Decoding Population Activity During Sensory Adaptation

DESCRIPTION (provided by applicant): A major goal of visual systems neuroscience understands how visual information is encoded by sensory cortical neurons and how their activity is then decoded to guide behavior. It is well known that the recent history of visual experience (adaptation) can often profoundly influence both the responses of individual neurons as well as subjects' perceptual judgments. Thus, a comprehensive understanding of how the visual system gives rise to perception and behavior in diverse natural environments requires determining how sensory adaptation affects the encoding and decoding of visual information by populations of neurons. We will address these questions using chronic multi-electrode arrays to simultaneously record the activity of dozens of neurons in area V1 of macaque monkeys, while animals perform a well-defined perceptual task. First, we will characterize the way in which adaptation influences the representation of information in the neuronal population, by measuring the structure of cortical network activity in un-adapted and adapted states. Second, we will address how that network activity is decoded in both un-adapted and adapted sensory states, by relating trial-by-trial fluctuations in population activity to the animal's perceptual decisions This study will elucidate how activity in neural circuits is altered by recent visual experience, ad how downstream decision areas interpret this plasticity. A thorough understanding of how adaptation influences the encoding of visual information and the decoding of neural activity is needed to address how computations within the visual system accommodate recent changes in the sensory environment. Basic knowledge of these influences within a cortical region whose physiological and anatomical properties are well-known will aid in identifying aberrant sensory function due to various mental disorders.