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Dissociation between LFP and spiking activity in macaque inferior temporal cortex reveals diagnosticity-based encoding of complex objects

MPG-Autoren
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

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

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Zitation

Nielsen, K., Logothetis, N., & Rainer, G. (2006). Dissociation between LFP and spiking activity in macaque inferior temporal cortex reveals diagnosticity-based encoding of complex objects. Journal of Neuroscience, 26(38), 9639-9645. doi:10.1523/JNEUROSCI.2273-06.2006.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0013-D02D-6
Zusammenfassung
Neurons in the inferior temporal (IT) cortex respond selectively to complex objects, and maintain their selectivity despite partial occlusion. However, relatively little is known about how the occlusion of different shape parts influences responses in the IT cortex. Here, we determine experimentally which parts of complex objects monkeys are relying on in a discrimination task. We then study the effect of occlusion of parts with different behavioral relevance on neural responses in the IT cortex at the level of spiking activity and local field potentials (LFPs). For both spiking activity and LFPs, we found that the diagnostic object parts, which were important for behavioral judgments, were preferentially represented in the IT cortex. Our data show that the effects of diagnosticity grew systematically stronger along a posterior–anterior axis for LFPs, but were evenly distributed for single units, suggesting that diagnosticity is first encoded in the posterior IT cortex. Our findings highlight the power of co mbined analysis of field potentials and spiking activity for mapping structure to computational function in the brain.