View PDF - CiteSeerX
... Figure 1. Temporal estimation data from humans (A, B) or rats (C, D) using peak-interval timing procedures. In the peak-interval procedure used with humans, participants were instructed to watch as a blue square appeared on a computer screen and to be “aware” of the amount of time that passed (eithe ...
... Figure 1. Temporal estimation data from humans (A, B) or rats (C, D) using peak-interval timing procedures. In the peak-interval procedure used with humans, participants were instructed to watch as a blue square appeared on a computer screen and to be “aware” of the amount of time that passed (eithe ...
Neurotransmitter Function
... The potential fluctuates depending on the flow and concentration of ions inside and outside the cell. • depolarized or hyperpolarized ...
... The potential fluctuates depending on the flow and concentration of ions inside and outside the cell. • depolarized or hyperpolarized ...
Rate versus Temporal Coding Models
... continually on the basis of new information obtained at all levels of inquiry, from the channels responsible for electrical activity in parts of the neuron, up to recordings from intact brains in behaving animals. Therefore, in addition to describing the ideas behind the putative temporal codes, thi ...
... continually on the basis of new information obtained at all levels of inquiry, from the channels responsible for electrical activity in parts of the neuron, up to recordings from intact brains in behaving animals. Therefore, in addition to describing the ideas behind the putative temporal codes, thi ...
nervous system - Zanichelli online per la scuola
... Across the membrane of cells there is a differential distribution of electrical charges due to a different concentration of ions inside and outside the cell. This difference creates the membrane potential. Sensory stimuli alter the membrane potential. If the sum of signals arriving to dendrites is h ...
... Across the membrane of cells there is a differential distribution of electrical charges due to a different concentration of ions inside and outside the cell. This difference creates the membrane potential. Sensory stimuli alter the membrane potential. If the sum of signals arriving to dendrites is h ...
Physiology and Ecology Review
... • When presented with unrealistic models – As long as some red is present, the attack behavior occurs ...
... • When presented with unrealistic models – As long as some red is present, the attack behavior occurs ...
Associative memory with spatiotemporal chaos control
... factor in the learning process, the recognition rate of the network can be much enhanced. Random and regular samplings of the pattern for the control are tested and the successful results of the associations are demonstrated. The chaotic behavior and recalling ability of the system are evaluated bas ...
... factor in the learning process, the recognition rate of the network can be much enhanced. Random and regular samplings of the pattern for the control are tested and the successful results of the associations are demonstrated. The chaotic behavior and recalling ability of the system are evaluated bas ...
Modeling goal-directed spatial navigation in the rat based on physiological
... the virtual rat enters a place field the corresponding place cell fires at late phases of theta in CA1—predictive spiking. As the virtual rat crosses the place field, place cell firing becomes earlier in theta in CA1—encoding spiking (Fig. 6). During encoding phases in the model we simulate suppress ...
... the virtual rat enters a place field the corresponding place cell fires at late phases of theta in CA1—predictive spiking. As the virtual rat crosses the place field, place cell firing becomes earlier in theta in CA1—encoding spiking (Fig. 6). During encoding phases in the model we simulate suppress ...
(addl. 3)
... Where a, b, c, d, and I are parameters that define the neuron’s behavior, v is a variable representing the membrane potential in millivolts, and u is a variable representing membrane recovery. The parameter I represents the synaptic current resulting from the combination of post-synaptic potentials. ...
... Where a, b, c, d, and I are parameters that define the neuron’s behavior, v is a variable representing the membrane potential in millivolts, and u is a variable representing membrane recovery. The parameter I represents the synaptic current resulting from the combination of post-synaptic potentials. ...
Challenges for Brain Emulation
... Where a, b, c, d, and I are parameters that define the neuron’s behavior, v is a variable representing the membrane potential in millivolts, and u is a variable representing membrane recovery. The parameter I represents the synaptic current resulting from the combination of post-synaptic potentials. ...
... Where a, b, c, d, and I are parameters that define the neuron’s behavior, v is a variable representing the membrane potential in millivolts, and u is a variable representing membrane recovery. The parameter I represents the synaptic current resulting from the combination of post-synaptic potentials. ...
48nervous
... In the northern flying squirrel (Glaucomys sabrinus), activity normally begins with the onset of darkness and ends at dawn, which suggests that light is an important external cue for the squirrel. To test this idea, researchers monitored the activity of captive squirrels for 23 days under two sets o ...
... In the northern flying squirrel (Glaucomys sabrinus), activity normally begins with the onset of darkness and ends at dawn, which suggests that light is an important external cue for the squirrel. To test this idea, researchers monitored the activity of captive squirrels for 23 days under two sets o ...
Computing auditory perception - Machine Learning Group, TU Berlin
... computational models. By combining formalised neurons, artificial neural networks and cognitive models, we can implement a model of auditory perception. Can we make use of such a model, e.g. in hearing aids, compression, automated music analysis, or music composition? We can, to some extent. But ofte ...
... computational models. By combining formalised neurons, artificial neural networks and cognitive models, we can implement a model of auditory perception. Can we make use of such a model, e.g. in hearing aids, compression, automated music analysis, or music composition? We can, to some extent. But ofte ...
Simulation of signal flow in 3D reconstructions of an anatomically
... and in vivo). This allows investigating how anatomical parameters of individual neurons, such as dendrite morphology, soma location or synaptic innervation patterns, may influence the signal flow within neural circuits. Several approaches aim to reconstruct wiring diagrams of complete neural circuit ...
... and in vivo). This allows investigating how anatomical parameters of individual neurons, such as dendrite morphology, soma location or synaptic innervation patterns, may influence the signal flow within neural circuits. Several approaches aim to reconstruct wiring diagrams of complete neural circuit ...
A neural model of hierarchical reinforcement learning
... attempts to output the value of its associated action given the current state (as represented by the activity of the s population). Using the NEF we can interpret the output of the a neurons as estimated Q values. Next, the system needs to select an action to perform based on those Q values. The “se ...
... attempts to output the value of its associated action given the current state (as represented by the activity of the s population). Using the NEF we can interpret the output of the a neurons as estimated Q values. Next, the system needs to select an action to perform based on those Q values. The “se ...
A Biologically Inspired Visuo-Motor Control Model based on a Deflationary
... – Mirror neurons code an expected perception; – Mirror neurons compare the expected perception representation with the actual perception. As we will argue below, this interpretation enables one to account for the following biological data: – mirror neuron are active in the same way during both execu ...
... – Mirror neurons code an expected perception; – Mirror neurons compare the expected perception representation with the actual perception. As we will argue below, this interpretation enables one to account for the following biological data: – mirror neuron are active in the same way during both execu ...
2 - IS MU
... formation of nerve impulses – action potentials caused by changes in ion flows across cell membranes. Action potential spread without decreasing along axons to the axon terminals. The lipidic dilayer is practically impermeable to the unevenly distributed Na+ and K+ ions. The resting membrane potenti ...
... formation of nerve impulses – action potentials caused by changes in ion flows across cell membranes. Action potential spread without decreasing along axons to the axon terminals. The lipidic dilayer is practically impermeable to the unevenly distributed Na+ and K+ ions. The resting membrane potenti ...
Neurotransmitter Parameter Definitions
... numbers of axons and are important in integrating neural circuits. This also provides an explanation for serotonin's role in so many health concerns. Downloadable PDF: Serotonin Pathway Taurine is an inhibitory neurotransmitter involved in neuromodulatory and neuroprotective actions. Supplementing w ...
... numbers of axons and are important in integrating neural circuits. This also provides an explanation for serotonin's role in so many health concerns. Downloadable PDF: Serotonin Pathway Taurine is an inhibitory neurotransmitter involved in neuromodulatory and neuroprotective actions. Supplementing w ...
Hebbian learning - Computer Science | SIU
... In contrast to supervised learning, unsupervised or self-organised learning does not require an external teacher. During the training session, the neural network receives a number of different input patterns, discovers significant features in these patterns and learns how to classify input data i ...
... In contrast to supervised learning, unsupervised or self-organised learning does not require an external teacher. During the training session, the neural network receives a number of different input patterns, discovers significant features in these patterns and learns how to classify input data i ...
The Superior Olivary Nucleus and Its Influence on Nucleus
... 20.4 and 10.9 nA current injections in a faster time scale. The resting membrane potential of this neuron was 259 mV. B, Function showing the relationship of current injected (in nanoamperes) and maximum membrane voltage deflection (in millivolts) for 23 SON cells (mean 6 SD). The slope of I–V f unc ...
... 20.4 and 10.9 nA current injections in a faster time scale. The resting membrane potential of this neuron was 259 mV. B, Function showing the relationship of current injected (in nanoamperes) and maximum membrane voltage deflection (in millivolts) for 23 SON cells (mean 6 SD). The slope of I–V f unc ...
Nervous System
... ______ 14. The part of the brain that controls balance, posture, and movement is the a. hypothalamus. b. cortex. c. cerebellum. ______ 15. The part of a neuron that receives information from other neurons is a a. synapse. b. dendrite. c. nucleus. ______ 16. A sudden, rapid, and involuntary self-prot ...
... ______ 14. The part of the brain that controls balance, posture, and movement is the a. hypothalamus. b. cortex. c. cerebellum. ______ 15. The part of a neuron that receives information from other neurons is a a. synapse. b. dendrite. c. nucleus. ______ 16. A sudden, rapid, and involuntary self-prot ...
Solving the Problem of Negative Synaptic Weights in Cortical Models
... arbitrary transformations on the encoded variables. Conveniently, the same methods can be employed. Instead of finding decoders φ to decode an estimate of x (i.e., computing the identity function), the same linear leastsquares method can be used to provide decoders φ g(x) for some arbitrary function ...
... arbitrary transformations on the encoded variables. Conveniently, the same methods can be employed. Instead of finding decoders φ to decode an estimate of x (i.e., computing the identity function), the same linear leastsquares method can be used to provide decoders φ g(x) for some arbitrary function ...
Epilepsy in Small
... models of excitatory neurons in hippocampus. To keep the number of free parameters manageable, to more easily constrain activity to spread in a controlled manner, and to eliminate the effects of boundary conditions, we restricted our analyses to one-dimensional “rings” of neurons. Because organizati ...
... models of excitatory neurons in hippocampus. To keep the number of free parameters manageable, to more easily constrain activity to spread in a controlled manner, and to eliminate the effects of boundary conditions, we restricted our analyses to one-dimensional “rings” of neurons. Because organizati ...
Time constants
... ms for neocortical pyramidal cells and 20-50 ms for other CNS neurons (Koch et al. 1996, p. 96), which in our notation gives α = 70 s-1 for pyramidal cells and α = 20-50 s-1 for other neurons. The value for pyramidal cells agrees fairly well with Rowe et al. (2004, p. 423), who reported α = 75 s-1 f ...
... ms for neocortical pyramidal cells and 20-50 ms for other CNS neurons (Koch et al. 1996, p. 96), which in our notation gives α = 70 s-1 for pyramidal cells and α = 20-50 s-1 for other neurons. The value for pyramidal cells agrees fairly well with Rowe et al. (2004, p. 423), who reported α = 75 s-1 f ...
Encoding of Movement Fragments in the Motor Cortex
... four MI neurons relative to movement onset computed in an instructed-delay center-out task to one of eight targets. B, Left, Example of a single successful behavioral trial in the RTP task starting with the blue target, proceeding through the green targets, and ending at the red target. A sample tra ...
... four MI neurons relative to movement onset computed in an instructed-delay center-out task to one of eight targets. B, Left, Example of a single successful behavioral trial in the RTP task starting with the blue target, proceeding through the green targets, and ending at the red target. A sample tra ...
TEACHERS`NOTES AND REFERENCES
... 3. describe the structure of a sensory neuron and a motor neuron, and outline their functions in a reflex arc. 4. describe and explain the transmission of an action potential in a myelinated neuron. (The importance of sodium and potassium ions in the impulse transmission should be emphasised.) 5. ex ...
... 3. describe the structure of a sensory neuron and a motor neuron, and outline their functions in a reflex arc. 4. describe and explain the transmission of an action potential in a myelinated neuron. (The importance of sodium and potassium ions in the impulse transmission should be emphasised.) 5. ex ...