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RatCog: A GUI maze simulation tool with plugin “rat brains”
RatCog: A GUI maze simulation tool with plugin “rat brains”

... 1998; Redish, 1999; Shapiro & Hetherington, 1993; Sharp, 1991; Trullier & Meyer, 1998; Zipser, 1985) have been aimed at issues relating to neuroscience, in order for these models to become widely available to practicing psychologists, a Graphical User Interface (GUI) needs to be provided. Just as wi ...
EmergentSemanticsBerkeleyMay2_2010
EmergentSemanticsBerkeleyMay2_2010

... ‘discover’ the unity of plants and animals as living things with many shared properties only around the age of 10. • She suggested that the coalescence of the concept of living thing depends on learning about diverse aspects of plants and animals including – Nature of life sustaining processes – Wha ...
Exercise Sheet 6 - Machine Learning
Exercise Sheet 6 - Machine Learning

Neurons & Transmission of Information
Neurons & Transmission of Information

a positive electrical signal
a positive electrical signal

... cell body: central part of cell; contains the nucleus ...
Brain Regions Involved in USCBP Reaching Models
Brain Regions Involved in USCBP Reaching Models

10 - 11 : Fundamentals of Neurocomputing
10 - 11 : Fundamentals of Neurocomputing

PDF version
PDF version

Appendix 4 Mathematical properties of the state-action
Appendix 4 Mathematical properties of the state-action

KS4_nervous_models_Pupil_Sheets
KS4_nervous_models_Pupil_Sheets

... An electrical impulse cannot travel across a gap so another mechanism needs to be used. When the impulse reaches the end of the neuron chemicals called neurotransmitters are released into the gap. These diffuse across and bind to receptors in the next neuron which sets off a new impulse. ...
Key Stage 4 – Nervous models Pupil worksheet
Key Stage 4 – Nervous models Pupil worksheet

... An electrical impulse cannot travel across a gap so another mechanism needs to be used. When the impulse reaches the end of the neuron chemicals called neurotransmitters are released into the gap. These diffuse across and bind to receptors in the next neuron which sets off a new impulse. ...
neurons
neurons

... The body’s information system is built from billions of interconnected cells called neurons. ...
Bounded Seed-AGI
Bounded Seed-AGI

DM-Lecture-10 - WordPress.com
DM-Lecture-10 - WordPress.com

Classical Conditioning
Classical Conditioning

... • Mignault, A. and Marley, A. A. J. (1997). A Real-Time Neuronal Model of Classical Conditioning. Adaptive Behavior. Vol. 6-1, 3-61. • Rescorla, R. A. (1988). Behavioral studies of Pavlovian conditioning. Annual Review of Neuroscience 11: 329 - 352. • Rescorla, R. A., and R. L. Solomon. (1967). Two- ...
Slayt 1 - Department of Information Technologies
Slayt 1 - Department of Information Technologies

... The dendrites are tree-like receptive networks of nerve fibers that carry electrical signals into the cell body The cell body effectively sums and thresholds these incoming signals. The axon is a single long fiber that carries the signal from the cell body out to other neurons. The point of contact ...
From AUDREY to Siri. - International Computer Science Institute
From AUDREY to Siri. - International Computer Science Institute

Invariant selectivity of auditory neurons due to predictive coding
Invariant selectivity of auditory neurons due to predictive coding

the physiological approach
the physiological approach

... K Na Na Na+Na+ + ...
Probabilistic Models for Unsupervised Learning
Probabilistic Models for Unsupervised Learning

... What is the order of my autoregressive process? How many sources in my ICA model? How many states in my HMM? Is this input relevant to predicting that output? Is this relationship linear or nonlinear? ...
The use of Models - NAU jan.ucc.nau.edu web server
The use of Models - NAU jan.ucc.nau.edu web server

... The strict-information processing approach to cognition was replaced with a broader, more inclusive approach now known as cognitive science. This approach described cognition as the coordinated, often parallel operation of mental processes within a multicomponent memory system. The approach is delib ...
modeller - Studentportalen
modeller - Studentportalen

Poster Sensopac
Poster Sensopac

... encoding approach. Each granule cell receives an explicit context signal and three randomly-chosen mossy fibers from current and desired positions and velocities The cerebellum module consists of a network which contains a considerable amount of spiking neurons. To simulate this network efficiently ...
Where does breathing start?
Where does breathing start?

... It comes from the respiratory centres called medulla oblongata and the pons which are located in the lower brainstem. The medulla oblongata contains the Ventral Respiratory Group (VRG) and the Dorsal Respiratory Group and the pons contains the Pneumotaxic (PNG) and the Apneustic centres (APN). The f ...
Slide 1
Slide 1

... coordinates into spike trains ...
< 1 ... 110 111 112 113 114 115 116 117 118 ... 124 >

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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