David R. Andresen

The representation of object viewpoint in human visual cortex.

Understanding the nature of object representations in the human brain is critical for understanding the neural basis of invariant object recognition. However, the degree to which object representations are sensitive to object viewpoint is unknown. Using fMRI we employed a parametric approach to examine the sensitivity to object view as a function of rotation (0 degrees-180 degrees ), category (animal/vehicle) and fMRI-adaptation paradigm (short or long-lagged). For both categories and fMRI-adaptation paradigms, object-selective regions recovered from adaptation when a rotated view of an object was shown after adaptation to a specific view of that object, suggesting that representations are sensitive to object rotation. However, we found evidence for differential representations across categories and ventral stream regions. Rotation cross-adaptation was larger for animals than vehicles, suggesting higher sensitivity to vehicle than animal rotation, and was largest in the left fusiform/occipito-temporal sulcus (pFUS/OTS), suggesting that this region has low sensitivity to rotation. Moreover, right pFUS/OTS and FFA responded more strongly to front than back views of animals (without adaptation) and rotation cross-adaptation depended both on the level of rotation and the adapting view. This result suggests a prevalence of neurons that prefer frontal views of animals in fusiform regions. Using a computational model of view-tuned neurons, we demonstrate that differential neural view tuning widths and relative distributions of neural-tuned populations in fMRI voxels can explain the fMRI results. Overall, our findings underscore the utility of parametric approaches for studying the neural basis of object invariance and suggest that there is no complete invariance to object view in the human ventral stream.

Does a causal relation exist between the functional hemispheric asymmetries of visual processing subsystems

Past research indicates that specific shape recognition and spatial-relations encoding rely on subsystems that exhibit right-hemisphere advantages, whereas abstract shape recognition and spatial-relations encoding rely on subsystems that exhibit left-hemisphere advantages. Given these apparent regularities, we tested whether asymmetries in shape processing are causally related to asymmetries in spatial-relations processing. We examined performance in four tasks using the same stimuli with divided-visual-field presentations. Importantly, the asymmetry observed in any one task did not correlate with the asymmetries observed in the other tasks in ways predicted by extant theories. Asymmetries in shape processing and spatial-relations encoding may not be due to a common causal force influencing multiple subsystems.

Effector-independent and effector-dependent sequence representations underlie general and specific perceptuomotor sequence learning

ABSTRACT Perceptuomotor sequence learning could be due to learning of effector-independent sequence information (e.g., response locations), effector-dependent information (e.g., motor movements of a particular effector), or both. Evidence also suggests that learning of statistical regularities in sequences (general-regularity learning) and specific sequences (specific-sequence learning) are dissociable. The authors examined the degree to which general and specific-sequence learning rely on effector-independent and effector-dependent representations. During training, participants typed sequences that followed a construction rule with a subset of sequences repeatedly processed. At test, effector-independent and effector-dependent learning was examined with respect to general-regularity and specific-sequence learning. Results suggest that general-regularity learning is subserved by effector-independent sequence representations, whereas specific-sequence learning is subserved by effector-dependent sequence representations, further dissociating these types of learning.