scholarly journals Dynamic salience processing in paraventricular thalamus gates associative learning

Science ◽  
2018 ◽  
Vol 362 (6413) ◽  
pp. 423-429 ◽  
Author(s):  
Yingjie Zhu ◽  
Gregory Nachtrab ◽  
Piper C. Keyes ◽  
William E. Allen ◽  
Liqun Luo ◽  
...  
Keyword(s):  
Associative Learning ◽  
Internal State ◽  
Environment Monitoring ◽  
Behavioral Context ◽  
Effective Learning ◽  
Dynamic Representation ◽  
Stimulus Salience ◽  
Flexible Behavior ◽  
Paraventricular Thalamus ◽  
Reinforcing Stimuli

The salience of behaviorally relevant stimuli is dynamic and influenced by internal state and external environment. Monitoring such changes is critical for effective learning and flexible behavior, but the neuronal substrate for tracking the dynamics of stimulus salience is obscure. We found that neurons in the paraventricular thalamus (PVT) are robustly activated by a variety of behaviorally relevant events, including novel (“unfamiliar”) stimuli, reinforcing stimuli and their predicting cues, as well as omission of the expected reward. PVT responses are scaled with stimulus intensity and modulated by changes in homeostatic state or behavioral context. Inhibition of the PVT responses suppresses appetitive or aversive associative learning and reward extinction. Our findings demonstrate that the PVT gates associative learning by providing a dynamic representation of stimulus salience.

Neural Activity in Primate Caudate Nucleus Associated With Pro- and Antisaccades

2009 ◽  
Vol 102 (4) ◽  
pp. 2334-2341 ◽  
Author(s):  
Kristen A. Ford ◽  
Stefan Everling
Keyword(s):  
Caudate Nucleus ◽  
Discharge Rate ◽  
Indirect Pathway ◽  
Behavioral Context ◽  
Firing Rates ◽  
Neuronal Populations ◽  
Input Structure ◽  
Flexible Behavior ◽  
Two Populations

The basal ganglia (BG) play a central role in movement and it has been demonstrated that the discharge rate of neurons in these structures are modulated by the behavioral context of a given task. Here we used the antisaccade task, in which a saccade toward a flashed visual stimulus must be inhibited in favor of a saccade to the opposite location, to investigate the role of the caudate nucleus, a major input structure of the BG, in flexible behavior. In this study, we recorded extracellular neuronal activity while monkeys performed pro- and antisaccade trials. We identified two populations of neurons: those that preferred contralateral saccades (CSNs) and those that preferred ipsilateral saccades (ISNs). CSNs increased their firing rates for prosaccades, but not for antisaccades, and ISNs increased their firing rates for antisaccades, but not for prosaccades. We propose a model in which CSNs project to the direct BG pathway, facilitating saccades, and ISNs project to the indirect pathway, suppressing saccades. This model suggests one possible mechanism by which these neuronal populations could be modulating activity in the superior colliculus.

Differential Neuroethological Effects of Aversive and Appetitive Reinforcing Stimuli on Associative Learning in Lymnaea stagnalis

1996 ◽  
Vol 13 (6) ◽  
pp. 803-812 ◽  
Author(s):  
Satoshi Kojima ◽  
Mari Yamanaka ◽  
Yutaka Fujito ◽  
Etsuro Ito
Keyword(s):  
Associative Learning ◽  
Lymnaea Stagnalis ◽  
Reinforcing Stimuli

A Cortical Network Sensitive to Stimulus Salience in a Neutral Behavioral Context Across Multiple Sensory Modalities

2002 ◽  
Vol 87 (1) ◽  
pp. 615-620 ◽  
Author(s):  
Jonathan Downar ◽  
Adrian P. Crawley ◽  
David J. Mikulis ◽  
Karen D. Davis
Keyword(s):  
Response Selection ◽  
Inferior Frontal Gyrus ◽  
Superior Temporal Gyrus ◽  
Brain Regions ◽  
Anterior Cingulate ◽  
Behavioral Context ◽  
General Role ◽  
Sensory Stimuli ◽  
Tactile Stimuli ◽  
Stimulus Salience

Stimulus salience depends both on behavioral context and on other factors such as novelty and frequency of occurrence. The temporo-parietal junction (TPJ) responds preferentially to behaviorally relevant stimuli and is thought to play a general role in detecting salient stimuli. If so, it should respond preferentially to novel or infrequent events, even in a neutral behavioral context. To test this hypothesis, we used event-related functional magnetic resonance imaging (fMRI) to identify brain regions sensitive to the novelty of visual, auditory, and tactile stimuli during passive observation. Cortical regions with a greater response to novel than familiar stimuli across all modalities were identified at two sites in the TPJ region: the supramarginal gyrus (SMG) and superior temporal gyrus. The right inferior frontal gyrus (IFG), right anterior insula, left anterior cingulate cortex (ACC), and left inferior temporal gyrus also showed sensitivity to novelty. The novelty-sensitive TPJ activation in SMG overlaps a region previously identified as sensitive behavioral context. This region may play a general role in identifying salient stimuli, whether the salience is due to the current behavioral context or not. The IFG activation overlaps regions previously identified as responsive to nonnovel sensory events regardless of behavioral context. The IFG may therefore play a general role in stimulus evaluation rather than a specific role in identifying novel stimuli. The ACC activation lies in a region active during complex response-selection tasks, suggesting a general role in detecting and/or planning responses to salient events. A frontal-parietal-cingulate network may serve to identify and evaluate salient sensory stimuli in general.

scholarly journals Design and Implementation of an EEG-Based Learning-Style Recognition Mechanism

2021 ◽  
Vol 11 (5) ◽  
pp. 613
Author(s):  
Bingxue Zhang ◽  
Chengliang Chai ◽  
Zhong Yin ◽  
Yang Shi
Keyword(s):  
Learning Styles ◽  
Learning Style ◽  
Recognition Accuracy ◽  
Internal State ◽  
Eeg Signals ◽  
Recognition Mechanism ◽  
Effective Learning ◽  
Design And Implementation ◽  
Actual Learning ◽  
Eeg Features

Existing methods for learning-style recognition are highly subjective and difficult to implement. Therefore, the present study aimed to develop a learning-style recognition mechanism based on EEG features. The process for the mechanism included labeling learners’ actual learning styles, designing a method to effectively stimulate different learners’ internal state differences regarding learning styles, designing the data-collection method, designing the preprocessing procedure, and constructing the recognition model. In this way, we designed and verified an experimental method that can effectively stimulate learning-style differences in the information-processing dimension. In addition, we verified the effectiveness of using EEG signals to recognize learning style. The recognition accuracy of the learning-style processing dimension was 71.2%. This result is highly significant for the further exploration of using EEG signals for effective learning-style recognition.

scholarly journals Dorsal Raphe Dopamine Neurons Signal Motivational Salience Dependent on Internal State, Expectation, and Behavioral Context

2021 ◽  
Vol 41 (12) ◽  
pp. 2645-2655
Author(s):  
Jounhong Ryan Cho ◽  
Xinhong Chen ◽  
Anat Kahan ◽  
J. Elliott Robinson ◽  
Daniel A. Wagenaar ◽  
...  
Keyword(s):  
Internal State ◽  
Dorsal Raphe ◽  
Dopamine Neurons ◽  
Behavioral Context ◽  
State Expectation ◽  
Motivational Salience ◽  
Dorsal Raphé

scholarly journals Amygdalo-striatal interaction in the enhancement of stimulus salience in associative learning.

2015 ◽  
Vol 129 (2) ◽  
pp. 87-95 ◽  
Author(s):  
Guillem R. Esber ◽  
Karina Torres-Tristani ◽  
Peter C. Holland
Keyword(s):  
Associative Learning ◽  
Stimulus Salience

scholarly journals Reconciling the influence of predictiveness and uncertainty on stimulus salience: a model of attention in associative learning

2011 ◽  
Vol 278 (1718) ◽  
pp. 2553-2561 ◽  
Author(s):  
Guillem R. Esber ◽  
Mark Haselgrove
Keyword(s):  
Selective Attention ◽  
Associative Learning ◽  
Neural Circuits ◽  
Attentional Model ◽  
Stimulus Salience ◽  
Cue Salience ◽  
Attentional Theory ◽  
Attentional Models ◽  
High Uncertainty

Theories of selective attention in associative learning posit that the salience of a cue will be high if the cue is the best available predictor of reinforcement (high predictiveness). In contrast, a different class of attentional theory stipulates that the salience of a cue will be high if the cue is an inaccurate predictor of reinforcement (high uncertainty). Evidence in support of these seemingly contradictory propositions has led to: (i) the development of hybrid attentional models that assume the coexistence of separate, predictiveness-driven and uncertainty-driven mechanisms of changes in cue salience; and (ii) a surge of interest in identifying the neural circuits underpinning these mechanisms. Here, we put forward a formal attentional model of learning that reconciles the roles of predictiveness and uncertainty in salience modification. The issues discussed are relevant to psychologists, behavioural neuroscientists and neuroeconomists investigating the roles of predictiveness and uncertainty in behaviour.

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