Simons Collaboration on Ecological Neuroscience

The Simons Collaboration on Ecological Neuroscience (SCENE) will establish a new paradigm — ecological neuroscience — that moves beyond conventional theories of sensory and motor processing.

Inspired by ecological psychology, SCENE proposes that one of the brain’s core functions is to encode affordances — that is, the opportunities for action available in an environment — rather than encoding all environmental causes or only rewarding stimuli. Based on this insight, SCENE will integrate cutting-edge neural recording technologies, computational modeling and cross-species experimentation to systematically test formal mathematical theories of how the brain represents and uses information to guide behavior. With an emphasis on open science, SCENE will unite leading scientists across neuroscience and machine learning, ensuring a comprehensive approach that links neural dynamics with real-world sensorimotor interactions in animals, humans and artificial systems. In doing this, SCENE aims to reveal fundamental principles of intelligence that apply across species.

SCENE expects to resolve how the brain organizes perception and action within ecological constraints, providing a robust, theoretically grounded and experimentally validated framework that describes if and how neural systems encode affordances. The collaboration anticipates revealing core computational principles that generalize across species, governing how brain-wide dynamics enable complex, adaptive behaviors. By formalizing affordances into a mathematically rigorous framework and demonstrating their neural underpinnings, SCENE will reshape our understanding of cognition and behavior.

The collaboration includes 20 principal investigators:

Dora Angelaki (New York University)
Aaron Batista (University of Pittsburgh)
Tesca Fitzgerald (Yale University)
Jonathan Kominsky (Central European University)
Máté Lengyel (University of Cambridge and Central European University)*
Alexander Mathis (École Polytechnique Fédérale de Lausanne)
Mackenzie Mathis (École Polytechnique Fédérale de Lausanne)*
Cynthia Moss (Johns Hopkins University)
Cris Niell (University of Oregon)
Jean-Paul Noel (University of Minnesota)
Xaq Pitkow (Carnegie Mellon University)
Constantin Rothkopf (Technical University of Darmstadt)
Cristina Savin (New York University)
Kimberly Stachenfeld (Columbia University and Google DeepMind)
Nanthia Suthana (Duke University)
Andreas Tolias (Stanford University)
Nachum Ulanovsky (Weizmann Institute of Science)
Daniel Wolpert (Columbia University)*
Alex Wong (Yale University)
Jan Zimmermann (University of Minnesota)

*Executive committee member