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

Post-Stroke Cognitive Impairment: Pathophysiological Insights into Brain Disconnectome from Advanced Neuroimaging Analysis Techniques

The neurological symptoms of stroke have traditionally provided the foundation for functional mapping of the brain. However, there are many unresolved aspects in our understanding of cerebral activity, especially regarding high-level cognitive functions. This review provides a comprehensive look at the pathophysiology of post-stroke cognitive impairment in light of recent findings from advanced imaging techniques. Combining network neuroscience and clinical neurology, our research focuses on how changes in brain networks correlate with post-stroke cognitive prognosis. More specifically, we first discuss the general consequences of stroke lesions due to damage of canonical resting-state large-scale networks or changes in the composition of the entire brain. We also review emerging methods, such as lesion-network mapping and gradient analysis, used to study the aforementioned events caused by stroke lesions. Lastly, we examine other patient vulnerabilities, such as superimposed amyloid pathology and blood-brain barrier leakage, which potentially lead to different outcomes for the brain network compositions even in the presence of similar stroke lesions. This knowledge will allow a better understanding of the pathophysiology of post-stroke cognitive impairment and provide a theoretical basis for the development of new treatments, such as neuromodulation.

Neuropsychological evidence of multi-domain network hubs in the human thalamus

Hubs in the human brain support behaviors that arise from brain network interactions. Previous studies have identified hub regions in the human thalamus that are connected with multiple functional networks. However, the behavioral significance of thalamic hubs has yet to be established. Our framework predicts that thalamic subregions with strong hub properties are broadly involved in functions across multiple cognitive domains. To test this prediction, we studied human patients with focal thalamic lesions in conjunction with network analyses of the human thalamocortical functional connectome. In support of our prediction, lesions to thalamic subregions with stronger hub properties were associated with widespread deficits in executive, language, and memory functions, whereas lesions to thalamic subregions with weaker hub properties were associated with more limited deficits. These results highlight how a large-scale network model can broaden our understanding of thalamic function for human cognition.

Linking irritability and functional brain networks: A transdiagnostic case for expanding consideration of development and environment in RDoC

The National Institute of Mental Health Research Domain Criteria (RDoC) framework promotes the dimensional and transdiagnostic operationalization of psychopathology, but consideration of the neurodevelopmental foundations of mental health problems requires deeper examination. Irritability, the dispositional tendency to angry emotion that has both mood and behavioral elements, is dimensional, transdiagnostic, and observable early in life-a promising target for the identification of early neural indicators or risk factors for psychopathology. Here, we examine functional brain networks linked to irritability from preschool to adulthood and discuss how development and early experience may influence these neural substrates. Functional connectivity measured with fMRI varies according to irritability and indicates the atypical coordination of several functional networks involved in emotion generation, emotion perception, attention, internalization, and cognitive control. We lay out an agenda to improve our understanding and detection of atypical brain:behavior patterns through advances in the characterization of both functional networks and irritability as well as the consideration and operationalization of developmental and early life environmental influences on this pathway.

Parallel hippocampal-parietal circuits for self- and goal-oriented processing

The hippocampus is critically important for a diverse range of cognitive processes, such as episodic memory, prospective memory, affective processing, and spatial navigation. Using individual-specific precision functional mapping of resting-state functional MRI data, we found the anterior hippocampus (head and body) to be preferentially functionally connected to the default mode network (DMN), as expected. The hippocampal tail, however, was strongly preferentially functionally connected to the parietal memory network (PMN), which supports goal-oriented cognition and stimulus recognition. This anterior-posterior dichotomy of resting-state functional connectivity was well-matched by differences in task deactivations and anatomical segmentations of the hippocampus. Task deactivations were localized to the hippocampal head and body (DMN), relatively sparing the tail (PMN). The functional dichotomization of the hippocampus into anterior DMN-connected and posterior PMN-connected parcels suggests parallel but distinct circuits between the hippocampus and medial parietal cortex for self- versus goal-oriented processing.

What have we really learned from functional connectivity in clinical populations?

Functional connectivity (FC), or the statistical interdependence of blood-oxygen dependent level (BOLD) signals between brain regions using fMRI, has emerged as a widely used tool for probing functional abnormalities in clinical populations due to the promise of the approach across conceptual, technical, and practical levels. With an already vast and steadily accumulating neuroimaging literature on neurodevelopmental, psychiatric, and neurological diseases and disorders in which FC is a primary measure, we aim here to provide a high-level synthesis of major concepts that have arisen from FC findings in a manner that cuts across different clinical conditions and sheds light on overarching principles. We highlight that FC has allowed us to discover the ubiquity of intrinsic functional networks across virtually all brains and clarify typical patterns of neurodevelopment over the lifespan. This understanding of typical FC maturation with age has provided important benchmarks against which to evaluate divergent maturation in early life and degeneration in late life. This in turn has led to the important insight that many clinical conditions are associated with complex, distributed, network-level changes in the brain, as opposed to solely focal abnormalities. We further emphasize the important role that FC studies have played in supporting a dimensional approach to studying transdiagnostic clinical symptoms and in enhancing the multimodal characterization and prediction of the trajectory of symptom progression across conditions. We highlight the unprecedented opportunity offered by FC to probe functional abnormalities in clinical conditions where brain function could not be easily studied otherwise, such as in disorders of consciousness. Lastly, we suggest high priority areas for future research and acknowledge critical barriers associated with the use of FC methods, particularly those related to artifact removal, data denoising and feasibility in clinical contexts.

Precision Functional Mapping of the Subcortex and Cerebellum

Human functional brain networks can be reliably characterized within individuals using precision functional mapping. This approach entails the collection of large quantities of functional magnetic resonance imaging (fMRI) data from each individual subject. Studies employing precision functional mapping in the cerebral cortex have found that individuals manifest unique representations of functional brain networks around a central tendency described by previous group average approaches. We recently extended precision functional mapping to the subcortex and cerebellum, which has revealed several novel organizational principles within these structures. Here, we detail these principles and provide insights into how precision functional mapping of subcortical structures and the cerebellum may become clinically translatable.

Basal ganglia-orbitofrontal circuits are associated with prospective memory deficits in Wilson's disease

Degenerative changes in the basal ganglia (BG) are thought to contribute to neurological symptoms in Wilson's disease (WD). However, very little is known about whether and how the BG have an influence on prospective memory (PM) by interacting with the cerebral cortex. Here, we employed structural magnetic resonance imaging to systematically examine the effect of volume atrophy of BG on cortical thickness and to evaluate the relationships between cortical thickness of regions associated with BG atrophy and PM performance in WD. Cortical thickness atrophy in the left temporal pole and medial frontal gyrus are not related to degenerative changes in BG. Cortical thickness in the left superior frontal gyrus and right orbitofrontal gyrus (ORB) have stronger correlations with volume atrophy of the left accumbens, pallidum, and putamen in WD when compared with healthy controls. Furthermore, the cortical thickness of the right ORB is not only significantly correlated with PM performance but can also distinguish the severity of PM impairment in WD. Additionally, the middle cingulate cortex was related to volume atrophy of the accumbens, and its cortical thickness has a significant positive correlation with event-based PM. Together, these findings highlight that BG-orbitofrontal circuits may serve as neural biomarkers of PM and provide implications for the neural mechanisms underlying cognitive impairment in WD.

Disentangling the influences of multiple thalamic nuclei on prefrontal cortex and cognitive control

The prefrontal cortex (PFC) has a complex relationship with the thalamus, involving many nuclei which occupy predominantly medial zones along its anterior-to-posterior extent. Thalamocortical neurons in most of these nuclei are modulated by the affective and cognitive signals which funnel through the basal ganglia. We review how PFC-connected thalamic nuclei likely contribute to all aspects of cognitive control: from the processing of information on internal states and goals, facilitating its interactions with mnemonic information and learned values of stimuli and actions, to their influence on high-level cognitive processes, attentional allocation and goal-directed behavior. This includes contributions to transformations such as rule-to-choice (parvocellular mediodorsal nucleus), value-to-choice (magnocellular mediodorsal nucleus), mnemonic-to-choice (anteromedial nucleus) and sensory-to-choice (medial pulvinar). Common mechanisms appear to be thalamic modulation of cortical gain and cortico-cortical functional connectivity. The anatomy also implies a unique role for medial PFC in modulating processing in thalamocortical circuits involving other orbital and lateral PFC regions. We further discuss how cortico-basal ganglia circuits may provide a mechanism through which PFC controls cortico-cortical functional connectivity.

Brain markers predicting response to cognitive-behavioral therapy for social anxiety disorder: an independent replication of Whitfield-Gabrieli et al. 2015

Predictive brain markers promise a number of important scientific, clinical, and societal applications. Over 600 predictive brain markers have been described in published reports, but very few have been tested in independent replication attempts. Here, we conducted an independent replication of a previously published marker predicting treatment response to cognitive-behavioral therapy for social anxiety disorder from patterns of resting-state fMRI amygdala connectivity1. The replication attempt was conducted in an existing dataset similar to the dataset used in the original report, by a team of independent investigators in consultation with the original authors. The precise model described in the original report positively predicted treatment outcomes in the replication dataset, but with marginal statistical significance, permutation test p = 0.1. The effect size was substantially smaller in the replication dataset, with the model explaining 2% of the variance in treatment outcomes, as compared to 21% in the original report. Several lines of evidence, including the current replication attempt, suggest that features of amygdala function or structure may be able to predict treatment response in anxiety disorders. However, predictive models that explain a substantial amount of variance in independent datasets will be needed for scientific and clinical applications.

Improving precision functional mapping routines with multi-echo fMRI

Rapidly developing approaches to acquiring and analyzing densely-sampled, single-subject fMRI data have opened new avenues for understanding the neurobiological basis of individual differences in behavior and could allow fMRI to become a more clinically useful tool. Here, we review briefly key insights from these precision functional mapping studies and a highlight significant barrier to their clinical translation. Specifically, that reliable delineation of functional brain networks in individual humans can require hours of resting-state fMRI data per-subject. We found recently that multi-echo fMRI improves the test-retest reliability of resting-state functional connectivity measurements, mitigating the need for acquiring large quantities of per -subject data. Because the benefits of multi-echo acquisitions are most pronounced in clinically important but artifact-prone brain regions, such as the subgenual cingulate and structures deep in the subcortex, this approach has the potential to increase the impact of precision functional mapping routines in both healthy and clinical populations.

Prolonged ketamine infusion modulates limbic connectivity and induces sustained remission of treatment-resistant depression

Ketamine produces a rapid antidepressant response in over 50% of adults with treatment-resistant depression. A long infusion of ketamine may provide durable remission of depressive symptoms, but the safety, efficacy, and neurobiological correlates are unknown. In this open-label, proof-of-principle study, adults with treatment-resistant depression (N = 23) underwent a 96-h infusion of intravenous ketamine (0.15 mg/kg/h titrated toward 0.6 mg/kg/h). Clonidine was co-administered to reduce psychotomimetic effects. We measured clinical response for 8 weeks post-infusion. Resting-state functional magnetic resonance imaging was used to assess functional connectivity in patients pre- and 2 weeks post-infusion and in matched non-depressed controls (N = 27). We hypothesized that responders to therapy would demonstrate response-dependent connectivity changes while all subjects would show treatment-dependent connectivity changes. Most participants completed infusion (21/23; mean final dose 0.54 mg/kg/h, SD 0.13). The infusion was well tolerated with minimal cognitive and psychotomimetic side effects. Depressive symptoms were markedly reduced (MADRS 29 ± 4 at baseline to 9 ± 8 one day post-infusion), which was sustained at 2 weeks (13 ± 8) and 8 weeks (15 ± 8). Imaging demonstrated a response-dependent decrease in hyperconnectivity of the subgenual anterior cingulate cortex to the default mode network, and a treatment-dependent decrease in hyperconnectivity within the limbic system (hippocampus, amygdala, medial thalamus, nucleus accumbens). In exploratory analyses, connectivity was increased between the limbic system and frontal areas, and smaller right hippocampus volume at baseline predicted larger MADRS change. A single prolonged infusion of ketamine provides a tolerated, rapid, and sustained response in treatment-resistant depression and normalizes depression-related hyperconnectivity in the limbic system and frontal lobe. ClinicalTrials.gov : Treatment Resistant Depression (Pilot), NCT01179009.

Editorial: The Centrality of Both Hyper- and Hypo-thalamocortical Connectivity in Psychosis

Long-standing hypotheses about schizophrenia as a "dysconnection" syndrome are consistent with the idea that mental illness arises in part from brain circuit disruptions, with impairments in cognition and behavior occurring because of a failure of coordinated action across multiple brain regions. One such theory, put forth by Andreasen and colleagues, suggested that schizophrenia involves a disruption in the integration of cortical-striatal-thalamic-cerebellar circuits.¹ Anatomical work in primates has shown that the thalamus is topographically organized into parallel pathways connecting specific thalamic nuclei to different regions of cortex. The medial dorsal and anterior nuclei of the thalamus project to the dorsolateral prefrontal cortex (dlPFC), whereas the lateral nuclei project more to sensorimotor regions, with similar findings in functional brain connectivity studies in humans. A large body of evidence has shown reduced connectivity from bilateral thalamic regions, medial dorsal, and anterior nuclei in particular, to the bilateral dlPFC, dorsal anterior cingulate, parts of the striatum, and bilateral cerebellum in schizophrenia.² This is often coupled increased connectivity between the thalamus, lateral nuclei in particular, and motor, visual, and/or auditory sensory regions.².

Cingulo-opercular control network and disused motor circuits joined in standby mode

Whole-brain resting-state functional MRI (rs-fMRI) during 2 wk of upper-limb casting revealed that disused motor regions became more strongly connected to the cingulo-opercular network (CON), an executive control network that includes regions of the dorsal anterior cingulate cortex (dACC) and insula. Disuse-driven increases in functional connectivity (FC) were specific to the CON and somatomotor networks and did not involve any other networks, such as the salience, frontoparietal, or default mode networks. Censoring and modeling analyses showed that FC increases during casting were mediated by large, spontaneous activity pulses that appeared in the disused motor regions and CON control regions. During limb constraint, disused motor circuits appear to enter a standby mode characterized by spontaneous activity pulses and strengthened connectivity to CON executive control regions.

ICA-based denoising strategies in breath-hold induced cerebrovascular reactivity mapping with multi echo BOLD fMRI

Performing a BOLD functional MRI (fMRI) acquisition during breath-hold (BH) tasks is a non-invasive, robust method to estimate cerebrovascular reactivity (CVR). However, movement and breathing-related artefacts caused by the BH can substantially hinder CVR estimates due to their high temporal collinearity with the effect of interest, and attention has to be paid when choosing which analysis model should be applied to the data. In this study, we evaluate the performance of multiple analysis strategies based on lagged general linear models applied on multi-echo BOLD fMRI data, acquired in ten subjects performing a BH task during ten sessions, to obtain subject-specific CVR and haemodynamic lag estimates. The evaluated approaches range from conventional regression models, i.e. including drifts and motion timecourses as nuisance regressors, applied on single-echo or optimally-combined data, to more complex models including regressors obtained from multi-echo independent component analysis with different grades of orthogonalization in order to preserve the effect of interest, i.e. the CVR. We compare these models in terms of their ability to make signal intensity changes independent from motion, as well as the reliability as measured by voxelwise intraclass correlation coefficients of both CVR and lag maps over time. Our results reveal that a conservative independent component analysis model applied on the optimally-combined multi-echo fMRI signal offers the largest reduction of motion-related effects in the signal, while yielding reliable CVR amplitude and lag estimates, although a conventional regression model applied on the optimally-combined data results in similar estimates. This work demonstrates the usefulness of multi-echo based fMRI acquisitions and independent component analysis denoising for precision mapping of CVR in single subjects based on BH paradigms, fostering its potential as a clinically-viable neuroimaging tool for individual patients. It also proves that the way in which data-driven regressors should be incorporated in the analysis model is not straight-forward due to their complex interaction with the BH-induced BOLD response.

Grasping and Manipulation: Neural Bases and Anatomical Circuitry in Humans

Neurophysiological and neuroimaging evidence suggests a significant contribution of several brain areas, including subdivisions of the parietal and the premotor cortex, during the processing of different components of hand and arm movements. Many investigations improved our knowledge about the neural processes underlying the execution of reaching and grasping actions, while few studies have directly investigated object manipulation. Most studies on the latter topic concern the use of tools to achieve specific goals. Yet, there are very few studies on pure manipulation performed in order to explore and recognize objects, as well as on manipulation performed with a high level of manual dexterity. Another dimension that is quite neglected by the available studies on grasping and manipulation is, on the one hand, the contribution of the subcortical nodes, first of all the basal ganglia and cerebellum, to these functions, and, on the other hand, recurrent connections of these structures with cortical areas. In the first part, we have reviewed the parieto-premotor and subcortical circuits underlying reaching and grasping in humans, with a focus on functional neuroimaging data. Then, we have described the main structures recruited during object manipulation. We have also reported the contribution of recent structural connectivity techniques whereby the cortico-cortical and cortico-subcortical connections of grasping-related and manipulation-related areas in the human brain can be determined. Based on our review, we have concluded that studies on cortical and subcortical circuits involved in grasping and manipulation might be promising to provide new insights about motor learning and brain plasticity in patients with motor disorders.

Morphological Abnormalities in the Basal Ganglia of Dystonia Patients

OBJECTIVE

The pathophysiology of dystonia is poorly understood. As opposed to secondary forms of dystonia, primary dystonia has long been believed to lack any neuroanatomical substrate. During trajectory planning for DBS, however, conspicuous T2-hyperinstensive signal alterations (SA) were registered within the target region, even in young patients, where ischemia is rare.

METHODS

Fifty MRIs of primary dystonia patients scheduled for DBS were analyzed. Total basal ganglia (BG) volumes, as well as proportionate SA volumes, were measured and compared to 50 age-matched control patients.

RESULTS

There was a 10-fold preponderance of percentaged SA within the globus pallidus (GP) in dystonia patients. The greatest disparity was in young patients <25 years. Also, total BG volume differences were observed with larger GP and markedly smaller putamen and caudate in the dystonia group.

CONCLUSIONS

BG morphology in primary dystonia differed from a control population. Volume reductions of the putamen and caudate may reflect functional degeneration, while volume increases of the GP may indicate overactivity. T2-hyperintensive SA in the GP of young primary dystonia patients, where microvascular lesions are highly unlikely, are striking. Their pathogenic role remains unclear.

Network variants are similar between task and rest states

Recent work has demonstrated that individual-specific variations in functional networks (termed “network variants”) can be identified in individuals using resting state functional magnetic resonance imaging (fMRI). These network variants exhibit reliability over time, suggesting that they may be trait-like markers of individual differences in brain organization. However, while networks variants are reliable at rest, is is still untested whether they are stable between task and rest states. Here, we use precision data from the Midnight Scan Club (MSC) to demonstrate that (1) task data can be used to identify network variants reliably, (2) these network variants show substantial spatial overlap with those observed in rest, although state-specific effects are present, (3) network variants assign to similar canonical functional networks in task and rest states, and (4) single tasks or a combination of multiple tasks produce similar network variants to rest. Together, these findings further reinforce the trait-like nature of network variants and demonstrate the utility of using task data to define network variants.

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.

The therapeutic mechanism of epilepsy seizures in different target areas: Research on a theoretical model

BACKGROUND

The selection of optimal target areas in the surgical treatment of epilepsy is always a difficult problem in medicine.

OBJECTIVE

We employed a theoretical calculation model to explore the control mechanism of seizures by an external voltage stimulus acting in different nerve nuclei.

METHODS

Theoretical analysis and numerical simulation were combined.

RESULTS

The globus pallidus, excitatory pyramidal neurons, striatal D1 neurons, thalamic reticular nucleus and specific relay nuclei were selected, we analyzed that the electrical stimulation has different effects in these target areas.

CONCLUSIONS

The data selected were reasonable in study, the results may give a theoretical support for similar studies in clinical.

Rapid Precision Functional Mapping of Individuals Using Multi-Echo fMRI

Resting-state functional magnetic resonance imaging (fMRI) is widely used in cognitive and clinical neuroscience, but long-duration scans are currently needed to reliably characterize individual differences in functional connectivity (FC) and brain network topology. In this report, we demonstrate that multi-echo fMRI can improve the reliability of FC-based measurements. In four densely sampled individual humans, just 10 min of multi-echo data yielded better test-retest reliability than 30 min of single-echo data in independent datasets. This effect is pronounced in clinically important brain regions, including the subgenual cingulate, basal ganglia, and cerebellum, and is linked to three biophysical signal mechanisms (thermal noise, regional variability in the rate of T2∗ decay, and S0-dependent artifacts) with spatially distinct influences. Together, these findings establish the potential utility of multi-echo fMRI for rapid precision mapping using experimentally and clinically tractable scan times and will facilitate longitudinal neuroimaging of clinical populations.

Low-motion fMRI data can be obtained in pediatric participants undergoing a 60-minute scan protocol

Performing functional magnetic resonance imaging (fMRI) scans of children can be a difficult task, as participants tend to move while being scanned. Head motion represents a significant confound in fMRI connectivity analyses. One approach to limit motion has been to use shorter MRI protocols, though this reduces the reliability of results. Hence, there is a need to implement methods to achieve high-quality, low-motion data while not sacrificing data quantity. Here we show that by using a mock scan protocol prior to a scan, in conjunction with other in-scan steps (weighted blanket and incentive system), it is possible to achieve low-motion fMRI data in pediatric participants (age range: 7-17 years old) undergoing a 60 min MRI session. We also observe that motion is low during the MRI protocol in a separate replication group of participants, including some with autism spectrum disorder. Collectively, the results indicate it is possible to conduct long scan protocols in difficult-to-scan populations and still achieve high-quality data, thus potentially allowing more reliable fMRI findings.

Individual variability in functional connectivity architecture of the mouse brain

In recent years precision fMRI has emerged in human brain research, demonstrating characterization of individual differences in brain organization. However, mechanistic investigations to the sources of individual variability are limited in humans and thus require animal models. Here, we used resting-state fMRI in awake mice to quantify the contribution of individual variation to the functional architecture of the mouse cortex. We found that the mouse connectome is also characterized by stable individual features that support connectivity-based identification. Unlike in humans, we found that individual variation is homogeneously distributed in sensory and association networks. Finally, connectome-based predictive modeling of motor behavior in the rotarod task revealed that individual variation in functional connectivity explained behavioral variability. Collectively, these results establish the feasibility of precision fMRI in mice and lay the foundation for future mechanistic investigations of individual brain organization and pre-clinical studies of brain disorders in the context of personalized medicine.

Examining cognitive change in magnetic resonance-guided focused ultrasound capsulotomy for psychiatric illness

Magnetic resonance-guided focused ultrasound (MRgFUS) anterior capsulotomy is a novel treatment option for patients with refractory obsessive compulsive disorder (OCD) or major depressive disorder (MDD). However, there is concern that lesional psychiatric surgery procedures may have adverse effects on cognition. In this study, we examined whether MRgFUS capsulotomy causes cognitive decline in patients with psychiatric illness. Ten patients with refractory OCD (n = 5) or MDD (n = 5) underwent MRgFUS capsulotomy. Cognitive functioning was measured at baseline as well as 6 months and 12 months postoperatively, with a battery of neuropsychological tests assessing domains of executive function, memory, and processing speed. Scores were analyzed at the individual-level, and changes ≥2 standard deviations were considered clinically significant. We also examined whether changes in clinical symptoms were associated with changes in cognitive performance. At baseline intellectual functioning was in the average to high-average range for the group. Following MRgFUS capsulotomy, there were no deteriorations in cognition that reached ≥2 standard deviations at 6 or 12 months. Eight out of ten patients demonstrated a ≥2 standard deviation improvement in at least one cognitive score at 6 or 12 months postoperatively. Improvements in clinical symptoms correlated significantly with self-reported improvements in frontal lobe function (p < 0.05), but not with objective measures of cognitive functioning. To summarize, MRgFUS capsulotomy did not result in cognitive decline in this cohort of patients with refractory OCD or MDD, suggesting that this procedure can be offered to patients with a very low risk of cognitive side effects.

Opportunities of connectomic neuromodulation

The process of altering neural activity - neuromodulation - has long been used to treat patients with brain disorders and answer scientific questions. Deep brain stimulation in particular has provided clinical benefit to over 150,000 patients. However, our understanding of how neuromodulation impacts the brain is evolving. Instead of focusing on the local impact at the stimulation site itself, we are considering the remote impact on brain regions connected to the stimulation site. Brain connectivity information derived from advanced magnetic resonance imaging data can be used to identify these connections and better understand clinical and behavioral effects of neuromodulation. In this article, we review studies combining neuromodulation and brain connectomics, highlighting opportunities where this approach may prove particularly valuable. We focus on deep brain stimulation, but show that the same principles can be applied to other forms of neuromodulation, such as transcranial magnetic stimulation and MRI-guided focused ultrasound. We outline future perspectives and provide testable hypotheses for future work.

Learning to control the brain through adaptive closed-loop patterned stimulation

OBJECTIVE

Stimulation of neural activity is an important scientific and clinical tool, causally testing hypotheses and treating neurodegenerative and neuropsychiatric diseases. However, current stimulation approaches cannot flexibly control the pattern of activity in populations of neurons. To address this, we developed a model-free, adaptive, closed-loop stimulation (ACLS) system that learns to use multi-site electrical stimulation to control the pattern of activity of a population of neurons.

APPROACH

The ACLS system combined multi-electrode electrophysiological recordings with multi-site electrical stimulation to simultaneously record the activity of a population of 5-15 multiunit neurons and deliver spatially-patterned electrical stimulation across 4-16 sites. Using a closed-loop learning system, ACLS iteratively updated the pattern of stimulation to reduce the difference between the observed neural response and a specific target pattern of firing rates in the recorded multiunits.

MAIN RESULTS

In silico and in vivo experiments showed ACLS learns to produce specific patterns of neural activity (in ∼15 min) and was robust to noise and drift in neural responses. In visual cortex of awake mice, ACLS learned electrical stimulation patterns that produced responses similar to the natural response evoked by visual stimuli. Similar to how repetition of a visual stimulus causes an adaptation in the neural response, the response to electrical stimulation was adapted when it was preceded by the associated visual stimulus.

SIGNIFICANCE

Our results show an ACLS system that can learn, in real-time, to generate specific patterns of neural activity. This work provides a framework for using model-free closed-loop learning to control neural activity.

Thalamus is a common locus of reading, arithmetic, and IQ: Analysis of local intrinsic functional properties

Neuroimaging studies of basic achievement skills - reading and arithmetic - often control for the effect of IQ to identify unique neural correlates of each skill. This may underestimate possible effects of common factors between achievement and IQ measures on neuroimaging results. Here, we simultaneously examined achievement (reading and arithmetic) and IQ measures in young adults, aiming to identify MRI correlates of their common factors. Resting-state fMRI (rs-fMRI) data were analyzed using two metrics assessing local intrinsic functional properties; regional homogeneity (ReHo) and fractional amplitude low frequency fluctuation (fALFF), measuring local intrinsic functional connectivity and intrinsic functional activity, respectively. ReHo highlighted the thalamus/pulvinar (a subcortical region implied for selective attention) as a common locus for both achievement skills and IQ. More specifically, the higher the ReHo values, the lower the achievement and IQ scores. For fALFF, the left superior parietal lobule, part of the dorsal attention network, was positively associated with reading and IQ. Collectively, our results highlight attention-related regions, particularly the thalamus/pulvinar as a key region related to individual differences in performance on all the three measures. ReHo in the thalamus/pulvinar may serve as a tool to examine brain mechanisms underlying a comorbidity of reading and arithmetic difficulties, which could co-occur with weakness in general intellectual abilities.

Regional, not global, functional connectivity contributes to isolated focal dystonia

OBJECTIVE

To test the hypothesis that there is shared regional or global functional connectivity dysfunction in a large cohort of patients with isolated focal dystonia affecting different body regions compared to control participants. In this case-control study, we obtained resting-state MRI scans (three or four 7.3-minute runs) with eyes closed in participants with focal dystonia (cranial [17], cervical [13], laryngeal [18], or limb [10]) and age- and sex-matched controls.

METHODS

Rigorous preprocessing for all analyses was performed to minimize effect of head motion during scan acquisition (dystonia n = 58, control n = 47 analyzed). We assessed regional functional connectivity by computing a seed-correlation map between putamen, pallidum, and sensorimotor cortex and all brain voxels. We assessed significant group differences on a cluster-wise basis. In a separate analysis, we applied 300 seed regions across the cortex, cerebellum, basal ganglia, and thalamus to comprehensively sample the whole brain. We obtained participant whole-brain correlation matrices by computing the correlation between seed average time courses for each seed pair. Weighted object-oriented data analysis assessed group-level whole-brain differences.

RESULTS

Participants with focal dystonia had decreased functional connectivity at the regional level, within the striatum and between lateral primary sensorimotor cortex and ventral intraparietal area, whereas whole-brain correlation matrices did not differ between focal dystonia and control groups. Rigorous quality control measures eliminated spurious large-scale functional connectivity differences between groups.

CONCLUSION

Regional functional connectivity differences, not global network level dysfunction, contributes to common pathophysiologic mechanisms in isolated focal dystonia. Rigorous quality control eliminated spurious large-scale network differences between patients with focal dystonia and control participants.

Network Localization of Executive Function Deficits in Patients with Focal Thalamic Lesions

The human thalamus has been suggested to be involved in executive function, based on animal studies and correlational evidence from functional neuroimaging in humans. Human lesion studies, examining behavioral deficits associated with focal brain injuries, can directly test the necessity of the human thalamus for executive function. The goal of our study was to determine the specific lesion location within the thalamus as well as the potential disruption of specific thalamocortical functional networks, related to executive dysfunction. We assessed executive function in 15 patients with focal thalamic lesions and 34 comparison patients with lesions that spared the thalamus. We found that patients with mediodorsal thalamic lesions exhibited more severe impairment in executive function when compared to both patients with thalamic lesions that spared the mediodorsal nucleus and to comparison patients with lesions outside the thalamus. Furthermore, we employed a lesion network mapping approach to map cortical regions that show strong functional connectivity with the lesioned thalamic subregions in the normative functional connectome. We found that thalamic lesion sites associated with more severe deficits in executive function showed stronger functional connectivity with ACC, dorsomedial PFC, and frontoparietal network, compared to thalamic lesions not associated with executive dysfunction. These are brain regions and functional networks whose dysfunction could contribute to impaired executive functioning. In aggregate, our findings provide new evidence that delineates a thalamocortical network for executive function.

Neuroimaging Advances in Deep Brain Stimulation: Review of Indications, Anatomy, and Brain Connectomics

Deep brain stimulation is an established therapy for multiple brain disorders, with rapidly expanding potential indications. Neuroimaging has advanced the field of deep brain stimulation through improvements in delineation of anatomy, and, more recently, application of brain connectomics. Older lesion-derived, localizationist theories of these conditions have evolved to newer, network-based "circuitopathies," aided by the ability to directly assess these brain circuits in vivo through the use of advanced neuroimaging techniques, such as diffusion tractography and fMRI. In this review, we use a combination of ultra-high-field MR imaging and diffusion tractography to highlight relevant anatomy for the currently approved indications for deep brain stimulation in the United States: essential tremor, Parkinson disease, drug-resistant epilepsy, dystonia, and obsessive-compulsive disorder. We also review the literature regarding the use of fMRI and diffusion tractography in understanding the role of deep brain stimulation in these disorders, as well as their potential use in both surgical targeting and device programming.

Hierarchical dynamics as a macroscopic organizing principle of the human brain

Multimodal evidence suggests that brain regions accumulate information over timescales that vary according to anatomical hierarchy. Thus, these experimentally defined "temporal receptive windows" are longest in cortical regions that are distant from sensory input. Interestingly, spontaneous activity in these regions also plays out over relatively slow timescales (i.e., exhibits slower temporal autocorrelation decay). These findings raise the possibility that hierarchical timescales represent an intrinsic organizing principle of brain function. Here, using resting-state functional MRI, we show that the timescale of ongoing dynamics follows hierarchical spatial gradients throughout human cerebral cortex. These intrinsic timescale gradients give rise to systematic frequency differences among large-scale cortical networks and predict individual-specific features of functional connectivity. Whole-brain coverage permitted us to further investigate the large-scale organization of subcortical dynamics. We show that cortical timescale gradients are topographically mirrored in striatum, thalamus, and cerebellum. Finally, timescales in the hippocampus followed a posterior-to-anterior gradient, corresponding to the longitudinal axis of increasing representational scale. Thus, hierarchical dynamics emerge as a global organizing principle of mammalian brains.

Plasticity and Spontaneous Activity Pulses in Disused Human Brain Circuits

To induce brain plasticity in humans, we casted the dominant upper extremity for 2 weeks and tracked changes in functional connectivity using daily 30-min scans of resting-state functional MRI (rs-fMRI). Casting caused cortical and cerebellar regions controlling the disused extremity to functionally disconnect from the rest of the somatomotor system, while internal connectivity within the disused sub-circuit was maintained. Functional disconnection was evident within 48 h, progressed throughout the cast period, and reversed after cast removal. During the cast period, large, spontaneous pulses of activity propagated through the disused somatomotor sub-circuit. The adult brain seems to rely on regular use to maintain its functional architecture. Disuse-driven spontaneous activity pulses may help preserve functionally disconnected sub-circuits.

Default-mode network streams for coupling to language and control systems

The human brain is organized into large-scale networks identifiable using resting-state functional connectivity (RSFC). These functional networks correspond with broad cognitive domains; for example, the Default-mode network (DMN) is engaged during internally oriented cognition. However, functional networks may contain hierarchical substructures corresponding with more specific cognitive functions. Here, we used individual-specific precision RSFC to test whether network substructures could be identified in 10 healthy human brains. Across all subjects and networks, individualized network subdivisions were more valid-more internally homogeneous and better matching spatial patterns of task activation-than canonical networks. These measures of validity were maximized at a hierarchical scale that contained ∼83 subnetworks across the brain. At this scale, nine DMN subnetworks exhibited topographical similarity across subjects, suggesting that this approach identifies homologous neurobiological circuits across individuals. Some DMN subnetworks matched known features of brain organization corresponding with cognitive functions. Other subnetworks represented separate streams by which DMN couples with other canonical large-scale networks, including language and control networks. Together, this work provides a detailed organizational framework for studying the DMN in individual humans.

Functional Organization for Response Inhibition in the Right Inferior Frontal Cortex of Individual Human Brains

The right inferior frontal cortex (IFC) is critical to response inhibition. The right IFC referred in the human studies of response inhibition is located in the posterior part of the inferior frontal gyrus and the surrounding regions and consists of multiple areas that implement distinct functions. Recent studies using resting-state functional connectivity have parcellated the cerebral cortex and revealed across-subject variability of parcel-based cerebrocortical networks. However, how the right IFC of individual brains is functionally organized and what functional properties the IFC parcels possess regarding response inhibition remain elusive. In the present functional magnetic resonance imaging study, precision functional mapping of individual human brains was adopted to the parcels in the right IFC to evaluate their functional properties related to response inhibition. The right IFC consisted of six modules or subsets of subregions, and the spatial organization of the modules varied considerably across subjects. Each module revealed unique characteristics of brain activity and its correlation to behavior related to response inhibition. These results provide updated functional features of the IFC and demonstrate the importance of individual-focused approaches in studying response inhibition in the right IFC.

A Critical, Event-Related Appraisal of Denoising in Resting-State fMRI Studies

This article advances two parallel lines of argument about resting-state functional magnetic resonance imaging (fMRI) signals, one empirical and one conceptual. The empirical line creates a four-part organization of the text: (1) head motion and respiration commonly cause distinct, major, unwanted influences (artifacts) in fMRI signals; (2) head motion and respiratory changes are, confoundingly, both related to psychological and clinical and biological variables of interest; (3) many fMRI denoising strategies fail to identify and remove one or the other kind of artifact; and (4) unremoved artifact, due to correlations of artifacts with variables of interest, renders studies susceptible to identifying variance of noninterest as variance of interest. Arising from these empirical observations is a conceptual argument: that an event-related approach to task-free scans, targeting common behaviors during scanning, enables fundamental distinctions among the kinds of signals present in the data, information which is vital to understanding the effects of denoising procedures. This event-related perspective permits statements like "Event X is associated with signals A, B, and C, each with particular spatial, temporal, and signal decay properties". Denoising approaches can then be tailored, via performance in known events, to permit or suppress certain kinds of signals based on their desirability.

Personality neuroscience and psychopathology: should we start with biology and look for neural-level factors?

"Personality is an abstraction used to explain consistency and coherency in an individual's pattern of affects, cognitions, desires and behaviors [ABCDs]" (Revelle, 2007, p. 37). But personality research currently provides more a taxonomy of patterns than theories of fundamental causes. Psychiatric disorders can be viewed as involving extremes of personality but are diagnosed via symptom patterns not biological causes. Such surface-level taxonomic description is necessary for science, but consistent predictive explanation requires causal theory. Personality constructs, and especially their clinical extremes, should predict variation in ABCD patterns, with parsimony requiring the lowest effective causal level of explanation. But, even biologically inspired personality theories currently use an intuitive language-based approach for scale development that lacks biological anchors. I argue that teleonomic "purpose" explains the organisation and outputs of conserved brain emotion systems, where high activation is adaptive in specific situations but is otherwise maladaptive. Simple modulators of whole-system sensitivity evolved because the requisite adaptive level can vary across people and time. Sensitivity to a modulator is an abstract predictive personality factor that operates at the neural level but provides a causal explanation of both coherence and occasional apparent incoherence in ABCD variation. Neuromodulators impact all levels of the "personality hierarchy" from metatraits to aspects: stability appears altered by serotonergic drugs, neuroticism by ketamine and trait anxiety by simple anxiolytic drugs. Here, the tools of psychiatry transfer to personality research and imply both interaction between levels and oblique factor mappings to ABCD. On this view, much psychopathology reflects extremes of neural-level personality factors, and we can view much pharmacotherapy as temporarily altering personality. So, particularly for personality factors linked to basic emotions and their disorders, I think we should start with evolutionary biology and look directly at conserved neural-level modulators for our explanatory personality constructs and only invoke higher order, emergent, explanations when neural-level explanation fails.

Precision Functional Mapping of Corticostriatal and Corticothalamic Circuits: Parallel Processing Reconsidered

In this issue of Neuron, Greene et al. (2020) identify zones of network specificity and multi-network integration in the basal ganglia and thalamus of individual human subjects. Such information could aid in the development of personalized and more effective brain stimulation therapies for neuropsychiatric disorders.

A set of functionally-defined brain regions with improved representation of the subcortex and cerebellum

An important aspect of network-based analysis is robust node definition. This issue is critical for functional brain network analyses, as poor node choice can lead to spurious findings and misleading inferences about functional brain organization. Two sets of functional brain nodes from our group are well represented in the literature: (1) 264 volumetric regions of interest (ROIs) reported in Power et al., 2011, and (2) 333 cortical surface parcels reported in Gordon et al., 2016. However, subcortical and cerebellar structures are either incompletely captured or missing from these ROI sets. Therefore, properties of functional network organization involving the subcortex and cerebellum may be underappreciated thus far. Here, we apply a winner-take-all partitioning method to resting-state fMRI data to generate novel functionally-constrained ROIs in the thalamus, basal ganglia, amygdala, hippocampus, and cerebellum. We validate these ROIs in three datasets using several criteria, including agreement with existing literature and anatomical atlases. Further, we demonstrate that combining these ROIs with established cortical ROIs recapitulates and extends previously described functional network organization. This new set of ROIs is made publicly available for general use, including a full list of MNI coordinates and functional network labels.