Accumulation of continuously time-varying sensory evidence constrains neural and behavioral responses in human collision threat detection
| Autor: | Richard M. Wilkie, Zeynep Uludağ, Gustav Markkula, Jac Billington |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Male
Time Factors Computer science Physiology Vision Social Sciences Event-Related Potentials 02 engineering and technology Electroencephalography 0302 clinical medicine Cognition 0203 mechanical engineering Looming Task Performance and Analysis 0202 electrical engineering electronic engineering information engineering Medicine and Health Sciences Psychology Biology (General) media_common Clinical Neurophysiology Brain Mapping Ecology medicine.diagnostic_test 05 social sciences Brain Replicate Middle Aged Electrophysiology 020303 mechanical engineering & transports Bioassays and Physiological Analysis Computational Theory and Mathematics Brain Electrophysiology Modeling and Simulation Physical Sciences Sensory Perception Female Anatomy Research Article Adult Imaging Techniques QH301-705.5 020209 energy media_common.quotation_subject Decision Making Models Neurological Neurophysiology Sensory system Neuroimaging Research and Analysis Methods 050105 experimental psychology 03 medical and health sciences Cellular and Molecular Neuroscience Young Adult Event-related potential Perception Genetics medicine Humans 0501 psychology and cognitive sciences Collision detection Molecular Biology Ecology Evolution Behavior and Systematics Behavior Scalp Electrophysiological Techniques Cognitive Psychology Biology and Life Sciences Computational Biology Collision Probability Theory Probability Distribution Space Perception Cognitive Science Clinical Medicine Neuroscience Head 030217 neurology & neurosurgery Mathematics |
| Zdroj: | PLoS Computational Biology, Vol 17, Iss 7, p e1009096 (2021) PLoS Computational Biology |
| ISSN: | 1553-7358 1553-734X |
| Popis: | Evidence accumulation models provide a dominant account of human decision-making, and have been particularly successful at explaining behavioral and neural data in laboratory paradigms using abstract, stationary stimuli. It has been proposed, but with limited in-depth investigation so far, that similar decision-making mechanisms are involved in tasks of a more embodied nature, such as movement and locomotion, by directly accumulating externally measurable sensory quantities of which the precise, typically continuously time-varying, magnitudes are important for successful behavior. Here, we leverage collision threat detection as a task which is ecologically relevant in this sense, but which can also be rigorously observed and modelled in a laboratory setting. Conventionally, it is assumed that humans are limited in this task by a perceptual threshold on the optical expansion rate–the visual looming–of the obstacle. Using concurrent recordings of EEG and behavioral responses, we disprove this conventional assumption, and instead provide strong evidence that humans detect collision threats by accumulating the continuously time-varying visual looming signal. Generalizing existing accumulator model assumptions from stationary to time-varying sensory evidence, we show that our model accounts for previously unexplained empirical observations and full distributions of detection response. We replicate a pre-response centroparietal positivity (CPP) in scalp potentials, which has previously been found to correlate with accumulated decision evidence. In contrast with these existing findings, we show that our model is capable of predicting the onset of the CPP signature rather than its buildup, suggesting that neural evidence accumulation is implemented differently, possibly in distinct brain regions, in collision detection compared to previously studied paradigms. Author summary Evidence accumulation models of decision-making propose that humans accumulate noisy sensory evidence over time up to a decision threshold. We demonstrate that this type of model can describe human behavior well not only in abstract, semi-static laboratory tasks, but also in a task that is relevant to human movement in the real world. Specifically, we show that a model directly accumulating the continuously time-varying visual looming (optical expansion) of an approaching obstacle explains full probability distributions of when humans can detect this collision threat. Using electroencephalography, we find indications that this type of evidence is accumulated differently in the brain compared to evidence accumulation in previously studied, more abstract tasks. Our experimental paradigm, model, and findings open for wider application of this type of decision-making model to laboratory and real-world tasks with ecologically relevant, time-varying sensory evidence, and further studies into how such decisions are implemented neurally. There are also societal implications: In applied safety research and traffic accident litigation it is conventionally assumed that human collision detection is limited by a fixed perceptual threshold, an assumption that our results show to be highly inaccurate. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
| Nepřihlášeným uživatelům se plný text nezobrazuje | K zobrazení výsledku je třeba se přihlásit. |