Brain rhythms in mental time travel
... the neural signature of this contextual retrieval process in topographic patterns of intracranially recorded oscillatory activity. The computational theory of mental time travel described here provides a set of properties we expect a neural contextual representation to exhibit (Polyn and Kahana, 200 ...
... the neural signature of this contextual retrieval process in topographic patterns of intracranially recorded oscillatory activity. The computational theory of mental time travel described here provides a set of properties we expect a neural contextual representation to exhibit (Polyn and Kahana, 200 ...
Visual Motion Perception using Critical Branching Neural Computation
... and is the previous time that Vi was updated. Thus, the model included continuous exponential leak, applied each time a given neuron received an input. Immediately after each Vi update, if Vi>θi, then Vi 0, and a postsynaptic potential Ij was generated for each axonal synapse of i. Each Ij=wj, and w ...
... and is the previous time that Vi was updated. Thus, the model included continuous exponential leak, applied each time a given neuron received an input. Immediately after each Vi update, if Vi>θi, then Vi 0, and a postsynaptic potential Ij was generated for each axonal synapse of i. Each Ij=wj, and w ...
Neural Networks - National Taiwan University
... A firing rule determines how one calculates whether a neuron should fire for any input pattern. A simple firing rule can be implemented by using Hamming distance technique: ◦ Take a collection of training patterns for a node, some of which cause it to fire (the 1-taught set of patterns) and others w ...
... A firing rule determines how one calculates whether a neuron should fire for any input pattern. A simple firing rule can be implemented by using Hamming distance technique: ◦ Take a collection of training patterns for a node, some of which cause it to fire (the 1-taught set of patterns) and others w ...
Techniques and Methods to Implement Neural Networks Using SAS
... for this Feedforward Backpropagation net. Here there are two matrices M1 and M2 whose elements are the weights on connections. M1 refers to the interface between the input and hidden layers, and M2 refers to that between the hidden layer and output layer. Since connections exist from each neuron in ...
... for this Feedforward Backpropagation net. Here there are two matrices M1 and M2 whose elements are the weights on connections. M1 refers to the interface between the input and hidden layers, and M2 refers to that between the hidden layer and output layer. Since connections exist from each neuron in ...
Activity 1 - Web Adventures
... electrical signal passed from the dendrites to the cell body of the neuron (move the lightning bolt along Neuron 1). From there the signal traveled at up to 250 miles per hour, down the axon carrying signals away from the cell body and on to other places. Suddenly, the signal reached a synapse (have ...
... electrical signal passed from the dendrites to the cell body of the neuron (move the lightning bolt along Neuron 1). From there the signal traveled at up to 250 miles per hour, down the axon carrying signals away from the cell body and on to other places. Suddenly, the signal reached a synapse (have ...
Neural Networks
... In the training mode, the neuron can be trained to fire (or not), for particular input patterns. In the using mode, when a taught input pattern is detected at the input, its associated output becomes the current output. If the input pattern does not belong in the taught list of input patterns, the f ...
... In the training mode, the neuron can be trained to fire (or not), for particular input patterns. In the using mode, when a taught input pattern is detected at the input, its associated output becomes the current output. If the input pattern does not belong in the taught list of input patterns, the f ...
Memory from the dynamics of intrinsic membrane currents
... The behavior of rhythmic networks depends on the complex interaction between the dynamics of the individual neurons (their intrinsic properties) and the strengths and time courses of the synapses among them (1–3). Years of research on networks as diverse as central pattern generators in invertebrate ...
... The behavior of rhythmic networks depends on the complex interaction between the dynamics of the individual neurons (their intrinsic properties) and the strengths and time courses of the synapses among them (1–3). Years of research on networks as diverse as central pattern generators in invertebrate ...
THE NEURON
... Dendrites receive impulses from other neurons and carry impulses to the cell body. ...
... Dendrites receive impulses from other neurons and carry impulses to the cell body. ...
Neural Networks
... It is a fixed weight network that can be used to implement boolean functions. Its characteristics are: Binary activation (1 ON, 0 OFF). i.e. it either fires with an activation 1 or does not fire with an activation of 0. Neurons are connected by directed weighted paths. If w > 0, excitatory, else inh ...
... It is a fixed weight network that can be used to implement boolean functions. Its characteristics are: Binary activation (1 ON, 0 OFF). i.e. it either fires with an activation 1 or does not fire with an activation of 0. Neurons are connected by directed weighted paths. If w > 0, excitatory, else inh ...
The Influence of Odor and Emotion on Memory
... hippocampus and the olfactory regions of the brain (Gourevitch et al., 2010). Diffusion tensor imaging of the limbic system has noted the circuit connections found between the hippocampus and other structures such as the olfactory bulb and amygdala (Concha et al., 2005). Research has found that the ...
... hippocampus and the olfactory regions of the brain (Gourevitch et al., 2010). Diffusion tensor imaging of the limbic system has noted the circuit connections found between the hippocampus and other structures such as the olfactory bulb and amygdala (Concha et al., 2005). Research has found that the ...
Ch24- Memory Systems - Biology Courses Server
... – At first, all cells respond to newly presented faces the same amount – With repeated exposures, some faces evoke a greater response than others - i.e., cells become more selective ...
... – At first, all cells respond to newly presented faces the same amount – With repeated exposures, some faces evoke a greater response than others - i.e., cells become more selective ...
Mechanisms underlying working memory for novel information
... Box 1. Computational modeling of single cell mechanisms for working memory The hypothetical link between the cellular data and behavioral data presented here has been described and analyzed in detailed computational models. Lisman and colleagues initially proposed that intrinsic afterdepolarization ...
... Box 1. Computational modeling of single cell mechanisms for working memory The hypothetical link between the cellular data and behavioral data presented here has been described and analyzed in detailed computational models. Lisman and colleagues initially proposed that intrinsic afterdepolarization ...
Recognition by Variance: Learning Rules for Spatiotemporal Patterns
... the remaining possible patterns are termed background patterns. The task is to build a model that recognizes a learned pattern as a familiar one by producing a larger output when presented with it, compared to when presented with a typical background pattern. The model therefore reduces the high di ...
... the remaining possible patterns are termed background patterns. The task is to build a model that recognizes a learned pattern as a familiar one by producing a larger output when presented with it, compared to when presented with a typical background pattern. The model therefore reduces the high di ...
Insect olfactory memory in time and space
... properties of DPM neuronal process after olfactory learning. They found that pairing odor with shock increased subsequent odor-evoked calcium influx and synaptic release from the DPM neurons, but this increase was delayed, appearing first at 30 min after training and persisting for at least an hour ...
... properties of DPM neuronal process after olfactory learning. They found that pairing odor with shock increased subsequent odor-evoked calcium influx and synaptic release from the DPM neurons, but this increase was delayed, appearing first at 30 min after training and persisting for at least an hour ...
neural_networks
... of active synapses into a scalar value termed the internal excitation or net input excitation (or just excitation for short). However, the output of such a McCulloch-Pitts neuron is either zero or one. Crude binary encoding of the internal excitation: neuron fires (output of one) when its net input ...
... of active synapses into a scalar value termed the internal excitation or net input excitation (or just excitation for short). However, the output of such a McCulloch-Pitts neuron is either zero or one. Crude binary encoding of the internal excitation: neuron fires (output of one) when its net input ...
Artificial Neural Network PPT
... comprising almost 80 percent of the data. • Testing data: This data set is used when the final ANN is ready. Testing data, which are completely unknown, are used to test the system’s actual performance. The testing data set consists of about 10 percent of the data. • Validation data: These data are ...
... comprising almost 80 percent of the data. • Testing data: This data set is used when the final ANN is ready. Testing data, which are completely unknown, are used to test the system’s actual performance. The testing data set consists of about 10 percent of the data. • Validation data: These data are ...
A Neuron Play - Web Adventures
... cell body and on to other places. Suddenly, the signal reached a synapse (have first neurotransmitter person come up). This was it. There was a gap and the electrical signal could not go across it. All of a sudden though, some chemicals, neurotransmitters, went across the gap and on to the dendrites ...
... cell body and on to other places. Suddenly, the signal reached a synapse (have first neurotransmitter person come up). This was it. There was a gap and the electrical signal could not go across it. All of a sudden though, some chemicals, neurotransmitters, went across the gap and on to the dendrites ...
Memory Dysfunction
... people’s names and other proper nouns, which is common, particularly in healthy older adults, or to a true loss of semantic information. Patients with mild dysfunction of semantic memory may show only reduced generation of words for semantic categories (e.g., the number of names of animals that can ...
... people’s names and other proper nouns, which is common, particularly in healthy older adults, or to a true loss of semantic information. Patients with mild dysfunction of semantic memory may show only reduced generation of words for semantic categories (e.g., the number of names of animals that can ...
Memory Dysfunction - New England Journal of Medicine
... people’s names and other proper nouns, which is common, particularly in healthy older adults, or to a true loss of semantic information. Patients with mild dysfunction of semantic memory may show only reduced generation of words for semantic categories (e.g., the number of names of animals that can ...
... people’s names and other proper nouns, which is common, particularly in healthy older adults, or to a true loss of semantic information. Patients with mild dysfunction of semantic memory may show only reduced generation of words for semantic categories (e.g., the number of names of animals that can ...
Inhibitory inputs increase a neurons`s "ring rate
... inputs to exactly balanced inhibitory and excitatory inputs. We term the phenomenon increasing-inhibition boosted "ring (IBF). A natural and interesting question is then why and when increasing inhibitory inputs to a neuron can boost its e!erent "ring rate. A full treatment of the HH and the FHN mod ...
... inputs to exactly balanced inhibitory and excitatory inputs. We term the phenomenon increasing-inhibition boosted "ring (IBF). A natural and interesting question is then why and when increasing inhibitory inputs to a neuron can boost its e!erent "ring rate. A full treatment of the HH and the FHN mod ...
The importance of mixed selectivity in complex
... would be considered an eigenvector of that transformation matrix (so would all multiples of it.) Eigenvectors can only be found for square matrices. o Not every square matrix has eigenvectors o For an nxn matrix that has eigenvectors, there are n of them. E.g if a mtrix is 3x3 and has eigenvectors ...
... would be considered an eigenvector of that transformation matrix (so would all multiples of it.) Eigenvectors can only be found for square matrices. o Not every square matrix has eigenvectors o For an nxn matrix that has eigenvectors, there are n of them. E.g if a mtrix is 3x3 and has eigenvectors ...
Systems memory consolidation in Drosophila
... to be acquired, encoded, stored, maintained and retrieved. As time passes after training, memories become less easily retrieved, but also become progressively more stable in the face of experimental perturbations. This process is referred to as consolidation. But the term has been used to describe t ...
... to be acquired, encoded, stored, maintained and retrieved. As time passes after training, memories become less easily retrieved, but also become progressively more stable in the face of experimental perturbations. This process is referred to as consolidation. But the term has been used to describe t ...
Physiology
... This leads to spread of the signal into an increasing number of neurons as it passes from one order of neurons into another (fig. 2-6). It may be called an "amplifying divergence". It occurs, for example, in the pyramidal tract where a single pyramidal neuron in the motor cerebral cortex can excite ...
... This leads to spread of the signal into an increasing number of neurons as it passes from one order of neurons into another (fig. 2-6). It may be called an "amplifying divergence". It occurs, for example, in the pyramidal tract where a single pyramidal neuron in the motor cerebral cortex can excite ...
A Neural Model of Rule Generation in Inductive Reasoning
... error rates), but it does not reflect the flexibility and variability of individual human performance nor take into account neurologic data. In addition, Carpenter et al.’s model has no ability to generate new rules; the rules are all specified beforehand by the modelers. This limitation of their mo ...
... error rates), but it does not reflect the flexibility and variability of individual human performance nor take into account neurologic data. In addition, Carpenter et al.’s model has no ability to generate new rules; the rules are all specified beforehand by the modelers. This limitation of their mo ...