Local response heterogeneity indexes experience-based neural differentiation in reading

Area of Science:

• Neuroscience
• Cognitive Science
• Psychology

Background:

• Neural codes for reading are shaped by experience.
• Well-learned representations correlate with differentiated blood oxygenation level dependent (BOLD) responses.

Purpose of the Study:

• Introduce a novel analysis method, local heterogeneity regression (Local-Hreg).
• Quantify cross-voxel heterogeneity of BOLD responses to assess neural representation differentiation.
• Investigate how word frequency impacts neural differentiation in literate adults.

Main Methods:

• Developed and applied Local-Hreg to functional magnetic resonance imaging (fMRI) data.
• Analyzed BOLD responses in literate adults reading letter strings of varying frequencies.
• Focused on the left ventral occipitotemporal cortex (vOTC), a key reading region.

Main Results:

• Local-Hreg effectively quantifies neural representation differentiation.
• Cross-voxel heterogeneity in the vOTC varied with letter string frequency.
• More frequent words elicited greater neural differentiation than less frequent or unfamiliar words.

Conclusions:

• The study introduces a novel method for analyzing neural differentiation.
• Demonstrates that reading experience, specifically word frequency, modulates neural representations in the vOTC.
• Well-learned words exhibit enhanced representational differentiation in the brain.