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Cognitive neuroscience
Cognitive neuroscience

... • Impossibility of explaining mind through brain - Non-linearity of neural processes • Psychological-neural equivalence – necessary at a level much lower that today (resolution of neuroimage mechanisms deal with brain areas too large) • Using lesions and image techniques, Uttal considers that we can ...
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Sonia Gasparini, PhD Degrees Assistant Professor of Cell Biology & Anatomy and

... the synaptic inputs and how they are integrated with voltage-dependent currents, the initiation of active processes in the dendrites (i.e. dendritic spikes) and their impact on the somatic output in hippocampal CA1 neurons and neurons of the deep layers of the entorhinal cortex. The ultimate goal is ...
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The Nervous System
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Central nervous system

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ES145 - Systems Analysis & Physiology

... region of the brain, would get picked up by only about 1% of the cells there, so you could see a single neuron. Brain is not a continuous web, but a network of discrete cells. Neurons are the elementary signaling parts of the nervous system. Embryology: Neurons have a common shape, a dendrite (input ...
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Laminar analysis of excitatory local circuits in vibrissal motor

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... many motor and cognitive functions. The striatum, the input stage of the basal ganglia, is a major recipient of massive glutamatergic inputs from the cerebral cortex and thalamus. Medium spiny neurons (MSNs) dominate in the striatum (up to 95% in rodents). They are inhibitory (GABAergic) and have me ...
The nervous system
The nervous system

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0pt20pt [1.44]Spike Train Correlations Induced [1ex] [1.44]by

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The nervous system
The nervous system

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The Nervous System - Hartland High School
The Nervous System - Hartland High School

... a. Sensory Input – gathered information from the body monitoring changes inside and outside of the body called stimuli. b. Integration – processing and interpreting sensory input and makes decisions about what needs to be done at each moment. c. Motor Output – effecting a response by activating musc ...
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Final review quiz

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Stockholm University
Stockholm University

... The simplest model for describing multi-neuron spike statistics is the pairwise Ising model [1,2]. To start, one divides the spike trains into small time bins, and to each neuron i and each time bin t assigns a binary variables si(t) = -1 if neuron i has not emitted any spikes in that time bin and 1 ...
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Nervous system network models

Network of human nervous system comprises nodes (for example, neurons) that are connected by links (for example, synapses). The connectivity may be viewed anatomically, functionally, or electrophysiologically. These are presented in several Wikipedia articles that include Connectionism (a.k.a. Parallel Distributed Processing (PDP)), Biological neural network, Artificial neural network (a.k.a. Neural network), Computational neuroscience, as well as in several books by Ascoli, G. A. (2002), Sterratt, D., Graham, B., Gillies, A., & Willshaw, D. (2011), Gerstner, W., & Kistler, W. (2002), and Rumelhart, J. L., McClelland, J. L., and PDP Research Group (1986) among others. The focus of this article is a comprehensive view of modeling a neural network (technically neuronal network based on neuron model). Once an approach based on the perspective and connectivity is chosen, the models are developed at microscopic (ion and neuron), mesoscopic (functional or population), or macroscopic (system) levels. Computational modeling refers to models that are developed using computing tools.
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