シンポジウム
42 双方向トランスレーショナル研究による精神疾患でみられる聴覚予測性障害の解明
42 Elucidating the impairment of auditory predictive function in psychiatric disorders by bi-directional translational research
座長：小池 進介（東京大学大学院総合文化研究科進化認知科学研究センター）・小松 三佐子（理化学研究所 脳神経科学研究センター） |
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| 2022年7月2日 16:10～16:34 沖縄コンベンションセンター 会議場A1 第2会場
3S02e-01
統合失調症における脳予測性の障害：臨床脳波研究
Altered predictive coding in schizophrenia: Clinical EEG studies
*切原 賢治(1,2)、多田 真理子(2,3)、越山 太輔(2)、藤岡 真生(2)、臼井 香(2)、西村 亮一(2)、荒木 剛(2,4)、笠井 清登(2)
1. 東京大学バリアフリー支援室、2. 東京大学医学部附属病院精神神経科、3. 東京大学相談支援研究開発センター精神保健支援室、4. 帝京大学医学部附属溝口病院精神科
*Kenji Kirihara(1,2), Mariko Tada(2,3), Daisuke Koshiyama(2), Mao Fujioka(2), Kaori Usui(2), Ryoichi Nishimura(2), Tsuyoshi Araki(2,4), Kiyoto Kasai(2)
1. Disability Services Office, The University of Tokyo, Tokyo, Japan, 2. Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan, 3. Office for Mental Health Support, Center for Research on Counseling and Support Services, The University of Tokyo, Tokyo, Japan, 4. Department of Psychiatry, Teikyo University Hospital, Mizonokuchi, Kawasaki, Japan
Keyword: predictive coding, schizophrenia, mismatch negativity, EEG
Mismatch negativity (MMN) is one of event-related potentials that is often measured with electroencephalography (EEG). Previous studies reported that MMN amplitude was reduced in schizophrenia and that reduced MMN amplitude was associated with cognitive impairments and poor functional outcome in schizophrenia. These findings suggest that clarifying neural mechanisms underlying reduced MMN amplitude may contribute to understanding pathophysiology of schizophrenia and development of new therapeutics for schizophrenia.
Recent studies suggest that altered predictive coding can explain clinical symptoms such as psychotic symptoms in schizophrenia. Predictive coding can also explain MMN, and reduction of MMN amplitude is thought to reflect altered predictive coding in schizophrenia. However, other hypotheses such as sensory-specific adaptation can also explain MMN. Therefore, it is important to investigate whether predictive coding can explain reduced MMN amplitude in schizophrenia better than other mechanisms or not.
Auditory oddball tasks are often used for measurement of MMN. However, both predictive coding and other mechanisms can explain MMN in oddball tasks. Therefore, several tasks have been developed to investigate what mechanisms underlie MMN. We used oddball tasks and many standards tasks to differentiate between predictive coding and sensory specific adaptation as underlying mechanisms of MMN. We found that patients with schizophrenia showed impairments in not sensory specific adaptation but predictive coding.
Several studies including our study indicate that altered predictive coding underlies reduced MMN amplitude in schizophrenia. These findings suggest that patients with schizophrenia may have impairments in neural circuits underlying predictive coding. However, clinical EEG studies cannot reveal detailed neural circuits underlying predictive coding because EEG has low spatial resolution. In order to clarify neural circuits underlying predictive coding, more invasive methods such as electrocorticography and translational studies using other animals are necessary. The bi-directional translational studies research will clarify neural circuits underlying predictive coding that is impaired in schizophrenia. | | 2022年7月2日 16:34～16:58 沖縄コンベンションセンター 会議場A1 第2会場
3S02e-02
Constructing the Hierarchy of Predictive Auditory Sequences in the Marmoset Brain
*Liping Wang(1), Yuwei Jiang(1), Misako Komatsu(2), Yuyan Chen(1), Ruoying Xie(1), Kaiwei Zhang(1), Ying Xia(1), Peng Gui(1), Zhifeng Liang (1)
1. CEBSIT, CAS, Shanghai, China, 2. Center for Brain Science, RIKEN, Saitama, Japan
Keyword: PREDICTIVE CODING, AUDITORY SEQUENCE, ELECTROCORTICOGRAPHY, FUNCTIONAL MAGNETIC RESONANCE IMAGING
Our brains constantly generate predictions of sensory input that are compared with actual inputs, propagate the prediction-errors through a hierarchy of brain regions, and subsequently update the internal predictions of the world. However, the essential feature of predictive coding, the notion of hierarchical depth and its neural mechanisms, remains largely unexplored. Here, we investigated the hierarchical depth of predictive auditory processing by combining functional magnetic resonance imaging (fMRI) and high-density whole-brain electrocorticography (ECoG) in marmoset monkeys during an auditory local-global paradigm in which the temporal regularities of the stimuli were designed at two hierarchical levels. The prediction-errors and prediction updates were examined as neural responses to auditory mismatches and omissions. Using fMRI, we identified a hierarchical gradient along the auditory pathway: midbrain and sensory regions represented local, shorter-time-scale predictive processing followed by associative auditory regions, whereas anterior temporal and prefrontal areas represented global, longer-time-scale sequence processing. The complementary ECoG recordings confirmed the activations at cortical surface areas and further differentiated the signals of prediction-error and update, which were transmitted via putative bottom-up g and top-down b oscillations, respectively. Furthermore, omission responses caused by absence of input, reflecting solely the two levels of prediction signals that are unique to the hierarchical predictive coding framework, demonstrated the hierarchical top-down process of predictions in the auditory, temporal, and prefrontal areas. Thus, our findings support the hierarchical predictive coding framework, and outline how neural networks and spatiotemporal dynamics are used to represent and arrange a hierarchical structure of auditory sequences in the marmoset brain. | | 2022年7月2日 16:58～17:22 沖縄コンベンションセンター 会議場A1 第2会場
3S02e-03
Proactive and frequency-specific prediction signals in hierarchical predictive coding
*Zenas C Chao(1), Yi-Yuan Huang(1), Chien-Te Wu(1)
1. IRCN, University of Tokyo
Keyword: Predictive coding, Hierarchy, Cortical oscillation, EEG
The ascending auditory stream of the human brain is a canonical cortical sensory network with a diverse class of feed-forward prediction-error and feedback prediction signals. While prediction-error signals are well described, the identification of prediction signals has remained elusive. Here, we identified and characterized hierarchical prediction signals in the human brain. We recorded EEG data during a local-global auditory paradigm and generated a hierarchical signal dependence model to analyze the results with a tensor decomposition analysis. Prior to auditory input, we identified a lower-level prediction signal representing the tone-to-tone transition in the high beta frequency band. This was accompanied by a higher-level prediction signal for multi-tone sequence structure in the low beta band. Subsequently, prediction-error signals dependent on the prior predictions were found in the gamma band. These findings reveal the existence and flow of hierarchical prediction signals in human brain confirming a core tenet of predictive-coding theory. | | 2022年7月2日 17:22～17:46 沖縄コンベンションセンター 会議場A1 第2会場
3S02e-04
聴覚予測における前頭側頭回路トップダウン信号の役割
The role of top-down signals in the frontotemporal circuit on auditory predictions
*小松 三佐子(1,2)
1. 東京工業大学科学技術創成研究院、2. 理化学研究所脳神経科学研究センター
*Misako Komatsu(1,2)
1. Institute of Innovative Research, Tokyo Institute of Technology, Kanagawa, Japan, 2. RIKEN Center for Brain Science, Saitama, Japan
Keyword: MARMOSET, OPTOGENETICS, ELECTROCORTICOGRAPHY, ECOG
In everyday life, we consciously and unconsciously predict how the environment changes based on sensory inputs. Especially, auditory prediction is fundamental to survive in the natural environment and to communicate with others. To investigate cortical-wide auditory prediction processing, we developed a large-scale electrocorticographic (ECoG) array for the common marmoset, a small non-human primate. The array provides an opportunity to capture global cortical information processing with high resolutions at a sub-millisecond order in time and millimeter order in space. We have applied this system to marmosets exposed several auditory stimuli involved in different auditory predictions. The results indicated that frontotemporal circuit involves in auditory predictions. Then, we examined causal relations of signals from the frontal to temporal cortex. We induced AAV-CAG-ArchT into the prefrontal cortex of a marmoset, and conducted optogenetic inhibition in temporal cortex of the animal exposed auditory two-tone oddball stimuli. We found that the inhibition of the signals from the frontal to temporal cortex lead to diminish mismatch negativity observed in the auditory areas in normal condition without the optogenetic manipulations. These results suggested that frontal top-down signal to the temporal cortex is essential to generate mismatch related activity in auditory prediction. Overall, our optogenetic system provides a candidates for animal models with abnormal frontotemporal circuit. Dysfunctions of this circuit has been reported to be associated with schizophrenia, and the reduction of the amplitude of mismatch negativity has also been reported in patients with schizophrenia. Within this framework, our optogenetic system would contribute to better understanding to the development of the animal model of the psychiatric disorder. | | 2022年7月2日 17:46～18:10 沖縄コンベンションセンター 会議場A1 第2会場
3S02e-05
ヒトECoGによる聴覚予測機能の研究
Human ECoG study on auditory predictive function
*國井 尚人(1)、高砂 恵(1)、石下 洋平(2,1)、永田 圭亮(1)、藤谷 茂太(1)、嶋田 勢二郎(1)、多田 真理子(1)、切原 賢治(1)、小松 三佐子(3)、宇賀 貴紀(4)、笠井 清登(1)、齊藤 延人(1)
1. 東京大学、2. 自治医科大学、3. 理化学研究所、4. 山梨大学
*Naoto Kunii(1), Megumi Takasago(1), Yohei Ishishita(2,1), Keisuke Nagata(1), Shigeta Fujitani(1), Seijiro Shimada(1), Mariko Tada(1), Kenji Kirihara(1), Misako Komatsu(3), Takanori Uka(4), Kiyoto Kasai(1), Nobuhito Saito(1)
1. The University of Tokyo, 2. Jichi Medical University, 3. RIKEN, 4. University of Yamanashi
Keyword: prediction, electrocorticography, human, mismatch
Human electrocorticogram (ECoG) allows us to observe temporal changes of human brain activity with high spatial resolution. On the other hand, ECoG does not reflect the pathophysiology of psychiatric disorders because the subjects are patients with drug-resistant epilepsy. Because of these characteristics, this human ECoG study is positioned as a bridge between human EEG and macaque marmoset ECoG study in bidirectional translational research on the pathogenesis of psychiatric disorders. We first investigated the ECoG correspondence of the mismatch negativity (MMN)using an auditory mismatch task shared among the research teams. Taking advantage of the high spatiotemporal resolution, we found that N1, a lower-order auditory response, can be spatiotemporally separated from MMN. This indicates that MMN is different from N1 adaptation. We then examined the localization of the components of the mismatch response using the high-frequency oscillation of the brain, which is more feasible for localization analysis. Using group-level analysis of brain activity from multiple cases, we found that the prediction error was a major component of the mismatch response and was localized in the superior temporal gyrus (STG). Although the above mismatch response is a prediction error response to sound frequency deviation, it is known that the response to duration deviation is more sensitive as a biomarker of psychiatric disorders. Therefore, we compared the responses to frequency and duration mismatch, and revealed that the prediction error responses to each mismatch behaves differently in STG and that the prediction-related response of the frontal lobe is involved only in frequency mismatch. Based on these results, we are now collaborating among the research teams to develop a novel auditory prediction task and analyze prediction-related responses. | | | |
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