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Narrow versus wide tuning curves: What`s best for a population code?
Narrow versus wide tuning curves: What`s best for a population code?

neural basis of deciding, choosing and acting
neural basis of deciding, choosing and acting

... understanding of how the brain makes decisions and generates actions. This review will emphasize findings obtained in experiments in which the activity of individual neurons was monitored in specific parts of the ...
The Octopus as a Possible Model for Invertebrate Consciousness
The Octopus as a Possible Model for Invertebrate Consciousness

... Mobility meant exploitation of far-flung food sources and, eventually, predatory strategies. This led to an “arms race” between predator and prey species in terms of innovations like faster (and more efficient) locomotion, armor, peptide mimicry of neuromodulatory signals, and other defenses, as wel ...
Connectionist AI, symbolic AI, and the brain
Connectionist AI, symbolic AI, and the brain

PDF file
PDF file

... the binocular stimuli with a specific disparity are matched with binocular neurons in the form of neuronal responses. Different neurons have developed different preferred patterns of weights, each pattern indicating the spatial pattern of the left and right receptive fields. Thus, the response of a ...
KKDP 3: The role of the neuron (dendrites, axon, myelin and
KKDP 3: The role of the neuron (dendrites, axon, myelin and

Combinatorial structures and processing in Neural Blackboard
Combinatorial structures and processing in Neural Blackboard

... are not only associative neural structures. They also incorporate relations, as illustrated with the relations is pet and has paw in Figure 1. The assembly or web-like structure of a concept representation entails that concepts representations are ‘in situ’ [4]. That is, wherever a concept is activa ...
PDF
PDF

... learn to predict their fate in those cases in which they cannot actually influence it. Indeed, although RL is primarily concerned with situations in which action selection is germane, such predictions play a major role in assessing the effects of different actions, and thereby in optimizing policies ...
Towards the integration of neural mechanisms and cognition in
Towards the integration of neural mechanisms and cognition in

... neural circuits and the robot; it is the control interface and it implements how the neural activity is translated in actuation. The Neural lattice layer is the brain model and it is fairly composed by at least two sublayers: the neural circuits and the cognition. The neural circuits layer contains ...
High-speed CCD movie camera with random pixel selection,
High-speed CCD movie camera with random pixel selection,

... Laser-scanning systems for voltage-sensitive dye recording have been developed by two groups (Morad et al., 1986; Saggau, 1994). These employ acousto-optic deflectors to rapidly steer a laser excitation spot to user- selectable regions in the specimen. Fluorescence is detected by a single photodiode ...
Karuza, E. A., Newport, E. L., Aslin, R. N., Starling, S. J., Tivarus
Karuza, E. A., Newport, E. L., Aslin, R. N., Starling, S. J., Tivarus

... be paired with a color cue indicating the type of stream being presented. The ‘‘languages’’ consisted of continuous streams of (1) forward speech, (2) backward speech formed by playing the recording of the forward speech stream in reverse, and (3) overlaid speech formed by layering three copies of t ...
Learning sensory maps with real-world stimuli in real time using a
Learning sensory maps with real-world stimuli in real time using a

1 Neural Affective Decision Theory: Choices, Brains, and Emotions
1 Neural Affective Decision Theory: Choices, Brains, and Emotions

... extensive connections with sensory processing areas of the brain. Several recent studies have indicated an important role for orbitofrontal neurons in providing a sort of “common neural currency” (Montague & Berns, 2002) which allows for the evaluation and comparison of figurative (or even literal) ...
Cognitive Architectures: Where do we go from here?
Cognitive Architectures: Where do we go from here?

... and direct reasoning [24]. SOAR architecture has demonstrated a variety of high-level cognitive functions, processing large and complex rule sets in planning, problem solving and natural language comprehension (NL-SOAR) in real-time distributed environments (see [25] for more references). At present ...
Building silicon nervous systems with dendritic tree neuromorphs
Building silicon nervous systems with dendritic tree neuromorphs

A Point Process Model for Auditory Neurons Considering
A Point Process Model for Auditory Neurons Considering

Neural tissue responsiveness to FGF and RA controlled by Cdx
Neural tissue responsiveness to FGF and RA controlled by Cdx

... vertebrate posterior hindbrain, where the spinal cord meets the tail end of the brain. They function in a broad range of other developmental processes as well, indicating that the ability to respond to these signals must be closely linked to the site of activity, and regulated accordingly. The brain ...
Unsupervised feature learning from finite data by
Unsupervised feature learning from finite data by

... Bayesian learning performance of the Hopfield model is shown in Fig. 3. This model does not show an entropy crisis in the explored range of α. As α increases, the entropy decreases much more slowly for weak features than for strong ones. For β = 0.5, the overlap stays slightly above zero for a wide ...
Role of Inhibitory Neurotransmitter Interactions in the Pathogenesis
Role of Inhibitory Neurotransmitter Interactions in the Pathogenesis

... GABA-containing neuronal cell bodies, dendrites, and axonal terminals are parvalbumenimmunoreactive.10 Hence, parvalbumen expression can be used to define the organization of GABAergic inhibitory circuits in the brain.11 Colocalization studies revealed that hypercapnia significantly increased c-Fos ...
Difficult Vomiting Disorders: Therapy. In: Proceedings of the
Difficult Vomiting Disorders: Therapy. In: Proceedings of the

... that vomiting occurs either through activation of the CRTZ by blood-borne substances (humoral pathway), or through activation of the emetic center by vago-sympathetic, CRTZ, vestibular, or cerebrocortical neurons (neural pathway). Thus, activation of the CRTZ by a variety of humoral emetogenic subst ...
Chapter 40 Neural Regulation
Chapter 40 Neural Regulation

The honeybee as a model for understanding the basis of cognition
The honeybee as a model for understanding the basis of cognition

... lead to richer crosstalk between sensory inputs and more centralized processing of higher order functions in the honeybee. The digital three-dimensional standard atlas of the bee brain (BOX 1) provides a useful reference for identify­ing and classifying neurons, as well as for determining their cont ...
Computation with Spikes in a Winner-Take-All Network
Computation with Spikes in a Winner-Take-All Network

... For stationary Poisson-distributed input spikes, we first consider a network of two neurons, labeled 0 and 1, with the connectivity shown in Figure 3. Because of the Poisson statistics of the inputs, the probability of selecting the correct winner depends on the ratio of their input Poisson rates ν a ...
Computational Psychiatry Seminar: Spring 2014 Week 11: The
Computational Psychiatry Seminar: Spring 2014 Week 11: The

... -First, keep in memory which action was taken at which state in the form of ‘eligibility traces’, and when a reward is given, reinforce the state-action associations in proportion to the eligibility traces. -Second, use so-called temporal difference learning (sampling the environment). In the case o ...
PDF - Center for Neural Science
PDF - Center for Neural Science

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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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