Memory formation: from network structure to neural dynamics
... complexity of the neuronal networks that comprise the brain. The cortex alone contains 1010 neurons and 1.5 × 1014 synapses, making it impossible to derive any detailed properties of its connectivity. It is not even clear that having a detailed knowledge of the connectivity would be sufficient to und ...
... complexity of the neuronal networks that comprise the brain. The cortex alone contains 1010 neurons and 1.5 × 1014 synapses, making it impossible to derive any detailed properties of its connectivity. It is not even clear that having a detailed knowledge of the connectivity would be sufficient to und ...
Information transmission and recovery in neural communications
... may be recovered at a later waystation and thus become useful again. Our discussion of the transmission properties of active neural channels is phrased in the context of an idealized channel composed on one neuron N1 that receives information in the form of a spike train and passes this on, modulate ...
... may be recovered at a later waystation and thus become useful again. Our discussion of the transmission properties of active neural channels is phrased in the context of an idealized channel composed on one neuron N1 that receives information in the form of a spike train and passes this on, modulate ...
STOCHASTIC GENERATION OF BIOLOGICALLY - G
... The neuronal connectivity of human and other mammalian brains is so far largely uncharted. Indeed, anatomically correct network models of the brain do not exist at present for the mammalian brain of any species; there is simply not enough threedimensional (3D) neuro-anatomical data available concern ...
... The neuronal connectivity of human and other mammalian brains is so far largely uncharted. Indeed, anatomically correct network models of the brain do not exist at present for the mammalian brain of any species; there is simply not enough threedimensional (3D) neuro-anatomical data available concern ...
Biomechanics Models Motor Cortex Using Spinal Cord and Limb
... stability against significant perturbations. This implies that the brain does not use significant co-activation of antagonist muscles to increase the hand’s impedance (Hogan 1984, 1989; Osu et al. 2004). Two essential properties related to the plant model are the number of degrees of freedoms (DOF) ...
... stability against significant perturbations. This implies that the brain does not use significant co-activation of antagonist muscles to increase the hand’s impedance (Hogan 1984, 1989; Osu et al. 2004). Two essential properties related to the plant model are the number of degrees of freedoms (DOF) ...
Cerebellum: The Brain for an Implicit Self
... Current systems neurobiology addresses this issue to some extent, but available methodology and technology are limited and guiding hypotheses are still sparse. To this end, research on the cerebellum is on the forefront for asking the question “How does our brain accomplish its most complex and soph ...
... Current systems neurobiology addresses this issue to some extent, but available methodology and technology are limited and guiding hypotheses are still sparse. To this end, research on the cerebellum is on the forefront for asking the question “How does our brain accomplish its most complex and soph ...
Irregular persistent activity induced by synaptic excitatory feedback
... The mechanisms of working memory at the neuronal level have been investigated in the last three decades using single neuron electrophysiological recordings in monkeys performing delayed response tasks (Funahashi et al., 1989; Fuster and Alexander, 1971; Fuster and Jervey, 1981; Goldman-Rakic, 1995; ...
... The mechanisms of working memory at the neuronal level have been investigated in the last three decades using single neuron electrophysiological recordings in monkeys performing delayed response tasks (Funahashi et al., 1989; Fuster and Alexander, 1971; Fuster and Jervey, 1981; Goldman-Rakic, 1995; ...
The Representation of Biological Classes in the Human Brain
... were screened for MRI scanning and provided informed consent in acexperiment for our six stimulus categories using deconvolution using cordance with the Institutional Review Board of Dartmouth College. AFNI software (3dDeconvolve). Each stimulus event was modeled by a Subjects were paid an hourly ra ...
... were screened for MRI scanning and provided informed consent in acexperiment for our six stimulus categories using deconvolution using cordance with the Institutional Review Board of Dartmouth College. AFNI software (3dDeconvolve). Each stimulus event was modeled by a Subjects were paid an hourly ra ...
Fixed-parameter complexity in AI and nonmonotonic reasoning
... theory when the attention is restricted to models of size k. This problem, referred-to as small model circumscription (SMC), is easily seen to be fixed-parameter intractable, but it does not seem to be complete for any of the fp-complexity classes defined by Downey and Fellows. We introduce the new ...
... theory when the attention is restricted to models of size k. This problem, referred-to as small model circumscription (SMC), is easily seen to be fixed-parameter intractable, but it does not seem to be complete for any of the fp-complexity classes defined by Downey and Fellows. We introduce the new ...
Lecture notes Neural Computation
... Introduction: Principles of Neural Computation The brain is a complex computing machine which is evolving to give the “fittest” output to a given input. Neural computation has as goal to describe the function of the nervous system in mathematical terms. By analysing or simulating the resulting equat ...
... Introduction: Principles of Neural Computation The brain is a complex computing machine which is evolving to give the “fittest” output to a given input. Neural computation has as goal to describe the function of the nervous system in mathematical terms. By analysing or simulating the resulting equat ...
Full Paper (PDF 376832 bytes). - Vanderbilt University School of
... evaluates groupings, patterns, and relationships using a relevant set of features selected in the context of a problem solving task [2]. Depending on the discovery engine employed in the system, the results can be further analyzed to derive models as rules, analytic equations, and concept definition ...
... evaluates groupings, patterns, and relationships using a relevant set of features selected in the context of a problem solving task [2]. Depending on the discovery engine employed in the system, the results can be further analyzed to derive models as rules, analytic equations, and concept definition ...
PowerPoint 簡報
... Why need Learning The problem domain knowledge for the complicated system usually does not exist or is extremely difficult to obtain. ...
... Why need Learning The problem domain knowledge for the complicated system usually does not exist or is extremely difficult to obtain. ...
Time-delay-induced phase-transition to synchrony in coupled
... (also known as gap junctions), and excitatory and inhibitory chemical synapses. Across all types of weak couplings and in both systems of coupled HR and IN neurons, we observe time-delay induced phase-flip bifurcations to synchrony or out-of-synchrony as time delay s is varied. In the case of period ...
... (also known as gap junctions), and excitatory and inhibitory chemical synapses. Across all types of weak couplings and in both systems of coupled HR and IN neurons, we observe time-delay induced phase-flip bifurcations to synchrony or out-of-synchrony as time delay s is varied. In the case of period ...
Modeling Toothpaste Brand Choice
... levels. Targeting to decompose sales increases, Gupta6 proposed a method within which brand sales were considered the result of consumer decisions about when, what, and how much to buy. Leaning on the assumption that “a customer decides to purchase a product category first and, if so, buys a particu ...
... levels. Targeting to decompose sales increases, Gupta6 proposed a method within which brand sales were considered the result of consumer decisions about when, what, and how much to buy. Leaning on the assumption that “a customer decides to purchase a product category first and, if so, buys a particu ...
Algorithm selection by rational metareasoning as
... of human strategy selection. Rational metareasoning appears to be a promising framework for reverse-engineering how people choose among cognitive strategies and translating the results into better solutions to the algorithm selection problem. ...
... of human strategy selection. Rational metareasoning appears to be a promising framework for reverse-engineering how people choose among cognitive strategies and translating the results into better solutions to the algorithm selection problem. ...
The Bifurcating Neuron Network 1q
... where each integrator represents a neuron. These two examples suggest that the possibility of a chaotic network out of non-chaotic elements is plentiful. However, we decided to follow the other option, a network of chaotic neurons, for the following reason. Chaotic activity will be more useful in th ...
... where each integrator represents a neuron. These two examples suggest that the possibility of a chaotic network out of non-chaotic elements is plentiful. However, we decided to follow the other option, a network of chaotic neurons, for the following reason. Chaotic activity will be more useful in th ...
A Well-Behaved Algorithm for Simulating Dependence Structures of
... Bayesian networks (BNs) [8, 5] have been widely accepted as an effective formalism for inference with uncertain knowledge in artificial intelligent systems [4]. A BN uses a directed acyclic graph (DAG) to represent the dependence structure of a set of domain variables and an underlying probability d ...
... Bayesian networks (BNs) [8, 5] have been widely accepted as an effective formalism for inference with uncertain knowledge in artificial intelligent systems [4]. A BN uses a directed acyclic graph (DAG) to represent the dependence structure of a set of domain variables and an underlying probability d ...
ANN Models Optimized using Swarm Intelligence Algorithms
... product attributes provides a real-time indication of the efficacy of the requirements, design, code and test cases and the overall quality of the software to be built [18]. Software quality of systems depends on the internal attributes of the software like size, coupling, and cohesion. These intern ...
... product attributes provides a real-time indication of the efficacy of the requirements, design, code and test cases and the overall quality of the software to be built [18]. Software quality of systems depends on the internal attributes of the software like size, coupling, and cohesion. These intern ...
Pathfinding in Computer Games
... There are four neighbouring nodes to (1,1) which are E(1,0), (2,1), (1,2), (2,2) respectively. Since E(1,0) is the only node, which is not on either of the lists, it is now looked at. Given that all the neighbours of (1,1) have been looked at, it is added to the Closed list. Since E(1,0) is the end ...
... There are four neighbouring nodes to (1,1) which are E(1,0), (2,1), (1,2), (2,2) respectively. Since E(1,0) is the only node, which is not on either of the lists, it is now looked at. Given that all the neighbours of (1,1) have been looked at, it is added to the Closed list. Since E(1,0) is the end ...
