Gradients in the mammalian cerebellar cortex enable Fourier-like transformation and improve storing capacity

eLife

Abdelmoneim Eshra¹  Laurens Witter²  Niklas Byczkowicz²  Miriam Hoidis²  Isabelle Straub²  Sebastian Maas²  Igor Delvendahl²  Kevin Dorgans²  Elise Savier³  Ingo Bechmann³  Stefan Hallermann³  Philippe Isope⁴  Martin Krueger⁴ 

[1] Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), VU University, Amsterdam, Netherlands;Carl-Ludwig-Institute for Physiology, Medical Faculty, Leipzig University, Leipzig, Germany;Institut des Neurosciences Cellulaires et Intégratives, CNRS, Université de Strasbourg, Strasbourg, France;Institute of Anatomy, Medical Faculty, Leipzig University, Leipzig, Germany;

关键词: electrophysiology;    cerebellum;    granule cell;    mossy fiber;   

DOI  :  10.7554/eLife.51771

来源: DOAJ

【 摘 要 】

Cerebellar granule cells (GCs) make up the majority of all neurons in the vertebrate brain, but heterogeneities among GCs and potential functional consequences are poorly understood. Here, we identified unexpected gradients in the biophysical properties of GCs in mice. GCs closer to the white matter (inner-zone GCs) had higher firing thresholds and could sustain firing with larger current inputs than GCs closer to the Purkinje cell layer (outer-zone GCs). Dynamic Clamp experiments showed that inner- and outer-zone GCs preferentially respond to high- and low-frequency mossy fiber inputs, respectively, enabling dispersion of the mossy fiber input into its frequency components as performed by a Fourier transformation. Furthermore, inner-zone GCs have faster axonal conduction velocity and elicit faster synaptic potentials in Purkinje cells. Neuronal network modeling revealed that these gradients improve spike-timing precision of Purkinje cells and decrease the number of GCs required to learn spike-sequences. Thus, our study uncovers biophysical gradients in the cerebellar cortex enabling a Fourier-like transformation of mossy fiber inputs.

【 授权许可】

Unknown