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GENERAL CONCLUSIONS
GENERAL CONCLUSIONS

A Self-Organizing Neural Network for Contour Integration through Synchronized Firing
A Self-Organizing Neural Network for Contour Integration through Synchronized Firing

Developmental Biology, 9e
Developmental Biology, 9e

... a. Led to jaws, face, skull, sensory neural ganglia b. Transient structure: exists briefly at neural tube closure 2. You should understand that the neural crest is specified into four overlapping regions along the anterior-posterior axis: a. Cranial neural crest b. Cardiac neural crest c. Trunk neur ...
Dear Notetaker:
Dear Notetaker:

... o In the retina and LGN there are neurons that are classified as M-like, P-like, or K-like with different anatomical features and functions o In V1 the info from P, K, and M cells is recombined, it does not stay segregated o The recombined info is sent to extra striate areas for even more processing ...
Oscillatory Neural Fields for Globally Optimal Path Planning
Oscillatory Neural Fields for Globally Optimal Path Planning

... The work reported here is related to resistive grid approaches for solving optimization problems (Chua, 1984). Resistive grid approaches may be viewed as "passive" relaxation methods, while the oscillatory neural field is an "active" approach. The primary virtue of the "active" approach lies in the ...
Understanding the brain by controlling neural activity
Understanding the brain by controlling neural activity

Are Action-based Lies easier to detect than Speech
Are Action-based Lies easier to detect than Speech

... blank for five seconds (resting period for acquiring neural data). ...
Neural Mechanisms of Bias and Sensitivity in Hiroshi Nishida Muneyoshi Takahashi
Neural Mechanisms of Bias and Sensitivity in Hiroshi Nishida Muneyoshi Takahashi

... reaction time during decision making. An important merit of reaction-time analysis is that it increases the statistical power, especially when considering neural activity on a trial-by-trial basis. The Linear Approach to Threshold with Ergodic Rate model (LATER model) is one model for the analysis o ...
Communication within the Nervous System
Communication within the Nervous System

... The Neural Membrane • Moves 3 Na+ outside for every 2 K+ inside ...
neural plasticity
neural plasticity

Representation of Number in Animals and Humans: A Neural Model
Representation of Number in Animals and Humans: A Neural Model

Document
Document

... Figure 3A.8 The dual functions of the autonomic nervous system The autonomic nervous system controls the more autonomous (or self-regulating) internal functions. Its sympathetic division arouses and expends energy. Its parasympathetic division calms and conserves energy, allowing routine maintenanc ...
The brain-machine disanalogy revisited
The brain-machine disanalogy revisited

... squares, each with two (local) states. For a tape of length n, there are 2n global states (or configurations), and no matter what the root cause, we can express the succession from any one state to the next by a transition function, or mapping, which assigns a unique successor to each of the 2n stat ...
Flexible sequence learning in a SOM model of the mirror system
Flexible sequence learning in a SOM model of the mirror system

... neurons may or may not be useful/essential for (see for instance Hickok, 2008; Rizzolatti & Sinigaglia, 2010, for such a debate), it appears that parietal mirror neurons in macaque monkeys organise into pools of neurons responding to specific motion primitives (e.g. a reach or a grasp but not both; ...
On real-world temporal pattern recognition using Liquid State
On real-world temporal pattern recognition using Liquid State

Training
Training

... defined. A vector quantizer with minimum encoding distortion is called a Voronoi or nearestneighbor quantizer. The collection of possible reproduction vectors is called the code book of the quantizer, and its members are called code vectors. ...
The Brain Implements Optimal Decision Making between Alternative Actions
The Brain Implements Optimal Decision Making between Alternative Actions

... which is known to innervate BG (Parthasarathy, Schall, & Graybiel, 1992). Eq. 4 implies that the salience signals yi(T) (or nonlinear combinations therein) have to be distributed to the output so as to yield both excitatory and inhibitory contributions. Eq. 4 includes two terms and below we propose ...
What is population genomics?
What is population genomics?

a musical instrument using in vitro neural networks
a musical instrument using in vitro neural networks

... There has been a growing interest in research into the development of hybrid wetware-silicon devices for nonlinear computations using cultured brain cells. The ambition is to harness the intricate dynamics of in vitro neuronal networks to perform computational tasks [4]. This paper presents a musica ...
The Brain Doesn`t Work That Way: From Microgenesis to Cognition
The Brain Doesn`t Work That Way: From Microgenesis to Cognition

Elite Co-Occurrence in the Media
Elite Co-Occurrence in the Media

... connected components. Everybody within a connected components is able to reach everybody else within that same component, while it is impossible to reach somebody in another connected component. Almost always most real networks consist of one very large connected component and possibly many other sm ...
Emergence - Brain Mind Forum
Emergence - Brain Mind Forum

... impossible to find, let alone correct any errors and make amendments. All programs are broken down into a hierarchy of sub units. Each function can then be programmed independently and a library of functions established. Each can be rigorously tested, then groups of sub units can be linked together ...
No Slide Title - Ohio University
No Slide Title - Ohio University

... Wernicke’s area ...
cangelosi parisi cogsci2001
cangelosi parisi cogsci2001

... abilities upon which it will be grounded have fully evolved. In this condition language has a beneficial influence on nonlinguistic behavior. If the evolutionary scenario involves both the practical task of pushing or pulling objects and the processing of linguistic signals from the beginning, it is ...
Imitating the Brain with Neurocomputer A New Way towards Artificial
Imitating the Brain with Neurocomputer A New Way towards Artificial

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Recurrent neural network

A recurrent neural network (RNN) is a class of artificial neural network where connections between units form a directed cycle. This creates an internal state of the network which allows it to exhibit dynamic temporal behavior. Unlike feedforward neural networks, RNNs can use their internal memory to process arbitrary sequences of inputs. This makes them applicable to tasks such as unsegmented connected handwriting recognition or speech recognition
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