Perceptual decision making over the lifespan

Project Summary Visual perceptual decision-making (PDM) is a ubiquitous process that translates our noisy visual experience of the environment into associated perceptual decisions. PDM is important as it directly influences how we interact with our surroundings and form our behavior. From prior studies, we know that many cognitive

processes undergo a developmental change as we age, usually characterized by an inverted U-shape pattern: increasing function from childhood to early adulthood and a later decline in senescence. However, there is no direct evidence about the full lifespan trajectory of PDM. We identified three gaps in our understanding of PDM:

1) PDM in children is not well studied, likely because of methodological issues, 2) conclusions about lifespan PDM trajectory are only derived by indirect comparisons between separate studies, and 3) we do not have a clear understanding about how noise interacts with PDM ability in children and older adults; this is notable as

PDM often becomes a key limiting factor in behavior under conditions of high stimulus noise. The overall goal of this proposal is to address these gaps in the literature by scrutinizing age-related effects of PDM as well as using different methods to map out the typical development of PDM across the lifespan. In Aim 1, we propose

to examine PDM across the lifespan using two tasks (i.e., a random dot motion task and a categorization task). We will use the classical reaction times (RT) method with modeling (i.e., DDM: drift-diffusion model), allowing us to decompose RT into its components (i.e., evidence accumulation, non-decision time, and the decision

time) to illuminate age-related effects of the different components of PDM. Aim 1 is the first step to understanding age-related effects of PDM and an important step to mapping out the typical development of PDM. In Aim 2, we will explore the use of a complementary method, duration threshold which is characterized

by the shortest amount of time that is sufficient for individuals to perceive a stimulus, as a novel approach for estimating temporal limits of PDM using the same tasks as Aim 1. This is a method with a clear benefit of not necessitating complex modeling and it is more suitable for children and older adults as it eliminates non-

decision components (i.e., motor response). In Aim 3 we will use both classical (RT/DDM) and novel (duration threshold) methods to examine how stimulus noise impacts PDM by including different levels of noise to the tasks mentioned in Aim 1. Our sensory experience is inherently noisy and there is evidence that children and

older adults are more susceptible to stimulus noise. Our hypothesis is that the presence of noise will exacerbate age-related deficits in PDM. This would be a significant advance in our understanding of PDM lifespan trajectory as effective PDM can be particularly important under noisy sensory conditions (e.g., riding a

bike under low visibility conditions). In summary, the proposed research will provide novel insights about the typical development and decline of PDM and, by extension, establish a baseline for studying atypical development and aging in PDM (e.g., Autism Spectrum Disorder, Alzheimer’s Disease).