Real-time EEG Feedback on Alpha Power Lateralization Leads to Behavioral Improvements in a Covert Attention Task

Visual attention can be spatially oriented, even in the absence of saccadic eye-movements, to facilitate the processing of incoming visual information. One behavioral proxy for this so-called covert visuospatial attention (CVSA) is the validity effect (VE): the reduction in reaction time (RT) to visual stimuli at attended locations and the increase in RT to stimuli at unattended locations. At the electrophysiological level, one correlate of CVSA is the lateralization in the occipital α-band oscillations, resulting from α-power increases ipsilateral and decreases contralateral to the attended hemifield. While this α-band lateralization has been considerably studied using electroencephalography (EEG) or magnetoencephalography (MEG), little is known about whether it can be trained to improve CVSA behaviorally. In this cross-over sham-controlled study we used continuous real-time feedback of the occipital α-lateralization to modulate behavioral and electrophysiological markers of covert attention. Fourteen subjects performed a cued CVSA task, involving fast responses to covertly attended stimuli. During real-time feedback runs, trials extended in time if subjects reached states of high α-lateralization. Crucially, the ongoing α-lateralization was fed back to the subject by changing the color of the attended stimulus. We hypothesized that this ability to self-monitor lapses in CVSA and thus being able to refocus attention accordingly would lead to improved CVSA performance during subsequent testing. We probed the effect of the intervention by evaluating the pre-post changes in the VE and the α-lateralization. Behaviorally, results showed a significant interaction between feedback (experimental–sham) and time (pre-post) for the validity effect, with an increase in performance only for the experimental condition. We did not find corresponding pre-post changes in the α-lateralization. Our findings suggest that EEG-based real-time feedback is a promising tool to enhance the level of covert visuospatial attention, especially with respect to behavioral changes. This opens up the exploration of applications of the proposed training method for the cognitive rehabilitation of attentional disorders.

Analysis of Anticipation Related Potentials for Brain Computer Interaction

Gangadhar Garipelli

Anticipation is a mental process during which a person actively engages in a phase required for the sensory perception and execution of the optimal actions at the arrival of the relevant future events. Since this process occurs before the execution of an intended action, it may be used as a control signal for Brain Computer Interface (BCI) applications. Recognition of neural correlates of this process can enhance the performance of a BCI and in turn reduce mental workload of its users. To this end, it is vital to understand the neural correlates involved in this process and to design robust methods for its recognition in single trials. The analysis of these correlates may also contribute to the basic knowledge of the mechanisms underlying this behavior. The thesis provides three major contributions: (i) it reports methods for the robust recognition of anticipation related Electroencephalogram (EEG) potentials (ii) it provides insights into the selection of appropriate preprocessing steps required for enhancing the Signal-to-Noise Ratio (SNR) of anticipatory slow cortical potentials (SCPs) and (iii) it identifies scalp area specific oscillatory activity related to different aspects of anticipatory behavior. First, we focus on methods for the single trial recognition of anticipatory SCPs using the widely known classical contingent negative variation (CNV) paradigm. Using this paradigm, we demonstrate the feasibility of recognizing the anticipatory SCPs (CNV potentials) using features thatmodel its temporal pattern. We propose a Bayesian approach that exploits temporal evolution and redundancy to quickly classify (e.g., within half of the anticipatory period), without compromising classification accuracy. We then improve upon these recognition rates by using a source localization technique based on the biophysical model of the human head. We further validate the feasibility of recognizing CNV potentials in an online experiment, and report for the first time that, under controlled conditions, these potentials can be reproduced and recognized in realistic interaction scenarios (assistive technology web-browsing) with high accuracies. Second, the thesis provides insights into the selection of appropriate preprocessing stages required for improving the SNR of SCPs. The CNV potentials are characterized by low frequencies that are usually recorded with full-DC, and hence suffer from task-irrelevant high amplitude fluctuations and spatial noise. To account for this, we identified appropriate spectral and spatial filters to improve the SNR. We demonstrate the potential of these preprocessing stages by using fusing multiple electrode specific linear classifiers, which achieve recognition performances of 90±2% (area under curve of receiver operating characteristic), where the classifiers are trained using recordings from one day and tested on the recordings from several days apart. Finally, the thesis identifies different facets of anticipatory behavior. Apart from the widely known CNV potentials, it is not clear which other spectral bands could be related to anticipatory behavior. Using recordings from an experiment (i.e., the assistive technology web browser) where multiple warning stimuli predicted an imperative stimulus, we explored the phase and amplitude response of various oscillatory sub-bands for the identification of markers that could be associated with different aspects of anticipation. From this study we report that: (i) there are duration (4-10 seconds) specific changes in Electroencephalography (EEG) activity in the range 0-1 Hz in the central electrodes correlate with reaction time, (ii) there exist slow oscillations (0.1-1 Hz) in the central electrodes that exhibit phase tuning up to 4 seconds before the onset of a target cue, (iii) there are delta oscillations (1.5-3 Hz), which are entrained to predictive rhythmic warning cues, (iv) there is a selective modulation (increase or decrease) in the amplitude of occipital alpha band (8-12 Hz) based on the relevance of forthcoming visual cue, and (v) there exist a reduction in the beta band (14-30 Hz) amplitude in the sensory motor and association areas lasting up to 10 seconds. The phase tuning and entrainment resulted in a low variance of phase values at the arrival of the imperative stimulus, which may be required for its optimal processing. The amplitude modulation of alpha band activity is likely to be a resultant of sensory suppression and attention. The reduction of beta-band activity over long periods of time suggests holding of sensory-motor association areas until the execution of a planned action. We believe that these observations are the consequence of the endogenous drive on the ongoing oscillations to enhance the processing of the forthcoming stimuli and preparation for an intended action. In summary, the thesis provides methods for the recognition of anticipatory SCPs by exploiting spectral and spatio-temporal characteristics with high performances. By exploring various other oscillatory sub-bands, the spectral characteristics of different aspects of anticipatory behavior are also identified. Further, methods modeling these characteristics can bring forth more robust and faster techniques for BCI systems.

EPFL2011

Converging intracortical signatures of two separated processing timescales in human early auditory cortex

Fabiano Baroni, Arwen Blanche Giraud

Neural oscillations in auditory cortex are argued to support parsing and representing speech constituents at their corresponding temporal scales. Yet, how incoming sensory information interacts with ongoing spontaneous brain activity, what features of the neuronal microcircuitry underlie spontaneous and stimulus-evoked spectral fin-gerprints, and what these fingerprints entail for stimulus encoding, remain largely open questions. We used a combination of human invasive electrophysiology, computational modeling and decoding techniques to assess the information encoding properties of brain activity and to relate them to a plausible underlying neuronal micro -architecture. We analyzed intracortical auditory EEG activity from 10 patients while they were listening to short sentences. Pre-stimulus neural activity in early auditory cortical regions often exhibited power spectra with a shoulder in the delta range and a small bump in the beta range. Speech decreased power in the beta range, and increased power in the delta-theta and gamma ranges. Using multivariate machine learning techniques, we assessed the spectral profile of information content for two aspects of speech processing: detection and discrimination. We obtained better phase than power information decoding, and a bimodal spectral profile of information content with better decoding at low (delta-theta) and high (gamma) frequencies than at intermediate (beta) frequencies. These experimental data were reproduced by a simple rate model made of two subnetworks with different timescales, each composed of coupled excitatory and inhibitory units, and connected via a negative feedback loop. Modeling and experimental results were similar in terms of pre-stimulus spectral profile (except for the iEEG beta bump), spectral modulations with speech, and spectral profile of information content. Altogether, we provide converging evidence from both univariate spectral analysis and decoding approaches for a dual timescale processing infrastructure in human auditory cortex, and show that it is consistent with the dynamics of a simple rate model.

2020

Orchestration of oscillatory activity to improve visual motion discrimination

Roberto Felipe Salamanca Giron

This thesis describes advances in the use of novel configurations of non-invasive brain stimulation over the visual system allowing to modulate of modifying electro-physiological activity, interregional interactions and by it, visual behavior such as motion discrimination capacity in healthy subjects. We have implemented three experimental protocols that include the application of a motion discrimination and integration task in combination with bifocal transcranial Alternating Current Stimulation (i.e. tACS) over the primary visual cortex (i.e. V1) and medio-temporal areas (i.e. V5), while varying some of the âorchestraâ parameters in each study. The common objective pursued in the three studies presented in the upcoming chapters was to evaluate physiological changes induced by tACS combined with the visual task, leading to enhanced visual performance expressed by the accurate distinction of the generalized movement orientation of a kinetogram. After introducing the scientific rationale of this thesis in Chapter 1, Chapter 2 describes whether applying two phase-shifted (Alpha) É-tACS conditions (Anti-Phase and In-Phase tACS) within the V1-V5 network were able to positively modulate behavior compared to Sham tACS. Our results suggest that the active Anti-Phase condition significantly increased visual motion discrimination compared to In-phase tACS which rather tended to decrease performances. These two case scenarios were associated with opposite changes in Alpha-Gamma oscillatory modulation (i.e. V1 phase â V5 amplitude coupling) determined by multichannel EEG. Based on these findings, in Chapter 3, we describe testing the effects of modulating Alpha-Gamma interregional interaction. Hence, two conditions V1ÉV5Æ tACS and vice versa, V1ÆV5É tACS, were behaviorally and electrophysiologically evaluated. The results suggested that there was a common electrophysiological feature between the two Verum tACS, which contrasted with Sham tACS, expressed through WPLIÆ (i.e. Weighted Phase Locking Value) connectivity. Furthermore, WPLIÉ and ZPAC V1amplitude â V5phase (i.e. Z-scored Phase Amplitude Coupling) were the inter-areal mechanisms in which both Verum conditions differed to explain the variance of their corresponding group behavior. However, the electrophysiological changes did not lead to significant difference in behavioral measures.In Chapter 4, we combined the knowledge gained in the first two studies and thus, we time-locked, short bursts of phase-shifted É-tACS to the visual stimulus onset. This permitted to find out that, despite the phase difference between the tACS conditions (i.e. In-Phase vs. Anti-Phase), there was a generalized augmentation of the performance after verum stimulation compared to the results with Sham. This amelioration was generally associated with changes in causal PSI (i.e. Phase Slope Index) flows in Æ, whereas specifically the Î-Æ modulation permitted to explain the differences in behavior between Verum and Sham. Moreover, dynamic PSI-causal Î² bottom-up and top-down flows revealed the mechanisms behind each type of Verum stimulation. These studies provided first interesting evidence that physiology-inspired bifocal tACS applied to the visual network might be used to modulate visual behavior and respective underlying mechanisms. The induced electrophysiological and behavioural effects achieved are complex and need to be studied in more details in upcoming studies.

EPFL2021