Categorization in IT and PFC: Model and Experiments
Abstract
In a recent experiment, Freedman et al. recorded from inferotemporal (IT) and prefrontal cortices (PFC) of monkeys performing a cat/dog categorization task ([3] and Freedman, Riesenhuber, Poggio, Miller, Soc. Neurosci. Abs.). In this paper we analyze the tuning properties of view-tuned units in our HMAX model of object recognition in cortex [7, 8] using the same paradigm and stimuli as in the experiment. We then compare the simulation results to the monkey inferotemporal neuron population data. We find that view-tuned model IT units that were trained without any explicit category information can show categoryrelated tuning as observed in the experiment. This suggests that the tuning properties of experimental IT neurons might primarily be shaped by bottom-up stimulus-space statistics, with little influence of topdown task-specific information. The population of experimental PFC neurons, on the other hand, shows tuning properties that cannot be explained just by stimulus tuning. These analyses are compatible with a model of object recognition in cortex [10] in which a population of shape-tuned neurons provides a general basis for neurons tuned to different recognition tasks.
Document Details
- Document Type
- Technical Report
- Publication Date
- Apr 01, 2002
- Accession Number
- ADA459495
Entities
People
- David J. Freedman
- Maximilian Riesenhuber
- Ulf Knoblich
Organizations
- Massachusetts Institute of Technology