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Abstract:
Much of current visual neuroscience is performed using standardized procedures. Most notably,
these generally include stimulus delivery using computer displays, the requirement of fixation,
repeated performance of experimental conditions and lengthy conditioning of animals on tasks to
allow for behavioral reports. Correlating neural responses with stimulus characteristics and
behavior lies at the heart of systems neuroscience. These controlled conditions have many
advantages, but at the same time can only represent an approximation of the processes that
occur during real world vision.
But how much are we missing under these constraints? Real world vision is characterized by eye
movements in three dimensions as observers fixate and track objects in the environment. What
are the characteristics of spike trains collected under such conditions and how do they differ from
those collected during task performance. How much can be said about neural activity by applying
the correlational approach to data acquired under these conditions? Does what we learn about
neural activity and selectivity during task performance generalize to real world vision? To begin to
address these questions, we have recorded extracellular activity of several inferior temporal
cortex neurons simultaneously while monkeys viewed face and object stimuli presented on a
computer monitor at the center of gaze during fixation. Then we record activity of the same
neurons during interaction with a human experimenter, while measuring the monkeys’ eye
position and recording the visual input using a camera. We compare about 5 minutes of activity
collected during these two conditions. Preliminary results suggest many IT neurons were
dynamically modulated during real world vision. Peak firing rates (eg at 200ms binwidth) tended
to be greater during real world vision than during task performance. Some IT neurons showed
markedly different interspike interval distributions in the two conditions.
Our findings suggest that a dynamic three dimensional visual environment may be a useful tool
for elucidating the function of visual neurons.
