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Neural Networks.Chap..
Neural Networks.Chap..

... Sometimes, the activation function ranges from -1 to +1. (How to do?) Assume the activation function ranging from 0 to +1 is denoted as j(×), ranging from -1 to +1 is denoted as j’(×)  j’(×)=j(×)*2-1 Notes: if j(v)=sigmoid function ...
Chapter 2: Biopsychology
Chapter 2: Biopsychology

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KKDP4: The role of neurotransmitters in the transmission of neural

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... Short answer questions 27) (6 pts) John was having one of his cholinergic (releases acetylcholine) neurons (X) signal a postsynaptic neuron (Y). But now he wants neuron Y to stop receiving the signals. Besides having neuron X stop sending action potentials down to the terminal, what other things mus ...
Artificial Neural Networks - Introduction -
Artificial Neural Networks - Introduction -

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intro to psych brain and behavior

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Nervous and Endocrine System

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Introduction to Neural Networks

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The Nervous System

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chapter 48

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UNIT 3A: Biological Bases of Behavior – Neural Processing and the

... Drugs and other chemicals affect brain chemistry at synapses, often by either amplifying or blocking a neurotransmitter’s activity a. Agonists are molecules that are similar enough to a neurotransmitter to bind to its receptor and mimic its effects i. Some opiate drugs are agonists and produce a tem ...
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Puzzle 2A: The Neuron and Nervous System

... 21. Type of message that increases the likelihood that a neuron will activate 22. Brain contains receptor sites for this group of pain-killing drugs 23. The parasympathetic nervous system helps maintain and _____ physical resources 25. What glia means, in Greek 26. Drug that produces an exhilarating ...
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... and bind to receptor molecules in the membrane of the postsynaptic neuron thus changing their shape. – This opens up holes that allow specific ions in or out. • The effectiveness of the synapse can be changed – vary the number of vesicles of transmitter – vary the number of receptor molecules. • Syn ...
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13. What determines the magnitude of the graded potential? (p. 240)

... are located) and travel down to the axon terminal where they are housed in vesicles until signaled for release. When the appropriate signal (action potential) arrives, neurotransmitter is released via exocytosis. The neurotransmitter then travels by diffusion to the postsynaptic membrane where it op ...
Synapses
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... Two neurons releasing neurotransmitters that act on a third neuron. The first two neurons could be in the Central Nervous System, and the third might be a motor neuron leading out to a muscle or gland. Schwann Cells form a myelin sheath Around the axon of motor neurons Neurons ...
Unit 3A: Neural Processing and the Endocrine System Introduction
Unit 3A: Neural Processing and the Endocrine System Introduction

... 1. Axons are insulated by the myelin sheath. This insulation helps control the impulses and speeds their travel. 2. Messages travel along neurons at between 2 and 200 mph (depending on the type of neuron). This may seem fast, but is very slow compared to computers. 4. Neurons “fire” when stimulated ...
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The Neuron - Austin Community College

... Na+ to enters the cell down its electrochemical gradient to produce depolarizing currents that are translated into action potentials Threshold Voltage – membrane is depolarized by ~ 15 mV stimulus (from -70 to -55mV) The AP is a brief reversal of membrane potential with a total amplitude of 100 mV ( ...
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Action Potential

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General design of the nervous system
General design of the nervous system

... The incoming signal enters the neuron throught synapses mainly on the neuronal dendrites, but also on the cell body. The output signal travels by way of a single axon, leaving the neuron, but this axon has many separate branches to other parts of the nervous system or peripheral body. ...
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Biological neuron model

A biological neuron model (also known as spiking neuron model) is a mathematical description of the properties of nerve cells, or neurons, that is designed to accurately describe and predict biological processes. This is in contrast to the artificial neuron, which aims for computational effectiveness, although these goals sometimes overlap.
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