Abstract

The specificity of neural responses to visual objects is a major topic in visual neuroscience. In humans, functional magnetic resonance imaging (fMRI) studies have identified several regions of the occipital and temporal lobe that appear specific to faces, letter strings, scenes, or tools. Direct electrophysiological recordings in the visual cortical areas of epileptic patients have largely confirmed this modular organization, using either single-neuron peri-stimulus time-histogram or intracerebral event-related potentials (iERP). In parallel, a new research stream has emerged using high-frequency gamma-band activity (50–150 Hz) (GBR) and low-frequency alpha/beta activity (8–24 Hz) (ABR) to map functional networks in humans. An obvious question is now whether the functional organization of the visual cortex revealed by fMRI, ERP, GBR, and ABR coincide. We used direct intracerebral recordings in 18 epileptic patients to directly compare GBR, ABR, and ERP elicited by the presentation of seven major visual object categories (faces, scenes, houses, consonants, pseudowords, tools, and animals), in relation to previous fMRI studies. Remarkably both GBR and iERP showed strong category-specificity that was in many cases sufficient to infer stimulus object category from the neural response at single-trial level. However, we also found a strong discrepancy between the selectivity of GBR, ABR, and ERP with less than 10% of spatial overlap between sites eliciting the same category-specificity. Overall, we found that selective neural responses to visual objects were broadly distributed in the brain with a prominent spatial cluster located in the posterior temporal cortex. Moreover, the different neural markers (GBR, ABR, and iERP) that elicit selectivity toward specific visual object categories present little spatial overlap suggesting that the information content of each marker can uniquely characterize high-level visual information in the brain.

Highlights

  • Several studies have shown that high-frequency neuronal activity in the brain is a marker of active information processing involved in perception, action, and cognition (Engel et al, 2001; Fell et al, 2001; Fries et al, 2001; Varela et al, 2001; Pesaran et al, 2002; Fries, 2009)

  • Spectral analysis has become a well-established technique in cognitive neuroscience, an important debate remains regarding whether low-amplitude GBR is more informative than high-amplitude intracerebral evoked response potentials as a neural marker of underlying mental processes

  • High fidelity intracranial GBR In the same line as previous studies that showed how neural responses can be evaluated regarding their capacity to accurately describe stimulation features or behavioral response value (Britten et al, 1992; Donner et al, 2007; Liu et al, 2009; Wyart and TallonBaudry, 2009), we examined whether the specific GBR and intracerebral event-related potentials (iERP) responses were able to objectively distinguish visual object category information based on the amplitude level of neural signals

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Summary

Introduction

Several studies have shown that high-frequency neuronal activity in the brain is a marker of active information processing involved in perception, action, and cognition (Engel et al, 2001; Fell et al, 2001; Fries et al, 2001; Varela et al, 2001; Pesaran et al, 2002; Fries, 2009). Reports often focus on either GBR or iERPs (Allison et al, 1994b; Halgren et al, 1994a,b, 1995a,b; McCarthy et al, 1999; Puce et al, 1999; Privman et al, 2007; Jacobs and Kahana, 2009) to reveal the high specificity of response to stimulation conditions, but recent studies combined both markers (Fisch et al, 2009; Engell and McCarthy, 2010) These markers show different stimulus response characteristics in terms of amplitude and latency, and it is still unknown whether they systematically reflect the same information processing. We decided to study the GBR patterns in relation to iERP and ABR amplitude in an experimental context requiring a high level of neuronal response specificity: visual object recognition

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