Olman, C. A. | bioRxiv Science

bioRxiv2019

Defining region-specific masks for reliable depth-dependent analysis of fMRI data

In high-field fMRI research, anatomical reference information (e.g., gray matter (GM) segmentation, cortical depth delineation) is often defined in volumes acquired with pulse sequences subject to different distortions than those in functional volumes. In these cases, reliable interpretation of ultra-high resolution fMRI data depends on excellent cross-modal registration of functional volumes to reference anatomical volumes. In this paper, we describe a two-step approach to automating assessments of cross-modal registration quality for the purpose of guiding depth-dependent analysis. First, each functional/anatomical registration was scored by the ratio of the number of GM voxels in the functional data overlapping anatomical GM to the number of GM voxels in the functional data overlapping anatomical white matter (WM). This GM:WM overlap ratio provided an objective metric for determining whether an alignment algorithm had converged on a solution that would pass visual inspection. Second, surface-based maps indicating the consistency of overlap between functional and anatomical GM throughout the GM depth were generated for the entire region of cortex covered by the experiment. These maps served as a mask for the purpose of excluding regions where registration between functional and anatomical data was inadequate and thus unable to support depth-dependent analyses. We found, for both real and simulated data, that functional response profiles that were less biased toward superficial responses in regions where these metrics indicated satisfactory registration.

neuroscience↗

bioRxiv2018

Human brain activity during mental imagery exhibits signatures of inference in a hierarchical generative model

Humans have long wondered about the function of mental imagery and its relationship to vision. Although visual representations are utilized during imagery, the computations they subserve are unclear. Building on a theory that treats vision as inference about the causes of sensory stimulation in an internal generative model, we propose that mental imagery is inference about the sensory consequences of predicted or remembered causes. The relation between these complementary inferences yields a relation between the brain activity patterns associated with imagery and vision. We show that this relation has the formal structure of an echo that makes encoding of imagined stimuli in low-level visual areas resemble the encoding of seen stimuli in higher areas. To test for evidence of this echo effect we developed imagery encoding models--a new tool for revealing how imagined stimuli are encoded in brain activity. We estimated imagery encoding models from brain activity measured with fMRI while human subjects imagined complex visual stimuli, and then compared these to visual encoding models estimated from a matched viewing experiment. Consistent with an echo effect, imagery encoding models in low-level visual areas exhibited decreased spatial frequency preference and larger, more foveal receptive fields, thus resembling visual encoding models in high-level visual areas where imagery and vision appeared to be almost interchangeable. Our findings support an interpretation of mental imagery as a predictive inference that is conditioned on activity in high-level visual cortex, and is related to vision through shared dependence on an internal model of the visual world.

neuroscience↗