Mapping Cytoarchitectonics and Receptor Architectonics to Understand Brain Function and Connectivity

Generative Modelling of Cortical Receptor Distributions from Cytoarchitectonic Images in the Macaque Brain

Neurotransmitter receptor densities are relevant for understanding the molecular architecture of brain regions. Quantitative in vitro receptor autoradiography, has been introduced to map neurotransmitter receptor distributions of brain areas. However, it is very time and cost-intensive, which makes it challenging to obtain whole-brain distributions. At the same time, high-throughput light microscopy and 3D reconstructions have enabled high-resolution brain maps capturing measures of cell density across the whole human brain. Aiming to bridge gaps in receptor measurements for building detailed whole-brain atlases, we study the feasibility of predicting realistic neurotransmitter density distributions from cell-body stainings. Specifically, we utilize conditional Generative Adversarial Networks (cGANs) to predict the density distributions of the M2 receptor of acetylcholine and the kainate receptor for glutamate in the macaque monkey's primary visual (V1) and motor cortex (M1), based on light microscopic scans of cell-body stained sections. Our model is trained on corresponding patches from aligned consecutive sections that display cell-body and receptor distributions, ensuring a mapping between the two modalities. Evaluations of our cGANs, both qualitative and quantitative, show their capability to predict receptor densities from cell-body stained sections while maintaining cortical features such as laminar thickness and curvature. Our work underscores the feasibility of cross-modality image translation problems to address data gaps in multi-modal brain atlases.

A synergetic turn in cognitive neuroscience of brain diseases

Despite significant improvements in our understanding of brain diseases, many barriers remain. Cognitive neuroscience faces four major challenges: complex structure-function associations; disease phenotype heterogeneity; the lack of transdiagnostic models; and oversimplified cognitive approaches restricted to the laboratory. Here, we propose a synergetics framework that can help to perform the necessary dimensionality reduction of complex interactions between the brain, body, and environment. The key solutions include low-dimensional spatiotemporal hierarchies for brain-structure associations, whole-brain modeling to handle phenotype diversity, model integration of shared transdiagnostic pathophysiological pathways, and naturalistic frameworks balancing experimental control and ecological validity. Creating whole-brain models with reduced manifolds combined with ecological measures can improve our understanding of brain disease and help identify novel interventions. Synergetics provides an integrated framework for future progress in clinical and cognitive neuroscience, pushing the boundaries of brain health and disease toward more mature, naturalistic approaches.

A framework to improve the alignment of individual cytoarchitectonic maps of the Julich-Brain atlas using cortical folding landmarks

The segregation of the cortical mantle into cytoarchitectonic areas provides a structural basis for the specialization of different brain regions. In vivo neuroimaging experiments can be linked to this postmortem cytoarchitectonic parcellation via Julich-Brain. This atlas embeds probabilistic maps that account for inter-individual variability in the localization of cytoarchitectonic areas in the reference spaces targeted by spatial normalization. We built a framework to improve the alignment of architectural areas across brains using cortical folding landmarks. This framework, initially designed for in vivo imaging, was adapted to postmortem histological data. We applied this to the first 14 brains used to establish the Julich-Brain atlas to infer a refined atlas with more focal probabilistic maps. The improvement achieved is significant in the primary regions and some of the associative areas. This framework also provides a tool for exploring the relationship between cortical folding patterns and cytoarchitectonic areas in different cortical regions to establish new landmarks in the remainder of the cortex.

Emotion-related impulsivity is related to orbitofrontal cortical sulcation

Background

Emotion-related impulsivity (ERI) describes the trait-like tendency toward poor self-control when experiencing strong emotions. ERI has been shown to be elevated across psychiatric disorders and predictive of the onset and worsening of psychiatric syndromes. Recent work has correlated ERI scores with the neuroanatomy of the orbitofrontal cortex (OFC). Informed by a growing body of research indicating that the morphology of cortical folds (sulci) can produce insights into behavioral outcomes, the present study modeled the association between ERI and the sulcal morphology of OFC at a finer scale than previously conducted.

Methods

Analyses were conducted in a transdiagnostic sample of 118 individuals with a broad range of psychiatric syndromes. We first manually defined over 2000 sulci across the 118 participants. We then implemented a model-based LASSO regression to relate OFC sulcal morphology to ERI and test whether effects were specific to ERI as compared to non-emotion-related impulsivity.

Results

The LASSO regression revealed bilateral associations of ERI with the depth of eight OFC sulci. These effects were specific to ERI and were not observed in non-emotion-related impulsivity. In addition, we identified a new transverse component of the olfactory sulcus in every hemisphere that is dissociable from the longitudinal component based on anatomical features and correlation with behavior, which could serve as a new transdiagnostic biomarker.

Conclusions

The results of this data-driven investigation provide greater neuroanatomical and neurodevelopmental specificity on how OFC is related to ERI. As such, findings link neuroanatomical characteristics to a trait that is highly predictive of psychopathology.