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Proceedings. Biological Sciences Sep 2019In conditions of constant illumination, the eye pupil diameter indexes the modulation of arousal state and responds to a large breadth of cognitive processes, including... (Review)
Review
In conditions of constant illumination, the eye pupil diameter indexes the modulation of arousal state and responds to a large breadth of cognitive processes, including mental effort, attention, surprise, decision processes, decision biases, value beliefs, uncertainty, volatility, exploitation/exploration trade-off, or learning rate. Here, I propose an information theoretic framework that has the potential to explain the ensemble of these findings as reflecting pupillary response to information processing. In short, updates of the brain's internal model, quantified formally as the Kullback-Leibler (KL) divergence between prior and posterior beliefs, would be the common denominator to all these instances of pupillary dilation to cognition. I show that stimulus presentation leads to pupillary response that is proportional to the amount of information the stimulus carries about itself and to the quantity of information it provides about other task variables. In the context of decision making, pupil dilation in relation to uncertainty is explained by the wandering of the evidence accumulation process, leading to large summed KL divergences. Finally, pupillary response to mental effort and variations in tonic pupil size are also formalized in terms of information theory. On the basis of this framework, I compare pupillary data from past studies to simple information-theoretic simulations of task designs and show good correspondance with data across studies. The present framework has the potential to unify the large set of results reported on pupillary dilation to cognition and to provide a theory to guide future research.
Topics: Arousal; Attention; Cognition; Decision Making; Humans; Learning; Photic Stimulation; Pupil; Uncertainty
PubMed: 31530143
DOI: 10.1098/rspb.2019.1593 -
Proceedings of the National Academy of... Nov 2020Adversarial examples are carefully crafted input patterns that are surprisingly poorly classified by artificial and/or natural neural networks. Here we examine...
Adversarial examples are carefully crafted input patterns that are surprisingly poorly classified by artificial and/or natural neural networks. Here we examine adversarial vulnerabilities in the processes responsible for learning and choice in humans. Building upon recent recurrent neural network models of choice processes, we propose a general framework for generating adversarial opponents that can shape the choices of individuals in particular decision-making tasks toward the behavioral patterns desired by the adversary. We show the efficacy of the framework through three experiments involving action selection, response inhibition, and social decision-making. We further investigate the strategy used by the adversary in order to gain insights into the vulnerabilities of human choice. The framework may find applications across behavioral sciences in helping detect and avoid flawed choice.
Topics: Choice Behavior; Computer Simulation; Decision Making; Humans; Learning; Neural Networks, Computer; Reinforcement, Psychology; Reward
PubMed: 33148802
DOI: 10.1073/pnas.2016921117 -
PLoS Computational Biology Apr 2020
Topics: Decision Making; Goals; Humans; Thinking
PubMed: 32240159
DOI: 10.1371/journal.pcbi.1007706 -
Current Opinion in Neurobiology Oct 2019Nature is in constant flux, so animals must account for changes in their environment when making decisions. How animals learn the timescale of such changes and adapt... (Review)
Review
Nature is in constant flux, so animals must account for changes in their environment when making decisions. How animals learn the timescale of such changes and adapt their decision strategies accordingly is not well understood. Recent psychophysical experiments have shown humans and other animals can achieve near-optimal performance at two alternative forced choice (2AFC) tasks in dynamically changing environments. Characterization of performance requires the derivation and analysis of computational models of optimal decision-making policies on such tasks. We review recent theoretical work in this area, and discuss how models compare with subjects' behavior in tasks where the correct choice or evidence quality changes in dynamic, but predictable, ways.
Topics: Animals; Choice Behavior; Decision Making; Humans; Learning
PubMed: 31326724
DOI: 10.1016/j.conb.2019.06.006 -
Nature Reviews. Neuroscience Oct 2019The outcome of a decision is often uncertain, and outcomes can vary over repeated decisions. Whether decision outcomes should substantially affect behaviour and learning... (Review)
Review
The outcome of a decision is often uncertain, and outcomes can vary over repeated decisions. Whether decision outcomes should substantially affect behaviour and learning depends on whether they are representative of a typically experienced range of outcomes or signal a change in the reward environment. Successful learning and decision-making therefore require the ability to estimate expected uncertainty (related to the variability of outcomes) and unexpected uncertainty (related to the variability of the environment). Understanding the bases and effects of these two types of uncertainty and the interactions between them - at the computational and the neural level - is crucial for understanding adaptive learning. Here, we examine computational models and experimental findings to distil computational principles and neural mechanisms for adaptive learning under uncertainty.
Topics: Adaptation, Biological; Animals; Brain; Choice Behavior; Decision Making; Humans; Learning; Nerve Net; Uncertainty
PubMed: 31147631
DOI: 10.1038/s41583-019-0180-y -
The Journals of Gerontology. Series B,... Oct 2023To test the hypotheses that decision making ability declines in old age and that a higher level of cognitive reserve is associated with a reduced rate of decline.
OBJECTIVES
To test the hypotheses that decision making ability declines in old age and that a higher level of cognitive reserve is associated with a reduced rate of decline.
METHODS
As part of an ongoing cohort study, 982 older adults without dementia at study enrollment completed measures of purpose in life and cognitive activity which were used as markers of cognitive reserve. At annual intervals thereafter, they completed 6 tests of decision making.
RESULTS
In a factor analysis of baseline decision making scores, 3 measures (financial/health literacy, financial/health decision making, scam susceptibility) loaded on an "analytic" factor and 3 (temporal discounting small stakes, temporal discounting large stakes, risk aversion) loaded on a "preferences" (for temporal discounting and avoiding risk) factor. During a mean of 4.7 years of follow-up (standard deviation = 2.9), analytic factor scores decreased (mean = 0.042-unit per year, standard error [SE] = 0.006, p < .001) and preferences factor scores increased (mean = 0.021-unit per year, SE = 0.006, p < .001), with a correlation of 0.13 (p < .001) between rates of change. Evidence of an association between cognitive reserve and decision making was mixed with purpose in life related to change in analytic decision making, whereas past (but not current) cognitive activity was related to change in decision making preferences.
DISCUSSION
Decision making analysis and preferences change over time in late life. Change over time in decision making components is relatively independent and differentially related to age and cognitive reserve.
Topics: Humans; Aged; Decision Making; Aging; Cohort Studies; Longitudinal Studies; Delay Discounting
PubMed: 36856705
DOI: 10.1093/geronb/gbad037 -
ELife Sep 2021Actions often require the selection of a specific goal amongst a range of possibilities, like when a softball player must precisely position her glove to field a...
Actions often require the selection of a specific goal amongst a range of possibilities, like when a softball player must precisely position her glove to field a fast-approaching ground ball. Previous studies have suggested that during goal uncertainty the brain prepares for all potential goals in parallel and averages the corresponding motor plans to command an intermediate movement that is progressively refined as additional information becomes available. Although intermediate movements are widely observed, they could instead reflect a neural decision about the single best action choice given the uncertainty present. Here we systematically dissociate these possibilities using novel experimental manipulations and find that when confronted with uncertainty, humans generate a motor plan that optimizes task performance rather than averaging potential motor plans. In addition to accurate predictions of population-averaged changes in motor output, a novel computational model based on this performance-optimization theory accounted for a majority of the variance in individual differences between participants. Our findings resolve a long-standing question about how the brain selects an action to execute during goal uncertainty, providing fundamental insight into motor planning in the nervous system.
Topics: Adolescent; Adult; Brain; Decision Making; Female; Humans; Male; Models, Biological; Movement; Uncertainty; Young Adult
PubMed: 34486520
DOI: 10.7554/eLife.67019 -
European Archives of Psychiatry and... Dec 2023
Topics: Humans; Schizophrenia; Antipsychotic Agents; Decision Making, Shared; Decision Making
PubMed: 38017193
DOI: 10.1007/s00406-023-01712-9 -
Trends in Cognitive Sciences Jan 2023Colombian drug lord Pablo Escobar, while on the run, purportedly burned two million dollars in banknotes to keep his daughter warm. A stark reminder that, in life,... (Review)
Review
Colombian drug lord Pablo Escobar, while on the run, purportedly burned two million dollars in banknotes to keep his daughter warm. A stark reminder that, in life, circumstances and goals can quickly change, forcing us to reassess and modify our values on-the-fly. Studies in decision-making and neuroeconomics have often implicitly equated value to reward, emphasising the hedonic and automatic aspect of the value computation, while overlooking its functional (concept-like) nature. Here we outline the computational and biological principles that enable the brain to compute the usefulness of an option or action by creating abstractions that flexibly adapt to changing goals. We present different algorithmic architectures, comparing ideas from artificial intelligence (AI) and cognitive neuroscience with psychological theories and, when possible, drawing parallels.
Topics: Artificial Intelligence; Goals; Brain; Reward; Brain Mapping; Decision Making; Choice Behavior
PubMed: 36446707
DOI: 10.1016/j.tics.2022.11.001 -
Philosophical Transactions of the Royal... Mar 2021Uncertainty is a ubiquitous component of human economic behaviour, yet people can vary in their preferences for risk across populations, individuals and different points... (Review)
Review
Uncertainty is a ubiquitous component of human economic behaviour, yet people can vary in their preferences for risk across populations, individuals and different points in time. As uncertainty also characterizes many aspects of animal decision-making, comparative research can help evaluate different potential mechanisms that generate this variation, including the role of biological differences or maturational change versus cultural learning, as well as identify human-unique components of economic decision-making. Here, we examine decision-making under risk across non-human primates, our closest relatives. We first review theoretical approaches and current methods for understanding decision-making in animals. We then assess the current evidence for variation in animal preferences between species and populations, between individuals based on personality, sex and age, and finally, between different contexts and individual states. We then use these primate data to evaluate the processes that can shape human decision-making strategies and identify the primate foundations of human economic behaviour. This article is part of the theme issue 'Existence and prevalence of economic behaviours among non-human primates'.
Topics: Animals; Behavior, Animal; Biological Evolution; Cultural Evolution; Decision Making; Humans; Primates; Uncertainty
PubMed: 33423637
DOI: 10.1098/rstb.2019.0671