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LT2Ch7
LT2Ch7

... Red vs green light. ...
Document
Document

... The main property of a neural network is an ability to learn from its environment, and to improve its performance through learning. So far we have considered supervised or active learning - learning with an external “teacher” or a supervisor who presents a training set to the network. But another ty ...
PDF (2_RMC_CH1_Introduction)
PDF (2_RMC_CH1_Introduction)

... and trace conditioning. We reasoned that if trace conditioning depended on high level mental resources, such as working memory, then having subjects perform a working memory task during conditioning would eliminate trace conditioning, leaving delay unaffected. Instead, we discovered that the working ...
$doc.title

... striatum, while including initial performance as covariates in the model. No correlation was found between striatum volumes and initial total scores in both groups, suggesting that initial performance of the task was not correlated with striatum volumes. However, striatum volumes significantly predi ...
Neural-Symbolic Learning and Reasoning: Contributions and
Neural-Symbolic Learning and Reasoning: Contributions and

... d'Avila Garcez, Lamb, and Gabbay (2009) for an overview). Meanwhile, there has been some suggestive recent work showing that neural networks can learn entire sequences of actions, thus amounting to "mental simulation" of some concrete, temporally extended activity. There is also a very well develope ...
14 Reinforcement Learning, High-Level Cognition, and the Human
14 Reinforcement Learning, High-Level Cognition, and the Human

... system and cognitive processes, providing what was called a sub-symbolic explanation of cognition. This new field was inspired by the fast developing neurosciences; in particular, the scientists developing this new branch not only did not adhere to the dogma that theorizing should remain at the beha ...
The Binding Problem
The Binding Problem

... identify the members of a representation as belonging together and to distinguish them from other representations that may be present at the same time. What internal dynamic structure of a cell assembly would distinguish it from all other neuronal activity present simultaneously in the cortical netw ...
LTNov12
LTNov12

... Red vs green light. ...
KleinCh4
KleinCh4

... The UCS occurs at regular intervals in time. Nominally, no CS is present, but aspects of the context in which the UCS occurs become conditioned to it. ...
Chap3aAlt
Chap3aAlt

... The stronger the US (UCS), the faster the learning and the stronger the association. The stronger the CS, the better the learning. ...
A coincidence detector neural network model of selective attention
A coincidence detector neural network model of selective attention

... More recently, Lavie (1995) provided results showing that selection may be early or late depending on task characteristics. In one of Lavie’s studies participants were asked to determine whether a presented stimulus was the letter x or the letter z. In one condition, termed the highload, the letter ...
MusNmind - University of Kentucky
MusNmind - University of Kentucky

...  Belongingness – a sensory element belongs to an organization (or stream) of which is a part.  Exclusive allocation – a sensory element cannot belong to more than one organization at a time.  Bregman & Rudnicky (1975) ...
A bio-inspired learning signal for the cumulative learning - laral
A bio-inspired learning signal for the cumulative learning - laral

... What we propose in this paper is that providing artificial agents with a learning signal that resembles the characteristic of the phasic DA signal, determined both by intrinsic and extrinsic reinforcements, would be an advancement in the development of more autonomous and versatile systems. In parti ...
Perception of English Vowel Reduction by Trained Spanish Learners
Perception of English Vowel Reduction by Trained Spanish Learners

... analysis of the students’ productions of vowel reduction will answer the remaining question of whether perceptual training actively contributes to developing students’ production abilities. The present study also revealed that the improvement in perception carried over to a non-instructed more chall ...
RL 19 - School of Informatics
RL 19 - School of Informatics

... sensitive to a characteristic dynamic response of the critic neurons, which encoding change in stimulus sensitive to a global signal representing the reward. bonus lecutre in 2015 Michael Herrmann RL 19 ...
Artificial Neural Networks
Artificial Neural Networks

... – The first layer is the input and the last layer is the output. – If there is more than one hidden layer, we call them “deep” neural networks. They compute a series of transformations that change the similarities between cases. – The activities of the neurons in each layer are a non-linear function ...
Workshop program booklet
Workshop program booklet

... has to solve, and propose an answer: how the nervous system ”should” optimally solve this problem given its limited amount of neural resources. Such a principled framework seems particularly important for understanding complex systems, where pure descriptive models often cannot provide satisfying an ...
Introduction to Programming - Villanova Computer Science
Introduction to Programming - Villanova Computer Science

... Reminder: logistic regression can do non-linear ...
Low vision and brain plasticity Symposium abstract
Low vision and brain plasticity Symposium abstract

... Symposium abstract In the past decade numerous studies have crossed the traditional boundaries between a ‘peripheral’ and ‘central’ visual system. There is growing evidence that ocular diseases may have cerebral consequences and that consequences of neurological diseases may be seen at the ocular/re ...
Biology
Biology

... •  To understand a new style of computation •  Inspired by neurons and their adaptive connections •  Very different style from sequential computation •  should be good for things that brains are good at (e.g. vision) •  Should be bad for things that brains are bad at (e.g. 23 x 71) ...
2) Classical Conditioning
2) Classical Conditioning

... two stimuli). To set up discrimination in the laboratory, a researcher creates a situation in which the two stimuli predict different things. For example, if a bell tone were the conditioned stimulus, discrimination would involve being able to tell the difference between the bell tone and other simi ...
What drives the plasticity of brain tissues?
What drives the plasticity of brain tissues?

... hypertrophy-correlated astroglial changes in the hippocampal formation appear to be dissociated from the experience-correlated visual cortex changes in complex environment research (Sirevaag et al., 1991). ...
Unsupervised Learning
Unsupervised Learning

... The main property of a neural network is an ability to learn from its environment, and to improve its performance through learning. So far we have considered supervised or active learning - learning with an external “teacher” or a supervisor who presents a training set to the network. But another ty ...
Altmann, L. Wiseheart R, Altmann LJ, Park H, Lombardino LJ.
Altmann, L. Wiseheart R, Altmann LJ, Park H, Lombardino LJ.

... extemporaneous utterances when sober and at three highly controlled levels of intoxication. Listener groups of university students and professionals attempted to identify both the existence and specific level of intoxication present. It was found that these individuals were proficient in recognizing ...
Reinforcement learning in populations of spiking neurons
Reinforcement learning in populations of spiking neurons

... feedback about the population response modulates synaptic plasticity. The role of neuronal populations in encoding sensory stimuli has been intensively studied1,2. However, most models of reinforcement learning with spiking neurons have focused on just single neurons or small neuronal assemblies3–6. ...
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Perceptual learning

Perceptual learning is the process of learning improved skills of perception. These improvements range from simple sensory discriminations (e.g., distinguishing two musical tones from one another) to complex categorizations of spatial and temporal patterns relevant to real-world expertise (e.g., reading, seeing relations among chess pieces, knowing whether or not an X-ray image shows a tumor). Sensory modalities may include visual, auditory, tactile, olfactory, and taste. Perceptual learning forms important foundations of complex cognitive processes (i.e., language) and interacts with other kinds of learning to produce perceptual expertise. Underlying perceptual learning are changes in the neural circuitry. The ability for perceptual learning is retained throughout life.
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