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Weigard A, Angstadt M, Taxali A, Heathcote A, Heitzeg MM, Sripada C. Flexible adaptation of task-positive brain networks predicts efficiency of evidence accumulation. Commun Biol 2024; 7:801. [PMID: 38956310 PMCID: PMC11220037 DOI: 10.1038/s42003-024-06506-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Accepted: 06/25/2024] [Indexed: 07/04/2024] Open
Abstract
Efficiency of evidence accumulation (EEA), an individual's ability to selectively gather goal-relevant information to make adaptive choices, is thought to be a key neurocomputational mechanism associated with cognitive functioning and transdiagnostic risk for psychopathology. However, the neural basis of individual differences in EEA is poorly understood, especially regarding the role of largescale brain network dynamics. We leverage data from 5198 participants from the Human Connectome Project and Adolescent Brain Cognitive Development Study to demonstrate a strong association between EEA and flexible adaptation to cognitive demand in the "task-positive" frontoparietal and dorsal attention networks. Notably, individuals with higher EEA displayed divergent task-positive network activation across n-back task conditions: higher activation under high cognitive demand (2-back) and lower activation under low demand (0-back). These findings suggest that brain networks' flexible adaptation to cognitive demands is a key neural underpinning of EEA.
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Affiliation(s)
| | - Mike Angstadt
- Department of Psychiatry, University of Michigan, Ann Arbor, USA
| | - Aman Taxali
- Department of Psychiatry, University of Michigan, Ann Arbor, USA
| | - Andrew Heathcote
- Department of Psychological Methods, University of Amsterdam, Amsterdam, Netherlands
| | - Mary M Heitzeg
- Department of Psychiatry, University of Michigan, Ann Arbor, USA
| | - Chandra Sripada
- Department of Psychiatry, University of Michigan, Ann Arbor, USA
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2
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Tang T, Samaha J, Peters MAK. Behavioral and neural measures of confidence using a novel auditory pitch identification task. PLoS One 2024; 19:e0299784. [PMID: 38950011 PMCID: PMC11216601 DOI: 10.1371/journal.pone.0299784] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Accepted: 02/16/2024] [Indexed: 07/03/2024] Open
Abstract
Observers can discriminate between correct versus incorrect perceptual decisions with feelings of confidence. The centro-parietal positivity build-up rate (CPP slope) has been suggested as a likely neural signature of accumulated evidence, which may guide both perceptual performance and confidence. However, CPP slope also covaries with reaction time, which also covaries with confidence in previous studies, and performance and confidence typically covary; thus, CPP slope may index signatures of perceptual performance rather than confidence per se. Moreover, perceptual metacognition-including neural correlates-has largely been studied in vision, with few exceptions. Thus, we lack understanding of domain-general neural signatures of perceptual metacognition outside vision. Here we designed a novel auditory pitch identification task and collected behavior with simultaneous 32-channel EEG in healthy adults. Participants saw two tone labels which varied in tonal distance on each trial (e.g., C vs D, C vs F), then heard a single auditory tone; they identified which label was correct and rated confidence. We found that pitch identification confidence varied with tonal distance, but performance, metacognitive sensitivity (trial-by-trial covariation of confidence with accuracy), and reaction time did not. Interestingly, however, while CPP slope covaried with performance and reaction time, it did not significantly covary with confidence. We interpret these results to mean that CPP slope is likely a signature of first-order perceptual processing and not confidence-specific signals or computations in auditory tasks. Our novel pitch identification task offers a valuable method to examine the neural correlates of auditory and domain-general perceptual confidence.
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Affiliation(s)
- Tamara Tang
- Department of Bioengineering, University of California, Riverside, Riverside, CA, United States of America
| | - Jason Samaha
- Department of Psychology, University of California, Santa Cruz, Santa Cruz, CA, United States of America
| | - Megan A. K. Peters
- Department of Bioengineering, University of California, Riverside, Riverside, CA, United States of America
- Department of Cognitive Sciences, University of California, Irvine, Irvine, CA, United States of America
- Program in Brain, Mind, & Consciousness, Canadian Institute for Advanced Research, Toronto, Canada
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3
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Ueno T, Kumano H, Uka T. Attention facilitates initiation of perceptual decision making: a combined psychophysical and electroencephalography study. Exp Brain Res 2024; 242:1721-1730. [PMID: 38816552 PMCID: PMC11208218 DOI: 10.1007/s00221-024-06862-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2024] [Accepted: 05/22/2024] [Indexed: 06/01/2024]
Abstract
Humans can selectively process information and make decisions by directing their attention to desired locations in their daily lives. Numerous studies have shown that attention increases the rate of correct responses and shortens reaction time, and it has been hypothesized that this phenomenon is caused by an increase in sensitivity of the sensory signals to which attention is directed. The present study employed psychophysical methods and electroencephalography (EEG) to test the hypothesis that attention accelerates the onset of information accumulation. Participants were asked to discriminate the motion direction of one of two random dot kinematograms presented on the left and right sides of the visual field, one of which was cued by an arrow in 80% of the trials. The drift-diffusion model was applied to the percentage of correct responses and reaction times in the attended and unattended fields of view. Attention primarily increased sensory sensitivity and shortened the time unrelated to decision making. Next, we measured centroparietal positivity (CPP), an EEG measure associated with decision making, and found that CPP latency was shorter in attended trials than in unattended trials. These results suggest that attention not only increases sensory sensitivity but also accelerates the initiation of decision making.
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Affiliation(s)
- Tomohiro Ueno
- Department of Integrative Physiology, Graduate School of Medicine, University of Yamanashi, 1110 Shimokato, Chuo-Shi, Yamanashi, Japan
| | - Hironori Kumano
- Department of Integrative Physiology, Graduate School of Medicine, University of Yamanashi, 1110 Shimokato, Chuo-Shi, Yamanashi, Japan
| | - Takanori Uka
- Department of Integrative Physiology, Graduate School of Medicine, University of Yamanashi, 1110 Shimokato, Chuo-Shi, Yamanashi, Japan.
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4
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Nunez MD, Fernandez K, Srinivasan R, Vandekerckhove J. A tutorial on fitting joint models of M/EEG and behavior to understand cognition. Behav Res Methods 2024:10.3758/s13428-023-02331-x. [PMID: 38409458 DOI: 10.3758/s13428-023-02331-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/21/2023] [Indexed: 02/28/2024]
Abstract
We present motivation and practical steps necessary to find parameter estimates of joint models of behavior and neural electrophysiological data. This tutorial is written for researchers wishing to build joint models of human behavior and scalp and intracranial electroencephalographic (EEG) or magnetoencephalographic (MEG) data, and more specifically those researchers who seek to understand human cognition. Although these techniques could easily be applied to animal models, the focus of this tutorial is on human participants. Joint modeling of M/EEG and behavior requires some knowledge of existing computational and cognitive theories, M/EEG artifact correction, M/EEG analysis techniques, cognitive modeling, and programming for statistical modeling implementation. This paper seeks to give an introduction to these techniques as they apply to estimating parameters from neurocognitive models of M/EEG and human behavior, and to evaluate model results and compare models. Due to our research and knowledge on the subject matter, our examples in this paper will focus on testing specific hypotheses in human decision-making theory. However, most of the motivation and discussion of this paper applies across many modeling procedures and applications. We provide Python (and linked R) code examples in the tutorial and appendix. Readers are encouraged to try the exercises at the end of the document.
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Affiliation(s)
- Michael D Nunez
- Psychological Methods, University of Amsterdam, Amsterdam, The Netherlands.
| | - Kianté Fernandez
- Department of Psychology, University of California, Los Angeles, CA, USA
| | - Ramesh Srinivasan
- Department of Cognitive Sciences, University of California, Irvine, CA, USA
- Department of Biomedical Engineering, University of California, Irvine, CA, USA
- Institute of Mathematical Behavioral Sciences, University of California, Irvine, CA, USA
| | - Joachim Vandekerckhove
- Department of Cognitive Sciences, University of California, Irvine, CA, USA
- Institute of Mathematical Behavioral Sciences, University of California, Irvine, CA, USA
- Department of Statistics, University of California, Irvine, CA, USA
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5
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Gherman S, Markowitz N, Tostaeva G, Espinal E, Mehta AD, O'Connell RG, Kelly SP, Bickel S. Intracranial electroencephalography reveals effector-independent evidence accumulation dynamics in multiple human brain regions. Nat Hum Behav 2024:10.1038/s41562-024-01824-9. [PMID: 38366105 DOI: 10.1038/s41562-024-01824-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Accepted: 01/10/2024] [Indexed: 02/18/2024]
Abstract
Neural representations of perceptual decision formation that are abstracted from specific motor requirements have previously been identified in humans using non-invasive electrophysiology; however, it is currently unclear where these originate in the brain. Here we capitalized on the high spatiotemporal precision of intracranial EEG to localize such abstract decision signals. Participants undergoing invasive electrophysiological monitoring for epilepsy were asked to judge the direction of random-dot stimuli and respond either with a speeded button press (N = 24), or vocally, after a randomized delay (N = 12). We found a widely distributed motor-independent network of regions where high-frequency activity exhibited key characteristics consistent with evidence accumulation, including a gradual buildup that was modulated by the strength of the sensory evidence, and an amplitude that predicted participants' choice accuracy and response time. Our findings offer a new view on the brain networks governing human decision-making.
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Affiliation(s)
- Sabina Gherman
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA.
| | - Noah Markowitz
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
| | - Gelana Tostaeva
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
| | - Elizabeth Espinal
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
- Department of Psychological and Brain Sciences, Drexel University, Philadelphia, PA, USA
| | - Ashesh D Mehta
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
- Departments of Neurology and Neurosurgery, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
| | - Redmond G O'Connell
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
- School of Psychology, Trinity College Dublin, Dublin, Ireland
| | - Simon P Kelly
- School of Electrical and Electronic Engineering and UCD Centre for Biomedical Engineering, University College Dublin, Dublin, Ireland
| | - Stephan Bickel
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA.
- Departments of Neurology and Neurosurgery, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA.
- Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute, Orangeburg, NY, USA.
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6
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Nuiten SA, de Gee JW, Zantvoord JB, Fahrenfort JJ, van Gaal S. Catecholaminergic neuromodulation and selective attention jointly shape perceptual decision-making. eLife 2023; 12:RP87022. [PMID: 38038722 PMCID: PMC10691802 DOI: 10.7554/elife.87022] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/02/2023] Open
Abstract
Perceptual decisions about sensory input are influenced by fluctuations in ongoing neural activity, most prominently driven by attention and neuromodulator systems. It is currently unknown if neuromodulator activity and attention differentially modulate perceptual decision-making and/or whether neuromodulatory systems in fact control attentional processes. To investigate the effects of two distinct neuromodulatory systems and spatial attention on perceptual decisions, we pharmacologically elevated cholinergic (through donepezil) and catecholaminergic (through atomoxetine) levels in humans performing a visuo-spatial attention task, while we measured electroencephalography (EEG). Both attention and catecholaminergic enhancement improved decision-making at the behavioral and algorithmic level, as reflected in increased perceptual sensitivity and the modulation of the drift rate parameter derived from drift diffusion modeling. Univariate analyses of EEG data time-locked to the attentional cue, the target stimulus, and the motor response further revealed that attention and catecholaminergic enhancement both modulated pre-stimulus cortical excitability, cue- and stimulus-evoked sensory activity, as well as parietal evidence accumulation signals. Interestingly, we observed both similar, unique, and interactive effects of attention and catecholaminergic neuromodulation on these behavioral, algorithmic, and neural markers of the decision-making process. Thereby, this study reveals an intricate relationship between attentional and catecholaminergic systems and advances our understanding about how these systems jointly shape various stages of perceptual decision-making.
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Affiliation(s)
- Stijn A Nuiten
- Department of Psychology, University of AmsterdamAmsterdamNetherlands
- Amsterdam Brain & Cognition, University of AmsterdamAmsterdamNetherlands
- Department of Psychiatry (UPK), University of BaselBaselSwitzerland
| | - Jan Willem de Gee
- Amsterdam Brain & Cognition, University of AmsterdamAmsterdamNetherlands
- Jan and Dan Duncan Neurological Research Institute, Texas Children’s HospitalHoustonUnited States
- Department of Neuroscience, Baylor College of MedicineHoustonUnited States
- Cognitive and Systems Neuroscience, Swammerdam Institute for Life Sciences, University of AmsterdamAmsterdamNetherlands
| | - Jasper B Zantvoord
- Department of Psychiatry, Amsterdam UMC location University of AmsterdamAmsterdamNetherlands
- Amsterdam NeuroscienceAmsterdamNetherlands
| | - Johannes J Fahrenfort
- Department of Psychology, University of AmsterdamAmsterdamNetherlands
- Amsterdam Brain & Cognition, University of AmsterdamAmsterdamNetherlands
- Institute for Brain and Behavior Amsterdam, Vrije Universiteit AmsterdamAmsterdamNetherlands
- Department of Experimental and Applied Psychology - Cognitive Psychology, Vrije Universiteit AmsterdamAmsterdamNetherlands
| | - Simon van Gaal
- Department of Psychology, University of AmsterdamAmsterdamNetherlands
- Amsterdam Brain & Cognition, University of AmsterdamAmsterdamNetherlands
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7
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den Ouden C, Zhou A, Mepani V, Kovács G, Vogels R, Feuerriegel D. Stimulus expectations do not modulate visual event-related potentials in probabilistic cueing designs. Neuroimage 2023; 280:120347. [PMID: 37648120 DOI: 10.1016/j.neuroimage.2023.120347] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Revised: 08/10/2023] [Accepted: 08/23/2023] [Indexed: 09/01/2023] Open
Abstract
Humans and other animals can learn and exploit repeating patterns that occur within their environments. These learned patterns can be used to form expectations about future sensory events. Several influential predictive coding models have been proposed to explain how learned expectations influence the activity of stimulus-selective neurons in the visual system. These models specify reductions in neural response measures when expectations are fulfilled (termed expectation suppression) and increases following surprising sensory events. However, there is currently scant evidence for expectation suppression in the visual system when confounding factors are taken into account. Effects of surprise have been observed in blood oxygen level dependent (BOLD) signals, but not when using electrophysiological measures. To provide a strong test for expectation suppression and surprise effects we performed a predictive cueing experiment while recording electroencephalographic (EEG) data. Participants (n=48) learned cue-face associations during a training session and were then exposed to these cue-face pairs in a subsequent experiment. Using univariate analyses of face-evoked event-related potentials (ERPs) we did not observe any differences across expected (90% probability), neutral (50%) and surprising (10%) face conditions. Across these comparisons, Bayes factors consistently favoured the null hypothesis throughout the time-course of the stimulus-evoked response. When using multivariate pattern analysis we did not observe above-chance classification of expected and surprising face-evoked ERPs. By contrast, we found robust within- and across-trial stimulus repetition effects. Our findings do not support predictive coding-based accounts that specify reduced prediction error signalling when perceptual expectations are fulfilled. They instead highlight the utility of other types of predictive processing models that describe expectation-related phenomena in the visual system without recourse to prediction error signalling.
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Affiliation(s)
- Carla den Ouden
- Melbourne School of Psychological Sciences, The University of Melbourne, Melbourne, Australia
| | - Andong Zhou
- Melbourne School of Psychological Sciences, The University of Melbourne, Melbourne, Australia
| | - Vinay Mepani
- Melbourne School of Psychological Sciences, The University of Melbourne, Melbourne, Australia
| | - Gyula Kovács
- Institute of Psychology, Friedrich Schiller University Jena, Jena, Germany
| | - Rufin Vogels
- Laboratorium voor Neuro- en Psychofysiologie, Department of Neurosciences, KU Leuven, Leuven, Belgium
| | - Daniel Feuerriegel
- Melbourne School of Psychological Sciences, The University of Melbourne, Melbourne, Australia.
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8
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Brosnan M, Pearce DJ, O'Neill MH, Loughnane GM, Fleming B, Zhou SH, Chong T, Nobre AC, O Connell RG, Bellgrove MA. Evidence Accumulation Rate Moderates the Relationship between Enriched Environment Exposure and Age-Related Response Speed Declines. J Neurosci 2023; 43:6401-6414. [PMID: 37507230 PMCID: PMC10500991 DOI: 10.1523/jneurosci.2260-21.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Revised: 07/10/2023] [Accepted: 07/20/2023] [Indexed: 07/30/2023] Open
Abstract
Older adults exposed to enriched environments (EEs) maintain relatively higher levels of cognitive function, even in the face of compromised markers of brain health. Response speed (RS) is often used as a simple proxy to measure the preservation of global cognitive function in older adults. However, it is unknown which specific selection, decision, and/or motor processes provide the most specific indices of neurocognitive health. Here, using a simple decision task with electroencephalography (EEG), we found that the efficiency with which an individual accumulates sensory evidence was a critical determinant of the extent to which RS was preserved in older adults (63% female, 37% male). Moreover, the mitigating influence of EE on age-related RS declines was most pronounced when evidence accumulation rates were shallowest. These results suggest that the phenomenon of cognitive reserve, whereby high EE individuals can better tolerate suboptimal brain health to facilitate the preservation of cognitive function, is not just applicable to neuroanatomical indicators of brain aging but can be observed in markers of neurophysiology. Our results suggest that EEG metrics of evidence accumulation may index neurocognitive vulnerability of the aging brain.Significance Statement Response speed in older adults is closely linked with trajectories of cognitive aging. Here, by recording brain activity while individuals perform a simple computer task, we identify a neural metric that is a critical determinant of response speed. Older adults exposed to greater cognitive and social stimulation throughout a lifetime could maintain faster responding, even when this neural metric was impaired. This work suggests EEG is a useful technique for interrogating how a lifetime of stimulation benefits brain health in aging.
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Affiliation(s)
- Méadhbh Brosnan
- Turner Institute for Brain and Mental Health and School of Psychological Sciences, Monash University, Melbourne, Victoria 3800, Australia
- Department of Experimental Psychology, University of Oxford, Oxford OX2 6GG, United Kingdom
- Oxford Centre for Human Brain Activity, University of Oxford, Oxford OX3 7JX, United Kingdom
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford OX3 9DU, United Kingdom
- School of Psychology, University College Dublin, Dublin 2, Ireland
| | - Daniel J Pearce
- Turner Institute for Brain and Mental Health and School of Psychological Sciences, Monash University, Melbourne, Victoria 3800, Australia
| | - Megan H O'Neill
- Turner Institute for Brain and Mental Health and School of Psychological Sciences, Monash University, Melbourne, Victoria 3800, Australia
| | - Gerard M Loughnane
- School of Business, National College of Ireland, Dublin 1, Ireland
- Trinity College Institute of Neuroscience and School of Psychology, Trinity College Dublin, Dublin 2, Ireland
| | - Bryce Fleming
- Turner Institute for Brain and Mental Health and School of Psychological Sciences, Monash University, Melbourne, Victoria 3800, Australia
| | - Shou-Han Zhou
- Department of Psychology, James Cook University, Brisbane, Queensland 4000, Australia
| | - Trevor Chong
- Turner Institute for Brain and Mental Health and School of Psychological Sciences, Monash University, Melbourne, Victoria 3800, Australia
| | - Anna C Nobre
- Department of Experimental Psychology, University of Oxford, Oxford OX2 6GG, United Kingdom
- Oxford Centre for Human Brain Activity, University of Oxford, Oxford OX3 7JX, United Kingdom
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford OX3 9DU, United Kingdom
| | - Redmond G O Connell
- Turner Institute for Brain and Mental Health and School of Psychological Sciences, Monash University, Melbourne, Victoria 3800, Australia
- School of Business, National College of Ireland, Dublin 1, Ireland
| | - Mark A Bellgrove
- Turner Institute for Brain and Mental Health and School of Psychological Sciences, Monash University, Melbourne, Victoria 3800, Australia
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9
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Borst JP, Aubin S, Stewart TC. A whole-task brain model of associative recognition that accounts for human behavior and neuroimaging data. PLoS Comput Biol 2023; 19:e1011427. [PMID: 37682986 PMCID: PMC10511112 DOI: 10.1371/journal.pcbi.1011427] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Revised: 09/20/2023] [Accepted: 08/10/2023] [Indexed: 09/10/2023] Open
Abstract
Brain models typically focus either on low-level biological detail or on qualitative behavioral effects. In contrast, we present a biologically-plausible spiking-neuron model of associative learning and recognition that accounts for both human behavior and low-level brain activity across the whole task. Based on cognitive theories and insights from machine-learning analyses of M/EEG data, the model proceeds through five processing stages: stimulus encoding, familiarity judgement, associative retrieval, decision making, and motor response. The results matched human response times and source-localized MEG data in occipital, temporal, prefrontal, and precentral brain regions; as well as a classic fMRI effect in prefrontal cortex. This required two main conceptual advances: a basal-ganglia-thalamus action-selection system that relies on brief thalamic pulses to change the functional connectivity of the cortex, and a new unsupervised learning rule that causes very strong pattern separation in the hippocampus. The resulting model shows how low-level brain activity can result in goal-directed cognitive behavior in humans.
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Affiliation(s)
- Jelmer P. Borst
- Bernoulli Institute, University of Groningen; Groningen, The Netherlands
| | - Sean Aubin
- Centre for Theoretical Neuroscience, University of Waterloo; Waterloo, Ontario, Canada
| | - Terrence C. Stewart
- National Research Council Canada, University of Waterloo Collaboration Centre; Waterloo, Ontario, Canada
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10
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Geuzebroek AC, Craddock H, O'Connell RG, Kelly SP. Balancing true and false detection of intermittent sensory targets by adjusting the inputs to the evidence accumulation process. eLife 2023; 12:e83025. [PMID: 37646405 PMCID: PMC10547474 DOI: 10.7554/elife.83025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Accepted: 08/29/2023] [Indexed: 09/01/2023] Open
Abstract
Decisions about noisy stimuli are widely understood to be made by accumulating evidence up to a decision bound that can be adjusted according to task demands. However, relatively little is known about how such mechanisms operate in continuous monitoring contexts requiring intermittent target detection. Here, we examined neural decision processes underlying detection of 1 s coherence targets within continuous random dot motion, and how they are adjusted across contexts with weak, strong, or randomly mixed weak/strong targets. Our prediction was that decision bounds would be set lower when weak targets are more prevalent. Behavioural hit and false alarm rate patterns were consistent with this, and were well captured by a bound-adjustable leaky accumulator model. However, beta-band EEG signatures of motor preparation contradicted this, instead indicating lower bounds in the strong-target context. We thus tested two alternative models in which decision-bound dynamics were constrained directly by beta measurements, respectively, featuring leaky accumulation with adjustable leak, and non-leaky accumulation of evidence referenced to an adjustable sensory-level criterion. We found that the latter model best explained both behaviour and neural dynamics, highlighting novel means of decision policy regulation and the value of neurally informed modelling.
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Affiliation(s)
- Anna C Geuzebroek
- School of Electrical and Electronic Engineering and UCD Centre for Biomedical Engineering, University College DublinDublinIreland
| | - Hannah Craddock
- School of Electrical and Electronic Engineering and UCD Centre for Biomedical Engineering, University College DublinDublinIreland
- Department of Statistics, University of WarwickWarwickUnited Kingdom
| | - Redmond G O'Connell
- Trinity College Institute of Neuroscience and School of Psychology, Trinity College DublinDublinIreland
| | - Simon P Kelly
- School of Electrical and Electronic Engineering and UCD Centre for Biomedical Engineering, University College DublinDublinIreland
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11
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Azizi Z, Ebrahimpour R. Explaining Integration of Evidence Separated by Temporal Gaps with Frontoparietal Circuit Models. Neuroscience 2023; 509:74-95. [PMID: 36457229 DOI: 10.1016/j.neuroscience.2022.10.019] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Revised: 10/17/2022] [Accepted: 10/20/2022] [Indexed: 11/07/2022]
Abstract
Perceptual decisions rely on accumulating sensory evidence over time. However, the accumulation process is complicated in real life when evidence resulted from separated cues over time. Previous studies demonstrate that participants are able to integrate information from two separated cues to improve their performance invariant to an interval between the cues. However, there is no neural model that can account for accuracy and confidence in decisions when there is a time interval in evidence. We used behavioral and EEG datasets from a visual choice task -Random dot motion- with separated evidence to investigate three candid distributed neural networks. We showed that decisions based on evidence accumulation by separated cues over time are best explained by the interplay of recurrent cortical dynamics of centro-parietal and frontal brain areas while an uncertainty-monitoring module included in the model.
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Affiliation(s)
- Zahra Azizi
- Department of Cognitive Modeling, Institute for Cognitive Science Studies, Tehran, Iran.
| | - Reza Ebrahimpour
- Institute for Convergence Science and Technology (ICST), Sharif University of Technology, Tehran, P.O.Box: 11155-8639, Iran; Faculty of Computer Engineering, Shahid Rajaee Teacher Training University, Postal Box: 16785-163, Tehran, Iran; School of Cognitive Sciences (SCS), Institute for Research in Fundamental Sciences (IPM), Niavaran, Postal Box: 19395-5746, Tehran, Iran.
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12
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Hu J, Konovalov A, Ruff CC. A unified neural account of contextual and individual differences in altruism. eLife 2023; 12:80667. [PMID: 36752704 PMCID: PMC9908080 DOI: 10.7554/elife.80667] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Accepted: 01/19/2023] [Indexed: 02/09/2023] Open
Abstract
Altruism is critical for cooperation and productivity in human societies but is known to vary strongly across contexts and individuals. The origin of these differences is largely unknown, but may in principle reflect variations in different neurocognitive processes that temporally unfold during altruistic decision making (ranging from initial perceptual processing via value computations to final integrative choice mechanisms). Here, we elucidate the neural origins of individual and contextual differences in altruism by examining altruistic choices in different inequality contexts with computational modeling and electroencephalography (EEG). Our results show that across all contexts and individuals, wealth distribution choices recruit a similar late decision process evident in model-predicted evidence accumulation signals over parietal regions. Contextual and individual differences in behavior related instead to initial processing of stimulus-locked inequality-related value information in centroparietal and centrofrontal sensors, as well as to gamma-band synchronization of these value-related signals with parietal response-locked evidence-accumulation signals. Our findings suggest separable biological bases for individual and contextual differences in altruism that relate to differences in the initial processing of choice-relevant information.
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Affiliation(s)
- Jie Hu
- Zurich Center for Neuroeconomics, Department of Economics, University of ZurichZurichSwitzerland
| | - Arkady Konovalov
- Zurich Center for Neuroeconomics, Department of Economics, University of ZurichZurichSwitzerland,Centre for Human Brain Health, School of Psychology, University of BirminghamBirminghamUnited Kingdom
| | - Christian C Ruff
- Zurich Center for Neuroeconomics, Department of Economics, University of ZurichZurichSwitzerland,University Research Priority Program 'Adaptive Brain Circuits in Development and Learning' (URPP AdaBD), University of ZurichZurichSwitzerland
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13
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Imperfect integration: Congruency between multiple sensory sources modulates decision-making processes. Atten Percept Psychophys 2022; 84:1566-1582. [PMID: 35460027 PMCID: PMC9232470 DOI: 10.3758/s13414-021-02434-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/23/2021] [Indexed: 11/18/2022]
Abstract
Decision-making on the basis of multiple information sources is common. However, to what extent such decisions differ from those with a single source remains unclear. We combined cognitive modelling and neural-mass modelling to characterise the neurocognitive process underlying perceptual decision-making with single or double information sources. Ninety-four human participants performed binary decisions to discriminate the coherent motion direction averaged across two independent apertures. Regardless of the angular distance of the apertures, separating motion information into two apertures resulted in a reduction in accuracy. Our cognitive and neural-mass modelling results are consistent with the hypotheses that the addition of the second information source led to a lower signal-to-noise ratio of evidence accumulation with two congruent information sources, and a change in the decision strategy of speed–accuracy trade-off with two incongruent sources. Thus, our findings support a robust behavioural change in relation to multiple information sources, which have congruency-dependent impacts on selective decision-making subcomponents.
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14
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Perceptual decision-making ‘in the wild’: How risk propensity and injury exposure experience influence the neural signatures of occupational hazard recognition. Int J Psychophysiol 2022; 177:92-102. [DOI: 10.1016/j.ijpsycho.2022.04.012] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Revised: 04/16/2022] [Accepted: 04/28/2022] [Indexed: 11/18/2022]
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15
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Spadone S, Tosoni A, Penna SD, Sestieri C. Alpha rhythm modulations in the intraparietal sulcus reflect decision signals during item recognition. Neuroimage 2022; 258:119345. [PMID: 35660462 DOI: 10.1016/j.neuroimage.2022.119345] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2021] [Revised: 05/14/2022] [Accepted: 05/30/2022] [Indexed: 01/05/2023] Open
Abstract
Theoretical work and empirical observations suggest a contribution of regions along the intraparietal sulcus to the process of evidence accumulation during episodic memory retrieval. In the present study, we recorded magnetoencephalographic signals in a group of healthy human participants to test whether the pattern of oscillatory modulations in the lateral parietal lobe is consistent with the mnemonic accumulator hypothesis. To this aim, the dynamic properties and the spatial distribution of MEG oscillatory power modulations were investigated during an item recognition task in which the amount of evidence for old vs. new memory decisions was manipulated across three levels. A data-driven approach was employed to identify brain nodes where oscillatory activity was sensitive to both retrieval success and the amount of evidence for old decisions. The analysis identified three nodes in the left lateral parietal lobe where the event-related desynchronization (ERD) in the alpha frequency band showed both effects. Further analyses revealed that the alpha ERD in the intraparietal sulcus, but not in other parietal nodes: i. showed modulation of duration in response to the amount of evidence for both old and new decisions, ii. was behaviorally significant, and iii. more accurately tracked the subjective memory judgment rather than the objective memory status. The present findings provide support for a recent anatomical-functional model of the parietal involvement in episodic memory retrieval and suggest that the alpha ERD in the intraparietal sulcus might represent a neural signature of the evidence accumulation process during simple memory-based decisions.
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Affiliation(s)
- Sara Spadone
- Department of Neuroscience, Imaging and Clinical Sciences and ITAB, Institute for Advanced Biomedical Technologies, G. d'Annunzio University of Chieti-Pescara, 66100, Italy
| | - Annalisa Tosoni
- Department of Neuroscience, Imaging and Clinical Sciences and ITAB, Institute for Advanced Biomedical Technologies, G. d'Annunzio University of Chieti-Pescara, 66100, Italy
| | - Stefania Della Penna
- Department of Neuroscience, Imaging and Clinical Sciences and ITAB, Institute for Advanced Biomedical Technologies, G. d'Annunzio University of Chieti-Pescara, 66100, Italy
| | - Carlo Sestieri
- Department of Neuroscience, Imaging and Clinical Sciences and ITAB, Institute for Advanced Biomedical Technologies, G. d'Annunzio University of Chieti-Pescara, 66100, Italy.
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16
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Harris A, Hutcherson CA. Temporal dynamics of decision making: A synthesis of computational and neurophysiological approaches. WILEY INTERDISCIPLINARY REVIEWS. COGNITIVE SCIENCE 2022; 13:e1586. [PMID: 34854573 DOI: 10.1002/wcs.1586] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/27/2021] [Revised: 10/06/2021] [Accepted: 10/18/2021] [Indexed: 06/13/2023]
Abstract
As interest in the temporal dynamics of decision-making has grown, researchers have increasingly turned to computational approaches such as the drift diffusion model (DDM) to identify how cognitive processes unfold during choice. At the same time, technological advances in noninvasive neurophysiological methods such as electroencephalography and magnetoencephalography now allow researchers to map the neural time course of decision making with millisecond precision. Combining these approaches can potentially yield important new insights into how choices emerge over time. Here we review recent research on the computational and neurophysiological correlates of perceptual and value-based decision making, from DDM parameters to scalp potentials and oscillatory neural activity. Starting with motor response preparation, the most well-understood aspect of the decision process, we discuss evidence that urgency signals and shifts in baseline activation, rather than shifts in the physiological value of the choice-triggering response threshold, are responsible for adjusting response times under speeded choice scenarios. Research on the neural correlates of starting point bias suggests that prestimulus activity can predict biases in motor choice behavior. Finally, studies examining the time dynamics of evidence construction and evidence accumulation have identified signals at frontocentral and centroparietal electrodes associated respectively with these processes, emerging 300-500 ms after stimulus onset. These findings can inform psychological theories of decision-making, providing empirical support for attribute weighting in value-based choice while suggesting theoretical alternatives to dual-process accounts. Further research combining computational and neurophysiological approaches holds promise for providing greater insight into the moment-by-moment evolution of the decision process. This article is categorized under: Psychology > Reasoning and Decision Making Neuroscience > Cognition Economics > Individual Decision-Making.
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Affiliation(s)
- Alison Harris
- Claremont McKenna College, Claremont, California, USA
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17
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A leaky evidence accumulation process for perceptual experience. Trends Cogn Sci 2022; 26:451-461. [DOI: 10.1016/j.tics.2022.03.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Revised: 03/08/2022] [Accepted: 03/09/2022] [Indexed: 11/23/2022]
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18
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Weigard A, Sripada C. Task-general efficiency of evidence accumulation as a computationally-defined neurocognitive trait: Implications for clinical neuroscience. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2022; 1:5-15. [PMID: 35317408 DOI: 10.1016/j.bpsgos.2021.02.001] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
Abstract
Quantifying individual differences in higher-order cognitive functions is a foundational area of cognitive science that also has profound implications for research on psychopathology. For the last two decades, the dominant approach in these fields has been to attempt to fractionate higher-order functions into hypothesized components (e.g., "inhibition", "updating") through a combination of experimental manipulation and factor analysis. However, the putative constructs obtained through this paradigm have recently been met with substantial criticism on both theoretical and empirical grounds. Concurrently, an alternative approach has emerged focusing on parameters of formal computational models of cognition that have been developed in mathematical psychology. These models posit biologically plausible and experimentally validated explanations of the data-generating process for cognitive tasks, allowing them to be used to measure the latent mechanisms that underlie performance. One of the primary insights provided by recent applications of such models is that individual and clinical differences in performance on a wide variety of cognitive tasks, ranging from simple choice tasks to complex executive paradigms, are largely driven by efficiency of evidence accumulation (EEA), a computational mechanism defined by sequential sampling models. This review assembles evidence for the hypothesis that EEA is a central individual difference dimension that explains neurocognitive deficits in multiple clinical disorders and identifies ways in which in this insight can advance clinical neuroscience research. We propose that recognition of EEA as a major driver of neurocognitive differences will allow the field to make clearer inferences about cognitive abnormalities in psychopathology and their links to neurobiology.
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O’Neill J, Schoth A. The Mental Maxwell Relations: A Thermodynamic Allegory for Higher Brain Functions. Front Neurosci 2022; 16:827888. [PMID: 35295094 PMCID: PMC8919724 DOI: 10.3389/fnins.2022.827888] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Accepted: 01/10/2022] [Indexed: 11/29/2022] Open
Abstract
The theoretical framework of classical thermodynamics unifies vastly diverse natural phenomena and captures once-elusive effects in concrete terms. Neuroscience confronts equally varied, equally ineffable phenomena in the mental realm, but has yet to unite or to apprehend them rigorously, perhaps due to an insufficient theoretical framework. The terms for mental phenomena, the mental variables, typically used in neuroscience are overly numerous and imprecise. Unlike in thermodynamics or other branches of physics, in neuroscience, there are no core mental variables from which all others formally derive and it is unclear which variables are distinct and which overlap. This may be due to the nature of mental variables themselves. Unlike the variables of physics, perhaps they cannot be interpreted as composites of a small number of axioms. However, it is well worth exploring if they can, as that would allow more parsimonious theories of higher brain function. Here we offer a theoretical exercise in the spirit of the National Institutes of Health Research Domain Criteria (NIH RDoC) Initiative and the Cognitive Atlas Project, which aim to remedy this state of affairs. Imitating classical thermodynamics, we construct a formal framework for mental variables, an extended analogy - an allegory - between mental and thermodynamic quantities. Starting with mental correlates of the physical indefinables length, time, mass or force, and charge, we pursue the allegory up to mental versions of the thermodynamic Maxwell Relations. The Maxwell Relations interrelate the thermodynamic quantities volume, pressure, temperature, and entropy and were chosen since they are easy to derive, yet capable of generating nontrivial, nonobvious predictions. Our "Mental Maxwell Relations" interlink the mental variables consciousness, salience, arousal, and distraction and make nontrivial, nonobvious statements about mental phenomena. The mental system thus constructed is internally consistent, in harmony with introspection, and respects the RDoC criteria of employing only psychologically valid constructs with some evidence of a brain basis. We briefly apply these concepts to the problem of decision-making and sketch how some of them might be tested empirically.
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Affiliation(s)
- Joseph O’Neill
- Division of Child and Adolescent Psychiatry, UCLA Semel Institute for Neuroscience, Los Angeles, CA, United States
| | - Andreas Schoth
- IMTEK Department for Process Technology, Institute of Microsystem Technology, Universität Freiburg, Freiburg, Germany
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20
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Snowden AW, Hancock AS, Buhusi CV, Warren CM. Event-related Correlates of Evolving Trust Evaluations. Soc Neurosci 2022; 17:154-169. [DOI: 10.1080/17470919.2022.2043935] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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21
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Stefanac NR, Zhou SH, Spencer-Smith MM, O'Connell R, Bellgrove MA. A neural index of inefficient evidence accumulation in dyslexia underlying slow perceptual decision making. Cortex 2021; 142:122-137. [PMID: 34265735 DOI: 10.1016/j.cortex.2021.05.021] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2020] [Revised: 12/18/2020] [Accepted: 05/13/2021] [Indexed: 10/21/2022]
Abstract
Visual processing deficits have been widely reported in developmental dyslexia however the locus of cognitive dysfunction remains unclear. Here, we examined the neural correlates of perceptual decision-making using a dot-motion task and electroencephalography (EEG) and investigated whether presenting deficits were unique to children with dyslexia or if they were also evident in other, typically developing children with equally immature reading systems. Sixty-eight children participated: 32 with dyslexia (DD; 16 females); 21 age-matched controls (AM; 11 females) and 15 reading-matched controls (RM; 9 females). All participants completed a bilaterally presented random-dot-motion task while EEG was recorded. Neural signatures of low level sensory processing (steady state visual evoked potentials; SSVEPs), pre-target attentional bias (posterior α power), attentional orienting (N2), evidence accumulation (centro-parietal positive decision signal; CPP) and execution of a motor response (β) were obtained to dissect the temporal sequence of perceptual decision-making. Reading profile provided a score of relative lexical and sublexical skills for each participant. Although all groups performed comparably in terms of task accuracy and false alarm rate, the DD group were slower and demonstrated an earlier peak latency, reduced slope and lower amplitude of the CPP compared with both AM and RM controls. Reading profile was found to moderate the relationship between word reading ability, reaction time as well as CPP indices showing that lexical dyslexics responded more slowly and had a shallower slope, reduced amplitude and earlier latency of CPP waveforms than sublexical dyslexics. These findings suggest that children with dyslexia, particularly those with relatively poorer lexical abilities, have a reduced rate and peak of evidence accumulation as denoted by CPP markers yet remain slow in their overt response. This is in keeping with hypotheses that children with dyslexia have impairment in effectively sampling and processing evidence about visual motion stimuli.
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Affiliation(s)
- Nicole R Stefanac
- Turner Institute for Brain and Mental Health and School of Psychological Sciences, Monash University, Melbourne, Vic, Australia.
| | - Shou-Han Zhou
- Turner Institute for Brain and Mental Health and School of Psychological Sciences, Monash University, Melbourne, Vic, Australia
| | - Megan M Spencer-Smith
- Turner Institute for Brain and Mental Health and School of Psychological Sciences, Monash University, Melbourne, Vic, Australia
| | - Redmond O'Connell
- Turner Institute for Brain and Mental Health and School of Psychological Sciences, Monash University, Melbourne, Vic, Australia; Trinity College Institute of Neuroscience, Trinity College Dublin, Ireland
| | - Mark A Bellgrove
- Turner Institute for Brain and Mental Health and School of Psychological Sciences, Monash University, Melbourne, Vic, Australia; Trinity College Institute of Neuroscience, Trinity College Dublin, Ireland
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22
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Abstract
The discovery of neural signals that reflect the dynamics of perceptual decision formation has had a considerable impact. Not only do such signals enable detailed investigations of the neural implementation of the decision-making process but they also can expose key elements of the brain's decision algorithms. For a long time, such signals were only accessible through direct animal brain recordings, and progress in human neuroscience was hampered by the limitations of noninvasive recording techniques. However, recent methodological advances are increasingly enabling the study of human brain signals that finely trace the dynamics of the unfolding decision process. In this review, we highlight how human neurophysiological data are now being leveraged to furnish new insights into the multiple processing levels involved in forming decisions, to inform the construction and evaluation of mathematical models that can explain intra- and interindividual differences, and to examine how key ancillary processes interact with core decision circuits.
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Affiliation(s)
- Redmond G O'Connell
- Trinity College Institute of Neuroscience and School of Psychology, Trinity College Dublin, Dublin 2, Ireland;
| | - Simon P Kelly
- School of Electrical and Electronic Engineering and UCD Centre for Biomedical Engineering, University College Dublin, Belfield, Dublin 4, Ireland;
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23
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Zhou SH, Loughnane G, O'Connell R, Bellgrove MA, Chong TTJ. Distractors Selectively Modulate Electrophysiological Markers of Perceptual Decisions. J Cogn Neurosci 2021; 33:1020-1031. [PMID: 34428789 DOI: 10.1162/jocn_a_01703] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
Current models of perceptual decision-making assume that choices are made after evidence in favor of an alternative accumulates to a given threshold. This process has recently been revealed in human EEG recordings, but an unresolved issue is how these neural mechanisms are modulated by competing, yet task-irrelevant, stimuli. In this study, we tested 20 healthy participants on a motion direction discrimination task. Participants monitored two patches of random dot motion simultaneously presented on either side of fixation for periodic changes in an upward or downward motion, which could occur equiprobably in either patch. On a random 50% of trials, these periods of coherent vertical motion were accompanied by simultaneous task-irrelevant, horizontal motion in the contralateral patch. Our data showed that these distractors selectively increased the amplitude of early target selection responses over scalp sites contralateral to the distractor stimulus, without impacting on responses ipsilateral to the distractor. Importantly, this modulation mediated a decrement in the subsequent buildup rate of a neural signature of evidence accumulation and accounted for a slowing of RTs. These data offer new insights into the functional interactions between target selection and evidence accumulation signals, and their susceptibility to task-irrelevant distractors. More broadly, these data neurally inform future models of perceptual decision-making by highlighting the influence of early processing of competing stimuli on the accumulation of perceptual evidence.
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24
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Wang Y, Yan J, Yin Z, Ren S, Dong M, Zheng C, Zhang W, Liang J. How Native Background Affects Human Performance in Real-World Visual Object Detection: An Event-Related Potential Study. Front Neurosci 2021; 15:665084. [PMID: 33994938 PMCID: PMC8119748 DOI: 10.3389/fnins.2021.665084] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2021] [Accepted: 03/31/2021] [Indexed: 11/13/2022] Open
Abstract
Visual processing refers to the process of perceiving, analyzing, synthesizing, manipulating, transforming, and thinking of visual objects. It is modulated by both stimulus-driven and goal-directed factors and manifested in neural activities that extend from visual cortex to high-level cognitive areas. Extensive body of studies have investigated the neural mechanisms of visual object processing using synthetic or curated visual stimuli. However, synthetic or curated images generally do not accurately reflect the semantic links between objects and their backgrounds, and previous studies have not provided answers to the question of how the native background affects visual target detection. The current study bridged this gap by constructing a stimulus set of natural scenes with two levels of complexity and modulating participants' attention to actively or passively attend to the background contents. Behaviorally, the decision time was elongated when the background was complex or when the participants' attention was distracted from the detection task, and the object detection accuracy was decreased when the background was complex. The results of event-related potentials (ERP) analysis explicated the effects of scene complexity and attentional state on the brain responses in occipital and centro-parietal areas, which were suggested to be associated with varied attentional cueing and sensory evidence accumulation effects in different experimental conditions. Our results implied that efficient visual processing of real-world objects may involve a competition process between context and distractors that co-exist in the native background, and extensive attentional cues and fine-grained but semantically irrelevant scene information were perhaps detrimental to real-world object detection.
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Affiliation(s)
- Yue Wang
- School of Electronic Engineering, Xidian University, Xi'an, China
| | - Jianpu Yan
- School of Electronic Engineering, Xidian University, Xi'an, China
| | - Zhongliang Yin
- School of Life Science and Technology, Xidian University, Xi'an, China
| | - Shenghan Ren
- School of Life Science and Technology, Xidian University, Xi'an, China
| | - Minghao Dong
- School of Life Science and Technology, Xidian University, Xi'an, China
| | - Changli Zheng
- Southwest China Research Institute of Electronic Equipment, Chengdu, China
| | - Wei Zhang
- Southwest China Research Institute of Electronic Equipment, Chengdu, China
| | - Jimin Liang
- School of Electronic Engineering, Xidian University, Xi'an, China
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25
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van den Brink RL, Murphy PR, Desender K, de Ru N, Nieuwenhuis S. Temporal Expectation Hastens Decision Onset But Does Not Affect Evidence Quality. J Neurosci 2021; 41:130-143. [PMID: 33172980 PMCID: PMC7786203 DOI: 10.1523/jneurosci.1103-20.2020] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2020] [Revised: 09/29/2020] [Accepted: 10/01/2020] [Indexed: 11/21/2022] Open
Abstract
The ability to predict the timing of forthcoming events, known as temporal expectation, has a strong impact on human information processing. Although there is growing consensus that temporal expectations enhance the speed and accuracy of perceptual decisions, it remains unclear whether they affect the decision process itself, or non-decisional (sensory/motor) processes. Here, healthy human participants (N = 21; 18 female) used predictive auditory cues to anticipate the timing of low-contrast visual stimuli they were required to detect. Modeling of the behavioral data using a prominent sequential sampling model indicated that temporal expectations speeded up non-decisional processes but had no effect on decision formation. Electrophysiological recordings confirmed and extended this result: temporal expectations hastened the onset of a neural signature of decision formation but had no effect on its build-up rate. Anticipatory α band power was modulated by temporal expectation and co-varied with intrinsic trial-by-trial variability in behavioral and neural signatures of the onset latency of the decision process. These findings highlight how temporal predictions optimize our interaction with unfolding sensory events.SIGNIFICANCE STATEMENT Temporal expectation enhances performance, but the locus of this effect remains debated. Here, we contrasted the two dominant accounts: enhancement through (1) expedited decision onset, or (2) an increase in the quality of sensory evidence. We manipulated expectations about the onset of a dim visual target using a temporal cueing paradigm, and probed the locus of the expectation effect with two complementary approaches: drift diffusion modeling (DDM) of behavior, and estimation of the onset and progression of the decision process from a supramodal accumulation-to-bound signal in simultaneously measured EEG signals. Behavioral modeling and neural data provided strong, converging evidence for an account in which temporal expectations enhance perception by speeding up decision onset, without affecting evidence quality.
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Affiliation(s)
- Ruud L van den Brink
- Section Computational Cognitive Neuroscience, Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, Hamburg, 20251 Germany
- Department of Psychology, Leiden University, Leiden, 2333 AK, The Netherlands
| | - Peter R Murphy
- Section Computational Cognitive Neuroscience, Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, Hamburg, 20251 Germany
- Department of Psychology, Leiden University, Leiden, 2333 AK, The Netherlands
| | - Kobe Desender
- Section Computational Cognitive Neuroscience, Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, Hamburg, 20251 Germany
- Department of Experimental Psychology, Ghent University, Ghent, 9000, Belgium
- Brain and Cognition, KU Leuven, Leuven, 3000, Belgium
| | - Nicole de Ru
- Department of Psychology, Leiden University, Leiden, 2333 AK, The Netherlands
| | - Sander Nieuwenhuis
- Department of Psychology, Leiden University, Leiden, 2333 AK, The Netherlands
- Leiden Institute for Brain and Cognition, Leiden, 2333 AK, The Netherlands
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26
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Neurocomputational mechanisms of prior-informed perceptual decision-making in humans. Nat Hum Behav 2020; 5:467-481. [PMID: 33318661 DOI: 10.1038/s41562-020-00967-9] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2019] [Accepted: 09/17/2020] [Indexed: 12/16/2022]
Abstract
To interact successfully with diverse sensory environments, we must adapt our decision processes to account for time constraints and prior probabilities. The full set of decision-process parameters that undergo such flexible adaptation has proven to be difficult to establish using simplified models that are based on behaviour alone. Here, we utilize well-characterized human neurophysiological signatures of decision formation to construct and constrain a build-to-threshold decision model with multiple build-up (evidence accumulation and urgency) and delay components (pre- and post-decisional). The model indicates that all of these components were adapted in distinct ways and, in several instances, fundamentally differ from the conclusions of conventional diffusion modelling. The neurally informed model outcomes were corroborated by independent neural decision signal observations that were not used in the model's construction. These findings highlight the breadth of decision-process parameters that are amenable to strategic adjustment and the value in leveraging neurophysiological measurements to quantify these adjustments.
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27
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Fearon C, Butler JS, Waechter SM, Killane I, Kelly SP, Reilly RB, Lynch T. Neurophysiological correlates of dual tasking in people with Parkinson's disease and freezing of gait. Exp Brain Res 2020; 239:175-187. [PMID: 33135132 DOI: 10.1007/s00221-020-05968-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2019] [Accepted: 10/21/2020] [Indexed: 11/24/2022]
Abstract
Freezing of gait in people with Parkinson's disease (PwP) is associated with executive dysfunction and motor preparation deficits. We have recently shown that electrophysiological markers of motor preparation, rather than decision-making, differentiate PwP with freezing of gait (FOG +) and without (FOG -) while sitting. To examine the effect of locomotion on these results, we measured behavioural and electrophysiological responses in PwP with and without FOG during a target response time task while sitting (single-task) and stepping-in-place (dual-task). Behavioural and electroencephalographic data were acquired from 18 PwP (eight FOG +) and seven young controls performing the task while sitting and stepping-in-place. FOG + had slower response times while stepping compared with sitting. However, response times were significantly faster while stepping compared with sitting for controls. Electrophysiological responses showed no difference in decision-making potentials (centroparietal positivity) between groups or conditions but there were differences in neurophysiological markers of response inhibition (N2) and motor preparation (lateralized readiness potential, LRP) in FOG + while performing a dual-task. This suggests that the addition of a second complex motor task (stepping-in-place) impacts automatic allocation of resources in FOG +, resulting in delayed response times. The impact of locomotion on the generation of the N2 and LRP potentials, particularly in freezers, indirectly implies that these functions compete with locomotion for resources. In the setting of multiple complex tasks or cognitive impairment, severe motor dysfunction may result, leading to freezing of gait.
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Affiliation(s)
- Conor Fearon
- Trinity Centre for Bioengineering, The School of Medicine and the School of Engineering, Trinity College, The University of Dublin, Dublin 2, Ireland.
- School of Engineering, Trinity College, The University of Dublin, Dublin 2, Ireland.
- Dublin Neurological Institute at the Mater Misericordiae University Hospital, 57 Eccles Street, Dublin 7, Ireland.
| | - John S Butler
- Trinity Centre for Bioengineering, The School of Medicine and the School of Engineering, Trinity College, The University of Dublin, Dublin 2, Ireland.
- School of Mathematical Sciences, Technological University Dublin, Kevin Street, Dublin, Ireland.
- School of Medicine, Trinity College, The University of Dublin, Dublin 2, Ireland.
| | - Saskia M Waechter
- Trinity Centre for Bioengineering, The School of Medicine and the School of Engineering, Trinity College, The University of Dublin, Dublin 2, Ireland
- School of Engineering, Trinity College, The University of Dublin, Dublin 2, Ireland
| | - Isabelle Killane
- Trinity Centre for Bioengineering, The School of Medicine and the School of Engineering, Trinity College, The University of Dublin, Dublin 2, Ireland
- School of Engineering, Trinity College, The University of Dublin, Dublin 2, Ireland
- School of Mechanical and Design Engineering, Technological University Dublin, Bolton Street, Dublin, Ireland
| | - Simon P Kelly
- School of Electrical and Electronic Engineering, University College Dublin, Dublin 4, Ireland
| | - Richard B Reilly
- Trinity Centre for Bioengineering, The School of Medicine and the School of Engineering, Trinity College, The University of Dublin, Dublin 2, Ireland
- School of Engineering, Trinity College, The University of Dublin, Dublin 2, Ireland
- School of Medicine, Trinity College, The University of Dublin, Dublin 2, Ireland
| | - Timothy Lynch
- Dublin Neurological Institute at the Mater Misericordiae University Hospital, 57 Eccles Street, Dublin 7, Ireland
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28
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The Role of Object Individuation in Attention and Visual Processing. J Neurosci 2020; 40:7387-7389. [PMID: 32968027 DOI: 10.1523/jneurosci.1257-20.2020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Revised: 08/16/2020] [Accepted: 08/19/2020] [Indexed: 11/21/2022] Open
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29
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Ouyang G, Zhou C. Characterizing the brain's dynamical response from scalp-level neural electrical signals: a review of methodology development. Cogn Neurodyn 2020; 14:731-742. [PMID: 33101527 DOI: 10.1007/s11571-020-09631-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2020] [Revised: 08/09/2020] [Accepted: 08/27/2020] [Indexed: 01/02/2023] Open
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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Affiliation(s)
- Guang Ouyang
- Faculty of Education, The University of Hong Kong, Pokfulam, Hong Kong Island Hong Kong
| | - Changsong Zhou
- Department of Physics, Centre for Nonlinear Studies, Institute of Computational and Theoretical Studies, Hong Kong Baptist University, Kowloon Tong, Hong Kong
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30
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Monnier A, Dell'Acqua R, Jolicoeur P. Distilling the distinct contralateral and ipsilateral attentional responses to lateral stimuli and the bilateral response to midline stimuli for upper and lower visual hemifield locations. Psychophysiology 2020; 57:e13651. [PMID: 32797636 DOI: 10.1111/psyp.13651] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Revised: 04/13/2020] [Accepted: 06/19/2020] [Indexed: 11/30/2022]
Abstract
A contralateral posterior negativity elicited by lateral oddballs (N2pc) and a bilateral posterior negativity elicited by vertical midline oddballs (bilateral N2) are ERP components reflecting attentional deployment that have been rarely compared. In different tasks, we explored to what extent they reflect similar underlying mechanisms of attention. We used a multiple-frame procedure to present pop-out color oddballs among distractors. A homogeneous condition contained only distractors (0 oddballs) and served as a control condition that was subtracted from oddball-present conditions to isolate attention effects. The number of oddballs and the vertical hemifield containing them (upper vs. lower) were two critical factors. For the lower hemifield, the signal amplitude increased with the number of oddballs, otherwise had similar effects and scalp distributions, suggesting the bilateral N2 acted as a bilateral N2pc and likely reflected similar underlying generators. For the upper hemifield, component amplitude also increased with the number of oddballs, but the scalp distributions were positive and more centered, suggesting inverted generators across the two vertical hemifields. An ipsilateral positivity occurred about 50 ms after a contralateral positivity, similar in magnitude, producing a biphasic contra-minus-ipsi difference wave. Previously reported smaller negative N2pc components for upper hemifield oddballs likely reflected a negative lobe artificially created by the subtraction of a lagged positive ipsilateral response. The results compel us to argue for a systematic separation of data for upper versus lower hemifields in studies of visuo-spatial attention, and the use of an experimental design permitting the separate estimation of contralateral and ipsilateral responses.
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Affiliation(s)
- Anne Monnier
- Département de Neurosciences, Université de Montréal, Montréal, QC, Canada.,Département de psychologie, Centre de recherche en neuropsychologie et cognition (CERNEC), Montréal, QC, Canada
| | | | - Pierre Jolicoeur
- Département de Neurosciences, Université de Montréal, Montréal, QC, Canada.,Département de psychologie, Centre de recherche en neuropsychologie et cognition (CERNEC), Montréal, QC, Canada.,International Laboratory for Brain, Music, and Sound Research (BRAMS), Montreal, QC, Canada.,Centre de recherche de l'Institut universitaire de gériatrie de Montréal (CRIUGM), Montréal, QC, Canada
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31
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Mazzi C, Mazzeo G, Savazzi S. Late Positivity Does Not Meet the Criteria to be Considered a Proper Neural Correlate of Perceptual Awareness. Front Syst Neurosci 2020; 14:36. [PMID: 32733211 PMCID: PMC7358964 DOI: 10.3389/fnsys.2020.00036] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2019] [Accepted: 05/18/2020] [Indexed: 11/19/2022] Open
Abstract
Contrastive analysis has been widely employed in the search for the electrophysiological neural correlates of consciousness. However, despite its clear logic, it has been argued that it may not succeed in isolating neural processes solely involved in the emergence of perceptual awareness. In fact, data from contrastive analysis would be contaminated by potential confounding factors reflecting distinct, though related, processes either preceding or following the conscious perception. At present, the ERP components representing the proper correlates of perceptual awareness still remain to be identified among those correlating with awareness (i.e., Visual Awareness Negativity, VAN and Late Positivity, LP). In order to dissociate visual awareness from post-perceptual confounds specifically related to decision making, we manipulated the response criterion, which affects how a percept is translated into a decision. In particular, while performing an orientation discrimination task, participants were asked to shift their response criterion across sessions. As a consequence, the resulting modulation should concern the ERP component(s) not exclusively reflecting mechanisms regulating the subjective conscious experience itself but rather the processes accompanying it. Electrophysiological results showed that N1 and P3 were sensitive to the response criterion adopted by participants. Additionally, the more the participants shifted their response criterion, the bigger the ERP modulation was; this was consequently indicative of the critical role of these components in the decision-making processes regardless of awareness level. When considering data independently from the response criterion, the aware vs. unaware contrast showed that both VAN and LP were significant. Crucially, the LP component was also modulated by the interaction of awareness and response criterion, while VAN results to be unaffected. In agreement with previous literature, these findings provide evidence supporting the hypothesis that VAN tracks the emergence of visual awareness by encoding the conscious percept, whereas LP reflects the contribution from post-perceptual processes related to response requirements. This excludes a direct functional role of this later component in giving rise to perceptual awareness.
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Affiliation(s)
- Chiara Mazzi
- Perception and Awareness (PandA) Laboratory, Department of Neuroscience, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Gaetano Mazzeo
- Perception and Awareness (PandA) Laboratory, Department of Neuroscience, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Silvia Savazzi
- Perception and Awareness (PandA) Laboratory, Department of Neuroscience, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
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32
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Evidence accumulation during perceptual decision-making is sensitive to the dynamics of attentional selection. Neuroimage 2020; 220:117093. [PMID: 32599268 DOI: 10.1016/j.neuroimage.2020.117093] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2019] [Revised: 06/19/2020] [Accepted: 06/22/2020] [Indexed: 11/20/2022] Open
Abstract
The ability to select and combine multiple sensory inputs in support of accurate decisions is a hallmark of adaptive behaviour. Attentional selection is often needed to prioritize task-relevant stimuli relative to irrelevant, potentially distracting stimuli. As most studies of perceptual decision-making to date have made use of task-relevant stimuli only, relatively little is known about how attention modulates decision making. To address this issue, we developed a novel 'integrated' decision-making task, in which participants judged the average direction of successive target motion signals while ignoring concurrent and spatially overlapping distractor motion signals. In two experiments that varied the role of attentional selection, we used regression to quantify the influence of target and distractor stimuli on behaviour. Using electroencephalography, we characterised the neural correlates of decision making, attentional selection and feature-specific responses to target and distractor signals. While targets strongly influenced perceptual decisions and associated neural activity, we also found that concurrent and spatially coincident distractors exerted a measurable bias on both behaviour and brain activity. Our findings suggest that attention operates as a real-time but imperfect filter during perceptual decision-making by dynamically modulating the contributions of task-relevant and irrelevant sensory inputs.
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33
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The interplay between multisensory integration and perceptual decision making. Neuroimage 2020; 222:116970. [PMID: 32454204 DOI: 10.1016/j.neuroimage.2020.116970] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2019] [Revised: 03/23/2020] [Accepted: 05/15/2020] [Indexed: 01/15/2023] Open
Abstract
Facing perceptual uncertainty, the brain combines information from different senses to make optimal perceptual decisions and to guide behavior. However, decision making has been investigated mostly in unimodal contexts. Thus, how the brain integrates multisensory information during decision making is still unclear. Two opposing, but not mutually exclusive, scenarios are plausible: either the brain thoroughly combines the signals from different modalities before starting to build a supramodal decision, or unimodal signals are integrated during decision formation. To answer this question, we devised a paradigm mimicking naturalistic situations where human participants were exposed to continuous cacophonous audiovisual inputs containing an unpredictable signal cue in one or two modalities and had to perform a signal detection task or a cue categorization task. First, model-based analyses of behavioral data indicated that multisensory integration takes place alongside perceptual decision making. Next, using supervised machine learning on concurrently recorded EEG, we identified neural signatures of two processing stages: sensory encoding and decision formation. Generalization analyses across experimental conditions and time revealed that multisensory cues were processed faster during both stages. We further established that acceleration of neural dynamics during sensory encoding and decision formation was directly linked to multisensory integration. Our results were consistent across both signal detection and categorization tasks. Taken together, the results revealed a continuous dynamic interplay between multisensory integration and decision making processes (mixed scenario), with integration of multimodal information taking place both during sensory encoding as well as decision formation.
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34
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Evidence accumulation during perceptual decisions in humans varies as a function of dorsal frontoparietal organization. Nat Hum Behav 2020; 4:844-855. [PMID: 32313233 DOI: 10.1038/s41562-020-0863-4] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2019] [Accepted: 03/16/2020] [Indexed: 11/08/2022]
Abstract
Animal neurophysiological studies have identified neural signals within dorsal frontoparietal areas that trace a perceptual decision by accumulating sensory evidence over time and trigger action upon reaching a threshold. Although analogous accumulation-to-bound signals are identifiable on extracranial human electroencephalography, their cortical origins remain unknown. Here neural metrics of human evidence accumulation, predictive of the speed of perceptual reports, were isolated using electroencephalography and related to dorsal frontoparietal network (dFPN) connectivity using diffusion and resting-state functional magnetic resonance imaging. The build-up rate of evidence accumulation mediated the relationship between the white matter macrostructure of dFPN pathways and the efficiency of perceptual reports. This association between steeper build-up rates of evidence accumulation and the dFPN was recapitulated in the resting-state networks. Stronger connectivity between dFPN regions is thus associated with faster evidence accumulation and speeded perceptual decisions. Our findings identify an integrated network for perceptual decisions that may be targeted for neurorehabilitation in cognitive disorders.
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35
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Devine CA, Gaffney C, Loughnane GM, Kelly SP, O'Connell RG. The role of premature evidence accumulation in making difficult perceptual decisions under temporal uncertainty. eLife 2019; 8:e48526. [PMID: 31774396 PMCID: PMC6904213 DOI: 10.7554/elife.48526] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2019] [Accepted: 11/26/2019] [Indexed: 12/31/2022] Open
Abstract
The computations and neural processes underpinning decision making have primarily been investigated using highly simplified tasks in which stimulus onsets cue observers to start accumulating choice-relevant information. Yet, in daily life we are rarely afforded the luxury of knowing precisely when choice-relevant information will appear. Here, we examined neural indices of decision formation while subjects discriminated subtle stimulus feature changes whose timing relative to stimulus onset ('foreperiod') was uncertain. Joint analysis of behavioural error patterns and neural decision signal dynamics indicated that subjects systematically began the accumulation process before any informative evidence was presented, and further, that accumulation onset timing varied systematically as a function of the foreperiod of the preceding trial. These results suggest that the brain can adjust to temporal uncertainty by strategically modulating accumulation onset timing according to statistical regularities in the temporal structure of the sensory environment with particular emphasis on recent experience.
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Affiliation(s)
- Ciara A Devine
- Trinity College Institute of Neuroscience and School of PsychologyThe University of Dublin, Trinity CollegeDublinIreland
| | - Christine Gaffney
- Trinity College Institute of Neuroscience and School of PsychologyThe University of Dublin, Trinity CollegeDublinIreland
| | | | - Simon P Kelly
- School of Electrical and Electronic Engineering and UCD Centre for Biomedical EngineeringUniversity College DublinDublinIreland
| | - Redmond G O'Connell
- Trinity College Institute of Neuroscience and School of PsychologyThe University of Dublin, Trinity CollegeDublinIreland
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36
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Nunez MD, Gosai A, Vandekerckhove J, Srinivasan R. The latency of a visual evoked potential tracks the onset of decision making. Neuroimage 2019; 197:93-108. [DOI: 10.1016/j.neuroimage.2019.04.052] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2018] [Revised: 01/23/2019] [Accepted: 04/18/2019] [Indexed: 12/30/2022] Open
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37
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The EEG signature of sensory evidence accumulation during decision formation closely tracks subjective perceptual experience. Sci Rep 2019; 9:4949. [PMID: 30894558 PMCID: PMC6426990 DOI: 10.1038/s41598-019-41024-4] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2018] [Accepted: 02/26/2019] [Indexed: 12/30/2022] Open
Abstract
How neural representations of low-level visual information are accessed by higher-order processes to inform decisions and give rise to conscious experience is a longstanding question. Research on perceptual decision making has revealed a late event-related EEG potential (the Centro-Parietal Positivity, CPP) to be a correlate of the accumulation of sensory evidence. We tested how this evidence accumulation signal relates to externally presented (physical) and internally experienced (subjective) sensory evidence. Our results show that the known relationship between the physical strength of the external evidence and the evidence accumulation signal (reflected in the CPP amplitude) is mediated by the level of subjective experience of stimulus strength. This shows that the CPP closely tracks the subjective perceptual evidence, over and above the physically presented evidence. We conclude that a remarkably close relationship exists between the evidence accumulation process (i.e. CPP) and subjective perceptual experience, suggesting that neural decision processes and components of conscious experience are tightly linked.
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38
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van Kempen J, Loughnane GM, Newman DP, Kelly SP, Thiele A, O'Connell RG, Bellgrove MA. Behavioural and neural signatures of perceptual decision-making are modulated by pupil-linked arousal. eLife 2019; 8:42541. [PMID: 30882347 PMCID: PMC6450670 DOI: 10.7554/elife.42541] [Citation(s) in RCA: 44] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2018] [Accepted: 03/16/2019] [Indexed: 01/21/2023] Open
Abstract
The timing and accuracy of perceptual decision-making is exquisitely sensitive to fluctuations in arousal. Although extensive research has highlighted the role of various neural processing stages in forming decisions, our understanding of how arousal impacts these processes remains limited. Here we isolated electrophysiological signatures of decision-making alongside signals reflecting target selection, attentional engagement and motor output and examined their modulation as a function of tonic and phasic arousal, indexed by baseline and task-evoked pupil diameter, respectively. Reaction times were shorter on trials with lower tonic, and higher phasic arousal. Additionally, these two pupil measures were predictive of a unique set of EEG signatures that together represent multiple information processing steps of decision-making. Finally, behavioural variability associated with fluctuations in tonic and phasic arousal, indicative of neuromodulators acting on multiple timescales, was mediated by its effects on the EEG markers of attentional engagement, sensory processing and the variability in decision processing. Driving along a busy street requires you to constantly monitor the behavior of other road users. You need to be able to spot and avoid the car that suddenly changes lane, or the pedestrian who steps out in front of you. How fast you can react to such events depends in part on your brain's level of alertness, or 'arousal'. This in turn depends on chemicals within the brain called neuromodulators. Neuromodulators are a type of neurotransmitter. But whereas other neurotransmitters enable brain cells to signal to each other, neuromodulators turn the volume of these signals up or down. The activity of brain regions that produce neuromodulators varies over time, leading to changes in brain arousal. These changes take place over different time scales. Sudden unexpected events, such as those on the busy street above, trigger sub-second changes in arousal. But arousal levels also show spontaneous fluctuations over minutes to hours. We can follow these changes in real-time by looking into a participant’s eyes. This is because the brain regions that produce neuromodulators also control pupil size. Van Kempen et al. have now combined measurements of pupil size with recordings of electrical brain activity. Healthy volunteers learned to press a button as soon as a target appeared on a screen. The larger a volunteer’s pupils were before the target appeared, the more slowly the volunteer responded on that trial. Large baseline pupil size is thought to indicate a high baseline level of brain arousal. By contrast, the larger the increase in pupil size in response to the target, the faster the volunteer responded on that trial. This increase in pupil size is thought to reflect an increase in brain arousal. The recordings of brain activity provided clues to the underlying mechanisms. In trials with large baseline pupil size – and therefore high baseline arousal – the volunteers’ brains showed more variable responses to the target. But in trials with a large increase in pupil size – and a large increase in arousal – the volunteers’ brains showed less variable responses, as well as stronger signals related to attention. Neuromodulators thus act on different timescales to influence different aspects of cognitive performance, including attention and target detection. Fluctuating levels of neuromodulator activity may help explain the variability in our behavior. Monitoring pupil size is one way to gain insights into the mechanisms that bring about these changes in neuromodulator activity.
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Affiliation(s)
- Jochem van Kempen
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, United Kingdom.,Monash Institute for Cognitive and Clinical Neurosciences, School of Psychological Sciences, Monash University, Melbourne, Australia
| | - Gerard M Loughnane
- School of Engineering, Trinity College Dublin, Dublin, Ireland.,Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Daniel P Newman
- Monash Institute for Cognitive and Clinical Neurosciences, School of Psychological Sciences, Monash University, Melbourne, Australia
| | - Simon P Kelly
- School of Electrical and Electronic Engineering, University College Dublin, Dublin, Ireland
| | - Alexander Thiele
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Redmond G O'Connell
- Monash Institute for Cognitive and Clinical Neurosciences, School of Psychological Sciences, Monash University, Melbourne, Australia.,Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland.,School of Psychology, Trinity College Dublin, Dublin, Ireland
| | - Mark A Bellgrove
- Monash Institute for Cognitive and Clinical Neurosciences, School of Psychological Sciences, Monash University, Melbourne, Australia.,School of Psychology, Trinity College Dublin, Dublin, Ireland
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39
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Loughnane GM, Brosnan MB, Barnes JJM, Dean A, Nandam SL, O'Connell RG, Bellgrove MA. Catecholamine Modulation of Evidence Accumulation during Perceptual Decision Formation: A Randomized Trial. J Cogn Neurosci 2019; 31:1044-1053. [PMID: 30883291 DOI: 10.1162/jocn_a_01393] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
Recent behavioral modeling and pupillometry studies suggest that neuromodulatory arousal systems play a role in regulating decision formation but neurophysiological support for these observations is lacking. We employed a randomized, double-blinded, placebo-controlled, crossover design to probe the impact of pharmacological enhancement of catecholamine levels on perceptual decision-making. Catecholamine levels were manipulated using the clinically relevant drugs methylphenidate and atomoxetine, and their effects were compared with those of citalopram and placebo. Participants performed a classic EEG oddball paradigm that elicits the P3b, a centro-parietal potential that has been shown to trace evidence accumulation, under each of the four drug conditions. We found that methylphenidate and atomoxetine administration shortened RTs to the oddball targets. The neural basis of this behavioral effect was an earlier P3b peak latency, driven specifically by an increase in its buildup rate without any change in its time of onset or peak amplitude. This study provides neurophysiological evidence for the catecholaminergic enhancement of a discrete aspect of human decision-making, that is, evidence accumulation. Our results also support theoretical accounts suggesting that catecholamines may enhance cognition via increases in neural gain.
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Affiliation(s)
| | | | | | | | | | | | - Mark A Bellgrove
- Trinity College, University of Dublin.,Monash University.,University of Queensland
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40
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van Vugt MK, Beulen MA, Taatgen NA. Relation between centro-parietal positivity and diffusion model parameters in both perceptual and memory-based decision making. Brain Res 2019; 1715:1-12. [PMID: 30876858 DOI: 10.1016/j.brainres.2019.03.008] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2018] [Revised: 03/04/2019] [Accepted: 03/11/2019] [Indexed: 11/17/2022]
Abstract
Several studies have suggested that the centro-parietal positivity (CPP), an EEG potential occurring approximately 500 ms post-stimulus, reflects the accumulation of evidence for making a decision. Yet, most previous studies of the CPP focused exclusively on perceptual decisions with very simple stimuli. In this study, we examined how the dynamics of the CPP depended on the type of decision being made, and whether its slope was related to parameters of an accumulator model of decision making. We show initial evidence that memory- and perceptual decisions about carefully-controlled face stimuli exhibit similar dynamics, but offset by a time difference in decision onset. Importantly, the individual-trial slopes of the CPP are related to the accumulator model's drift parameter. These findings help to further understand the role of the CPP across different kinds of decisions.
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Affiliation(s)
- Marieke K van Vugt
- Bernoulli Institute of Mathematics, Computer Science and Artificial Intelligence, University of Groningen, Nijenborgh 9, 9747 AG Groningen, The Netherlands.
| | - Marijke A Beulen
- Bernoulli Institute of Mathematics, Computer Science and Artificial Intelligence, University of Groningen, Nijenborgh 9, 9747 AG Groningen, The Netherlands
| | - Niels A Taatgen
- Bernoulli Institute of Mathematics, Computer Science and Artificial Intelligence, University of Groningen, Nijenborgh 9, 9747 AG Groningen, The Netherlands
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41
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Implicit visual cues tune oscillatory motor activity during decision-making. Neuroimage 2019; 186:424-436. [DOI: 10.1016/j.neuroimage.2018.11.027] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2018] [Revised: 11/05/2018] [Accepted: 11/16/2018] [Indexed: 12/21/2022] Open
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42
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Drisdelle BL, Jolicœur P. Stimulus- and Response-locked Posterior Contralateral Negativity Bisect Cognitive Operations in Visual Search. J Cogn Neurosci 2018; 31:574-591. [PMID: 30566367 DOI: 10.1162/jocn_a_01364] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
We explored the flow of information during visual search by examining activity indexing visual attention (N2pc) and the subsequent processing of the selected objects in visual short-term memory (SPCN) time-locked to stimulus presentation and to the motor response. We measured event-related activity at posterior sites (PO7/PO8) for 96 participants during a simple visual search task. A response-locked posterior contralateral negativity (RLpcN) was observed with a scalp distribution similar to that of the N2pc and SPCN. The RLpcN was compared with the stimulus-locked activity (N2pc and SPCN) across experimental manipulations (targets were either closer or farther from fixation in visual space, and the response was either more frequent [75%] or less frequent [25%]) and across response speeds (EEG data were separated into tertiles by RT both within-subjects and between-subjects). The leading edge and early portion of the RLpcN appeared to reflect the initial deployment of attention (N2pc), whereas the later portion (up to peak amplitude) reflected subsequent processing of visual information (SPCN). SPCN and RLpcN also had similar modulations in amplitude for both analyses. Moreover, whereas very small N2pc and SPCN onset latency differences were observed when data were separated into tertiles by RT, there were large onset differences for the RLpcN, with earlier RLpcN onsets for longer RTs, suggesting that RT variance is in large determined by processing after the initial deployment of attention. The results show how we can bisect processing responsible for variations in RT relative to the onset of visual spatial attention.
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Affiliation(s)
- Brandi Lee Drisdelle
- Université de Montréal.,International Laboratory for Brain, Music, and Sound Research (BRAMS), Montreal, Canada.,Institut Universitaire de Gériatrie de Montréal (CRIUGM)
| | - Pierre Jolicœur
- Université de Montréal.,International Laboratory for Brain, Music, and Sound Research (BRAMS), Montreal, Canada.,Institut Universitaire de Gériatrie de Montréal (CRIUGM)
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43
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Reconciling age-related changes in behavioural and neural indices of human perceptual decision-making. Nat Hum Behav 2018; 2:955-966. [PMID: 30988441 DOI: 10.1038/s41562-018-0465-6] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2018] [Accepted: 10/02/2018] [Indexed: 01/08/2023]
Abstract
Ageing impacts on decision-making behaviour across a range of cognitive tasks and scenarios. Computational modelling has proved valuable in providing mechanistic interpretations of these age-related differences; however, the extent to which model parameter differences accurately reflect changes to the underlying neural computations remains unclear. Here, we report that age-related effects on neural signatures of decision formation are inconsistent with behavioural fits derived from a prominent accumulation-to-bound model. Most notably, model-predicted bound differences were absent neurophysiologically. However, constraining the model to match the decision-predictive elements of the brain signals provided more parsimonious fits to behaviour and generated predictions regarding the neural data that were empirically validated. These included a task-dependent slowing of evidence accumulation among older adults and reduced between-trial accumulation rate variability, which was linked to enhanced attentional engagement. Our findings highlight how combining neurophysiological measurements with computational modelling can yield unique insights into group differences in neural decision mechanisms.
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44
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O'Connell RG, Shadlen MN, Wong-Lin K, Kelly SP. Bridging Neural and Computational Viewpoints on Perceptual Decision-Making. Trends Neurosci 2018; 41:838-852. [PMID: 30007746 PMCID: PMC6215147 DOI: 10.1016/j.tins.2018.06.005] [Citation(s) in RCA: 74] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2018] [Revised: 06/12/2018] [Accepted: 06/13/2018] [Indexed: 12/22/2022]
Abstract
Sequential sampling models have provided a dominant theoretical framework guiding computational and neurophysiological investigations of perceptual decision-making. While these models share the basic principle that decisions are formed by accumulating sensory evidence to a bound, they come in many forms that can make similar predictions of choice behaviour despite invoking fundamentally different mechanisms. The identification of neural signals that reflect some of the core computations underpinning decision formation offers new avenues for empirically testing and refining key model assumptions. Here, we highlight recent efforts to explore these avenues and, in so doing, consider the conceptual and methodological challenges that arise when seeking to infer decision computations from complex neural data.
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Affiliation(s)
- Redmond G O'Connell
- Trinity College Institute of Neuroscience and School of Psychology, Trinity College Dublin, Ireland.
| | - Michael N Shadlen
- Howard Hughes Medical Institute and Department of Neuroscience, Columbia University, New York, NY 10032, USA; Zuckerman Mind Brain Behaviour Institute and Kavli Institute for Brain Science, Columbia University, New York, NY 10032, USA
| | - KongFatt Wong-Lin
- Intelligent Systems Research Centre, University of Ulster, Magee Campus, Northland Road, Derry, BT48 7JL, UK
| | - Simon P Kelly
- School of Electrical and Electronic Engineering, University College Dublin, Dublin, Ireland.
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45
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Having More Choices Changes How Human Observers Weight Stable Sensory Evidence. J Neurosci 2018; 38:8635-8649. [PMID: 30143576 DOI: 10.1523/jneurosci.0440-18.2018] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2018] [Revised: 08/07/2018] [Accepted: 08/14/2018] [Indexed: 02/04/2023] Open
Abstract
Decision-making becomes slower when more choices are available. Existing models attribute this slowing to poor sensory processing, to attenuated rates of sensory evidence accumulation, or to increases in the amount of evidence required before committing to a decision (a higher decision threshold). However, studies have not isolated the effects of having more choices on sensory and decision-related processes from changes in task difficulty and divided attention. Here, we controlled task difficulty while independently manipulating the distribution of attention and the number of choices available to male and female human observers. We used EEG to measure steady-state visually evoked potentials (SSVEPs) and a frontal late positive deflection (LPD), EEG markers of sensory and postsensory decision-related processes, respectively. We found that dividing attention decreased SSVEP and LPD amplitudes, consistent with dampened sensory responses and slower rates of evidence accumulation, respectively. In contrast, having more choices did not alter SSVEP amplitude and led to a larger LPD. These results suggest that having more options largely spares early sensory processing and slows down decision-making via a selective increase in decision thresholds.SIGNIFICANCE STATEMENT When more choices are available, decision-making becomes slower. We tested whether this phenomenon is due to poor sensory processing, to reduced rates of evidence accumulation, or to increases in the amount of evidence required before committing to a decision (a higher decision threshold). We measured choice modulations of sensory and decision-related neural responses using EEG. We also minimized potential confounds from changes in the distribution of attention and task difficulty, which often covary with having more choices. Dividing attention reduced the activity levels of both sensory and decision-related responses. However, having more choices did not change sensory processing and led to larger decision-related responses. These results suggest that having more choices spares sensory processing and selectively increases decision thresholds.
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Single Trial Plasticity in Evidence Accumulation Underlies Rapid Recalibration to Asynchronous Audiovisual Speech. Sci Rep 2018; 8:12499. [PMID: 30131578 PMCID: PMC6104055 DOI: 10.1038/s41598-018-30414-9] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2018] [Accepted: 07/20/2018] [Indexed: 01/12/2023] Open
Abstract
Asynchronous arrival of audiovisual information at the peripheral sensory organs is a ubiquitous property of signals in the natural environment due to differences in the propagation time of light and sound. As these cues are constantly changing their distance from the observer, rapid adaptation to asynchronies is crucial for their appropriate integration. We investigated the neural basis of rapid recalibration to asynchronous audiovisual speech in humans using a combination of psychophysics, drift diffusion modeling, and electroencephalography (EEG). Consistent with previous reports, we found that perception of audiovisual temporal synchrony depends on the temporal ordering of the previous trial. Drift diffusion modelling indicated that this recalibration effect is well accounted for by changes in the rate of evidence accumulation (i.e. drift rate). Neural responses as indexed via evoked potentials were similarly found to vary based on the temporal ordering of the previous trial. Within and across subject correlations indicated that the observed changes in drift rate and the modulation of evoked potential magnitude were related. These results indicate that the rate and direction of evidence accumulation are affected by immediate sensory history and that these changes contribute to single trial recalibration to audiovisual temporal asynchrony.
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Rungratsameetaweemana N, Itthipuripat S, Salazar A, Serences JT. Expectations Do Not Alter Early Sensory Processing during Perceptual Decision-Making. J Neurosci 2018; 38:5632-5648. [PMID: 29773755 PMCID: PMC8174137 DOI: 10.1523/jneurosci.3638-17.2018] [Citation(s) in RCA: 49] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2017] [Revised: 04/27/2018] [Accepted: 05/04/2018] [Indexed: 11/21/2022] Open
Abstract
Two factors play important roles in shaping perception: the allocation of selective attention to behaviorally relevant sensory features, and prior expectations about regularities in the environment. Signal detection theory proposes distinct roles of attention and expectation on decision-making such that attention modulates early sensory processing, whereas expectation influences the selection and execution of motor responses. Challenging this classic framework, recent studies suggest that expectations about sensory regularities enhance the encoding and accumulation of sensory evidence during decision-making. However, it is possible, that these findings reflect well documented attentional modulations in visual cortex. Here, we tested this framework in a group of male and female human participants by examining how expectations about stimulus features (orientation and color) and expectations about motor responses impacted electroencephalography (EEG) markers of early sensory processing and the accumulation of sensory evidence during decision-making (the early visual negative potential and the centro-parietal positive potential, respectively). We first demonstrate that these markers are sensitive to changes in the amount of sensory evidence in the display. Then we show, counter to recent findings, that neither marker is modulated by either feature or motor expectations, despite a robust effect of expectations on behavior. Instead, violating expectations about likely sensory features and motor responses impacts posterior alpha and frontal theta oscillations, signals thought to index overall processing time and cognitive conflict. These findings are inconsistent with recent theoretical accounts and suggest instead that expectations primarily influence decisions by modulating post-perceptual stages of information processing.SIGNIFICANCE STATEMENT Expectations about likely features or motor responses play an important role in shaping behavior. Classic theoretical frameworks posit that expectations modulate decision-making by biasing late stages of decision-making including the selection and execution of motor responses. In contrast, recent accounts suggest that expectations also modulate decisions by improving the quality of early sensory processing. However, these effects could instead reflect the influence of selective attention. Here we examine the effect of expectations about sensory features and motor responses on a set of electroencephalography (EEG) markers that index early sensory processing and later post-perceptual processing. Counter to recent empirical results, expectations have little effect on early sensory processing but instead modulate EEG markers of time-on-task and cognitive conflict.
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Affiliation(s)
| | - Sirawaj Itthipuripat
- Neurosciences Graduate Program, University of California, San Diego, La Jolla, California 92093-0109
- Learning Institute, King Mongkut's University of Technology Thonburi, Bangkok, Thailand 10140
- Department of Psychology, Vanderbilt University, Nashville, Tennessee 37235
| | - Annalisa Salazar
- Department of Psychology, University of California, San Diego, La Jolla, California 92093-0109, and
| | - John T Serences
- Neurosciences Graduate Program, University of California, San Diego, La Jolla, California 92093-0109,
- Department of Psychology, University of California, San Diego, La Jolla, California 92093-0109, and
- Kavli Institute for Brain and Mind, University of California, San Diego, La Jolla, California 92093-0109
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Antagonistic Interactions Between Microsaccades and Evidence Accumulation Processes During Decision Formation. J Neurosci 2018; 38:2163-2176. [PMID: 29371320 DOI: 10.1523/jneurosci.2340-17.2018] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2017] [Revised: 12/20/2017] [Accepted: 01/14/2018] [Indexed: 02/05/2023] Open
Abstract
Despite their small size, microsaccades can impede stimulus detections if executed at inopportune times. Although it has been shown that microsaccades evoke both inhibitory and excitatory responses across different visual regions, their impact on the higher-level neural decision processes that bridge sensory responses to action selection has yet to be examined. Here, we show that when human observers monitor stimuli for subtle feature changes, the occurrence of microsaccades long after (up to 800 ms) change onset predicts slower reaction times and this is accounted for by momentary suppression of neural signals at each key stage of decision formation: visual evidence encoding, evidence accumulation, and motor preparation. Our data further reveal that, independent of the timing of the change events, the onset of neural decision formation coincides with a systematic inhibition of microsaccade production, persisting until the perceptual report is executed. Our combined behavioral and neural measures highlight antagonistic interactions between microsaccade occurrence and evidence accumulation during visual decision-making tasks.SIGNIFICANCE STATEMENT When fixating on a location in space, we frequently make tiny eye movements called microsaccades. In the present study, we show that these microsaccades impede our ability to make perceptual decisions about visual stimuli and this impediment specifically occurs via the disruption of several processing levels of the sensorimotor network: the encoding of visual evidence itself, the accumulation of visual evidence toward a response, and effector-selective motor preparation. Furthermore, we show that the production of microsaccades is inhibited during the perceptual decision, possibly as a counteractive measure to mitigate their negative effect on behavior in this context. The combined behavioral and neural measures used in this study provide strong and novel evidence for the interaction of fixational eye movements and the perceptual decision-making process.
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Dully J, McGovern DP, O'Connell RG. The impact of natural aging on computational and neural indices of perceptual decision making: A review. Behav Brain Res 2018; 355:48-55. [PMID: 29432793 DOI: 10.1016/j.bbr.2018.02.001] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2017] [Revised: 02/01/2018] [Accepted: 02/01/2018] [Indexed: 01/12/2023]
Abstract
It is well established that natural aging negatively impacts on a wide variety of cognitive functions and research has sought to identify core neural mechanisms that may account for these disparate changes. A central feature of any cognitive task is the requirement to translate sensory information into an appropriate action - a process commonly known as perceptual decision making. While computational, psychophysical, and neurophysiological research has made substantial progress in establishing the key computations and neural mechanisms underpinning decision making, it is only relatively recently that this knowledge has begun to be applied to research on aging. The purpose of this review is to provide an overview of this work which is beginning to offer new insights into the core psychological processes that mediate age-related cognitive decline in adults aged 65 years and over. Mathematical modelling studies have consistently reported that older adults display longer non-decisional processing times and implement more conservative decision policies than their younger counterparts. However, there are limits on what we can learn from behavioural modeling alone and neurophysiological analyses can play an essential role in empirically validating model predictions and in pinpointing the precise neural mechanisms that are impacted by aging. Although few studies to date have explicitly examined correspondences between computational models and neural data with respect to cognitive aging, neurophysiological studies have already highlighted age-related changes at multiple levels of the sensorimotor hierarchy that are likely to be consequential for decision making behaviour. Here, we provide an overview of this literature and suggest some future directions for the field.
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Affiliation(s)
- Jessica Dully
- Trinity College Dublin Institute of Neuroscience and School of Psychology, Trinity College Dublin, Dublin 2, Ireland.
| | - David P McGovern
- Trinity College Dublin Institute of Neuroscience and School of Psychology, Trinity College Dublin, Dublin 2, Ireland
| | - Redmond G O'Connell
- Trinity College Dublin Institute of Neuroscience and School of Psychology, Trinity College Dublin, Dublin 2, Ireland
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50
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Laube I, Matthews N, Dean AJ, O'Connell RG, Mattingley JB, Bellgrove MA. Scopolamine Reduces Electrophysiological Indices of Distractor Suppression: Evidence from a Contingent Capture Task. Front Neural Circuits 2017; 11:99. [PMID: 29270112 PMCID: PMC5723636 DOI: 10.3389/fncir.2017.00099] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2017] [Accepted: 11/20/2017] [Indexed: 11/13/2022] Open
Abstract
Limited resources for the in-depth processing of external stimuli make it necessary to select only relevant information from our surroundings and to ignore irrelevant stimuli. Attentional mechanisms facilitate this selection via top-down modulation of stimulus representations in the brain. Previous research has indicated that acetylcholine (ACh) modulates this influence of attention on stimulus processing. However, the role of muscarinic receptors as well as the specific mechanism of cholinergic modulation remains unclear. Here we investigated the influence of ACh on feature-based, top-down control of stimulus processing via muscarinic receptors by using a contingent capture paradigm which specifically tests attentional shifts toward uninformative cue stimuli which display one of the target defining features In a double-blind, placebo controlled study we measured the impact of the muscarinic receptor antagonist scopolamine on behavioral and electrophysiological measures of contingent attentional capture. The results demonstrated all the signs of functional contingent capture, i.e., attentional shifts toward cued locations reflected in increased amplitudes of N1 and N2Pc components, under placebo conditions. However, scopolamine did not affect behavioral or electrophysiological measures of contingent capture. Instead, scopolamine reduced the amplitude of the distractor-evoked Pd component which has recently been associated with active suppression of irrelevant distractor information. The findings suggest a general cholinergic modulation of top-down control during distractor processing.
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Affiliation(s)
- Inga Laube
- Queensland Brain Institute and School of Psychology, The University of QueenslandBrisbane, QLD, Australia.,ImpAct Team, Lyon Neuroscience Research Center, INSERM U1028, CRNS-UMR5292Lyon, France
| | - Natasha Matthews
- ImpAct Team, Lyon Neuroscience Research Center, INSERM U1028, CRNS-UMR5292Lyon, France
| | - Angela J Dean
- Queensland Brain Institute and School of Psychology, The University of QueenslandBrisbane, QLD, Australia
| | - Redmond G O'Connell
- School of Psychological Sciences and Monash Institute of Cognitive and Clinical Neurosciences, Monash UniversityMelbourne, VIC, Australia.,Trinity College Dublin, Trinity College Institute of NeuroscienceDublin, Ireland
| | - Jason B Mattingley
- Queensland Brain Institute and School of Psychology, The University of QueenslandBrisbane, QLD, Australia
| | - Mark A Bellgrove
- Queensland Brain Institute and School of Psychology, The University of QueenslandBrisbane, QLD, Australia.,School of Psychological Sciences and Monash Institute of Cognitive and Clinical Neurosciences, Monash UniversityMelbourne, VIC, Australia
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