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Distinct roles of visual, parietal, and frontal motor cortices in memory-guided sensorimotor decisions.

eLife | Aug 4, 2016

Mapping specific sensory features to future motor actions is a crucial capability of mammalian nervous systems. We investigated the role of visual (V1), posterior parietal (PPC), and frontal motor (fMC) cortices for sensorimotor mapping in mice during performance of a memory-guided visual discrimination task. Large-scale calcium imaging revealed that V1, PPC, and fMC neurons exhibited heterogeneous responses spanning all task epochs (stimulus, delay, response). Population analyses demonstrated unique encoding of stimulus identity and behavioral choice information across regions, with V1 encoding stimulus, fMC encoding choice even early in the trial, and PPC multiplexing the two variables. Optogenetic inhibition during behavior revealed that all regions were necessary during the stimulus epoch, but only fMC was required during the delay and response epochs. Stimulus identity can thus be rapidly transformed into behavioral choice, requiring V1, PPC, and fMC during the transformation period, but only fMC for maintaining the choice in memory prior to execution.

Pubmed ID: 27490481 RIS Download

Mesh terms: Animals | Brain Mapping | Choice Behavior | Functional Neuroimaging | Memory | Mice | Optogenetics | Parietal Lobe | Sensorimotor Cortex | Visual Cortex | Visual Perception

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Allen Institute for Brain Science

Independent 501(c)(3) nonprofit medical research organization dedicated to accelerating the understanding of how the human brain works. Utilizing the mouse model system, a multidisciplinary group of neuroscientists, molecular biologists, informaticists, engineers, mathematicians, statisticians, and computational biologists have joined together to investigate expression of 20,000 genes in the adult mouse brain and to map gene expression to a cellular level beyond neuroanatomic boundaries. The data generated from this joint effort is contained in the publicly available Allen Brain Atlas application. Molecular approaches to understanding the functional organization of the brain promise new insights into the relationships between genes, brain, behavior and disease. To facilitate such insights, the Allen Institute produces large-scale projects and makes the resulting data and tools freely available online to scientists worldwide. These open resources, all available at www.brain-map.org, are intended to foster scientific discovery and collaboration. Atlases: Allen Developing Mouse Brain Atlas: A map of gene expression in the developing mouse brain. Building on the Allen Mouse Brain Atlas, this atlas reveals gene expression patterns from embryonic through postnatal stages to provide information about both spatial and temporal regulation of gene expression. Allen Spinal Cord Atlas: A genome-wide map of gene expression throughout the adult and juvenile mouse spinal cord. The Atlas was made possible through the generous support of a diverse consortium of funders, representing disease organizations, foundations, and corporate and private donors. Allen Mouse Brain Atlas (formerly Allen Brain Atlas): A genome-wide, three-dimensional map of gene expression in the adult mouse brain. Similar in scale to the Human Genome Project, the Atlas reveals the expression patterns of approximately 20,000 genes throughout the entire adult mouse brain down to the cellular level. The Allen Institutes inaugural project, the Atlas was completed in 2006. Studies: Mouse Diversity Study: Characterization of gene expression in the brain across genetic backgrounds and sex. Expanding on the Allen Mouse Brain Atlas, this resource includes data for 49 pharmaceutical drug target genes and a selected set of additional genes across seven mouse strains and in female mice. Transgenic Mouse Study: Comprehensive characterization of the expression patterns of genetically-controlled markers or tool genes in the brains of transgenic mice. Providing standardized, detailed, anatomical profiling of transgene expression throughout the brain, this dataset is intended to reveal the potential of each transgenic mouse line and help researchers choose the appropriate tools for their studies. Human Cortex Study: A collection of gene expression data in the adult human neocortex. Providing data for several categories of genes across different cortical regions and human individuals, including control and schizophrenic cases, the dataset has the potential to enable exploration of variability in cortical gene expression across different ages, between genders across different regions of the cortex and in schizophrenia. Sleep Study: A comprehensive collection of gene expression data in the mouse brain for five different conditions of sleep and wakefulness. Generated in collaboration with SRI International, this unique dataset is intended to help sleep researchers advance understanding of sleep deprivation and the dynamic changes underlying sleep/wake cycles. The sleep study was funded by an award from the U.S. Department of Defense.

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MATLAB

A multi-paradigm numerical computing environment and fourth-generation programming language. It allows matrix manipulations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages, including C, C++, Java, Fortran and Python. (Adapted from Wikipedia) The high-level language and interactive environment lets you explore and visualize ideas and collaborate across disciplines including signal and image processing, communications, control systems, and computational finance.

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NEURON

NEURON is a simulation environment for modeling individual neurons and networks of neurons. It provides tools for conveniently building, managing, and using models in a way that is numerically sound and computationally efficient. It is particularly well-suited to problems that are closely linked to experimental data, especially those that involve cells with complex anatomical and biophysical properties. NEURON has benefited from judicious revision and selective enhancement, guided by feedback from the growing number of neuroscientists who have used it to incorporate empirically-based modeling into their research strategies. NEURON's computational engine employs special algorithms that achieve high efficiency by exploiting the structure of the equations that describe neuronal properties. It has functions that are tailored for conveniently controlling simulations, and presenting the results of real neurophysiological problems graphically in ways that are quickly and intuitively grasped. Instead of forcing users to reformulate their conceptual models to fit the requirements of a general purpose simulator, NEURON is designed to let them deal directly with familiar neuroscience concepts. Consequently, users can think in terms of the biophysical properties of membrane and cytoplasm, the branched architecture of neurons, and the effects of synaptic communication between cells. * helps users focus on important biological issues rather than purely computational concerns * has a convenient user interface * has a user-extendable library of biophysical mechanisms * has many enhancements for efficient network modeling * offers customizable initialization and simulation flow control * is widely used in neuroscience research by experimentalists and theoreticians * is well-documented and actively supported * is free, open source, and runs on (almost) everything

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