The effects of task similarity during representation learning in brains and neural networks

Nicholas Menghi (), W. Jeffrey Johnston, Simone Vigano’, Max Andreas Bosse Hinrichs, Burkhard Maess, Stefano Fusi and Christian F. Doeller
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Nicholas Menghi: Max Planck Institute for Human Cognitive and Brain Sciences, Department of Psychology
W. Jeffrey Johnston: Columbia University, Center for Theoretical Neuroscience and Mortimer B. Zuckerman Mind, Brain, and Behavior Institute
Simone Vigano’: Max Planck Institute for Human Cognitive and Brain Sciences, Department of Psychology
Max Andreas Bosse Hinrichs: Max Planck Institute for Human Cognitive and Brain Sciences, Department of Psychology
Burkhard Maess: Max Planck Institute for Human Cognitive and Brain Sciences, Department of Psychology
Stefano Fusi: Columbia University, Center for Theoretical Neuroscience and Mortimer B. Zuckerman Mind, Brain, and Behavior Institute
Christian F. Doeller: Max Planck Institute for Human Cognitive and Brain Sciences, Department of Psychology

Nature Communications, 2025, vol. 16, issue 1, 1-13

Abstract: Abstract The complexity of our environment poses significant challenges for adaptive behavior. Recognizing shared structures across tasks can theoretically improve learning through generalization. However, how such shared representations emerge and influence performance remains poorly understood. Contrary to expectations, our findings revealed that individuals trained on tasks with similar low-dimensional structures performed worse than those trained on dissimilar tasks. Magnetoencephalography revealed correlated neural representations in the same-structure group and anticorrelated ones in the different-structure group. Crucially, practice reduced this performance gap and shifted the neural representations of the tasks in the same-structure group towards anticorrelation, resembling those in the different-structure group. A neural network model trained on similar tasks replicated these findings: tasks with similar structures require more iterations to orthogonalize their representations. These results highlight a complex interplay between task similarity, neural dynamics, and behavior, challenging traditional assumptions about learning and generalization.

Date: 2025
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DOI: 10.1038/s41467-025-66849-8

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