Biology subjects

Braunlich, K.

Publications and source records attributed to Braunlich, K..

3 recordsLinked to original sources

bioRxiv2026

Translating functional brain activity between humans and monkeys

Comparing brain responses across species is essential for identifying models of human cognition and testing theories of brain evolution, but differences in brain size, measurement techniques, and signal dynamics make it challenging. Here we collected dense fMRI data in macaques and humans using the same movies, static-image sequences, and tasks, and developed a multivariate analysis method that aligns neural representations temporally and spatially. The resulting data-driven framework provides a quantitative translation of brain responses among individuals and between species. Using this framework, we uncovered a broadly conserved cross-species hierarchy of retinotopic visual areas and whole-brain correspondence. Yet within this structure, we found that higher-order macaque areas shared more information with lower-order human areas, particularly during movies, providing evidence of species differences. We also identified potential macaque precursors to human regions involved in high-level cognition, including theory-of-mind and reading. These results offer a blueprint for common representational principles across species.

neuroscience↗

bioRxiv2022

Color and Spatial Frequency Provide Functional Signatures of Retinotopic Visual Areas

Primate vision relies on retinotopically organized cortex defined by representations of hemifield (upper versus lower visual field), eccentricity (fovea versus periphery), and area (V1, V2, V3, V4). To test for the functional signatures of these organizing principles, we used fMRI to measure responses to colored gratings with varying spatial frequency, color, and saturation across rentinotopically defined parcels in macaque monkeys. Using an approach we call Sparse Supervised Embedding (SSE), we identified stimulus features that differed most across the cortical parcels. Constraining the model according to each voxels eccentricity revealed the expected variation of spatial frequency and S-cone modulation with eccentricity. Constraining according to voxel dorsal-ventral location and retinotopic area, revealed two additional components which together provide unexpected functional signatures. First earlier visual areas were more sensitive to contrast and saturation compared to later areas. Second, ventral parcels responded less to luminance contrast and more to color, particularly along the orange-blue intermediate axis in cone-opponent color space. This dorsal-ventral asymmetry resembles differences between candidate dorsal and ventral subdivisions of human V4 but extends to include all retinotopic visual areas, with a magnitude that increased from V1 to V4. Overall, our study demonstrates SSE as a data-driven tool for generating hypotheses about cortical function and behavior, and provides insight into the functional roles of different retinotopic areas. Significance StatementThis study explores the functional roles of visual areas (V1, V2, V3, V4, V3a, MT) parceled by eccentricity preference and visual hemifield. We employ a new approach called Sparse Supervised Embedding (SSE), a promising technique for visualizing and understanding complex neuroimaging datasets. Analyzing fMRI responses to different color grating stimuli, we uncover a functional organization across these parcels, shedding light on their roles in visual computation. This study enhances our knowledge of processing in early visual cortex and how it varies across the retinotopic map. It also aids in resolving apparent differences between prior human and macaque studies.

neuroscience↗

bioRxiv2018

Occipitotemporal Representations Reflect Individual Differences in Conceptual Knowledge

Through selective attention, decision-makers can learn to ignore behaviorally-irrelevant stimulus dimensions. This can improve learning and increase the perceptual discriminability of relevant stimulus information. To account for this effect, popular contemporary cognitive models of categorization typically include of attentional parameters, which provide information about the importance of each stimulus dimension in decision-making. The effect of these parameters on psychological representation is often described geometrically, such that perceptual differences over relevant psychological dimensions are accentuated (or stretched), and differences over irrelevant dimensions are down-weighted (or compressed). In sensory and association cortex, representations of stimulus features are known to covary with their behavioral relevance. Although this implies that neural representational space might closely resemble that hypothesized by formal categorization theory, to date, attentional effects in the brain have been demonstrated through powerful experimental manipulations (e.g., contrasts between relevant and irrelevant features). This approach sidesteps the role of idiosyncratic conceptual knowledge in guiding attention to useful information sources. To bridge this divide, we used formal categorization models, which were fit to behavioral data, to make inferences about the concepts and strategies used by individual participants during decision-making. We found that when greater attentional weight was devoted to a particular visual feature (e.g., \"color\"), its value (e.g., \"red\") was more accurately decoded from occipitotemporal cortex. We additionally found that this effect was sufficiently sensitive to reflect individual differences in conceptual knowledge. The results indicate that occipitotemporal stimulus representations are embedded within a space closely resembling that proposed by classic categorization models.

neuroscience↗