A single word (the noun “ elephant ”) encapsulates a complex multidimensional meaning, including both perceptual (“ big ”, “ gray ”, “ trumpeting ”) and conceptual (“ mammal ”, “ can be found in India ”) features. Opposing theories make different predictions as to whether different features (also conceivable as dimensions of the semantic space) are stored in similar neural regions and recovered with similar temporal dynamics during word reading. In this magnetoencephalography study, we tracked the brain activity of healthy human participants while reading single words varying orthogonally across three semantic dimensions: two perceptual ones (i.e., the average implied real-world size and the average strength of association with a prototypical sound) and a conceptual one (i.e., the semantic category). The results indicate that perceptual and conceptual representations are supported by partially segregated neural networks: Whereas visual and auditory dimensions are encoded in the phase coherence of low-frequency oscillations of occipital and superior temporal regions, respectively, semantic features are encoded in the power of low-frequency oscillations of anterior temporal and inferior parietal areas. However, despite the differences, these representations appear to emerge at the same latency: around 200 msec after stimulus onset. Taken together, these findings suggest that perceptual and conceptual dimensions of the semantic space are recovered automatically, rapidly, and in parallel during word reading.

The lateral occipital complex (LOC) is a set of areas in the human occipito-temporal cortex responding to objects as opposed to low-level control stimuli. Conventional functional magnetic resonance imaging (fMRI) analysis methods based on regional averages could not detect signals discriminative of different types of objects in this region. Here, we examined fMRI signals using multivariate pattern recognition (support vector classification) to systematically explore the nature of object-related information available in fine-grained activity patterns in the LOC. Distributed fMRI signals from the LOC allowed for above-chance discrimination not only of the category but also of within-category exemplars of everyday man-made objects, and such exemplar-specific information generalized across changes in stimulus size and viewpoint, particularly in posterior subregions. Object identity could also be predicted from responses of the early visual cortex, even significantly across the changes in size and viewpoint used here. However, a dissociation was observed between these two regions of interest in the degree of discrimination for objects relative to size: In the early visual cortex, two different sizes of the same object were even better discriminated than two different objects (in accordance with measures of pixelwise stimulus similarity), whereas the opposite was true in the LOC. These findings provide the first evidence that direct evoked fMRI activity patterns in the LOC can be different for individual object exemplars (within a single category). We propose that pattern recognition methods as used here may provide an alternative approach to study mechanisms of neuronal representation based on aspects of the fMRI response independent of those assessed in adaptation paradigms.