The goal of this proposal Is to extend our understanding of decision-making beyond the simple paradigms that have been studied thus far. During the mentored phase, I used an experimental and theoretical approach to examine how subjects Integrate sensory evidence for simple decisions. The research proposed here will explore how subjects Integrate evidence for more complex decisions- in particular, decisions where the sensory evidence comes not only from the visual system (single cue decisions), but from the auditory system as well (cue Integration decisions). While it has been known for some time that vision can be influenced by other modalities, the neural mechanisms underlying this phenomenon remain largely unknown. To investigate the neural mechanisms underlying cue integration, I will use a rate discrimination decision task. I will examine how the speed and accuracy of subjects'decisions changes depending on whether rate information is presented to the visual system, the auditory system, or both. Because the information about rate in the task is noisy and unreliable, subjects can potentially make better decisions if they integrate information from the two modalities. I will record electrophysiological responses from parietal cortex as the animals are engaged in the task. Further, I will use theoretical models to ask: can the behavioral differences on the single-cue vs cue integration tasks be explained by the different electrophysiological responses on the two tasks? My training thus fa r makes me ideally suited for this endeavor: I have extensive experience conducting physiology experiments in awake, behaving animals. Further, because of the mentored phase, I have gained expertise in theoretical modeling and have developed analysis tools that will be critical for interpreting the physiological data.
A number of clinical disorders, foremost among them autism, appear to cause Impairments in the ability to integrate sensory information. Identifying neural mechanisms that underlie sensory integration within and across modalities may inform clinical treatments for autistic patients.
|Raposo, David; Kaufman, Matthew T; Churchland, Anne K (2014) A category-free neural population supports evolving demands during decision-making. Nat Neurosci 17:1784-1792|
|Sheppard, John P; Raposo, David; Churchland, Anne K (2013) Dynamic weighting of multisensory stimuli shapes decision-making in rats and humans. J Vis 13:|
|Carandini, Matteo; Churchland, Anne K (2013) Probing perceptual decisions in rodents. Nat Neurosci 16:824-31|
|Drugowitsch, Jan; Moreno-Bote, Rubén; Churchland, Anne K et al. (2012) The cost of accumulating evidence in perceptual decision making. J Neurosci 32:3612-28|
|Raposo, David; Sheppard, John P; Schrater, Paul R et al. (2012) Multisensory decision-making in rats and humans. J Neurosci 32:3726-35|
|Churchland, Anne K; Ditterich, Jochen (2012) New advances in understanding decisions among multiple alternatives. Curr Opin Neurobiol 22:920-6|
|Churchland, Anne K; Kiani, R; Chaudhuri, R et al. (2011) Variance as a signature of neural computations during decision making. Neuron 69:818-31|