Automatic Composition of Music with Methods of Computational
... methods like Markov chains of different order. A great introduction to the modelling of interrelations in music with statistical methods can be found in [23]. Another important thing to point out is that the implementation is licensed under the Gnu Public Licence1 so that everyone can try out the pr ...
... methods like Markov chains of different order. A great introduction to the modelling of interrelations in music with statistical methods can be found in [23]. Another important thing to point out is that the implementation is licensed under the Gnu Public Licence1 so that everyone can try out the pr ...
Visuomotor neurons: ambiguity of the discharge or `motor` perception?
... towards the stimulus ŽB2.. This last condition is the critical one that allows to determine whether F4 visual receptive fields are coded in a non-retinotopic coordinate system: In the case of a retinotopically coded visual receptive field, the gaze deviation towards the visual stimulus should be acc ...
... towards the stimulus ŽB2.. This last condition is the critical one that allows to determine whether F4 visual receptive fields are coded in a non-retinotopic coordinate system: In the case of a retinotopically coded visual receptive field, the gaze deviation towards the visual stimulus should be acc ...
Rate versus Temporal Coding Models
... neuron, up to recordings from intact brains in behaving animals. Therefore, in addition to describing the ideas behind the putative temporal codes, this article will try to evaluate the evidence in support of each code. The evidence for a temporal code can be divided broadly into four categories (se ...
... neuron, up to recordings from intact brains in behaving animals. Therefore, in addition to describing the ideas behind the putative temporal codes, this article will try to evaluate the evidence in support of each code. The evidence for a temporal code can be divided broadly into four categories (se ...
Differentiating features for the Weibull, Gamma, Log
... hidden nodes are reduced using QLP decomposition. The algorithm is based in the reduction of number hidden nodes with QLP. For each trial, a training set ( xi , p i ) was established, where p is an indicator function representing the density function which generated the sample vector x. An out of sa ...
... hidden nodes are reduced using QLP decomposition. The algorithm is based in the reduction of number hidden nodes with QLP. For each trial, a training set ( xi , p i ) was established, where p is an indicator function representing the density function which generated the sample vector x. An out of sa ...
different sensory modalities
... extension of the superficial ones – somatosensory neurons in the deeper layers have large receptive fields and are organized in maps which show a regular relationship with visual maps: the front of the animal is represented rostral while the hindparts are caudal, the upper surface is represented med ...
... extension of the superficial ones – somatosensory neurons in the deeper layers have large receptive fields and are organized in maps which show a regular relationship with visual maps: the front of the animal is represented rostral while the hindparts are caudal, the upper surface is represented med ...
choosing the greater of two goods: neural currencies for valuation
... an eye movement to one of two targets that are aligned with the axis of stimulus motion. b | In a perceptual discrimination task, a psychometric function quantifies the reliance of behaviour on the sensory signals being manipulated experimentally. c | The general structure of a free-choice task, in ...
... an eye movement to one of two targets that are aligned with the axis of stimulus motion. b | In a perceptual discrimination task, a psychometric function quantifies the reliance of behaviour on the sensory signals being manipulated experimentally. c | The general structure of a free-choice task, in ...
Vision`s First Steps: Anatomy, Physiology, and Perception in the
... Each LGN receives input from both eyes, but the input from each eye is segregated to different monocular layers: layers 1, 3, and 6 get input from the contralateral eye, whereas layers 2, 4, and 5 get input from the ipsilateral eye [94]. Hubel and Wiesel discovered that LGN receptive fields have a s ...
... Each LGN receives input from both eyes, but the input from each eye is segregated to different monocular layers: layers 1, 3, and 6 get input from the contralateral eye, whereas layers 2, 4, and 5 get input from the ipsilateral eye [94]. Hubel and Wiesel discovered that LGN receptive fields have a s ...
Life and Death of Neurons in the Aging Brain
... labeling) (C). As AD progresses, these neurons eventually lose neurofilament-protein immunoreactivity (13). In a more advanced AD case, transitional forms can be observed in layer III of the superior frontal cortex (D through F ). Several neurons contain both neurofilament-protein immunoreactivity ( ...
... labeling) (C). As AD progresses, these neurons eventually lose neurofilament-protein immunoreactivity (13). In a more advanced AD case, transitional forms can be observed in layer III of the superior frontal cortex (D through F ). Several neurons contain both neurofilament-protein immunoreactivity ( ...
The Constructive Nature of Visual Processing
... involves analysis of the layout of scenes and of surface properties, parsing the visual image into surfaces and global contours, and distinguishing foreground from background (see Chapter 27). The highest level involves object recognition (see Chapter 28). Once a scene has been parsed by the brain a ...
... involves analysis of the layout of scenes and of surface properties, parsing the visual image into surfaces and global contours, and distinguishing foreground from background (see Chapter 27). The highest level involves object recognition (see Chapter 28). Once a scene has been parsed by the brain a ...
Laminar Differences in Dendritic Structure of Pyramidal Neurons in
... cells has been reported to be area specific. For example, pyramidal cells in the temporal lobe of higher primates are larger, but less spinous, than those of the granular prefrontal cortex (Lund et al. 1993; Elston et al. 2001; Jacobs et al. 2001; Elston and Rockland 2002; Elston et al. 2011; Bianchi ...
... cells has been reported to be area specific. For example, pyramidal cells in the temporal lobe of higher primates are larger, but less spinous, than those of the granular prefrontal cortex (Lund et al. 1993; Elston et al. 2001; Jacobs et al. 2001; Elston and Rockland 2002; Elston et al. 2011; Bianchi ...
PDF
... (1987). They further suggest that there are two types of reward prediction errors: a signal representing error in the timing of reward prediction, which may be related to the TD model, and a signal coding for error in the type and amount of reward prediction, which may be related to the adaptive res ...
... (1987). They further suggest that there are two types of reward prediction errors: a signal representing error in the timing of reward prediction, which may be related to the TD model, and a signal coding for error in the type and amount of reward prediction, which may be related to the adaptive res ...
Fifty years of CPGs: two neuroethological papers that shaped BEHAVIORAL NEUROSCIENCE
... sequence of spikes in the five neurons (Wyman, 1965). Thus, major features of neural control of flight were very different in these different classes of insects. Here, we will first summarize work on four difficult questions that arose immediately from Wiersma’s and Wilson’s insights, and then consi ...
... sequence of spikes in the five neurons (Wyman, 1965). Thus, major features of neural control of flight were very different in these different classes of insects. Here, we will first summarize work on four difficult questions that arose immediately from Wiersma’s and Wilson’s insights, and then consi ...
29.2 Neurons - Cloudfront.net
... Directions: Please make a picture bubble map of this neuron. Use p. 876-879 in your book to help you. Label all major parts of a neuron (cell body, dendrites, axon, myelin sheath, axon terminals, action potential, synapse, neurotransmitters). Once all parts are labeled, you need to describe the func ...
... Directions: Please make a picture bubble map of this neuron. Use p. 876-879 in your book to help you. Label all major parts of a neuron (cell body, dendrites, axon, myelin sheath, axon terminals, action potential, synapse, neurotransmitters). Once all parts are labeled, you need to describe the func ...
Marginal chimera state at cross-frequency locking of pulse
... (see Ref. [5] for its experimental observation). Remarkably, partial synchronization can be explained within a simplest setup of one-dimensional oscillators, described either by their phase dynamics [4] or as integrate-and-fire units [3]. Quite recently, chimera states in populations of coupled osci ...
... (see Ref. [5] for its experimental observation). Remarkably, partial synchronization can be explained within a simplest setup of one-dimensional oscillators, described either by their phase dynamics [4] or as integrate-and-fire units [3]. Quite recently, chimera states in populations of coupled osci ...
Text S1.
... could have differentiated into an axon. The discrepancy between random choice at 1-2 DIV and axonal preference along L1 at 3 DIV corresponds to failures of polarization along curved lines. It is thus possible to calculate a success probability for a neurite to become an axon when growing over a curv ...
... could have differentiated into an axon. The discrepancy between random choice at 1-2 DIV and axonal preference along L1 at 3 DIV corresponds to failures of polarization along curved lines. It is thus possible to calculate a success probability for a neurite to become an axon when growing over a curv ...
A review of artificial intelligence applications in
... corresponding outputs using machine learning by repeatedly presenting examples of the model inputs and outputs (training) to find the function y5f(x) that minimizes the error between the historical (actual) outputs and the outputs predicted by the AI model. If the relationship between x and y is non ...
... corresponding outputs using machine learning by repeatedly presenting examples of the model inputs and outputs (training) to find the function y5f(x) that minimizes the error between the historical (actual) outputs and the outputs predicted by the AI model. If the relationship between x and y is non ...
The horizontal brain slice preparation: a novel approach for
... the pattern and strength of the different inputs received by outer-layer neurons can be explored. Also, this preparation makes it possible to study the development of local tectal-tectal connectivity between the different layers. Although it is evident that there exists extensive local connectivity ...
... the pattern and strength of the different inputs received by outer-layer neurons can be explored. Also, this preparation makes it possible to study the development of local tectal-tectal connectivity between the different layers. Although it is evident that there exists extensive local connectivity ...
as a PDF
... have plausible neuronal implementations, but there is no associated claim, express or implied, that the brain actually performs those calculations. Put simply, BECCA’s purpose is not to describe the brain, but to perform like it. ...
... have plausible neuronal implementations, but there is no associated claim, express or implied, that the brain actually performs those calculations. Put simply, BECCA’s purpose is not to describe the brain, but to perform like it. ...
Viewpoint - Columbia University
... can robust behavioral dynamics emerge naturally out of the biophysics of spontaneously active, imprecisely specified networks of unreliable and heterogeneous neuronal elements? We address this fundamental question by examining the dynamics of single neurons in the lateral intraparietal area (LIP) of ...
... can robust behavioral dynamics emerge naturally out of the biophysics of spontaneously active, imprecisely specified networks of unreliable and heterogeneous neuronal elements? We address this fundamental question by examining the dynamics of single neurons in the lateral intraparietal area (LIP) of ...
KISHORE Aswathy - School of Computing
... representation’. Accordingly, different features of the object such as shape, texture and colour will be represented in different parts of the brain. Hence, in order to have a complete representation for the object, these individual localised representations have to be bound together to form a globa ...
... representation’. Accordingly, different features of the object such as shape, texture and colour will be represented in different parts of the brain. Hence, in order to have a complete representation for the object, these individual localised representations have to be bound together to form a globa ...
Spike Train - CMU Statistics
... In probability and statistics, irregular sequences of event times are modeled as point processes. If we start at time t = 0 and let X1 , X2 , .P . . be a sequence of random variables representing the ISIs, then the time of the jth spike is given by Sj = ji=1 Xi and the sequence S1 , S2 , . . . forms ...
... In probability and statistics, irregular sequences of event times are modeled as point processes. If we start at time t = 0 and let X1 , X2 , .P . . be a sequence of random variables representing the ISIs, then the time of the jth spike is given by Sj = ji=1 Xi and the sequence S1 , S2 , . . . forms ...
Fast and slow neurons in the nucleus of the
... TF combination for each neuron. At the end of the experiments, the birds were given an overdose of sodium pentobarbitol (100 mg/kg intraperitoneally (i.p.)) and immediately perfused with saline followed by 4% paraformaldehyde. The brains were extracted and sectioned such that the electrode tracts co ...
... TF combination for each neuron. At the end of the experiments, the birds were given an overdose of sodium pentobarbitol (100 mg/kg intraperitoneally (i.p.)) and immediately perfused with saline followed by 4% paraformaldehyde. The brains were extracted and sectioned such that the electrode tracts co ...
Markov logic networks | SpringerLink
... Popescul & Ungar, 2003). They are often quite complex. In this paper, we introduce Markov logic networks (MLNs), a representation that is quite simple, yet combines probability and first-order logic with no restrictions other than finiteness of the domain. We develop efficient algorithms for inferen ...
... Popescul & Ungar, 2003). They are often quite complex. In this paper, we introduce Markov logic networks (MLNs), a representation that is quite simple, yet combines probability and first-order logic with no restrictions other than finiteness of the domain. We develop efficient algorithms for inferen ...
Untitled
... Two-photon (2P) excitation is a method that has revolutionized many areas of biological science as it enables three-dimensionally defined excitation of chromophores in biological tissue. We have developed 2P uncaging methods to reveal the microarchitecture of synaptic connections at a level of singl ...
... Two-photon (2P) excitation is a method that has revolutionized many areas of biological science as it enables three-dimensionally defined excitation of chromophores in biological tissue. We have developed 2P uncaging methods to reveal the microarchitecture of synaptic connections at a level of singl ...
