Search bioRxiv⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/2024.05.27.596021

Mapping and Modeling the Semantic Space of Math Concepts

Debray, S.·Dehaene, S.
View original source ↗Export metadata ↓

Abstract

Mathematics is an underexplored domain of human cognition. While many studies have focused on subsets of math concepts such as numbers, fractions, or geometric shapes, few have ventured beyond these elementary domains. Here, we attempted to map out the full space of math concepts and to answer two specific questions: can distributed semantic models, such a GloVe, provide a satisfactory fit to human semantic judgments in mathematics? And how does this fit vary with education? We first analyzed all of the French and English Wikipedia pages with math contents, and used a semi-automatic procedure to extract the 1,000 most frequent math terms in both languages. In a second step, we collected extensive behavioral judgments of familiarity and semantic similarity between them. About half of the variance in human similarity judgments was explained by vector embeddings that attempt to capture latent semantic structures based on cooccurence statistics. Participants self-reported level of education modulated familiarity and similarity, allowing us to create a partial hierarchy among high-level math concepts. Our results converge onto the proposal of a map of math space, organized as a database of math terms with information about their frequency, familiarity, grade of acquisition, and entanglement with other concepts.

Source connections

Explore related subjects

neurosciencePreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Debray, S., Dehaene, S.. 2024-06-01. Mapping and Modeling the Semantic Space of Math Concepts. https://doi.org/10.1101/2024.05.27.596021

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

A Mechanistic Account of Dedifferentiation in the Aging Visual System

To uncover the mechanisms of age-related dedifferentiation, we simulated neural degradation in a computational model of the ventral visual stream. Severing connections or adding noise, whether in inferotemporal cortex (IT) or upstream, reduced IT differentiation, indicating that dedifferentiation need not originate locally. Degrading peripheral V1, which preferentially drove place-selective IT neurons, selectively reduced place differentiation, a candidate mechanism for the stronger place dedifferentiation reported in aging.

neuroscience↗
bioRxiv2026

Reusing pipettes in Patch-seq: a foundation for automated multimodal profiling

Patch-seq is a technique for single-cell multimodal characterization. It combines whole-cell electrophysiology, single-cell transcriptomics, and morphological reconstruction in single neurons. Patch-seq morphologies are a critical bridge among cell types, genes, physiology, and large-scale connectivity platforms such as EM connectomes and single-cell-resolution projectomes. However, patch-seq experimental complexity and operator dependence limit throughput. Automation could enable scalable Patch-seq but requires procedural adaptations, including detergent-based pipette cleaning, robotic nucleus extraction and collection. The impact of these automations on Patch-seq quality has not been systematically evaluated. Here, we show that each of these modifications preserves or improves key Patch-seq outcomes. Automated nucleus extraction performs comparably to, or better than, expert manual operation, preserving key RNA and morphological metrics. Detergent-cleaned, reused pipettes supported a viable sealing success rate across multiple cleaning cycles and preserved electrophysiological quality and transcriptomic yield without introducing excess contamination. Sonication effectively allows collection of nuclear material without damaging RNA and supports subsequent pipette cleaning and reuse. Enhanced automated sealing and break-in procedures increased throughput regardless of brain region, cell type or species. Together, these results validate the core procedural adaptations required for automated Patch-seq and establish a foundation for high-throughput, standardized multimodal single-cell characterization.

neuroscience↗
bioRxiv2026

Development of direction selectivity in the Xenopus tadpole optic tectum and midbrain tegmentum

Detecting motion direction is a fundamental function performed by direction selective (DS) neurons. DS neurons in the optic tectum (superior colliculus in mammals) enable the tracking of moving objects. DS neurons of the accessory optic system support reflexive eye / head movements that stabilize gaze during self-motion. By developmental stage 48 (10 days postfertilization), Xenopus tadpoles display visually guided behaviors that require both types of DS neurons. Our previous work has shown that these two regions are not only functionally distinct but also follow different developmental programs. Here we characterized and compared how direction selectivity develops in both visual processing centers. Using in vivo electrophysiological recordings during moving bar visual stimulation, we measured DS synaptic inputs and spiking outputs in both regions across three key developmental stages of the retinotectal projection. Tegmental neurons were direction selective ab initio, and both input and output tuning remained stable across development. Tectal neurons were observed to receive DS inputs early, and their input selectivity also remained stable across development. However, their spiking output grew substantially more DS at the later developmental stage. This was due at least in part to a naturally occurring decrease in intrinsic excitability which preferentially dampened overall spike rates, but especially in response to the non-preferred direction of motion, thereby increasing direction selectivity. These results reveal distinct developmental trajectories in parallel visual pathways. Tegmental direction selectivity is established early and stays stable, whereas tectal output tuning sharpens during development through a decrease in intrinsic excitability.

neuroscience↗