AUTHOR=Pchitskaya Ekaterina , Bezprozvanny Ilya 

TITLE=Dendritic Spines Shape Analysis—Classification or Clusterization? Perspective

JOURNAL=Frontiers in Synaptic Neuroscience

VOLUME=Volume 12 - 2020

YEAR=2020

URL=https://www.frontiersin.org/journals/synaptic-neuroscience/articles/10.3389/fnsyn.2020.00031

DOI=10.3389/fnsyn.2020.00031

ISSN=1663-3563

ABSTRACT=Dendritic spines are small protrusions from dendrite membrane, where the contact with neighboring axons is formed in order to receive synaptic input. Changes in size, shape and density of synaptic spines are associated with learning and memory, and also observed after exposure to the drugs of abuse, and in a variety of neurodegenerative, neurodevelopmental and psychiatric disorders.  Due to its preeminent importance, major effort is spend on developing techniques which enable visualization and analysis of dendritic spines in cultured neurons, in fixed slices and in intact brain tissue. Classification into predefined morphological groups is a standard approach that is used in neuroscience research, where spines are divided into fixed categories such as thin, mushroom and stubby subclasses.   In this perspective we reason that accumulated evidence supports the existence of the dendritic spine shapes continuum rather than clearly separated classes.   We further suggest that new approaches and software tools reflecting complex dendritic spines shape and their highly dynamic nature are required to perform valuable analysis of their morphology.  We discuss and compare recently developed algorithms that rely on clusterization rather than classification, and therefore enable a new level of spine shapes analysis.  We reason that improved methods of analysis may help to investigate a link between dendritic spine shape and its function, and facilitate studies of learning and memory as well as studies of brain disorders.