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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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Prior probability cues bias sensory encoding with increasing task exposure
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InfluentialPatterns of electrical brain activation in response to socially-disputed perceptual judgments
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“…with long stimulus durations that encourage participants to accumulate evidence (e.g., random dot motion kinematogram task with >1 s of stimulation 57 ), beha-vioralandneuralmarkersofevidenceaccumulationhavealsobeenobserved duringtaskswithstimulusdurations~200 ms(asinthecurrentexperiment) and…”
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“…such decision processes are reflected over parietal areas and resemble a classic target-detection component, at 300 ms after stimulus onset (Kelly & O’Connell, 2013; Polanía, Krajbich, Grueschow, & Ruff, 2014; Twomey, Murphy, Kelly, & O’Connell, 2015; Wyart, de Gardelle, Scholl, &…”
BackgroundFeuerriegel, D., Murphy, M., Konski, A., Mepani, V., Sun, J., Hester, R., & Bode, S. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.11.22.469610 · Cited by 3
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Prior probability cues bias sensory encoding with increasing task exposurePreprint
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“Recently, such decision-related activity has been measured in humans via electroencephalography (EEG) (O’Connell et al. 2012; Kelly and O’Connell 2013, 2015; Loughnane et al. 2016).”
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“course of evidence accumulation: specifically, its amplitude builds up gradually, the build-up slope is proportional to stimulus quality, and it is observed even in the absence of overt responses (11,12,41).”
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BackgroundResultPearce, D. J., Loughnane, G. M., Chong, T. T. ‐., Demeyere, N., Mattingley, J. B., Moore, M. J., New, P. W., O’Connell, R. G., O'Neill, M., Rangelov, D., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.12.12.571233 · Cited by 1
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“In RDM, neural firing-rates in the lateral intraparietal cortex (LIP) of monkeys 47–49 and the central parietal positivity (CPP) in humans 50,51 show a similar pattern: they ramp up during evidence accrual until they reach a peak and dampen after the decision is taken.”
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A Common Neural Signal of Evidence Accumulation for Perceptual and Mnemonic DecisionsPreprint
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“…decisions, evidence accumulation begins shortly after stimulus presentation and continuously builds as long as sensory evidence is available until a decision threshold is reached (Herding et al., 2019; Kelly & O’Connell, 2013; O’Connell et al., 2012; Shadlen & Shohamy, 2016; Twomey et al., 2015).”
InfluentialDistinct brain mechanisms support trust violations, belief integration, and bias in human-AI teamsPreprint
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“…with human EEG studies showing a centroparietal decision signal whose buildup tracks evidence accumulation toward a bound (O’Connell et al., 2012; Kelly and O’Connell, 2013; Twomey et al., 2015), and with single-unit and computational studies implicating posterior parietal cortex in perceptual…”
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Mancuso, G., & Plomp, G. (2019) · PsyArXiv (OSF Preprints) · doi:10.31234/osf.io/87ksu
Fleming, S. M. (2019) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.734068306.793559296
Catecholaminergic neuromodulation and selective attention jointly shape perceptual decision-makingPreprint
Nuiten, S. A., de Gee, J. W., Zantvoord, J. B., Fahrenfort, J. J., & van Gaal, S. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.11.03.515022
“Note that we have transformed the EEG data to current source density (CSD) to sharpen the spatial sensitivity of our EEG results, which is suggested to be optimal for CPP analyses ( Kelly and O’Connell, 2013 ; non- CSD-transformed topographic maps can be observed in Figure 3—figure supplement 1 ).”
MethodAngulo, R., Cipriani, G. A., Carboni, A., & Kessel, D. (2023) · Psychological Research · doi:10.1007/s00426-023-01825-9
“…averaging, given that recent studies have proposed this method as a promising and, in some cases, more accurate alternative (e.g., Berchicci et al., 2016; Johnson et al., 2003; Kelly & O’Connell, 2013; O’Connell et al., 2012; Saville et al., 2011; Twomey et al., 2015; Verleger et al., 2005).”
O’Connell, R. G. (2023) · eLife · doi:10.7554/elife.87022.1.sa2
Self-citationNuiten, S. A., De Gee, J. W., Fahrenfort, J. J., et al. (2023) · eLife · doi:10.7554/elife.87022.1.sa0
Nuiten, S. A., De Gee, J. W., Fahrenfort, J. J., et al. (2023) · eLife · doi:10.7554/elife.87022.1.sa1
Takács, E. (2019) · Eötvös Loránd Tudományegyetem · doi:10.15476/elte.2019.193
Prior probability cues bias sensory encoding with increasing task exposurePreprint
Walsh, K. S., McGovern, D. P., Dully, J., Kelly, S. P., & O’Connell, R. G. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.07.15.549123
Self-citationOğuz, O. Ç., Aydın, B., & Ürgen, B. A. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.09.16.558064
“18 FC3 and FC4) in line with the previous literature (Kelly and O’Connell, 2013).”
ResultOğuz, O. Ç., Aydın, B., & Ürgen, B. A. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4595129
Dynamic reduction of neural uncertainty regulates perceptual decisions in a Bayes-optimal mannerPreprint
Rangelov, D., Bitzer, S., & Mattingley, J. B. (2023) · Research Square · doi:10.21203/rs.3.rs-3409042/v1
Catecholaminergic neuromodulation and selective attention jointly shape perceptual decision-makingPreprint
Nuiten, S. A., de Gee, J. W., Zantvoord, J. B., Fahrenfort, J. J., & van Gaal, S. (2023) · eLife · doi:10.7554/elife.87022.2
Prior probability cues bias sensory encoding with increasing task exposurePreprint
Walsh, K. S., McGovern, D. P., Dully, J., Kelly, S. P., & O’Connell, R. G. (2023) · eLife · doi:10.7554/elife.91135.1
Self-citationShared patterns of cognitive control behaviour and electrophysiological markers in adolescencePreprint
Wiker, T., Alnæs, D., Pedersen, M. L., Norbom, L. B., Boer, O. D., Kjelkenes, R., Voldsbekk, I., Karl, V., Bukhari, S. H., Moberget, T., et al. (2024) · doi:10.31234/osf.io/jcbde
Enhancing altruism by electrically augmenting frontoparietal gamma-band phase couplingPreprint
Hu, J., Moisa, M., & Ruff, C. C. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.04.01.587528
“…et al., 2023), and with the well-documented role of parietal regions in evidence accumulation processes underlying nonsocial (Brosnan et al., 2020; Kelly & O’Connell, 2013) and social decision making (Hu et al., 2023; Pisauro et al., 2017; Polanía et al., 2014; Yao et al., 2020; Zhong et al.,…”
BackgroundLin, Y.-S., Billington, J., Srinivasan, A. R., Leonetti, M., & Markkula, G. M. (2024) · PsyArXiv (OSF Preprints) · doi:10.31234/osf.io/h5qwa
Algısal Karar Verme Süreçleri Çerçevesinde İnsan Hareketlerini Tanıma
Urgen, B. A., & Evsen, Ş. (2024) · Ayna Klinik Psikoloji Dergisi · doi:10.31682/ayna.1344345
The interactions between spontaneous thoughts and decision-making in the context of depression
Yang, H. (2024) · University of Groningen research database (University of Groningen / Centre for Information Technology) · doi:10.33612/diss.1030953542
Age-related differences in working memory subprocesses decomposed by the reference-back paradigmPreprint
Gaál, Z. A., Nagy, B., Czigler, I., Csizmadia, P., Petró, B., & Kojouharova, P. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.07.04.602161
Posterior ERP tracks evidence accumulation for memory-based decisions.Preprint
Fukuda, K., Printzlau, F. A. B., Kang, M.-S., & Woodman, G. F. (2024) · doi:10.31234/osf.io/28j7s
Pereira‐Morales, A. J., Ramírez-Cortázar, F., Mayorga, M. F. R., & Eslava-Schmalbach, J. H. (2024) · Current Psychology · doi:10.1007/s12144-024-06799-4
“The process of accumulating sensory information is known as evidence accumulation (EA) (Kelly & O’Connell, 2013 ; Polanía et al., 2014 ).”
Re-thinking the Prediction of Construction Hazard Identification Based on Multimodal Data
Wang, J., Liu, M., Liang, M., & Liao, P. (2024) · Lecture notes in operations research · doi:10.1007/978-981-97-1949-5_128
Electrophysiological correlates of selective speech adaptation
Stekelenburg, J. J., Limpens, J., Baart, M., & Vroomen, J. (2025) · Brain and Language · doi:10.1016/j.bandl.2025.105545
“However, it is doubtful whether the late ERP effects are similar to the CPP because the CPP has its maximum at the central-parietal electrodes (Kelly & O ’ Connell, 2013; Tagliabue et al., 2019) and its neural source within the parietal and frontal lobes (Philiastides et al., 2014), whereas in our…”
Perceptual glimpses are locally accumulated and globally maintained at distinct processing levelsPreprint
Parés-Pujolràs, E., Geuzebroek, A. C., O’Connell, R. G., & Kelly, S. P. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.04.30.651428
“Occipital Alpha-band power has been linked to attention and temporal expectations (Rohenkohl & Nobre, 2011), and also to the onset (Van Den Brink et al., 2021) and build-up rate (Kelly & O’Connell, 2013) of evidence accumulation signals like the CPP.”
InfluentialSelf-citationTarget Selection Signals Causally Influence Human Perceptual Decision-Making
Pearce, D. J., Loughnane, G. M., Chong, T. T. ‐., Demeyere, N., Mattingley, J. B., Moore, M. J., New, P. W., O’Connell, R. G., O'Neill, M., Rangelov, D., et al. (2025) · Journal of Neuroscience · doi:10.1523/jneurosci.2048-24.2025
“Using a bilateral variant of the random dot motion task (Kelly and O’Connell, 2013; Loughnane et al., 2016; Newman et al., 2017; Brosnan et al., 2020) we looked at whether contralesional slowing of response time (RT) in stroke patients would be related to a disruption in the dynamics of early…”
Self-citationLee, H., Lim, J., & Lee, S. (2025) · iScience · doi:10.1016/j.isci.2025.112844 · Cited by 1
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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