Mapping Symptoms to Brain Networks with the Human Connectome

Network Localization of State and Trait of Auditory Verbal Hallucinations in Schizophrenia

BACKGROUND AND HYPOTHESIS

Neuroimaging studies investigating the neural substrates of auditory verbal hallucinations (AVH) in schizophrenia have yielded mixed results, which may be reconciled by network localization. We sought to examine whether AVH-state and AVH-trait brain alterations in schizophrenia localize to common or distinct networks.

STUDY DESIGN

We initially identified AVH-state and AVH-trait brain alterations in schizophrenia reported in 48 previous studies. By integrating these affected brain locations with large-scale discovery and validation resting-state functional magnetic resonance imaging datasets, we then leveraged novel functional connectivity network mapping to construct AVH-state and AVH-trait dysfunctional networks.

STUDY RESULTS

The neuroanatomically heterogeneous AVH-state and AVH-trait brain alterations in schizophrenia localized to distinct and specific networks. The AVH-state dysfunctional network comprised a broadly distributed set of brain regions mainly involving the auditory, salience, basal ganglia, language, and sensorimotor networks. Contrastingly, the AVH-trait dysfunctional network manifested as a pattern of circumscribed brain regions principally implicating the caudate and inferior frontal gyrus. Additionally, the AVH-state dysfunctional network aligned with the neuromodulation targets for effective treatment of AVH, indicating possible clinical relevance.

CONCLUSIONS

Apart from unifying the seemingly irreproducible neuroimaging results across prior AVH studies, our findings suggest different neural mechanisms underlying AVH state and trait in schizophrenia from a network perspective and more broadly may inform future neuromodulation treatment for AVH.

Embracing variability in the search for biological mechanisms of psychiatric illness

Despite decades of research, we lack objective diagnostic or prognostic biomarkers of mental health problems. A key reason for this limited progress is a reliance on the traditional case-control paradigm, which assumes that each disorder has a single cause that can be uncovered by comparing average phenotypic values of patient and control samples. Here, we discuss the problematic assumptions on which this paradigm is based and highlight recent efforts that seek to characterize, rather than minimize, the inherent clinical and biological variability that underpins psychiatric populations. Embracing such variability is necessary to understand pathophysiological mechanisms and develop more targeted and effective treatments.

Repetitive Transcranial Magnetic Stimulation for Auditory Verbal Hallucinations in Schizophrenia: A Randomized Clinical Trial

Importance

Auditory verbal hallucinations (AVH) are a common symptom of schizophrenia, increasing the patient's risks of suicide and violence. Repetitive transcranial magnetic stimulation (rTMS) is a potential treatment for AVH.

Objective

To investigate the effect of imaging-navigated rTMS on AVH in patients with schizophrenia.

Design, Setting, and Participants

This 6-week, double-blind, sham-controlled, randomized clinical trial was performed at the Anhui Mental Health Center, Hefei, China, from September 1, 2016, to August 31, 2021. Participants included 66 patients with AVH and schizophrenia. Data were analyzed from May 1, 2022, to March 31, 2023.

Interventions

Participants were randomly assigned 1:1 to either imaging-navigated active or sham rTMS over the left temporoparietal junction for 2 weeks.

Main Outcomes and Measures

The primary outcome measured improvements in AVH from baseline to week 2 and week 6 using the Auditory Hallucination Rating Scale (AHRS) scores. In addition, the TMS-induced electric field strength was used to estimate improvements in AVH as a secondary outcome.

Results

A total of 62 participants (33 women [53%]; mean [SD] age, 27.4 [9.2] years) completed the 2-week treatments. Of these, 32 were randomized to the active rTMS group (18 women [56%]; mean [SD] age, 26.9 [9.2] years) and 30 to the sham treatment group (15 women [50%]; mean [SD] age, 27.8 [9.4] years). In the intention-to-treat analyses, patients receiving active rTMS showed a significantly greater reduction in AHRS scores compared with those receiving sham treatment at week 2 (difference, 5.96 [95% CI, 3.42-8.50]; t = 4.61; P < .001; Cohen d, 1.17 [95% CI, 0.62-1.71]). These clinical effects were sustained at week 6. Additionally, a stronger TMS-induced electric field within a predefined AVH brain network was associated with greater reductions in AHRS scores (B = 3.12; t = 3.58; P = .002). No serious adverse event was observed.

Conclusions and Relevance

The findings of this randomized clinical trial suggest that imaging-navigated rTMS may effectively and safely alleviate AVH in patients with schizophrenia. Findings also suggest that the electric field strength in the individualized AVH network is a vital parameter for optimizing the efficacy of the rTMS protocol.

Trial Registration

ClinicalTrials.gov Identifier: NCT02863094.

Breakthroughs and challenges for generating brain network-based biomarkers of treatment response in depression

Treatment outcomes widely vary for individuals diagnosed with major depressive disorder, implicating a need for deeper understanding of the biological mechanisms conferring a greater likelihood of response to a particular treatment. Our improved understanding of intrinsic brain networks underlying depression psychopathology via magnetic resonance imaging and other neuroimaging modalities has helped reveal novel and potentially clinically meaningful biological markers of response. And while we have made considerable progress in identifying such biomarkers over the last decade, particularly with larger, multisite trials, there are significant methodological and practical obstacles that need to be overcome to translate these markers into the clinic. The aim of this review is to review current literature on brain network structural and functional biomarkers of treatment response or selection in depression, with a specific focus on recent large, multisite trials reporting predictive accuracy of candidate biomarkers. Regarding pharmaco- and psychotherapy, we discuss candidate biomarkers, reporting that while we have identified candidate biomarkers of response to a single intervention, we need more trials that distinguish biomarkers between first-line treatments. Further, we discuss the ways prognostic neuroimaging may help to improve treatment outcomes to neuromodulation-based therapies, such as transcranial magnetic stimulation and deep brain stimulation. Lastly, we highlight obstacles and technical developments that may help to address the knowledge gaps in this area of research. Ultimately, integrating neuroimaging-derived biomarkers into clinical practice holds promise for enhancing treatment outcomes and advancing precision psychiatry strategies for depression management. By elucidating the neural predictors of treatment response and selection, we can move towards more individualized and effective depression interventions, ultimately improving patient outcomes and quality of life.

A potential target for noninvasive neuromodulation of PTSD symptoms derived from focal brain lesions in veterans

Neuromodulation trials for the treatment of posttraumatic stress disorder (PTSD) have yielded mixed results, and the optimal neuroanatomical target remains unclear. Here we analyzed three datasets to study brain circuitry causally linked to PTSD in military veterans. In veterans with penetrating traumatic brain injury, lesion locations that reduced probability of PTSD were preferentially connected to a circuit including the medial prefrontal cortex, amygdala and anterolateral temporal lobe. In veterans without lesions, PTSD was specifically associated with increased connectivity within this circuit. Reduced functional connectivity within this circuit after transcranial magnetic stimulation correlated with symptom reduction, even though the circuit was not directly targeted. This lesion-based 'PTSD circuit' may serve as a target for clinical trials of neuromodulation in veterans with PTSD.

Tau-network mapping of domain-specific cognitive impairment in Alzheimer's disease

Fibrillar tau gradually progresses in the brain during the course of Alzheimer's disease (AD). However, the contribution of tau accumulation in a given brain region to decline in different cognitive domains and thus phenotypic heterogeneity in AD remains unclear. Here, we leveraged the functional connectome to link the locality of tau accumulation to domain-specific cognitive impairment. In the current study, we mapped regional tau-PET accumulation onto the normative functional connectome. Subsequently, we cross-validated in two samples of AD-patients the associations between the tau-connectivity profiles and cognitive domains (episodic memory, executive function, or language). Lastly, we tested the effect of local tau-PET accumulation on the domain-specific tau-lesion networks and cognition. We identified cognitive-domain-specific tau-lesion networks, where closer topological proximity of tau-PET locations to a network was predictive of worse impairment in that domain. Higher tau-PET was associated with decreased domain-specific network connectivity, and the decrease in connectivity was associated with lower domain-specific cognition. The tau locations' connectivity profile explained domain-specific cognitive impairment, where disrupted connectivity may underlie the effect of tau on cognitive impairment.

Structural alterations in a rumination-related network in patients with major depressive disorder

Rumination is a common symptom in major depressive disorder (MDD). Previous work has connected individual differences in rumination to structural properties in various brain regions. Some of these, such as the dorsolateral prefrontal cortex (dlPFC), have also been highlighted as being altered in MDD, suggesting a connection between structural changes and ruminative symptoms. Although informative, such localised relations have limitations in the context of a network view of the brain. To further investigate rumination-related structural changes in depression, and to situate these within potential functional networks, we acquired T1-weighted structural MRI data from patients with MDD (n = 32) and controls (n = 69). Rumination was measured with the Rumination Response Scale. Surface-based, whole-brain analysis of cortical grey-matter identified group differences in the dlPFC that were, however, not related to rumination. Instead, rumination was correlated with grey-matter properties in the right precuneus. Using normative functional connectivity analysis on an independent sample (n = 100), we show these two regions to be interconnected. Further developing a network-based perspective, it was shown that the rumination-related precuneus region is connected with networks associated with processes such as executive function, autobiographical memory, and visual perception. Notably, these processes have been connected to rumination. These results suggest that rumination in depression may be linked to focal structural changes. The effects of these focal changes on rumination may then be connected to their influence on distributed functional networks.

Brain metabolic response to repetitive transcranial magnetic stimulation to lesion network in cervical dystonia

BACKGROUND

A previous study identified a brain network underlying cervical dystonia (CD) based on causal brain lesions. This network was shown to be abnormal in idiopathic CD and aligned with connections mediating treatment response to deep brain stimulation, suggesting generalizability across etiologies and relevance for treatment. The main nodes of this network were located in the deep cerebellar structures and somatosensory cortex (S1), the latter of which can be easily reached via non-invasive brain stimulation. To date, there are no studies testing brain stimulation to networks identified using lesion network mapping.

OBJECTIVES

To assess target engagement by stimulating the S1 and testing the brain's acute metabolic response to repetitive transcranial magnetic stimulation in CD patients and healthy controls.

METHODS

Thirteen CD patients and 14 controls received a single session of continuous theta burst (cTBS) and sham to the right S1. Changes in regional brain glucose metabolism were measured using [18F]FDG-PET.

RESULTS

cTBS increased metabolism at the stimulation site in CD (P = 0.03) but not in controls (P = 0.15; group difference P = 0.01). In subcortical regions, cTBS increased metabolism in the brainstem in CD only (PFDR = 0.04). The remote activation was positively associated with dystonia severity and efficacy of sensory trick phenomenon in CD patients.

CONCLUSIONS

Our results provide further evidence of abnormal sensory system function in CD and show that a single session of S1 cTBS is sufficient to induce measurable changes in brain glucose metabolism. These findings support target engagement, motivating therapeutic trials of cTBS to the S1 in CD.

Prediction of stroke severity: systematic evaluation of lesion representations

OBJECTIVE

To systematically evaluate which lesion-based imaging features and methods allow for the best statistical prediction of poststroke deficits across independent datasets.

METHODS

We utilized imaging and clinical data from three independent datasets of patients experiencing acute stroke (N1 = 109, N2 = 638, N3 = 794) to statistically predict acute stroke severity (NIHSS) based on lesion volume, lesion location, and structural and functional disconnection with the lesion location using normative connectomes.

RESULTS

We found that prediction models trained on small single-center datasets could perform well using within-dataset cross-validation, but results did not generalize to independent datasets (median R2 N1 = 0.2%). Performance across independent datasets improved using large single-center training data (R2 N2 = 15.8%) and improved further using multicenter training data (R2 N3 = 24.4%). These results were consistent across lesion attributes and prediction models. Including either structural or functional disconnection in the models outperformed prediction based on volume or location alone (P < 0.001, FDR-corrected).

INTERPRETATION

We conclude that (1) prediction performance in independent datasets of patients with acute stroke cannot be inferred from cross-validated results within a dataset, as performance results obtained via these two methods differed consistently, (2) prediction performance can be improved by training on large and, importantly, multicenter datasets, and (3) structural and functional disconnection allow for improved prediction of acute stroke severity.

Heterogenous brain activations across individuals localize to a common network

Task functional magnetic resonance imaging research has generally shielded away from studying individuals due to the low reproducibility. Here, we propose that heterogeneous brain activations across individuals localize to a common network. To test this hypothesis, we use working memory (WM) as our example. First, we showed that discrete-brain-based reproducibility of brain activation during WM across individuals was low. Then, we used activation network mapping (ANM) technique to identify each individual's brain network of WM and found that network-based reproducibility was rather high. Prediction analyses using machine learning algorithms indicated that individual WM networks identified via ANM can predict WM behavioral performance. This predictive ability even outperformed that of brain activations. Our study provides a new explanation on the low reproducibility of brain activations across individuals. The results suggest that ANM can be used to identify individual brain networks of cognitive processes, thus promising broad potential applications.

Mapping lesion-related human aggression to a common brain network

BACKGROUND

Aggression exacts a significant toll on human societies and is highly prevalent among neuropsychiatric patients for which neural mechanisms are unclear and treatment options are limited.

METHODS

Using recently validated lesion network mapping technique, we derived an aggression associated network by analyzing 182 patients who had suffered penetrating head injuries during their service in the Vietnam War. To test whether damage to this lesion-derived network would increase the risk of aggression related neuropsychiatric symptoms, we used the Harvard Lesion Repository (N = 928). To explore potential therapeutic relevance of this network, we used an independent Deep brain stimulation dataset of 25 patients with epilepsy, in which irritability and aggression are known potential side effects.

RESULTS

We found that lesions associated with aggression occurred in many different brain locations but were characterized by a specific brain network defined by functional connectivity to a hub region in the right prefrontal cortex (PFC). This network involves positive connectivity to the ventromedial PFC, dorsolateral PFC, frontal pole, posterior cingulate cortex, anterior cingulate cortex, temporal-parietal junction, and lateral temporal lobe and negative connectivity to the amygdala, hippocampus, insula, and visual cortex. Among all 25 neuropsychiatric symptoms included in the Harvard Lesion Repository, criminality demonstrated the most alignment with our aggression associated network. DBS site connectivity to this same network was associated with increased irritability.

CONCLUSIONS

We conclude that brain lesions associated with aggression map to a specific human brain circuit, and the functionally connected regions in this circuit provide testable targets for therapeutic neuromodulation.

Investigating Mood and Cognition in People with Multiple Sclerosis: A Prospective Study Protocol

Multiple sclerosis (MS) is an immune-mediated neurological disorder that affects one million people in the United States. Up to 50% of people with MS experience depression, yet the mechanisms of depression in MS remain under-investigated. Studies of medically healthy participants with depression have described associations between white matter variability and depressive symptoms, but frequently exclude participants with medical comorbidities and thus cannot be extrapolated to people with intracranial diseases. White matter lesions are a key pathologic feature of MS and could disrupt pathways involved in depression symptoms. The purpose of this study is to investigate the impact of brain network disruption on depression using MS as a model. We will obtain structured clinical and cognitive assessments from two hundred fifty participants with MS and prospectively evaluate white matter lesion burden as a predictor of depressive symptoms. Ethics approval was obtained from The University of Pennsylvania Institutional Review Board (Protocol #853883). The results of this study will be presented at scientific meetings and conferences and published in peer-reviewed journals.

Lesions Causing Alice in Wonderland Syndrome Map to a Common Brain Network Linking Body and Size Perception

OBJECTIVE

Alice in Wonderland syndrome (AIWS) profoundly affects human perception of size and scale, particularly regarding one's own body and the environment. Its neuroanatomical basis has remained elusive, partly because brain lesions causing AIWS can occur in different brain regions. Here, we aimed to determine if brain lesions causing AIWS map to a distributed brain network.

METHODS

A retrospective case-control study analyzing 37 cases of lesion-induced AIWS identified through systematic literature review was conducted. Using resting-state functional connectome data from 1,000 healthy individuals, the whole-brain connections of each lesion were estimated and contrasted with those from a control dataset comprising 1,073 lesions associated with 25 other neuropsychiatric syndromes. Additionally, connectivity findings from lesion-induced AIWS cases were compared with functional neuroimaging results from 5 non-lesional AIWS cases.

RESULTS

AIWS-associated lesions were located in various brain regions with minimal overlap (≤33%). However, the majority of lesions (≥85%) demonstrated shared connectivity to the right extrastriate body area, known to be selectively activated by viewing body part images, and the inferior parietal cortex, involved in size and scale judgements. This pattern was uniquely characteristic of AIWS when compared with other neuropsychiatric disorders (family-wise error-corrected p < 0.05) and consistent with functional neuroimaging observations in AIWS due to nonlesional causes (median correlation r = 0.56, interquartile range 0.24).

INTERPRETATION

AIWS-related perceptual distortions map to one common brain network, encompassing regions critical for body representation and size-scale processing. These findings lend insight into the neuroanatomical localization of higher-order perceptual functions, and may inform future therapeutic strategies for perceptual disorders. ANN NEUROL 2024;96:662-674.

Large-scale meta-analyses and network analyses of neural substrates underlying human escalated aggression

Escalated aggression represents a frequent and severe form of violence, sometimes manifesting as antisocial behavior. Driven by the pressures of modern life, escalated aggression is of particular concern due to its rising prevalence and its destructive impact on both individual well-being and socioeconomic stability. However, a consistent neural circuitry underpinning it remains to be definitively identified. Here, we addressed this issue by comparing brain alterations between individuals with escalated aggression and those without such behavioral manifestations. We first conducted a meta-analysis to synthesize previous neuroimaging studies on functional and structural alterations of escalated aggression (325 experiments, 2997 foci, 16,529 subjects). Following-up network and functional decoding analyses were conducted to provide quantitative characterizations of the identified brain regions. Our results revealed that brain regions constantly involved in escalated aggression were localized in the subcortical network (amygdala and lateral orbitofrontal cortex) associated with emotion processing, the default mode network (dorsal medial prefrontal cortex and middle temporal gyrus) associated with mentalizing, and the salience network (anterior cingulate cortex and anterior insula) associated with cognitive control. These findings were further supported by additional meta-analyses on emotion processing, mentalizing, and cognitive control, all of which showed conjunction with the brain regions identified in the escalated aggression. Together, these findings advance the understanding of the risk biomarkers of escalated aggressive populations and refine theoretical models of human aggression.

Human-derived monoclonal autoantibodies as interrogators of cellular proteotypes in the brain

A major aim of neuroscience is to identify and model the functional properties of neural cells whose dysfunction underlie neuropsychiatric illness. In this article, we propose that human-derived monoclonal autoantibodies (HD-mAbs) are well positioned to selectively target and manipulate neural subpopulations as defined by their protein expression; that is, cellular proteotypes. Recent technical advances allow for efficient cloning of autoantibodies from neuropsychiatric patients. These HD-mAbs can be introduced into animal models to gain biological and pathobiological insights about neural proteotypes of interest. Protein engineering can be used to modify, enhance, silence, or confer new functional properties to native HD-mAbs, thereby enhancing their versatility. Finally, we discuss the challenges and limitations confronting HD-mAbs as experimental research tools for neuroscience.

Advancements in surgical treatments for Huntington disease: From pallidotomy to experimental therapies

Huntington disease (HD) is an autosomal dominant neurodegenerative disorder characterized by choreic movements, behavioral changes, and cognitive impairment. The pathogenesis of this process is a consequence of mutant protein toxicity in striatal and cortical neurons. Thus far, neurosurgical management of HD has largely been limited to symptomatic relief of motor symptoms using ablative and stimulation techniques. These interventions, however, do not modify the progressive course of the disease. More recently, disease-modifying experimental therapeutic strategies have emerged targeting intrastriatal infusion of neurotrophic factors, cell transplantation, HTT gene silencing, and delivery of intrabodies. Herein we review therapies requiring neurosurgical intervention, including those targeting symptom management and more recent disease-modifying agents, with a focus on safety, efficacy, and surgical considerations.

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

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

Localization and Network Connectivity of Lesions Causing Limb Ataxia in Patients With Stroke

BACKGROUND AND OBJECTIVES

Ataxia is primarily considered to originate from the cerebellum. However, it can manifest without obvious cerebellar damage, such as in anterior circulation stroke, leaving the mechanisms of ataxia unclear. The aim of this study was to investigate whether stroke lesions causing limb ataxia localize to a common brain network.

METHODS

In this prospective cohort study, adult patients with new-onset stroke with visible lesions on CT or MRI from Turku University Hospital, Finland, were clinically examined (1) after their stroke while still admitted to the hospital (baseline) and (2) 4 months later (follow-up) to assess limb ataxia. Lesion locations and their functional connectivity, computed using openly available data from 1,000 healthy volunteers from the Brain Genome Superstruct Project, were compared voxel-by-voxel across the whole brain between patients with and without ataxia, using voxel-based lesion-symptom mapping and lesion network mapping. The findings were confirmed in an independent stroke patient cohort with identical clinical assessments.

RESULTS

One hundred ninety-seven patients (mean age 67.2 years, 39%female) were included in this study. At baseline, 35 patients (68.3 years, 34%female) had and 162 (67.0 years, 40%female) did not have new-onset acute limb ataxia. At follow-up, additional 4 patients had developed late-onset limb ataxia, totalling to 39 patients (68.6 years, 36%female) with limb ataxia at any point. One hundred eighteen patients (66.2 years, 40%female) did not have ataxia at any point (n = 40 with missing follow-up data). Lesions in 54% of the patients with acute limb ataxia were located outside the cerebellum and cerebellar peduncles, and we did not find an association between specific lesion locations and ataxia. Lesions causing acute limb ataxia, however, were connected to a common network centered on the intermediate zone cerebellum and cerebellar peduncles (lesion connectivity in patients with vs without acute limb ataxia, pFWE < 0.05). The results were similar when comparing patients with and without ataxia at any point, and when excluding lesions in the cerebellum and cerebellar peduncles (pFWE < 0.05). The findings were confirmed in the independent stroke dataset (n = 96), demonstrating an OR of 2.27 (95% CI 1.32-3.91) for limb ataxia per standard deviation increase in limb ataxia network damage score.

DISCUSSION

Lesions causing limb ataxia occur in heterogeneous locations but localize to a common brain network.

Circuit-based neuromodulation enhances delayed recall in amnestic mild cognitive impairment

BACKGROUND

This study aimed to investigate the efficacy of circuits-based paired associative stimulation (PAS) in adults with amnestic mild cognitive impairment (aMCI).

METHODS

We conducted a parallel-group, randomised, controlled clinical trial. Initially, a cohort of healthy subjects was recruited to establish the cortical-hippocampal circuits by tracking white matter fibre connections using diffusion tensor imaging. Subsequently, patients diagnosed with aMCI, matched for age and education, were randomly allocated in a 1:1 ratio to undergo a 2-week intervention, either circuit-based PAS or sham PAS. Additionally, we explored the relationship between changes in cognitive performance and the functional connectivity (FC) of cortical-hippocampal circuits.

RESULTS

FCs between hippocampus and precuneus and between hippocampus and superior frontal gyrus (orbital part) were most closely associated with the Auditory Verbal Learning Test (AVLT)_N5 score in 42 aMCI patients, thus designated as target circuits. The AVLT_N5 score improved from 2.43 (1.43) to 5.29 (1.98) in the circuit-based PAS group, compared with 2.52 (1.44) to 3.86 (2.39) in the sham PAS group (p=0.003; Cohen's d=0.97). A significant decrease was noted in FC between the left hippocampus and left precuneus in the circuit-based PAS group from baseline to postintervention (p=0.013). Using a generalised linear model, significant group×FC interaction effects for the improvements in AVLT_N5 scores were found within the circuit-based PAS group (B=3.4, p=0.017).

CONCLUSIONS

Circuit-based PAS effectively enhances long-term delayed recall in adults diagnosed with aMCI, which includes individuals aged 50-80 years. This enhancement is potentially linked to the decreased functional connectivity between the left hippocampus and left precuneus.

TRIAL REGISTRATION NUMBER

ChiCTR2100053315; Chinese Clinical Trial Registry.

A neural network for religious fundamentalism derived from patients with brain lesions

Religious fundamentalism, characterized by rigid adherence to a set of beliefs putatively revealing inerrant truths, is ubiquitous across cultures and has a global impact on society. Understanding the psychological and neurobiological processes producing religious fundamentalism may inform a variety of scientific, sociological, and cultural questions. Research indicates that brain damage can alter religious fundamentalism. However, the precise brain regions involved with these changes remain unknown. Here, we analyzed brain lesions associated with varying levels of religious fundamentalism in two large datasets from independent laboratories. Lesions associated with greater fundamentalism were connected to a specific brain network with nodes in the right orbitofrontal, dorsolateral prefrontal, and inferior parietal lobe. This fundamentalism network was strongly right hemisphere lateralized and highly reproducible across the independent datasets (r = 0.82) with cross-validations between datasets. To explore the relationship of this network to lesions previously studied by our group, we tested for similarities to twenty-one lesion-associated conditions. Lesions associated with confabulation and criminal behavior showed a similar connectivity pattern as lesions associated with greater fundamentalism. Moreover, lesions associated with poststroke pain showed a similar connectivity pattern as lesions associated with lower fundamentalism. These findings are consistent with the current understanding of hemispheric specializations for reasoning and lend insight into previously observed epidemiological associations with fundamentalism, such as cognitive rigidity and outgroup hostility.

Atrophy network mapping of clinical subtypes and main symptoms in frontotemporal dementia

Frontotemporal dementia (FTD) is a disease of high heterogeneity, apathy and disinhibition present in all subtypes of FTD and imposes a significant burden on families/society. Traditional neuroimaging analysis has limitations in elucidating the network localization due to individual clinical and neuroanatomical variability. The study aims to identify the atrophy network map associated with different FTD clinical subtypes and determine the specific localization of the network for apathy and disinhibition. Eighty FTD patients [45 behavioural variant FTD (bvFTD) and 35 semantic variant progressive primary aphasia (svPPA)] and 58 healthy controls at Xuanwu Hospital were enrolled as Dataset 1; 112 FTD patients including 50 bvFTD, 32 svPPA and 30 non-fluent variant PPA (nfvPPA) cases, and 110 healthy controls from the Frontotemporal Lobar Degeneration Neuroimaging Initiative (FTLDNI) dataset were included as Dataset 2. Initially, single-subject atrophy maps were defined by comparing cortical thickness in each FTD patient versus healthy controls. Next, the network of brain regions functionally connected to each FTD patient's location of atrophy was determined using seed-based functional connectivity in a large (n = 1000) normative connectome. Finally, we used atrophy network mapping to define clinical subtype-specific network (45 bvFTD, 35 svPPA and 58 healthy controls in Dataset 1; 50 bvFTD, 32 svPPA, 30 nfvPPA and 110 healthy controls in Dataset 2) and symptom-specific networks [combined Datasets 1 and 2, apathy without depression versus non-apathy without depression (80:26), disinhibition versus non-disinhibition (88:68)]. We compare the result with matched symptom networks derived from patients with focal brain lesions or conjunction analysis. Through the analysis of two datasets, we identified heterogeneity in atrophy patterns among FTD patients. However, these atrophy patterns are connected to a common brain network. The primary regions affected by atrophy in FTD included the frontal and temporal lobes, particularly the anterior temporal lobe. bvFTD connects to frontal and temporal cortical areas, svPPA mainly impacts the anterior temporal region and nfvPPA targets the inferior frontal gyrus and precentral cortex regions. The apathy-specific network was localized in the orbital frontal cortex and ventral striatum, while the disinhibition-specific network was localized in the bilateral orbital frontal gyrus and right temporal lobe. Apathy and disinhibition atrophy networks resemble known motivational and criminal lesion networks, respectively. A significant correlation was found between the apathy/disinhibition scores and functional connectivity between atrophy maps and the peak of the networks. This study localizes the common network of clinical subtypes and main symptoms in FTD, guiding future FTD neuromodulation interventions.

One side effect: two networks? Lateral and posteromedial stimulation spreads induce dysarthria in subthalamic deep brain stimulation for Parkinson's disease

BACKGROUND

Stimulation-induced dysarthria (SID) is a troublesome and potentially therapy-limiting side effect of deep brain stimulation of the subthalamic nucleus (STN-DBS) in patients with Parkinson's disease (PD). To date, the origin of SID, and especially whether there is an involvement of cerebellar pathways as well as the pyramidal tract, remains a matter of debate. Therefore, this study aims to shed light on structural networks associated with SID and to derive a data-driven model to predict SID in patients with PD and STN-DBS.

METHODS

Randomised, double-blinded monopolar reviews determining SID thresholds were conducted in 25 patients with PD and STN-DBS. A fibre-based mapping approach, implementing the calculation of fibr-wise ORs for SID, was employed to identify the distributional pattern of SID in the STN's vicinity. The ability of the data-driven model to classify stimulation volumes as 'causing SID' or 'not causing SID' was validated by calculating receiver operating characteristics (ROC) in an independent out-of-sample cohort comprising 14 patients with PD and STN-DBS.

RESULTS

Local fibre-based stimulation maps showed an involvement of fibres running lateral and posteromedial to the STN in the pathogenesis of SID, independent of the investigated hemisphere. ROC analysis in the independent out-of-sample cohort resulted in a good fit of the data-driven model for both hemispheres (area under the curve (AUC)left=0.88, AUCright=0.88).

CONCLUSIONS

This study reveals an involvement of both, cerebello-thalamic fibres, as well as the pyramidal tract, in the pathogenesis of SID in STN-DBS. The results may impact future postoperative programming strategies to avoid SID in patients with PD and STN-DBS TRIAL REGISTRATION NUMBER: DRKS00023221; German Clinical Trials Register (DRKS) Number.

Multimodal neuroimaging to characterize symptom-specific networks in movement disorders

Movement disorders, such as Parkinson's disease, essential tremor, and dystonia, are characterized by their predominant motor symptoms, yet diseases causing abnormal movement also encompass several other symptoms, including non-motor symptoms. Here we review recent advances from studies of brain lesions, neuroimaging, and neuromodulation that provide converging evidence on symptom-specific brain networks in movement disorders. Although movement disorders have traditionally been conceptualized as disorders of the basal ganglia, cumulative data from brain lesions causing parkinsonism, tremor and dystonia have now demonstrated that this view is incomplete. Several recent studies have shown that lesions causing a given movement disorder occur in heterogeneous brain locations, but disrupt common brain networks, which appear to be specific to each motor phenotype. In addition, findings from structural and functional neuroimaging in movement disorders have demonstrated that brain abnormalities extend far beyond the brain networks associated with the motor symptoms. In fact, neuroimaging findings in each movement disorder are strongly influenced by the constellation of patients' symptoms that also seem to map to specific networks rather than individual anatomical structures or single neurotransmitters. Finally, observations from deep brain stimulation have demonstrated that clinical changes, including both symptom improvement and side effects, are dependent on the modulation of large-scale networks instead of purely local effects of the neuromodulation. Combined, this multimodal evidence suggests that symptoms in movement disorders arise from distinct brain networks, encouraging multimodal imaging studies to better characterize the underlying symptom-specific mechanisms and individually tailor treatment approaches.

Brain Network Localization of Gray Matter Atrophy and Neurocognitive and Social Cognitive Dysfunction in Schizophrenia

BACKGROUND

Numerous studies have established the presence of gray matter atrophy and brain activation abnormalities during neurocognitive and social cognitive tasks in schizophrenia. Despite a growing consensus that diseases localize better to distributed brain networks than individual anatomical regions, relatively few studies have examined brain network localization of gray matter atrophy and neurocognitive and social cognitive dysfunction in schizophrenia.

METHODS

To address this gap, we initially identified brain locations of structural and functional abnormalities in schizophrenia from 301 published neuroimaging studies with 8712 individuals with schizophrenia and 9275 healthy control participants. By applying novel functional connectivity network mapping to large-scale resting-state functional magnetic resonance imaging datasets, we mapped these affected brain locations to 3 brain abnormality networks of schizophrenia.

RESULTS

The gray matter atrophy network of schizophrenia comprised a broadly distributed set of brain areas predominantly implicating the ventral attention, somatomotor, and default networks. The neurocognitive dysfunction network was also composed of widespread brain areas primarily involving the frontoparietal and default networks. By contrast, the social cognitive dysfunction network consisted of circumscribed brain regions mainly implicating the default, subcortical, and visual networks.

CONCLUSIONS

Our findings suggest shared and unique brain network substrates of gray matter atrophy and neurocognitive and social cognitive dysfunction in schizophrenia, which may not only refine the understanding of disease neuropathology from a network perspective but may also contribute to more targeted and effective treatments for impairments in different cognitive domains in schizophrenia.

Cerebellar Functions Beyond Movement and Learning

The cerebellum has a well-established role in controlling motor functions, including coordination, posture, and the learning of skilled movements. The mechanisms for how it carries out motor behavior remain under intense investigation. Interestingly though, in recent years the mechanisms of cerebellar function have faced additional scrutiny since nonmotor behaviors may also be controlled by the cerebellum. With such complexity arising, there is now a pressing need to better understand how cerebellar structure, function, and behavior intersect to influence behaviors that are dynamically called upon as an animal experiences its environment. Here, we discuss recent experimental work that frames possible neural mechanisms for how the cerebellum shapes disparate behaviors and why its dysfunction is catastrophic in hereditary and acquired conditions-both motor and nonmotor. For these reasons, the cerebellum might be the ideal therapeutic target.

Predictors of cognition after glioma surgery: connectotomy, structure-function phenotype, plasticity

Determining preoperatively the maximal extent of resection that would preserve cognitive functions is the core challenge of brain tumour surgery. Over the past decade, the methodological framework to achieve this goal has been thoroughly renewed: the population-level topographically-focused voxel-based lesion-symptom mapping has been progressively overshadowed by machine learning (ML) algorithmics, in which the problem is framed as predicting cognitive outcomes in a patient-specific manner from a typically large set of variables. However, the choice of these predictors is of utmost importance, as they should be both informative and parsimonious. In this perspective, we first introduce the concept of connectotomy: instead of parameterizing resection topography through the status (intact/resected) of a huge number of voxels (or parcels) paving the whole brain in the Cartesian 3D-space, the connectotomy models the resection in the connectivity space, by computing a handful number of networks disconnection indices, measuring how the structural connectivity sustaining each network of interest was hit by the resection. This connectivity-informed reduction of dimensionality is a necessary step for efficiently implementing ML tools, given the relatively small number of patient-examples in available training datasets. We further argue that two other major sources of interindividual variability must be considered to improve the accuracy with which outcomes are predicted: the underlying structure-function phenotype and neuroplasticity, for which we provide an in-depth review and propose new ways of determining relevant predictors. We finally discuss the benefits of our approach for precision surgery of glioma.

Linking Invasive and Noninvasive Brain Stimulation in Parkinson's Disease: A Randomized Trial

BACKGROUND

Recent imaging studies identified a brain network associated with clinical improvement following deep brain stimulation (DBS) in Parkinson's disease (PD), the PD response network.

OBJECTIVES

This study aimed to assess the impact of neuromodulation on PD motor symptoms by targeting this network noninvasively using multifocal transcranial direct current stimulation (tDCS).

METHODS

In a prospective, randomized, double-blinded, crossover trial, 21 PD patients (mean age 59.7 years, mean Hoehn & Yahr [H&Y] 2.4) received multifocal tDCS targeting the a-priori network. Twenty-minute sessions of tDCS and sham were administered on 2 days in randomized order. Movement Disorder Society-Unified Parkinson's Disease Rating Scale-Part III (MDS-UPDRS-III) scores were assessed.

RESULTS

Before intervention, MDS-UPDRS-III scores were comparable in both conditions (stimulation days: 37.38 (standard deviation [SD] = 12.50, confidence interval [CI] = 32.04, 42.73) vs. sham days: 36.95 (SD = 13.94, CI = 30.99, 42.91), P = 0.63). Active stimulation resulted in a reduction by 3.6 points (9.7%) to 33.76 (SD = 11.19, CI = 28.98, 38.55) points, whereas no relevant change was observed after sham stimulation (36.43 [SD = 14.15, CI = 30.38, 42.48], average improvement: 0.5 [1.4%]). Repeated-measures analysis of variance (ANOVA) confirmed significance (main effect of time: F(1,20)=4.35, P < 0.05). Tukey's post hoc tests indicated MDS-UPDRS-III improvement after active stimulation (t [20] = 2.9, P = 0.03) but not after sham (t [20] = 0.42, P > 0.05). In a subset of patients that underwent DBS surgery later, their DBS response correlated with tDCS effects (R = 0.55, P(1) = 0.04).

CONCLUSION

Noninvasive, multifocal tDCS targeting a DBS-derived network significantly improved PD motor symptoms. Despite a small effect size, this study provides proof of principle for the successful noninvasive neuromodulation of an invasively identified network. Future studies should investigate repeated tDCS sessions and their utility for screening before DBS surgery. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Connectome reorganization associated with temporal lobe pathology and its surgical resection

Network neuroscience offers a unique framework to understand the organizational principles of the human brain. Despite recent progress, our understanding of how the brain is modulated by focal lesions remains incomplete. Resection of the temporal lobe is the most effective treatment to control seizures in pharmaco-resistant temporal lobe epilepsy (TLE), making this syndrome a powerful model to study lesional effects on network organization in young and middle-aged adults. Here, we assessed the downstream consequences of a focal lesion and its surgical resection on the brain's structural connectome, and explored how this reorganization relates to clinical variables at the individual patient level. We included adults with pharmaco-resistant TLE (n = 37) who underwent anterior temporal lobectomy between two imaging time points, as well as age- and sex-matched healthy controls who underwent comparable imaging (n = 31). Core to our analysis was the projection of high-dimensional structural connectome data-derived from diffusion MRI tractography from each subject-into lower-dimensional gradients. We then compared connectome gradients in patients relative to controls before surgery, tracked surgically-induced connectome reconfiguration from pre- to postoperative time points, and examined associations to patient-specific clinical and imaging phenotypes. Before surgery, individuals with TLE presented with marked connectome changes in bilateral temporo-parietal regions, reflecting an increased segregation of the ipsilateral anterior temporal lobe from the rest of the brain. Surgery-induced connectome reorganization was localized to this temporo-parietal subnetwork, but primarily involved postoperative integration of contralateral regions with the rest of the brain. Using a partial least-squares analysis, we uncovered a latent clinical imaging signature underlying this pre- to postoperative connectome reorganization, showing that patients who displayed postoperative integration in bilateral fronto-occipital cortices also had greater preoperative ipsilateral hippocampal atrophy, lower seizure frequency and secondarily generalized seizures. Our results bridge the effects of focal brain lesions and their surgical resections with large-scale network reorganization and interindividual clinical variability, thus offering new avenues to examine the fundamental malleability of the human brain.

Common neural dysfunction of economic decision-making across psychiatric conditions

Adaptive decision-making, which is often impaired in various psychiatric conditions, is essential for well-being. Recent evidence has indicated that decision-making capacity in multiple tasks could be accounted for by latent dimensions, enlightening the question of whether there is a common disruption of brain networks in economic decision-making across psychiatric conditions. Here, we addressed the issue by combining activation/lesion network mapping analyses with a transdiagnostic brain imaging meta-analysis. Our findings indicate that there were transdiagnostic alterations in the thalamus and ventral striatum during the decision or outcome stage of decision-making. The identified regions represent key nodes in a large-scale network, which is composed of multiple heterogeneous brain regions and plays a causal role in motivational functioning. The findings suggest that disturbances in the network associated with emotion- and reward-related processing play a key role in dysfunctions of decision-making observed in various psychiatric conditions. This study provides the first meta-analytic evidence of common neural alterations linked to deficits in economic decision-making.

Fatigue in Parkinson's Disease Is Due to Decreased Efficiency of the Frontal Network: Quantitative EEG Analysis

OBJECTIVE

Fatigue is a common, debilitating nonmotor symptom of Parkinson's disease (PD), but its mechanism is poorly understood. We aimed to determine whether electroencephalography (EEG) could objectively measure fatigue and to explore the pathophysiology of fatigue in PD.

METHODS

We studied 32 de novo PD patients who underwent EEG. We compared brain activity between 19 PD patients without fatigue and 13 PD patients with fatigue via EEG power spectra and graphs, including the global efficiency, characteristic path length, clustering coefficient, small-worldness, local efficiency, degree centrality, closeness centrality, and betweenness centrality.

RESULTS

No significant differences in absolute or relative power were detected between PD patients without or with fatigue (all p > 0.02, Bonferroni-corrected). According to our network analysis, brain network efficiency differed by frequency band. Generally, the brain network in the frontal area for theta and delta bands showed greater efficiency, and in the temporal area, the alpha1 band was less efficient in PD patients without fatigue (p < 0.0001, p = 0.0011, and p = 0.0007, respectively, Bonferroni-corrected).

CONCLUSION

Our study suggests that PD patients with fatigue have less efficient networks in the frontal area than PD patients without fatigue. These findings may explain why fatigue is common in PD, a frontostriatal disorder. Increased efficiency in the temporal area in PD patients with fatigue is assumed to be compensatory. Brain network analysis using graph theory is more valuable than power spectrum analysis in revealing the brain mechanism related to fatigue.

Divergent suicidal symptomatic activations converge on somato-cognitive action network in depression

Individuals with depression have the highest lifetime prevalence of suicide attempts (SA) among mental illnesses. Numerous neuroimaging studies have developed biomarkers from task-related neural activation in depressive patients with SA, but the findings are inconsistent. Empowered by the contemporary interconnected view of depression as a neural system disorder, we sought to identify a specific brain circuit utilizing published heterogeneous neural activations. We systematically reviewed all published cognitive and emotional task-related functional MRI studies that investigated differences in the location of neural activations between depressive patients with and without SA. We subsequently mapped an underlying brain circuit functionally connecting to each experimental activation using a large normative connectome database (n = 1000). The identified SA-related functional network was compared to the network derived from the disease control group. Finally, we decoded this convergent functional connectivity network using microscale transcriptomic and chemo-architectures, and macroscale psychological processes. We enrolled 11 experimental tasks from eight studies, including depressive patients with SA (n = 147) and without SA (n = 196). The heterogeneous SA-related neural activations localized to the somato-cognitive action network (SCAN), exhibiting robustness to little perturbations and specificity for depression. Furthermore, the SA-related functional network was colocalized with brain-wide gene expression involved in inflammatory and immunity-related biological processes and aligned with the distribution of the GABA and noradrenaline neurotransmitter systems. The findings demonstrate that the SA-related functional network of depression is predominantly located at the SCAN, which is an essential implication for understanding depressive patients with SA.

Transcranial Direct Current Stimulation to Ameliorate Post-Stroke Cognitive Impairment

Post-stroke cognitive impairment is a common and disabling condition with few effective therapeutic options. After stroke, neural reorganization and other neuroplastic processes occur in response to ischemic injury, which can result in clinical improvement through spontaneous recovery. Neuromodulation through transcranial direct current stimulation (tDCS) is a promising intervention to augment underlying neuroplasticity in order to improve cognitive function. This form of neuromodulation leverages mechanisms of neuroplasticity post-stroke to optimize neural reorganization and improve function. In this review, we summarize the current state of cognitive neurorehabilitation post-stroke, the practical features of tDCS, its uses in stroke-related cognitive impairment across cognitive domains, and special considerations for the use of tDCS in the post-stroke patient population.

Mapping the Relationship of White Matter Lesions to Depression in Multiple Sclerosis

BACKGROUND

Multiple sclerosis (MS) is an immune-mediated neurological disorder, and up to 50% of patients experience depression. We investigated how white matter network disruption is related to depression in MS.

METHODS

Using electronic health records, 380 participants with MS were identified. Depressed individuals (MS+Depression group; n = 232) included persons who had an ICD-10 depression diagnosis, had a prescription for antidepressant medication, or screened positive via Patient Health Questionnaire (PHQ)-2 or PHQ-9. Age- and sex-matched nondepressed individuals with MS (MS-Depression group; n = 148) included persons who had no prior depression diagnosis, had no psychiatric medication prescriptions, and were asymptomatic on PHQ-2 or PHQ-9. Research-quality 3T structural magnetic resonance imaging was obtained as part of routine care. We first evaluated whether lesions were preferentially located within the depression network compared with other brain regions. Next, we examined if MS+Depression patients had greater lesion burden and if this was driven by lesions in the depression network. Primary outcome measures were the burden of lesions (e.g., impacted fascicles) within a network and across the brain.

RESULTS

MS lesions preferentially affected fascicles within versus outside the depression network (β = 0.09, 95% CI = 0.08 to 0.10, p < .001). MS+Depression patients had more lesion burden (β = 0.06, 95% CI = 0.01 to 0.10, p = .015); this was driven by lesions within the depression network (β = 0.02, 95% CI = 0.003 to 0.040, p = .020).

CONCLUSIONS

We demonstrated that lesion location and burden may contribute to depression comorbidity in MS. MS lesions disproportionately impacted fascicles in the depression network. MS+Depression patients had more disease than MS-Depression patients, which was driven by disease within the depression network. Future studies relating lesion location to personalized depression interventions are warranted.

Indirect functional connectivity does not predict overall survival in glioblastoma

BACKGROUND

Lesion network mapping (LNM) is a popular framework to assess clinical syndromes following brain injury. The classical approach involves embedding lesions from patients into a normative functional connectome and using the corresponding functional maps as proxies for disconnections. However, previous studies indicated limited predictive power of this approach in behavioral deficits. We hypothesized similarly low predictiveness for overall survival (OS) in glioblastoma (GBM).

METHODS

A retrospective dataset of patients with GBM was included (n = 99). Lesion masks were registered in the normative space to compute disconnectivity maps. The brain functional normative connectome consisted in data from 173 healthy subjects obtained from the Human Connectome Project. A modified version of the LNM was then applied to core regions of GBM masks. Linear regression, classification, and principal component (PCA) analyses were conducted to explore the relationship between disconnectivity and OS. OS was considered both as continuous and categorical (low, intermediate, and high survival) variable.

RESULTS

The results revealed no significant associations between OS and network disconnection strength when analyzed at both voxel-wise and classification levels. Moreover, patients stratified into different OS groups did not exhibit significant differences in network connectivity patterns. The spatial similarity among the first PCA of network maps for each OS group suggested a lack of distinctive network patterns associated with survival duration.

CONCLUSIONS

Compared with indirect structural measures, functional indirect mapping does not provide significant predictive power for OS in patients with GBM. These findings are consistent with previous research that demonstrated the limitations of indirect functional measures in predicting clinical outcomes, underscoring the need for more comprehensive methodologies and a deeper understanding of the factors influencing clinical outcomes in this challenging disease.

Brain Structural and Functional Damage Network Localization of Suicide

BACKGROUND

Extensive neuroimaging research on brain structural and functional correlates of suicide has produced inconsistent results. Despite increasing recognition that damage in multiple different brain locations that causes the same symptom can map to a common brain network, there is still a paucity of research investigating network localization of suicide.

METHODS

To clarify this issue, we initially identified brain structural and functional damage locations in relation to suicide from 63 published studies with 2135 suicidal and 2606 nonsuicidal individuals. By applying novel functional connectivity network mapping to large-scale discovery and validation resting-state functional magnetic resonance imaging datasets, we mapped these affected brain locations to 3 suicide brain damage networks corresponding to different imaging modalities.

RESULTS

The suicide gray matter volume damage network comprised widely distributed brain areas primarily involving the dorsal default mode, basal ganglia, and anterior salience networks. The suicide task-induced activation damage network was similar to but less extensive than the gray matter volume damage network, predominantly implicating the same canonical networks. The suicide resting-state activity damage network manifested as a localized set of brain regions encompassing the orbitofrontal cortex and middle cingulate cortex.

CONCLUSIONS

Our findings not only may help reconcile prior heterogeneous neuroimaging results, but also may provide insights into the neurobiological mechanisms of suicide from a network perspective, which may ultimately inform more targeted and effective strategies to prevent suicide.

Fronto-thalamic networks and the left ventral thalamic nuclei play a key role in aphasia after thalamic stroke

Thalamic aphasia results from focal thalamic lesions that cause dysfunction of remote but functionally connected cortical areas due to language network perturbation. However, specific local and network-level neural substrates of thalamic aphasia remain incompletely understood. Using lesion symptom mapping, we demonstrate that lesions in the left ventrolateral and ventral anterior thalamic nucleus are most strongly associated with aphasia in general and with impaired semantic and phonemic fluency and complex comprehension in particular. Lesion network mapping (using a normative connectome based on fMRI data from 1000 healthy individuals) reveals a Thalamic aphasia network encompassing widespread left-hemispheric cerebral connections, with Broca's area showing the strongest associations, followed by the superior and middle frontal gyri, precentral and paracingulate gyri, and globus pallidus. Our results imply the critical involvement of the left ventrolateral and left ventral anterior thalamic nuclei in engaging left frontal cortical areas, especially Broca's area, during language processing.

Brain lesions causing parkinsonism versus seizures map to opposite brain networks

Recent epidemiological studies propose an association between parkinsonism and seizures, but the direction of this association is unclear. Focal brain lesions causing new-onset parkinsonism versus seizures may provide a unique perspective on the causal relationship between the two symptoms and involved brain networks. We studied lesions causing parkinsonism versus lesions causing seizures and used the human connectome to identify their connected brain networks. Brain networks for parkinsonism and seizures were compared using spatial correlations on a group and individual lesion level. Lesions not associated with either symptom were used as controls. Lesion locations from 29 patients with parkinsonism were connected to a brain network with the opposite spatial topography (spatial r = -0.85) compared to 347 patients with lesions causing seizures. A similar inverse relationship was found when comparing the connections that were most specific on a group level (spatial r = -0.51) and on an individual lesion level (average spatial r = -0.042; P < 0.001). The substantia nigra was found to be most positively correlated to the parkinsonism network but most negatively correlated to the seizure network (spatial r > 0.8). Brain lesions causing parkinsonism versus seizures map to opposite brain networks, providing neuroanatomical insight into conflicting epidemiological evidence.

Localization of stuttering based on causal brain lesions

Stuttering affects approximately 1 in 100 adults and can result in significant communication problems and social anxiety. It most often occurs as a developmental disorder but can also be caused by focal brain damage. These latter cases may lend unique insight into the brain regions causing stuttering. Here, we investigated the neuroanatomical substrate of stuttering using three independent datasets: (i) case reports from the published literature of acquired neurogenic stuttering following stroke (n = 20, 14 males/six females, 16-77 years); (ii) a clinical single study cohort with acquired neurogenic stuttering following stroke (n = 20, 13 males/seven females, 45-87 years); and (iii) adults with persistent developmental stuttering (n = 20, 14 males/six females, 18-43 years). We used the first two datasets and lesion network mapping to test whether lesions causing acquired stuttering map to a common brain network. We then used the third dataset to test whether this lesion-based network was relevant to developmental stuttering. In our literature dataset, we found that lesions causing stuttering occurred in multiple heterogeneous brain regions, but these lesion locations were all functionally connected to a common network centred around the left putamen, including the claustrum, amygdalostriatal transition area and other adjacent areas. This finding was shown to be specific for stuttering (PFWE < 0.05) and reproducible in our independent clinical cohort of patients with stroke-induced stuttering (PFWE < 0.05), resulting in a common acquired stuttering network across both stroke datasets. Within the common acquired stuttering network, we found a significant association between grey matter volume and stuttering impact for adults with persistent developmental stuttering in the left posteroventral putamen, extending into the adjacent claustrum and amygdalostriatal transition area (PFWE < 0.05). We conclude that lesions causing acquired neurogenic stuttering map to a common brain network, centred to the left putamen, claustrum and amygdalostriatal transition area. The association of this lesion-based network with symptom severity in developmental stuttering suggests a shared neuroanatomy across aetiologies.

Application of individual brain connectome in chronic ischemia: mapping symptoms before and after reperfusion

How brain functions in the distorted ischemic state before and after reperfusion is unclear. It is also uncertain whether there are any indicators within ischemic brain that could predict surgical outcomes. To alleviate these issues, we applied individual brain connectome in chronic steno-occlusive vasculopathy (CSOV) to map both ischemic symptoms and their postbypass changes. A total of 499 bypasses in 455 CSOV patients were collected and followed up for 47.8 ± 20.5 months. Using multimodal parcellation with connectivity-based and pathological distortion-independent approach, areal MR features of brain connectome were generated with three measurements of functional connectivity (FC), structural connectivity, and PageRank centrality at the single-subject level. Thirty-three machine-learning models were then trained with clinical and areal MR features to obtain acceptable classifiers for both ischemic symptoms and their postbypass changes, among which, 11 were deemed acceptable (AUC > 0.7). Notably, the FC feature-based model for long-term neurological outcomes performed very well (AUC > 0.8). Finally, a Shapley additive explanations plot was adopted to extract important individual features in acceptable models to generate "fingerprints" of brain connectome. This study not only establishes brain connectomic fingerprint databases for brain ischemia with distortion, but also provides informative insights for how brain functions before and after reperfusion.

Predictors of post stroke cognitive impairment: VITATOPS cognition substudy

INTRODUCTION

Post stroke cognitive impairment (PSCI) is a common complication of ischemic stroke. PSCI can involve different depending on clinical and stroke related characteristics. The aim of this study is to determine the factors associated with impairments in specific cognitive domains.

METHODS

The Vitamins to Prevent Stroke (VITATOPS) trial is a large, multinational randomised controlled trial. In this substudy, consecutive patients admitted for ischaemic stroke or transient ischaemic attack (TIA) at a tertiary hospital in Singapore were included. PSCI was defined as impairment of any of the six cognitive subgroups - visuoconstruction, attention, verbal memory, language, visual memory and visuomotor function - that were assessed annually for up to five years. Univariate and multivariate Cox proportional hazard models were used to determine factors associated with impairments in each of these cognitive domains.

RESULTS

A total of 736 patients were included in this study, of which 173 (23.5 %) developed cognitive impairment. Out of the six cognitive domains, the greatest proportion of patients had an impairment in visuoconstruction (26.4 %) followed by attention (19.8 %), verbal memory (18.3 %), language (17.5 %), visual memory (17.3 %) and visuomotor function (14.8 %). Patients with posterior circulation cerebral infarction (POCI) as the index stroke subtype had higher rates of cognitive impairment. Further subgroup analyses show that Indian race and advanced age were predictive of language impairment, whilst fewer years of education and POCI were predictive of verbal memory impairment. POCI was predictive of visual memory impairment, and advanced age and POCI were predictive of visuomotor function impairment.

CONCLUSION

We identified visuoconstruction and attention domains to be the most affected in our Asian cohort of PSCI. Advanced age, lower levels of education, posterior circulation strokes and concomitant comorbidities such as peripheral artery disease are independent predictors of PSCI.

Cholinergic modulation supports dynamic switching of resting state networks through selective DMN suppression

Brain activity during the resting state is widely used to examine brain organization, cognition and alterations in disease states. While it is known that neuromodulation and the state of alertness impact resting-state activity, neural mechanisms behind such modulation of resting-state activity are unknown. In this work, we used a computational model to demonstrate that change in excitability and recurrent connections, due to cholinergic modulation, impacts resting-state activity. The results of such modulation in the model match closely with experimental work on direct cholinergic modulation of Default Mode Network (DMN) in rodents. We further extended our study to the human connectome derived from diffusion-weighted MRI. In human resting-state simulations, an increase in cholinergic input resulted in a brain-wide reduction of functional connectivity. Furthermore, selective cholinergic modulation of DMN closely captured experimentally observed transitions between the baseline resting state and states with suppressed DMN fluctuations associated with attention to external tasks. Our study thus provides insight into potential neural mechanisms for the effects of cholinergic neuromodulation on resting-state activity and its dynamics.

Same, Same but Different? A Multi-Method Review of the Processes Underlying Executive Control

Attention, working memory, and executive control are commonly considered distinct cognitive functions with important reciprocal interactions. Yet, longstanding evidence from lesion studies has demonstrated both overlap and dissociation in their behavioural expression and anatomical underpinnings, suggesting that a lower dimensional framework could be employed to further identify processes supporting goal-directed behaviour. Here, we describe the anatomical and functional correspondence between attention, working memory, and executive control by providing an overview of cognitive models, as well as recent data from lesion studies, invasive and non-invasive multimodal neuroimaging and brain stimulation. We emphasize the benefits of considering converging evidence from multiple methodologies centred on the identification of brain mechanisms supporting goal-driven behaviour. We propose that expanding on this approach should enable the construction of a comprehensive anatomo-functional framework with testable new hypotheses, and aid clinical neuroscience to intervene on impairments of executive functions.

Postoperative cerebellar mutism syndrome is an acquired autism-like network disturbance

BACKGROUND

Cerebellar mutism syndrome (CMS) is a common and debilitating complication of posterior fossa tumor surgery in children. Affected children exhibit communication and social impairments that overlap phenomenologically with subsets of deficits exhibited by children with Autism spectrum disorder (ASD). Although both CMS and ASD are thought to involve disrupted cerebro-cerebellar circuitry, they are considered independent conditions due to an incomplete understanding of their shared neural substrates.

METHODS

In this study, we analyzed postoperative cerebellar lesions from 90 children undergoing posterior fossa resection of medulloblastoma, 30 of whom developed CMS. Lesion locations were mapped to a standard atlas, and the networks functionally connected to each lesion were computed in normative adult and pediatric datasets. Generalizability to ASD was assessed using an independent cohort of children with ASD and matched controls (n = 427).

RESULTS

Lesions in children who developed CMS involved the vermis and inferomedial cerebellar lobules. They engaged large-scale cerebellothalamocortical circuits with a preponderance for the prefrontal and parietal cortices in the pediatric and adult connectomes, respectively. Moreover, with increasing connectomic age, CMS-associated lesions demonstrated stronger connectivity to the midbrain/red nuclei, thalami and inferior parietal lobules and weaker connectivity to the prefrontal cortex. Importantly, the CMS-associated lesion network was independently reproduced in ASD and correlated with communication and social deficits, but not repetitive behaviors.

CONCLUSIONS

Our findings indicate that CMS-associated lesions may result in an ASD-like network disturbance that occurs during sensitive windows of brain development. A common network disturbance between CMS and ASD may inform improved treatment strategies for affected children.

Brain lesions causing parkinsonism versus seizures map to opposite brain networks

Recent epidemiological studies propose an association between parkinsonism and seizures, but the direction of this association is unclear. Focal brain lesions causing new-onset parkinsonism versus seizures may provide a unique perspective on the causal relationship between the two symptoms and involved brain networks. We studied lesions causing parkinsonism versus lesions causing seizures and utilized human connectome data to identify their connected brain networks. Brain networks for parkinsonism and seizures were compared using spatial correlations on a group and individual lesion level. Lesions not associated with either symptom were used as controls. Lesion locations from 29 patients with parkinsonism were connected to a brain network with the opposite spatial topography (spatial r =-0.85) compared to 347 patients with lesions causing seizures. A similar inverse relationship was found when comparing the connections that were most specific for lesions causing parkinsonism versus seizures on a group level (spatial r =- 0.51) and on an individual lesion level (average spatial r =-0.042; p<0.001). The substantia nigra was found to be most positively correlated to the parkinsonism network but most negatively correlated to the seizure network (spatial r >0.8). Brain lesions causing parkinsonism versus seizures map to opposite brain networks, providing neuroanatomical insight into conflicting epidemiological evidence.

Hayling and stroop tests tap dissociable deficits and network-level neural correlates

Although many executive function screens have been developed, it is not yet clear whether these assessments are equally effective in detecting post-stroke deficits of initiation and inhibition. This study presents a comparative analysis of the Stroop and Hayling tests aiming to evaluate whether these tests measure the same underlying cognitive functions and to identify the neural correlates of the deficits detected by both tasks. Sixty six stroke survivors and 70 healthy ageing controls completed the Hayling and Stroop tests. Stroke patients were found to exhibit qualitative performance differences across analogous Stroop and Hayling Test metrics intended to tap initiation and inhibition. The Stroop test was found to have high specificity to abnormal performance, but low sensitivity relative to the Hayling Test. Minimal overlap was present between the network-level correlates of analogous Stroop and Hayling Test metrics. Hayling Task strategy use metrics were significantly associated with distinct patterns of disconnection in stroke survivors, providing novel insight into the neural correlates of fine-grained behavioural patterns. Overall, these findings strongly suggest that the functions tapped by the Stroop and Hayling Test are both behaviourally and anatomically dissociable. The Hayling Test was found to offer improved sensitivity and detail relative to the Stroop test. This novel demonstration of the Hayling Test within the stroke population suggests that this task represents an effective measure for quantifying post-stroke initiation and inhibition deficits.

Studying the social mind: An updated summary of findings from the Vietnam Head Injury Study

Lesion mapping studies allow us to evaluate the potential causal contribution of specific brain areas to human cognition and complement other cognitive neuroscience methods, as several authors have recently pointed out. Here, we present an updated summary of the findings from the Vietnam Head Injury Study (VHIS) focusing on the studies conducted over the last decade, that examined the social mind and its intricate neural and cognitive underpinnings. The VHIS is a prospective, long-term follow-up study of Vietnam veterans with penetrating traumatic brain injury (pTBI) and healthy controls (HC). The scope of the work is to present the studies from the latest phases (3 and 4) of the VHIS, 70 studies since 2011, when the Raymont et al. paper was published (Raymont et al., 2011). These studies have contributed to our understanding of human social cognition, including political and religious beliefs, theory of mind, but also executive functions, intelligence, and personality. This work finally discusses the usefulness of lesion mapping as an approach to understanding the functions of the human brain from basic science and clinical perspectives.

Verbal memory network mapping in individual patients predicts postoperative functional impairments

Verbal memory decline is a significant concern following temporal lobe surgeries in patients with epilepsy, emphasizing the need for precision presurgical verbal memory mapping to optimize functional outcomes. However, the inter-individual variability in functional networks and brain function-structural dissociations pose challenges when relying solely on group-level atlases or anatomical landmarks for surgical guidance. Here, we aimed to develop and validate a personalized functional mapping technique for verbal memory using precision resting-state functional MRI (rs-fMRI) and neurosurgery. A total of 38 patients with refractory epilepsy scheduled for surgical interventions were enrolled and 28 patients were analyzed in the study. Baseline 30-min rs-fMRI scanning, verbal memory and language assessments were collected for each patient before surgery. Personalized verbal memory networks (PVMN) were delineated based on preoperative rs-fMRI data for each patient. The accuracy of PVMN was assessed by comparing post-operative functional impairments and the overlapping extent between PVMN and surgical lesions. A total of 14 out of 28 patients experienced clinically meaningful declines in verbal memory after surgery. The personalized network and the group-level atlas exhibited 100% and 75.0% accuracy in predicting postoperative verbal memory declines, respectively. Moreover, six patients with extra-temporal lesions that overlapped with PVMN showed selective impairments in verbal memory. Furthermore, the lesioned ratio of the personalized network rather than the group-level atlas was significantly correlated with postoperative declines in verbal memory (personalized networks: r = -0.39, p = .038; group-level atlas: r = -0.19, p = .332). In conclusion, our personalized functional mapping technique, using precision rs-fMRI, offers valuable insights into individual variability in the verbal memory network and holds promise in precision verbal memory network mapping in individuals.

Increased Cortical Thickness in Alzheimer's Disease

OBJECTIVE

Patients with Alzheimer's disease (AD) have diffuse brain atrophy, but some regions, such as the anterior cingulate cortex (ACC), are spared and may even show increase in size compared to controls. The extent, clinical significance, and mechanisms associated with increased cortical thickness in AD remain unknown. Recent work suggested neural facilitation of regions anticorrelated to atrophied regions in frontotemporal dementia. Here, we aim to determine whether increased thickness occurs in sporadic AD, whether it relates to clinical symptoms, and whether it occur in brain regions functionally connected to-but anticorrelated with-locations of atrophy.

METHODS

Cross-sectional clinical, neuropsychological, and neuroimaging data from the Alzheimer's Disease Neuroimaging Initiative were analyzed to investigate cortical thickness in AD subjects versus controls. Atrophy network mapping was used to identify brain regions functionally connected to locations of increased thickness and atrophy.

RESULTS

AD patients showed increased thickness in the ACC in a region-of-interest analysis and the visual cortex in an exploratory analysis. Increased thickness in the left ACC was associated with preserved cognitive function, while increased thickness in the left visual cortex was associated with hallucinations. Finally, we found that locations of increased thickness were functionally connected to, but anticorrelated with, locations of brain atrophy (r = -0.81, p < 0.05).

INTERPRETATION

Our results suggest that increased cortical thickness in Alzheimer's disease is relevant to AD symptoms and preferentially occur in brain regions functionally connected to, but anticorrelated with, areas of brain atrophy. Implications for models of compensatory neuroplasticity in response to neurodegeneration are discussed. ANN NEUROL 2024;95:929-940.