Neural Engineering / Neuroengineering / Brain Engineering
Mohammad Reza Nazari; Mohammad Reza Daliri; Ali Motie Nasrabadi
Volume 16, Issue 1 , May 2022, , Pages 51-62
Abstract
Visual attention as a cognitive factor plays a significant role in the processing of higher-order mental information that happens in the brain and affects brain activity in various areas of the visual cortex. Among the various recording systems, local field potentials, due to their stability, robustness, ...
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Visual attention as a cognitive factor plays a significant role in the processing of higher-order mental information that happens in the brain and affects brain activity in various areas of the visual cortex. Among the various recording systems, local field potentials, due to their stability, robustness, and frequency content have received interest in brain structure and cognitive processing research, as well as brain-computer interface (BCI) systems. Hence, the extraction and interpretation of information from local field potential (LFP) signals during visual attention has been considered to control cognitive systems. Cross-frequency coupling (CFC) as one of the information encoding strategies in the brain plays a functional role in perception, working memory, and visual attention tasks. However, the role of CFC as informative features for spatial attention decoding has not been adequately investigated. This paper aims to examine spatial attention decoding using LFP signals recorded from the monkey middle temporal area (MT). For this purpose, phase-phase and phase-amplitude coupling features and machine learning algorithms have been employed. The results show that the highest decoding performance was achieved by applying selected optimal features and the support vector machine classifier (90.36%). Moreover, among the selected features, gamma-delta, gamma-alpha, and beta-delta coupling contain the most cognitive information and the most effective features to improve the decoding performance of spatial attention in the visual system. Generally, the results suggest that cross-frequency coupling of LFP signals contains significant information in spatial attention tasks, and can be used as a suitable alternative to the time-frequency features of brain signals in cognitive BCI systems.
Neural Engineering / Neuroengineering / Brain Engineering
Ghazaleh Soleimani; Mehrdad Saviz; Farzad Towhidkhah; Hamed Ekhtiari
Volume 14, Issue 3 , October 2020, , Pages 251-266
Abstract
Transcranial direct current stimulation (tDCS) is the most-used non-invasive brain stimulation method. However, the main challenge in tDCS studies is its heterogeneity and large inter-individual variability in response. Brain anatomy, that varies from person to person, can change electric field distribution ...
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Transcranial direct current stimulation (tDCS) is the most-used non-invasive brain stimulation method. However, the main challenge in tDCS studies is its heterogeneity and large inter-individual variability in response. Brain anatomy, that varies from person to person, can change electric field distribution patterns in the brain and should be considered as a source of variation. Previous findings support that tDCS-induced EFs affect brain activity and ultimately change behavioral outcomes. Nonetheless, the exact relationship between EFs and brain activity alterations has not yet been investigated. In this randomized double-blinded sham-controlled crossover study, 14 subjects with methamphetamine use disorders were recruited and tDCS with 2 mA current intensity was applied over the dorsolateral prefrontal cortex. Each subject participated in two sessions for sham or real stimulation with at least a 1-week washout period. In each session, structural and functional MRI during a cue-induced craving task were collected immediately before and after tDCS. Individualized computational head models were simulated based on structural MR images and finite element methods. Group-level analysis of the models showed inter-individual variability across the subjects with maximum electric field intensity in frontal pole (0.3424±0.07). Furthermore, functional data, based on a drug minus neutral contrast, showed that real versus sham stimulation decreased brain activity in superior temporal gyrus and posterior cingulate cortex (P<0.001). However, we did not find a significant correlation between induced EFs and brain activity alterations. In sum, in this study, we suggested a pipeline for integrating electric fields with functional neuroimaging data to bring new insights into the tDCS mechanism of action and future studies are required to establish, or to refute, this conclusion.
