Biomedical subjects

Esther A Nimchinsky

Publications and source records attributed to Esther A Nimchinsky.

3 recordsLinked to original sources

PubMed2002

Facilitation at single synapses probed with optical quantal analysis.

Many synapses can change their strength rapidly in a use-dependent manner, but the mechanisms of such short-term plasticity remain unknown. To understand these mechanisms, measurements of neurotransmitter release at single synapses are required. We probed transmitter release by imaging transient increases in [Ca(2+)] mediated by synaptic N-methyl-D-aspartate receptors (NMDARs) in individual dendritic spines of CA1 pyramidal neurons in rat brain slices, enabling quantal analysis at single synapses. We found that changes in release probability, produced by paired-pulse facilitation (PPF) or by manipulation of presynaptic adenosine receptors, were associated with changes in glutamate concentration in the synaptic cleft, indicating that single synapses can release a variable amount of glutamate per action potential. The relationship between release probability and response size is consistent with a binomial model of vesicle release with several (>5) independent release sites per active zone, suggesting that multivesicular release contributes to facilitation at these synapses.

2-Chloroadenosine↗

PubMed2002

Structure and function of dendritic spines.

Spines are neuronal protrusions, each of which receives input typically from one excitatory synapse. They contain neurotransmitter receptors, organelles, and signaling systems essential for synaptic function and plasticity. Numerous brain disorders are associated with abnormal dendritic spines. Spine formation, plasticity, and maintenance depend on synaptic activity and can be modulated by sensory experience. Studies of compartmentalization have shown that spines serve primarily as biochemical, rather than electrical, compartments. In particular, recent work has highlighted that spines are highly specialized compartments for rapid large-amplitude Ca(2+) signals underlying the induction of synaptic plasticity.

Animals↗

PubMed2002

An image analysis algorithm for dendritic spines.

The structure of neuronal dendrites and their spines underlie the connectivity of neural networks. Dendrites, spines, and their dynamics are shaped by genetic programs as well as sensory experience. Dendritic structures and dynamics may therefore be important predictors of the function of neural networks. Based on new imaging approaches and increases in the speed of computation, it has become possible to acquire large sets of high-resolution optical micrographs of neuron structure at length scales small enough to resolve spines. This advance in data acquisition has not been accompanied by comparable advances in data analysis techniques; the analysis of dendritic and spine morphology is still accomplished largely manually. In addition to being extremely time intensive, manual analysis also introduces systematic and hard-to-characterize biases. We present a geometric approach for automatically detecting and quantifying the three-dimensional structure of dendritic spines from stacks of image data acquired using laser scanning microscopy. We present results on the measurement of dendritic spine length, volume, density, and shape classification for both static and time-lapse images of dendrites of hippocampal pyramidal neurons. For spine length and density, the automated measurements in static images are compared with manual measurements. Comparisons are also made between automated and manual spine length measurements for a time-series data set. The algorithm performs well compared to a human analyzer, especially on time-series data. Automated analysis of dendritic spine morphology will enable objective analysis of large morphological data sets. The approaches presented here are generalizable to other aspects of neuronal morphology.

Algorithms↗