Quantitative Methods in Neuroscience: A Neuroanatomical ApproachStephen M. Evans, Ann Marie Janson, Jens Randel Nyengaard Oxford University Press, 2004 - 327 pages Stereology is a valuable tool for neuroscientists, allowing them to obtain 3-Dimensional information from 2-Dimensional measurements made on appropriately sampled sections (usually obtained from histological sections or MRI/CT/PET scans). This 3-D information is invaluable in correlatingstructural/functional relationships in the pursuit of far greater understanding of the function of the central nervous system. However, in carrying out such measurements, often based on limited data sets, there is a risk of experimenter bias. An important feature of modern design based stereology isto be aware of potential sources of bias and eliminate them during the data collection. With many of the major neuroscience journals now insisting that quantitative data be presented, there is a greater need than ever for neuroscientists to understand the theory and practice behind quantitativemethods, such as those offered by stereology. Quantitative Methods in Neuroscience is a cookbook of stereological methods written especially for neuroscientists. It provides clear and accessible advice about when and when not to use stereology. Throughout the book, the emphasis is on practical guidance, rather than discussions and formulae.Written by leading scientists in the field of stereology, with a Foreword by D.C. Sterio, the book will be a valuable introduction to these methods for neuroscientists, and all those involved in development of new drug programmes. |
Contents
A case study from neuroscience involving stereology and multivariate | 16 |
Section introduction | 67 |
The use of fluorescent probes in cellcounting procedures | 85 |
Counting in situ hybridized neurons | 115 |
estimation of total number of synapses in | 146 |
The number of microvessels estimated by an unbiased stereological method | 167 |
Section 2 | 185 |
The nucleator and the planar and optical rotators applied in rat dorsal root | 197 |
Estimation of number and volume of immunohistochemically stained | 216 |
Section introduction | 241 |
Virtual test systems for estimation of orientationdependent parameters | 264 |
Spatial distribution | 287 |
Unbiased morphometrical techniques for the quantitative assessment of cells | 301 |
Glossary | 314 |
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Common terms and phrases
animals antibody brain white matter calbindin Cavalieri cell number coefficient of error coefficient of variation counting rule Cruz-Orive distribution dorsal root ganglion example field of view fluorescent probes fluorophores focal plane GFAP glial cells grid hippocampus hybridization intersection isotropic length density length estimation linear structure mean volume measurements Microsc microscope mRNA myelinated nerve fibers neocortex neuron number Neurosci nodes nucleator nucleolus number of neurons number of synapses numerical density Nyengaard object observed obtained optical disector optical fractionator orientation Pakkenberg population profiles quantitative reference space region rotator S-PLUS sampling box sampling fraction sampling scheme section thickness shrinkage simple random sampling slices somatostatin spatial stained statistical stereological stereological estimation stereological methods subpopulation surface area synapses systematic sampling Table technique test lines three-dimensional tissue blocks total number total volume two-dimensional unbiased counting frame unbiased estimator uniformly random V(ref variance vertical sections virtual plane volume estimators white matter