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Learning to represent reward structure: A key to adapting to complex
Learning to represent reward structure: A key to adapting to complex

Chapter 5 Development
Chapter 5 Development

... • Reduces the number of functional synapses • Influenced by neutrophins and functionality of the synapse ...
From/To LTM - Ohio University
From/To LTM - Ohio University

... •One long-term memory (LTM) cell stores one particular sequence whose length determines the number of required PNs (Fig.3). Cells can be combined into hierarchy (Fig. 4). •Symbol neurons (SN) excite primary neurons (PN) through Win. S PN (t )  S SN (t )Win ...
Confidence-Related Decision Making
Confidence-Related Decision Making

... population, although it really represents confidence or a prediction that the decision just made will have a positive outcome. LC corresponds to a second decision to abort a trial and not wait for a possible reward, i.e., what they call the negative outcome population, although it really represents ...
Dynamic Stochastic Synapses as Computational Units
Dynamic Stochastic Synapses as Computational Units

Cerebellum: Movement Regulation and Cognitive Functions
Cerebellum: Movement Regulation and Cognitive Functions

... they transmit relatively specific error information to those PCs that are capable of reducing a particular movement error. As each PC is innervated by only a single climbing fibre, its training information can be quite specific. In contrast, recall that the PC receives more than 100 000 inputs conveyin ...
Development and function of human cerebral cortex neural networks
Development and function of human cerebral cortex neural networks

A Model of Distributed Sensorimotor Control in the Cockroach
A Model of Distributed Sensorimotor Control in the Cockroach

... ablation, the windfields of the vGIs on the ablated side are significantly reduced. Following the thirty day recovery period, however, these windfields are largely restored. We have also examined these effects in the model. After cercal ablation, the model vGI windfields show some similarities to th ...
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PDF

... layer of neurons, each representing a specific action. It learned stimulus-action pairs based on the prediction error signal provided by the critic. A winner-take-all rule that can be implemented through lateral inhibition between neurons ensured that only one action was selected at a given time. Us ...
Words in the Brain - Rice University -
Words in the Brain - Rice University -

... – something in there to compare them with forms entering the brain as it hears someone speaking – otherwise, how can an incoming word be recognized? ...
Structure-function relationship in hierarchical model of brain networks
Structure-function relationship in hierarchical model of brain networks

to receive a reprint - Institute for Learning and Brain Sciences
to receive a reprint - Institute for Learning and Brain Sciences

... Reading comprehension, like all complex cognitive tasks, is resource demanding. Hence, the efficiency with which an individual can encode, access, and represent the basic units (words) of a sentence is an important component of comprehension ability. According to the lexical quality hypothesis (e.g., ...
A simulation of parahippocampal and hippocampal structures guiding spatial navigation of
A simulation of parahippocampal and hippocampal structures guiding spatial navigation of

... maze, into the left arm, back to the stem, up into the right arm and back to the original starting position in the stem. This represents the stage of initial exploration necessary to obtain effective behavior by any rat in a spatial environment. The first problem arises because there is a fundamenta ...
Cortical and basal ganglia contributions to habit learning and
Cortical and basal ganglia contributions to habit learning and

... has received significantly more training than is required for accuracy and speed to asymptote. Although this criterion is commonly used, other more formal tests have been proposed. In cognitive science, the most widely used criteria come from Schneider and Shiffrin [83], who proposed that a behavior ...
Acquired Equivalence and Distinctiveness of Cues: I. Exploring a
Acquired Equivalence and Distinctiveness of Cues: I. Exploring a

... which the pattern of links (arrows) depicted in Figure 1 is established will be described together with the rationale for Experiment 2. The suggestion that the links to the hidden units have been tuned in the way described receives support from the consequences of a subsequent revaluation procedure ...
An architectural model of conscious and unconscious brain
An architectural model of conscious and unconscious brain

... A theatre metaphor for GWT is a useful first approximation. Unconscious processors in the theatre audience receive broadcasts from a conscious “bright spot” on the stage. Control of the bright spot corresponds to selective attention. Backstage, unconscious contextual systems operate to shape and dir ...
Creating Buzz: The Neural Correlates of Effective Message
Creating Buzz: The Neural Correlates of Effective Message

... structural scan. The MPRAGE data were normalized into standard stereotactic space (Montreal Neurological Institute, or MNI, space), and these parameters were applied to the functional data. The resulting images were smoothed with an 8-mm Gaussian kernel, full width at half maximum. Individual behavi ...
Biomechanics Models Motor Cortex Using Spinal Cord and Limb
Biomechanics Models Motor Cortex Using Spinal Cord and Limb

... of optimal control (Chow and Jacobson 1971; Engelbrecht 2001; Pandy 2001), which proposes that the system operates by optimizing a given cost function under the appropriate constraints. A second possible approach is to simply postulate an empirical redundancy resolution rule, verifying that it indee ...
How cognitive theory guides neuroscience
How cognitive theory guides neuroscience

... Indeed, in tasks that require storing some information in WM and ignoring irrelevant distractors, subjects learn to attend to the relevant information in such a way that accords with reinforcement learn ...
Tsodyks-Banbury-2006
Tsodyks-Banbury-2006

... (Synfire chains? – I don’t like it!) What is the relation between the spike patterns and the stimuli that they are coding for? How can the information carried by spike patterns be processed? ...
Module 4 SG - HallquistCPHS.com
Module 4 SG - HallquistCPHS.com

... 10. An action potential occurs when the first part of ...
Neural Induction in Xenopus: Requirement for Ectodermal and
Neural Induction in Xenopus: Requirement for Ectodermal and

... suggested that a cell-autonomous requirement of Chd for neural plate formation might exist in the ectoderm itself. At the blastula stage, the BMP antagonists Chd and Nog are expressed in the dorsal animal cap and marginal zone, in a region we had originally designated as the ‘‘preorganizer center’’ ...
Developmental origin of shark electrosensory organs
Developmental origin of shark electrosensory organs

... participate in mechanoreceptor development in at least two osteichthyans (Collazo et al. 1994), we hypothesized that electroreceptors also may have a dual embryonic origin in the neural crest and epidermal placodes. We tested this hypothesis by examining the neural crest contribution during developm ...
The Involvement of Recurrent Connections in Area CA3 in
The Involvement of Recurrent Connections in Area CA3 in

... and ␴ are in units such that the shorter side of the rectangular environment used in most simulations is of unit length. ␶ and ␶⬘ are given in time steps used during simulations of recall, and all other quantities are in their natural units. Note that, because the parameters only appear in certain c ...
CNS*2004 July 18-22, 2004 Baltimore, Maryland
CNS*2004 July 18-22, 2004 Baltimore, Maryland

... Baltimre’s Inner Harbor from Sunday, July 18th to Tuesday, July 20th. Workshops will take place in the hotel as well in smaller meeting rooms equipped with audio visual equipment from Thursday, July 22nd to Friday July 23rd. Maps of the Inner Harbor and surrounding areas are included on the followin ...
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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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