Decoding of task-relevant and task-irrelevant intracranial EEG representations.

Natural stimuli consist of multiple properties. However, not all of these properties are equally relevant in a given situation. In this study, we applied multivariate classification algorithms to intracranial electroencephalography data of human epilepsy patients performing an auditory Stroop task. This allowed us to identify neuronal representations of task-relevant and irrelevant pitch and semantic information of spoken words in a subset of patients. When properties were relevant, representations could be detected after about 350ms after stimulus onset. When irrelevant, the association with gamma power differed for these properties. Patients with more reliable representations of irrelevant pitch showed increased gamma band activity (35-64Hz), suggesting that attentional resources allow an increase in gamma power in some but not all patients. This effect was not observed for irrelevant semantics, possibly because the more automatic processing of this property allowed for less variation in free resources. Processing of different properties of the same stimulus seems therefore to be dependent on the characteristics of the property.

MEG-based decoding of the spatiotemporal dynamics of visual category perception.

Visual processing is a complex task which is best investigated using sensitive multivariate analysis methods that can capture representation-specific brain activity over both time and space. In this study, we applied a multivariate decoding algorithm to MEG data of subjects engaged in passive viewing of images of faces, scenes, bodies and tools. We used reconstructed source-space time courses as input to the algorithm in order to localize brain regions involved in optimal image discrimination. Applying this method to the interval of 115 to 315 ms after stimulus onset, we show a focal localization of regression coefficients in the inferior occipital, middle occipital, and lingual gyrus that drive decoding of the different perceived image categories. Classifier accuracy was highest (over 90% correctly classified trials, compared to a chance level accuracy of 50%) when dissociating the perception of faces from perception of other object categories. Furthermore, we applied this method to each single time point to extract the temporal evolution of visual perception. This allowed for the detection of differences in visual category perception as early as 85 ms after stimulus onset. Furthermore, localizing the corresponding regression coefficients of each time point allowed us to capture the spatiotemporal dynamics of visual category perception. This revealed initial involvement of sources in the inferior occipital, inferior temporal and superior occipital gyrus. During sustained stimulation additional sources in the anterior inferior temporal gyrus and superior parietal gyrus became involved. We conclude that decoding of source-space MEG data provides a suitable method to investigate the spatiotemporal dynamics of ongoing cognitive processing.