Distinguishing abstract from concrete concepts in supramodal brain regions.

Concrete words have been shown to have a processing advantage over abstract words, yet theoretical accounts and neural correlates underlying the distinction between concrete and abstract concepts are still unresolved. In an fMRI study, participants performed a property verification task on abstract and concrete concepts. Property comparisons of concrete concepts were predominantly based on either visual or haptic features. Multivariate pattern analysis successfully distinguished between abstract and concrete stimulus comparisons at the whole brain level. Multivariate searchlight analyses showed that posterior and middle cingulate cortices contained information that distinguished abstract from concrete concepts regardless of feature dominance. These results support the view that supramodal convergence zones play an important role in representation of concrete and abstract concepts.

Representations of modality-specific affective processing for visual and auditory stimuli derived from functional magnetic resonance imaging data.

There is converging evidence that people rapidly and automatically encode affective dimensions of objects, events, and environments that they encounter in the normal course of their daily routines. An important research question is whether affective representations differ with sensory modality. This research examined the nature of the dependency of affect and sensory modality at a whole-brain level of analysis in an incidental affective processing paradigm. Participants were presented with picture and sound stimuli that differed in positive or negative valence in an event-related functional magnetic resonance imaging experiment. Global statistical tests, applied at a level of the individual, demonstrated significant sensitivity to valence within modality, but not valence across modalities. Modality-general and modality-specific valence hypotheses predict distinctly different multidimensional patterns of the stimulus conditions. Examination of lower dimensional representation of the data demonstrated separable dimensions for valence processing within each modality. These results provide support for modality-specific valence processing in an incidental affective processing paradigm at a whole-brain level of analysis. Future research should further investigate how stimulus-specific emotional decoding may be mediated by the physical properties of the stimuli.

Decoding abstract and concrete concept representations based on single-trial fMRI data.

Previously, multi-voxel pattern analysis has been used to decode words referring to concrete object categories. In this study we investigated if single-trial-based brain activity was sufficient to distinguish abstract (e.g., mercy) versus concrete (e.g., barn) concept representations. Multiple neuroimaging studies have identified differences in the processing of abstract versus concrete concepts based on the averaged activity across time by using univariate methods. In this study we used multi-voxel pattern analysis to decode functional magnetic resonance imaging (fMRI) data when participants perform a semantic similarity judgment task on triplets of either abstract or concrete words with similar meanings. Classifiers were trained to identify individual trials as concrete or abstract. Cross-validated accuracies for classifying trials as abstract or concrete were significantly above chance (P < 0.05) for all participants. Discriminating information was distributed in multiple brain regions. Moreover, accuracy of identifying single trial data for any one participant as abstract or concrete was also reliably above chance (P < 0.05) when the classifier was trained solely on data from other participants. These results suggest abstract and concrete concepts differ in representations in terms of neural activity patterns during a short period of time across the whole brain.

Decoding the neural representation of affective states.

Brain activity was monitored while participants viewed picture sets that reflected high or low levels of arousal and positive, neutral, or negative valence. Pictures within a set were presented rapidly in an incidental viewing task while fMRI data were collected. The primary purpose of the study was to determine if multi-voxel pattern analysis could be used within and between participants to predict valence, arousal and combined affective states elicited by pictures based on distributed patterns of whole brain activity. A secondary purpose was to determine if distributed patterns of whole brain activity can be used to derive a lower dimensional representation of affective states consistent with behavioral data. Results demonstrated above chance prediction of valence, arousal and affective states that was robust across a wide range of number of voxels used in prediction. Additionally, individual differences multidimensional scaling based on fMRI data clearly separated valence and arousal levels and was consistent with a circumplex model of affective states.