(provided by candidate): The broad objective of this project is to contribute to the understanding of the neural mechanisms of simple decision-making. Recent work in the neurosciences reveals that neurons in the macaque visuomotor system behave in ways consistent with the leading cognitive models of the decision process. These 'sequential sampling'models not only provide a parsimonious and intuitive picture of decision formation, but possess mathematical properties that allow them to reproduce behavior (error rates, response times) with surprising accuracy. Sequential sampling models can explain, and statistically account for, variance attributed to a wide variety of manipulations. Thus, it is not surprising that research has now turned towards identifying neural correlates of sequential sampling models. This is an important step in the evaluation of a model: Can it be plausibly implemented in the brain, and does neural activity conform to predictions set forth by the models? Recent work suggests that, indeed, sequential sampling models do have neural correlates, the most widely studied of which are in the macaque visuomotor system. However, the bridge between sequential sampling models and neural activity is far from complete, and there are at least two critical areas that have not been adequately addressed. First, while sequential sampling models can predict the ubiquitous 'speed-accuracy trade-off,'no neural correlate has yet been observed. This is doubly concerning given that the model makes clear predictions as to where, and under what conditions, such a correlate should be found. Secondly, sequential sampling models make very specific predictions about errant behavior. However, error trial neural activity is less well understood, and attempts to model such activity in sequential sampling models have failed. This too is very important, as the ability of sequential sampling models to handle errors is touted as one of its strongest points. The relationship between neural activity and decision making stands at the core of a variety of psychopathological and neurological impairment. For instance, subjects who show characteristic impulsivity and perseveration (focal brain damage, schizophrenia, low working memory capacity, etc.) may be understood through these models. A detailed understanding of the mechanisms behind simple decision making is necessary for the development of treatments, and also to stimulate further health-related research.
| Heitz, Richard P; Schall, Jeffrey D (2013) Neural chronometry and coherency across speed-accuracy demands reveal lack of homomorphism between computational and neural mechanisms of evidence accumulation. Philos Trans R Soc Lond B Biol Sci 368:20130071 |
| Heitz, Richard P; Schall, Jeffrey D (2012) Neural mechanisms of speed-accuracy tradeoff. Neuron 76:616-28 |
| Schall, Jeffrey D; Purcell, Braden A; Heitz, Richard P et al. (2011) Neural mechanisms of saccade target selection: gated accumulator model of the visual-motor cascade. Eur J Neurosci 33:1991-2002 |
| Heitz, Richard P; Cohen, Jeremiah Y; Woodman, Geoffrey F et al. (2010) Neural correlates of correct and errant attentional selection revealed through N2pc and frontal eye field activity. J Neurophysiol 104:2433-41 |
