Relating neurophysiology and drift diffusion models

Relating neural activity and drift diffusion models Braden A. Purcell (braden.a.purcell@vanderbilt.edu) Jeffrey D. Schall (jeffrey.d.schall@vanderbilt.edu) Thomas J. Palmeri (thomas.j.palmeri@vanderbilt.edu) Vanderbilt University, Department of Psychology, Center for Integrative & Cognitive Neuroscience, Nashville, TN 37240 USA Abstract before a saccade; the movement is executed when activity reaches a fixed threshold (Hanes & Schall, 1996). Neurophysiological (Lee, Helms, Augustine, & Hall, 1997) and modeling (Purcell, Heitz, Cohen, Logan, Schall, & Palmeri, 2007) work suggest a functional connection between visual and movement neurons in FEF and SC. Visual and movement neurons represent distinct perceptual and motor processes. During saccade visual search, the time when visual neurons select a target from among distractors is modulated by changes in target- distractor similarity, but not response interference (Sato, Murthy, Thompson, & Schall, 2001). This time may indicate the conclusion of perceptual processing. A recent study asked whether movement neuron activity could be used to identify the start of response preparation (Woodman, Kang, Thompson, & Schall, 2008). They found that varying target-distractor similarity or set size modified the onset of movement neuron activity (when activity began increasing above baseline). The onset of movement neuron activity also correlated with RT within difficulty conditions, but the growth rate did not. These results suggest that both systematic and random variability in RT is due to delays in the start of response preparation. Movement neuron activity has been interpreted in terms of stochastic accumulator models. These models assume that perceptual evidence is integrated over time until it reaches a response boundary (Boucher et al, 2007). Evidence accumulation is preceded by perceptual processing time, T er (Figure 1). The output of perceptual processing is the drift rate, v, which is the average rate of accumulation. Typically, these models predict that changing the difficulty of a perceptual discrimination should primarily affect the quality of the information (the drift rate), but not the duration of perceptual processing (T er ). If the onset of movement neuron activity corresponds to T er , then this suggests that variability in RT is due to variability in the duration of perceptual processing. This contradicts a key assumption of the stochastic accumulator framework: manipulating the difficulty of a perceptual decision should primarily influence the drift rate. What can the onset of movement neuron activity tell us about the transmission of information from perceptual processing (visual neurons) to response preparation (movement neurons)? It seems intuitive that variations in the drift rate must lead to variations in the rate of stochastic growth and not the time when activity begins increasing. However, the onset of neurophysiological activity cannot be The drift diffusion model predicts that variability in response time (RT) is primarily due to the time required for evidence to stochastically accumulate to a response boundary. Total RT depends on both the quality of perceptual processing output (the mean rate of accumulation), and also the duration of perceptual processing (the delay from stimulus to start of accumulation). The activity of movement neurons in the frontal eye field (FEF) is associated with a stochastic accumulation; these cells initiate a saccade when activity reaches a fixed threshold. During saccade visual search, the onset of movement neuron activity correlates with RT, and increases when search is more difficult. This suggests that the duration of perceptual processing was increased. We simulated trajectories using various forms of the drift diffusion model and measured the onset with the same analyses used to detect the onset of neurophysiological activity. We found that varying the rate of accumulation resulted in large changes in the measured onset of model trajectories even when the start of the accumulation was fixed. These results show that a correlation between the onset of neural activity and RT alone is not sufficient to conclude that changes in RT were due to changes in the duration, but not quality, of perceptual processing. Keywords: response time models; frontal eye field; eye movements. Neural and Mental Chronometry One hallmark approach of cognitive psychology is decomposing response time (RT) into distinguishable stages of processing (Meyer, Osman, Irwin, & Yantis, 1988) Consider an organism confronted with a stimulus relevant to two or more potential actions. Determining the relevance of object features to potential responses first requires a perceptual stage of processing. Perceptual output is interpreted by a response preparation stage which determines whether and when a response is made. Neurophysiological data recorded from sensorimotor structures in the primate brain have been used to test competing hypotheses about the flow of information between perceptual processing and response preparation. Different populations of neurons in the frontal eye field (FEF) and superior colliculus (SC) reflect visual information about object relevance versus explicit decisions about where and when to move the eyes. Visual neurons respond to a visual stimulus in their response field (Thompson, Hanes, Bichot, & Schall, 1996). Visual neuron activity evolves over time to select the location of a task- relevant object. Movement neurons increase their activity