Reassessing prediction in the brain: Pre-onset neural encoding during natural listening does not reflect pre-activation

Fuente: arXiv
Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Azizpour, Sahel, Westner, Britta U., Szewczyk, Jakub, Güçlü, Umut, Geerligs, Linda
Format: Preprint
Veröffentlicht: 2024
Schlagworte:
Online-Zugang:
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
_version_ 1866917451566940160
author Azizpour, Sahel
Westner, Britta U.
Szewczyk, Jakub
Güçlü, Umut
Geerligs, Linda
author_facet Azizpour, Sahel
Westner, Britta U.
Szewczyk, Jakub
Güçlü, Umut
Geerligs, Linda
contents Predictive processing theories propose that the brain continuously anticipates upcoming input. However, direct neural evidence for predictive pre-activation during natural language comprehension remains limited and debated. Previous studies using large language model (LLM)-based encoding models with fMRI and ECoG have reported pre-onset signals that appear to encode upcoming words, but these effects may instead reflect dependencies in the stimulus or autocorrelations in neural activity. Here, we re-examined this question by aligning LLM-derived word embeddings with neural activity recorded during naturalistic listening using magnetoencephalography (MEG) and electrocorticography (ECoG). We replicated pre-onset encoding effects previously observed in ECoG across both modalities, and found that they persist even after controlling for stimulus correlations. Crucially, temporal generalization analyses revealed no stable overlap between pre- and post-onset representations, indicating that pre-onset activity does not reflect pre-activation of the next word. Consistent with this, long-range predictive effects previously reported in fMRI did not replicate in our higher-temporal-resolution data. While we found no evidence for predictive pre-activation, we observed clear signatures of postdiction, with neural activity reflecting persistent encoding of prior words. These results suggest that reported apparent predictive signals do not reflect pre-activation of upcoming input. They call for caution in interpreting LLM-based encoding models and highlight the need for a more nuanced understanding of what constitutes "prediction" in language comprehension.
format Preprint
id arxiv_https___arxiv_org_abs_2412_19622
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Reassessing prediction in the brain: Pre-onset neural encoding during natural listening does not reflect pre-activation
Azizpour, Sahel
Westner, Britta U.
Szewczyk, Jakub
Güçlü, Umut
Geerligs, Linda
Neurons and Cognition
Predictive processing theories propose that the brain continuously anticipates upcoming input. However, direct neural evidence for predictive pre-activation during natural language comprehension remains limited and debated. Previous studies using large language model (LLM)-based encoding models with fMRI and ECoG have reported pre-onset signals that appear to encode upcoming words, but these effects may instead reflect dependencies in the stimulus or autocorrelations in neural activity. Here, we re-examined this question by aligning LLM-derived word embeddings with neural activity recorded during naturalistic listening using magnetoencephalography (MEG) and electrocorticography (ECoG). We replicated pre-onset encoding effects previously observed in ECoG across both modalities, and found that they persist even after controlling for stimulus correlations. Crucially, temporal generalization analyses revealed no stable overlap between pre- and post-onset representations, indicating that pre-onset activity does not reflect pre-activation of the next word. Consistent with this, long-range predictive effects previously reported in fMRI did not replicate in our higher-temporal-resolution data. While we found no evidence for predictive pre-activation, we observed clear signatures of postdiction, with neural activity reflecting persistent encoding of prior words. These results suggest that reported apparent predictive signals do not reflect pre-activation of upcoming input. They call for caution in interpreting LLM-based encoding models and highlight the need for a more nuanced understanding of what constitutes "prediction" in language comprehension.
title Reassessing prediction in the brain: Pre-onset neural encoding during natural listening does not reflect pre-activation
topic Neurons and Cognition
url https://arxiv.org/abs/2412.19622