human electrophysiology
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NeuroImage ◽  
2021 ◽  
pp. 118788
Author(s):  
Sepideh Sadaghiani ◽  
Matthew J Brookes ◽  
Sylvain Baillet

2021 ◽  
Author(s):  
Sepideh Sadaghiani ◽  
Matthew J Brookes ◽  
Sylvain Baillet

We present both a scientific overview and conceptual positions concerning the challenges and assets of electrophysiological measurements in the search for the nature and functions of the human connectome. We discuss how the field has been inspired by findings and approaches from functional magnetic resonance imaging (fMRI) and informed by a small number of significant multimodal empirical studies, which show that the canonical networks that are commonplace in fMRI are in fact rooted in electrophysiological processes. This review is also an opportunity to produce a brief, up-to-date critical survey of current data modalities and signal processing methods available for deriving both static and dynamic connectomes using electrophysiological data. We review hurdles that challenge the significance and impact of current electrophysiology connectome research. We then encourage the field to take a leap of faith and embrace the wealth of electrophysiological signals, despite their apparent, disconcerting complexity. Our position is that electrophysiology connectomics is poised to inform testable mechanistic models of information integration in hierarchical brain networks, constructed from observable oscillatory and aperiodic signal components and their polyrhythmic interactions.


2021 ◽  
Author(s):  
Elaine A. Corbett ◽  
L. Alexandra Martinez-Rodriguez ◽  
Cian Judd ◽  
Redmond G. O’Connell ◽  
Simon P. Kelly

AbstractPerceptual decisions are biased toward higher-value options when overall gains can be improved. When stimuli demand immediate reactions, the neurophysiological decision process dynamically evolves through distinct phases of growing anticipation, detection and discrimination, but how value biases are exerted through these phases remains unknown. Here, by parsing motor preparation dynamics in human electrophysiology, we uncovered a multiphasic pattern of countervailing biases operating in speeded decisions. Anticipatory preparation of higher-value actions began earlier, conferring a “starting point”-advantage at stimulus onset, but the delayed preparation of lower-value actions was steeper, conferring a value-opposed buildup rate bias. This, in turn, was countered by a transient deflection toward the higher value action evoked by stimulus detection. A neurally-constrained process model featuring anticipatory urgency, biased detection, and accumulation of growing stimulus-discriminating evidence, successfully captured both behavior and motor preparation dynamics. Thus, an intricate interplay of distinct biasing mechanisms serves to prioritise time-constrained perceptual decisions.


Nanoscale ◽  
2021 ◽  
Author(s):  
Quan-Liang Zhao ◽  
Zhen-Ming Wang ◽  
Jing-Hao Chen ◽  
Shi-Qi Liu ◽  
Yi-Kai Wang ◽  
...  

Highly conductive multilayer graphene nanosheet films are self-assembled for tattoo dry electrodes and strain sensors, which can be used for detecting human electrocardiogram, electromyogram, wrist pulse and breath.


Author(s):  
Yuecui Kan ◽  
Xuewei Wang ◽  
Xitong Chen ◽  
Hanxuan Zhao ◽  
Jijun Lan ◽  
...  

Cognition ◽  
2020 ◽  
Vol 205 ◽  
pp. 104462
Author(s):  
Zhicheng Lin ◽  
Chengguo Miao ◽  
Yang Zhang

2020 ◽  
Author(s):  
Peter E Clayson ◽  
Scott Baldwin ◽  
Michael J. Larson

Replication failures of influential findings across fields of science have contributed to a credibility crisis, and the sub-area of human electrophysiology has not escaped unscathed. In an effort to restore credibility, recent initiatives aim to improve methodological rigor of research via transparency and openness. We sought to determine the impact of such initiatives on open access publishing in the sub-area of human electrophysiology and the impact of open access on the attention articles received in the scholarly literature and other outlets. Data for 35,144 articles across 967 journals from the last 20 years were examined. Approximately 35% of articles were open access, and the rate of publication of open-access articles increased over time. Open access articles showed 9 to 21% more PubMed and CrossRef citations and 39% more Altmetric mentions than closed access articles. Green open access articles (i.e., author archived) did not differ from non-green open access articles with respect to citations and were related to higher Altmetric mentions. These findings demonstrate that open-access publishing is increasing in popularity in the sub-area of human electrophysiology and that open-access articles enjoy the “open access advantage” in citations similar to the larger scientific literature. The benefit of the open access advantage may motivate researchers to make their publications open access and pursue publication outlets that support it. In consideration of the direct connection between citations and journal impact factor, journal editors may improve the accessibility and impact of published articles by encouraging authors to self-archive manuscripts on preprint servers.


Author(s):  
Paul S. Muhle-Karbe ◽  
Nicholas E. Myers ◽  
Mark G. Stokes

AbstractExtensive research has examined how information is maintained in working memory (WM), but it remains unknown how WM is used to guide behaviour. We addressed this question by combining human electrophysiology with pattern analyses, cognitive modelling, and a task requiring maintenance of two WM items and priority shifts between them. This enabled us to discern neural states coding for immediately and prospectively task-relevant items, and to examine their contribution to WM-based decisions. We identified two qualitatively different states: a functionally active state encoded only immediately task-relevant items and closely tracked the quality of evidence integration on the current trial. In contrast, prospectively relevant items were encoded in a functionally latent state that did not engage with ongoing processing but tracked memory precision at longer time scales. These results delineate a hierarchy of functional states, whereby latent memories supporting general maintenance are transformed into active decision-circuits to guide flexible behaviour.


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