Modeling Task Effects on Meaning Representation in the Brain via Zero-Shot MEG Prediction
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Abstract (arXiv)
How meaning is represented in the brain is still one of the big open questions in neuroscience. Does a word (e.g., bird) always have the same representation, or does the task under which the word is processed alter its representation (answering "can you eat it?" versus "can it fly?")? The brain activity of subjects who read the same word while performing different semantic tasks has been shown to differ across tasks. However, it is still not understood how the task itself contributes to this difference. In the current work, we study Magnetoencephalography (MEG) brain recordings of participants tasked with answering questions about concrete nouns. We investigate the effect of the task (i.e. the question being asked) on the processing of the concrete noun by predicting the millisecond-resolution MEG recordings as a function of both the semantics of the noun and the task. Using this approach, we test several hypotheses about the task-stimulus interactions by comparing the zero-shot predictions made by these hypotheses for novel tasks and nouns not seen during training. We find that incorporating the task semantics significantly improves the prediction of MEG recordings, across participants. The improvement occurs 475-550ms after the participants first see the word, which corresponds to what is considered to be the ending time of semantic processing for a word. These results suggest that only the end of semantic processing of a word is task-dependent, and pose a challenge for future research to formulate new hypotheses for earlier task effects as a function of the task and stimuli.
Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). First posted on arXiv 17 Sep 2020.
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Citing papers per year: 2022: 2; 2023: 4; 2024: 0; 2025: 0; 2026: 1.
7 papers.
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- 2026HDND: Hierarchical Dynamic Neural Decoding for Multilingual Word/Character Retrieval from Non-Invasive Brain Recordingscited by 1
- 2026HDND: Hierarchical Dynamic Neural Decoding for Multilingual Word/Character Retrieval from Non-Invasive Brain Recordings21 Sep 2026
- 2023Getting aligned on representational alignment18 Oct 2023
- 2023Deep Neural Networks and Brain Alignment: Brain Encoding and Decoding (Survey)17 Jul 2023
- 2023Syntactic Structure Processing in the Brain while Listening16 Feb 2023
- 2023Language Cognition and Language Computation -- Human and Machine Language Understanding12 Jan 2023
- 2022Neural Language Models are not Born Equal to Fit Brain Data, but Training Helps7 Jul 2022
- 2022Neural Language Taskonomy: Which NLP Tasks are the most Predictive of fMRI Brain Activity?3 May 2022