title: Average activity, but not variability, is the dominant factor in the representation of object categories in the brain.
abstract: To categorize the perceived objects, brain utilizes a broad set of its resources and encoding strategies. Yet, it remains elusive how the category information is encoded in the brain. While many classical studies have sought the category information in the across-trial-averaged activity of neurons/neural populations, several recent studies have observed category information also in the within-trial correlated variability of activities between neural populations (i.e. dependent variability). Moreover, other studies have observed that independent variability of activity, which is the variability of the measured neural activity without any influence from correlated variability with other neurons/populations, could also be modulated for improved categorization. However, it was unknown how important each of the three factors (i.e. average activity, dependent and independent variability of activities) was in category encoding. Therefore, we designed an EEG experiment in which human subjects viewed a set of object exemplars from four categories. Using a computational model, we evaluated the contribution of each factor separately in category encoding. Results showed that the average activity played a significant role while the independent variability, although effective, contributed moderately to the category encoding. The inter-channel dependent variability showed an ignorable effect on the encoding. We also investigated the role of those factors in the encoding of variations which showed similar effects. These results imply that the brain, rather than variability, seems to use the average activity to convey information on the category of the perceived objects.
authors.affiliation: Department of Electrical Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran; School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran.
authors.forename: Hamid
authors.initials: H
authors.lastname: Karimi-Rouzbahani
authors.affiliation: Department of Electrical Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran; School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran.
authors.forename: Nasour
authors.initials: N
authors.lastname: Bagheri
authors.affiliation: Cognitive Science Research Lab., Department of Computer Engineering, Shahid Rajaee Teacher Training University, Lavizan, Tehran, Iran; School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran; Institute for Advanced Technologies, Shahid Rajaee Teacher Training University, Lavizan, Tehran, Iran. Electronic address: rebrahimpour@srttu.edu.
authors.forename: Reza
authors.initials: R
authors.lastname: Ebrahimpour
mesh_terms: D000328:Adult; D001921:Brain / Q000502:physiology*; D004569:Electroencephalography; D005260:Female; D005556:Form Perception; D006801:Humans; D008297:Male; D008959:Models, Neurological; D010364:Pattern Recognition, Visual / Q000502:physiology*; D010775:Photic Stimulation; D012815:Signal Processing, Computer-Assisted; D055815:Young Adult
keywords: EEG; computational model; object category encoding; representational analysis; signal variability