An Information Compass for Probabilistic Reasoning in the Brain

Abstract

Probabilistic reasoning in the brain has been studied primarily using simple two-choice tasks that are experimentally and theoretically tractable but have unclear relevance to more complex problems. Here we generalize principles from these studies using information geometry, which treats probability distributions (``beliefs'') as points on statistical manifolds whose geometry captures relationships between those beliefs. We introduce an ``information compass,'' a context-dependent, one-dimensional axis along which an arbitrarily complex belief is reinforced or repudiated. Projecting high-dimensional belief updates onto this axis casts even complex decisions into familiar forms of deliberation and commitment used for simpler decisions. Our framework provides a unified account of how biological and artificial systems can use geometric forms of probabilistic reasoning to make decisions across a range of tasks and domains.

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BibTeX RIS

BibTeX

@misc{bosulu2026information,
  title = {{An Information Compass for Probabilistic Reasoning in the Brain}},
  author = {J. Bosulu and V. Balasubramanian and Z. P. Kilpatrick and K. Josic and J. I. Gold},
  howpublished = {bioRxiv},
  year = {2026},
  month = oct,
  doi = {10.64898/2026.10.07.757408},
  url = {https://www.biorxiv.org/content/10.64898/2026.10.07.757408v1},
  note = {CC BY-NC-ND},
}

RIS

TY  - UNPB
TI  - An Information Compass for Probabilistic Reasoning in the Brain
AU  - J. Bosulu
AU  - V. Balasubramanian
AU  - Z. P. Kilpatrick
AU  - K. Josic
AU  - J. I. Gold
PY  - 2026
DA  - 2026/10/07
PB  - bioRxiv
DO  - 10.64898/2026.10.07.757408
UR  - https://www.biorxiv.org/content/10.64898/2026.10.07.757408v1
AB  - Probabilistic reasoning in the brain has been studied primarily using simple two-choice tasks that are experimentally and theoretically tractable but have unclear relevance to more complex problems. Here we generalize principles from these studies using information geometry, which treats probability distributions (``beliefs'') as points on statistical manifolds whose geometry captures relationships between those beliefs. We introduce an ``information compass,'' a context-dependent, one-dimensional axis along which an arbitrarily complex belief is reinforced or repudiated. Projecting high-dimensional belief updates onto this axis casts even complex decisions into familiar forms of deliberation and commitment used for simpler decisions. Our framework provides a unified account of how biological and artificial systems can use geometric forms of probabilistic reasoning to make decisions across a range of tasks and domains.
ER  -

Abstract

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