ArticleAdvances in experimental medicine and biology2022
Bringing Anatomical Information into Neuronal Network Models.
Article in Advances in experimental medicine and biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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15 citing papers in PubMed.
- A brain-constrained neural model of cognition and language with NEST: transitioning from the Felix framework.Cognitive neurodynamics · 2026Article
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- From cortical and white matter structure to meaning: a brain-constrained neural network of semantic grounding in action and perception.Frontiers in human neuroscience · 2026Article
- Advances in Neuroimaging and Deep Learning for Emotion Detection: A Systematic Review of Cognitive Neuroscience and Algorithmic Innovations.Diagnostics (Basel, Switzerland) · 2025Review
- Multi-scale spiking network model of human cerebral cortex.Cerebral cortex (New York, N.Y. : 1991) · 2024Article
- Reconciliation of weak pairwise spike-train correlations and highly coherent local field potentials across space.Cerebral cortex (New York, N.Y. : 1991) · 2024Article
- A layered microcircuit model of somatosensory cortex with three interneuron types and cell-type-specific short-term plasticity.Cerebral cortex (New York, N.Y. : 1991) · 2024Article
- Neurobiological mechanisms for language, symbols and concepts: Clues from brain-constrained deep neural networks.Progress in neurobiology · 2023Review
- Ubiquitous lognormal distribution of neuron densities in mammalian cerebral cortex.Cerebral cortex (New York, N.Y. : 1991) · 2023Article
- Interpretable machine learning approach for neuron-centric analysis of human cortical cytoarchitecture.Scientific reports · 2023Article
- Translating single-neuron axonal reconstructions into meso-scale connectivity statistics in the mouse somatosensory thalamus.Frontiers in neuroinformatics · 2023Article
- Connectivity concepts in neuronal network modeling.PLoS computational biology · 2022Review
- Systematic perturbation of an artificial neural network: A step towards quantifying causal contributions in the brain.PLoS computational biology · 2022Article
- Article
- Biological constraints on neural network models of cognitive function.Nature reviews. Neuroscience · 2021Review
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9 authors.
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Abstract
For constructing neuronal network models computational neuroscientists have access to wide-ranging anatomical data that nevertheless tend to cover only a fraction of the parameters to be determined. Finding and interpreting the most relevant data, estimating missing values, and combining the data and estimates from various sources into a coherent whole is a daunting task. With this chapter we aim to provide guidance to modelers by describing the main types of anatomical data that may be useful for informing neuronal network models. We further discuss aspects of the underlying experimental techniques relevant to the interpretation of the data, list particularly comprehensive data sets, and describe methods for filling in the gaps in the experimental data. Such methods of "predictive connectomics" estimate connectivity where the data are lacking based on statistical relationships with known quantities. Exploiting organizational principles that link the plethora of data in a unifying framework can be useful for informing computational models. Besides overarching principles, we touch upon the most prominent features of brain organization that are likely to influence predicted neuronal network dynamics, with a focus on the mammalian cerebral cortex. Given the still existing need for modelers to navigate a complex data landscape full of holes and stumbling blocks, it is vital that the field of neuroanatomy is moving toward increasingly systematic data collection, representation, and publication.
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