Slide 1
... walking and with gait postural instability. Cognitive and behavioral problems in more advanced stages: dementia, sensory, sleep and emotional problems. ...
... walking and with gait postural instability. Cognitive and behavioral problems in more advanced stages: dementia, sensory, sleep and emotional problems. ...
Phase synchronization of bursting neurons in clustered small
... connectivity of the cat suggests that a model for numerical simulations of this structure can be a clustered network, or a network formed by interacting subnetworks [10]. The subnetworks stand for the clusters and the neurons in subnetworks are connected with neurons belonging to the same cluster an ...
... connectivity of the cat suggests that a model for numerical simulations of this structure can be a clustered network, or a network formed by interacting subnetworks [10]. The subnetworks stand for the clusters and the neurons in subnetworks are connected with neurons belonging to the same cluster an ...
Aggregate Input-Output Models of Neuronal Populations
... are biophysical-based models, which characterize the nonlinear dynamics of ionic conductances and synapses between neurons [6], [7]. Although useful in understanding underlying physiology and mechanisms of spike generation, these models become intractable for analysis of populations of neurons. Furt ...
... are biophysical-based models, which characterize the nonlinear dynamics of ionic conductances and synapses between neurons [6], [7]. Although useful in understanding underlying physiology and mechanisms of spike generation, these models become intractable for analysis of populations of neurons. Furt ...
Anthony Chang - Artificial Nerual Networks in Protein Secondary Structure Predictions
... Learning/ Training In a feed-forward neural network architecture, a unit will receive input from several nodes or neurons belonging to another layer. These highly interconnected neurons therefore form an infrastructure (similar to the biological central nervous system) that is capable of learning by ...
... Learning/ Training In a feed-forward neural network architecture, a unit will receive input from several nodes or neurons belonging to another layer. These highly interconnected neurons therefore form an infrastructure (similar to the biological central nervous system) that is capable of learning by ...
SEGMENTATION OF NEURONS BASED ON ONE
... the size of the training set B: the larger the training set, the smaller the bin size to obtain a good approximation of the distribution. Hence, we randomly select 1M samples from B and fix N = 500, we set σs = 5 because it is an adequate value for the size of the histogram, k2 = 1.5k1 because it al ...
... the size of the training set B: the larger the training set, the smaller the bin size to obtain a good approximation of the distribution. Hence, we randomly select 1M samples from B and fix N = 500, we set σs = 5 because it is an adequate value for the size of the histogram, k2 = 1.5k1 because it al ...
Changes in GABA Modulation During a Theta Cycle May Be
... the energy of afferent input relative to recurrent excitation and inhibition. 3.1 Why Do the Relative Energies of Afferent and Recurrent Inputs Change? Because activation of GABAB receptors selectively suppresses recurrent but not afferent connections (Ault & Nadler, 1982; Colbert & Levy, 1992), the ...
... the energy of afferent input relative to recurrent excitation and inhibition. 3.1 Why Do the Relative Energies of Afferent and Recurrent Inputs Change? Because activation of GABAB receptors selectively suppresses recurrent but not afferent connections (Ault & Nadler, 1982; Colbert & Levy, 1992), the ...
Two Kinds of Reverse Inference in Cognitive Neuroscience
... overlap in part of the neural pattern observed in both conditions (execution and observation) but neither makes specific predictions regarding the fine-grained structure of this pattern. Next, consider location, the result that MN (the set of mirror neurons that selectively fire at the same rate in ...
... overlap in part of the neural pattern observed in both conditions (execution and observation) but neither makes specific predictions regarding the fine-grained structure of this pattern. Next, consider location, the result that MN (the set of mirror neurons that selectively fire at the same rate in ...
Probabilistic
... Assuming a balanced binary tree structure for system level performance estimation ...
... Assuming a balanced binary tree structure for system level performance estimation ...
Neural Axis Representing Target Range in the Auditory
... second) and signal duration (7 to 34 msec). In the auditory system, the Determining the identities and exact magnetic resonance techniques. Howsynthesis of a range axis, which has no spatial arrangement of the atoms sur- ever, these techniques have the drawcorresponding anatomical precursor in round ...
... second) and signal duration (7 to 34 msec). In the auditory system, the Determining the identities and exact magnetic resonance techniques. Howsynthesis of a range axis, which has no spatial arrangement of the atoms sur- ever, these techniques have the drawcorresponding anatomical precursor in round ...
Robust Reinforcement Learning Control with Static and Dynamic
... model of the system is LTI and “uncertainties” are added with gains that are guaranteed to bound the true gains of unknown, or known and nonlinear, parts of the plant. Robust control techniques are applied to the plant model augmented with uncertainties and candidate controllers to analyze the stabi ...
... model of the system is LTI and “uncertainties” are added with gains that are guaranteed to bound the true gains of unknown, or known and nonlinear, parts of the plant. Robust control techniques are applied to the plant model augmented with uncertainties and candidate controllers to analyze the stabi ...
A Point Process Model for Auditory Neurons Considering
... function. The Volterra expansion models the neuron’s baseline spike rate, its intrinsic dynamics spiking history - and the stimulus effect which in this case is the analog of the spectro-temporal receptive field (STRF). We performed the model fitting efficiently in a generalized linear model framewo ...
... function. The Volterra expansion models the neuron’s baseline spike rate, its intrinsic dynamics spiking history - and the stimulus effect which in this case is the analog of the spectro-temporal receptive field (STRF). We performed the model fitting efficiently in a generalized linear model framewo ...
Pareto-Based Multiobjective Machine Learning: An
... algorithms and other population-based stochastic search methods. It has been shown that Pareto-based multiobjective learning approaches are more powerful compared to learning algorithms with a scalar cost function in addressing various topics of machine learning, such as clustering, feature selectio ...
... algorithms and other population-based stochastic search methods. It has been shown that Pareto-based multiobjective learning approaches are more powerful compared to learning algorithms with a scalar cost function in addressing various topics of machine learning, such as clustering, feature selectio ...
Realizing Biological Spiking Network Models in a Configurable
... the point of signal insertion does not need to be configurable, but it is done for all network chips according to the same scheme: Chips implementing up to 64 neurons insert their output signals into horizontal lane no. 0. This way, only after a horizontal routing distance of 64 network chips, two ch ...
... the point of signal insertion does not need to be configurable, but it is done for all network chips according to the same scheme: Chips implementing up to 64 neurons insert their output signals into horizontal lane no. 0. This way, only after a horizontal routing distance of 64 network chips, two ch ...
Artificial neural network model for river flow forecasting
... Grijsen et al. (1992), Elmahi & O’Connor (1995), Shamseldin et al. (1999), Shamseldin & O’Connor (2003) and Antar et al. (2005). Thus, this paper will shed more light on potential data-driven models which can be used for flood forecasting on the Blue Nile. The ANN river flow forecasting models have ...
... Grijsen et al. (1992), Elmahi & O’Connor (1995), Shamseldin et al. (1999), Shamseldin & O’Connor (2003) and Antar et al. (2005). Thus, this paper will shed more light on potential data-driven models which can be used for flood forecasting on the Blue Nile. The ANN river flow forecasting models have ...
On the Sum Secure Degrees of Freedom of Two
... communication with their respective receivers simultaneously, by utilizing a layered network between the transmitters and receivers. The single-layer version of this network is an interference channel, whose capacity is unknown in general; it is known only in certain special cases, e.g., a class of ...
... communication with their respective receivers simultaneously, by utilizing a layered network between the transmitters and receivers. The single-layer version of this network is an interference channel, whose capacity is unknown in general; it is known only in certain special cases, e.g., a class of ...
146 - BISITE
... design of CBR systems (37). ART stands for Adaptive Resonance Theory English, developed by Stephen Grossberg and Gail Carpenter is a network of three layers: input layer, without performing any pre-processing of the input data. Hidden layer. Output layer neurons is a competitive layer. The input lay ...
... design of CBR systems (37). ART stands for Adaptive Resonance Theory English, developed by Stephen Grossberg and Gail Carpenter is a network of three layers: input layer, without performing any pre-processing of the input data. Hidden layer. Output layer neurons is a competitive layer. The input lay ...
The role of temporal parameters in a thalamocortical model of analogy
... cortex-driven cortical activity? As suggested in [27] and [28], the TRN is a promising location where such a filtering can occur. The basic idea is that the reticular neurons receive both ascending thalamic input- and descending-cortical feedback, and reticular inhibition cancels out cortical feedba ...
... cortex-driven cortical activity? As suggested in [27] and [28], the TRN is a promising location where such a filtering can occur. The basic idea is that the reticular neurons receive both ascending thalamic input- and descending-cortical feedback, and reticular inhibition cancels out cortical feedba ...
PDF
... Abstract. In developing mammalian (mouse) brain, Reelin (Reln) is secreted by the Cajal-Retzius (CR) neurons in the marginal zone, binds apolipoprotein E receptor 2 (ApoER2) and very low density lipoprotein receptor (Vldlr), and induces the phosphorylation of the downstream cytoplasmic molecule disa ...
... Abstract. In developing mammalian (mouse) brain, Reelin (Reln) is secreted by the Cajal-Retzius (CR) neurons in the marginal zone, binds apolipoprotein E receptor 2 (ApoER2) and very low density lipoprotein receptor (Vldlr), and induces the phosphorylation of the downstream cytoplasmic molecule disa ...
Reinforcement learning in cortical networks
... As compared to the policy gradient rules above, the TD learning rule (17) is obtained by replacing the reward R in Eq. 1 with the TD-δ. Since this δ converges to zero during learning, any systematic weight drift is also suppressed. TD learning in the form of actor-critic has been implemented in spik ...
... As compared to the policy gradient rules above, the TD learning rule (17) is obtained by replacing the reward R in Eq. 1 with the TD-δ. Since this δ converges to zero during learning, any systematic weight drift is also suppressed. TD learning in the form of actor-critic has been implemented in spik ...
Stochastic fluctuations of the synaptic function
... Diffusion of the neurotransmitter molecules in the synaptic cleft is one of its crucial points that is influenced by the geometry of the synaptic space, both at the presynaptic side and at the postsynaptic one, and by probabilistic factors. The problem of synaptic transmission was discussed in our r ...
... Diffusion of the neurotransmitter molecules in the synaptic cleft is one of its crucial points that is influenced by the geometry of the synaptic space, both at the presynaptic side and at the postsynaptic one, and by probabilistic factors. The problem of synaptic transmission was discussed in our r ...
lingue e linguaggio - Istituto di Linguistica Computazionale
... by interference effects between false morphological friends (or pseudoderivations) such as broth and brother, sharing a conspicuous word onset but unrelated morphologically (Frost, Forster & Deutsch, 1997; Rastle, Davis & New, 2004; Post et al., 2008). The evidence shows that as soon as a given lett ...
... by interference effects between false morphological friends (or pseudoderivations) such as broth and brother, sharing a conspicuous word onset but unrelated morphologically (Frost, Forster & Deutsch, 1997; Rastle, Davis & New, 2004; Post et al., 2008). The evidence shows that as soon as a given lett ...
Bayesian Spiking Neurons II: Learning
... more (or less) probable than average was xt when a spike was received from that synapse. Thus, the weights are positively or negatively incremented depending on whether the probability of xt tends to be larger or smaller than its running average at the moment of the synaptic input. Similarly, learni ...
... more (or less) probable than average was xt when a spike was received from that synapse. Thus, the weights are positively or negatively incremented depending on whether the probability of xt tends to be larger or smaller than its running average at the moment of the synaptic input. Similarly, learni ...
Development of neuromotor prostheses
... designs are in wide use in animals for acute recording and these can function chronically in rats (Kipke et al., 2003). New polyamide and ceramic electrode arrays, which provide flexibility using a biocompatible material, are also in development (Moxon, 1999; Rousche et al., 2001). These electrodes ...
... designs are in wide use in animals for acute recording and these can function chronically in rats (Kipke et al., 2003). New polyamide and ceramic electrode arrays, which provide flexibility using a biocompatible material, are also in development (Moxon, 1999; Rousche et al., 2001). These electrodes ...