Lesion network localization of depression in multiple sclerosis

Siddiqi, Shan; Kletenik, Isaiah; Anderson, Mark; Cavallari, Michele; Chitnis, Tanuja; Glanz, Bonnie I.; Khalil, Samar; Palotai, Miklós; Bakshi, Rohit; Fox, Michael

doi:10.1038/s44220-022-00002-y

Cited by 21 publications

(11 citation statements)

References 54 publications

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“…For this reason, we used a recently validated technique termed lesion network mapping to test whether these lesion-induced deficits map to specific brain networks. [11][12][13][14] We sought to identify (1) brain network connections associated with domain-specific anosognosia and (2) brain network connections associated with anosognosia in general, independent of the specific deficit.…”

Section: Introductionmentioning

confidence: 99%

“…As these 2 forms of anosognosia are in different locations, most often due to strokes in different vascular territories, lesions causing motor or visual anosognosia are less likely to directly overlap so the cross‐modal correlates are ideally examined at the network level. For this reason, we used a recently validated technique termed lesion network mapping to test whether these lesion‐induced deficits map to specific brain networks 11–14 . We sought to identify (1) brain network connections associated with domain‐specific anosognosia and (2) brain network connections associated with anosognosia in general, independent of the specific deficit.…”

Section: Introductionmentioning

confidence: 99%

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Network Localization of Awareness in Visual and Motor Anosognosia

Kletenik,

Gaudet,

Prasad

et al. 2023

Annals of Neurology

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ObjectiveUnawareness of a deficit, anosognosia, can occur for visual or motor deficits and lends insight into awareness itself; however, lesions associated with anosognosia occur in many different brain locations.MethodsWe analyzed 267 lesion locations associated with either vision loss (with and without awareness) or weakness (with and without awareness). The network of brain regions connected to each lesion location was computed using resting‐state functional connectivity from 1,000 healthy subjects. Both domain specific and cross‐modal associations with awareness were identified.ResultsThe domain‐specific network for visual anosognosia demonstrated connectivity to visual association cortex and posterior cingulate while motor anosognosia was defined by insula, supplementary motor area, and anterior cingulate connectivity. A cross‐modal anosognosia network was defined by connectivity to the hippocampus and precuneus (false discovery rate p < 0.05).InterpretationOur results identify distinct network connections associated with visual and motor anosognosia and a shared, cross‐modal network for awareness of deficits centered on memory‐related brain structures. ANN NEUROL 2023

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Network Localization of Awareness in Visual and Motor Anosognosia

Kletenik,

Gaudet,

Prasad

et al. 2023

Annals of Neurology

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“…A set of interconnected areas, with sometime opposite signs in their relationship, is reliably implicated in association with depression. In addition to the original discovery 3 , a very recent lesion mapping study in patients with multiple sclerosis resulted in a very similar map, showing close correlation with depression rates 4 . While our methodology deviates from traditional lesion mapping, as it is measuring structural volume change patterns, the second principal component of the variance shows a distinct similarity with the networks reported previously.…”

Section: Multivariate Analysis and Clinical Effectmentioning

confidence: 84%

Electroconvulsive therapy-induced volumetric brain changes converge on a common causal circuit in depression

Deng,

Ousdal,

Oltedal

et al. 2023

Preprint

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Neurostimulation is a mainstream treatment option for major depression. Neuromodulation techniques apply repetitive magnetic or electrical stimulation to some neural target but significantly differ in their invasiveness, spatial selectivity, mechanism of action, and efficacy. Despite these differences, recent analyses of transcranial magnetic stimulation (TMS) and deep brain stimulation (DBS)-treated individuals converged on a common neural network that might have a causal role in treatment response. We set out to investigate if the neuronal underpinnings of electroconvulsive therapy (ECT) are similarly associated with this common causal network (CCN). Our aim here is to provide a comprehensive analysis in three cohorts of patients segregated by electrode placement (N = 246 with right unilateral, 79 with bitemporal, and 61 with mixed) who underwent ECT. We conducted a data-driven, unsupervised multivariate neuroimaging analysis (Principal Component Analysis, PCA) of the cortical and subcortical volume changes and electric field (EF) distribution to explore changes within the CCN associated with antidepressant outcomes. Despite the different treatment modalities (ECT vs TMS and DBS) and methodological approaches (structural vs functional networks), we found a highly similar pattern of change within the CCN in the three cohorts of patients (spatial similarity across 85 regions: r = 0.65, 0.58, 0.40, df = 83). Most importantly, the expression of this pattern correlated with clinical outcomes. This evidence further supports that treatment interventions converge on a CCN in depression. Optimizing modulation of this network could serve to improve the outcome of neurostimulation in depression.

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“…Application of LNM has been shown to predict clinical symptoms in a variety of neurological disorders that can be understood as "disconnection syndromes", such as stroke or multiple sclerosis. 11,12 Here, we propose LNM as a technique to quantify WMHrelated, strategic neuronal disconnectivity for improved prediction of cognitive performance in CSVD. We employ LNM on a large-scale, multicenter dataset, integrating cognitive test results and MRI-based WMH segmentations from 3485 patients of 10 memory clinic cohorts through the Meta VCI Map Consortium.…”

Section: Introductionmentioning

confidence: 99%

Enhancing Cognitive Performance Prediction through White Matter Hyperintensity Connectivity Assessment: A Multicenter Lesion Network Mapping Analysis of 3,485 Memory Clinic Patients

Petersen,

Coenen,

DeCarli

et al. 2024

Preprint

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Introduction: White matter hyperintensities of presumed vascular origin (WMH) are associated with cognitive impairment and are a key imaging marker in evaluating cognitive health. However, WMH volume alone does not fully account for the extent of cognitive deficits and the mechanisms linking WMH to these deficits remain unclear. We propose that lesion network mapping (LNM), enabling the inference of brain networks disconnected by lesions, represents a promising technique for enhancing our understanding of the role of WMH in cognitive disorders. Our study employed this approach to test the following hypotheses: (1) LNM-informed markers surpass WMH volumes in predicting cognitive performance, and (2) WMH contributing to cognitive impairment map to specific brain networks. Methods & results: We analyzed cross-sectional data of 3,485 patients from 10 memory clinic cohorts within the Meta VCI Map Consortium, using harmonized test results in 4 cognitive domains and WMH segmentations. WMH segmentations were registered to a standard space and mapped onto existing normative structural and functional brain connectome data. We employed LNM to quantify WMH connectivity across 480 atlas-based gray and white matter regions of interest (ROI), resulting in ROI-level structural and functional LNM scores. The capacity of total and regional WMH volumes and LNM scores in predicting cognitive function was compared using ridge regression models in a nested cross-validation. LNM scores predicted performance in three cognitive domains (attention and executive function, information processing speed, and verbal memory) significantly better than WMH volumes. LNM scores did not improve prediction for language functions. ROI-level analysis revealed that higher LNM scores, representing greater disruptive effects of WMH on regional connectivity, in gray and white matter regions of the dorsal and ventral attention networks were associated with lower cognitive performance. Conclusion: WMH-related brain network disconnectivity significantly improves the prediction of current cognitive performance in memory clinic patients compared to WMH volume as a traditional imaging marker of cerebrovascular disease. This highlights the crucial role of network effects, particularly in attention-related brain regions, improving our understanding of vascular contributions to cognitive impairment. Moving forward, refining WMH information with connectivity data could contribute to patient-tailored therapeutic interventions and facilitate the identification of subgroups at risk of cognitive disorders.

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Lesion network localization of depression in multiple sclerosis

Cited by 21 publications

References 54 publications

Network Localization of Awareness in Visual and Motor Anosognosia

Network Localization of Awareness in Visual and Motor Anosognosia

Electroconvulsive therapy-induced volumetric brain changes converge on a common causal circuit in depression

Enhancing Cognitive Performance Prediction through White Matter Hyperintensity Connectivity Assessment: A Multicenter Lesion Network Mapping Analysis of 3,485 Memory Clinic Patients

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