Neural Mechanisms of Decision Making
The central goal of our lab is to elucidate the neural mechanisms that underlie decision making. Decision making occurs at the interface between cognition and behavior, so we believe that understanding its neural basis holds the promise of exposing the general principles of neural computation that support cognition. Our primary approach is to train rodents to perform complex behavioral tasks that are carefully designed to allow us to develop mathematical descriptions of the underlying decision processes. We employ high-throughput, automated training methods to provide a steady pipeline of subjects for these studies. We harness the rapidly expanding toolkit of cutting-edge molecular and cellular techniques available for rodents, such as optogenetics, in combination with high- density neural recordings to both measure and manipulate neural activity across a range of brain regions, including cortical and subcortical networks. We use the knowledge gained from these experiments to develop and constrain circuit-level descriptions of the computations that underlie decision making. The nature of our research is highly collaborative, and the UC Davis neuroscience community provides a wealth of opportunities for these collaborations.
The long-term goal of our research is to connect general principles of decision making to neural circuit mechanisms, thus paving the way for the development of more principled treatments for disorders of higher brain function. There are a number of such disorders that involve impairments to decision making, including depression, schizophrenia, and dementia, among others. The experiments we perform naturally lead to information about what interventions are necessary to produce specific alterations of the neural computations that underlie decision making behaviors. Furthermore, the same technologies that we employ also furnish the potential capacity to perform these targeted interventions. Thus, our vision is that by elucidating the neural mechanisms that govern decision processes, we will help to initiate hypothesis-driven approaches towards the directed treatment of disorders of higher brain function.
Hanks TD, Kopec CD, Brunton BW, Duan CA, Erlich JC, Brody CD. (2015) Distinct relationships of parietal and prefrontal cortices to evidence accumulation. Nature. 520(7546): 220-3.
Erlich JC, Brunton BW, Duan CA, Hanks TD, Brody CD. (2015) Distinct behavioral effects of prefrontal and parietal cortex inactivations on an accumulation of evidence task in the rat. eLife. Apr 14; 4.
Hanks TD, Kiani R, Shadlen MN. (2014) A neural mechanism of speed-accuracy tradeoff in macaque area LIP. eLife. May 27; 3.
Hanks TD, Mazurek ME, Kiani R, Hopp E, Shadlen MN. (2011) Elapsed decision time affects the weighting of prior probability in a perceptual decision task. The Journal of Neuroscience. 31(17): 6339-52.
Beck JM, Ma WJ, Kiani R, Hanks T, Churchland AK, Roitman J, Shadlen MN, Latham PE, Pouget A (2008) Probabilistic population codes for Bayesian decision making. Neuron. 60(6): 1142-52.
Kiani R, Hanks TD, Shadlen MN (2008) Bounded integration in parietal cortex underlies decisions even when viewing duration is dictated by the environment. The Journal of Neuroscience. 28(12): 3017–3029.
Hanks TD, Ditterich J, Shadlen MN (2006) Microstimulation of macaque area LIP affects decision-making in a motion discrimination task. Nature Neuroscience. 9(5): 682-9.