Mapping Cytoarchitectonics and Receptor Architectonics to Understand Brain Function and Connectivity

Relationships and representations of brain structures, connectivity, dynamics and functions

The review explores the complex interplay between brain structures and their associated functions, presenting a diversity of hierarchical models that enhances our understanding of these relationships. Central to this approach are structure-function flow diagrams, which offer a visual representation of how specific neuroanatomical structures are linked to their functional roles. These diagrams are instrumental in mapping the intricate connections between different brain regions, providing a clearer understanding of how functions emerge from the underlying neural architecture. The study details innovative attempts to develop new functional hierarchies that integrate structural and functional data. These efforts leverage recent advancements in neuroimaging techniques such as fMRI, EEG, MEG, and PET, as well as computational models that simulate neural dynamics. By combining these approaches, the study seeks to create a more refined and dynamic hierarchy that can accommodate the brain's complexity, including its capacity for plasticity and adaptation. A significant focus is placed on the overlap of structures and functions within the brain. The manuscript acknowledges that many brain regions are multifunctional, contributing to different cognitive and behavioral processes depending on the context. This overlap highlights the need for a flexible, non-linear hierarchy that can capture the brain's intricate functional landscape. Moreover, the study examines the interdependence of these functions, emphasizing how the loss or impairment of one function can impact others. Another crucial aspect discussed is the brain's ability to compensate for functional deficits following neurological diseases or injuries. The investigation explores how the brain reorganizes itself, often through the recruitment of alternative neural pathways or the enhancement of existing ones, to maintain functionality despite structural damage. This compensatory mechanism underscores the brain's remarkable plasticity, demonstrating its ability to adapt and reconfigure itself in response to injury, thereby ensuring the continuation of essential functions. In conclusion, the study presents a system of brain functions that integrates structural, functional, and dynamic perspectives. It offers a robust framework for understanding how the brain's complex network of structures supports a wide range of cognitive and behavioral functions, with significant implications for both basic neuroscience and clinical applications.

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 region-level neuroanatomical properties of the orbitofrontal cortex (OFC), but not posteromedial cortex (PMC). Informed by a growing body of research indicating that examining the morphology of specific cortical folds (sulci) can produce unique insights into behavioral outcomes, the present study modeled the association between ERI and the morphology of sulci within OFC and PMC, which is a finer scale than previously conducted.

METHODS

Analyses were conducted in a transdiagnostic sample of 118 adult individuals with a broad range of psychiatric syndromes. First, we manually defined over 4,000 sulci across 236 cerebral hemispheres. Second, we implemented a model-based LASSO regression to relate OFC sulcal morphology to ERI. Third, we tested whether effects were specific to OFC sulci, sulcal depth, and ERI (as compared to PMC sulci, sulcal gray matter thickness, and non-emotion-related impulsivity).

RESULTS

The LASSO regression revealed bilateral associations of ERI with the depths of eight OFC sulci. These effects were strongest for OFC sulci, sulcal depth, and ERI in comparison to PMC sulci, sulcal gray matter thickness, and 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.

Reduced Vestibular Function is Associated with Cortical Surface Shape Changes in the Frontal Cortex

Aging-associated decline in peripheral vestibular function is linked to deficits in executive ability, self-motion perception, and motor planning and execution. While these behaviors are known to rely on the sensorimotor and frontal cortices, the precise pathways involving the frontal and sensorimotor cortices in these vestibular-associated behaviors are unknown. To fill this knowledge gap, this cross-sectional study investigates the relationship between age-related variation in vestibular function and surface shape alterations of the frontal and sensorimotor cortices, considering age, intracranial volume, and sex. Data from 117 participants aged 60+ from the Baltimore Longitudinal Study of Aging, who underwent end-organ-specific vestibular tests (cVEMP for the saccule, oVEMP for the utricle, and vHIT for the horizontal canal) and T1-weighted MRI scans on the same visit, were analyzed. We examined ten brain structures in the putative "vestibular cortex": the middle-superior part of the prefrontal cortex (SFG_PFC), frontal pole (SFG_pole), and posterior pars of the superior frontal gyrus (SFG), the dorsal prefrontal cortex and posterior pars of middle frontal gyrus (MFG_DPFC, MFG), the pars opercularis, pars triangularis, and pars orbitalis of the inferior frontal gyrus, as well as the precentral gyrus and postcentral gyrus (PoCG) of the sensori-motor cortex. For each region of interest (ROI), shape descriptors were estimated as local compressions and expansions of the population average ROI surface using surface LDDMM. Shape descriptors were linearly regressed onto standardized vestibular variables, age, intracranial volume, and sex. Lower utricular function was linked with surface compression in the left MFG and expansion in the bilateral SFG_pole and left SFG. Reduced canal function was associated with surface compression in the right SFG_PFC and SFG_pole and left SFG. Both reduced saccular and utricular function correlated with surface compression in the posterior medial part of the left MFG. Our findings illuminate the complexity of the relationship between vestibular function and the morphology of the frontal and sensorimotor cortices in aging. Improved understanding of these relationships could help in developing interventions to enhance quality of life in aging and populations with cognitive impairment.

α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid (AMPA) receptor density underlies intraregional and interregional functional centrality

Local and global functional connectivity densities (lFCD and gFCD, respectively), derived from functional magnetic resonance imaging (fMRI) data, represent the degree of functional centrality within local and global brain networks. While these methods are well-established for mapping brain connectivity, the molecular and synaptic foundations of these connectivity patterns remain unclear. Glutamate, the principal excitatory neurotransmitter in the brain, plays a key role in these processes. Among its receptors, the α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid receptor (AMPAR) is crucial for neurotransmission, particularly in cognitive functions such as learning and memory. This study aimed to examine the association of the AMPAR density and FCD metrics of intraregional and interregional functional centrality. Using [11C]K-2, a positron emission tomography (PET) tracer specific for AMPARs, we measured AMPAR density in the brains of 35 healthy participants. Our findings revealed a strong positive correlation between AMPAR density and both lFCD and gFCD-lFCD across the entire brain. This correlation was especially notable in key regions such as the anterior cingulate cortex, posterior cingulate cortex, pre-subgenual frontal cortex, Default Mode Network, and Visual Network. These results highlight that postsynaptic AMPARs significantly contribute to both local and global functional connectivity in the brain, particularly in network hub regions. This study provides valuable insights into the molecular and synaptic underpinnings of brain functional connectomes.

Multi-scale spiking network model of human cerebral cortex

Although the structure of cortical networks provides the necessary substrate for their neuronal activity, the structure alone does not suffice to understand the activity. Leveraging the increasing availability of human data, we developed a multi-scale, spiking network model of human cortex to investigate the relationship between structure and dynamics. In this model, each area in one hemisphere of the Desikan-Killiany parcellation is represented by a $1\,\mathrm{mm^{2}}$ column with a layered structure. The model aggregates data across multiple modalities, including electron microscopy, electrophysiology, morphological reconstructions, and diffusion tensor imaging, into a coherent framework. It predicts activity on all scales from the single-neuron spiking activity to the area-level functional connectivity. We compared the model activity with human electrophysiological data and human resting-state functional magnetic resonance imaging (fMRI) data. This comparison reveals that the model can reproduce aspects of both spiking statistics and fMRI correlations if the inter-areal connections are sufficiently strong. Furthermore, we study the propagation of a single-spike perturbation and macroscopic fluctuations through the network. The open-source model serves as an integrative platform for further refinements and future in silico studies of human cortical structure, dynamics, and function.

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.