2019 Fiscal Year Research-status Report
Hierarchical interactions of predictions and prediction errors in normal and schizophrenic brains
| Project/Area Number |
19K06906
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| Research Institution | The University of Tokyo |
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Principal Investigator |
Chao Zenas 東京大学, ニューロインテリジェンス国際研究機構, 准教授 (30532113)
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| Project Period (FY) |
2019-04-01 – 2022-03-31
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| Keywords | Predictive coding / Brain / Network / EEG |
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| Outline of Annual Research Achievements |
Research Aim #1 has been completed. We have collected and analyzed EEG data from 30 healthy participants, and are preparing for the paper in which we describe the neural activity components underlying prediction errors at two different hierarchies. We also propose a theoretical model that successfully explains the data, and provides a new way to analyze mismatch negativity (MMN) data that are commonly used for schizophrenia diagnosis.
Research Aim #2 is still ongoing. We have collected data with unimodal stimuli (auditory or visual), but still need to collect data with multimodal stimuli (audiovisual). The reason for the delay will be explained below.
Research Aim #3 is in preparation. We plan to first try an alternative plan: instead of collect EEG data from schizophrenic patients, we will apply the new method obtained from Aim #1 to re-analyze existing MMN data from patients.
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| Current Status of Research Progress |
Current Status of Research Progress
3: Progress in research has been slightly delayed.
Reason
We have finished Research Aim #1 as planned, and are in the process to submit a paper. Research Aim #2, which we expected to finish by now, is only half way through. The main reason is the Principal Investigator moved from Kyoto University to the University of Tokyo in FY2020, and experiments required a new setup. After the moving, the experiment was further delayed due to the coronavirus outbreak. We plan to resume and speed up the data collection for Aim #2 in September 2020. Regarding the Aim #3, we need to regain the access of schizophrenic patients at the University Tokyo Hospital, which will take more time. But meanwhile we plan to apply a new analytical pipeline to re-analyze existing MMN data in schizophrenic patients based on our findings in Aim #1.
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| Strategy for Future Research Activity |
Our strategy to promote our research findings is to clearly identify who can make use of the findings and how to get the findings to them with minimal delay and maximal benefits. The target audiences of the proposed study are not only brain scientists, but also AI researchers and mental health clinicians. We will reach out to them through publications in scientific journals, scientific conferences, and workshops and courses. Furthermore, to channel our findings to the general public, we will utilize not only the social media but also scientific exhibitions such as the IRCN Outreach project with NOMURA Co., Ltd, which will be launched in Miraikan (Science Museum) in late 2020. I will also share my findings in college lecture series (e.g. Introduction of Neurointelligence” at the University of Tokyo), and in high-school student programs that are regularly held by WPI-IRCN.
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| Causes of Carryover |
I have set up a new EEG system at the University of Tokyo, and will need to replace an EEG electrode cap. Other than this main purchase, I will need to purchase a small workstation for data analysis.
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Research Products
(3 results)
