ReviewCognitive neurodynamics2020
Characterizing the brain's dynamical response from scalp-level neural electrical signals: a review of methodology development.
Review in Cognitive neurodynamics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Intuition criticizes self, analysis protects mother: evidence from an ERPs study.Cognitive, affective & behavioral neuroscience · 2026Article
- Assessing the influence of latency variability on EEG classifiers - a case study of face repetition priming.Cognitive neurodynamics · 2024Article
- Adiposity influences intraindividual variability in behavioral and neuroelectric indices of attentional inhibition.Psychophysiology · 2024Article
- Neural representations of statistical and rule-based predictions in Gilles de la Tourette syndrome.Human brain mapping · 2024Article
- Exploiting Information in Event-Related Brain Potentials from Average Temporal Waveform, Time-Frequency Representation, and Phase Dynamics.Bioengineering (Basel, Switzerland) · 2023Article
- Modality-specific and modality-independent neural representations work in concert in predictive processes during sequence learning.Cerebral cortex (New York, N.Y. : 1991) · 2023Article
- Investigation of global brain dynamics depending on emotion regulation strategies indicated by graph theoretical brain network measures at system level.Cognitive neurodynamics · 2023Article
- On the relative importance of attention and response selection processes for multi-component behavior - Evidence from EEG-based deep learning.Neuroimage. Reports · 2022Article
- A survey of brain network analysis by electroencephalographic signals.Cognitive neurodynamics · 2022Article
- Multi-level decoding of task sets in neurophysiological data during cognitive flexibility.iScience · 2021Article
- Neurophysiological and functional neuroanatomical coding of statistical and deterministic rule information during sequence learning.Human brain mapping · 2021Article
- Neurophysiological mechanisms underlying motor feature binding processes and representations.Human brain mapping · 2021Article
- Pushing to the Limits: What Processes during Cognitive Control are Enhanced by Reaction-Time Feedback?Cerebral cortex communications · 2021Article
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2 authors.
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Abstract
The brain displays dynamical system behaviors at various levels that are functionally and cognitively relevant. Ample researches have examined how the dynamical properties of brain activity reflect the neural cognitive working mechanisms. A prevalent approach in this field is to extract the trial-averaged brain electrophysiological signals as a representation of the dynamical response of the complex neural system to external stimuli. However, the responses are intrinsically variable in latency from trial to trial. The variability compromises the accuracy of the detected dynamical response pattern based on trial-averaged approach, which may mislead subsequent modelling works. More accurate characterization of the brain's dynamical response incorporating single trial variability information is of profound significance in deepening our understanding of neural cognitive dynamics and brain's working principles. Various methods have been attempted to address the trial-to-trial asynchrony issue in order to achieve an improved representation of the dynamical response. We review the latest development of methodology in this area and the contribution of latency variability-based decomposition and reconstruction of dynamical response to neural cognitive researches.
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