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Inhibitory inputs increase a neurons`s "ring rate
Inhibitory inputs increase a neurons`s "ring rate

In search of musical fitness on consonance
In search of musical fitness on consonance

... What sort of information does sound convey? Human mental representations of acoustic events can be elaborate in a way that the word sound doesn't offer. Sound refers indifferently to the physical sound in the world and to the mental experience of it, so that consonance/dissonance is related to physi ...
Integrating Optogenetic and Pharmacological Approaches to Study
Integrating Optogenetic and Pharmacological Approaches to Study

Media Release
Media Release

Chaos and neural dynamics
Chaos and neural dynamics

... Let us discuss at first what progress has been achieved in this area for the last fifteen years and what key experiments can be used for the analysis. The main results in this avenue are associated with the analysis of the behavior of individual neurons and neural ensembles, which confirms that the ...
Theory of Mind: A Neural Prediction Problem
Theory of Mind: A Neural Prediction Problem

Buzsaki and Draguhn (2004), Neuronal Oscillations in Cortical
Buzsaki and Draguhn (2004), Neuronal Oscillations in Cortical

For Motor Outputs, as for Sensory Inputs, Spike Timing Carries More
For Motor Outputs, as for Sensory Inputs, Spike Timing Carries More

... Freelance Science Writer, Sherborn, Massachusetts, United States of America ...
Darwin VII after - Ohio University
Darwin VII after - Ohio University

... Mirror neurons fire when a monkey observes an action it may imitate. Note that this figure shows a monkey brain, looking to the ...
Not all vosial categorization tasks require attention
Not all vosial categorization tasks require attention

Physiologically-Inspired Model for the Visual Tuning Properties of
Physiologically-Inspired Model for the Visual Tuning Properties of

... in robotics, since they have been discussed as physiological basis of the imitation learning of actions and potentially also of action understanding [2], [3]. Beyond the fact that they are active during motor planning, mirror neurons have a number of interesting visual tuning properties. They are se ...
Neural Transcription Factors: from Embryos to Neural Stem Cells
Neural Transcription Factors: from Embryos to Neural Stem Cells

A Maximum-Likelihood Approach to Modeling Multisensory
A Maximum-Likelihood Approach to Modeling Multisensory

... where CM is the mean number of impulses evoked by the combined-modality stimulus in a given time interval, and SMmax refers to the response of the most effective single-modality stimulus (cf. [3]). Response enhancement in the DSC neurons can be quite impressive, with values of M RE sometimes reachin ...
Spike-Timing-Dependent Hebbian Plasticity as
Spike-Timing-Dependent Hebbian Plasticity as

... where g is the maximal ionic conductance density, A and B are activation and inactivation variables, respectively (x denotes the order of kinetics— see Mainen & Sejonowski, 1996), and E is the reversal potential for the given ion species (EK D ¡90 mV, ENa D 60 mV, ECa D 140 mV, Eleak D ¡70 mV). For ...
The role of protein interaction networks in systems biomedicine
The role of protein interaction networks in systems biomedicine

... and the average distance to the center (essential genes) to analyze the hierarchy structure of their PPI network. Assuming essential genes as the center of the network, the disease genes appeared closer to the center than other genes. Their findings concluded that compared with other genes, both dise ...
Neural Networks
Neural Networks

On the choice of a sparse prior
On the choice of a sparse prior

... standard optimisation algorithms. Frequently used options are scaled gradient descent, conjugate gradient descent and even faster methods like the fastICA (Hyvärinen 1999) method. The properties of the optimized neurons are subsequently compared to properties of real neurons in the visual system. I ...
Schizophrenia is a multi-faceted disorder with highly complex p
Schizophrenia is a multi-faceted disorder with highly complex p

... contributions of synaptic plasticity (ref). Therefore these studies as applied to schizophrenia may elucidate fundamental neurobiological alterations in the illness. However, computational models are essential to integrate date obtained by different techniques and different levels of organization. T ...
A biologically constrained learning mechanism in networks of formal
A biologically constrained learning mechanism in networks of formal

Are all declarative memories false memories?
Are all declarative memories false memories?

... memory traces can be reactivated given a certain context, whether it is an external stimulus or an internal narrative, the ability to recall is crucial. It does not mean, however, that declarative memories are recalled only within a certain context (as is the case with associative learning like oper ...
Elsevier Editorial System(tm) for Current Opinion in Neurobiology Manuscript Draft  Manuscript Number:
Elsevier Editorial System(tm) for Current Opinion in Neurobiology Manuscript Draft Manuscript Number:

Differential Roles of the Frontal Cortex, Basal Ganglia, and
Differential Roles of the Frontal Cortex, Basal Ganglia, and

Document
Document

The Neural Control of Speech
The Neural Control of Speech

... process analogous to infant babbling and early word imitation. Synaptic projections between auditory, somatosensory, and motor cortical regions are tuned during a babbling phase in which semi-random articulator movements are used to produce auditory and somatosensory feedback. Learning in this stage ...
Memory, Concepts, and Mental Representations
Memory, Concepts, and Mental Representations

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Recurrent neural network

A recurrent neural network (RNN) is a class of artificial neural network where connections between units form a directed cycle. This creates an internal state of the network which allows it to exhibit dynamic temporal behavior. Unlike feedforward neural networks, RNNs can use their internal memory to process arbitrary sequences of inputs. This makes them applicable to tasks such as unsegmented connected handwriting recognition or speech recognition
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