Auditory Mismatch Negativity Under Predictive Coding Framework and Its Role in Psychotic Disorders

Fong, Chun Yuen; Law, Wai Him Crystal; Uka, Takanori; Koike, Shinsuke

doi:10.3389/fpsyt.2020.557932

Cited by 19 publications

(18 citation statements)

References 176 publications

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“…information processing which may reflect altered predictive coding in schizophrenia. [126][127][128] The amplitude of MMN (especially duration MMN) is reduced in chronic schizophrenia, first-episode schizophrenia, and even at the clinical highrisk state. 125,129 Mechanistically, this reduced MMN amplitude may reflect N-methyl-D-aspartate receptor (NMDAR) dysfunction in patients with schizophrenia since NMDAR antagonists reduce the MMN amplitude.…”

Section: Interpretation To Other Brain Measurements: Eeg and Meg Research In Schizophreniamentioning

confidence: 99%

Recent Advances and Future Directions in Brain MR Imaging Studies in Schizophrenia: Toward Elucidating Brain Pathology and Developing Clinical Tools

et al. 2022

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Schizophrenia is a common severe psychiatric disorder that affects approximately 1% of general population through the life course. Historically, in Kraepelin's time, schizophrenia was a disease unit conceptualized as dementia praecox; however, since then, the disease concept has changed. Recent MRI studies had shown that the neuropathology of the brain in this disorder was characterized by mild progression before and after the onset of the disease, and that the brain alterations were relatively smaller than assumed. Although genetic factors contribute to the brain alterations in schizophrenia, which are thought to be trait differences, other changes include factors that are common in psychiatric diseases. Furthermore, it has been shown that the brain differences specific to schizophrenia were relatively small compared to other changes, such as those caused by brain development, aging, and gender. In addition, compared to the disease and participant factors, machine and imaging protocol differences could affect MRI signals, which should be addressed in multi-site studies. Recent advances in MRI modalities, such as multi-shell diffusion-weighted imaging, magnetic resonance spectroscopy, and multimodal brain imaging analysis, may be candidates to sharpen the characterization of schizophrenia-specific factors and provide new insights. The Brain/MINDS Beyond Human Brain MRI (BMB-HBM) project has been launched considering the differences and noises irrespective of the disease pathologies and includes the future perspectives of MRI studies for various psychiatric and neurological disorders. The sites use restricted MRI machines and harmonized multi-modal protocols, standardized image preprocessing, and traveling subject harmonization. Data sharing to the public will be planned in FY 2024. In the future, we believe that combining a high-quality human MRI dataset with genetic data, randomized controlled trials, and MRI for non-human primates and animal models will enable us to understand schizophrenia, elucidate its neural bases and therapeutic targets, and provide tools for clinical application at bedside.

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Section: Interpretation To Other Brain Measurements: Eeg and Meg Research In Schizophreniamentioning

confidence: 99%

Recent Advances and Future Directions in Brain MR Imaging Studies in Schizophrenia: Toward Elucidating Brain Pathology and Developing Clinical Tools

et al. 2022

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“…Perception is a process where error signals nudge generative models into forms which minimise the prediction error, thereby offering the best explanation of the sensory input. In this framework, the repetition suppression of the N1 response to the standard is due to a dampening of the sensory signal by a successful prediction signal (Auksztulewicz and Friston, 2016) and the MMN to the deviant is a prediction error signal (Garrido et al, 2009;Wacongne et al, 2012;Chennu et al, 2013;Lieder et al, 2013a,b;Rentzsch et al, 2015;Carbajal and Malmierca, 2018;Fong et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

The Adaptation Model Offers a Challenge for the Predictive Coding Account of Mismatch Negativity

May

2021

Front. Hum. Neurosci.

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An unpredictable stimulus elicits a stronger event-related response than a high-probability stimulus. This differential in response magnitude is termed the mismatch negativity (MMN). Over the past decade, it has become increasingly popular to explain the MMN terms of predictive coding, a proposed general principle for the way the brain realizes Bayesian inference when it interprets sensory information. This perspective article is a reminder that the issue of MMN generation is far from settled, and that an alternative model in terms of adaptation continues to lurk in the wings. The adaptation model has been discounted because of the unrealistic and simplistic fashion in which it tends to be set up. Here, simulations of auditory cortex incorporating a modern version of the adaptation model are presented. These show that locally operating short-term synaptic depression accounts both for adaptation due to stimulus repetition and for MMN responses. This happens even in cases where adaptation has been ruled out as an explanation of the MMN (e.g., in the stimulus omission paradigm and the multi-standard control paradigm). Simulation models that would demonstrate the viability of predictive coding in a similarly multifaceted way are currently missing from the literature, and the reason for this is discussed in light of the current results.

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“…In future research, it might be important to further examine the early perceptual deficits and their influence on the consecutive phoneme perception and language comprehension processes. The precise neural mechanisms underlying the MMN remain unclear but one of the theories that have been used to explain the manifestation of the MMN is the predictive coding theory (Chennu et al, 2013;Fitzgerald and Todd, 2020;Fong et al, 2020). According to this theory, the MMN reflects the level of prediction error when an unexpected stimulus is presented.…”

Section: Discussionmentioning

confidence: 99%

“…The precise neural mechanisms underlying the MMN remain unclear but one of the theories that have been used to explain the manifestation of the MMN is the predictive coding theory (Chennu et al, 2013 ; Fitzgerald and Todd, 2020 ; Fong et al, 2020 ). According to this theory, the MMN reflects the level of prediction error when an unexpected stimulus is presented.…”

Section: Discussionmentioning

confidence: 99%

The Electrophysiological Correlates of Phoneme Perception in Primary Progressive Aphasia: A Preliminary Case Series

Stalpaert

Miatton

Sieben

et al. 2021

Front. Hum. Neurosci.

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Aims: This study aimed to investigate phoneme perception in patients with primary progressive aphasia (PPA) by using the event-related potential (ERP) technique. These ERP components might contribute to the diagnostic process of PPA and its clinical variants (NFV: nonfluent variant, SV: semantic variant, LV: logopenic variant) and reveal insights about phoneme perception processes in these patients.Method: Phoneme discrimination and categorization processes were investigated by the mismatch negativity (MMN) and P300 in eight persons with early- and late-stage PPA (3 NFV, 2 LV, 2 SV, and 1 PPA-NOS; not otherwise specified) and 30 age-matched healthy adults. The mean amplitude, the onset latency, and the topographic distribution of both components in each patient were compared to the results of the control group.Results: The MMN was absent or the onset latency of the MMN was delayed in the patients with the NFV, LV, and PPA-NOS in comparison to the control group. In contrast, no differences in mean amplitudes and onset latencies of the MMN were found between the patients with the SV and the control group. Concerning the P300, variable results were found in the patients with the NFV, SV, and PPA-NOS, but the P300 of both patients with the LV was delayed and prolonged with increased mean amplitude in comparison to the control group.Conclusion: In this preliminary study, phoneme discrimination deficits were found in the patients with the NFV and LV, and variable deficits in phoneme categorization processes were found in all patients with PPA. In clinical practice, the MMN might be valuable to differentiate the SV from the NFV and the LV and the P300 to differentiate the LV from the NFV and the SV. Further research in larger and independent patient groups is required to investigate the applicability of these components in the diagnostic process and to determine the nature of these speech perception deficits in the clinical variants of PPA.

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Auditory Mismatch Negativity Under Predictive Coding Framework and Its Role in Psychotic Disorders

Cited by 19 publications

References 176 publications

Recent Advances and Future Directions in Brain MR Imaging Studies in Schizophrenia: Toward Elucidating Brain Pathology and Developing Clinical Tools

Recent Advances and Future Directions in Brain MR Imaging Studies in Schizophrenia: Toward Elucidating Brain Pathology and Developing Clinical Tools

The Adaptation Model Offers a Challenge for the Predictive Coding Account of Mismatch Negativity

The Electrophysiological Correlates of Phoneme Perception in Primary Progressive Aphasia: A Preliminary Case Series

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