Lesion network mapping for symptom localization: recent developments and future directions

Multiple voxel pattern analysis shows associations between chronic fatigue syndrome and cortical atrophy

Chronic Fatigue Syndrome (CFS) is a disease characterized by unexplained fatigue and impaired cognition for more than 6 months. Recent studies have reported declines in large-scale brain networks' functional connections among patients with CFS, and these declines correlated with the patients' symptom severity. However, these reported networks are inconsistent. Brain structure serves as the essential architecture supporting brain functional fluctuations. Investigating structural alterations could provide insights into functional changes in different brain areas and facilitate the clinical diagnosis of CFS. In this study, we recruited 37 patients with CFS and 34 healthy controls to collect their clinical assessments and structural magnetic resonance imaging data. Multiple Voxel Pattern Analysis (MVPA) was employed to recognize chronic fatigue-related brain areas, and cortical thickness was compared between the two groups. By constructing a predictive MVPA classifier with 70% balanced accuracy, we identified five relevant brain areas, including the paracentral cortex, precentral cortex, central cortex, intraparietal cortex, and superior temporal cortex. Subsequently, the results showed that the thickness of these areas had associations with fatigue severity, healthy life status, and pain levels among our subjects. Furthermore, compared to healthy controls, the thickness reduction was observed in patients with CFS. In summary, our study revealed a pathological chronic fatigue pattern for understanding CFS and suggested associations between cortical atrophy and CFS, with the aim of highlighting potential impacts of chronic fatigue. The trial was registered in the Chinese Clinical Trial Registry (ChiCTR2000032577).

Mapping Neuroimaging Findings of Creativity and Brain Disease Onto a Common Brain Circuit

Importance

Creativity is important for problem solving, adaptation to a changing environment, and innovation. Neuroimaging studies seeking to map creativity have yielded conflicting results, and studies of patients with brain disease have reported both decreases and paradoxical increases in creativity, leaving the neural basis of creativity unclear.

Objective

To investigate the brain circuit underlying creativity and assess its association with brain injury and neurodegenerative disease.

Design, Setting, and Participants

This study examined neuroimaging coordinates from a meta-analysis of 36 studies published between 2004 and 2019 associated with increased activity during creative tasks in healthy participants. A validated method termed coordinate network mapping and a database of resting-state functional connectivity from 1000 healthy individuals were used to test whether these coordinates mapped to a common brain circuit. Specificity was assessed through comparison to random coordinates and coordinates from working memory tasks in healthy participants. Reproducibility was assessed using an independent dataset of coordinates from additional studies of creativity in healthy participants. Finally, alignment with effects of focal brain damage on creativity was tested using data from patients with brain lesions and coordinates of brain atrophy from 7 different neurodegenerative disorders.

Main Outcomes and Measures

The primary outcomes were creativity or no creativity and alignment with a creativity circuit or no alignment.

Results

Creativity tasks activated heterogenous locations, with coordinates scattered across many different brain regions (415 coordinates derived from 857 healthy participants; pooled mean [SD] age, 24.1 [6.91] years; 461 [54%] female). However, these activation coordinates were part of a common brain circuit, defined by negative connectivity to the right frontal pole. This result was consistent across creative domains, reproducible in an independent dataset (383 coordinates derived from 691 participants) and specific to creativity when compared with random gray matter coordinates (n = 415) or coordinates activated by working memory tasks (3072 coordinates derived from 2900 healthy participants). Damage to this creativity circuit by lesions (n = 56 patients) or neurodegenerative disease (2262 coordinates derived from 4804 patients) aligned with both decreases and increases in creativity observed in these disorders.

Conclusions and Relevance

Findings from this study suggest that brain regions activated by creativity tasks map to a brain circuit defined by negative functional connectivity to the right frontal pole. Damage to this circuit aligned with changes in creativity observed in individuals with certain brain diseases, including paradoxical creativity increases.

Iowa Brain-Behavior Modeling Toolkit: An Open-Source MATLAB Tool for Inferential and Predictive Modeling of Imaging-Behavior and Lesion-Deficit Relationships

The traditional analytical framework taken by neuroimaging studies in general, and lesion-behavior studies in particular, has been inferential in nature and has focused on identifying and interpreting statistically significant effects within the sample under study. While this framework is well-suited for hypothesis testing approaches, achieving the modern goal of precision medicine requires a different framework that is predictive in nature and that focuses on maximizing the predictive power of models and evaluating their ability to generalize beyond the data that were used to train them. However, few tools exist to support the development and evaluation of predictive models in the context of neuroimaging or lesion-behavior research, creating an obstacle to the widespread adoption of predictive modeling approaches in the field. Further, existing tools for lesion-behavior analysis are often unable to accommodate categorical outcome variables and often impose restrictions on the predictor data. Researchers therefore often must use different software packages and analytical approaches depending on (a) whether they are addressing a classification versus regression problem and (b) whether their predictor data correspond to binary lesion images, continuous lesion-network images, connectivity matrices, or other data modalities. To address these limitations, we have developed a MATLAB software toolkit that supports both inferential and predictive modeling frameworks, accommodates both classification and regression problems, and does not impose restrictions on the modality of the predictor data. The toolkit features both a graphical user interface and scripting interface, includes implementations of multiple mass-univariate, multivariate, and machine learning models, features built-in and customizable routines for hyper-parameter optimization, cross-validation, model stacking, and significance testing, and automatically generates text-based descriptions of key methodological details and modeling results to improve reproducibility and minimize errors in the reporting of methods and results. Here, we provide an overview and discussion of the toolkit's features and demonstrate its functionality by applying it to the question of how expressive and receptive language impairments relate to lesion location, structural disconnection, and functional network disruption in a large sample of patients with left hemispheric brain lesions. We find that impairments in expressive versus receptive language are most strongly associated with left lateral prefrontal and left posterior temporal/parietal damage, respectively. We also find that impairments in expressive vs. receptive language are associated with partially overlapping patterns of fronto-temporal structural disconnection and with similar functional networks. Importantly, we find that lesion location and lesion-derived network measures are highly predictive of both types of impairment, with predictions from models trained on these measures explaining ~30%-40% of the variance on average when applied to data from patients not used to train the models. We have made the toolkit publicly available, and we have included a comprehensive set of tutorial notebooks to support new users in applying the toolkit in their studies.

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.

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.

Iowa Brain-Behavior Modeling Toolkit: An Open-Source MATLAB Tool for Inferential and Predictive Modeling of Imaging-Behavior and Lesion-Deficit Relationships

The traditional analytical framework taken by neuroimaging studies in general, and lesion-behavior studies in particular, has been inferential in nature and has focused on identifying and interpreting statistically significant effects within the sample under study. While this framework is well-suited for hypothesis testing approaches, achieving the modern goal of precision medicine requires a different framework that is predictive in nature and that focuses on maximizing the predictive power of models and evaluating their ability to generalize beyond the data that were used to train them. However, few tools exist to support the development and evaluation of predictive models in the context of neuroimaging or lesion-behavior research, creating an obstacle to the widespread adoption of predictive modeling approaches in the field. Further, existing tools for lesion-behavior analysis are often unable to accommodate categorical outcome variables and often impose restrictions on the predictor data. Researchers therefore often must use different software packages and analytical approaches depending on whether they are addressing a classification vs. regression problem and on whether their predictor data correspond to binary lesion images, continuous lesion-network images, connectivity matrices, or other data modalities. To address these limitations, we have developed a MATLAB software toolkit that supports both inferential and predictive modeling frameworks, accommodates both classification and regression problems, and does not impose restrictions on the modality of the predictor data. The toolkit features both a graphical user interface and scripting interface, includes implementations of multiple mass-univariate, multivariate, and machine learning models, features built-in and customizable routines for hyper-parameter optimization, cross-validation, model stacking, and significance testing, and automatically generates text-based descriptions of key methodological details and modeling results to improve reproducibility and minimize errors in the reporting of methods and results. Here, we provide an overview and discussion of the toolkit features and demonstrate its functionality by applying it to the question of how expressive and receptive language impairments relate to lesion location, structural disconnection, and functional network disruption in a large sample of patients with left hemispheric brain lesions. We find that impairments in expressive vs. receptive language are most strongly associated with left lateral prefrontal and left posterior temporal/parietal damage, respectively. We also find that impairments in expressive vs. receptive language are associated with partially overlapping patterns of fronto-temporal structural disconnection, and that the associated functional networks are also similar. Importantly, we find that lesion location and lesion-derived network measures are highly predictive of both types of impairment, with predictions from models trained on these measures explaining ~30-40% of the variance on average when applied to data from patients not used to train the models. We have made the toolkit publicly available, and we have included a comprehensive set of tutorial notebooks to support new users in applying the toolkit in their studies.

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.

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.

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.

Sensing, feeling and regulating: investigating the association of focal brain damage with voluntary respiratory and motor control

Breathing is a complex, vital function that can be modulated to influence physical and mental well-being. However, the role of cortical and subcortical brain regions in voluntary control of human respiration is underexplored. Here we investigated the influence of damage to human frontal, temporal or limbic regions on the sensation and regulation of breathing patterns. Participants performed a respiratory regulation task across regular and irregular frequencies ranging from 6 to 60 breaths per minute (bpm), with a counterbalanced hand motor control task. Interoceptive and affective states induced by each condition were assessed via questionnaire, and autonomic signals were indexed via skin conductance. Participants with focal lesions to the bilateral frontal lobe, right insula/basal ganglia and left medial temporal lobe showed reduced performance relative to individually matched healthy comparisons during the breathing and motor tasks. They also reported significantly higher anxiety during the 60 bpm regular and irregular breathing trials, with anxiety correlating with difficulty in rapid breathing specifically within this group. This study demonstrates that damage to frontal, temporal or limbic regions is associated with abnormal voluntary respiratory and motor regulation and tachypnoea-related anxiety, highlighting the role of the forebrain in affective and motor responses during breathing. This article is part of the theme issue 'Sensing and feeling: an integrative approach to sensory processing and emotional experience'.

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.

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.

Proposal for a Mechanistic Disease Conceptualization in Clinical Neurosciences: The Neural Network Components (NNC) Model

ABSTRACT

Clinical neurosciences, and psychiatry specifically, have been challenged by the lack of a comprehensive and practical framework that explains the core mechanistic processes of variable psychiatric presentations. Current conceptualization and classification of psychiatric presentations are primarily centered on a non-biologically based clinical descriptive approach. Despite various attempts, advances in neuroscience research have not led to an improved conceptualization or mechanistic classification of psychiatric disorders. This perspective article proposes a new-work-in-progress-framework for conceptualizing psychiatric presentations based on neural network components (NNC). This framework could guide the development of mechanistic disease classification, improve understanding of underpinning pathology, and provide specific intervention targets. This model also has the potential to dissolve artificial barriers between the fields of psychiatry and neurology.

Normative modelling of molecular-based functional circuits captures clinical heterogeneity transdiagnostically in psychiatric patients

Advanced methods such as REACT have allowed the integration of fMRI with the brain's receptor landscape, providing novel insights transcending the multiscale organisation of the brain. Similarly, normative modelling has allowed translational neuroscience to move beyond group-average differences and characterise deviations from health at an individual level. Here, we bring these methods together for the first time. We used REACT to create functional networks enriched with the main modulatory, inhibitory, and excitatory neurotransmitter systems and generated normative models of these networks to capture functional connectivity deviations in patients with schizophrenia, bipolar disorder (BPD), and ADHD. Substantial overlap was seen in symptomatology and deviations from normality across groups, but these could be mapped into a common space linking constellations of symptoms through to underlying neurobiology transdiagnostically. This work provides impetus for developing novel biomarkers that characterise molecular- and systems-level dysfunction at the individual level, facilitating the transition towards mechanistically targeted treatments.

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.

Focal Brain Lesions Causing Acquired Amusia Map to a Common Brain Network

Music is a universal human attribute. The study of amusia, a neurologic music processing deficit, has increasingly elaborated our view on the neural organization of the musical brain. However, lesions causing amusia occur in multiple brain locations and often also cause aphasia, leaving the distinct neural networks for amusia unclear. Here, we utilized lesion network mapping to identify these networks. A systematic literature search was carried out to identify all published case reports of lesion-induced amusia. The reproducibility and specificity of the identified amusia network were then tested in an independent prospective cohort of 97 stroke patients (46 female and 51 male) with repeated structural brain imaging, specifically assessed for both music perception and language abilities. Lesion locations in the case reports were heterogeneous but connected to common brain regions, including bilateral temporoparietal and insular cortices, precentral gyrus, and cingulum. In the prospective cohort, lesions causing amusia mapped to a common brain network, centering on the right superior temporal cortex and clearly distinct from the network causally associated with aphasia. Lesion-induced longitudinal structural effects in the amusia circuit were confirmed as reduction of both gray and white matter volume, which correlated with the severity of amusia. We demonstrate that despite the heterogeneity of lesion locations disrupting music processing, there is a common brain network that is distinct from the language network. These results provide evidence for the distinct neural substrate of music processing, differentiating music-related functions from language, providing a testable target for noninvasive brain stimulation to treat amusia.

Causal network localization of brain stimulation targets for trait anxiety

Transcranial magnetic stimulation (TMS) and deep brain stimulation (DBS) can treat some neuropsychiatric disorders, but there is no consensus approach for identifying new targets. We localized causal circuit-based targets for anxiety that converged across multiple natural experiments. Lesions (n=451) and TMS sites (n=111) that modify anxiety mapped to a common normative brain circuit (r=0.68, p=0.01). In an independent dataset (n=300), individualized TMS site connectivity to this circuit predicted anxiety change (p=0.02). Subthalamic DBS sites overlapping the circuit caused more anxiety (n=74, p=0.006), thus demonstrating a network-level effect, as the circuit was derived without any subthalamic sites. The circuit was specific to trait versus state anxiety in datasets that measured both (p=0.003). Broadly, this illustrates a pathway for discovering novel circuit-based targets across neuropsychiatric disorders.

Lesion voxels to lesion networks: The enduring value of the Vietnam Head Injury Study

The Vietnam Head Injury Study has been curated by Dr Jordan Grafman since the 1980s in an effort to study patients with penetrating traumatic brain injuries suffered during the Vietnam War. Unlike many datasets of ischemic stroke lesions, the VHIS collected extraordinarily deep phenotyping and was able to sample lesion locations that are not constrained to typical vascular territories. For decades, this dataset has helped researchers draw causal links between neuroanatomical regions and neuropsychiatric symptoms. The value of the VHIS has only increased over time as techniques for analyzing the dataset have developed and evolved. Tools such as voxel lesion symptom mapping allowed one to relate symptoms to individual brain voxels. With the advent of the human connectome, tools such as lesion network mapping allow one to relate symptoms to connected brain networks by combining lesion datasets with new atlases of human brain connectivity. In a series of recent studies, lesion network mapping has been combined with the Vietnam Head Injury dataset to identify brain networks associated with spirituality, religiosity, consciousness, memory, emotion regulation, addiction, depression, and even transdiagnostic mental illness. These findings are enhancing our ability to make diagnoses, identify potential treatment targets for focal brain stimulation, and understand the human brain generally. Our techniques for studying brain lesions will continue to improve, as will our tools for modulating brain circuits. As these advances occur, the value of well characterized lesion datasets such as the Vietnam Head Injury Study will continue to grow. This study aims to review the history of the Vietnam Head Injury Study and contextualize its role in modern-day localization of neurological symptoms.

Neuroimaging of neuropsychological disturbances following ischaemic stroke (CONNECT): a prospective cohort study protocol

INTRODUCTION

Neuropsychiatric distubance is a common clinical manifestation in acute ischemic stroke. However, it is frequently overlooked by clinicians. This study aimed to explore the possible aetiology and pathogenesis of neuropsychiatric disturbances following ischaemic stroke (NDIS) from an anatomical and functional perspective with the help of neuroimaging methods.

METHOD AND ANALYSIS

CONNECT is a prospective cohort study of neuroimaging and its functional outcome in NDIS. We aim to enrol a minimum of 300 individuals with first-ever stroke. The neuropsychological disturbances involved in this study include depression, anxiety disorder, headache, apathy, insomnia, fatigue and cognitive impairment. Using scales that have been shown to be effective in assessing the above symptoms, the NDIS evaluation battery requires at least 2 hours at baseline. Moreover, all patients will be required to complete 2 years of follow-up, during which the NDIS will be re-evaluated at 3 months, 12 months and 24 months by telephone and 6 months by outpatient interview after the index stroke. The primary outcome of our study is the incidence of NDIS at the 6-month mark. Secondary outcomes are related to the severity of NDIS as well as functional rehabilitation of patients. Functional imaging evaluation will be performed at baseline and 6-month follow-up using specific sequences including resting-state functional MRI, diffusion tensor imaging, T1-weighted imaging, T2-weighted imaging, diffusion-weighted imaging, arterial spin labelling, quantitative susceptibility mapping and fluid-attenuated inversion recovery imaging. In addition, we collect haematological information from patients to explore potential biological and genetic markers of NDIS through histological analysis.

ETHICS AND DISSEMINATION

The CONNECT Study was approved by the Ethics Review Committee of the First Hospital of the University of Science and Technology of China (2021-ky012) and written informed consent will be obtained from all participants. Results will be disseminated via a peer-reviewed journal.

TRIAL REGISTRATION NUMBER

ChiCTR2100043886.

The future of brain circuit-targeted therapeutics

The principle of targeting brain circuits has drawn increasing attention with the growth of brain stimulation treatments such as transcranial magnetic stimulation (TMS), deep brain stimulation (DBS), and focused ultrasound (FUS). Each of these techniques can effectively treat different neuropsychiatric disorders, but treating any given disorder depends on choosing the right treatment target. Here, we propose a three-phase framework for identifying and modulating these targets. There are multiple approaches to identifying a target, including correlative neuroimaging, retrospective optimization based on existing stimulation sites, and lesion localization. These techniques can then be optimized using personalized neuroimaging, physiological monitoring, and engagement of a specific brain state using pharmacological or psychological interventions. Finally, a specific stimulation modality or combination of modalities can be chosen after considering the advantages and tradeoffs of each. While there is preliminary literature to support different components of this framework, there are still many unanswered questions. This presents an opportunity for the future growth of research and clinical care in brain circuit therapeutics.

Stroke-Related Visceral Alterations: A Voxel-Based Neuroanatomic Localization Study

OBJECTIVE

Functional and morphologic changes in extracranial organs can occur after acute brain injury. The neuroanatomic correlates of such changes are not fully known. Herein, we tested the hypothesis that brain infarcts are associated with cardiac and systemic abnormalities (CSAs) in a regionally specific manner.

METHODS

We generated voxelwise p value maps of brain infarcts for poststroke plasma cardiac troponin T (cTnT) elevation, QTc prolongation, in-hospital infection, and acute stress hyperglycemia (ASH) in 1,208 acute ischemic stroke patients prospectively recruited into the Heart-Brain Interactions Study. We examined the relationship between infarct location and CSAs using a permutation-based approach and identified clusters of contiguous voxels associated with p < 0.05.

RESULTS

cTnT elevation not attributable to a known cardiac reason was detected in 5.5%, QTc prolongation in the absence of a known provoker in 21.2%, ASH in 33.9%, and poststroke infection in 13.6%. We identified significant, spatially segregated voxel clusters for each CSA. The clusters for troponin elevation and QTc prolongation mapped to the right hemisphere. There were 3 clusters for ASH, the largest of which was in the left hemisphere. We found 2 clusters for poststroke infection, one associated with pneumonia in the left and one with urinary tract infection in the right hemisphere. The relationship between infarct location and CSAs persisted after adjusting for infarct volume.

INTERPRETATION

Our results show that there are discrete regions of brain infarcts associated with CSAs. This information could be used to bootstrap toward new markers for better differentiation between neurogenic and non-neurogenic mechanisms of poststroke CSAs. ANN NEUROL 2023;94:1155-1163.

Multiple sclerosis lesions that impair memory map to a connected memory circuit

BACKGROUND

Nearly 1 million Americans are living with multiple sclerosis (MS) and 30-50% will experience memory dysfunction. It remains unclear whether this memory dysfunction is due to overall white matter lesion burden or damage to specific neuroanatomical structures. Here we test if MS memory dysfunction is associated with white matter lesions to a specific brain circuit.

METHODS

We performed a cross-sectional analysis of standard structural images and verbal memory scores as assessed by immediate recall trials from 431 patients with MS (mean age 49.2 years, 71.9% female) enrolled at a large, academic referral center. White matter lesion locations from each patient were mapped using a validated algorithm. First, we tested for associations between memory dysfunction and total MS lesion volume. Second, we tested for associations between memory dysfunction and lesion intersection with an a priori memory circuit derived from stroke lesions. Third, we performed mediation analyses to determine which variable was most associated with memory dysfunction. Finally, we performed a data-driven analysis to derive de-novo brain circuits for MS memory dysfunction using both functional (n = 1000) and structural (n = 178) connectomes.

RESULTS

Both total lesion volume (r = 0.31, p < 0.001) and lesion damage to our a priori memory circuit (r = 0.34, p < 0.001) were associated with memory dysfunction. However, lesion damage to the memory circuit fully mediated the association of lesion volume with memory performance. Our data-driven analysis identified multiple connections associated with memory dysfunction, including peaks in the hippocampus (T = 6.05, family-wise error p = 0.000008), parahippocampus, fornix and cingulate. Finally, the overall topography of our data-driven MS memory circuit matched our a priori stroke-derived memory circuit.

CONCLUSIONS

Lesion locations associated with memory dysfunction in MS map onto a specific brain circuit centered on the hippocampus. Lesion damage to this circuit fully mediated associations between lesion volume and memory. A circuit-based approach to mapping MS symptoms based on lesions visible on standard structural imaging may prove useful for localization and prognosis of higher order deficits in MS.

Mapping Essential Tremor to a Common Brain Network Using Functional Connectivity Analysis

BACKGROUND AND OBJECTIVES

The cerebello-thalamo-cortical circuit plays a critical role in essential tremor (ET). However, abnormalities have been reported in multiple brain regions outside this circuit, leading to inconsistent characterization of ET pathophysiology. Here, we test whether these mixed findings in ET localize to a common functional network and whether this network has therapeutic relevance.

METHODS

We conducted a systematic literature search to identify studies reporting structural or metabolic brain abnormalities in ET. We then used 'coordinate network mapping,' which leverages a normative connectome (n = 1,000) of resting-state fMRI data to identify regions commonly connected to findings across all studies. To assess whether these regions may be relevant for the treatment of ET, we compared our network with a therapeutic network derived from lesions that relieved ET. Finally, we investigated whether the functional connectivity of this ET symptom network is abnormal in an independent cohort of patients with ET as compared with healthy controls.

RESULTS

Structural and metabolic brain abnormalities in ET were located in heterogeneous regions throughout the brain. However, these coordinates were connected to a common functional brain network, including the cerebellum, thalamus, motor cortex, precuneus, inferior parietal lobe, and insula. The cerebellum was identified as the hub of this network because it was the only brain region that was both functionally connected to the findings of over 90% of studies and significantly different in connectivity compared with a control data set of other movement disorders. This network was strikingly similar to the therapeutic network derived from lesions improving ET, with key regions aligning in the thalamus and cerebellum. Furthermore, positive functional connectivity between the cerebellar network hub and the sensorimotor cortices was significantly reduced in patients with ET compared with healthy controls, and connectivity within this network was correlated with tremor severity and cognitive functioning.

DISCUSSION

These findings suggest that the cerebellum is the central hub of a network commonly connected to structural and metabolic abnormalities in ET. This network may have therapeutic utility in refining and informing new targets for neuromodulation of ET.

Regional, circuit and network heterogeneity of brain abnormalities in psychiatric disorders

The substantial individual heterogeneity that characterizes people with mental illness is often ignored by classical case-control research, which relies on group mean comparisons. Here we present a comprehensive, multiscale characterization of the heterogeneity of gray matter volume (GMV) differences in 1,294 cases diagnosed with one of six conditions (attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, depression, obsessive-compulsive disorder and schizophrenia) and 1,465 matched controls. Normative models indicated that person-specific deviations from population expectations for regional GMV were highly heterogeneous, affecting the same area in <7% of people with the same diagnosis. However, these deviations were embedded within common functional circuits and networks in up to 56% of cases. The salience-ventral attention system was implicated transdiagnostically, with other systems selectively involved in depression, bipolar disorder, schizophrenia and attention-deficit/hyperactivity disorder. Phenotypic differences between cases assigned the same diagnosis may thus arise from the heterogeneous localization of specific regional deviations, whereas phenotypic similarities may be attributable to the dysfunction of common functional circuits and networks.

Functional and structural lesion network mapping in neurological and psychiatric disorders: a systematic review

Background

The traditional approach to studying the neurobiological mechanisms of brain disorders and localizing brain function involves identifying brain abnormalities and comparing them to matched controls. This method has been instrumental in clinical neurology, providing insight into the functional roles of different brain regions. However, it becomes challenging when lesions in diverse regions produce similar symptoms. To address this, researchers have begun mapping brain lesions to functional or structural networks, a process known as lesion network mapping (LNM). This approach seeks to identify common brain circuits associated with lesions in various areas. In this review, we focus on recent studies that have utilized LNM to map neurological and psychiatric symptoms, shedding light on how this method enhances our understanding of brain network functions.

Methods

We conducted a systematic search of four databases: PubMed, Scopus, and Web of Science, using the term "Lesion network mapping." Our focus was on observational studies that applied lesion network mapping in the context of neurological and psychiatric disorders.

Results

Following our screening process, we included 52 studies, comprising a total of 6,814 subjects, in our systematic review. These studies, which utilized functional connectivity, revealed several regions and network overlaps across various movement and psychiatric disorders. For instance, the cerebellum was found to be part of a common network for conditions such as essential tremor relief, parkinsonism, Holmes tremor, freezing of gait, cervical dystonia, infantile spasms, and tics. Additionally, the thalamus was identified as part of a common network for essential tremor relief, Holmes tremor, and executive function deficits. The dorsal attention network was significantly associated with fall risk in elderly individuals and parkinsonism.

Conclusion

LNM has proven to be a powerful tool in localizing a broad range of neuropsychiatric, behavioral, and movement disorders. It holds promise in identifying new treatment targets through symptom mapping. Nonetheless, the validity of these approaches should be confirmed by more comprehensive prospective studies.

Associations of lesion location, structural disconnection, and functional diaschisis with depressive symptoms post stroke

Introduction

Post-stroke depressive symptoms (PSDS) are common and relevant for patient outcome, but their complex pathophysiology is ill understood. It likely involves social, psychological and biological factors. Lesion location is a readily available information in stroke patients, but it is unclear if the neurobiological substrates of PSDS are spatially localized. Building on previous analyses, we sought to determine if PSDS are associated with specific lesion locations, structural disconnection and/or localized functional diaschisis.

Methods

In a prospective observational study, we examined 270 patients with first-ever stroke with the Hospital Anxiety and Depression Scale (HADS) around 6 months post-stroke. Based on individual lesion locations and the depression subscale of the HADS we performed support vector regression lesion-symptom mapping, structural-disconnection-symptom mapping and functional lesion network-symptom-mapping, in a reanalysis of this previously published cohort to infer structure-function relationships.

Results

We found that depressive symptoms were associated with (i) lesions in the right insula, right putamen, inferior frontal gyrus and right amygdala and (ii) structural disconnection in the right temporal lobe. In contrast, we found no association with localized functional diaschisis. In addition, we were unable to confirm a previously described association between depressive symptom load and a network damage score derived from functional disconnection maps.

Discussion

Based on our results, and other recent lesion studies, we see growing evidence for a prominent role of right frontostriatal brain circuits in PSDS.

The functional anatomy of dystonia: Recent developments

While dystonia has traditionally been viewed as a disorder of the basal ganglia, the involvement of other key brain structures is now accepted. However, just what these structures are remains to be defined. Neuroimaging has been an especially valuable tool in dystonia, yet traditional cross-sectional designs have not been able to separate causal from compensatory brain activity. Therefore, this chapter discusses recent studies using causal brain lesions, and animal models, to converge upon the brain regions responsible for dystonia with increasing precision. This evidence strongly implicates the basal ganglia, thalamus, brainstem, cerebellum, and somatosensory cortex, yet shows that different types of dystonia involve different nodes of this brain network. Nearly all of these nodes fall within the recently identified two-way networks connecting the basal ganglia and cerebellum, suggesting dysfunction of these specific pathways. Localisation of the functional anatomy of dystonia has strong implications for targeted treatment options, such as deep brain stimulation, and non-invasive brain stimulation.

Mapping a network for tics in Tourette syndrome using causal lesions and structural alterations

Tics are sudden stereotyped movements or vocalizations. Cases of lesion-induced tics are invaluable, allowing for causal links between symptoms and brain structures. While a lesion network for tics has recently been identified, the degree to which this network translates to Tourette syndrome has not been fully elucidated. This is important given that patients with Tourette syndrome make up a large portion of tic cases; therefore, existing and future treatments should apply to these patients. The aim of this study was to first localize a causal network for tics from lesion-induced cases and then refine and validate this network in patients with Tourette syndrome. We independently performed 'lesion network mapping' using a large normative functional connectome (n = 1000) to isolate a brain network commonly connected to lesions causing tics (n = 19) identified through a systematic search. The specificity of this network to tics was assessed through comparison to lesions causing other movement disorders. Using structural brain coordinates from prior neuroimaging studies (n = 7), we then derived a neural network for Tourette syndrome. This was done using standard anatomical likelihood estimation meta-analysis and a novel method termed 'coordinate network mapping', which uses the same coordinates, yet maps their connectivity using the aforementioned functional connectome. Conjunction analysis was used to refine the network for lesion-induced tics to Tourette syndrome by identifying regions common to both lesion and structural networks. We then tested whether connectivity from this common network is abnormal in a separate resting-state functional connectivity MRI data set from idiopathic Tourette syndrome patients (n = 21) and healthy controls (n = 25). Results showed that lesions causing tics were distributed throughout the brain; however, consistent with a recent study, these were part of a common network with predominant basal ganglia connectivity. Using conjunction analysis, coordinate network mapping findings refined the lesion network to the posterior putamen, caudate nucleus, globus pallidus externus (positive connectivity) and precuneus (negative connectivity). Functional connectivity from this positive network to frontal and cingulate regions was abnormal in patients with idiopathic Tourette syndrome. These findings identify a network derived from lesion-induced and idiopathic data, providing insight into the pathophysiology of tics in Tourette syndrome. Connectivity to our cortical cluster in the precuneus offers an exciting opportunity for non-invasive brain stimulation protocols.

Multimodal and multidomain lesion network mapping enhances prediction of sensorimotor behavior in stroke patients

Beyond the characteristics of a brain lesion, such as its etiology, size or location, lesion network mapping (LNM) has shown that similar symptoms after a lesion reflects similar dis-connectivity patterns, thereby linking symptoms to brain networks. Here, we extend LNM by using a multimodal strategy, combining functional and structural networks from 1000 healthy participants in the Human Connectome Project. We apply multimodal LNM to a cohort of 54 stroke patients with the aim of predicting sensorimotor behavior, as assessed through a combination of motor and sensory tests. Results are two-fold. First, multimodal LNM reveals that the functional modality contributes more than the structural one in the prediction of sensorimotor behavior. Second, when looking at each modality individually, the performance of the structural networks strongly depended on whether sensorimotor performance was corrected for lesion size, thereby eliminating the effect that larger lesions generally produce more severe sensorimotor impairment. In contrast, functional networks provided similar performance regardless of whether or not the effect of lesion size was removed. Overall, these results support the extension of LNM to its multimodal form, highlighting the synergistic and additive nature of different types of network modalities, and their corresponding influence on behavioral performance after brain injury.

Lesions causing central sleep apnea localize to one common brain network

Objectives

To characterize the specific brain regions for central sleep apnea (CSA) and identify its functional connectivity network.

Methods

We performed a literature search and identified 27 brain injuries causing CSA. We used a recently validated methodology termed “lesion network mapping” to identify the functional brain network subtending the pathophysiology of CSA. Two separate statistical approaches, the two-sample t-test and the Liebermeister test, were used to evaluate the specificity of this network for CSA through a comparison of our results with those of two other neurological syndromes. An additional independent cohort of six CSA cases was used to assess reproducibility.

Results

Our results showed that, despite lesions causing CSA being heterogeneous for brain localization, they share a common brain network defined by connectivity to the middle cingulate gyrus and bilateral cerebellar posterior lobes. This CSA-associated connectivity pattern was unique when compared with lesions causing the other two neurological syndromes. The CAS-specific regions were replicated by the additional independent cohort of six CSA cases. Finally, we found that all lesions causing CSA aligned well with the network defined by connectivity to the cingulate gyrus and bilateral cerebellar posterior lobes.

Conclusion

Our results suggest that brain injuries responsible for CSA are part of a common brain network defined by connectivity to the middle cingulate gyrus and bilateral cerebellar posterior lobes, lending insight into the neuroanatomical substrate of CSA.