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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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“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.”
BackgroundKononowicz, T. W., van Rijn, H., & Meck, W. H. (2018) · Wiley eBooks · doi:10.1002/9781119170174.epcn114 · Cited by 767
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).”
BackgroundA common mechanism underlies changes of mind about decisions and confidence
van den Berg, R., Anandalingam, K., Zylberberg, A., Kiani, R., Shadlen, M. N., & Wolpert, D. M. (2016) · eLife · doi:10.7554/elife.12192 · Cited by 270
“…1998) explains the tradeoff between speed and accuracy, and many of the essential steps have correlates in neurophysiology (Romo et al., 2002; Heekeren et al., 2004; Ploran et al., 2007; Heitz and Schall, 2012; White et al., 2012; Kelly and O’Connell, 2013; Hanks et al., 2014; Hanks et al., 2015).”
BackgroundPolanía, R., Krajbich, I. M., Grueschow, M., & Ruff, C. C. (2014) · Neuron · doi:10.1016/j.neuron.2014.03.014 · Cited by 285
“However, recent EEG investigations (Kelly and O’Connell, 2013; O’Connell et al., 2012) of PDM showed that it is possible to simultaneously capture parallel decision formation and motor preparatory signals in parietal and motor regions, respectively.”
Verleger, R. (2020) · Psychophysiology · doi:10.1111/psyp.13542 · Cited by 207
“Furthermore, the time-course of P3b's increase from onset to peak closely resembled random-walk processes leading to decisions (Kelly & O'Connell, 2013; O'Connell, Dockree, & Kelly, 2012; Twomey, Murphy, Kelly, & O'Connell, 2015).”
BackgroundPisauro, M. A., Fouragnan, E. F., Retzler, C., & Philiastides, M. G. (2017) · Nature Communications · doi:10.1038/ncomms15808 · Cited by 229
“…electroencephalography (EEG) studies in humans, which report that electrical activity measured at the scalp builds up gradually in time during perceptual decisions 5–9 , and from fMRI studies, which propose that this activity is generated in sensorimotor and higher-level prefrontal areas 10–15 .”
Bridging Neural and Computational Viewpoints on Perceptual Decision-Making
O’Connell, R. G., Shadlen, M. N., Wong‐Lin, K., & Kelly, S. P. (2018) · Trends in Neurosciences · doi:10.1016/j.tins.2018.06.005 · Cited by 217
“The latter supramodal, motor-independent signal, termed the ‘centroparietal positivity’ (CPP), was also found to precede evidenceselective motor preparation signals [58], further suggesting that it operates at a level of processing intermediating between sensory encoding and motor preparation.”
Self-citationPupil-Linked Arousal Determines Variability in Perceptual Decision Making
Murphy, P. R., Vandekerckhove, J., & Nieuwenhuis, S. (2014) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003854 · Cited by 205
“While recent research has worked to characterize the neural correlates of trial-to-trial variability in decision making [8–14], very little is known about the neuro-”
BackgroundSpontaneous Brain Oscillations and Perceptual Decision-Making
Samaha, J., Iemi, L., Haegens, S., & Busch, N. A. (2020) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2020.05.004 · Cited by 209
Neural evidence accumulation persists after choice to inform metacognitive judgments
Murphy, P. R., Robertson, I. H., Harty, S., & O'Connell, R. G. (2015) · eLife · doi:10.7554/elife.11946 · Cited by 170
Self-citationRespiration aligns perception with neural excitability
Kluger, D. S., Balestrieri, E., Busch, N. A., & Groß, J. (2021) · eLife · doi:10.7554/elife.70907 · Cited by 178
Decisions are expedited through multiple neural adjustments spanning the sensorimotor hierarchy
Steinemann, N. A., O’Connell, R. G., & Kelly, S. P. (2018) · Nature Communications · doi:10.1038/s41467-018-06117-0 · Cited by 166
Self-citationWhite, C. N., Servant, M., & Logan, G. D. (2017) · Psychonomic Bulletin & Review · doi:10.3758/s13423-017-1271-2 · Cited by 162
“…individual differences in cognitive function have been used to probe neural activation in studies using methodologies like electroencephalography (Kelly & O’Connell, 2013; Philiastides, Heekeren, & Sajda, 2014; Servant, White, Montagnini, & Burle, 2016), electromyography (Servant, White,…”
Tagliabue, C. F., Veniero, D., Benwell, C., Cecere, R., Savazzi, S., & Thut, G. (2019) · Scientific Reports · doi:10.1038/s41598-019-41024-4 · Cited by 150
“2c) [repeated-measures ANOVA: F(2,20) = 35.”
Gherman, S., & Philiastides, M. G. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.11.036 · Cited by 149
“3B), consistent with a process of evidence accumulation (Kelly and O'Connell, 2013; Philiastides et al., in press).”
BackgroundCavanagh, J. F. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.02.007 · Cited by 154
“To imperative cues, P3b-like activities correlate with decision confidence (Fischer and Ullsperger, 2013), and peak at the moment of response execution, thus co-varying with the objective marker of decision execution, the RT (O'Connell et al., 2012; Kelly and O'Connell, 2013).”
BackgroundVerleger, R., Metzner, M. F., Ouyang, G., Śmigasiewicz, K., & Zhou, C. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.06.036 · Cited by 144
“…" response set selections " (Hillyard and Kutas, 1983), i.e., about what to do with the current stimulus (cf. Falkenstein et al., 1994; Hohnsbein et al., 1991; Rösler et al., 1985; Squires et al., 1973; more recently Kelly and O'Connell, 2013; Nieuwenhuis et al., 2005; O'Connell et al., 2012).”
Neurocomputational mechanisms of prior-informed perceptual decision-making in humans
Kelly, S. P., Corbett, E. A., & O’Connell, R. G. (2020) · Nature Human Behaviour · doi:10.1038/s41562-020-00967-9 · Cited by 152
Self-citationKelly, S. P., & O’Connell, R. G. (2014) · Journal of Physiology-Paris · doi:10.1016/j.jphysparis.2014.08.003 · Cited by 142
“In two recent studies, we used simple paradigm innovations to enable parallel tracking of freely-evolving sensory evidence, decision variable and motor preparation signals (O’Connell et al., 2012a,b; Kelly and O’Connell, 2013).”
InfluentialSelf-citationSpatiotemporal brain mapping during preparation, perception, and action
Russo, F. D., Lucci, G., Sulpizio, V., Berchicci, M., Spinelli, D., Pitzalis, S., & Galati, G. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.11.036 · Cited by 120
“This aIPs activitymay also be associated with the central–parietal positive potential that has been identified as a supramodal decision signal (O'Connell et al., 2012; Kelly and O'Connell, 2013).”
Neurophysiology of Human Perceptual Decision-Making
O’Connell, R. G., & Kelly, S. P. (2021) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-092019-100200 · Cited by 130
Self-citationLoughnane, G. M., Newman, D. P., Bellgrove, M. A., Lalor, E. C., Kelly, S. P., & O’Connell, R. G. (2016) · Current Biology · doi:10.1016/j.cub.2015.12.049 · Cited by 113
“In experiment 1, participants performedavariant of the random dotmotion task (RDM; [6–8]) in which theymonitored two peripheral dot kinematograms for intermittent periods of coherent motion occurring equally likely in either patch at unpredictable times (Figure 1A).”
InfluentialSelf-citationA computational analysis of the neural bases of Bayesian inference
Kolossa, A., Kopp, B., & Fingscheidt, T. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.11.007 · Cited by 123
Human Scalp Potentials Reflect a Mixture of Decision-Related Signals during Perceptual Choices
Philiastides, M. G., Heekeren, H. R., & Sajda, P. (2014) · Journal of Neuroscience · doi:10.1523/jneurosci.3012-14.2014 · Cited by 118
“More specifically, in the study by Kelly and O’Connell (2013), the direction discrimination task was designed such that the dynamic motion stimulus was continuously active, whereby long periods of pure noise were interleaved with periods of partially coherent motion based on which choice was made.”
BackgroundResultInfluentialHuman VMPFC encodes early signatures of confidence in perceptual decisions
Gherman, S., & Philiastides, M. G. (2018) · eLife · doi:10.7554/elife.38293 · Cited by 107
Iemi, L., Gwilliams, L., Samaha, J., Auksztulewicz, R., Cycowicz, Y. M., King, J.-R., Nikulin, V. V., Thesen, T., Doyle, W., Devinsky, O., et al. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118746 · Cited by 117
Twomey, D. M., Kelly, S. P., & O’Connell, R. G. (2016) · Journal of Neuroscience · doi:10.1523/jneurosci.4162-15.2016 · Cited by 113
“We used a discrete-trial version of a flickered motion discrimination task modeled on the classic random dot motion task (Newsome et al., 1989; Britten et al., 1992; Kelly and O’Connell, 2013) in which participants judged the direction of motion in a patch of moving dots (Fig.”
BackgroundMethodResultInfluentialSelf-citationExpectations Do Not Alter Early Sensory Processing during Perceptual Decision-Making
Rungratsameetaweemana, N., Itthipuripat, S., Salazar, A., & Serences, J. T. (2018) · Journal of Neuroscience · doi:10.1523/jneurosci.3638-17.2018 · Cited by 121
“The centro-parietal positive potential (CPP) The CPP recorded from the CPz electrode is an established ERP marker thought to track a running sum of sensory evidence over time (Squires et al., 1973, 1975a,b; O’Connell et al., 2012; Kelly and O’Connell, 2013; Itthipuripat et al., 2015; Loughnane et al., 2016; Twomey et…”
MethodStatistical context dictates the relationship between feedback-related EEG signals and learning
Nassar, M. R., Bruckner, R., & Frank, M. J. (2019) · eLife · doi:10.7554/elife.46975 · Cited by 101
“particular decision or course of action (43,44), or anticipate the need to inhibit 635 responding (41,45), as both of these theories could be framed in terms of the 636 latent states above (e.”
BackgroundThalamocortical excitability modulation guides human perception under uncertainty
Kosciessa, J. Q., Lindenberger, U., & Garrett, D. D. (2021) · Nature Communications · doi:10.1038/s41467-021-22511-7 · Cited by 102
New insights into old waves. Matching stimulus- and response-locked ERPs on the same time-window
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Decoding motion direction using the topography of sustained ERPs and alpha oscillations
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“To this end, we computed the mean, slope and linear projection (de Gee et al., 2014; Kloosterman et al., 2015) over a 400 ms time window around the peak of the derivative of the pupil IRF (636 ms using the canonical IRF).”
BackgroundMethodSelf-citationDissociating sensory from decision processes in human perceptual decision making
Mostert, P., Kok, P., & de Lange, F. P. (2015) · Scientific Reports · doi:10.1038/srep18253 · Cited by 95
Understanding neural signals of post-decisional performance monitoring: An integrative review
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“This positivity showed a strong resemblance to the traditional P300 and might revitalize the idea of the P300 reflecting a decision making process (Hillyard and Kutas, 1983; Nieuwenhuis et al., 2005; O’Connell et al., 2012b; Kelly and O’Connell, 2013).”
BackgroundNeural Mechanisms of Human Perceptual Choice Under Focused and Divided Attention
Wyart, V., Myers, N. E., & Summerfield, C. (2015) · Journal of Neuroscience · doi:10.1523/jneurosci.3276-14.2015 · Cited by 85
“44), which is consistent with the idea of a gradual transition from spatially selective sensory representations to a supramodal, associative decision code (O’Connell et al., 2012; Kelly and O’Connell, 2013).”
BackgroundResultInfluentialDoes the P300 reflect conscious perception or its consequences?
Rutiku, R., Martin, M., Bachmann, T., & Aru, J. (2015) · Neuroscience · doi:10.1016/j.neuroscience.2015.04.029 · Cited by 87
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Selective overweighting of larger magnitudes during noisy numerical comparison
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A P300-Based Brain-Computer Interface for Improving Attention
Arvaneh, M., Robertson, I. H., & Ward, T. E. (2019) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2018.00524 · Cited by 83
Rats adopt the optimal timescale for evidence integration in a dynamic environment
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Repetition enhancement and memory effects for duration
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“, 2013) and late positive deflection (Itthipuripat et al., 2014; Kelly and O'Connell, 2013; Hilyard et al., 1971).”
BackgroundMethodNeural Mechanisms That Make Perceptual Decisions Flexible
Okazawa, G., & Kiani, R. (2022) · Annual Review of Physiology · doi:10.1146/annurev-physiol-031722-024731 · Cited by 83
“Although this does not deny domain general mechanisms for decision making (31, 77, 78, 144), the prevalence of neural signals encoding the decision variable ( Figure 1 c ) indicates that many brain structures form an interconnected network for decision making.”
BackgroundThe Role of Speed in ADHD-Related Working Memory Deficits
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“More attentive predecision states, as indexed by ERP correlates, have been linked to increases in the rate of evidence accumulation (Kelly & O’Connell, 2013), the guidance of visual attention toward relevant stimuli increases drift rate (Ho, Brown, Abuyo, Ku, & Serences, 2012; Smith, Ratcliff, &…”
BackgroundSubjective visual awareness emerges prior to P3
Koivisto, M., Salminen‐Vaparanta, N., Grassini, S., & Revonsuo, A. (2016) · European Journal of Neuroscience · doi:10.1111/ejn.13264 · Cited by 79
The role of cortical beta oscillations in time estimation
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“3D for abbreviations. r 3275 r similar to their proposed role in the accumulation of evidence for sensory processing for b [Donner et al., 2009; Haegens et al., 2011b] as well as for a [Kelly and O’Connell, 2013] bands.”
BackgroundInfluentialServant, M., White, C. N., Montagnini, A., & Burle, B. (2016) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_00989 · Cited by 82
“Recently, Kelly and O ’ Connell (2013) have argued that the lateralized readiness potential (LRP 1 ), an EEG marker of unimanual motor preparation, reflects key properties of the theoretical decision variable.”
BackgroundInfluentialVerleger, R., Baur, N., Metzner, M. F., & Śmigasiewicz, K. (2014) · Psychophysiology · doi:10.1111/psyp.12262 · Cited by 70
Beyond decision! Motor contribution to speed–accuracy trade-off in decision-making
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Value-based attentional capture influences context-dependent decision-making
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Cognitive Models in Intelligence Research: Advantages and Recommendations for Their Application
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“In particular, the latency of the N2, which is a neural correlate of visual encoding time, has been shown to be associated with the non-decision time parameter of the diffusion model [109], and the buildup rate of a positive centroparietral positive potential has been suggested to directly reflect the rate of evidence…”
BackgroundBenwell, C., Keitel, C., Harvey, M., Groß, J., & Thut, G. (2017) · European Journal of Neuroscience · doi:10.1111/ejn.13688 · Cited by 61
A Bayesian Perspective on Accumulation in the Magnitude System
Martin, B., Wiener, M., & van Wassenhove, V. (2017) · Scientific Reports · doi:10.1038/s41598-017-00680-0 · Cited by 58
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“When, on the other hand, 3b is assumed to reflect decision processes (O’Connell, Dockree, Kelly, 2012; Kelly & O’Connell, 2013) then, if anything, P3b is xpected to increase when difficult decisions have to be made.”
BackgroundP300 amplitude variations, prior probabilities, and likelihoods: a Bayesian ERP study
Kopp, B., Seer, C., Lange, F., Kluytmans, A., Kolossa, A., Fingscheidt, T., & Hoijtink, H. (2016) · Cognitive, Affective, & Behavioral Neuroscience · doi:10.3758/s13415-016-0442-3 · Cited by 60
“Although the underlying neural mechanisms are less understood, a similar framework explains a variety of P3b-like phenomena that are related to perceptual decisions in humans (Kelly & O’Connell, 2013; O’Connell, Dockree, & Kelly, 2012).”
BackgroundSaville, C. W. N., Feige, B., Kluckert, C., Bender, S., Biscaldi, M., Berger, A., Fleischhaker, C., Hennighausen, K., & Klein, C. (2014) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.12348 · Cited by 58
Precision and neuronal dynamics in the human posterior parietal cortex during evidence accumulation
FitzGerald, T. H. B., Moran, R., Friston, K. J., & Dolan, R. J. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.12.015 · Cited by 59
“Recent studies of perceptual decision-making have found evidence for evolving decision signals in centro-parietal EEG electrodes (O'Connell et al., 2012; Kelly and O'Connell, 2013) and MEG sensors (de Lange et al.”
Verleger, R., Grauhan, N., & Śmigasiewicz, K. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.08.049 · Cited by 62
van Vugt, M. K., Beulen, M. A., & Taatgen, N. (2019) · Brain Research · doi:10.1016/j.brainres.2019.03.008 · Cited by 57
Dully, J., McGovern, D. P., & O’Connell, R. G. (2018) · Behavioural Brain Research · doi:10.1016/j.bbr.2018.02.001 · Cited by 62
Self-citationEvent Related Potentials Index Rapid Recalibration to Audiovisual Temporal Asynchrony
Simon, D. M., Noel, J., & Wallace, M. T. (2017) · Frontiers in Integrative Neuroscience · doi:10.3389/fnint.2017.00008 · Cited by 57
“…investigations of rapid temporal recalibration for audiovisual stimuli (Van der Burg et al., 2013; Noel et al., 2016a) and strongly indicate that the temporal structure of audiovisual stimuli on the preceding trial (i.e., t−1) impacts perceptual processing of the current trial (i.e., t).”
BackgroundRevisiting the relationship between the P3b and working memory updating
Rac-Lubashevsky, R., & Kessler, Y. (2019) · Biological Psychology · doi:10.1016/j.biopsycho.2019.107769 · Cited by 60
Scale (in)variance in a unified diffusion model of decision making and timing.
Simen, P., Vlasov, K. Y., & Papadakis, S. (2015) · Psychological Review · doi:10.1037/rev0000014 · Cited by 54
The Effects of Methylphenidate on the Neural Signatures of Sustained Attention
Dockree, P. M., Barnes, J. J., Matthews, N. L., Dean, A. J., Abe, R., Nandam, L. S., Kelly, S. P., Bellgrove, M. A., & O’Connell, R. G. (2017) · Biological Psychiatry · doi:10.1016/j.biopsych.2017.04.016 · Cited by 52
Self-citationMcGovern, D. P., Hayes, A., Kelly, S. P., & O’Connell, R. G. (2018) · Nature Human Behaviour · doi:10.1038/s41562-018-0465-6 · Cited by 54
Self-citationThe interplay between multisensory integration and perceptual decision making
Mercier, M. R., & Cappe, C. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.116970 · Cited by 52
Seow, T. X. F., Benoit, E., Dempsey, C., Jennings, M., Maxwell, A., O’Connell, R. G., & Gillan, C. M. (2021) · Journal of Neuroscience · doi:10.1523/jneurosci.0031-21.2021 · Cited by 52
“We also examined the build-up rate of the responselocked P300 as a measure of how quickly evidence for the decision was accumulated (Kelly and O’Connell, 2013).”
MethodSelf-citationvan Vugt, M. K., Simen, P., Nystrom, L. E., Holmes, P. J., & Cohen, J. D. (2014) · PLoS ONE · doi:10.1371/journal.pone.0090943 · Cited by 53
“Our proposal is similar to that of Kelly & O’Connell [49], who recently showed that the LRP occurred at a later point in time than a putative correlate of evidence accumulation (in their account, the centroparietal positive potential).”
ResultDecision ambiguity is mediated by a late positive potential originating from cingulate cortex
Sun, S., Zhen, S., Fu, Z., Wu, D.-A. J., Shimojo, S., Adolphs, R., Yu, R., & Wang, S. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.06.003 · Cited by 52
“Furthermore, the LPP is not only associated with accumulating sensory information but also determining choices (O'Connell et al., 2012; Kelly and O'Connell, 2013; Murphy et al., 2015), two aspects that we aimed to further tease apart in the present study with a series of control experiments.”
Verleger, R., & Śmigasiewicz, K. (2016) · Advances in Cognitive Psychology · doi:10.5709/acp-0189-9 · Cited by 50
“More recently, P3 has been considered to directly reflect the decision process rather than some post-decision adaptation (Kelly & O’Connell, 2013; O’Connell, Dockree, & Kelly, 2012).”
BackgroundDynamic Interplay of Value and Sensory Information in High-Speed Decision Making
Afacan-Seref, K., Steinemann, N. A., Blangero, A., & Kelly, S. P. (2018) · Current Biology · doi:10.1016/j.cub.2018.01.071 · Cited by 56
“reflects differential decision-variable dynamics [10, 26, 27].”
Self-citationLeib, R., Karniel, A., & Nisky, I. (2015) · Journal of Neurophysiology · doi:10.1152/jn.00229.2014 · Cited by 46
Perceptual difficulty modulates the direction of information flow in familiar face recognition
Karimi-Rouzbahani, H., Ramezani, F., Woolgar, A., Rich, A. N., & Ghodrati, M. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.117896 · Cited by 49
An integrated theory of deciding and acting.
Servant, M., Logan, G. D., Gajdos, T., & Evans, N. J. (2021) · Journal of Experimental Psychology General · doi:10.1037/xge0001063 · Cited by 53
A rise-to-threshold process for a relative-value decision
Vijayan, V., Wang, F., Wang, K., Chakravorty, A., Adachi, A., Akhlaghpour, H., Dickson, B. J., & Maimon, G. (2023) · Nature · doi:10.1038/s41586-023-06271-6 · Cited by 49
Perceptual learning alters post-sensory processing in human decision-making
Diaz, J. A., Queirazza, F., & Philiastides, M. G. (2017) · Nature Human Behaviour · doi:10.1038/s41562-016-0035 · Cited by 46
Maksimenko, V., Kuc, A. K., Frolov, N. S., Khramova, M. V., Pisarchik, A. N., & Hramov, A. E. (2020) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2020.00095 · Cited by 49
Predictions of Visual Content across Eye Movements and Their Modulation by Inferred Information
Ehinger, B., Peter König, B., & Ossandón, J. (2015) · Journal of Neuroscience · doi:10.1523/jneurosci.5114-14.2015 · Cited by 43
“The second interpretation follows the results of EEG experiments about perceptual decision-making (O’Connell et al., 2012; Wyart et al., 2012; Kelly and O’Connell, 2013; Cheadle et al., 2014), in which a similar posterior topography and time course to the one observed here is seen for the updating…”
BackgroundInfluentialRelating accumulator model parameters and neural dynamics
Purcell, B. A., & Palmeri, T. J. (2016) · Journal of Mathematical Psychology · doi:10.1016/j.jmp.2016.07.001 · Cited by 42
Neurophysiological Correlates of Attentional Fluctuation in Attention-Deficit/Hyperactivity Disorder
Cheung, C. H. M., McLoughlin, G., Brandeis, D., Banaschewski, T., Asherson, P. J., & Kuntsi, J. (2017) · Brain Topography · doi:10.1007/s10548-017-0554-2 · Cited by 47
“…condition), we conducted separate analyses with a later interval of the P3 (between 450 and 600 ms at Pz, Figure S1), along with a response-aligned ERP measured as the area amplitude measures (μV*ms) at Pz at the −250 to −100 ms interval before the response onset (Kelly and O’Connell 2013).”
BackgroundMethodResultInfluentialDevine, C. A., Gaffney, C., Loughnane, G. M., Kelly, S. P., & O’Connell, R. G. (2019) · eLife · doi:10.7554/elife.48526 · Cited by 46
Self-citationTwo different mechanisms support selective attention at different phases of training
Itthipuripat, S., Cha, K., Byers, A., & Serences, J. T. (2017) · PLoS Biology · doi:10.1371/journal.pbio.2001724 · Cited by 42
Evidence accumulation as a model for lexical selection
Anders, R., Riès, S., van Maanen, L., & Alario, F. ‐. (2015) · Cognitive Psychology · doi:10.1016/j.cogpsych.2015.07.002 · Cited by 48
Peripheral visual perception during natural overground dual-task walking in older and younger adults
Protzak, J., Wiczorek, R., & Gramann, K. (2020) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2020.10.009 · Cited by 42
Brosnan, M. B., Sabaroedin, K., Silk, T. J., Genc, S., Newman, D. P., Loughnane, G. M., Fornito, A., O’Connell, R. G., & Bellgrove, M. A. (2020) · Nature Human Behaviour · doi:10.1038/s41562-020-0863-4 · Cited by 42
Self-citationTemporal Expectation Hastens Decision Onset But Does Not Affect Evidence Quality
van den Brink, R. L., Murphy, P. R., Desender, K., de Ru, N., & Nieuwenhuis, S. (2020) · Journal of Neuroscience · doi:10.1523/jneurosci.1103-20.2020 · Cited by 41
Prior probabilities modulate cortical surprise responses: A study of event-related potentials
Seer, C., Lange, F., Boos, M., Dengler, R., & Kopp, B. (2016) · Brain and Cognition · doi:10.1016/j.bandc.2016.04.011 · Cited by 40
Evidence and Urgency Related EEG Signals during Dynamic Decision-Making in Humans
Yau, Y. H. C., Hinault, T., Taylor, M., Cisek, P., Fellows, L. K., & Dagher, A. (2021) · Journal of Neuroscience · doi:10.1523/jneurosci.2551-20.2021 · Cited by 37
Anders, R., Riès, S., van Maanen, L., & Alario, F. ‐. (2017) · Cognitive Neuropsychology · doi:10.1080/02643294.2017.1282447 · Cited by 43
“…Donkin & Van Maanen, 2014; Mulder et al., 2013; Ratcliff, Gomez, & McKoon, 2004; Ratcliff & McKoon, 2008; Ratcliff, Van Zandt, & McKoon, 1999), as well as neuroscience research (e.g. Dehaene, 2008; Kelly & O’Connell, 2013; Mulder, Van Maanen, & Forstmann, 2014; O’Connell, Dockree, & Kelly, 2012).”
Newman, D. P., Loughnane, G. M., Kelly, S. P., O’Connell, R. G., & Bellgrove, M. A. (2017) · Journal of Neuroscience · doi:10.1523/jneurosci.3512-16.2017 · Cited by 37
“, 2016); those that support evidence accumulation and are measured via the centroparietal positivity (CPP), whose build-up rate predicts reaction time (RT) and scales with sensory evidence strength independent of sensory or motor demands (O’Connell et al., 2012; Kelly and O’Connell, 2013); and those that enable limb-s…”
BackgroundMethodResultInfluentialSelf-citationPersistent deterioration of visuospatial performance in spaceflight
Takács, E., Barkaszi, I., Czigler, I., Pató, L. G., Altbäcker, A., McIntyre, J., Cheron, G. A., & Balázs, L. (2021) · Scientific Reports · doi:10.1038/s41598-021-88938-6 · Cited by 39
Dou, W., Arango, L. J. M., Castaneda, O. G., Arellano, L., Mcintyre, E., Yballa, C., & Samaha, J. (2024) · Psychological Science · doi:10.1177/09567976241246561 · Cited by 42
“We focused on an event-related potential (ERP) component termed the central parietal positivity (CPP), which has previously been found to encode the (unsigned) accumulated evidence for a perceptual decision (Kelly et al., 2021; Kelly & O’Connell, 2013; O’Connell et al., 2012, 2018).”
Cortical Components of Reaction-Time during Perceptual Decisions in Humans
Dmochowski, J., & Norcia, A. M. (2015) · PLoS ONE · doi:10.1371/journal.pone.0143339 · Cited by 39
“To compute the centroparietal positivity (CPP) [12, 24] and lateralized readiness potential (LRP) [25–27], earlier decision-making components which were contrasted with the RCs, we followed the procedure of [24].”
BackgroundMethodInfluentialSchubert, A., Nunez, M. D., Hagemann, D., & Vandekerckhove, J. (2018) · Computational Brain & Behavior · doi:10.1007/s42113-018-0021-5 · Cited by 39
“O’Connell et al. (2012) and Kelly and O’Connell (2013) even suggested that the buildup rate of this positive centroparietral positive potential may directly reflect the rate of evidence accumulation on a neural level.”
BackgroundResultManning, C., Hassall, C. D., Hunt, L. T., Norcia, A. M., Wagenmakers, E., Snowling, M. J., Scerif, G., & Evans, N. J. (2021) · Journal of Neuroscience · doi:10.1523/jneurosci.1232-21.2021 · Cited by 36
“Specifically, we used a data-driven component decomposition technique to find a centro-parietal component previously linked to decision-making (O ’ Connell et al., 2012; Kelly and O ’ Connell, 2013; Manning et al., 2021a), and then “ unmixed ” overlapping stimulus-and response-locked activity.”
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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