[2512.15891] Dynamical Mechanisms for Coordinating Long-term Working Memory Based on the Precision of Spike-timing in Cortical Neurons

[2512.15891] Dynamical Mechanisms for Coordinating Long-term Working Memory Based on the Precision of Spike-timing in Cortical Neurons

arXiv - AI 4 min read Article

Summary

The article explores the mechanisms of long-term working memory in cortical neurons, emphasizing the role of spike-timing precision in cognitive processing.

Why It Matters

Understanding the neural basis of long-term working memory is crucial for advancements in cognitive neuroscience and artificial intelligence. This research could inform models of memory and learning, impacting fields such as robotics and machine learning.

Key Takeaways

  • Cortical neurons may utilize spike-timing precision to support long-term working memory.
  • Spike-timing-dependent plasticity (STDP) plays a significant role in cognitive processing.
  • Cognitive states can exist independently of sensory or motor activity.

Quantitative Biology > Neurons and Cognition arXiv:2512.15891 (q-bio) [Submitted on 17 Dec 2025 (v1), last revised 12 Feb 2026 (this version, v4)] Title:Dynamical Mechanisms for Coordinating Long-term Working Memory Based on the Precision of Spike-timing in Cortical Neurons Authors:Terrence J. Sejnowski View a PDF of the paper titled Dynamical Mechanisms for Coordinating Long-term Working Memory Based on the Precision of Spike-timing in Cortical Neurons, by Terrence J. Sejnowski View PDF Abstract:In the last century, most sensorimotor studies of cortical neurons relied on average firing rates. Rate coding is efficient for fast sensorimotor processing that occurs within a few seconds. Much less is known about the neural mechanisms underlying long-term working memory with a time scale of hours (Ericsson and Kintsch, 1995). Cognitive states may not have sensory or motor correlates. For example, you can sit in a quiet room making plans without moving or sensory processing. You can also make plans while out walking. This suggests that the neural substrate for cognitive states neither depends on nor interferes with ongoing sensorimotor brain activity. In this perspective, I make the case for a possible second tier of neural activity that coexists with the well-established sensorimotor tier, based on coordinated spike-timing activity. The discovery of millisecond-precision spike initiation in cortical neurons was unexpected (Mainen and Sejnowski, 1995). Even more striking was the...

Related Articles

Fostering breakthrough AI innovation through customer-back engineering | MIT Technology Review
Nlp

Fostering breakthrough AI innovation through customer-back engineering | MIT Technology Review

Despite years of digitization, organizations capture less than one-third of the value expected from digital investments, according to McK...

MIT Technology Review - AI · 8 min ·
Machine Learning

What to expect from AlphaZero's value predictions [D]

An AlphaZero agent has learnt to predict the value of a game state by training on data generated by self-play by the model and a series o...

Reddit - Machine Learning · 1 min ·
Machine Learning

A Geometric Perspective on Robustness in Vision Transformers [R]

Hi everyone! I'm sharing a paper I've been working on that investigates how different positional encoding schemes (learned absolute, sinu...

Reddit - Machine Learning · 1 min ·
[2602.07026] Modality Gap-Driven Subspace Alignment Training Paradigm For Multimodal Large Language Models
Llms

[2602.07026] Modality Gap-Driven Subspace Alignment Training Paradigm For Multimodal Large Language Models

Abstract page for arXiv paper 2602.07026: Modality Gap-Driven Subspace Alignment Training Paradigm For Multimodal Large Language Models

arXiv - AI · 4 min ·
More in Nlp: This Week Guide Trending

No comments

No comments yet. Be the first to comment!

Stay updated with AI News

Get the latest news, tools, and insights delivered to your inbox.

Daily or weekly digest • Unsubscribe anytime