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Inferior temporal cortex during real world vision

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http://pubman.mpdl.mpg.de/cone/persons/resource/persons84221

Sigala,  R
Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons84054

Liebe,  S
Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons84110

Nielsen,  K
Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons84063

Logothetis,  NK
Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons84154

Reiner,  G
Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Citation

Sigala, R., Liebe, S., Nielsen, K., Logothetis, N., & Reiner, G. (2006). Inferior temporal cortex during real world vision. Poster presented at AREADNE 2006: Research in Encoding and Decoding of Neural Ensembles, Santorini, Greece.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0013-D167-9
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.