SWC at COSYNE 2026

Researchers from SWC are presenting at the COSYNE 2026 conference in Portugal.

1-022 A frontal motor circuit for economic decision and actions - Oliver Gauld, Chaofei Bao, Jingjie Li, Timothy Sit, Gauthier Boeshertz, Joseph Warren, Joseph Tutt, Yang Pan, Claudia Clopath, Jeffrey Erlich, Chunyu A Duan
1-050 From sequences to schemas: How recurrent neural networks learn temporal abstractions - Vezha Boboeva, Alberto Pezzotta, George Dimitriadis, Athena Akrami
1-079 Balancing generalisation and discrimination through structured hippocampal representations - Wanqing Jiang, Noe Hamou, Andrew Saxe, Andrew MacAskill
1-098 Value-driven behaviours emerge from local learning rules in minimal neural networks using online interactions - Chenguang Li, Hanming Ye, Joanna Aloor, Chunyu A Duan, Jeffrey Erlich
1-131 Rat frontal cortex shows context-dependent neural coding during economic decisions - Margarida Pexirra, Margot Tirole, Diksha Gupta, Jingjie Li, Jeffrey Erlich
1-139 Dopamine and nucleus accumbens influence risk preference through learning, not policy - Cong Sun, Chaofei Bao, Jeffrey Erlich
1-181 RNN initialisation schemes bring learning trajectories into alignment with rodent hippocampal data - Hugo Kaladjian, Tyler Boyd-Meredith, Andrew Saxe
1-208 A Neural Mechanism for Nested Repetition - Mathias Sable-Meyer, Svenja Kuchenhoff, Arya Bhomick, Diksha Gupta, Alon Baram, Kristopher Jensen, Sandra Reinert, Jeffrey Erlich, Mohamady El-Gaby, Timothy Behrens

2-013 Decoding Medial Entorhinal Cortical Dynamics Produces Planning-Like Alternations in Hippocampal Theta Sequences - Masahiro Nakano, Caswell Barry, Claudia Clopath
2-017 Distinct neuromodulatory contributions to strategic decisions in a competitive multi-player game - Joanna Aloor, Timothy Sit, Joschua Geuter, Joseph Tutt, Chunyu A Duan.
2-038 Frontal cortex represents social context and opponent information during competitive foraging - Ivana Orsolic, Huma Erboru, Christopher Douthwaite, Mehul Rastogi, Roshni Patel, Jeffrey Erlich, Chunyu A Duan
2-073 Dorso-ventrally increasing theta-sweep angles reflect firing rate adaptation and efficient sampling - Huiwen Zhang, Callum Marshall, Zilong Ji, Neil Burgess
2-151 Distinct striatal subcircuits for flexible choice and spatial value updating - Catarina Albergaria, Christopher D Hall, Thomas Ryan, Tiago Branco, Marcus Stephenson-Jones
2-221 Attraction to hierarchical feature memory explains orientation bias - Kira Dusterwald, Peter Vincent, Ana Kapros, Athena Akrami, Maneesh Sahani

16:30 A deep learning account of stage-like transitions in long-term learning - Andrew Saxe

17:30 Shared optimal behavior arises from distinct generative and discriminative learning algorithms - Quentin Pajot-Moric
18:45 Context-dependent localisation of short-term memory - Jingjie Li

3-006 The hippocampus is essential for statistical learning of abstract sensory sequences - Adedamola Onih, Ryan Shen, Lida Pentousi, Athena Akrami
3-067 Cognitive map restructuring along the hippocampal-entorhinal pathway in goal-directed navigation - Zilong Ji, Tianhao Chu, Si Wu, Neil Burgess
3-090 A hierarchical attractor network of the subicular-entorhinal-hippocampal circuitry explains goal-directed hippocampal theta sweeps - Changmin Yu, Zilong Ji, Jake Ormond, John O'Keefe, Neil Burgess
3-102 Goal-directed theta sweeps explain field shifts in vector trace cells - Athina Apostolelli, Zilong Ji, Neil Burgess
3-130 Sensory prediction errors update predictive representations - Sarah Elnozahy, Shohei Furutachi, Morio Hamada, Brant Yin, Sonja Hofer
3-139 Stage-like emergence of task strategies in animals and in neural networks trained by gradient descent - Tyler Boyd-Meredith, Cristofer Holobetz, Andrew Saxe
3-220 Learning dynamics of non-linear combinatorial tasks in rats and deep networks - Samuel Liebana, Antonio Sclocchi, Clara Kumpel, Jeffrey Erlich, Andrew Saxe

An Analytically Tractable Model of Optimal Replay for Schema Learning and Few-Shot Generalization - Andrew Saxe
Surfing symmetries in overparametrized neural networks: Consequences for representational comparisons between biological and artificial neural networks and the brain - Andrew Saxe