UC San Diego
Neural dynamics of probabilistic perceptual decision making in the human brain
- Author(s): Rungratsameetaweemana, Nuttida
- Advisor(s): Serences, John T
- et al.
Our visual world is full of ambiguous sensory signals, from which we have to extract relevant and meaningful information in order to guide optimal actions. To maximize the efficiency of this process, our visual system relies on foreknowledge to prioritize the processing of relevant or expected features. Knowledge of statistical regularities in the environment can lead to faster detection and recognition of objects when they are encountered in an expected context (e.g., a bird in a backyard) than when they are encountered in unlikely context (e.g., a bird in a washing machine). In addition, knowledge about the current task goals can also support faster and more accurate processing of relevant over irrelevant items--a mechanism referred to as selective attention. In what manner do these “top down” modulatory factors individually and jointly affect visual sensory processing, decision making, and behavior? In three studies, we examined how perceptual decision making is modulated by prior expectation about stimulus probabilities alone and in the context where knowledge about the current behavioral goals were available. We examined these effects both neurally via electroencephalography (EEG) and behaviorally through psychophysics and also in amnesic patients in relation to age-matched controls. To this end, we first devised an experimental paradigm where prior expectation and selective attention could be individually manipulated. The behavioral readouts from this paradigm were continuous which made it possible for the temporal evolution of the effects of expectation and attention on decision process to be probed both behaviorally and in relation to the continuous neural (EEG) measures. We first demonstrated that prior expectation improves decision processes by primarily affecting post-perceptual operations such as initiation and execution of motor responses, instead of directly improving the efficiency of early sensory processing. This finding confirms an idea that has been put forth by traditional theoretical framework that prior expectation affects decision making by preferentially modulating motor responses that correspond to sensory inputs with high probability of occurring. Further, we showed that while both expectation and attention improved behavior, the underlying neural mechanisms that give rise to these effects differed: while attention operates on the early processing of sensory inputs, expectation affects the late stage of decision making by biasing motor responses towards the most likely decision choice. These differential temporal dynamics of expectation and attention were observed bot h behaviorally and neurally. Finally, we demonstrated that an ability to utilize knowledge about current task goals and to form expectation based on statistical regularities of the sensory environment can be independent of a declarative memory system.