Biology subjects

Linhardt, D.

Publications and source records attributed to Linhardt, D..

5 recordsLinked to original sources

bioRxiv2026

Computational simulations reproduce in vivo population receptive field mapping fMRI results

Population receptive field (pRF) mapping is widely used to characterize retinotopic organization based on functional magnetic resonance imaging (fMRI) data. Despite its broad adoption, the factors governing intra- and inter-subject variability in pRF estimates remain incompletely understood, limiting the ability to evaluate and optimize visual stimulation paradigms prior to data collection. Here, we investigate whether large-scale simulations can reproduce in vivo run-to-run variability patterns observed in pRF mapping and provide mechanistic insight into their origins. With GEMSim-pRF, our newly proposed computational framework for large-scale simulation and estimation of pRF responses, we generated millions of synthetic fMRI time courses across a wide range of receptive field parameters and noise conditions. We analyzed the variability of pRF estimation results derived from simulations and compared them with in vivo data from the publicly available NYU Retinotopy Dataset. Here we show that our simulation results matched the characteristic eccentricity-dependent variability observed in empirical pRF estimates. These findings show that key variability patterns observed in empirical pRF mapping can be successfully reproduced in large-scale simulations, establishing simulation-based analysis as a practical approach for understanding, predicting, evaluating and ultimately improving the behaviour of retinotopic mapping paradigms before empirical data collection.

neuroscience↗

bioRxiv2026

Population receptive field properties of the human visual claustrum zone

The claustrum is a thin, bilateral sheet of grey matter between the insula and putamen that stands out by its high interconnectivity with almost the entire cortex. Despite continuing research in humans and animals, its functional role remains largely unknown. In the present study, we explored the topographic organization of the recently described human visual claustrum zone. We performed a population receptive field (pRF) analysis on the 7T retinotopy dataset of the Young Adult Human Connectome Project (N = 181, 109 female) comparing the visual claustrum with established visual field properties of the lateral geniculate nucleus, the primary visual cortex, and higher-level topographic maps of the dorsal and the ventral stream. Our results demonstrate for the first time that the human visual claustrum showed several topographic properties typical for visual areas, including a representational bias towards the contralateral visual field, and a pRF size increase with increasing eccentricity. At the same time, the claustrum also exhibited a positive eccentricity gradient along the posterior-anterior axis, an extended representation of the visual periphery compared to other areas and a lack of horizontal meridian bias. These latter two properties highlight the claustrums role as a higher-level nucleus which is less dependent on sensory input. This study is the first to characterize the topographic organization of the visual claustrum zone in humans, highlighting its uniqueness among the known visually responsive regions. Significance StatementThe claustrum is a thin subcortical brain region whose function is still largely unknown. Previous animal studies showing unimodal sensory zones within the nucleus suggest an involvement in sensory processing. The present study focuses on the visual claustrum zone and is the first to characterize its topographic organization in humans. We used population receptive field mapping for functional Magnetic Resonance Imaging on the 7T retinotopy dataset of the human connectome project. We could demonstrate similarities to other visually responsive areas and characteristics that distinguish the visual claustrum. Our study yields important information on the claustrums visuotopic organization that can guide further investigation of its role in visual processing and cognition.

neuroscience↗

bioRxiv2025

Predicting functional topography of the human visual cortex from cortical anatomy at scale

Topographic organization, whereby neighboring cortical locations encode neighboring features in sensory or cognitive space, is a fundamental principle of brain function. Existing approaches for obtaining individual-specific topographic maps either require resource-intensive functional neuroimaging or, when relying on population atlases, lack precision for individual-level inference. Here, we introduce deepRetinotopy toolbox, a deep learning-based application for predicting the functional topographic organization of human visual cortex from cortical anatomy alone. DeepRetinotopy toolbox produces accurate retinotopic maps across diverse experimental conditions, imaging sites, and scanner types. We demonstrate how predicted maps can be utilized to automatically generate individual-specific visual area boundaries, overcoming common biases in manual annotations. Finally, we applied our method to 11,060 anatomical scans, which allowed us to quantify age-related changes in the functional organization of visual cortex predictable from anatomy alone, underscoring the methods broad utility for scalable, anatomy-based functional brain mapping.

neuroscience↗

bioRxiv2025

GEM-pRF: GPU-Empowered Mapping of Population Receptive Fields for Large-Scale fMRI Analysis

Population receptive field (pRF) mapping is a fundamental technique for understanding retinotopic organization of the human visual system. Since its introduction in 2008, however, its scalability has been severely hindered by the computational bottleneck of iterative parameter refinement. Current state-of-the-art implementations either sacrifice precision for speed or rely on slow iterative parameter updates, limiting their applicability to large-scale datasets. Here, we present a novel mathematical reformulation of the General Linear Model (GLM), wrapped in a GPU-Empowered Mapping of population Receptive Fields (GEM-pRF) software implementation. By orthogonalizing the design matrix, our approach enables the direct and fast computation of the objective functions derivatives, which are used to eliminate the iterative refinement process. This approach dramatically accelerates pRF estimation while maintaining full accuracy. Validation using empirical and simulated data confirms GEM-pRFs accuracy, and benchmarking against established tools demonstrates an order-of-magnitude reduction in computation time. With its modular and extensible design, GEM-pRF provides a critical advancement for large-scale fMRI retinotopic mapping. Furthermore, our reformulated GLM approach in combination with GPU-based implementation offer a broadly applicable solution that may extend beyond visual neuroscience, accelerating computational modelling across various domains in neuroimaging and beyond.

neuroscience↗

bioRxiv2023

High-resolution 7T fMRI reveals the visual sensory zone of the human claustrum

The claustrum is a thin subcortical gray matter structure located between the insula and the putamen. It has numerous bilateral connections with the cortex and is thought to play an important role in higher-level aspects of perception and cognition, with hypotheses including multisensory integration, attention and consciousness. The claustrums thin shape makes it difficult to investigate, leaving the hypothesis regarding its function largely untested. In the current study, we used high-resolution ultra-high field (7 Tesla) functional magnetic resonance imaging (fMRI) to measure claustrum activity in human participants, while they were presented with visual, auditory or audiovisual naturalistic stimuli. We found distinct visual responses in the claustrum at a spatial location that was consistent across participants, hemispheres and scanning sessions. This is the first study to demonstrate evoked sensory responses within the human claustrum. It opens the possibility for future noninvasive investigation of the claustrums role in sensory processing.

neuroscience↗