Multimodal laminar characterization of visual areas along the cortical hierarchy

Abstract

Understanding the relationship between brain structure and function is a central goal in neuroscience. While post-mortem studies using microscopic techniques have provided detailed insights into the brains cytoarchitectonic and myeloarchitectonic patterns, linking these structural findings to functional outcomes remains challenging. Magnetic resonance imaging (MRI) has emerged as a powerful non-invasive tool for studying both structure and function, but discrepancies in spatial resolution between structural and functional imaging, especially in layer-fMRI, complicate the interpretation of functional results. In this study, we explore how visual cortical hierarchy relates to microscopic and mesoscopic laminar features. Focusing on visual areas that span progressive hierarchical levels, V1, V2, V3, and hMT+, we apply a multimodal approach combining post-mortem histology, post-mortem and in-vivo quantitative MRI (qMRI), and resting-state layer-fMRI. Using the open-access post-mortem AHEAD dataset, which integrates histological and qMRI contrasts from the same brain samples, we bridge microscopic observations with qMRI data. In parallel, we incorporate high-resolution [Formula] MRI and resting-state layer-fMRI from the same participant, allowing for a comparative analysis of laminar profiles across cortical depth. For computing laminar profiles, we developed an analysis pipeline that bridges histology images, mesoscopic qMRI, and layer-fMRI. Our findings highlight parvalbumin laminar profiles (reflecting interneuron parvalbumin density) as the most discriminative feature for differentiating brain areas. Additionally, we report laminar quantitative [Formula] profiles from post-mortem and in-vivo data, together with [Formula]-weighted resting-state layer-fMRI, all of which exhibit a similar overall shape across modalities. Using our methodological framework, a similar laminar characterization can be extended to study other brain regions. Generative models for layer fMRI will benefit from incorporating these new empirical microstructural (parvalbumin) and physical quantitative [Formula] data, leading to more area-specific and accurate models. HighlightsO_LIWe present a multimodal analysis of the laminar organization of four visual regions (V1, V2, V3, hMT+), characterizing progressive visual hierarchy levels in humans. This analysis spans from post-mortem microscopy and quantitative MRI (qMRI) to in-vivo qMRI and laminar fMRI during resting state. C_LIO_LIAmong the three microscopy contrasts, parvalbumin, a marker of interneuron density, emerges as the most distinctive regional feature. Notably, the parvalbumin laminar profiles vary across hierarchy levels, with hMT+ showing the greatest divergence compared to V1, V2, and V3. C_LIO_LIQuantitative [Formula] measurements, from both post-mortem and in-vivo data, reveal a clear increase towards the superficial cortical layers. These depth-dependent patterns closely mirror the laminar profiles observed in both task and resting-state fMRI. C_LIO_LISurprisingly, no substantial difference was observed in laminar [Formula] profiles between post-mortem and in-vivo data across the visual areas. C_LI