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Grid Cell Mechanisms and Function: Contributions of Michael E. Hasselmo*
Grid Cell Mechanisms and Function: Contributions of Michael E. Hasselmo*

... The model of grid cell firing based on persistent firing neurons requires separate populations of neurons showing persistent firing at the same stable baseline frequency that remains constant in the absence of input. Figure 1A shows an example of 20 s of stable persistent firing in a Layer V pyramid ...
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full text pdf

Pyrokinin/PBAN-like peptides in the central nervous system of
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angol tézisfüzet0531

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FEATURE ARTICLE Cortical Auditory Adaptation
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David Hunter Hubel. 27 February 1926 — 22 September 2013
David Hunter Hubel. 27 February 1926 — 22 September 2013

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Sensory Afferent Neurotransmission in Caudal Nucleus Tractus

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... al., 1994) and (medial) superior olive (Guinan et al., 1972; Grothe et al., 1997, 2001). Offset responding neurons have also been observed in the (medial) superior olivary complex (Guinan et al., 1972; Grothe et al., 1997, 2001), where dense excitatory projections lead into the ICc (Oliver et al., 1 ...
Optogenetic drive of neocortical pyramidal neurons generates fMRI
Optogenetic drive of neocortical pyramidal neurons generates fMRI

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MMNeuropharm2011

... 100 to 500 trillion synapses. The word “synapse” comes from the Greek “syn-” (“together”) and “haptein” (“to clasp”), coined by Sherrington in the late 19th century. In the CNS most synapses are chemical: the presynaptic neuron releases a neurotransmitter into the synaptic cleft that interacts with ...
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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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