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001050720 1001_ $$0P:(DE-Juel1)156459$$aDahmen, David$$b0$$ufzj
001050720 245__ $$aHow heterogeneity shapes dynamics and computation in the brain
001050720 260__ $$a[Cambridge, Mass.]$$bCell Press$$c2025
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001050720 520__ $$aMuch effort has been spent clustering neurons into transcriptomic or functional cell types and characterizingthe differences between them. Beyond subdividing neurons into categories, we must recognize that no twoneurons are identical and that graded physiological or transcriptomic properties exist within cells of agiven type. This often overlooked ‘‘within-type’’ heterogeneity is a specific neuronal implementation ofwhat statistical physics refers to as ‘‘disorder’’ and exhibits rich computational properties, the identificationof which may shed crucial insights into theories of brain function. In this perspective article, we address thisgap by highlighting theoretical frameworks for the study of neural tissue heterogeneity and discussing thebenefits and implications of within-type heterogeneity for neural network dynamics, computation, andself-organization.
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001050720 7001_ $$0P:(DE-HGF)0$$aHutt, Axel$$b1
001050720 7001_ $$0P:(DE-HGF)0$$aIndiveri, Giacomo$$b2
001050720 7001_ $$0P:(DE-HGF)0$$aKennedy, Ann$$b3
001050720 7001_ $$0P:(DE-HGF)0$$aLefebvre, Jeremie$$b4
001050720 7001_ $$0P:(DE-HGF)0$$aMazzucato, Luca$$b5
001050720 7001_ $$0P:(DE-HGF)0$$aMotter, Adilson E.$$b6
001050720 7001_ $$0P:(DE-HGF)0$$aNarayanan, Rishikesh$$b7
001050720 7001_ $$0P:(DE-HGF)0$$aPayvand, Melika$$b8
001050720 7001_ $$0P:(DE-HGF)0$$aPlanert, Henrike$$b9
001050720 7001_ $$0P:(DE-HGF)0$$aGast, Richard$$b10$$eCorresponding author
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001050720 8564_ $$uhttps://www.cell.com/neuron/fulltext/S0896-6273(25)00896-7
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