Abstract
In order to understand the relationship between neuronal organization and behavior, precise methods that identify and quantify functional cellular ensembles are required. This is especially true in the quest to understand the mechanisms of memory. Brain structures involved in memory formation and storage, as well as the molecular determinates of memory are well-known, however, the microanatomy of functional neuronal networks remain largely unidentified. We developed a novel approach to statistically map molecular markers in neuronal networks through quantitative topographic measurement. Brain nuclei and their subdivisions are well-defined – our approach allows for the identification of new functional micro-regions within established subdivisions. A set of analytic methods relevant for measurement of discrete neuronal data across a diverse range of brain subdivisions are presented. We provide a methodology for the measurement and quantitative comparison of functional micro-neural network activity based on immunohistochemical markers matched across individual brains using micro-binning and heat mapping within brain sub-nuclei. These techniques were applied to the measurement of different memory traces, allowing for greater understanding of the functional encoding within sub-nuclei and its behavior mediated change. These approaches can be used to understand other functional and behavioral questions, including sub-circuit organization, normal memory function and the complexities of pathology. Precise micro-mapping of functional neuronal topography provides essential data to decode network activity underlying behavior.
Highlights
Following Cajal’s identification of the neuron as the fundamental functional unit of the nervous system (López-Muñoz et al, 2006), the field of neuroscience has endeavored to understand how neurons operates in local groups and distributed networks to bring about behavior. Cajal (1894) proposed a theory that memory storage requires the formation of new connections between neurons in the brain
In order to best handle the analysis of topographical data we have investigated and utilized a variety of statistical approaches for large multiple comparison data sets – these include analysis of variance (ANOVA) and its variants; principal component analysis (PCA); and false discovery rate (FDR) correction
Our approach for the measurement and contrasting of neuronal topographic data in behavioral experiments has been successfully applied to the study of the microanatomy of memory formation
Summary
Following Cajal’s identification of the neuron as the fundamental functional unit of the nervous system (López-Muñoz et al, 2006), the field of neuroscience has endeavored to understand how neurons operates in local groups (ensembles) and distributed networks to bring about behavior. Cajal (1894) proposed a theory that memory storage requires the formation of new connections between neurons in the brain. Cajal (1894) proposed a theory that memory storage requires the formation of new connections between neurons in the brain How neurons and their 1000s of synaptic connections act together to encode a memory was first conceptualized by Hebb (1949) as neuronal ensembles that both spatially and temporally act together to encode a component of the memory. A key challenge in the neuroscience of memory is in identifying which neurons have been allocated to the memory trace and which have not, while some progress has been made (Bergstrom et al, 2008, 2011, 2013a,b; Bergstrom and Johnson, 2014; Mayford, 2014; Rogerson et al, 2014; Frankland and Josselyn, 2015; Bergstrom, 2016; Josselyn and Frankland, 2018), new techniques and approaches for understanding microanatomy are needed. This aim can be aided by the development of methods and approaches to help reliably identify and quantify systematic topographies of neurons allocated to specific memory traces
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