Spiking Neurons - Computing Science and Mathematics
... or T = 500 ms are typical , but the duration may also be longer or shorter. This definition of rate has been successfully used in many preparations , particularly in experiments on sensory or motor systems. A classicalexample is the stretch receptor in a muscle spindle [Adrian, 1926] . The number of ...
... or T = 500 ms are typical , but the duration may also be longer or shorter. This definition of rate has been successfully used in many preparations , particularly in experiments on sensory or motor systems. A classicalexample is the stretch receptor in a muscle spindle [Adrian, 1926] . The number of ...
Multiplicative Gain Changes Are Induced by Excitation or Inhibition
... voltage-dependent increase of the NMDA conductance. However, when we simulated the iontophoresis of AMPA by opening a constant 1.0 nS AMPA conductance, we observed a similar increase in firing rates. The maximum firing rate increased to 48 Hz, and the firing rate at C ⫽ 0.0 increased to 0.81 Hz. The ...
... voltage-dependent increase of the NMDA conductance. However, when we simulated the iontophoresis of AMPA by opening a constant 1.0 nS AMPA conductance, we observed a similar increase in firing rates. The maximum firing rate increased to 48 Hz, and the firing rate at C ⫽ 0.0 increased to 0.81 Hz. The ...
The role of spiking nonlinearity in contrast gain control
... The obtained ropt increases with saturation g (see Fig. 2e). It also increases slightly with an increase in threshold h (Fig. 2f). This might provide a mechanism and rules for a neuron to adjust its transfer function and gain tuning curve according to the statistical context of the input signals. Ho ...
... The obtained ropt increases with saturation g (see Fig. 2e). It also increases slightly with an increase in threshold h (Fig. 2f). This might provide a mechanism and rules for a neuron to adjust its transfer function and gain tuning curve according to the statistical context of the input signals. Ho ...
Improving CNN Performance with Min-Max Objective
... can be broadly divided into the following three categories: (1) increasing the model complexity, (2) increasing the training samples, and (3) improving training strategies. This section reviews representative works for each category. Increasing the model complexity includes adding either the network ...
... can be broadly divided into the following three categories: (1) increasing the model complexity, (2) increasing the training samples, and (3) improving training strategies. This section reviews representative works for each category. Increasing the model complexity includes adding either the network ...
Neural computations associated with goal
... Consider a canonical decision making problem. Every day a hungry animal is placed at the bottom of a Y-‐maze and is allowed to run towards the upper left or right to collect a reward. The left ...
... Consider a canonical decision making problem. Every day a hungry animal is placed at the bottom of a Y-‐maze and is allowed to run towards the upper left or right to collect a reward. The left ...
Mechanisms to synchronize neuronal activity
... cortex (area 17) of anesthetized cats (Gray and Singer 1989; Gray et al. 1990) a broad peak in the frequency spectrum has been found in the range 35±70 Hz. This is in line with results by Eckhorn et al. (1988) who reported an even broader distribution of oscillation frequencies in areas 17 and 18 of ...
... cortex (area 17) of anesthetized cats (Gray and Singer 1989; Gray et al. 1990) a broad peak in the frequency spectrum has been found in the range 35±70 Hz. This is in line with results by Eckhorn et al. (1988) who reported an even broader distribution of oscillation frequencies in areas 17 and 18 of ...
EVOLUTIONARY AUTONOMOUS AGENTS: A NEUROSCIENCE
... really begin to realize this potential? And what can be learned from these studies? Here, I selectively review a few studies that explore specific questions that are of relevance to neuroscience. I begin with studies that have modelled simple animal systems, and proceed with models of evolution and ...
... really begin to realize this potential? And what can be learned from these studies? Here, I selectively review a few studies that explore specific questions that are of relevance to neuroscience. I begin with studies that have modelled simple animal systems, and proceed with models of evolution and ...
Text S1.
... 70% of the neurons were excitatory, which connected to other postsynaptic neurons with excitatory synapses, and the other neurons were inhibitory (30%) [10]. The setup of excitatory and inhibitory synapses is described later. The relations between several properties of spontaneous bursting and the p ...
... 70% of the neurons were excitatory, which connected to other postsynaptic neurons with excitatory synapses, and the other neurons were inhibitory (30%) [10]. The setup of excitatory and inhibitory synapses is described later. The relations between several properties of spontaneous bursting and the p ...
PDF file
... network, inappropriate for online autonomous development for an open length of time period. IHDR overcomes both problems by allowing dynamic spawning nodes from a growing tree, while shallow nodes and unmatched leaf nodes serving as the long term memory. However, IHDR is not an in-place learner (e.g ...
... network, inappropriate for online autonomous development for an open length of time period. IHDR overcomes both problems by allowing dynamic spawning nodes from a growing tree, while shallow nodes and unmatched leaf nodes serving as the long term memory. However, IHDR is not an in-place learner (e.g ...
Adding Data Mining Support to SPARQL via Statistical
... information provided by the links between objects. These links are usually hard to model by traditional propositional learning techniques. We extend this idea to the Semantic Web. In this paper we introduce a novel approach we call SPARQL-ML to perform data mining for Semantic Web data. Our approach ...
... information provided by the links between objects. These links are usually hard to model by traditional propositional learning techniques. We extend this idea to the Semantic Web. In this paper we introduce a novel approach we call SPARQL-ML to perform data mining for Semantic Web data. Our approach ...
Review of Logical Foundations of Artificial Intelligence
... on page 133: "Let MIA I and M*la I be two models of A. (You may want to refer to Chapter 2 to review the definition of a model in logic.)" A reader who needs to review the definition of model will have probems in deciphering the barrage of symbols in the subsequent two paragraphs. An example at this ...
... on page 133: "Let MIA I and M*la I be two models of A. (You may want to refer to Chapter 2 to review the definition of a model in logic.)" A reader who needs to review the definition of model will have probems in deciphering the barrage of symbols in the subsequent two paragraphs. An example at this ...