A common cortical metric for spatial, temporal, and social distance

Area of Science:

• Cognitive Neuroscience
• Neuroimaging
• Computational Neuroscience

Background:

• Metaphorical language commonly uses spatial terms (e.g., "close friends," "near future") to describe non-spatial concepts.
• The origin of these spatial metaphors—whether coincidental or rooted in common neural computations—remains an open question.

Purpose of the Study:

• To investigate whether the brain encodes egocentric distance similarly across spatial, temporal, and social domains.
• To identify potential neural underpinnings for the common use of spatial metaphors.

Main Methods:

• Functional magnetic resonance imaging (fMRI) was used to collect human brain activity data.
• Machine learning algorithms (statistical pattern recognition) were employed to decode brain response patterns.
• A cross-domain classification approach was used to test if distance representations in one domain could predict those in another.

Main Results:

• Above-chance decoding of egocentric distance was consistently achieved across spatial, temporal, and social domains within the right inferior parietal lobule (IPL).
• The representational similarity structure in the right IPL correlated with participants' subjective judgments of spatial distance, temporal proximity, and social familiarity.
• These findings suggest a shared neural mechanism for processing proximity across different frames of reference.

Conclusions:

• The right inferior parietal lobule (IPL) may host a unified neural code for proximity to self.
• This shared representation could explain the prevalence and intuitive nature of spatial metaphors in language.
• The findings support the hypothesis that abstract concepts are grounded in shared neural computations related to spatial experience.