Dataset Information

Mapping effective connectivity in the human brain with concurrent intracranial electrical stimulation and BOLD-fMRI.

ABSTRACT: BACKGROUND:Understanding brain function requires knowledge of how one brain region causally influences another. This information is difficult to obtain directly in the human brain, and is instead typically inferred from resting-state fMRI. NEW METHOD:Here, we demonstrate the safety and scientific promise of a novel and complementary approach: concurrent electrical stimulation and fMRI (es-fMRI) at 3T in awake neurosurgical patients with implanted depth electrodes. RESULTS:We document the results of safety testing, actual experimental setup, and stimulation parameters, that safely and reliably evoke activation in distal structures through stimulation of amygdala, cingulate, or prefrontal cortex. We compare connectivity inferred from the evoked patterns of activation with that estimated from standard resting-state fMRI in the same patients: while connectivity patterns obtained with each approach are correlated, each method produces unique results. Response patterns were stable over the course of 11min of es-fMRI runs. COMPARISON WITH EXISTING METHOD: es-fMRI in awake humans yields unique information about effective connectivity, complementing resting-state fMRI. Although our stimulations were below the level of inducing any apparent behavioral or perceptual effects, a next step would be to use es-fMRI to modulate task performances. This would reveal the acute network-level changes induced by the stimulation that mediate the behavioral and cognitive effects seen with brain stimulation. CONCLUSIONS:es-fMRI provides a novel and safe approach for mapping effective connectivity in the human brain in a clinical setting, and will inform treatments for psychiatric and neurodegenerative disorders that use deep brain stimulation.

SUBMITTER: Oya H

PROVIDER: S-EPMC5534177 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature

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Mapping effective connectivity in the human brain with concurrent intracranial electrical stimulation and BOLD-fMRI.

Oya Hiroyuki H Howard Matthew A MA Magnotta Vincent A VA Kruger Anton A Griffiths Timothy D TD Lemieux Louis L Carmichael David W DW Petkov Christopher I CI Kawasaki Hiroto H Kovach Christopher K CK Sutterer Matthew J MJ Adolphs Ralph R

Journal of neuroscience methods 20161221

<h4>Background</h4>Understanding brain function requires knowledge of how one brain region causally influences another. This information is difficult to obtain directly in the human brain, and is instead typically inferred from resting-state fMRI.<h4>New method</h4>Here, we demonstrate the safety and scientific promise of a novel and complementary approach: concurrent electrical stimulation and fMRI (es-fMRI) at 3T in awake neurosurgical patients with implanted depth electrodes.<h4>Results</h4>W ...[more]

PMID: 28012852

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Project description:ProposeDirected cortical responses to intracranial electrical stimulation are a good standard for mapping inter-regional direct connectivity. Cortico-cortical evoked potential (CCEP), elicited by single pulse electrical stimulation (SPES), has been widely used to map the normal and abnormal brain effective network. However, automated processing of CCEP datasets and visualization of connectivity results remain challenging for researchers and clinicians. In this study, we develop a Matlab toolbox named MRIES (Mapping the Responses to Intracranial Electrical Stimulation) to automatically process CCEP data and visualize the connectivity results.MethodThe MRIES integrates the processing pipeline of the CCEP datasets and various methods for connectivity calculation based on low- and high-frequency signals with stimulation artifacts removed. The connectivity matrices are saved in different folders for visualization. Different visualization patterns (connectivity matrix, circle map, surface map, and volume map) are also integrated to the graphical user interface (GUI), which makes it easy to intuitively display and compare different connectivity measurements. Furthermore, one sample CCEP data set collected from eight epilepsy patients is used to validate the MRIES toolbox.ResultWe show the GUI and visualization functions of MRIES using one example CCEP data that has been described in a complete tutorial. We applied this toolbox to the sample CCEP data set to investigate the direct connectivity between the medial temporal lobe and the insular cortex. We find bidirectional connectivity between MTL and insular that are consistent with the findings of previous studies.ConclusionMRIES has a friendly GUI and integrates the full processing pipeline of CCEP data and various visualization methods. The MRIES toolbox, tutorial, and example data can be freely downloaded. As an open-source package, MRIES is expected to improve the reproducibility of CCEP findings and facilitate clinical translation.

Project description:ObjectiveThe objective of this study was to explore the distributed network effects of intracranial electrical stimulation in patients with medically refractory epilepsy using dynamic functional connectivity (dFC) and graph indicators.MethodsThe time-varying connectivity patterns of dFC (state-based metrics) as well as topological properties of static functional connectivity (sFC) and dFC (graph indicators) were assessed before and after the intracranial electrical stimulation. The sliding window method and k-means clustering were used for the analysis of dFC states, which were characterized by connectivity strength, occupancy rate, dwell time, and transition. Graph indicators for sFC and dFC were obtained using group statistical tests.ResultsDFCs were clustered into two connectivity configurations: a strongly connected state (state 1) and a sparsely connected state (state 2). After electrical stimulation, the dwell time and occupancy rate of state 1 decreased, while that of state 2 increased. Connectivity strengths of both state 1 and state 2 decreased. For graph indicators, the clustering coefficient, k-core, global efficiency, and local efficiency of patients showed a significant decrease, but the brain networks of patients exhibited higher modularity after electrical stimulation. Especially, for state 1, there was a significant decrease in functional connectivity strength after stimulation within and between the frontal lobe and temporary lobe, both of which are associated with the seizure onset.ConclusionOur findings demonstrated that intracranial electrical stimulation significantly changed the time-varying connectivity patterns and graph indicators of the brain in patients with medically refractory epilepsy. Specifically, the electrical stimulation decreased functional connectivity strength in both local-level and global-level networks. This might provide a mechanism of understanding for the distributed network effects of intracranial electrical stimulation and extend the knowledge of the pathophysiological network of medically refractory epilepsy.

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Dataset Information

Mapping effective connectivity in the human brain with concurrent intracranial electrical stimulation and BOLD-fMRI.

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Mapping effective connectivity in the human brain with concurrent intracranial electrical stimulation and BOLD-fMRI.

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