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Leech Heart CPG
Leech Heart CPG

... Due to their reciprocally inhibitory synapses the pair of HN(3) neurons can produce oscillations (Fig 4, B). This is the smallest group of cells that can produce oscillations and hence are called the elemental oscillator (Fig 4, C). The HN(4) neurons are also considered as an elemental or half-cente ...
The Composition Effect: Conjunctive or Compensatory?
The Composition Effect: Conjunctive or Compensatory?

... approximated very well by the AND gate + guess/slip. While cognitive modelers may be interested in the slight compensatory effect seen in Table 3, ITS developers can have confidence in using an AND assumption for accurate assessment when dealing with multi skill items. ...
- Wiley Online Library
- Wiley Online Library

... rats prenatally treated with poly(I:C) and mice prenatally treated with IL-6, however, to date, are unreported in prenatal LPS models (Zuckerman et al., 2003a; Zuckerman and Weiner, 2003; Meyer et al., 2006a; Smith et al., 2007). Recently, alterations in attentional set shifting, indicative of perse ...
Intelligent Information Retrieval and Web Search
Intelligent Information Retrieval and Web Search

here
here

... that I am aware of can handle this, at least not in full generality. Logic in general starts with a fixed syntax—it can’t be changed on the fly. Of course, in first-order logic, we can always add relation symbols to a vocabulary. In the same way, we can add new modal operators to modal logic. I’m not s ...
*αí  *ß>*   *p  "*  " G6*ç"ê"ë"è"ï"î"ì"Ä"Å"É"æ"Æ"ô"ö"ò"û"ù"ÿ"Ö"Ü
*αí *ß>* *p "* " G6*ç"ê"ë"è"ï"î"ì"Ä"Å"É"æ"Æ"ô"ö"ò"û"ù"ÿ"Ö"Ü

... system. It is connected via three different CORBA interfaces with the remaining sensory and actoric tasks. Two of these are sensory input interfaces [Kaufmann et al. 2005, Knoblauch et al. 2004]. The first one supplies the entered sentence (e.g. "bot show orange") and the second recognizes objects i ...
CCNBook/Neuron
CCNBook/Neuron

Getting to Know You: Reputation and Trust in a Two
Getting to Know You: Reputation and Trust in a Two

... To probe neural substrates of social interactions, we scan the brains of multiple subjects engaged in a social interaction. Social decision-making critically depends on internally represented models of social partners. In principle, such covert knowledge might be inferred from behavioral observation ...
neuronal coding of prediction errors
neuronal coding of prediction errors

Negatively-Correlated Firing - Department of Computer Science
Negatively-Correlated Firing - Department of Computer Science

Algorithmic Specified Complexity in the Game of Life
Algorithmic Specified Complexity in the Game of Life

... probability of a pattern arising directly from some sort of random pattern generator. However, once the Game of Life rules are applied, determining what patterns would arise from the initial random patterns is nontrivial. In order to approximate the probabilities, we will assume that the probability ...
The non-motor complications in Parkinson`s disease
The non-motor complications in Parkinson`s disease

Basal Ganglia - Adaptive Behaviour Research Group
Basal Ganglia - Adaptive Behaviour Research Group

... to both of these structures originate from virtually the entire brain including, cerebral cortex, many parts of the brainstem (via the thalamus), and the limbic system. Input connections provide phasic (intermittent) excitatory input. The main output nuclei of the basal ganglia are the substantia ni ...
Predictive Coding as a Model of Biased Competition in Visual
Predictive Coding as a Model of Biased Competition in Visual

... ySi ← (1 − η − ϑ)ySi + ζWSi eSi + η WSi+1 ySi+1 + WSz ySz + . . . Where the term in square brackets is simply the sum of the feedback received from each separate source of top3 ...
Anticipated synchronization in neuronal circuits
Anticipated synchronization in neuronal circuits

... maps are discrete, the dimensionality of the problem remains finite, whereas ordinary differential equations with finite time delays mathematically constitute an infinite-dimensional system. Depending on the parameters, the maps may present AS or delayed synchronization (the usual retarded or lag sy ...
Unsupervised Learning of Cell Activities in the Associative Cortex of Behaving Monkeys, Using HMM
Unsupervised Learning of Cell Activities in the Associative Cortex of Behaving Monkeys, Using HMM

Self-referential forces are sufficient to explain different dendritic
Self-referential forces are sufficient to explain different dendritic

... An interpretation thereof is that a single dendritic morphology is the result of interactions with the environment in which it grew. These interactions are de facto not in the reconstructed data, which is a snapshot of one of their possible outcomes. Experimental evidence backs this interpretation a ...
November 2008_Neural_Computing_Systems.SupervisedBackProp
November 2008_Neural_Computing_Systems.SupervisedBackProp

Synaptic plasticity: taming the beast
Synaptic plasticity: taming the beast

... small differences between pre- and postsynaptic spike times, and no plasticity is induced if this difference grows too large. In some cases, the sign of the time difference (that is, whether the presynaptic spike precedes or follows the postsynaptic spike) determines whether the protocol induces LTP ...
A Model of Prefrontal Cortical Mechanisms for Goal-directed Behavior Michael E. Hasselmo Abstract
A Model of Prefrontal Cortical Mechanisms for Goal-directed Behavior Michael E. Hasselmo Abstract

PhD Thesis in Cognitive Science
PhD Thesis in Cognitive Science

... closely in our research team and whose comments were invaluable in some of the papers. I cannot forget to thank Kajsa Nalin who helped me in practical issues during my initial time and acted as a mentor. I am also grateful to all other colleagues at the division of cognition and communication, inclu ...
Wiring optimization can relate neuronal structure and function
Wiring optimization can relate neuronal structure and function

... which, with a few exceptions, does not make synapses with other neurons or muscles. Thus each sensory fixed point, by construction, connects to a neuron through a dedicated wire and needs not be normalized. An alternative way to incorporate this neuronal morphology is by using a ‘‘shared-wire’’ mode ...
Vestibular Signals of Posterior Parietal Cortex Neurons during
Vestibular Signals of Posterior Parietal Cortex Neurons during

... about and control and correct our own movements. Recent studies on vestibular nuclei neurons during passive and active head movements showed that vestibular signals were strongly influenced by self-generated movements as early as the first vestibular projection neurons,2–4 and furthermore neurons in ...
Reward and punishment act as distinct factors in guiding behavior
Reward and punishment act as distinct factors in guiding behavior

A Layered Dynamic Emotion Representation for the Creation of
A Layered Dynamic Emotion Representation for the Creation of

... corresponding E.S. occurs but only if the intensity of this emotion is currently the highest. Otherwise, higher intensities of opposing emotions, such as Anger for Happiness, have their normal decay accelerated. The mood state is described by two variables: Energy and Tension [7] (see Fig. 2). These ...
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Neural modeling fields

Neural modeling field (NMF) is a mathematical framework for machine learning which combines ideas from neural networks, fuzzy logic, and model based recognition. It has also been referred to as modeling fields, modeling fields theory (MFT), Maximum likelihood artificial neural networks (MLANS).This framework has been developed by Leonid Perlovsky at the AFRL. NMF is interpreted as a mathematical description of mind’s mechanisms, including concepts, emotions, instincts, imagination, thinking, and understanding. NMF is a multi-level, hetero-hierarchical system. At each level in NMF there are concept-models encapsulating the knowledge; they generate so-called top-down signals, interacting with input, bottom-up signals. These interactions are governed by dynamic equations, which drive concept-model learning, adaptation, and formation of new concept-models for better correspondence to the input, bottom-up signals.
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