The role of temporal parameters in a thalamocortical model of analogy
... selectively directs information received from the sensory periphery and also from the cortex. This insight is due to the massive convergence of both afferent and cortical feedback on to the thalamus (which is supposed to integrate diverse information), and also due to the inhibitory network surround ...
... selectively directs information received from the sensory periphery and also from the cortex. This insight is due to the massive convergence of both afferent and cortical feedback on to the thalamus (which is supposed to integrate diverse information), and also due to the inhibitory network surround ...
A neural implementation of Bayesian inference based on predictive
... values; 1 and 2 are parameters; and and ⊗ indicate element-wise division and multiplication respectively. For all the experiments described in this paper 1 and 2 were given the values 1 × 10−6 and 1 × 10−4 respectively. Parameter 1 prevents prediction neurons becoming permanently non-responsi ...
... values; 1 and 2 are parameters; and and ⊗ indicate element-wise division and multiplication respectively. For all the experiments described in this paper 1 and 2 were given the values 1 × 10−6 and 1 × 10−4 respectively. Parameter 1 prevents prediction neurons becoming permanently non-responsi ...
From format to function: Embodiment and the functional roles of
... the biological substrate of cognition. It is a claimed overlap at the neural level that gives concepts their perceptual or motor format. Importantly, modal accounts often do not specify whether it is conceptual representations or processes that are proposed to be modal (Machery, 2007). See, for inst ...
... the biological substrate of cognition. It is a claimed overlap at the neural level that gives concepts their perceptual or motor format. Importantly, modal accounts often do not specify whether it is conceptual representations or processes that are proposed to be modal (Machery, 2007). See, for inst ...
The Neural Foundations of Reaction and Action in Aversive Motivation
... Actions are also complex behaviors, but they are not simply elicited by a stimulus. Rather, they are emitted in the combined presence of certain stimuli and internal factors such as motivation and arousal and performed in order to obtain a goal or reward (Skinner 1938; Estes and Skinner 1941; Estes ...
... Actions are also complex behaviors, but they are not simply elicited by a stimulus. Rather, they are emitted in the combined presence of certain stimuli and internal factors such as motivation and arousal and performed in order to obtain a goal or reward (Skinner 1938; Estes and Skinner 1941; Estes ...
cur op e-print version
... The computation of utility involves sensory, perceptual, motivational, and cognitive mechanisms. How can such a process be brought under tight experimental control so as to link particular components to the activity of identifiable neural populations? One approach is to replace or supplement natural ...
... The computation of utility involves sensory, perceptual, motivational, and cognitive mechanisms. How can such a process be brought under tight experimental control so as to link particular components to the activity of identifiable neural populations? One approach is to replace or supplement natural ...
Abstracts - BCCN 2009
... But this meeting also differs in some ways from its four predecessors. We were charged with the task of opening the meeting internationally. To this end, we solicited the submission of abstracts from all over the world and recruited an international program committee to evaluate abstracts for their ...
... But this meeting also differs in some ways from its four predecessors. We were charged with the task of opening the meeting internationally. To this end, we solicited the submission of abstracts from all over the world and recruited an international program committee to evaluate abstracts for their ...
Efficient Event-Driven Simulation of Large Networks of Spiking
... far as a static prescription for synaptic efficacies, according to some chosen “learning rule.” In this way, a long and important series of results have been obtained, which have made these models candidates for an account of the retrieval and maintenance of “learned” internal representations of a s ...
... far as a static prescription for synaptic efficacies, according to some chosen “learning rule.” In this way, a long and important series of results have been obtained, which have made these models candidates for an account of the retrieval and maintenance of “learned” internal representations of a s ...
Review Early Steps in the Development of the Forebrain
... the anterior neural plate and the regional subdivision of this territory into the different domains of the prospective forebrain. The Structure, Origins, and Morphogenesis of the Forebrain Our conscious thoughts, our emotions, and many of our memories reside within the forebrain, and indeed it is th ...
... the anterior neural plate and the regional subdivision of this territory into the different domains of the prospective forebrain. The Structure, Origins, and Morphogenesis of the Forebrain Our conscious thoughts, our emotions, and many of our memories reside within the forebrain, and indeed it is th ...
Sparse Coding in the Neocortex
... can be highly selective to faces and other objects (e.g., Kendrick and Baldwin, 1987; Quiroga, et al. 2005). However, those promoting the usefulness of sparse representations are not proposing that the ultimate goal is to have one neuron for every object—and certainly not for a particular view of e ...
... can be highly selective to faces and other objects (e.g., Kendrick and Baldwin, 1987; Quiroga, et al. 2005). However, those promoting the usefulness of sparse representations are not proposing that the ultimate goal is to have one neuron for every object—and certainly not for a particular view of e ...
Migration and Differentiation of Neural Crest
... were used to determine retention times and the quantitative response of the electrochemical detector. Limits of detection were arbitrarily defined as a clear peak with a height at least 5 times baseline noise. Table 1 shows typical retention times and limits of detection. The identities of peaks fro ...
... were used to determine retention times and the quantitative response of the electrochemical detector. Limits of detection were arbitrarily defined as a clear peak with a height at least 5 times baseline noise. Table 1 shows typical retention times and limits of detection. The identities of peaks fro ...
The migration of neural crest cells and the growth of
... stages being found where the segmental plate is dividing into somites, and the most advanced next to the otic vesicle. At these stages the distribution of neural crest cells is the same a given number of somites rostral to the region where somites are forming from the segmental plate, regardless of ...
... stages being found where the segmental plate is dividing into somites, and the most advanced next to the otic vesicle. At these stages the distribution of neural crest cells is the same a given number of somites rostral to the region where somites are forming from the segmental plate, regardless of ...
PDF
... E11.5 mouse embryos. Although elements of these expression patterns have been published (Adams et al., 1996; Kawasaki et al., 2002), we wanted to compare expression levels and localization directly over a defined time period. Trunk neural crest cells migrate segmentally through the somites at E9.5, ...
... E11.5 mouse embryos. Although elements of these expression patterns have been published (Adams et al., 1996; Kawasaki et al., 2002), we wanted to compare expression levels and localization directly over a defined time period. Trunk neural crest cells migrate segmentally through the somites at E9.5, ...
CNS*2004 July 18-22, 2004 Baltimore, Maryland
... July 21st the Regisration desk will be open from 8:00 am until 5:00 pm. Oral Sessions: An LCD projector will be available for all speakers to use and the main meeting room is supplied with a large screen and an ampification system. Poster Sessions: Posters should be set up before lunch time and remo ...
... July 21st the Regisration desk will be open from 8:00 am until 5:00 pm. Oral Sessions: An LCD projector will be available for all speakers to use and the main meeting room is supplied with a large screen and an ampification system. Poster Sessions: Posters should be set up before lunch time and remo ...
Visuomotor development
... neural circuits involved in this process in the primate brain are faced with significant issues of complexity. This is because, it is not obvious how the perceptual areas are connected with the motor regions for sensory information transfer (Glickstein, 2000; Kandel et al., 2000). Second, in order t ...
... neural circuits involved in this process in the primate brain are faced with significant issues of complexity. This is because, it is not obvious how the perceptual areas are connected with the motor regions for sensory information transfer (Glickstein, 2000; Kandel et al., 2000). Second, in order t ...
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.