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Part IV- Single neuron computation
Part IV- Single neuron computation

... at very low threshold, inactivate fast. 2. L type voltage activated Ca channels (L for long)- open only at higher threshold, very very slow de-activation (not inactivation-what is the difference?) =>T open at low threshold (Vm)->inward current->depolarization-> action potential (T close)->higher dep ...
Foundations for a Circuit Complexity Theory of Sensory
Foundations for a Circuit Complexity Theory of Sensory

... “threshold gates” or “winner-take-all gates” of inputs, that take one unit of time for their computation like all the other gates, but which occupy each a set of intersection points of the grid that are all connected by an undirected wire (whose length contributes to the total wire length) in some a ...
Neural ensemble coding and statistical periodicity: Speculations on
Neural ensemble coding and statistical periodicity: Speculations on

... This map is referred to as the tent map because of its graphical appearance [98]. The variable x could be taken to represent, for example, the instantaneous neural firing rate or the inter-spike interval. Models of the nervous system in which time is discrete arise in the description of pulse-couple ...
Neural Machines for Music Recognition
Neural Machines for Music Recognition

... between individual brain cells. Therefore the patterns in the outside world are transformed into a neural encoding in the peripheral zones of the sensory organs. Observations from the outside world represented as patterns of electrochemical signals can subsequently be processed and interpreted by ou ...
Williams Syndrome Neuronal Size and Neuronal-Packing Density in Primary Visual Cortex
Williams Syndrome Neuronal Size and Neuronal-Packing Density in Primary Visual Cortex

... pathways have been characterized on the basis of anatomical,41 psychophysical,42,43 and physiological properties.28,44 Neurons in these 2 systems differ in terms of receptive field size, sensitivity to color and light contrast, and timing properties. The parvo system is ideally suited for form, text ...
Pontine Respiratory Center
Pontine Respiratory Center

... then inhibits the apneustic centre thus switching off the inspiration . • This is a protective mechanism preventing excess inflation of the lungs. The threshold for this reflex is tidal volume more than 1.5 litres(T.V.≥1.5l) ...
Classification of Clustered Microcalcifications using Resilient
Classification of Clustered Microcalcifications using Resilient

... accepted imaging method for routine breast cancer screening. It is recommended that women at the ages of 40 or above should have a mammogram every one to two years [3]. Although mammography is widely used around the world for breast cancer detection, it is difficult for expert radiologists to provid ...
Sequencing the connectome. - Cold Spring Harbor Laboratory
Sequencing the connectome. - Cold Spring Harbor Laboratory

... circuits at single-neuron resolution. Sequencing technology has not previously been applied in the context of neural connectivity, but the sequencing approach has tremendous potential. The advantage of sequencing is that it is already fast—sequencing billions of nucleotides per day is now routine—an ...
Neurons - Holterman
Neurons - Holterman

... 4. The sodium-potassium pump pushes 3 Na and 2 K against their concentration gradients using 1 ATP. It restores and maintains the resting potential by pushing more Na out of neuron and pushing more K into neuron. (But overall, it pushes more positive charges out of the cell than it brings in.) 5. T ...
Difficult Vomiting Disorders: Therapy. In: Proceedings of the
Difficult Vomiting Disorders: Therapy. In: Proceedings of the

... Physiology of Emesis: The essential components of the emetic reflex are visceral receptors, vagal and sympathetic afferent neurons, a chemoreceptor trigger zone (CRTZ) located within the area postrema that is sensitive to blood-borne substances, and an emetic center within the reticular formation of ...
Theory of Mind: A Neural Prediction Problem
Theory of Mind: A Neural Prediction Problem

... (Meyer and Olson, 2011; Egner et al., 2010; de Gardelle et al., 2013). However, (as described in more detail below) signatures of the predictor neurons can also be observed; for example, the predictor neurons would likely show increased response when the input matches their predictions (e.g., de Gar ...
Carl L.Faingold, Manish Raisinghani, Prosper N`Gouemo
Carl L.Faingold, Manish Raisinghani, Prosper N`Gouemo

... responses of the inferior colliculus (IC) to acoustic stimulation, and defects in specific forms of inhibition are key causative factors in audiogenic seizure initiation. Line (A) illustrates binaural inhibition common in ICc neurons. In the poststimulus time histogram (PSTH) example in line (A) (“N ...
Computing with Spiking Neuron Networks
Computing with Spiking Neuron Networks

... distance k X −W k between the weights W and inputs X instead of the dot product, usually denoted by < X,W > (Figure 2). Remarkably, networks of such simple, connected computational elements can implement a wide range of mathematical functions relating input states to output states: With algorithms f ...
14.10 Insight 775 Gilbert
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 ...
On the choice of a sparse prior
On the choice of a sparse prior

... Willmore and Tolhurst 2001). Thus, sparse coding offers an approach that leads to simulated neurons with properties which compare well to those of real neurons. An important property of the ICA paradigm was demonstrated in a seminal contribution by Hyvärinen and Oja (1998). Given a known and finite ...
eref Saglroglu Intelligent Systems Research Group, Contra
eref Saglroglu Intelligent Systems Research Group, Contra

... reported. The following are examples found in the literature:- Integrating the visual data into the control process without calculating an inverse kinematic of a'manipulator [54]; Using two CMAC ANNs to learn the non-linear mapping between image data from a vision system and control signals to chang ...
Sparse Coding in the Neocortex
Sparse Coding in the Neocortex

... the alphabet. If we looked at the histogram of any given pixel, we might discover that the pixel was on roughly half the time. However, if we were to represent these letters with templates that respond uniquely to each letter, each template would respond just 1/26th of the time. This letter code is ...
A Taxonomy of Artificial Intelligence Approaches for Adaptive
A Taxonomy of Artificial Intelligence Approaches for Adaptive

... adaptive DRE systems support smart grids well because of (1) the distributed nature of disseminating power, (2) the timeliness requirements of addressing changes in the system, and (3) the embedded nature of a widely diverse system which precludes regular direct human control and intervention. This ...
Transfer Learning through Indirect Encoding - Eplex
Transfer Learning through Indirect Encoding - Eplex

... the agent also requests actions within the same BEV perspective. For example, to request a pass the agent can indicate its target by simply highlighting it on a two-dimensional output array. That way, instead of making decisions blind to the geometry of physical space, it can be taken into account. ...
prediction of india`s electricity demand using anfis
prediction of india`s electricity demand using anfis

... Artificial Neural Networks (ANNs) are computational models inspired by the architecture of human brain. The ANN is a tool of great importance in forecasting, classification and pattern recognition. The feed forward multilayer perceptron model with the back propagation techniques is the most popular ...
Memory fields of neurons in the primate prefrontal cortex
Memory fields of neurons in the primate prefrontal cortex

... where information. What-and-where neurons were able to simultaneously communicate the identity and location of a sample object throughout a large portion of the visual field at and near the fovea as well as in the periphery. The MFs of these neurons were similar in size and location to those of wher ...
New neurons retire early - The Gould Lab
New neurons retire early - The Gould Lab

... activation, and not just new neuron presence, in the hippocampus is critical for memory retrieval and enhanced synaptic plasticity. This study opens the door for the use of optogenetic techniques to confirm the influence of new neurons of different ages on other proposed functions, such as pattern s ...
Ch 15 Notes: The Autonomic Nervous System 2012
Ch 15 Notes: The Autonomic Nervous System 2012

... from the CNS and synapses in a ganglion with the second neuron. 2) the second neuron synapses on an effector. Preganglionic fibers release acetylcholine and postganglionic fibers release acetylcholine or norepinephrine. The output (efferent) part of the ANS is divided into two principal parts: the S ...
Relative sparing of primary auditory cortex in Williams Syndrome
Relative sparing of primary auditory cortex in Williams Syndrome

... a Sony GVM 1310 monitor that was connected to a Macintosh Centris 650 workstation. The 3-dimensional count box (95 Am  85 Am  20 Am) was placed within these images. A Heidenhain MP-25 photoelectric micrometer interfaced to a National Instrument NB-GPIB card in the Macintosh recorded movement in th ...
Relative sparing of primary auditory cortex in Williams Syndrome
Relative sparing of primary auditory cortex in Williams Syndrome

... a Sony GVM 1310 monitor that was connected to a Macintosh Centris 650 workstation. The 3-dimensional count box (95 Am  85 Am  20 Am) was placed within these images. A Heidenhain MP-25 photoelectric micrometer interfaced to a National Instrument NB-GPIB card in the Macintosh recorded movement in th ...
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Convolutional neural network

In machine learning, a convolutional neural network (CNN, or ConvNet) is a type of feed-forward artificial neural network where the individual neurons are tiled in such a way that they respond to overlapping regions in the visual field. Convolutional networks were inspired by biological processes and are variations of multilayer perceptrons which are designed to use minimal amounts of preprocessing. They are widely used models for image and video recognition.
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