Modulating oscillatory brain activity correlates of behavioral inhibition using transcranial direct current stimulation

Jacobson, Liron; Ezra, Adi; Berger, Uri; Lavidor, Michal

doi:10.1016/j.clinph.2011.09.016

Cited by 90 publications

(67 citation statements)

References 38 publications

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“…Similarly, DBS can reverse hippocampal information processing deficits among in animals with a variety of developmental manipulations thought to model schizophrenia (Ewing and Grace, 2013;Klein et al, 2013;Perez et al, 2013). In humans, transcranial direct current stimulation has been used to induce changes in brain activity, suggesting that non-pharmacological approaches may also have promise in treating the abnormal underlying brain rhythms in the disorder (Zaehle et al, 2010(Zaehle et al, , 2011a(Zaehle et al, , 2011bKeeser et al, 2011;Jacobson et al, 2012). Patients are shown in blue and controls in red.…”

Section: Discussionmentioning

confidence: 99%

Cellular and Circuit Models of Increased Resting State Network Gamma Activity in Schizophrenia

White

Siegel

2016

The Neurobiology of Schizophrenia

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Section: Discussionmentioning

confidence: 99%

Cellular and Circuit Models of Increased Resting State Network Gamma Activity in Schizophrenia

White

Siegel

2016

The Neurobiology of Schizophrenia

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“…Active stimulation groups received anodal stimulation for 10 min at an intensity of 0.5 mA (which in terms of current density is equal to 1.5 mA using 25-cm 2 saline sponges). We based our selection of stimulation intensity and polarity on previous studies (Batsikadze et al 2013;Jacobson et al 2011;Jacobson et al 2012a;Juan and Muggleton 2012). The stimulation began and ended with a current ramp up of 30 s. The sham condition received an electrical current only during the 30-s ramp up and then the 30-s ramp down.…”

Section: Methodsmentioning

confidence: 99%

Without Blinking an Eye: Proactive Motor Control Enhancement

Yaniv

Lavidor

2017

J Cogn Enhanc

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While most cognitive control enhancement studies have focused on reactive inhibition paradigms, enhancement of proactive control of urge-driven behaviors has been relatively neglected. With the aim of focusing on the proactive components of cognitive control over motor output, we designed a simple, ecologically valid eye blinking suppression task and applied transcranial direct current stimulation (tDCS) over the right inferior frontal gyrus (rIFG). Fifty-three subjects randomly allocated to three different stimulation groups underwent active or sham stimulation, subsequently performing eye blinking and stop signal tasks. Results showed that anodal stimulation over the rIFG increased the ability to suppress blinks compared to sham and active control stimulation. In addition, the rIFG group demonstrated a general slowdown of the stop signal reaction time, implying proactive control enhancement. Herein, we discuss our results with regard to previous findings as well as possible interventions in clinical populations.

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“…EEG plays a vital role in understanding the functional state of the brain and diagnosing disorders. For example, EEG has been used to study the modulatory effect of transcranial direct current stimulation (tDCS) on changes in cortical activities [3] and the treatment of brain disorders [4].…”

Section: Introductionmentioning

confidence: 99%

A Multichannel Deep Belief Network for the Classification of EEG Data

Al-Kaysi

Al-Ani

Boonstra

2015

Neural Information Processing

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Abstract. Deep learning, and in particular Deep Belief Network (DBN), has recently witnessed increased attention from researchers as a new classification platform. It has been successfully applied to a number of classification problems, such as image classification, speech recognition and natural language processing. However, deep learning has not been fully explored in electroencephalogram (EEG) classification. We propose in this paper three implementations of DBNs to classify multichannel EEG data based on different channel fusion levels. In order to evaluate the proposed method, we used EEG data that has been recorded to study the modulatory effect of transcranial direct current stimulation. One of the proposed DBNs produced very promising results when compared to three well-established classifiers; which are Support Vector Machine (SVM), Linear Discriminant Analysis (LDA) and Extreme Learning Machine (ELM).

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Modulating oscillatory brain activity correlates of behavioral inhibition using transcranial direct current stimulation

Cited by 90 publications

References 38 publications

Cellular and Circuit Models of Increased Resting State Network Gamma Activity in Schizophrenia

Cellular and Circuit Models of Increased Resting State Network Gamma Activity in Schizophrenia

Without Blinking an Eye: Proactive Motor Control Enhancement

A Multichannel Deep Belief Network for the Classification of EEG Data

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