ReviewProgress in neurobiology2023
Neurobiological mechanisms for language, symbols and concepts: Clues from brain-constrained deep neural networks.
Review in Progress in neurobiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Research trends in post-stroke aphasia (2004-2024): a bibliometric and visualized analysis.Frontiers in neurology · 2025Pooled it
- What is so hard about abstract words, anyways? A neuromechanistic explanation using brain-constrained neural network models.Cognitive neurodynamics · 2026Article
- A brain-constrained neural model of cognition and language with NEST: transitioning from the Felix framework.Cognitive neurodynamics · 2026Article
- Article
- From Spontaneous Ignitions to Sensorimotor Cell Assemblies via Dopamine: A Spiking Neurocomputational Model of Infants' Hand Action Acquisition.Brain sciences · 2026Article
- Visualization of functional and effective connectivity underlying auditory descriptive naming.Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology · 2025Article
- Analysis of argument structure constructions in a deep recurrent language model.Frontiers in computational neuroscience · 2025Article
- Analysis of argument structure constructions in the large language model BERT.Frontiers in artificial intelligence · 2025Article
- The cost of language: functionally over-dominant language circuits in the human brain may limit cognitive abilities and non-verbal executive functions.Frontiers in human neuroscience · 2025Article
- On the ability of standard and brain-constrained deep neural networks to support cognitive superposition: a position paper.Cognitive neurodynamics · 2024Article
- Active Inference and Social Actors: Towards a Neuro-Bio-Social Theory of Brains and Bodies in Their Worlds.Kolner Zeitschrift fur Soziologie und Sozialpsychologie · 2024Article
- Exploring neural oscillations during speech perception via surrogate gradient spiking neural networks.Frontiers in neuroscience · 2024Article
Corrections and comments
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1 author.
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Abstract
Neural networks are successfully used to imitate and model cognitive processes. However, to provide clues about the neurobiological mechanisms enabling human cognition, these models need to mimic the structure and function of real brains. Brain-constrained networks differ from classic neural networks by implementing brain similarities at different scales, ranging from the micro- and mesoscopic levels of neuronal function, local neuronal links and circuit interaction to large-scale anatomical structure and between-area connectivity. This review shows how brain-constrained neural networks can be applied to study in silico the formation of mechanisms for symbol and concept processing and to work towards neurobiological explanations of specifically human cognitive abilities. These include verbal working memory and learning of large vocabularies of symbols, semantic binding carried by specific areas of cortex, attention focusing and modulation driven by symbol type, and the acquisition of concrete and abstract concepts partly influenced by symbols. Neuronal assembly activity in the networks is analyzed to deliver putative mechanistic correlates of higher cognitive processes and to develop candidate explanations founded in established neurobiological principles.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.