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All-Optical Interrogation of Neural Circuits
All-Optical Interrogation of Neural Circuits

On the Role of Biophysical Properties of Cortical Neurons in Binding
On the Role of Biophysical Properties of Cortical Neurons in Binding

The role of spiking nonlinearity in contrast gain control
The role of spiking nonlinearity in contrast gain control

Matching tutor to student: rules and mechanisms for
Matching tutor to student: rules and mechanisms for

... output. To test this, we numerically simulated the birdsong circuit using the linear model from Fig. 2A with a motor output ya filtered to more realistically reflect muscle response times (see Methods). We selected plasticity rules as described in Fig. 2B and picked a target output pattern to learn. ...
Reinforcement Learning Using a Continuous Time Actor
Reinforcement Learning Using a Continuous Time Actor

VALUE-DEPENDENT SELECTION IN THE BRAIN: SIMULATION IN
VALUE-DEPENDENT SELECTION IN THE BRAIN: SIMULATION IN

The subtle body: an interoceptive map of central nervous system
The subtle body: an interoceptive map of central nervous system

... reproductive—plus five that modulate the five senses. The eight drops include four pairs of arousing (masculine) and calming (feminine) vital fluids that together modulate the four main levels and states of consciousness—waking, dreaming, sleeping, and orgasmic. Although primarily located within the ...
Associative learning signals in the brain
Associative learning signals in the brain

ITU / BDT Regional Network Planning Arab Region
ITU / BDT Regional Network Planning Arab Region

... – How to forecast services and traffic demands? – How many nodes to install ? – What is best location for systems and related communication media ? – What is the best network architecture and routing ? – Best balance between built and lease ? – How to plan capacity evolution and solutions migration ...
link to pdf of article - UCSF Center for Integrative Neuroscience
link to pdf of article - UCSF Center for Integrative Neuroscience

... involves “replaying” this contextual signal that, in turn, preferentially activates the items associated with the current state of the signal. Such models require the ability to form associations between context signal and component item through one-shot learning to allow for novel sequence performa ...
Models of Information Processing in the Visual Cortex
Models of Information Processing in the Visual Cortex

... receptive field w(t) of the neuron. In signal processing jargon, y(t) is the basis coefficient. To some extent, a set of I neurons can be assimilated into a bank of I finite impulse response filters (FIR) which impulse response is equal to a set of I receptive fields w. Depending on the number of neurons ...
Nonlinear Population Codes - Department of Nonlinear Dynamics
Nonlinear Population Codes - Department of Nonlinear Dynamics

Physiology
Physiology

... The synapse is an early site of fatigue in the reflex arc and the fatigue of the neural synapses is caused by: i. Exhaustion of the chemical transmitter in the presynaptic terminals which is the main cause. ii. Inactivation of some postsynaptic receptors due to accumulation of ...
One Computer Scientist`s (Deep) Superior Colliculus
One Computer Scientist`s (Deep) Superior Colliculus

... Every natural organism embodies solutions to a host of ecological problems, found through eons of evolution. The study of these solutions and their applications in technical settings is called biomimetics and it has been a driving force in many areas of research. Biomimetic approaches at various lev ...
the cognitive neuroscience of motivation and learning
the cognitive neuroscience of motivation and learning

... course, such devaluation insensitive behavior does not demonstrate that animals are literally ignorant of the action-outcome contingency, only that this information does not impact their decision to lever press. It is important to note that, because it excludes habits and requires that behavior demo ...
Sparse Coding in the Neocortex
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 ...
Human frequency-following response: representation of pitch
Human frequency-following response: representation of pitch

... hypothesis. In their electrophysiological study, Cariani and Delgutte (1996) recorded responses of cat auditory nerve ¢bers and combined interval distributions from many ¢bers to form an estimate of population interval distribution in the entire auditory nerve. Many deep correspondences between feat ...
cur op e-print version
cur op e-print version

... within-session stability. Larger shifts have been produced by performance manipulations such as adding weight to the lever [8]. The notion that BSR and gustatory reward are combined downstream from the point where physiological feedback signals modulate gustatory value [4] is not easily reconciled w ...
Neural realisation of the SP theory
Neural realisation of the SP theory

The Computation and Comparison of Value in Goal
The Computation and Comparison of Value in Goal

... Goal-directed systems are capable of computing values in novel situations and in environments with rapidly changing action–outcome contingencies. These systems assign values to actions by computing action–outcome contingencies and then evaluating the rewards associated with the different outcomes. U ...
The hippocampal–striatal axis in learning, prediction and
The hippocampal–striatal axis in learning, prediction and

DSS Chapter 1
DSS Chapter 1

... Relation between internal activation and output ...
PVLV: The Primary Value and Learned Value
PVLV: The Primary Value and Learned Value

... using an eligibility trace as in TD(␭), where 0 ⬍ ␭ ⬍1 parameterizes an exponentially decaying trace of the input stimuli used for learning. This can smooth over rough spots in the chain but at the potential cost of reducing the temporal precision of reward predictions as a result of excessive smear ...
BMP inhibitors and neural patterning
BMP inhibitors and neural patterning

Cell Adhesion Molecules in Neural Stem Cell and
Cell Adhesion Molecules in Neural Stem Cell and

... CAMs have been shown to play distinct roles in the nervous system. 2.1.1. L1CAM subfamily L1CAM subfamily proteins, which include L1, close homolog of L1 (CHL1), NrCAM, and Neurofascin, are one of the most well known groups of IgSF CAMs and are widely studied in the nervous system. L1CAM proteins ca ...
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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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