Learning to Remember Rare Events
... Figure 3: Extended Neural GPU with memory module. Memory query is read from the position one below the current output logit, and the embedded memory value is put at the same position of the output tape p. The network learns to use these values to produce the output in the next step. Sequence-to-sequ ...
... Figure 3: Extended Neural GPU with memory module. Memory query is read from the position one below the current output logit, and the embedded memory value is put at the same position of the output tape p. The network learns to use these values to produce the output in the next step. Sequence-to-sequ ...
A neural implementation of Bayesian inference based on predictive
... a (n by m) matrix of feedforward synaptic weight values; V is a (m by n) matrix of feedback synaptic weight values; 1 and 2 are parameters; and and ⊗ indicate element-wise division and multiplication respectively. For all the experiments described in this paper 1 and 2 were given the values 1 ...
... a (n by m) matrix of feedforward synaptic weight values; V is a (m by n) matrix of feedback synaptic weight values; 1 and 2 are parameters; and and ⊗ indicate element-wise division and multiplication respectively. For all the experiments described in this paper 1 and 2 were given the values 1 ...
Preparation of Papers in Two-Column Format for
... Emotions entail different components, such as subjective experience, cognitive processes, expressive behavior, psychophysiological changes, and behavior. These various components of emotion are categorized in a different way depending on the academic discipline. In psychology and philosophy, emotion ...
... Emotions entail different components, such as subjective experience, cognitive processes, expressive behavior, psychophysiological changes, and behavior. These various components of emotion are categorized in a different way depending on the academic discipline. In psychology and philosophy, emotion ...
Paper: Temporal Convergence of Dynamic Cell Assemblies in the
... The Hebrew University-Hadassah Medical Schoo ...
... The Hebrew University-Hadassah Medical Schoo ...
neural basis of deciding, choosing and acting
... areas of the cerebral cortex, not to mention the subcortical structures. This box provides a simplified perspective of the brain regions described in the text. Vision starts in the retina and is fulfilled in the cerebral cortex. Visual processing in the cortex starts in the primary visual area (area ...
... areas of the cerebral cortex, not to mention the subcortical structures. This box provides a simplified perspective of the brain regions described in the text. Vision starts in the retina and is fulfilled in the cerebral cortex. Visual processing in the cortex starts in the primary visual area (area ...
Epilepsy in Small
... Thus, an excitable pool of CA1 neurons is always available, leading to sustainable seizure-like activity. To test these hypotheses, we simulated networks intended to mimic regions CA3 and CA1. We used “small-world” network topologies, in which the majority of connections between cells are “local,” b ...
... Thus, an excitable pool of CA1 neurons is always available, leading to sustainable seizure-like activity. To test these hypotheses, we simulated networks intended to mimic regions CA3 and CA1. We used “small-world” network topologies, in which the majority of connections between cells are “local,” b ...
A Model for Delay Activity Without Recurrent Excitation
... that a moderately higher potentiation of a relatively small fraction of its input synapses can lead to a firing rate which is significantly higher than baseline activity. Hence, it is possible that spontaneous firing rates significantly above baseline could emerge in such a population, if there is no co ...
... that a moderately higher potentiation of a relatively small fraction of its input synapses can lead to a firing rate which is significantly higher than baseline activity. Hence, it is possible that spontaneous firing rates significantly above baseline could emerge in such a population, if there is no co ...
Engines of the brain
... In addition to input from striosomes just described, SNc receives input from the environment conveying “good” or “bad” state measurement information; i.e., if the action just performed resulted in a good outcome, SNc’s activity is increased (“reward”) whereas if the action resulted in an undesired s ...
... In addition to input from striosomes just described, SNc receives input from the environment conveying “good” or “bad” state measurement information; i.e., if the action just performed resulted in a good outcome, SNc’s activity is increased (“reward”) whereas if the action resulted in an undesired s ...
Towards comprehensive foundations of computational intelligence.
... learning and associative memories. High-level cognition requires different approach than perception-action sequences at the lower cognitive level, where artificial neural networks, pattern recognition and control techniques are used. Knowledge used in reasoning and understanding language is based on ...
... learning and associative memories. High-level cognition requires different approach than perception-action sequences at the lower cognitive level, where artificial neural networks, pattern recognition and control techniques are used. Knowledge used in reasoning and understanding language is based on ...
Dependence of the input-firing rate curve of neural cells on
... The brain consists of about of neurons. Each of these neurons is connected to about 7000 of other neurons, creating a complex and sophisticated network. Simulating such an enormous network, is computationally almost impossible, certainly when taking into account all the different parameters of each ...
... The brain consists of about of neurons. Each of these neurons is connected to about 7000 of other neurons, creating a complex and sophisticated network. Simulating such an enormous network, is computationally almost impossible, certainly when taking into account all the different parameters of each ...
Sensory system evolution at the origin of craniates
... symmetrical animals, the reverse combination of elaborated migratory neural crest^ placodal sensory systems with an enlarged, elaborated brain but without large, paired, lateral eyes has never arisen. The implication of this pattern is that the genesis of the paired-eye visual system plus brain comb ...
... symmetrical animals, the reverse combination of elaborated migratory neural crest^ placodal sensory systems with an enlarged, elaborated brain but without large, paired, lateral eyes has never arisen. The implication of this pattern is that the genesis of the paired-eye visual system plus brain comb ...
Specific and Nonspecific Plasticity of the Primary
... • The BF shift was generally based on a decrease in response (inhibition) at the BF of the cortical neuron in the control condition and an increase in response (facilitation) at the BF of the stimulated thalamic neuron. Such a BF shift is also elicited by auditory fear conditioning, and has been kn ...
... • The BF shift was generally based on a decrease in response (inhibition) at the BF of the cortical neuron in the control condition and an increase in response (facilitation) at the BF of the stimulated thalamic neuron. Such a BF shift is also elicited by auditory fear conditioning, and has been kn ...
ANN Models Optimized using Swarm Intelligence Algorithms
... layers, hidden neurons, activation function and weight values. Since weight values are the key to a well trained ANN, finding the optimal weight values of ANN has been considered in many research studies. ANN can be trained using many techniques. Gradient Descent (GD) algorithm is a widely used ANN ...
... layers, hidden neurons, activation function and weight values. Since weight values are the key to a well trained ANN, finding the optimal weight values of ANN has been considered in many research studies. ANN can be trained using many techniques. Gradient Descent (GD) algorithm is a widely used ANN ...
מצגת של PowerPoint
... Consistent with these findings, responses to both eyes were up-regulated after BD. ...
... Consistent with these findings, responses to both eyes were up-regulated after BD. ...
Does computational neuroscience need new synaptic
... prediction. Machine learning has developed powerful models and methods, such as support vector machines [9], Gaussian Processes [10], or stochastic gradient descent in deep neural networks [11] that allow to minimize the classification or regression error. In contrast with the above, in unsupervised ...
... prediction. Machine learning has developed powerful models and methods, such as support vector machines [9], Gaussian Processes [10], or stochastic gradient descent in deep neural networks [11] that allow to minimize the classification or regression error. In contrast with the above, in unsupervised ...
Perception - U
... only the “on area” or the “off area” of its receptive field; if one light is shone in the “on area” and one is simultaneously shone in the “off area”, their effects cancel one another out by lateral inhibition; these neurons respond little to diffuse light ...
... only the “on area” or the “off area” of its receptive field; if one light is shone in the “on area” and one is simultaneously shone in the “off area”, their effects cancel one another out by lateral inhibition; these neurons respond little to diffuse light ...
Three-Dimensional Reconstruction and Stereoscopic Display of
... Data points separated by more than two RIs are interpreted as the end of one and the beginning of a new contour, i.e. a new profile of the same structure. To reconstruct contours, subsequent data points are joined by a line, as long as their distance D < 2RI. When D > 2RI, no connecting line is draw ...
... Data points separated by more than two RIs are interpreted as the end of one and the beginning of a new contour, i.e. a new profile of the same structure. To reconstruct contours, subsequent data points are joined by a line, as long as their distance D < 2RI. When D > 2RI, no connecting line is draw ...
Using Expert Systems and Artificial Intelligence For Real Estate
... learning algorithm similar to the function of the human brain. They work by a series of interconnected neurons in a similar manner to the working of the brain. However even with the largest modern computers it is estimated that an ANN with 10 million interconnections would have a neuron structure so ...
... learning algorithm similar to the function of the human brain. They work by a series of interconnected neurons in a similar manner to the working of the brain. However even with the largest modern computers it is estimated that an ANN with 10 million interconnections would have a neuron structure so ...
INFORMATION PROCESSING WITH POPULATION CODES
... concerns how information is encoded by the neural architecture of the brain. What are the units of computation and how is information represented at the neural level? An important part of the answers to these questions is that individual elements of information are encoded not by single cells, but r ...
... concerns how information is encoded by the neural architecture of the brain. What are the units of computation and how is information represented at the neural level? An important part of the answers to these questions is that individual elements of information are encoded not by single cells, but r ...
Multistage Cross-Sell Model of Employers in the Financial Industry
... human brain. By combining many simple computing elements into a highly interconnected system, these researchers hoped to produce complex phenomena such as intelligence. While there is considerable controversy over whether artificial neural networks are really intelligent, there is no doubt that they ...
... human brain. By combining many simple computing elements into a highly interconnected system, these researchers hoped to produce complex phenomena such as intelligence. While there is considerable controversy over whether artificial neural networks are really intelligent, there is no doubt that they ...
paper - Gatsby Computational Neuroscience Unit
... the variables z1 , . . . ,zl representing a motor plan or motor commands to muscles. Recent publications show that human reasoning and learning can also be cast into the form of probabilistic inference problems [27–29]. In these models learning of concepts, ranging from concrete to more abstract one ...
... the variables z1 , . . . ,zl representing a motor plan or motor commands to muscles. Recent publications show that human reasoning and learning can also be cast into the form of probabilistic inference problems [27–29]. In these models learning of concepts, ranging from concrete to more abstract one ...
The Journal of Neuroscience, June 1, 2003 • 23(11):4657– 4666
... Ilan A. Kerman1,2,3 Lynn W. Enquist,4 Stanley J. Watson,3 and Bill J. Yates Previous physiological investigations have suggested the existence of a neural circuit that coordinates activation of motor and autonomic efferents before or at the onset of exercise. Traditionally these circuits have been p ...
... Ilan A. Kerman1,2,3 Lynn W. Enquist,4 Stanley J. Watson,3 and Bill J. Yates Previous physiological investigations have suggested the existence of a neural circuit that coordinates activation of motor and autonomic efferents before or at the onset of exercise. Traditionally these circuits have been p ...
Self-Organizing Feature Maps with Lateral Connections: Modeling
... a erent (input) connections to the cortex. The self-organizing process is driven by external input [4, 20, 19], and appears to be based on correlated (i.e. cooccurring) neuronal activity and the resulting cooperation and competition between neurons [19, 18]. In addition to the a erent connections, t ...
... a erent (input) connections to the cortex. The self-organizing process is driven by external input [4, 20, 19], and appears to be based on correlated (i.e. cooccurring) neuronal activity and the resulting cooperation and competition between neurons [19, 18]. In addition to the a erent connections, t ...
Computation with Spikes in a Winner-Take-All Network
... case of spike rate inputs that input discrimination and the effects of selfexcitation and inhibition on this discrimination are consistent with results obtained from the standard rate-based WTA models. We also extend this discrimination analysis of spiking WTAs to nonstationary inputs with time-vary ...
... case of spike rate inputs that input discrimination and the effects of selfexcitation and inhibition on this discrimination are consistent with results obtained from the standard rate-based WTA models. We also extend this discrimination analysis of spiking WTAs to nonstationary inputs with time-vary ...
Phonemic Coding Might Result From Sensory
... example that if one optimizes the energy of vowel systems as defined by a compromise between articulatory cost and perceptual distinctiveness, one finds systems which follow the structural and frequency regularities of human languages. (Schwartz et al. 1997) reproduced and extended the results to CV s ...
... example that if one optimizes the energy of vowel systems as defined by a compromise between articulatory cost and perceptual distinctiveness, one finds systems which follow the structural and frequency regularities of human languages. (Schwartz et al. 1997) reproduced and extended the results to CV s ...