Algorithmic and Neural Basis of Naturalistic Decision Making
When a situation affords a long latency between stimulus and response, deliberative behavioral control can be used to generate behavior that is strategic, variable, and hard to predict by an adversary. As this latency decreases, reactive control takes over and generates responses that are fast, less variable, and easier to predict by an adversary. We can characterize deliberative behavioral control or planning as action choices that occur after internally simulating more than one action sequence and its respective consequences. Conversely, reactive control is a rapid stimulus-evoked response. A large amount of research suggests that these two decision making systems have different neural substrates. Interestingly, the similarities between the lamprey (jawless fish that preceded mammals by 560 million years) and mammalian neural system that is implicated in reflexive behavior suggests that reactive control evolved very early on in the vertebrate evolution. In contrast, behavioral and neural evidence for planing and higher level cognition seems to only exist for mammals and birds. Evidence for planning is less clear for reptiles and amphibians, and similarly ambiguous or absent in fish.
Assuming the apparent absence of plan-based decision making in fish and other early vertebrates is correct (and not simply due to a lack of study relative to terrestrial vertebrates), we can use the uneven distribution of higher level cognition to gain insight into why we only see this in (certain) animals.
Rooted in evolution, we study both the algorithmic formalization and neural substrates of naturalistic decision making, which encompasses decision making in temporally extended naturalistic environments. Our theoretical and algorithmic work aims to elucidate the effects of environment topology and complexity on state-space representations, and choice of arbitration between habit and planning. Our empirical work, conducted in collaboration with Daniel Dombeck (Department of Neurobiology), involves both behavioral and in-vivo imaging of mammalian brains in highly uncertain environments that mimic idealized predator-prey interactions to understand the biological mechanisms involved in decision making in more naturalistic tasks.
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Collaborators
Prof. Daniel Dombeck, Department of Neurobiology, Northwestern University
Related Publications
Tuning movement for sensing in an uncertain world, bioRxiv, 06/2020/ 2020 Google Scholar
Spatial planning with long visual range benefits escape from visual predators in complex naturalistic environments, Nature Communications, 07/2020/ 2020 Google Scholar
How Sensory Ecology Affects the Utility of Planning, Conference on Cognitive Computational Neuroscience, September/ 2018 Google Scholar PDF
Massive increase in visual range preceded the origin of terrestrial vertebrates, Proceeding of the National Academy of Sciences, vol. 114, pp. E2375-E2384, 03/2017/ 2017 DOI Google Scholar Video
Neuroscience needs behavior correcting a reductionist bias, Neuron, vol. 93, pp. 480--490, 02/2017/ 2017 Google Scholar PDF
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