Uncovering the brain’s flexible mechanisms for representing diverse numbers

The National Institute of Information and Communications Technology (NICT, President: TOKUDA Hideyuki, Ph.D.) has revealed, through fMRI-based brain activity analysis, that multiple regions in the human cerebral cortex flexibly represent numerical quantity. This finding comes from research by HAYASHI Masamichi (Researcher (Tenure-Track)) at Center for Information and Neural Networks (CiNet), part of NICT’s Advanced ICT Research Institute, in collaboration with the University of Tokyo’s graduate student KIDO Teruaki (NICT cooperative visiting researcher), and Prof. YOTSUMOTO Yuko.

Although certain brain areas are known to respond to numerical quantity, this study expands that understanding by showing that some regions respond to relative quantity (e.g., “extra-small,” “small,” “large,” and “extra-large”) rather than absolute quantity (i.e., specific quantity). Moreover, these context-dependent, relative representations become more pronounced along the pathway from the parietal to the frontal lobe.

These results highlight the flexible nature of numerical quantity processing in the brain, and they are expected to advance our understanding of how the brain handles other types of “magnitude” concepts, including time and size.

This work was published in the journal “Nature Communications” on January 6, 2025.

 

Background

It has long been known that certain brain regions contain neurons that respond selectively to specific numbers. However, it remained unclear whether they always react to the same numbers, such as 8 or 15, regardless of context (absolute representation), or if their response changes depending on the situation. If neurons strictly followed absolute quantity, an impractically large number of neurons would be required to process infinite numerical quantities, making it unclear how the human brain, with its limited neurons, efficiently processes such a wide range of numbers.

 

Achievements

In this study, we used functional magnetic resonance imaging (fMRI) to measure participants’ brain activity and analyzed it with multivariate pattern analysis. Over three days, participants viewed black-and-white dot patterns that presented numerical information in different ranges while their brain activity was recorded.

The results showed that despite variations in numbers, certain brain regions exhibited similar activity patterns (Figure 1). This occurred when the relative magnitude within the range was the same (e.g., XS in the large set and that in the small set). This suggests that neurons may adjust their responses to numbers based on context (i.e., the numerical range), enabling efficient encoding while conserving neural resources.

Furthermore, our study revealed a hierarchical structure in visual processing: lower sensory regions represented numbers in absolute terms, whereas higher-order cortices, from the parietal to the frontal lobe, gradually shifted toward relative numerical quantity representations. This shift highlights how the brain flexibly encodes numerical magnitude based on context (Figure 2).

Numerical information is embedded in various forms of media, and its accurate and effective communication plays a crucial role in determining the quality of communication. This study aims to enhance communication quality by uncovering the brain functions involved in processing numerical concepts.

 

Future Prospects

While this study focused on numerical quantity, similar mechanisms may also underlie other quantitative concepts, such as size and time. Investigating whether the brain represents these concepts in a relative manner could provide deeper insights into how the brain perceives and interprets its environment as a whole.

 

Article information

Journal: Nature Communications

DOI: 10.1038/s41467-024-55599-8

URL: https://doi.org/10.1038/s41467-024-55599-8

Title: Hierarchical representations of relative numerical magnitudes in the human frontoparietal cortex

Authors: Teruaki Kido, Yuko Yotsumoto, Masamichi J. Hayashi

 

Research team

KIDO Teruaki

Graduate Student, Department of Life Sciences, Graduate School of Arts and Sciences, The University of Tokyo, Tokyo, Japan

Cooperative Visiting Researcher, Center for Information and Neural Networks (CiNet), Advanced ICT Research Institute, National Institute of Information and Communications Technology, Suita, Japan

YOTSUMOTO Yuko

Professor, Department of Life Sciences, Graduate School of Arts and Sciences, The University of Tokyo, Tokyo, Japan

HAYASHI Masamichi

Researcher (Tenure-Track), Center for Information and Neural Networks (CiNet), Advanced ICT Research Institute, National Institute of Information and Communications Technology, Suita, Japan

Guest Associate Professor, Graduate School of Frontier Biosciences, Osaka University, Suita, Japan

END