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Carlson, T. A.

Publications and source records attributed to Carlson, T. A..

3 recordsLinked to original sources

The representational dynamics of visual objects in rapid serial visual processing streams

In our daily lives, we are bombarded with a stream of rapidly changing visual input. Humans have the remarkable capacity to detect and identify objects in fast-changing scenes. Yet, when studying brain representations, stimuli are generally presented in isolation. Here, we studied the dynamics of human vision using a combination of fast stimulus presentation rates, electroencephalography and multivariate decoding analyses. Using a presentation rate of 5 images per second, we obtained the representational structure of a large number of stimuli, and showed the emerging abstract categorical organisation of this structure. Furthermore, we could separate the temporal dynamics of perceptual processing from higher-level target selection effects. In a second experiment, we used the same paradigm at 20Hz to show that shorter image presentation limits the categorical abstraction of object representations. Our results show that applying multivariate pattern analysis to every image in rapid serial visual processing streams has unprecedented potential for studying the temporal dynamics of the structure of representations in the human visual system.

neuroscience

Neural signatures of dynamic emotion constructs in the human brain

How is emotion represented in the brain: is it categorical or along dimensions? In the present study, we applied multivariate pattern analysis (MVPA) to magnetoencephalography (MEG) to study the brains temporally unfolding representations of different emotion constructs. First, participants rated 525 images on the dimensions of valence and arousal and by intensity of discrete emotion categories (happiness, sadness, fear, disgust, and sadness). Thirteen new participants then viewed subsets of these images within an MEG scanner. We used Representational Similarity Analysis (RSA) to compare behavioral ratings to the unfolding neural representation of the stimuli in the brain. Ratings of valence and arousal explained significant proportions of the MEG data, even after corrections for low-level image properties. Additionally, behavioral ratings of the discrete emotions fear, disgust, and happiness significantly predicted early neural representations, whereas rating models of anger and sadness did not. Different emotion constructs also showed unique temporal signatures. Fear and disgust - both highly arousing and negative - were rapidly discriminated by the brain, but disgust was represented for an extended period of time relative to fear. Overall, our findings suggest that 1) dimensions of valence and arousal are quickly represented by the brain, as are some discrete emotions, and 2) different emotion constructs exhibit unique temporal dynamics. We discuss implications of these findings for theoretical understanding of emotion and for the interplay of discrete and dimensional aspects of emotional experience.

neuroscience

Asymmetric compression of representational space for object animacy categorization under degraded viewing conditions

Animacy is a robust organizing principle amongst object category representations in the human brain. Using multivariate pattern analysis methods (MVPA), it has been shown that distance to the decision boundary of a classifier trained to discriminate neural activation patterns for animate and inanimate objects correlates with observer reaction times for the same animacy categorization task (Carlson, Ritchie, Kriegeskorte, Durvasula, & Ma, 2014; Ritchie, Tovar, & Carlson, 2015). Using MEG decoding, we tested if the same relationship holds when a stimulus manipulation (degradation) increases task difficulty, which we predicted would systematically decrease the distance of activation patterns from the decision boundary, and increase reaction times. In addition, we tested whether distance to the classifier boundary correlates with drift rates in the Linear Ballistic Accumulator (Brown & Heathcote, 2008). We found that distance to the classifier boundary correlated with reaction time, accuracy, and drift rates in an animacy categorization task. Split by animacy, the correlations between brain and behavior were sustained for longer over the time course for animate than for inanimate stimuli. Interestingly, when examining the distance to the classifier boundary during the peak correlation between brain and behavior, we found that only degraded versions of animate, but not inanimate, objects had systematically shifted towards the classifier decision boundary as predicted. Our results support an asymmetry in the representation of animate and inanimate object categories in the human brain.

neuroscience