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Dual-axes of functional organisation across lateral parietal cortex: the angular gyrus forms part of a multi-modal buffering system
Decades of neuropsychological and neuroimaging evidence have implicated the lateral parietal cortex (LPC) in a myriad of cognitive domains, generating numerous influential theoretical models. However, these theories fail to explain why distinct cognitive activities appear to implicate common neural...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9813060/ https://www.ncbi.nlm.nih.gov/pubmed/35670844 http://dx.doi.org/10.1007/s00429-022-02510-0 |
Sumario: | Decades of neuropsychological and neuroimaging evidence have implicated the lateral parietal cortex (LPC) in a myriad of cognitive domains, generating numerous influential theoretical models. However, these theories fail to explain why distinct cognitive activities appear to implicate common neural regions. Here we discuss a unifying model in which the angular gyrus forms part of a wider LPC system with a core underlying neurocomputational function; the multi-sensory buffering of spatio-temporally extended representations. We review the principles derived from computational modelling with neuroimaging task data and functional and structural connectivity measures that underpin the unified neurocomputational framework. We propose that although a variety of cognitive activities might draw on shared underlying machinery, variations in task preference across angular gyrus, and wider LPC, arise from graded changes in the underlying structural connectivity of the region to different input/output information sources. More specifically, we propose two primary axes of organisation: a dorsal–ventral axis and an anterior–posterior axis, with variations in task preference arising from underlying connectivity to different core cognitive networks (e.g. the executive, language, visual, or episodic memory networks). |
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