Change point detection with multiple alternatives reveals parallel evaluation of the same stream of evidence along distinct timescales

Booras, Alexa; Stevenson, Tanner; McCormack, Connor N.; Rhoads, Marie E.

doi:10.1038/s41598-021-92470-y

Cited by 4 publications

(4 citation statements)

References 56 publications

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“…In particular, the well-known P300 component has long been argued to be associated with detection of statistical surprise (Donchin, 1981;Duncan-Johnson and Donchin, 1977;Mars et al, 2008;Squires et al, 1976) or, more recently, a correlate of a continuous time-evolving decision variable (Twomey et al, 2015) that is equivalent to the centroparietal positivity (Kelly and O'Connell, 2013;O'Connell et al, 2012). Our centroparietal responses to |Devidence| (Figure 6b) are consistent with a changepoint detection account of continuous decision making (Booras et al, 2021), in which decision-relevant input (Figure 8) is evaluated for a change in latent state from a baseline period to a response period (Nassar et al, 2019). This account would also explain why these signals are enhanced when response periods are rarer, as a large |Devidence| is more statistically surprising when response periods are rare than when they are common.…”

Section: Discussionsupporting

confidence: 78%

Quantifying decision-making in dynamic, continuously evolving environments

Ruesseler

Weber

Marshall

et al. 2022

Preprint

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During perceptual decision-making tasks, centroparietal EEG potentials report an evidence accumulation-to-bound process that is time locked to trial onset. However, decisions in real-world environments are rarely confined to discrete trials; they instead unfold continuously, with accumulation of time-varying evidence being recency-weighted towards its immediate past. Confronted with time-varying stimuli, humans can appropriately adapt their weighting of recent evidence according to the statistics of the environment. The neural mechanisms supporting this adaptation currently remain unclear. Here, we show that humans' ability to adapt evidence weighting to different sensory environments is reflected in changes in centroparietal EEG potentials. We use a novel continuous task design to show that the Centroparietal Positivity (CPP) becomes more sensitive to fluctuations in sensory evidence when large shifts in evidence are less frequent, and is primarily sensitive to fluctuations in decision-relevant (not decision-irrelevant) sensory input. A complementary triphasic component over parietal cortex encodes the sum of recently accumulated sensory evidence, and its magnitude covaries with the duration over which different individuals integrate sensory evidence. Our findings reveal how adaptations in centroparietal responses reflect flexibility in evidence accumulation to the statistics of dynamic sensory environments.

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Section: Discussionsupporting

confidence: 78%

Quantifying decision-making in dynamic, continuously evolving environments

Ruesseler

Weber

Marshall

et al. 2022

Preprint

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show abstract

“…In particular, the well-known P300 component has long been argued to be associated with detection of statistical surprise ( Donchin, 1981 ; Duncan-Johnson and Donchin, 1977 ; Mars et al, 2008 ; Squires et al, 1976 ) or, more recently, a correlate of a continuous time-evolving decision variable ( Twomey et al, 2015 ) that is equivalent to the CPP ( Kelly and O’Connell, 2013 ; O’Connell et al, 2012 ). Our centroparietal responses to |Δevidence| ( Figure 6b ) are consistent with a changepoint detection account of continuous decision-making ( Booras et al, 2021 ), in which decision-relevant input ( Figure 8 ) is evaluated for a change in latent state from a baseline period to a response period ( Nassar et al, 2019 ). This account would also explain why these signals are enhanced when response periods are rarer as a large |Δevidence| is more statistically surprising when response periods are rare than when they are common.…”

Section: Discussionsupporting

confidence: 73%

Quantifying decision-making in dynamic, continuously evolving environments

Ruesseler,

Weber,

Marshall

et al. 2023

eLife

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During perceptual decision-making tasks, centroparietal electroencephalographic (EEG) potentials report an evidence accumulation-to-bound process that is time locked to trial onset. However, decisions in real-world environments are rarely confined to discrete trials; they instead unfold continuously, with accumulation of time-varying evidence being recency-weighted towards its immediate past. The neural mechanisms supporting recency-weighted continuous decision-making remain unclear. Here, we use a novel continuous task design to study how the centroparietal positivity (CPP) adapts to different environments that place different constraints on evidence accumulation. We show that adaptations in evidence weighting to these different environments are reflected in changes in the CPP. The CPP becomes more sensitive to fluctuations in sensory evidence when large shifts in evidence are less frequent, and the potential is primarily sensitive to fluctuations in decision-relevant (not decision-irrelevant) sensory input. A complementary triphasic component over occipito-parietal cortex encodes the sum of recently accumulated sensory evidence, and its magnitude covaries with parameters describing how different individuals integrate sensory evidence over time. A computational model based on leaky evidence accumulation suggests that these findings can be accounted for by a shift in decision threshold between different environments, which is also reflected in the magnitude of pre-decision EEG activity. Our findings reveal how adaptations in EEG responses reflect flexibility in evidence accumulation to the statistics of dynamic sensory environments.

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“…It has been demonstrated that different evidence integration strategies can be explained by specific differences in behavioural paradigms. Among important features that influence weighting profiles are the division of evidence during a trial (Bronfman et al, 2016;Levi et al, 2018;Raposo et al, 2012) and choice expectation (Booras et al, 2021;Talluri et al, 2021). When stimulus information is equally informative throughout the trial (Kiani et al, 2008;Levi et al, 2018) and the observer is able to report the decision at any time, like here, there is no need to integrate late information after the decision has been made.…”

Section: Discussionmentioning

confidence: 99%

“…Different strategies have been revealed for studying sensory evidence accumulation. A number of studies using fluctuating visual information (i.e., where the evidence changes over time) have demonstrated that observers tend to weight early sensory information more heavily than late information (Booras et al, 2021;Huk and Shadlen, 2005;Kiani et al, 2008;Nienborg and Cumming, 2009;Odoemene et al, 2018;Zylberberg et al, 2012). However, late sensory information integration strategies (Bronfman et al, 2016;Cheadle et al, 2014;Levi et al, 2018) and flat weighting profiles (Bronfman et al, 2016;Odoemene et al, 2018) have also been observed.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Weighting of Time-Varying Visual and Auditory Evidence During Multisensory Decision Making

et al. 2022

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Perceptual decision-making in a dynamic environment requires two integration processes: integration of sensory evidence from multiple modalities to form a coherent representation of the environment, and integration of evidence across time to accurately make a decision. Only recently studies started to unravel how evidence from two modalities is accumulated across time to form a perceptual decision. One important question is whether information from individual senses contributes equally to multisensory decisions. We designed a new psychophysical task that measures how visual and auditory evidence is weighted across time. Participants were asked to discriminate between two visual gratings, and/or two sounds presented to the right and left ear based on respectively contrast and loudness. We varied the evidence, i.e., the contrast of the gratings and amplitude of the sound, over time. Results showed a significant increase in performance accuracy on multisensory trials compared to unisensory trials, indicating that discriminating between two sources is improved when multisensory information is available. Furthermore, we found that early evidence contributed most to sensory decisions. Weighting of unisensory information during audiovisual decision-making dynamically changed over time. A first epoch was characterized by both visual and auditory weighting, during the second epoch vision dominated and the third epoch finalized the weighting profile with auditory dominance. Our results suggest that during our task multisensory improvement is generated by a mechanism that requires cross-modal interactions but also dynamically evokes dominance switching.

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Change point detection with multiple alternatives reveals parallel evaluation of the same stream of evidence along distinct timescales

Cited by 4 publications

References 56 publications

Quantifying decision-making in dynamic, continuously evolving environments

Quantifying decision-making in dynamic, continuously evolving environments

Quantifying decision-making in dynamic, continuously evolving environments

Dynamic Weighting of Time-Varying Visual and Auditory Evidence During Multisensory Decision Making

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