A very large number of studies have investigated the relationship between the activity of sensory neurons and behavior. The model that implicitly or explicitly guides most of that work is that single neurons are the unit of computation. The underlying hypothesis is that different groupings of neurons are responsible for each sensory, cognitive or premotor role in decision-making. However, each neuron's responses encode a unique combination of sensory and cognitive signals as well as noise, and have distinct interactions with the rest of the network. These observations, combined with the staggering flexibility of mappings from sensory stimuli to actions suggest that different weighted sums of the activity of the entire population may be more informative about sensory and behavioral variables than different groupings of neurons. This idea represents a new way of thinking about neural coding. It has important implications for the neuronal mechanisms underlying many behavioral processes, including perceptual decision-making in the primate visual system, which is our model system. This paradigm can also explain longstanding paradoxes about the aspects of the neural code that limit performance on perceptual tasks. The goal of this proposal is to identify the aspects of population activity that guide and gate perceptual decisions. We hypothesize that the sensory information that is used to flexibly guide and gate decisions is shared between populations of visual and premotor neurons. The two cornerstones of our approach are 1) to record simultaneously from groups of neurons in the middle temporal area (MT), which encodes visual motion, and in the superior colliculus (SC), whose responses are visual, oculomotor, and everything in between and 2) to use novel measures of neuronal activity that incorporate the activity of the whole population.
In Aim 1, we will compare the extent to which individual perceptual decisions can be predicted from the dominant fluctuations in population responses within MT or the SC or activity that is correlated on a trial by trial basis between the two areas.
In Aim 2, we will determine whether task-irrelevant stimulus information, which can cause large changes in the activity of sensory neurons, is filtered out by interactions between MT and the SC.
In Aim 3, we will conduct a strong test of the hypothesis that visuo-motor interactions guide perceptual decision-making by measuring the relationship between choices and interactions between MT and SC neurons with receptive fields in opposite hemifields. Together, these studies will address long-standing questions about the extent to which perception is limited by the fidelity with which stimulus information is encoded in sensory cortex or by the information that is flexibly communicated to downstream areas in a task-dependent way. More generally, this work will establish a set of experimental and data analysis techniques for revealing the relationship between neuronal populations and behavior.
Most neurological diseases including depression, schizophrenia, and attention deficit hyperactivity disorder are thought to involve networks of neurons in multiple brain areas, but very few studies have focused on how neurons in different areas interact and how these interactions are modulated by task or cognitive factors. Understanding the way that information is encoded and decoded by neuronal populations will be critical for diagnosing and developing drug therapies to treat these diseases. The proposed projects will elucidate general mechanisms for population coding as well as the relationship between the activity of groups of neurons in different areas and behavior.
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