Brain Topography

Papers
(The H4-Index of Brain Topography is 17. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2021-04-01 to 2025-04-01.)
ArticleCitations
Eeg Microstates and Balance Parameters for Stroke Discrimination: A Machine Learning Approach110
Individuals’ Food Preferences can be Influenced by the Music Styles: An ERP Study100
Electroencephalogram (EEG) Based Fuzzy Logic and Spiking Neural Networks (FLSNN) for Advanced Multiple Neurological Disorder Diagnosis50
Cortical and Subcortical Changes in MEG Activity Reflect Parkinson’s Progression over a Period of 7 Years45
Side-of-Implantation Effect on Functional Asymmetry in the Auditory Cortex of Single-Sided Deaf Cochlear-Implant Users35
Decoding the Preparation Stage of Target Shooting under Audiovisual Restricted Conditions: Investigating Neural Mechanisms Using Microstate Analysis32
Examination of the Development and Asymmetry of the Cerebellum and Its Lobules in Individuals Aged 1–18 Years: A Retrospective MRI Study28
Timing of Allocentric and Egocentric Spatial Processing in Human Intracranial EEG22
Motor Circuit and Superior Temporal Sulcus Activities Linked to Individual Differences in Multisensory Speech Perception21
MEG Microstates: An Investigation of Underlying Brain Sources and Potential Neurophysiological Processes21
Effects of Intermittent Theta Burst Stimulation on the Clock Drawing Test Performances in Patients with Alzheimer’s Disease21
Linear and Non-linear Analyses of EEG in a Group of ASD Children During Resting State Condition20
Evoked EEG Responses to TMS Targeting Regions Outside the Primary Motor Cortex and Their Test–Retest Reliability20
Resting‐State EEG Microstates Parallel Age‐Related Differences in Allocentric Spatial Working Memory Performance19
Modulating Long Term Memory at Late-Encoding Phase: An rTMS Study18
Neural Mechanisms Underlying Human Auditory Evoked Responses Revealed By Human Neocortical Neurosolver18
Neural Networks to Recognize Patterns in Topographic Images of Cortical Electrical Activity of Patients with Neurological Diseases17
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