Dataset Information

Impact of non-brain anatomy and coil orientation on inter- and intra-subject variability in TMS at midline.

ABSTRACT: OBJECTIVE:To investigate inter-subject variability with respect to cerebrospinal fluid thickness and brain-scalp distance, and to investigate intra-subject variability with different coil orientations. METHODS:Simulations of the induced electric field (E-Field) using a figure-8 coil over the vertex were conducted on 50 unique head models and varying orientations on 25 models. Metrics exploring stimulation intensity, spread, and localization were used to describe inter-subject variability and effects of non-brain anatomy. RESULTS:Both brain-scalp distance and CSF thickness were correlated with weaker stimulation intensity and greater spread. Coil rotations show that for the dorsal portion of the stimulated brain, E-Field intensities are highest when the anterior-posterior axis of the coil is perpendicular to the longitudinal fissure, but highest for the medial portion of the stimulated brain when the coil is oriented parallel to the longitudinal fissure. CONCLUSIONS:Normal anatomical variation in healthy individuals leads to significant differences in the site of TMS, the intensity, and the spread. These variables are generally neglected but could explain significant variability in basic and clinical studies. SIGNIFICANCE:This is the first work to show how brain-scalp distance and cerebrospinal fluid thickness influence focality, and to show the disassociation between dorsal and medial TMS.

SUBMITTER: Lee EG

PROVIDER: S-EPMC6563831 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

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Impact of non-brain anatomy and coil orientation on inter- and intra-subject variability in TMS at midline.

Lee Erik G EG Rastogi Priyam P Hadimani Ravi L RL Jiles David C DC Camprodon Joan A JA

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology 20180706 9

<h4>Objective</h4>To investigate inter-subject variability with respect to cerebrospinal fluid thickness and brain-scalp distance, and to investigate intra-subject variability with different coil orientations.<h4>Methods</h4>Simulations of the induced electric field (E-Field) using a figure-8 coil over the vertex were conducted on 50 unique head models and varying orientations on 25 models. Metrics exploring stimulation intensity, spread, and localization were used to describe inter-subject vari ...[more]

PMID: 30005214

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Project description:The stop signal task has been used to quantify the human inhibitory control. The inter-subject and intra-subject variability was investigated under the inhibition of human response with a realistic environmental scenario. In present study, we used a battleground scenario where a sniper-scope picture was the background, a target picture was a go signal, and a nontarget picture was a stop signal. The task instructions were to respond on the target image and inhibit the response if a nontarget image appeared. This scenario produced a threatening situation and endorsed the evaluation of how subject's response inhibition manifests in a real situation. In this study, 32 channels of electroencephalography (EEG) signals were collected from 20 participants during successful stop (response inhibition) and failed stop (response) trials. These EEG signals were used to predict two possible outcomes: successful stop or failed stop. The inter-subject variability (between-subjects) and intra-subject variability (within-subjects) affect the performance of participants in the classification system. The EEG signals of successful stop versus failed stop trials were classified using quadratic discriminant analysis (QDA) and linear discriminant analysis (LDA) (i.e., parametric) and K-nearest neighbor classifier (KNNC) and Parzen density-based (PARZEN) (i.e., nonparametric) under inter- and intra-subject variability. The EEG activities were found to increase during response inhibition in the frontal cortex (F3 and F4), presupplementary motor area (C3 and C4), parietal lobe (P3 and P4), and occipital (O1 and O2) lobe. Therefore, power spectral density (PSD) of EEG signals (1-50Hz) in F3, F4, C3, C4, P3, P4, O1, and O2 electrodes were measured in successful stop and failed stop trials. The PSD of the EEG signals was used as the feature input for the classifiers. Our proposed method shows an intra-subject classification accuracy of 97.61% for subject 15 with QDA classifier in C3 (left motor cortex) and an overall inter-subject classification accuracy of 71.66% ± 9.81% with the KNNC classifier in F3 (left frontal lobe). These results display how inter-subject and intra-subject variability affects the performance of the classification system. These findings can be used effectively to improve the psychopathology of attention deficit hyperactivity disorder (ADHD), obsessive-compulsive disorder (OCD), schizophrenia, and suicidality.

Dataset Information

Impact of non-brain anatomy and coil orientation on inter- and intra-subject variability in TMS at midline.

Publications

Impact of non-brain anatomy and coil orientation on inter- and intra-subject variability in TMS at midline.

Similar Datasets

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