AIMC Topic: Gamma Rhythm
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Single pulse electrical stimulation of the medial thalamic surface induces narrower high gamma band activities in the sensorimotor cortex.
Scientific reports
Jul 1, 2025
The human thalamus projects nerve fibers to all cortical regions and propagates epileptic activity. However, opportunities to directly record thalamic and cortical neural activities simultaneously are extremely limited and their electrophysiological ...
γ neuromodulations: unraveling biomarkers for neurological and psychiatric disorders.
Military Medical Research
Jun 27, 2025
γ neuromodulation has emerged as a promising strategy for addressing neurological and psychiatric disorders, particularly in regulating executive and cognitive functions. This review explores the latest neuromodulation techniques, focusing on the cri...
Uncovering key predictive channels and clinical variables in the gamma band auditory steady-state response in early-stage psychosis: a longitudinal study.
Acta neuropsychiatrica
Dec 9, 2024
OBJECTIVE: Psychotic disorders are characterised by abnormalities in the synchronisation of neuronal responses. A 40 Hz gamma band deficit during auditory steady-state response (ASSR) measured by electroencephalogram (EEG) is a robust observation in ...
Coordination of top-down influence on V1 responses by interneurons and brain rhythms.
Bio Systems
Jun 15, 2021
Top-down processing in neocortex underlies functions such as prediction, expectation, and attention. Visual systems have much feedback connection that carries information of behavioral context. Top-down signals along feedback pathways modulate the re...
The Function of Color and Structure Based on EEG Features in Landscape Recognition.
International journal of environmental research and public health
May 3, 2021
Both color and structure make important contributions to human visual perception, as well as the evaluation of landscape quality and landscape aesthetics. The EEG equipment liveamp32 was used to record the EEG signals of humans when viewing landscape...
The Generation and Modulation of Distinct Gamma Oscillations with Local, Horizontal, and Feedback Connections in the Primary Visual Cortex: A Model Study on Large-Scale Networks.
Neural plasticity
Jan 18, 2021
Gamma oscillation (GAMMA) in the local field potential (LFP) is a synchronized activity commonly found in many brain regions, and it has been thought as a functional signature of network connectivity in the brain, which plays important roles in infor...
Empirically constrained network models for contrast-dependent modulation of gamma rhythm in V1.
NeuroImage
Jan 15, 2021
Gamma oscillations are thought to play a key role in neuronal network function and neuronal communication, yet the underlying generating mechanisms have not been fully elucidated to date. At least partly, this may be due to the fact that even in simp...
Prefrontal oscillations modulate the propagation of neuronal activity required for working memory.
Neurobiology of learning and memory
Jun 17, 2020
Cognition involves using attended information, maintained in working memory (WM), to guide action. During a cognitive task, a correct response requires flexible, selective gating so that only the appropriate information flows from WM to downstream ef...
Human visual cortical gamma reflects natural image structure.
NeuroImage
Jun 24, 2019
Many studies have reported visual cortical gamma-band activity related to stimulus processing and cognition. Most respective studies used artificial stimuli, and the few studies that used natural stimuli disagree. Electrocorticographic (ECoG) recordi...
A Channel-Projection Mixed-Scale Convolutional Neural Network for Motor Imagery EEG Decoding.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
May 8, 2019
Motor imagery electroencephalography (EEG) decoding is an essential part of brain-computer interfaces (BCIs) which help motor-disabled patients to communicate with the outside world by external devices. Recently, deep learning algorithms using decomp...
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