Mapping Cytoarchitectonics and Receptor Architectonics to Understand Brain Function and Connectivity

Zachlod, Daniel; Palomero-Gallagher, Nicola; Dickscheid, Timo; Amunts, Katrin

doi:10.1016/j.biopsych.2022.09.014

Cited by 13 publications

(6 citation statements)

References 71 publications

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“…Nevertheless, it may be tempting to also conclude that these structures are the most important neuroanatomical link to ERI (i.e., a more localized “modular” view). We emphasize that the neuroanatomical underpinnings of ERI likely include many more neuroanatomical structures across spatial scales and that our present findings are the next step in uncovering the infrastructure of a complex neural network underlying ERI that is presently unknown (56). Indeed, previous findings relating sulcal morphology to cognition in different populations discuss the relationship between sulcal morphology and network connectivity with an emphasis on white matter architecture (11,12,15,57–60).…”

Section: Discussionmentioning

confidence: 79%

Emotion-related impulsivity is related to orbitofrontal cortical sulcation

Hastings,

Willbrand,

Elliott

et al. 2024

Preprint

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BackgroundEmotion-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.MethodsAnalyses 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.ResultsThe 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.ConclusionsThe 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.

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Section: Discussionmentioning

confidence: 79%

Emotion-related impulsivity is related to orbitofrontal cortical sulcation

Hastings,

Willbrand,

Elliott

et al. 2024

Preprint

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“…We focussed on assessing the explanatory power of cortical neurotransmitter receptors as key mediators of signal transduction between neurons (2, 65, 66). Aggregated regional receptor compositions represent a useful descriptor with molecular specificity, which may approximate meso- and macroscale electrophysiology (35–37). And topographic overlap of receptor density data and electrophysiological frequency bands was previously shown statistically (32).…”

Section: Discussionmentioning

confidence: 99%

Topographic variation in neurotransmitter receptor densities explains differences in intracranial EEG spectra

Stoof,

Friston,

Tisdall

et al. 2024

Preprint

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Neurotransmitter receptor expression and neuronal population dynamics show regional variability across the human cortex. However, currently there is an explanatory gap regarding how cortical microarchitecture and mesoscopic electrophysiological signals are mechanistically related, limiting our ability to exploit these measures of brain (dys)function for improved treatments of brain disorder; e.g., epilepsy. To bridge this gap, we leveraged dynamic causal modelling (DCM) and fitted biophysically informed neural mass models to a normative set of intracranial EEG data. Subsequently, using a hierarchical Bayesian modelling approach, we evaluated whether model evidence improved when information about regional neurotransmitter receptor densities is provided. We then tested whether the inferred constraints - furnished by receptor density - generalise across different electrophysiological recording modalities. The neural mass models explained regionally specific intracranial EEG spectra accurately, when fitted independently. Incorporating prior information on receptor distributions, further improved model evidence, indicating that variability in receptor density explains some variance in cortical population dynamics. The output of this modelling provides a cortical atlas of neurobiologically informed intracortical synaptic connectivity parameters that can be used as empirical priors in future - e.g., patient specific - modelling, as demonstrated in a worked example (a single-subject mismatch negativity study). In summary, we show that molecular cortical characteristics (i.e., receptor densities) can be incorporated to improve generative, biophysically plausible models of coupled neuronal populations. This work can help to explain regional variations in human electrophysiology, may provide a methodological foundation to integrate multi-modal data, and might serve as a normative resource for future DCM studies of electrophysiology.

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“…A new freely available dataset aligns block face images and microscopic sections stained for histology or immuhistochemistry with 7-T MRI images for two human brains ( Alkemade et al, 2022 ). Furthermore, detailed human cytoarchitecture and receptor densities are gathered in the BigBrain( Amunts et al, 2013 ; Wagstyl et al, 2020 ; Zachlod et al, 2023 ), and are still being complemented with new measurements. These data follow the Julich-Brain parcellation ( Amunts et al, 2020 ), which is more fine-grained than the Desikan-Killiany parcellation used here.…”

Section: Discussionmentioning

confidence: 99%

“…Enabling further model refinement, a number of valuable resources and results have recently been published, detailing various aspects of histology, immunohistochemistry (Alkemade et al, 2022), transcriptomics (Jorstad et al, 2023; Siletti et al, 2023), and depth-resolved fMRI (Pais-Roldán et al, 2023) of the human brain. Furthermore, detailed human cytoarchitecture and receptor densities are gathered in the BigBrain (Amunts et al, 2013; Wagstyl et al, 2020; Zachlod et al, 2023), and are still being complemented with new measurements. These data follow the Julich-Brain parcellation (Amunts et al, 2020), which is more fine-grained than the Desikan-Killiany parcellation used here.…”

Section: Discussionmentioning

confidence: 99%

Multi-Scale Spiking Network Model of Human Cerebral Cortex

Pronold

Meegen

Vollenbroeker

et al. 2023

Preprint

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Although the structure of cortical networks provides the necessary substrate for their neuronal activity, the structure alone does not suffice to understand it. 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 1mm2 column with a layered structure. The model aggregates data across multiple modalities, including electron microscopy, electrophysiology, morphological reconstructions, and DTI, into a coherent framework. It predicts activity on all scales from single-neuron spiking activity to the area-level functional connectivity. We compared the model activity against human electrophysiological data and human resting-state fMRI data. This comparison reveals that the model can reproduce both spiking statistics and fMRI correlations if the cortico-cortical connections are sufficiently strong. Furthermore, we show that a single-spike perturbation propagates through the network within a time close to the limit imposed by the delays.

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Mapping Cytoarchitectonics and Receptor Architectonics to Understand Brain Function and Connectivity

Cited by 13 publications

References 71 publications

Emotion-related impulsivity is related to orbitofrontal cortical sulcation

Emotion-related impulsivity is related to orbitofrontal cortical sulcation

Topographic variation in neurotransmitter receptor densities explains differences in intracranial EEG spectra

Multi-Scale Spiking Network Model of Human Cerebral Cortex

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