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Internal and External Influences on the Rate of Sensory Evidence Accumulation in the Human Brain
Open accessAbstract
We frequently need to make timely decisions based on sensory evidence that is weak, ambiguous, or noisy resulting from conditions in the external environment (e.g., a cluttered visual scene) or within the brain itself (e.g., inattention, neural noise). Here we examine how externally and internally driven variations in the quality of sensory evidence affect the build-to-threshold dynamics of a supramodal “decision variable” signal and, hence, the timing and accuracy of decision reports in humans. Observers performed a continuous-monitoring version of the prototypical two-alternative dot-motion discrimination task, which is known to strongly benefit from sequential sampling and temporal accumulation of evidence. A centroparietal positive potential (CPP), which we previously established as a supramodal decision signal based on its invariance to motor or sensory parameters, exhibited two key identifying properties associated with the “decision variable” long described in sequential sampling models: (1) its buildup rate systematically scaled with sensory evidence strength across four levels of motion coherence, consistent with temporal integration; and (2) its amplitude reached a stereotyped level at the moment of perceptual report executions, consistent with a boundary-crossing stopping criterion. The buildup rate of the CPP also strongly predicted reaction time within coherence levels (i.e., independent of physical evidence strength), and this endogenous variation was linked with attentional fluctuations indexed by the level of parieto-occipital α-band activity preceding target onset. In tandem with the CPP, build-to-threshold dynamics were also observed in an effector-selective motor preparation signal; however, the buildup of this motor-specific process significantly lagged that of the supramodal process.
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“This suggests that the P3 may encode motivationally significant events, which, in the present study, were the saliently colored/ethnic Black hands during SRC processing, potentially contributing to a dynamic decision process of linking perception to action31,42–45”
From Event-related potentials of automatic imitation are modulated by ethnicity during stimulus processing, but not during motor execution (2018) · cites this paper as [43]
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“It has been suggested that the role of the P3 component lies in bridging stimulus perception and response execution31,44 in a dynamically evolving decision process, linking sensory encoding of stimulus perception to the preparation of action42,43,45, and/or response control44.”
From Event-related potentials of automatic imitation are modulated by ethnicity during stimulus processing, but not during motor execution (2018) · cites this paper as [43]
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“Which process should evolve first is uncertain because several signals resembling the CPP are thought to peak after the first-order decision (e.g., Nieuwenhuis et al., 2005; Murphy et al., 2012).”
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Diffusion decision model: Current issues and history
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“Some investigations have supported nonstationarity but have not generated the critical predictions for correct and error RT distributions ([52,87,111–113], see also [45,86,114]).”
BackgroundThe speed-accuracy tradeoff: history, physiology, methodology, and behavior
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“…supporting this claim derives from several sources, including human fMRI (Heekeren et al., 2004) and EEG (Ratcliff et al., 2009; O’Connell et al., 2012; van Vugt et al., 2012; Kelly and O’Connell, 2013), but by far the most convincing stems from single-neuron recordings in non-human primates.”
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The classic P300 encodes a build‐to‐threshold decision variable
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“All single-trial EEG data were converted to current source density (CSD; Kayser & Tenke, 2006) to counteract spatial overlap between the P300 and a functionally distinct frontocentral negativity (see Data S1 and Kelly & O’Connell, 2013).”
BackgroundMethodSelf-citationPerceptual Decision Making in Rodents, Monkeys, and Humans
Hanks, T. D., & Summerfield, C. (2017) · Neuron · doi:10.1016/j.neuron.2016.12.003 · Cited by 409
“More recently, EEG studies have identified a positive potential recorded over midline parietal electrodes that grows in a signal-dependent fashion as sensory evidence accumulates (Kelly and O’Connell, 2013; O’Connell et al., 2012).”
Background
Metadata
- Authors
- Kelly, S. P., & O'Connell, R. G.
- Affiliations
- City College of New York (US)
- ORCID
- Kelly, Simon P.
- Venue
- The Journal of Neuroscience
- Publisher
- Society for Neuroscience
- Published
- 2013-12-11
- Volume
- 33
- Issue
- 50
- Pages
- 19434-19441
- ISSN
- 0270-6474 (ISSN-L)
- 1529-2401
- PMC
- PMC6618757
- OpenAlex
- W2119976941
- Cited by
- 455
- References
- 56
- Citations by year
- 2026: 44 · 2025: 41 · 2024: 55 · 2023: 47 · 2022: 29 · 2021: 37 · 2020: 38 · 2019: 31 · 2018: 31 · 2017: 29 · 2016: 33 · 2015: 23 · 2014: 17
- FWCI
- 13.35
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Journal of Neuroscience (publishedVersion, cc-by-nc-sa)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Arrow@dit (Dublin Institute of Technology) (acceptedVersion)
- Research Repository UCD (University College Dublin) (submittedVersion, cc-by-nc-nd)
- Arrow@dit (Dublin Institute of Technology) (submittedVersion)
- Trinity's Access to Research Output (TARA) (Trinity College Dublin) (submittedVersion, cc-by-nc-sa)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Keywords
- sensory evidence accumulation, sequential sampling, decision variables, motion coherence, temporal integration, boundary crossing, reaction time, alpha activity, attentional fluctuations, motor preparation, perceptual decision making
- MeSH terms
- Adult, Brain, Brain Mapping, Decision Making, Electroencephalography, Female, Humans, Male, Models, Neurological, Reaction Time
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