scholarly journals Connectomics of Human Electrophysiology

NeuroImage ◽  
2021 ◽  
pp. 118788
Author(s):  
Sepideh Sadaghiani ◽  
Matthew J Brookes ◽  
Sylvain Baillet
2009 ◽  
Vol 73 (2) ◽  
pp. 222-232 ◽  
Author(s):  
Rosalie Perron ◽  
Christine Lefebvre ◽  
Nicolas Robitaille ◽  
Benoit Brisson ◽  
Frédéric Gosselin ◽  
...  

2015 ◽  
Vol 39 (1) ◽  
pp. 15-26 ◽  
Author(s):  
Javier Rodriguez-Falces

A concept of major importance in human electrophysiology studies is the process by which activation of an excitable cell results in a rapid rise and fall of the electrical membrane potential, the so-called action potential. Hodgkin and Huxley proposed a model to explain the ionic mechanisms underlying the formation of action potentials. However, this model is unsuitably complex for teaching purposes. In addition, the Hodgkin and Huxley approach describes the shape of the action potential only in terms of ionic currents, i.e., it is unable to explain the electrical significance of the action potential or describe the electrical field arising from this source using basic concepts of electromagnetic theory. The goal of the present report was to propose a new model to describe the electrical behaviour of the action potential in terms of elementary electrical sources (in particular, dipoles). The efficacy of this model was tested through a closed-book written exam. The proposed model increased the ability of students to appreciate the distributed character of the action potential and also to recognize that this source spreads out along the fiber as function of space. In addition, the new approach allowed students to realize that the amplitude and sign of the extracellular electrical potential arising from the action potential are determined by the spatial derivative of this intracellular source. The proposed model, which incorporates intuitive graphical representations, has improved students' understanding of the electrical potentials generated by bioelectrical sources and has heightened their interest in bioelectricity.


1996 ◽  
Vol 38 (3-4) ◽  
pp. 299-304 ◽  
Author(s):  
Michael E. Houlihan ◽  
Walter S. Pritchard ◽  
John H. Robinson

1988 ◽  
Vol 21 (1) ◽  
pp. 139-141 ◽  
Author(s):  
Kemal S. Türker ◽  
Timothy S. Miles ◽  
Hoanh T. Le

2000 ◽  
Vol 11 (2) ◽  
pp. 167-171 ◽  
Author(s):  
John J. McDonald ◽  
Lawrence M. Ward

It is well known that sensory events of one modality can influence judgments of sensory events in other modalities. For example, people respond more quickly to a target appearing at the location of a previous cue than to a target appearing at another location, even when the two stimuli are from different modalities. Such cross-modal interactions suggest that involuntary spatial attention mechanisms are not entirely modality-specific. In the present study, event-related brain potentials (ERPs) were recorded to elucidate the neural basis and timing of involuntary, cross-modal spatial attention effects. We found that orienting spatial attention to an irrelevant sound modulates the ERP to a subsequent visual target over modality-specific, extrastriate visual cortex, but only after the initial stages of sensory processing are completed. These findings are consistent with the proposal that involuntary spatial attention orienting to auditory and visual stimuli involves shared, or at least linked, brain mechanisms.


2015 ◽  
Vol 27 (5) ◽  
pp. 945-958 ◽  
Author(s):  
Laura Dugué ◽  
Philippe Marque ◽  
Rufin VanRullen

Visual search—finding a target element among similar-looking distractors—is one of the prevailing experimental methods to study attention. Current theories of visual search postulate an early stage of feature extraction interacting with an attentional process that selects candidate targets for further analysis; in difficult search situations, this selection is iterated until the target is found. Although such theories predict an intrinsic periodicity in the neuronal substrates of attentional search, this prediction has not been extensively tested in human electrophysiology. Here, using EEG and TMS, we study attentional periodicities in visual search. EEG measurements indicated that successful and unsuccessful search trials were associated with different amounts of poststimulus oscillatory amplitude and phase-locking at ∼6 Hz and opposite prestimulus oscillatory phase at ∼6 Hz. A trial-by-trial comparison of pre- and poststimulus ∼6 Hz EEG phases revealed that the functional interplay between prestimulus brain states, poststimulus oscillations, and successful search performance was mediated by a partial phase reset of ongoing oscillations. Independently, TMS applied over occipital cortex at various intervals after search onset demonstrated a periodic pattern of interference at ∼6 Hz. The converging evidence from independent TMS and EEG measurements demonstrates that attentional search is modulated periodically by brain oscillations. This periodicity is naturally compatible with a sequential exploration by attention, although a parallel but rhythmically modulated attention spotlight cannot be entirely ruled out.


2020 ◽  
Author(s):  
Zoltan Derzsi

To detect a weak signal in human electrophysiology that is a response of a periodic external stimulus, spectral evaluation is mostly used. The recorded signal’s amplitude and phase noise components of the signal are statistically independent from each other, but both of them are decreasing the signal-to-noise ratio, which results in a lower probability of successful signal detection. Provided that the phase information of the stimuli is preserved, we found that a way to reject an additional phase noise component, which improves the detection probability considerably, by analysing the signal’s phase coherency instead of its spectrum.


2019 ◽  
Author(s):  
Alain de Cheveigné

AbstractPower line artifacts are the bane of animal and human electrophysiology. A number of methods are available to help attenuate or eliminate them, but each has its own set of drawbacks. In this brief note I present a simple method that combines the advantages of spectral and spatial filtering, while minimizing their downsides. This method is applicable to multichannel data such as electroencephalography (EEG), magnetoencephalography (MEG), or multichannel local field potentials (LFP). I briefly review past methods, pointing out their drawbacks, describe the new method, and evaluate the outcome using synthetic and real data.


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