Table of Contents

Neural Tuning for Ordinal Processing: Convergent Patterns in Human Brains and Artificial Networks

  1. Serge O. Dumoulin1,2,3,4
  1. 1Spinoza Centre for Neuroimaging, Amsterdam 1105 BK, Netherlands
  2. 2Computational Cognitive Neuroscience and Neuroimaging, Netherlands Institute for Neuroscience, Amsterdam 1105 BA, Netherlands
  3. 3Experimental and Applied Psychology, Vrije University Amsterdam, Amsterdam 1081 HV, Netherlands
  4. 4Experimental Psychology, Utrecht University, Utrecht 3584 CS, Netherlands
  1. Author contributions: S.H. and S.O.D. designed research; S.H. and M.D. performed research; S.H. analyzed data; S.H. and S.O.D. wrote the paper.

Abstract

Processing ordinality, i.e., the rank of an item in a series such as 1st, 2nd, 3rd, etc., is a fundamental skill shared by humans and animals. While humans often use symbolic sequences like numbers or letters, ordinality does not depend on language or symbols. Across species, ordinality plays a critical role in behaviors such as decision-making, foraging, and social organization. We hypothesize that ordinality perception is supported by neuronal tuning, i.e., neurons selectively responsive to specific ranks. Using ultrahigh-field 7 T fMRI and population receptive field (pRF) modeling in human participants (both female and male), we identified neural populations in parietal and premotor cortices that are tuned to nonsymbolic ordinal positions. Comparable with other sensory domains, tuning width increased with preferred ordinal rank, suggesting reduced precision and potentially lower perceptual accuracy for higher ranks. Additionally, pRF measurements revealed that cortical territory devoted to higher ordinalities decreased with rank, reinforcing that neural precision is greatest for early positions (e.g., 1st and 2nd) and declines with rank. These responses did not generalize to symbolic ordinality. Similar tuning to nonsymbolic ordinality emerged spontaneously in hierarchical convolutional neural networks trained on visual tasks. Together, these results suggest that the tuning properties of these neuronal populations support nonsymbolic ordinality perception and may reflect an inherent feature of neural processing.

  • Received June 20, 2025.
  • Revision received December 10, 2025.
  • Accepted January 10, 2026.

This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license, which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properly attributed.

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