scholarly journals Time in Associative Learning: A Review on Temporal Maps

2021 ◽  
Vol 15 ◽  
Author(s):  
Midhula Chandran ◽  
Anna Thorwart
Keyword(s):  
Associative Learning ◽  
Behavioral Interventions ◽  
Temporal Coding ◽  
Common Element ◽  
Missing Information ◽  
Behavioral Outcome ◽  
Integration Mechanism ◽  
Temporal Aspect ◽  
Temporal Learning

Ability to recall the timing of events is a crucial aspect of associative learning. Yet, traditional theories of associative learning have often overlooked the role of time in learning association and shaping the behavioral outcome. They address temporal learning as an independent and parallel process. Temporal Coding Hypothesis is an attempt to bringing together the associative and non-associative aspects of learning. This account proposes temporal maps, a representation that encodes several aspects of a learned association, but attach considerable importance to the temporal aspect. A temporal map helps an agent to make inferences about missing information by applying an integration mechanism over a common element present in independently acquired temporal maps. We review the empirical evidence demonstrating the construct of temporal maps and discuss the importance of this concept in clinical and behavioral interventions.

The Role of Repetition in Associative Learning

1963 ◽  
Vol 76 (1) ◽  
pp. 148
Author(s):  
James H. Straughan
Keyword(s):  
Associative Learning

scholarly journals GluA1 Phosphorylation Alters Evoked Firing PatternIn Vivo

2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
Balázs Barkóczi ◽  
Gábor Juhász ◽  
Robert G. Averkin ◽  
Imre Vörös ◽  
Petra Vertes ◽  
...  
Keyword(s):  
Synaptic Plasticity ◽  
Spike Trains ◽  
Temporal Coding ◽  
Relative Contribution ◽  
Ampa Receptor Subunit ◽  
Ampa And Nmda Receptors ◽  
Characteristic Features ◽  
Evoked Activity

AMPA and NMDA receptors convey fast synaptic transmission in the CNS. Their relative contribution to synaptic output and phosphorylation state regulate synaptic plasticity. The AMPA receptor subunit GluA1 is central in synaptic plasticity. Phosphorylation of GluA1 regulates channel properties and trafficking. The firing rate averaged over several hundred ms is used to monitor cellular input. However, plasticity requires the timing of spiking within a few ms; therefore, it is important to understand how phosphorylation governs these events. Here, we investigate whether the GluA1 phosphorylation (p-GluA1) alters the spiking patterns of CA1 cellsin vivo. The antidepressant Tianeptine was used for inducing p-GluA1, which resulted in enhanced AMPA-evoked spiking. By comparing the spiking patterns of AMPA-evoked activity with matched firing rates, we show that the spike-trains after Tianeptine application show characteristic features, distinguishing from spike-trains triggered by strong AMPA stimulation. The interspike-interval distributions are different between the two groups, suggesting that neuronal output may differ when new inputs are activated compared to increasing the gain of previously activated receptors. Furthermore, we also show that NMDA evokes spiking with different patterns to AMPA spike-trains. These results support the role of the modulation of NMDAR/AMPAR ratio and p-GluA1 in plasticity and temporal coding.

scholarly journals Role of Prefrontal and Parietal Cortices in Associative Learning

2007 ◽  
Vol 18 (4) ◽  
pp. 904-914 ◽  
Author(s):  
J. R. Anderson ◽  
D. Byrne ◽  
J. M. Fincham ◽  
P. Gunn
Keyword(s):  
Associative Learning ◽  
Parietal Cortices

Toward heterogeneity in feedforward network with synaptic delays based on FitzHugh–Nagumo model

2018 ◽  
Vol 32 (01) ◽  
pp. 1750274 ◽  
Author(s):  
Ying-Mei Qin ◽  
Cong Men ◽  
Jia Zhao ◽  
Chun-Xiao Han ◽  
Yan-Qiu Che
Keyword(s):  
Neuronal Excitability ◽  
Temporal Coding ◽  
Feedforward Network ◽  
Firing Patterns ◽  
In Vivo Experiments ◽  
Connection Probability ◽  
Rate Coding

We focus on the role of heterogeneity on the propagation of firing patterns in feedforward network (FFN). Effects of heterogeneities both in parameters of neuronal excitability and synaptic delays are investigated systematically. Neuronal heterogeneity is found to modulate firing rates and spiking regularity by changing the excitability of the network. Synaptic delays are strongly related with desynchronized and synchronized firing patterns of the FFN, which indicate that synaptic delays may play a significant role in bridging rate coding and temporal coding. Furthermore, quasi-coherence resonance (quasi-CR) phenomenon is observed in the parameter domain of connection probability and delay-heterogeneity. All these phenomena above enable a detailed characterization of neuronal heterogeneity in FFN, which may play an indispensable role in reproducing the important properties of in vivo experiments.

scholarly journals Assistive Technology and Cognitive-Behavioral Programs for Promoting Adaptive Skills of Persons with Alzheimer Disease: A Selective Review

2018 ◽  
Vol 2 (3) ◽  
pp. 14-29
Author(s):  
Viviana Perilli ◽  
Fabrizio Stasolla ◽  
Stefania Maselli ◽  
Isabel Morelli
Keyword(s):  
Quality Of Life ◽  
Alzheimer Disease ◽  
Assistive Technology ◽  
Challenging Behavior ◽  
Behavioral Interventions ◽  
Challenging Behaviors ◽  
Cognitive Behavioral ◽  
Adaptive Responding

Background: Person with Alzheimer Disease may present cognitive, social, communication, physical, and orientation impairments. Furthermore, individuals with Alzheimer Disease may exhibit challenging behavior, isolation, and passivity. Objectives: To emphasize the role of Assistive Technology-based interventions and Cognitive-Behavioral Programs to improve the independence, and the quality of life of patients with Alzheimer Disease. To assess the effects on teaching adaptive responding, and decreasing challenging behaviors. Method: A selective literature review was carried out considering Alzheimer, Assistive Technology, Cognitive-Behavioral Programs, Adaptive Responding, Challenging Behaviors, and Quality of life as keywords. Twenty-six studies were reviewed. Results: Empirical data demonstrated the effectiveness, and the suitability of the selected interventions, although few failures occurred. The participants involved significantly increased their adaptive responding during the intervention phases, and maintained their performance over the time. Conclusion: Assistive Technology-based rehabilitative programs and Cognitive-Behavioral Interventions may be helpful for promoting the independence and the quality of life of individuals with Alzheimer Disease.

scholarly journals The role of intolerance of uncertainty in the acquisition and extinction of reward

2020 ◽  
Author(s):  
Jayne Morriss ◽  
Nicolo Biagi ◽  
Tina B. Lonsdorf ◽  
Marta Andreatta
Keyword(s):  
Associative Learning ◽  
Conceptual Understanding ◽  
Skin Conductance Response ◽  
Intolerance Of Uncertainty ◽  
Acquisition Training ◽  
Learning Task ◽  
Partial Reward ◽  
Extinction Training ◽  
Corrugator Supercilii

AbstractIndividuals, who score high in self-reported intolerance of uncertainty (IU), tend to find uncertainty anxiety-provoking. IU has been reliably associated with disrupted threat extinction. However, it remains unclear whether IU would be related to disrupted extinction to other arousing stimuli that are not threatening (i.e., rewarding). We addressed this question by conducting a reward associative learning task with acquisition and extinction training phases (n = 58). Throughout the associative learning task, we recorded valence ratings (i.e. liking), skin conductance response (SCR) (i.e. sweating), and corrugator supercilii activity (i.e. brow muscle indicative or negative and positive affect) to learned reward and neutral cues. During acquisition training with partial reward reinforcement, higher IU was associated with greater corrugator supercilii activity to neutral compared to reward cues. IU was not related to valence ratings or SCR’s during the acquisition or extinction training phases. These preliminary results suggest that IU-related deficits during extinction may be limited to situations with threat. The findings further our conceptual understanding of IU’s role in the associative learning and extinction of reward, and in relation to the processing of threat and reward more generally.

scholarly journals The role of trait anxiety in associative learning during and after an aversive event

2019 ◽  
Vol 26 (2) ◽  
pp. 56-59 ◽  
Author(s):  
Arne Ilse ◽  
Virginia Prameswari ◽  
Evelyn Kahl ◽  
Markus Fendt
Keyword(s):  
Associative Learning ◽  
Trait Anxiety ◽  
Aversive Event

scholarly journals SOCIAL AND BEHAVIORAL FACTORS IN COGNITIVE AGING: APPLYING THE CAUSAL INFERENCE FRAMEWORK IN OBSERVATIONAL STUDIES

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S323-S323
Author(s):  
Anja K Leist
Keyword(s):  
Machine Learning ◽  
Cognitive Decline ◽  
Causal Inference ◽  
Cognitive Aging ◽  
Behavioral Interventions ◽  
Observational Studies ◽  
Intervention Research ◽  
Learning Approaches ◽  
Behavioral Factors

Abstract Rationale: There is an urgent need to better understand how to maintain cognitive functioning at older ages with social and behavioral interventions, given that there is currently no medical cure available to prevent, halt or reverse the progression of cognitive decline and dementia. However, in current models, it is still not well established which factors (e.g. education, BMI, physical activity, sleep, depression) matter most at which ages, and which behavioral profiles are most protective against cognitive decline. In the last years, advances in the fields of causal inference and machine learning have equipped epidemiology and social sciences with methods and models to approach causal questions in observational studies. Method: The presentation will give an overview of the causal inference framework and different machine learning approaches to investigate cognitive aging. First, we will present relevant research questions on the role of social and behavioral factors in cognitive aging in observational studies. Second, we will introduce the causal inference framework and recent methods to visualize and compute the strength of causal paths. Third, promising machine learning approaches to arrive at robust predictions are presented. The 13-year follow-up from the European SHARE survey that employs well-established cognitive performance tests is used to demonstrate the usefulness of the approach. Discussion: The causal inference framework, combined with recent machine learning approaches and applied in observational studies, provides a robust alternative to intervention research. Advantages for investigations under the new framework, e.g., fewer ethical considerations compared to intervention research, as well as limitations are discussed.

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