8 pages - Science for Monks
... of the brain, conscious perception and its reporting take place. Take vision, for example, where there is a recurrent connection to my language area. From there I have a recurrent connection to my frontal cortex and access to my vocabulary for words to describe what I am seeing. These recurrent conn ...
... of the brain, conscious perception and its reporting take place. Take vision, for example, where there is a recurrent connection to my language area. From there I have a recurrent connection to my frontal cortex and access to my vocabulary for words to describe what I am seeing. These recurrent conn ...
Neural Crest_Origin, Migration and Differentiation
... neural crest migration is especially well studied. At the trunk level, neural crest cells migrate ventrally between the neural tube and somites, until they arrive at the interface between the myotome and sclerotome. Here they abruptly turn almost 908 and migrate medially to laterally through the som ...
... neural crest migration is especially well studied. At the trunk level, neural crest cells migrate ventrally between the neural tube and somites, until they arrive at the interface between the myotome and sclerotome. Here they abruptly turn almost 908 and migrate medially to laterally through the som ...
Edge of chaos and prediction of computational performance for
... are examples of noisy variations (Gaussian jitter with SD 10 ms) of these spike patterns which were used as circuit inputs. (b) Fraction of examples (for 500 test examples) for which the output of a linear readout (trained by linear regression with 2000 training examples) agreed with the target clas ...
... are examples of noisy variations (Gaussian jitter with SD 10 ms) of these spike patterns which were used as circuit inputs. (b) Fraction of examples (for 500 test examples) for which the output of a linear readout (trained by linear regression with 2000 training examples) agreed with the target clas ...
Large-scale cognitive model design using the Nengo neural simulator
... decodings are combined with the neural encodings to determine the connection weights between populations of neurons. The function to be computed by the weights is specified in Nengo when making a connection between ensembles (the default function is identity, i:e: fðxÞ ¼ x). Fig. 3 demonstrates two ...
... decodings are combined with the neural encodings to determine the connection weights between populations of neurons. The function to be computed by the weights is specified in Nengo when making a connection between ensembles (the default function is identity, i:e: fðxÞ ¼ x). Fig. 3 demonstrates two ...
14.10 Insight 775 Gilbert
... case of contrast discrimination. Adini et al.7 assume that perceptual learning is mediated by an increase in contrast sensitivity. This, in turn, results from stimulus-evoked modifications to recurrent connections in the local network in the primary visual cortex. The model assumes that contrast dis ...
... case of contrast discrimination. Adini et al.7 assume that perceptual learning is mediated by an increase in contrast sensitivity. This, in turn, results from stimulus-evoked modifications to recurrent connections in the local network in the primary visual cortex. The model assumes that contrast dis ...
A Small World of Neuronal Synchrony
... simultaneously the spiking activity of up to 24 neurons that were distributed within and across several microcolumns of cat primary visual cortex. This allowed us to relate network properties to some of the characteristic features of visual neurons such as their orientation tuning. When using correl ...
... simultaneously the spiking activity of up to 24 neurons that were distributed within and across several microcolumns of cat primary visual cortex. This allowed us to relate network properties to some of the characteristic features of visual neurons such as their orientation tuning. When using correl ...
Temporal Lobe Epilepsy
... with epilepsy. Physicians diagnose 200,000 new cases of epilepsy each year. A variety of insults to the brain may result in epilepsy such as a birth defect, birth injury, bleeding in the brain, brain infection, brain tumor, head injury or stroke [2]. There are hundreds of epilepsy syndromes, many of ...
... with epilepsy. Physicians diagnose 200,000 new cases of epilepsy each year. A variety of insults to the brain may result in epilepsy such as a birth defect, birth injury, bleeding in the brain, brain infection, brain tumor, head injury or stroke [2]. There are hundreds of epilepsy syndromes, many of ...
Synaptic energy efficiency in retinal processing
... symmetric error correction network (Baldi & Hornik, 1995). In its unmodified form this calculates the optimal (least squared reconstruction error) filters, for a set of M inputs which converge on N outputs. An input sample, denoted by the column vector x, is forward propagated through filters W to give ...
... symmetric error correction network (Baldi & Hornik, 1995). In its unmodified form this calculates the optimal (least squared reconstruction error) filters, for a set of M inputs which converge on N outputs. An input sample, denoted by the column vector x, is forward propagated through filters W to give ...
Deep Learning Overview
... All parameters are “tuned” for the supervised task at hand Representation is adjusted to be more discriminative ...
... All parameters are “tuned” for the supervised task at hand Representation is adjusted to be more discriminative ...
Time representation in reinforcement learning models of
... 1999): (1) the microstimulus representation and (2) states with variable durations (a semi-Markov formalism) and only partial observability. For the former, Ludvig et al. (2008) proposed that when a stimulus is presented, it leaves a slowly decaying memory trace, which is then encoded by a series of ...
... 1999): (1) the microstimulus representation and (2) states with variable durations (a semi-Markov formalism) and only partial observability. For the former, Ludvig et al. (2008) proposed that when a stimulus is presented, it leaves a slowly decaying memory trace, which is then encoded by a series of ...
Evolution of central pattern generators and rhythmic behaviours
... analogous rhythmic behaviours have evolved independently, it has generally been with different neural mechanisms. Repeated evolution of particular rhythmic behaviours has occurred within some lineages due to parallel evolution or latent CPGs. Particular motor pattern generating mechanisms have also ...
... analogous rhythmic behaviours have evolved independently, it has generally been with different neural mechanisms. Repeated evolution of particular rhythmic behaviours has occurred within some lineages due to parallel evolution or latent CPGs. Particular motor pattern generating mechanisms have also ...
Artificial neural network
In machine learning and cognitive science, artificial neural networks (ANNs) are a family of statistical learning models inspired by biological neural networks (the central nervous systems of animals, in particular the brain) and are used to estimate or approximate functions that can depend on a large number of inputs and are generally unknown. Artificial neural networks are generally presented as systems of interconnected ""neurons"" which exchange messages between each other. The connections have numeric weights that can be tuned based on experience, making neural nets adaptive to inputs and capable of learning.For example, a neural network for handwriting recognition is defined by a set of input neurons which may be activated by the pixels of an input image. After being weighted and transformed by a function (determined by the network's designer), the activations of these neurons are then passed on to other neurons. This process is repeated until finally, an output neuron is activated. This determines which character was read.Like other machine learning methods - systems that learn from data - neural networks have been used to solve a wide variety of tasks that are hard to solve using ordinary rule-based programming, including computer vision and speech recognition.