A multichannel Deep Belief Network for the classification of EEG data

© Springer International Publishing Switzerland 2015. 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 Vec- tor Machine (SVM), Linear Discriminant Analysis (LDA) and Extreme Learning Machine (ELM)

Transcranial Direct Current Stimulation Modulates Working Memory Maintenance Processes in Healthy Individuals

The effects of transcranial direct current stimulation (tDCS) at the pFC are often investigated using cognitive paradigms, particularly working memory tasks. However, the neural basis for the neuromodulatory cognitive effects of tDCS, including whi ch subprocesses are af f ected by sti mul ati on, i s not completely understood. We investigated the effects of tDCS on working memory task-related spectral activity during and after tDCS to gain better insights into the neurophysiological changes associated with stimulation. We reanalyzed data from 100 healthy participants grouped by allocation to receive either sham (0 mA, 0.016 mA, and 0.034 mA) or active (1 mA or 2 mA) stimulation during a 3-back task. EEG data were used to analyze event-related spectral power in frequency bands associated with working memory performance. Frontal theta event-related synchronization (ERS) was significantly reduced post-tDCS in the active group. Participants receiving active tDCS had slower RTs following tDCS compared with sham, suggesting interference with practice effects associated with task repetition. Theta ERS was not significantly correlated with RTs or accuracy. tDCS reduced frontal theta ERS poststimulation, suggesting a selective disruption to working memory cognitive control and maintenance processes. These findings suggest that tDCS selectively affects specific subprocesses during working memory, which may explain heterogenous behavioral effects

Reliability of transcranial magnetic stimulation evoked potentials to detect the effects of theta-burst stimulation of the prefrontal cortex

Background: Transcranial magnetic stimulation (TMS) with simultaneous electroencephalography (EEG) is a novel method for assessing cortical properties outside the motor region. Theta burst stimulation (TBS), a form of repetitive TMS, can non-invasively modulate cortical excitability and has been increasingly used to treat psychiatric disorders by targetting the dorsolateral prefrontal cortex (DLPFC). The TMS-evoked potentials (TEPs) and local mean field power (LMFP) analyses have been used to evaluate local cortical excitability changes after TBS. However, it remains unclear whether TEPs can detect the neuromodulatory effects of TBS. Objectives: To confirm the reliability of TEP components and LMFP within and between sessions and to measure changes in neural excitability induced by intermittent (iTBS) and continuous TBS (cTBS) applied to the left DLPFC. Methods: Test-retest reliability of TEPs/LMFP and TBS-induced changes in cortical excitability were assessed in twenty-four healthy participants by stimulating the DLPFC in five separate sessions, once with sham and twice with iTBS and cTBS. EEG responses were recorded of 100 single TMS pulses before and after TBS, and the reproducibility measures were quantified with the concordance correlation coefficient (CCC). Results: The N100 and P200 components presented substantial reliability within the baseline block (CCCs>0.8) and moderate concordance between sessions (CCCmax> 0.6). Both N40 and P60 TEP amplitudes showed little concordance between sessions. Similar results were achieved using LMFP responses. Changes in TEP amplitudes after iTBS were marginally reliable for N100 (CCCmax = 0.52), P200 (CCCmax = 0.47) and P60 (CCCmax = 0.40), presenting only fair levels of concordance at specific time points. LMFP changes showed poor reproducibility after iTBS and cTBS. Conclusions: The present findings show that only the N100 and P200 components had good concordance between sessions. The reliability of earlier TEP components and LMF responses may have been affected by a sub-optimal removal of TMS-related artefacts. The poor reliability in detecting changes in neural excitability induced by TBS indicates that TEPs/LMFP do not provide a precise estimate of the changes in excitability in the DLPFC or, alternatively, that TBS did not induce consistent changes in neural excitability

Neuromodulatory effects of theta burst stimulation to the prefrontal cortex

Theta burst stimulation (TBS) is a new form of repetitive transcranial magnetic stimulation (TMS) capable of non-invasively modulating cortical excitability. In recent years TBS has been increasingly used as a neuroscientific investigative tool and therapeutic intervention for psychiatric disorders, in which the dorsolateral prefrontal cortex (DLPFC) is often the primary target. However, the neuromodulatory effects of TBS on prefrontal regions remain unclear. Here we share EEG and ECG recordings and structural MRI scans, including high-resolution DTI, from twenty-four healthy participants who received intermittent TBS (two sessions), continuous TBS (two sessions), and sham stimulation (one session) applied to the left DLPFC using a single-blinded crossover design. Each session includes eyes-open resting-state EEG and single-pulse TMS-EEG obtained before TBS and 2−, 15−, and 30-minutes post-stimulation. This dataset enables foundational basic science investigations into the neuromodulatory effects of TBS on the DLPFC

The influence of age and gender in the interaction with touch screens

Touch screens are nowadays one of the major interfaces in the interaction between humans and technology, mostly due to the significant growth in the use of smartphones and tablets in the last years. This broad use, that reaches people from all strata of society, makes touch screens a relevant tool to study the mechanisms that influence the way we interact with electronic devices. In this paper we collect data regarding the interaction patterns of different users with mobile devices. We present a way to formalize these interaction patterns and analyze how aspects such as age and gender influence them. The results of this research may be relevant for developing mobile applications that identify and adapt to the users or their characteristics, including impairments in fine motor skills or in cognitive function.Fundos Europeus Estruturais e de Investimento (FEEI) through Programa Operacional Regional Norte, in the scope of project NORTE01-0145-FEDER-02357

Towards responsible use of cognitive-enhancing drugs by the healthy

In this article, we propose actions that will help society accept the benefits of enhancement, given appropriate research and evolved regulation. Prescription drugs are regulated as such not for their enhancing properties but primarily for considerations of safety and potential abuse. Still, cognitive enhancement has much to offer individuals and society, and a proper societal response will involve making enhancements available while managing their risks

Non-identical smoothing operators for estimating time-frequency interdependence in electrophysiological recordings

Synchronization of neural activity from distant parts of the brain is crucial for the coordination of cognitive activities. Because neural synchronization varies both in time and frequency, time–frequency (T-F) coherence is commonly employed to assess interdependences in electrophysiological recordings. T-F coherence entails smoothing the cross and power spectra to ensure statistical consistency of the estimate, which reduces its T-F resolution. This trade-off has been described in detail when the cross and power spectra are smoothed using identical smoothing operators, which may yield spurious coherent frequencies. In this article, we examine the use of non-identical smoothing operators for the estimation of T-F interdependence, i.e., phase synchronization is characterized by phase locking between signals captured by the cross spectrum and we may hence improve the trade-off by selectively smoothing the auto spectra. We first show that the frequency marginal density of the present estimate is bound within [0,1] when using non-identical smoothing operators. An analytic calculation of the bias and variance of present estimators is performed and compared with the bias and variance of standard T-F coherence using Monte Carlo simulations. We then test the use of non-identical smoothing operators on simulated data, whose T-F properties are known through construction. Finally, we analyze empirical data from eyes-closed surface electroencephalography recorded in human subjects to investigate alpha-band synchronization. These analyses show that selectively smoothing the auto spectra reduces the bias of the estimator and may improve the detection of T-F interdependence in electrophysiological data at high temporal resolution

Flanker performance in female college students with ADHD: a diffusion model analysis

Attention-deficit hyperactivity disorder (ADHD) is characterized by poor adaptation to environmental demands, which leads to various everyday life problems. The present study had four aims: (1) to compare performance in a flanker task in female college students with and without ADHD (N = 39) in a classical analyses of reaction time and error rate and studying the underlying processes using a diffusion model, (2) to compare the amount of focused attention, (3) to explore the adaptation of focused attention, and (4) to relate adaptation to psychological functioning. The study followed a 2-between (group: ADHD vs. control) × 2-within (flanker conflict: incongruent vs. congruent) × 2-within (conflict frequency: 20 vs. 80 %) design. Compared to a control group, the ADHD group displayed prolonged response times accompanied by fewer errors in a flanker task. Results from the diffusion model analyses revealed that the members of the ADHD group showed deficits in non-decisional processes (i.e., higher non-decision time) and leaned more toward accuracy than participants without ADHD (i.e., setting higher boundaries). The ADHD group showed a more focused attention and less adaptation to the task conditions which is related to psychological functioning. Deficient non-decisional processes and poor adaptation are in line with theories of ADHD and presumably typical for the ADHD population, although this has not been shown using a diffusion model. However, we assume that the cautious strategy of trading speed of for accuracy is specific to the subgroup of female college students with ADHD and might be interpreted as a compensation mechanism