Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 189 tok/s
Gemini 2.5 Pro 53 tok/s Pro
GPT-5 Medium 36 tok/s Pro
GPT-5 High 36 tok/s Pro
GPT-4o 75 tok/s Pro
Kimi K2 160 tok/s Pro
GPT OSS 120B 443 tok/s Pro
Claude Sonnet 4.5 37 tok/s Pro
2000 character limit reached

The right time to learn: mechanisms and optimization of spaced learning (1606.08370v1)

Published 27 Jun 2016 in q-bio.NC and q-bio.MN

Abstract: For many types of learning, spaced training that involves repeated long inter-trial intervals (ITIs) leads to more robust memory formation than does massed training that involves short or no intervals. Several cognitive theories have been proposed to explain this superiority, but only recently has data begun to delineate the underlying cellular and molecular mechanisms of spaced training. We review these theories and data here. Computational models of the implicated signaling cascades have predicted that spaced training with irregular ITIs can enhance learning. This strategy of using models to predict optimal spaced training protocols, combined with pharmacotherapy, suggests novel ways to rescue impaired synaptic plasticity and learning.

Summary

We haven't generated a summary for this paper yet.

Dice Question Streamline Icon: https://streamlinehq.com

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.