis of the laterality of the regions within the megaclusters further revealed that they possess asymmetries paralleling their cortical counterparts. For example, caudate regions linked to the language network were left lateralized. These results extend the general notion of parallel specialized basal ganglia circuits with the additional discovery that, even within the caudate, there is fine-grained separation of multiple distinct higher-order networks that reflects the organization and lateralization found in the cerebral cortex.NEW & NOTEWORTHY An individualized precision neuroimaging approach reveals juxtaposed zones of the caudate that are coupled with five distinct networks in association cortex. The organization of these caudate zones recapitulates organization observed in the cerebral cortex and extends the notion of specialized basal ganglia circuits.

Alterations in cortical thickness and volumes of subcortical structures in pediatric patients with complete spinal cord injury

AIMS

To study the changes in cortical thickness and subcortical gray matter structures in children with complete spinal cord injury (CSCI), reveal the possible causes of dysfunction beyond sensory motor dysfunction after CSCI, and provide a possible neural basis for corresponding functional intervention training.

METHODS

Thirty-seven pediatric CSCI patients and 34 age-, gender-matched healthy children as healthy controls (HCs) were recruited. The 3D high-resolution T1-weighted structural images of all subjects were obtained using a 3.0 Tesla MRI system. Statistical differences between pediatric CSCI patients and HCs in cortical thickness and volumes of subcortical gray matter structures were evaluated. Then, correlation analyses were performed to analyze the correlation between the imaging indicators and clinical characteristics.

RESULTS

Compared with HCs, pediatric CSCI patients showed decreased cortical thickness in the right precentral gyrus, superior temporal gyrus, and posterior segment of the lateral sulcus, while increased cortical thickness in the right lingual gyrus and inferior occipital gyrus. The volume of the right thalamus in pediatric CSCI patients was significantly smaller than that in HCs. No significant correlation was found between the imaging indicators and the injury duration, sensory scores, and motor scores of pediatric CSCI patients.

CONCLUSIONS

These findings demonstrated that the brain structural reorganizations of pediatric CSCI occurred not only in sensory motor areas but also in cognitive and visual related brain regions, which may suggest that the visual processing, cognitive abnormalities, and related early intervention therapy also deserve greater attention beyond sensory motor rehabilitation training in pediatric CSCI patients.

BAI-Net: Individualized Anatomical Cerebral Cartography Using Graph Neural Network

Brain atlas is an important tool in the diagnosis and treatment of neurological disorders. However, due to large variations in the organizational principles of individual brains, many challenges remain in clinical applications. Brain atlas individualization network (BAI-Net) is an algorithm that subdivides individual cerebral cortex into segregated areas using brain morphology and connectomes. The presented method integrates group priors derived from a population atlas, adjusts areal probabilities using the context of connectivity fingerprints derived from the fiber-tract embedding of tractography, and provides reliable and explainable individualized brain areas across multiple sessions and scanners. We demonstrate that BAI-Net outperforms the conventional iterative clustering approach by capturing significantly heritable topographic variations in individualized cartographies. The topographic variability of BAI-Net cartographies has shown strong associations with individual variability in brain morphology, connectivity as well as higher relationship on individual cognitive behaviors and genetics. This study provides an explainable framework for individualized brain cartography that may be useful in the precise localization of neuromodulation and treatments on individual brains.

Towards personalized precision functional mapping in infancy

The precise network topology of functional brain systems is highly specific to individuals and undergoes dramatic changes during critical periods of development. Large amounts of high-quality resting state data are required to investigate these individual differences, but are difficult to obtain in early infancy. Using the template matching method, we generated a set of infant network templates to use as priors for individualized functional resting-state network mapping in two independent neonatal datasets with extended acquisition of resting-state functional MRI (fMRI) data. We show that template matching detects all major adult resting-state networks in individual infants and that the topology of these resting-state network maps is individual-specific. Interestingly, there was no plateau in within-subject network map similarity with up to 25 minutes of resting-state data, suggesting that the amount and/or quality of infant data required to achieve stable or high-precision network maps is higher than adults. These findings are a critical step towards personalized precision functional brain mapping in infants, which opens new avenues for clinical applicability of resting-state fMRI and potential for robust prediction of how early functional connectivity patterns relate to subsequent behavioral phenotypes and health outcomes.

A precision functional atlas of personalized network topography and probabilities

Although the general location of functional neural networks is similar across individuals, there is vast person-to-person topographic variability. To capture this, we implemented precision brain mapping functional magnetic resonance imaging methods to establish an open-source, method-flexible set of precision functional network atlases-the Masonic Institute for the Developing Brain (MIDB) Precision Brain Atlas. This atlas is an evolving resource comprising 53,273 individual-specific network maps, from more than 9,900 individuals, across ages and cohorts, including the Adolescent Brain Cognitive Development study, the Developmental Human Connectome Project and others. We also generated probabilistic network maps across multiple ages and integration zones (using a new overlapping mapping technique, Overlapping MultiNetwork Imaging). Using regions of high network invariance improved the reproducibility of executive function statistical maps in brain-wide associations compared to group average-based parcellations. Finally, we provide a potential use case for probabilistic maps for targeted neuromodulation. The atlas is expandable to alternative datasets with an online interface encouraging the scientific community to explore and contribute to understanding the human brain function more precisely.

Thalamic nuclei segmentation from T1-weighted MRI: Unifying and benchmarking state-of-the-art methods

The thalamus and its constituent nuclei are critical for a broad range of cognitive, linguistic, and sensorimotor processes, and are implicated in many neurological and neurodegenerative conditions. However, the functional involvement and specificity of thalamic nuclei in human neuroimaging work is underappreciated and not well studied due, in part, to technical challenges of accurately identifying and segmenting nuclei. This challenge is further exacerbated by a lack of common nomenclature for comparing segmentation methods. Here, we use data from healthy young (Human Connectome Project, n = 100) and older healthy adults, plus those with mild cognitive impairment and Alzheimer's disease (Alzheimer's Disease Neuroimaging Initiative, n = 540), to benchmark four state-of-the-art thalamic segmentation methods for T1 MRI (FreeSurfer, histogram-based polynomial synthesis [HIPS]-THOMAS, synthesized contrast segmentation [SCS]-convolutional neural network [CNN], and T1-THOMAS) under a single segmentation framework. Segmentations were compared using overlap and dissimilarity metrics to the Morel stereotaxic atlas, a widely accepted thalamic atlas. We also quantified each method's estimation of thalamic nuclear degeneration across Alzheimer's disease progression, and how accurately early and late mild cognitive impairment, and Alzheimer's disease could be distinguished from healthy controls. We show that the HIPS-THOMAS approach produced the most effective segmentations of individual thalamic nuclei relative to the Morel atlas, and was also most accurate in discriminating healthy controls from those with mild cognitive impairment and Alzheimer's disease using individual nucleus volumes. This latter result was different when using whole thalamus volumes, where the SCS-CNN approach was the most accurate in classifying healthy controls. This work is the first to systematically compare the efficacy of anatomical thalamic segmentation approaches under a unified nomenclature. We also provide recommendations of which segmentation method to use for studying the functional relevance of specific thalamic nuclei, based on their overlap and dissimilarity with the Morel atlas.

Modeling the neurocognitive dynamics of language across the lifespan

Healthy aging is associated with a heterogeneous decline across cognitive functions, typically observed between language comprehension and language production (LP). Examining resting-state fMRI and neuropsychological data from 628 healthy adults (age 18-88) from the CamCAN cohort, we performed state-of-the-art graph theoretical analysis to uncover the neural mechanisms underlying this variability. At the cognitive level, our findings suggest that LP is not an isolated function but is modulated throughout the lifespan by the extent of inter-cognitive synergy between semantic and domain-general processes. At the cerebral level, we show that default mode network (DMN) suppression coupled with fronto-parietal network (FPN) integration is the way for the brain to compensate for the effects of dedifferentiation at a minimal cost, efficiently mitigating the age-related decline in LP. Relatedly, reduced DMN suppression in midlife could compromise the ability to manage the cost of FPN integration. This may prompt older adults to adopt a more cost-efficient compensatory strategy that maintains global homeostasis at the expense of LP performances. Taken together, we propose that midlife represents a critical neurocognitive juncture that signifies the onset of LP decline, as older adults gradually lose control over semantic representations. We summarize our findings in a novel synergistic, economical, nonlinear, emergent, cognitive aging model, integrating connectomic and cognitive dimensions within a complex system perspective.

Neuromelanin-sensitive magnetic resonance imaging in the study of mental disorder: A systematic review

Dopamine and norepinephrine are implicated in the pathophysiology of mental disorders, but non-invasive study of their neuronal function remains challenging. Recent research suggests that neuromelanin-sensitive magnetic resonance imaging (NM-MRI) techniques may overcome this limitation by enabling the non-invasive imaging of the substantia nigra (SN)/ ventral tegmental area (VTA) dopaminergic and locus coeruleus (LC) noradrenergic systems. A review of 19 studies that met the criteria for NM-MRI application in mental disorders found that despite the use of heterogeneous sequence parameters and metrics, nearly all studies reported differences in contrast ratio (CNR) of LC or SN/VTA between patients with mental disorders and healthy controls. These findings suggest that NM-MRI is a valuable tool in psychiatry, but the differences in sequence parameters across studies hinder comparability, and a standardized analysis pipeline is needed to improve the reliability of results. Further research using standardized methods is needed to better understand the role of dopamine and norepinephrine in mental disorders.

Personalized and Circuit-Based Transcranial Magnetic Stimulation: Evidence, Controversies, and Opportunities

The development of neuroimaging methodologies to map brain connectivity has transformed our understanding of psychiatric disorders, the distributed effects of brain stimulation, and how transcranial magnetic stimulation can be best employed to target and ameliorate psychiatric symptoms. In parallel, neuroimaging research has revealed that higher-order brain regions such as the prefrontal cortex, which represent the most common therapeutic brain stimulation targets for psychiatric disorders, show some of the highest levels of interindividual variation in brain connectivity. These findings provide the rationale for personalized target site selection based on person-specific brain network architecture. Recent advances have made it possible to determine reproducible personalized targets with millimeter precision in clinically tractable acquisition times. These advances enable the potential advantages of spatially personalized transcranial magnetic stimulation targeting to be evaluated and translated to basic and clinical applications. In this review, we outline the motivation for target site personalization, preliminary support (mostly in depression), convergent evidence from other brain stimulation modalities, and generalizability beyond depression and the prefrontal cortex. We end by detailing methodological recommendations, controversies, and notable alternatives. Overall, while this research area appears highly promising, the value of personalized targeting remains unclear, and dedicated large prospective randomized clinical trials using validated methodology are critical.

A distinctive subcortical functional connectivity pattern linking negative affect and treatment outcome in major depressive disorder

Major depressive disorder (MDD) is associated with functional disturbances in subcortical regions. In this naturalistic prospective study (NCT03294525), we aimed to investigate relationships among subcortical functional connectivity (FC), mood symptom profiles and treatment outcome in MDD using multivariate methods. Medication-free participants with MDD (n = 135) underwent a functional magnetic resonance imaging scan at baseline and completed posttreatment clinical assessment after 8 weeks of antidepressant monotherapy. We used partial least squares (PLS) correlation analysis to explore the association between subcortical FC and mood symptom profiles. FC score, reflecting the weighted representation of each individual in this association, was computed. Replication analysis was undertaken in an independent sample (n = 74). We also investigated the relationship between FC score and treatment outcome in the main sample. A distinctive subcortical connectivity pattern was found to be associated with negative affect. In general, higher FC between the caudate, putamen and thalamus was associated with greater negative affect. This association was partly replicated in the independent sample (similarity between the two samples: r = 0.66 for subcortical connectivity, r = 0.75 for mood symptom profile). Lower FC score predicted both remission and response to treatment after 8 weeks of antidepressant monotherapy. The emphasis here on the role of dorsal striatum and thalamus consolidates prior work of subcortical connectivity in MDD. The findings provide insight into the pathogenesis of MDD, linking subcortical FC with negative affect. However, while the FC score significantly predicted treatment outcome, the low odds ratio suggests that finding predictive biomarkers for depression remains an aspiration.

Thalamic deep brain stimulation for tourette syndrome increases cortical beta activity

BACKGROUND

Deep brain stimulation (DBS) of the thalamus can effectively reduce tics in severely affected patients with Tourette syndrome (TS). Its effect on cortical oscillatory activity is currently unknown.

OBJECTIVE

We assessed whether DBS modulates beta activity at fronto-central electrodes. We explored concurrent EEG sources and probabilistic stimulation maps.

METHODS

Resting state EEG of TS patients treated with thalamic DBS was recorded in repeated DBS-on and DBS-off states. A mixed linear model was employed for statistical evaluation. EEG sources were estimated with eLORETA. Thalamic probabilistic stimulation maps were obtained by assigning beta power difference scores (DBS-on minus DBS-off) to stimulation sites.

RESULTS

We observed increased beta power in DBS-on compared to DBS-off states. Modulation of cortical beta activity was localized to the midcingulate cortex. Beta modulation was more pronounced when stimulating the thalamus posteriorly, peaking in the ventral posterior nucleus.

CONCLUSION

Thalamic DBS in TS patients modulates beta frequency oscillations presumably important for sensorimotor function and relevant to TS pathophysiology.

Non-human contributions to personality neuroscience: From fish through primates - a concluding editorial overview

This special issue attempts to integrate personality, psychopathology, and neuroscience as means to improve understanding of specific traits and trait structures in humans. The key strategy is to dive into comparative research using a range of species to provide simple models. This strategy has, as its foundation, the fact that the most basic functions, and their supporting neural systems, are highly conserved in evolution. The papers collected in the issue show that, from fish, through rats, to primates, the homologies in brain systems and underlying functions (despite species-specific forms of expression) allow simpler cases to provide insights into the neurobiology behind more complex ones including human. Our introductory editorial paper to this special issue took a bottom-up approach, starting with the genetics of conserved brain systems and working up to cognition. Here, we deconstruct the different aspects of personality, progressing from more complex ones in primates to least complex in fish. With the primate section, we summarize papers that discuss the factors that contribute to sociability in primates and how they apply to healthy and pathological human personality traits. In the rat section, the focus is driven by psychopathology and the way that "high" strains selected for extreme behaviors can illuminate the neurobiology of motivated responses to environmental cues. The section on fish summarizes papers that look into the most fundamental emotional reactions to the environment that are governed by primitive and conserved brain structures. This raises metatheoretical questions on the nature of traits and to a section that asks "which animals have personalities." We believe that the issue as a whole provides a nuanced answer to this question and shines a new, comparative, light on the interpretation of personality structure and the effects on it of evolution.

Brain connectivity and academic skills in English learners

English learners (ELs) are a rapidly growing population in schools in the United States with limited experience and proficiency in English. To better understand the path for EL's academic success in school, it is important to understand how EL's brain systems are used for academic learning in English. We studied, in a cohort of Hispanic middle-schoolers (n = 45, 22F) with limited English proficiency and a wide range of reading and math abilities, brain network properties related to academic abilities. We applied a method for localizing brain regions of interest (ROIs) that are group-constrained, yet individually specific, to test how resting state functional connectivity between regions that are important for academic learning (reading, math, and cognitive control regions) are related to academic abilities. ROIs were selected from task localizers probing reading and math skills in the same participants. We found that connectivity across all ROIs, as well as connectivity of just the cognitive control ROIs, were positively related to measures of reading skills but not math skills. This work suggests that cognitive control brain systems have a central role for reading in ELs. Our results also indicate that an individualized approach for localizing brain function may clarify brain-behavior relationships.

Should one go for individual- or group-level brain parcellations? A deep-phenotyping benchmark

The analysis and understanding of brain characteristics often require considering region-level information rather than voxel-sampled data. Subject-specific parcellations have been put forward in recent years, as they can adapt to individual brain organization and thus offer more accurate individual summaries than standard atlases. However, the price to pay for adaptability is the lack of group-level consistency of the data representation. Here, we investigate whether the good representations brought by individualized models are merely an effect of circular analysis, in which individual brain features are better represented by subject-specific summaries, or whether this carries over to new individuals, i.e., whether one can actually adapt an existing parcellation to new individuals and still obtain good summaries in these individuals. For this, we adapt a dictionary-learning method to produce brain parcellations. We use it on a deep-phenotyping dataset to assess quantitatively the patterns of activity obtained under naturalistic and controlled-task-based settings. We show that the benefits of individual parcellations are substantial, but that they vary a lot across brain systems.

The brainstem's red nucleus was evolutionarily upgraded to support goal-directed action

The red nucleus is a large brainstem structure that coordinates limb movement for locomotion in quadrupedal animals (Basile et al., 2021). The humans red nucleus has a different pattern of anatomical connectivity compared to quadrupeds, suggesting a unique purpose (Hatschek, 1907). Previously the function of the human red nucleus remained unclear at least partly due to methodological limitations with brainstem functional neuroimaging (Sclocco et al., 2018). Here, we used our most advanced resting-state functional connectivity (RSFC) based precision functional mapping (PFM) in highly sampled individuals (n = 5) and large group-averaged datasets (combined N ~ 45,000), to precisely examine red nucleus functional connectivity. Notably, red nucleus functional connectivity to motor-effector networks (somatomotor hand, foot, and mouth) was minimal. Instead, red nucleus functional connectivity along the central sulcus was specific to regions of the recently discovered somato-cognitive action network (SCAN; (Gordon et al., 2023)). Outside of primary motor cortex, red nucleus connectivity was strongest to the cingulo-opercular (CON) and salience networks, involved in action/cognitive control (Dosenbach et al., 2007; Newbold et al., 2021) and reward/motivated behavior (Seeley, 2019), respectively. Functional connectivity to these two networks was organized into discrete dorsal-medial and ventral-lateral zones. Red nucleus functional connectivity to the thalamus recapitulated known structural connectivity of the dento-rubral thalamic tract (DRTT) and could prove clinically useful in functionally targeting the ventral intermediate (VIM) nucleus. In total, our results indicate that far from being a 'motor' structure, the red nucleus is better understood as a brainstem nucleus for implementing goal-directed behavior, integrating behavioral valence and action plans.

Personalized functional brain network topography is associated with individual differences in youth cognition

Individual differences in cognition during childhood are associated with important social, physical, and mental health outcomes in adolescence and adulthood. Given that cortical surface arealization during development reflects the brain's functional prioritization, quantifying variation in the topography of functional brain networks across the developing cortex may provide insight regarding individual differences in cognition. We test this idea by defining personalized functional networks (PFNs) that account for interindividual heterogeneity in functional brain network topography in 9-10 year olds from the Adolescent Brain Cognitive Development℠ Study. Across matched discovery (n = 3525) and replication (n = 3447) samples, the total cortical representation of fronto-parietal PFNs positively correlates with general cognition. Cross-validated ridge regressions trained on PFN topography predict cognition in unseen data across domains, with prediction accuracy increasing along the cortex's sensorimotor-association organizational axis. These results establish that functional network topography heterogeneity is associated with individual differences in cognition before the critical transition into adolescence.

Compressed primary-to-transmodal gradient is accompanied with subcortical alterations and linked to neurotransmitters and cellular signatures in major depressive disorder

Major depressive disorder (MDD) has been shown to involve widespread changes in low-level sensorimotor and higher-level cognitive functions. Recent research found that a primary-to-transmodal gradient could capture a cortical hierarchical organization ranging from perception and action to cognition in healthy subjects, but a prominent gradient dysfunction in MDD patients. However, whether and how this cortical gradient is linked to subcortical impairments and whether it is reflected in the microscale neurotransmitter systems and cell type-specific transcriptional signatures remain largely unknown. Data were acquired from 323 MDD patients and 328 sex- and age-matched healthy controls derived from the REST-meta-MDD project, and the human brain neurotransmitter systems density maps and gene expression data were drawn from two publicly available datasets. We investigated alterations of the primary-to-transmodal gradient in MDD patients and their correlations with clinical symptoms of depression and anxiety, as well as  their paralleled subcortical impairments. The correlations between MDD-related gradient alterations and densities of the neurotransmitter systems and gene expression information were assessed, respectively. The results demonstrated that MDD patients had a compressed primary-to-transmodal gradient accompanied by paralleled alterations in subcortical regions including the caudate, amygdala, and thalamus. The case-control gradient differences were spatially correlated with the densities of the neurotransmitter systems including the serotonin and dopamine receptors, and meanwhile with gene expression enriched in astrocytes, excitatory and inhibitory neuronal cells. These findings mapped the paralleled subcortical impairments in cortical hierarchical organization and also helped us understand the possible molecular and cellular substrates of the co-occurrence of high-level cognitive impairments with low-level sensorimotor abnormalities in MDD.

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.

Paraneoplastic Neurologic Syndromes

OBJECTIVE

Progress is ongoing in understanding paraneoplastic neurologic disorders, with new syndromes and antibodies being described and more detailed evidence available to guide workup for diagnosis and treatment to improve outcomes. Many excellent reviews have summarized the molecular features of different antibodies, but this article emphasizes the clinical features of each syndrome that may help guide initial diagnosis and treatment, which often should occur before an antibody or cancer is found to confirm the diagnosis.

LATEST DEVELOPMENTS

Recent findings include updated diagnostic criteria with validated sensitivity and specificity, discovery of novel antibodies, and clinical findings that increase the likelihood of an underlying paraneoplastic disorder. Suggestive syndromes that have been recently identified include faciobrachial dystonic seizures and pilomotor auras in anti-leucine-rich glioma inactivated protein 1 encephalitis, extreme delta brush on EEG in N-methyl-d-aspartate (NMDA)-receptor encephalitis, déjà vu aura in anti-glutamic acid decarboxylase 65 (GAD65) encephalitis, and sleep disturbances in several disorders. In addition, there is confirmed utility of brain positron emission tomography (PET) and CSF markers, including carcinoembryonic antigen and oligoclonal bands, as well as improved tests for the presence of leptomeningeal cancer cells in CSF. Associations of cancer immunotherapies with paraneoplastic syndromes and herpes simplex virus encephalitis (and COVID-19) with NMDA-receptor encephalitis have been described.

ESSENTIAL POINTS

All neurologists should be aware of advances regarding paraneoplastic neurologic syndromes, as patients can present with a wide variety of neurologic symptoms and earlier diagnosis and treatment can improve outcomes.

Anterior Capsulotomy for Refractory Obsessive-Compulsive Disorder: A Tractography and Lesion Geometry study

INTRODUCTION

A bilateral anterior capsulotomy effectively treats refractory obsessive-compulsive disorder (OCD). We investigated the geometry of lesions and disruption of white matter pathways within the anterior limb of the internal capsule (ALIC) in patients with different outcomes.

METHODS

In this retrospective study, we analyzed data from 18 patients with refractory OCD who underwent capsulotomies. Patients were grouped into "responders" and "nonresponders" based on the percentage of decrease in the Yale-Brown Obsessive-Compulsive Scale (YBOCS) after surgery. We investigated neurobehavioral adverse effects and analyzed the overlap between lesions and the ventromedial prefrontal (vmPFC) and dorsolateral prefrontal (dlPFC) pathways. Probabilistic maps were constructed to investigate the relationship between lesion location and clinical outcomes.

RESULTS

Of the 18 patients who underwent capsulotomies, 12 were responders (>35% improvement in YBOCS), and six were nonresponders. The vmPFC pathway was more involved than the dlPFC pathway in responders (p = 0.01), but no significant difference was observed in nonresponders (p = 0.10). The probabilistic voxel-wise efficacy map showed a relationship between ventral voxels within the ALIC with symptom improvement. Weight gains occurred in 11/18 (61%) patients and could be associated with medial voxels within the ALIC.

CONCLUSION

The optimal outcome after capsulotomy in refractory OCD is linked to vmPFC disruption in the ALIC. Medial voxels within the ALIC could be associated with weight gains following capsulotomy.

The spatial extent of anatomical connections within the thalamus varies across the cortical hierarchy in humans and macaques

Each cortical area has a distinct pattern of anatomical connections within the thalamus, a central subcortical structure composed of functionally and structurally distinct nuclei. Previous studies have suggested that certain cortical areas may have more extensive anatomical connections that target multiple thalamic nuclei, which potentially allows them to modulate distributed information flow. However, there is a lack of quantitative investigations into anatomical connectivity patterns within the thalamus. Consequently, it remains unknown if cortical areas exhibit systematic differences in the extent of their anatomical connections within the thalamus. To address this knowledge gap, we used diffusion magnetic resonance imaging (dMRI) to perform brain-wide probabilistic tractography for 828 healthy adults from the Human Connectome Project. We then developed a framework to quantify the spatial extent of each cortical area's anatomical connections within the thalamus. Additionally, we leveraged resting-state functional MRI, cortical myelin, and human neural gene expression data to test if the extent of anatomical connections within the thalamus varied along the cortical hierarchy. Our results revealed two distinct corticothalamic tractography motifs: 1) a sensorimotor cortical motif characterized by focal thalamic connections targeting posterolateral thalamus, associated with fast, feed-forward information flow; and 2) an associative cortical motif characterized by diffuse thalamic connections targeting anteromedial thalamus, associated with slow, feed-back information flow. These findings were consistent across human subjects and were also observed in macaques, indicating cross-species generalizability. Overall, our study demonstrates that sensorimotor and association cortical areas exhibit differences in the spatial extent of their anatomical connections within the thalamus, which may support functionally-distinct cortico-thalamic information flow.

Substructure of the brain's Cingulo-Opercular network

The Cingulo-Opercular network (CON) is an executive network of the human brain that regulates actions. CON is composed of many widely distributed cortical regions that are involved in top-down control over both lower-level (i.e., motor) and higher-level (i.e., cognitive) functions, as well as in processing of painful stimuli. Given the topographical and functional heterogeneity of the CON, we investigated whether subnetworks within the CON support separable aspects of action control. Using precision functional mapping (PFM) in 15 participants with > 5 hours of resting state functional connectivity (RSFC) and task data, we identified three anatomically and functionally distinct CON subnetworks within each individual. These three distinct subnetworks were linked to Decisions, Actions, and Feedback (including pain processing), respectively, in convergence with a meta-analytic task database. These Decision, Action and Feedback subnetworks represent pathways by which the brain establishes top-down goals, transforms those goals into actions, implemented as movements, and processes critical action feedback such as pain.

Human Striatal Association Megaclusters

The striatum receives projections from multiple regions of the cerebral cortex consistent with its role in diverse motor, affective, and cognitive functions. Supporting cognitive functions, the caudate receives projections from cortical association regions. Building on recent insights about the details of how multiple cortical networks are specialized for distinct aspects of higher-order cognition, we revisited caudate organization using within-individual precision neuroimaging (n=2, each participant scanned 31 times). Detailed analysis revealed that the caudate has side-by-side zones that are coupled to at least Give distinct distributed association networks, paralleling the specialization observed in the cerebral cortex. Examining correlation maps from closely juxtaposed seed regions in the caudate recapitulated the Give distinct cerebral networks including their multiple spatially distributed regions. These results extend the general notion of parallel specialized basal ganglia circuits, with the additional discovery that even within the caudate, there is Gine-grained separation of multiple distinct higher-order networks.

Controversies and progress on standardization of large-scale brain network nomenclature

Progress in scientific disciplines is accompanied by standardization of terminology. Network neuroscience, at the level of macroscale organization of the brain, is beginning to confront the challenges associated with developing a taxonomy of its fundamental explanatory constructs. The Workgroup for HArmonized Taxonomy of NETworks (WHATNET) was formed in 2020 as an Organization for Human Brain Mapping (OHBM)-endorsed best practices committee to provide recommendations on points of consensus, identify open questions, and highlight areas of ongoing debate in the service of moving the field toward standardized reporting of network neuroscience results. The committee conducted a survey to catalog current practices in large-scale brain network nomenclature. A few well-known network names (e.g., default mode network) dominated responses to the survey, and a number of illuminating points of disagreement emerged. We summarize survey results and provide initial considerations and recommendations from the workgroup. This perspective piece includes a selective review of challenges to this enterprise, including (1) network scale, resolution, and hierarchies; (2) interindividual variability of networks; (3) dynamics and nonstationarity of networks; (4) consideration of network affiliations of subcortical structures; and (5) consideration of multimodal information. We close with minimal reporting guidelines for the cognitive and network neuroscience communities to adopt.