scholarly journals Prediction Error-Driven Memory Consolidation for Continual Learning: On the Case of Adaptive Greenhouse Models

2021 ◽  
Author(s):  
Guido Schillaci ◽  
Uwe Schmidt ◽  
Luis Miranda
Keyword(s):  
Online Learning ◽  
Episodic Memory ◽  
Prior Knowledge ◽  
Memory Consolidation ◽  
Prediction Error ◽  
Neural Model ◽  
Adaptive Architecture ◽  
Brain Sciences ◽  
Research Facilities ◽  
Continual Learning

AbstractThis work presents an adaptive architecture that performs online learning and faces catastrophic forgetting issues by means of an episodic memory system and of prediction-error driven memory consolidation. In line with evidence from brain sciences, memories are retained depending on their congruence with the prior knowledge stored in the system. In this work, congruence is estimated in terms of prediction error resulting from a deep neural model. The proposed AI system is transferred onto an innovative application in the horticulture industry: the learning and transfer of greenhouse models. This work presents models trained on data recorded from research facilities and transferred to a production greenhouse.

Positive Arousal Enhances the Consolidation of Item Memory

2015 ◽  
Vol 74 (2) ◽  
pp. 91-104 ◽  
Author(s):  
Bo Wang
Keyword(s):  
Episodic Memory ◽  
Memory Consolidation ◽  
Source Memory ◽  
Emotional Arousal ◽  
Theoretical Models ◽  
Memory Test ◽  
Learning Phase ◽  
Item Memory ◽  
Memory Tests ◽  
Immediate Memory

Emotional arousal induced after learning has been shown to modulate memory consolidation. However, it is unclear whether the effect of postlearning arousal can extend to different aspects of memory. This study examined the effect of postlearning positive arousal on both item memory and source memory. Participants learned a list of neutral words and took an immediate memory test. Then they watched a positive or a neutral videoclip and took delayed memory tests after either 25 minutes or 1 week had elapsed after the learning phase. In both delay conditions, positive arousal enhanced consolidation of item memory as measured by overall recognition. Furthermore, positive arousal enhanced consolidation of familiarity but not recollection. However, positive arousal appeared to have no effect on consolidation of source memory. These findings have implications for building theoretical models of the effect of emotional arousal on consolidation of episodic memory and for applying postlearning emotional arousal as a technique of memory intervention.

Knowledge is power: prior knowledge aids memory formation for both congruent and incongruent events, but in different ways.

2017 ◽  
Author(s):  
Andrea Greve ◽  
Elisa Cooper ◽  
Roni Tibon ◽  
Richard Henson
Keyword(s):  
Episodic Memory ◽  
Prior Knowledge ◽  
Memory Performance ◽  
Memory Formation ◽  
Memory Test ◽  
World Knowledge ◽  
Apparent Paradox ◽  
Power Prior

Events that conform to our expectations, i.e, are congruent with our world knowledge or schemas, are better remembered than unrelated events. Yet events that conflict with schemas can also be remembered better. We examined this apparent paradox in four experiments, in which schemas were established by training ordinal relationships between randomly-paired objects, while episodic memory was tested for the number of objects on each trial. Better memory was found for both congruent and incongruent trials, relative to unrelated trials, producing memory performance that was a “U-shaped” function of congruency. Furthermore, the incongruency advantage, but not congruency advantage, emerged even if the information probed by the memory test was irrelevant to the schema, while the congruency advantage, but not incongruency advantage, also emerged after initial encoding. Schemas therefore augment episodic memory in multiple ways, depending on the match between novel and existing information.

scholarly journals Bi-Temporal Anodal Transcranial Direct Current Stimulation during Slow-Wave Sleep Boosts Slow-Wave Density but Not Memory Consolidation

2021 ◽  
Vol 11 (4) ◽  
pp. 410
Author(s):  
Simon Ruch ◽  
Kristoffer Fehér ◽  
Stephanie Homan ◽  
Yosuke Morishima ◽  
Sarah Maria Mueller ◽  
...  
Keyword(s):  
Episodic Memory ◽  
Slow Wave ◽  
Direct Current ◽  
Memory Consolidation ◽  
Transcranial Direct Current Stimulation ◽  
Slow Wave Sleep ◽  
Memory Performance ◽  
Direct Current Stimulation ◽  
Sleep Parameters ◽  
Episodic Memories

Slow-wave sleep (SWS) has been shown to promote long-term consolidation of episodic memories in hippocampo–neocortical networks. Previous research has aimed to modulate cortical sleep slow-waves and spindles to facilitate episodic memory consolidation. Here, we instead aimed to modulate hippocampal activity during slow-wave sleep using transcranial direct current stimulation in 18 healthy humans. A pair-associate episodic memory task was used to evaluate sleep-dependent memory consolidation with face–occupation stimuli. Pre- and post-nap retrieval was assessed as a measure of memory performance. Anodal stimulation with 2 mA was applied bilaterally over the lateral temporal cortex, motivated by its particularly extensive connections to the hippocampus. The participants slept in a magnetic resonance (MR)-simulator during the recordings to test the feasibility for a future MR-study. We used a sham-controlled, double-blind, counterbalanced randomized, within-subject crossover design. We show that stimulation vs. sham significantly increased slow-wave density and the temporal coupling of fast spindles and slow-waves. While retention of episodic memories across sleep was not affected across the entire sample of participants, it was impaired in participants with below-average pre-sleep memory performance. Hence, bi-temporal anodal direct current stimulation applied during sleep enhanced sleep parameters that are typically involved in memory consolidation, but it failed to improve memory consolidation and even tended to impair consolidation in poor learners. These findings suggest that artificially enhancing memory-related sleep parameters to improve memory consolidation can actually backfire in those participants who are in most need of memory improvement.

scholarly journals 0234 Role of Midday Naps on Episodic Memory Consolidation in Preschool Children

SLEEP ◽  
2019 ◽  
Vol 42 (Supplement_1) ◽  
pp. A97-A97
Author(s):  
Sanna Lokhandwala ◽  
Jamie Allfisher ◽  
Rebecca M C Spencer
Keyword(s):  
Preschool Children ◽  
Episodic Memory ◽  
Memory Consolidation

scholarly journals Sleep Spindle Density Predicts the Effect of Prior Knowledge on Memory Consolidation

2016 ◽  
Vol 36 (13) ◽  
pp. 3799-3810 ◽  
Author(s):  
Nora Hennies ◽  
Matthew A. Lambon Ralph ◽  
Marleen Kempkes ◽  
James N. Cousins ◽  
Penelope A. Lewis
Keyword(s):  
Prior Knowledge ◽  
Memory Consolidation ◽  
Sleep Spindle

scholarly journals Preschool-aged children jointly consider others’ emotional expressions and prior knowledge to decide when to explore

2019 ◽  
Author(s):  
Yang Wu ◽  
Hyowon Gweon
Keyword(s):  
Prior Knowledge ◽  
Prediction Error ◽  
Emotional Expressions ◽  
Children’S Learning ◽  
Causal Function ◽  
Salient Function ◽  
Adult Play ◽  
Preschool Aged Children ◽  
Children's Learning

Emotional expressions are abundant in children’s lives. What role do these expressions play in children’s learning? Here we ask whether preschool-aged children use others’ emotional expressions to infer the presence of unknown causal functions and guide their exploration accordingly. Children (3.0-4.9 years; N=112) learned about one salient causal function of a novel toy, and then saw an adult play with the toy. Children explored the toy more when the adult expressed surprise than when she expressed happiness (Experiment 1), but only when the adult already knew about the toy's salient function (Experiment 2). These results suggest that children selectively interpret others’ surprise as “vicarious prediction error” based on others’ knowledge, and use it to guide their own exploration and discovery.

scholarly journals Prediction of Slot Shape and Slot Size for Improving the Performance of Microstrip Antennas Using Knowledge-Based Neural Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Taimoor Khan ◽  
Asok De
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Prior Knowledge ◽  
Neural Model ◽  
Microstrip Antennas ◽  
Performance Parameters ◽  
Dual Frequency ◽  
Knowledge Based ◽  
Slot Size ◽  
Good Agreement

In the last decade, artificial neural networks have become very popular techniques for computing different performance parameters of microstrip antennas. The proposed work illustrates a knowledge-based neural networks model for predicting the appropriate shape and accurate size of the slot introduced on the radiating patch for achieving desired level of resonance, gain, directivity, antenna efficiency, and radiation efficiency for dual-frequency operation. By incorporating prior knowledge in neural model, the number of required training patterns is drastically reduced. Further, the neural model incorporated with prior knowledge can be used for predicting response in extrapolation region beyond the training patterns region. For validation, a prototype is also fabricated and its performance parameters are measured. A very good agreement is attained between measured, simulated, and predicted results.

scholarly journals Surprise and destabilize: prediction error influences episodic memory reconsolidation

2018 ◽  
Vol 25 (8) ◽  
pp. 369-381 ◽  
Author(s):  
Alyssa H. Sinclair ◽  
Morgan D. Barense
Keyword(s):  
Episodic Memory ◽  
Prediction Error ◽  
Memory Reconsolidation

Encouraging and Increasing Student Engagement and Participation in an Online Classroom

2016 ◽  
pp. 426-447
Author(s):  
Kathryn Woods
Keyword(s):  
Online Learning ◽  
Student Engagement ◽  
Learning Environment ◽  
Prior Knowledge ◽  
Learning Environments ◽  
Online Courses ◽  
Traditional Classroom ◽  
Online Classroom ◽  
Online Learning Environments ◽  
The Impact

Advances in technology have increased opportunities for students to participate in online courses. While some instructors are beginning their careers teaching only online courses, others are discovering a need to teach sections of courses online after they have enjoyed a long career teaching in a traditional classroom. In either situation, it is important for instructors to recognize that students in online learning environments require the use of different strategies for encouraging engagement and participation in class. In this chapter, the author describes the challenges that students and instructors face specifically in the online learning environment as well as strategies for success, including how to maximize the impact of students' experiences and prior knowledge, using multiple platforms to deliver information, discouraging procrastination, setting clear expectations, encouraging individuality, capitalizing on diversity, and providing and utilizing helpful resources.

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