Response repetition biases in human perceptual decisions are explained by activity decay in competitive attractor models

Bonaiuto, James; Berker, Archy O. de; Bestmann, Sven

doi:10.7554/elife.20047

Cited by 44 publications

(73 citation statements)

References 114 publications

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“…This last observation suggests that the predictive activity of chosen juice cells may be the cause underlying choice hysteresis, although this hypothesis awaits testing. As already noted, choice hysteresis and the predictive activity of chosen juice cells are naturally reproduced by the neural network model illustrated in Figure 4A (Bonaiuto et al, 2016; Rustichini and Padoa-Schioppa, 2015). …”

Section: Neuronal Fluctuations and Choice Variabilitysupporting

confidence: 53%

Orbitofrontal Cortex: A Neural Circuit for Economic Decisions

Padoa-Schioppa

Conen

2017

Neuron

254

180

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Economic choice behavior entails the computation and comparison of subjective values. A central contribution of neuroeconomics has been to show that subjective values are represented explicitly at the neuronal level. With this result at hand, the field has increasingly focused on the difficult question of where in the brain and how exactly subjective values are compared to make a decision. Here we review a broad range of experimental and theoretical results suggesting that good-based decisions are generated in a neural circuit within the orbitofrontal cortex (OFC). The main lines of evidence supporting this proposal include the fact that goal-directed behavior is specifically disrupted by OFC lesions, the fact that different groups of neurons in this area encode the input and the output of the decision process, the fact that activity fluctuations in each of these cell groups correlate with choice variability, and the fact that these groups of neurons are computationally sufficient to generate decisions. Results from other brain regions are consistent with the idea that good-based decisions take place in OFC, and indicate that value signals inform a variety of mental functions. We also contrast the present proposal with other leading models for the neural mechanisms of economic decisions. Finally, we indicate open questions and suggest possible directions for future research.

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Section: Neuronal Fluctuations and Choice Variabilitysupporting

confidence: 53%

Orbitofrontal Cortex: A Neural Circuit for Economic Decisions

Padoa-Schioppa

Conen

2017

Neuron

254

180

View full text Add to dashboard Cite

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“…Taken together, the data by Akaishi et al (2014) and our present study indicate that history biases in perceptual decision-making are governed by decision variables encoded in an abstract, action-independent format. Such representations of the decision variable exist in associative brain regions, such as posterior parietal or prefrontal cortex (Bennur and Gold, 2011;Hebart et al, 2012Hebart et al, , 2016, which also exhibit the short-term memory dynamics necessary for the persistence of biases in the decision-making machinery (Wang, 2002;Bonaiuto et al, 2016;Morcos and Harvey, 2016).…”

Section: Discussionmentioning

confidence: 99%

“…Computational models posit that choice history biases result from the temporal accumulation of signals from past decisions (Yu and Cohen, 2009;Glaze et al, 2015;Bonaiuto et al, 2016). Such a mechanism may serve to continuously update the decision-makers' prior belief about the upcoming stimulus category and adjust their choice behavior to structured environments (Yu and Cohen, 2009;Glaze et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Adaptive History Biases Result from Confidence-weighted Accumulation of Past Choices

Braun

Urai

Donner

2017

Preprint

101

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Perceptual decision-making is biased by previous events, including the history of preceding choices: Observers tend to repeat (or alternate) their judgments of the sensory environment more often than expected by chance. Computational models postulate that these so-called choice history biases result from the accumulation of internal decision signals across trials. Here, we provide psychophysical evidence for such a mechanism and its adaptive utility. Male and female human observers performed different variants of a challenging visual motion discrimination task near psychophysical threshold. In a first experiment, we decoupled categorical perceptual choices and motor responses on a trial-by-trial basis. Choice history bias was explained by previous perceptual choices, not motor responses, highlighting the importance of internal decision signals in action-independent formats. In a second experiment, observers performed the task in stimulus environments containing different levels of autocorrelation and providing no external feedback about choice correctness. Despite performing under overall high levels of uncertainty, observers adjusted both the strength and the sign of their choice history biases to these environments. When stimulus sequences were dominated by either repetitions or alternations, the individual degree of this adjustment of history bias was about as good a predictor of individual performance as individual perceptual sensitivity. The history bias adjustment scaled with two proxies for observers’ confidence about their previous choices (accuracy and reaction time). Taken together, our results are consistent with the idea that action-independent, confidence-modulated decision variables are accumulated across choices in a flexible manner that depends on decision-makers’ model of their environment.Significance statementDecisions based on sensory input are often influenced by the history of one’s preceding choices, manifesting as a bias to systematically repeat (or alternate) choices. We here provide support for the idea that such choice history biases arise from the context-dependent accumulation of a quantity referred to as the decision variable: the variable’s sign dictates the choice and its magnitude the confidence about choice correctness. We show that choices are accumulated in an actionindependent format and a context-dependent manner, weighted by the confidence about their correctness. This confidence-weighted accumulation of choices enables decision-makers to flexibly adjust their behavior to different sensory environments. The bias adjustment can be as important for optimizing performance as one’s sensitivity to the momentary sensory input.

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“…Previous theoretical accounts have postulated a shift in the starting point of the decision variables towards the bound of the previous choice (Yu and Cohen, 2008;Zhang et al, 2014;Glaze et al, 2015). This is based on the assumption that the representation of the decision variable decays slowly, leaving a trace of the observer's choice in the next trial (Cho et al, 2002;Gao et al, 2009Gao et al, , 2009Bonaiuto et al, 2016). However, choice history biases might also originate from a slower (i.e., tens of seconds) across-trial accumulation of internal decision variables -analogous to the accumulation of external outcomes in value-based decisions (Sutton and Barto, 1998;Sugrue et al, 2004).…”

Section: Introductionmentioning

confidence: 99%

Choice History Biases Subsequent Evidence Accumulation

Urai

Gee

Donner

2018

Preprint

126

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Perceptual choices depend not only on the current sensory input, but also on the behavioral context. An important contextual factor is the history of one's own choices. Choice history often strongly biases perceptual decisions, and leaves traces in the activity of brain regions involved in decision processing. Yet, it remains unknown how such history signals shape the dynamics of later decision formation. Models of perceptual choice construe decision formation as the accumulation of sensory evidence towards decision bounds. In this framework, it is commonly assumed that choice history signals shift the starting point of accumulation towards the bound reflecting the previous choice. We here present results that challenge this idea. We fit a bounded accumulation ('drift diffusion') decision model to behavioral data from multiple perceptual choice tasks and sensory modalities, and estimated bias terms that dependent on observers' previous choices. Individual history biases in behavior were consistently explained by a history-dependent change in the evidence accumulation, rather than in its starting point. Choice history signals thus seem to affect the interpretation of current sensory input, akin to shifting endogenous attention towards (or away from) the previously selected interpretation.

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Response repetition biases in human perceptual decisions are explained by activity decay in competitive attractor models

Cited by 44 publications

References 114 publications

Orbitofrontal Cortex: A Neural Circuit for Economic Decisions

Orbitofrontal Cortex: A Neural Circuit for Economic Decisions

Adaptive History Biases Result from Confidence-weighted Accumulation of Past Choices

Choice History Biases Subsequent Evidence Accumulation

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