Marie Amalric

The paper investigates how the brain processes pure logic by comparing neural activity during logic, language, and arithmetic tasks, finding distinct brain circuits for logic.

This study uses fMRI to identify distinct brain networks for language, mathematics, and social knowledge, showing similar activation patterns across written and spoken modalities.

This study uses fMRI to examine if short math videos change brain networks for mathematical knowledge, finding minimal lasting changes and engagement of domain-general regions instead.

The paper shows that naturalistic and laboratory arithmetic tasks activate overlapping brain regions in children and adults, specifically the intraparietal cortex, indicating it processes mathematical content regardless of task mode.

The paper investigates how the human brain stores spatial sequences in working memory, finding that it compresses sequences using numerical and geometrical regularities rather than storing each item separately.

The paper examines neural responses in children and adults during naturalistic and laboratory mathematics tasks, finding that neural maturity and entropy are independent markers of brain development.

The paper identifies shared genetic influences between cognitive performance and brain activation in language and math tasks using the HCP dataset.

This paper demonstrates how to select grammar productions for a Language of Thought (LoT) using Bayesian inference, testing it in a geometric LoT model and finding an empirical relationship between sequence probability and complexity.