How sensory systems rapidly adapt to changing stimulus statistics remains unclear. Here the authors show that gain adaptation in recurrent networks can implement fast efficient coding, unifying prior ...

Context-dependent behavior selects actions according to task demands. Using direct brain recordings in humans, Binish et al. uncover how coordinated population activity efficiently channels informatio...

Harvard Management Company (Harvard Management) provides investment management services to Harvard, a private university with more than $60 billion in net assets.  Consequently, revenue comes from …

Neuroscience has become increasingly concerned with prediction, and machine learning with causal explanation, with each field adopting methods from the other. I asked eight experts to weigh in on what...

A trumpet-shaped, single-celled organism seems able to predict one thing will follow another, hinting that such associative learning emerged long before multicellular nervous systems

A trumpet-shaped, single-celled organism seems able to predict one thing will follow another, hinting that such associative learning emerged long before multicellular nervous systems

Humans learn abstractions and use them to plan efficiently to quickly generalize across tasks -- an ability that remains challenging for state-of-the-art large language model (LLM) agents and deep rei...

New research also offers hints for devising ways to stop students from creating obstacles to success.

An agent facing a planning problem can use answers to how-to questions to reduce uncertainty and fill knowledge gaps, helping it solve both current and future tasks. However, their open ended nature, ...

In the past decade, motivated by the putative failure of naive self-play deep reinforcement learning (DRL) in adversarial imperfect-information games, researchers have developed numerous DRL algorithm...

NIH Funding Opportunities and Notices in the NIH Guide for Grants and Contracts: BRAIN Initiative: Theories, Models and Methods for Analysis of Complex Data from the Brain (R01 Clinical Trial Not Allo...

We present Probabilistic Structure Integration (PSI), a system for learning richly controllable and flexibly promptable world models from data. PSI consists of a three-step cycle. The first step, Prob...

We consider emergence from the perspective of dynamics: states of a system evolving with time. We focus on the role of a decomposition of wholes into parts, and attempt to characterize relationships b...

The Kempner brings leading, early-stage postdoctoral scientists to Harvard to work on projects that advance the fundamental understanding of intelligence.

Classical models of memory in psychology and neuroscience rely on similarity-based retrieval of stored patterns, where similarity is a function of ret…

Modern reinforcement learning (RL) systems have demonstrated remarkable capabilities in complex environments, such as video games. However, they still fall short of achieving human-like sample efficie...