Electrophysiology | EPFL Graph Search

Electrophysiology (from Greek ἥλεκτ, ēlektron, "amber" [see the etymology of "electron"]; φύσις, physis, "nature, origin"; and -λογία, -logia) is the branch of physiology that studies the electrical properties of biological cells and tissues. It involves measurements of voltage changes or electric current or manipulations on a wide variety of scales from single ion channel proteins to whole organs like the heart. In neuroscience, it includes measurements of the electrical activity of neurons, and, in particular, action potential activity. Recordings of large-scale electric signals from the nervous system, such as electroencephalography, may also be referred to as electrophysiological recordings. They are useful for electrodiagnosis and monitoring. Definition and scope Classical electrophysiological techniques Principle and mechanisms Electrophysiology is the branch of physiology that pertains broadly to the flow of ions (ion current) in biological tissu

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

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

The EBRAINS Hodgkin-Huxley Neuron Builder: An online resource for building data-driven neuron models

Shailesh Appukuttan, Luca Leonardo Bologna, Jean-Denis Georges Emile Courcol, Genrich Ivaska, Carmen Alina Lupascu, Michele Migliore

In the last decades, brain modeling has been established as a fundamental tool for understanding neural mechanisms and information processing in individual cells and circuits at different scales of observation. Building data-driven brain models requires the availability of experimental data and analysis tools as well as neural simulation environments and, often, large scale computing facilities. All these components are rarely found in a comprehensive framework and usually require ad hoc programming. To address this, we developed the EBRAINS Hodgkin-Huxley Neuron Builder (HHNB), a web resource for building single cell neural models via the extraction of activity features from electrophysiological traces, the optimization of the model parameters via a genetic algorithm executed on high performance computing facilities and the simulation of the optimized model in an interactive framework. Thanks to its inherent characteristics, the HHNB facilitates the data-driven model building workflow and its reproducibility, hence fostering a collaborative approach to brain modeling.