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The Origin of Electromyograms - Explanations Based on the
The Origin of Electromyograms - Explanations Based on the

High-Level Perception, Representation, and
High-Level Perception, Representation, and

... A given set of input data may be perceived in a number of different ways, depending on the context and the state of the perceiver. Due to this flexibility, it is a mistake to regard perception as a process that associates a fixed representation with a particular situation. Both contextual factors a ...
A Model of a Segmental Oscillator in the Leech Heartbeat Neuronal
A Model of a Segmental Oscillator in the Leech Heartbeat Neuronal

Learning Distance Functions For Gene Expression Data
Learning Distance Functions For Gene Expression Data

BRAIN DYNAMICS AT MULTIPLE SCALES: CAN ONE RECONCILE
BRAIN DYNAMICS AT MULTIPLE SCALES: CAN ONE RECONCILE

... Nonlinear time series analyses have suggested that the human electroencephalogram (EEG) may share statistical and dynamical properties with chaotic systems. During slow-wave sleep or pathological states like epilepsy, correlation dimension measurements display low values, while in awake and attentiv ...
Reinforcement learning, conditioning, and the brain
Reinforcement learning, conditioning, and the brain

Fuzzy Genetic Algorithms
Fuzzy Genetic Algorithms

... completely true and completely false. Compared to traditional binary sets (where variables only take on true or false values), fuzzy logic variables have a truth value that ranges in degree between 0 and 1. Fuzzy systems suggest a mathematic model to translate the real processes of human knowledge ( ...
Tolerance to Sound Intensity of Binaural
Tolerance to Sound Intensity of Binaural

... All data were obtained with a “loose patch” technique, which permitted well isolated and stable extracellular recordings (Fig. 1). This is an important technical advance in the study of NL, because isolation of single neurons is very difficult to obtain, presumably because of the sparsely distribute ...
A dendritic disinhibitory circuit mechanism for pathway
A dendritic disinhibitory circuit mechanism for pathway

... istinct classes of inhibitory interneurons form cell-typespecific connections among themselves and with pyramidal neurons in the cortex1,2. Interneurons expressing parvalbumin (PV) specifically target the perisomatic area of pyramidal neurons. Interneurons expressing somatostatin (SOM) specifically tar ...
Practical Applications of Biological Realism in Artificial Neural
Practical Applications of Biological Realism in Artificial Neural

A Relational Approach to Tool
A Relational Approach to Tool

... objects that can potentially be used as a tool for accomplishing the task. Some of these objects are clearly inappropriate since they cannot be inserted into the tube, lack a suitable “hook” affordance or are not long enough. However, the ...
Full-Text PDF
Full-Text PDF

... many different in vitro applications, using 64 electrode channels. In a parallel respect, Franke and colleagues [6] used a high-density (HD) electrode array to perform real-time spike sorting for closed-loop experiments that study neural plasticity. These studies exploited the existing electrode arr ...
Integration of Sensory and Reward Information
Integration of Sensory and Reward Information

... to create a payoff-weighted likelihood function [2,21,26]. Furthermore, the effects of payoff information on discrimination accuracy and reaction times are well described by drift diffusion models that postulate a two-stage accumulation process—an initial stage of accumulation about the payoffs foll ...
chapter one
chapter one

ASL: Hierarchy, Composition, Heterogeneity, and Multi
ASL: Hierarchy, Composition, Heterogeneity, and Multi

Encoding and decoding in fMRI
Encoding and decoding in fMRI

... stimulus, experimental or task variables are nonlinearly mapped into measured activity. We then present a critical comparison of encoding and decoding models that answers several fundamental questions about their relative utility for fMRI. Is there any difference between the sensory or cognitive rep ...
working draft - DAVID KAPLAN | Macquarie University
working draft - DAVID KAPLAN | Macquarie University

Design of a Second-Order Delta-Sigma Modulator for
Design of a Second-Order Delta-Sigma Modulator for

... connected to a paralyzed individual’s intention to perform an act and then is able to restore communication and/or movement to that immobilized person [Sch:06]. This restoration of communication or movement is accomplished by stimulating actuators that in turn carry out the intended act. The BCI dev ...
i S dS i S dS Fuzzy Logic, Sets and Systems Lecture 1 Introduction
i S dS i S dS Fuzzy Logic, Sets and Systems Lecture 1 Introduction

Relationship between muscle output and functional MRI
Relationship between muscle output and functional MRI

Imitating others by composition of primitive actions: a neuro
Imitating others by composition of primitive actions: a neuro

Following non-stationary distributions by controlling the
Following non-stationary distributions by controlling the

... actual T value. As any value of T leads to a stable quantization, one can also tune T empirically, from successive tries, starting from high values i.e. sparse quantization. To sum up, we have shown that, if an epoch consists of the interval between meaningful events, accordingly to the problem, and ...
reciprocal inhibition in the motor nervous system of the nematode
reciprocal inhibition in the motor nervous system of the nematode

... neurons. The DE21 neuron synapses onto the next three posterior VI neurons. A weak response of the VI:,, neuron was revealed by signal averaging techniques in two of five experiments. No interaction with the VI& was observed. The diagram on the left shows the array of commissures in the first three ...
Neural Machines for Music Recognition
Neural Machines for Music Recognition

Contents | Zoom in | Zoom out Search Issue | Next Page For
Contents | Zoom in | Zoom out Search Issue | Next Page For

... the human operating it is the latter’s sense of feeling, pervasiveness and ability to understand rather than to process. Often we may be amused by the smartphone’s speech recognition ability (For example, we said: “Define perception” and the phone comes up with “Are you asking about “The Fine Person ...
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Neural modeling fields

Neural modeling field (NMF) is a mathematical framework for machine learning which combines ideas from neural networks, fuzzy logic, and model based recognition. It has also been referred to as modeling fields, modeling fields theory (MFT), Maximum likelihood artificial neural networks (MLANS).This framework has been developed by Leonid Perlovsky at the AFRL. NMF is interpreted as a mathematical description of mind’s mechanisms, including concepts, emotions, instincts, imagination, thinking, and understanding. NMF is a multi-level, hetero-hierarchical system. At each level in NMF there are concept-models encapsulating the knowledge; they generate so-called top-down signals, interacting with input, bottom-up signals. These interactions are governed by dynamic equations, which drive concept-model learning, adaptation, and formation of new concept-models for better correspondence to the input, bottom-up signals.
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