Journal
FRONTIERS IN NEURAL CIRCUITS
Volume 7, Issue -, Pages -Publisher
FRONTIERS MEDIA SA
DOI: 10.3389/fncir.2013.00013
Keywords
neuronal diversity; interneuron diversity; barrel cortex; petilla terminology; atypical cells; fuzzy sets; unsupervised clustering
Categories
Funding
- German Federal Ministry of Education and Research (BMBF) via the Bernstein Center for Computational Neuroscience-Gottingen [01GQ1005B]
- Human Frontier Science Program [RGY0070/2007]
- Agence Nationale pour la Recherche [ANR 2011 MALZ 003 01]
- Fondation pour la Recherche Medicale fellowship [FDT20100920106]
Ask authors/readers for more resources
Cortical neurons and, particularly, inhibitory interneurons display a large diversity of morphological, synaptic, electrophysiological and molecular properties, as well as diverse embryonic origins. Various authors have proposed alternative classification schemes that rely on the concomitant observation of several multimodal features. However, a broad variability is generally observed even among cells that are grouped into a same class. Furthermore, the attribution of specific neurons to a single defined class is often difficult, because individual properties vary in a highly graded fashion, suggestive of continua of features between types. Going beyond the description of representative traits of distinct classes, we focus here on the analysis of atypical cells. We introduce a novel paradigm for neuronal type classification, assuming explicitly the existence of a structured continuum of diversity. Our approach, grounded on the theory of fuzzy sets, identifies a small optimal number of model archetypes. At the same time, it quantifies the degree of similarity between these archetypes and each considered neuron. This allows highlighting archetypal cells, which bear a clear similarity to a single model archetype, and edge cells, which manifest a convergence of traits from multiple archetypes.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available