Relationship of auditory electrophysiological responses to magnetic resonance spectroscopy metabolites in Early Phase Psychosis

Bartolomeo, Lisa A.; Wright, Andrew Martin; Ruoyun, E.; Hummer, Tom A.; Francis, Michael; Visco, Andrew; Mehdiyoun, Nicole F.; Bolbecker, Amanda R.; Hetrick, William P.; Dydak, Ulrike; Barnard, John; O’Donnell, Brian F.; Breier, Alan

doi:10.1016/j.ijpsycho.2019.05.009

Cited by 13 publications

(17 citation statements)

References 70 publications

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“…Consistent with our hypothesis, we found a reduction in 40-Hz-ASSR amplitudes in both FEP and CHR-P participants in auditory and thalamic regions. This contrasts with several recent EEG-studies that found intact 40-Hz-ASSRs in both CHR-P (27) and FEP-groups (28). One possible explanation are differences in recording techniques of 40-Hz-ASSRs.…”

Section: Discussioncontrasting

confidence: 98%

40 Hz Auditory Steady-State Responses Predict Transition to Psychosis in Clinical-High-Risk Participants: A MEG Study

Grent-‘t-Jong

Gajwani

Groß

et al. 2020

Preprint

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Objective: To examine whether 40-Hz Auditory Steady-State Responses (ASSR) in participants at clinical high-risk for psychosis predict clinical outcomes. Method: In this study, magnetoencephalography (MEG) data were collected during a 40-Hz ASSR paradigm in 116 participants meeting clinical high-risk (CHR-P) for psychosis criteria, a clinical control group characterized by affective disorders and/or substance abuse (CHR-N: n=38), 32 first-episode psychosis patients (FEP, 14 antipsychotic-naive), and 49 healthy controls. We examined 40-Hz-ASSR- source-activity in bilateral Heschl's gyrus, superior temporal gyrus, Rolandic operculum, and the thalamus. Group differences in ASSR amplitudes were tested and correlated with neuropsychological scores, psychosocial functioning, and clinical symptoms. Linear discriminant analyses was used to assess whether 40-Hz-ASSR predicts transition to psychosis and persistence of APS. Results: Compared to controls, 40-Hz-ASSR responses in CHR-Ps were impaired in right Rolandic operculum (d=0.41) and right thalamus (d=0.43), particularly in those with combined UHR/BS symptoms and CHR-Ps who transitioned to psychosis (n=11). FEP-patients showed significant impairments in the right thalamus (d=0.58), while the CHR-N group was unaffected. Importantly, right thalamus 40-Hz-ASSRs predicted transition to psychosis (transitioned [n=11] vs non-transitioned [n=105]); classification accuracy 73.3%, AUC=0.827), whereas this was not the case for persistent APS (Persistent [n=41] vs non-Persistent [n=37]; classification accuracy 56.4%). Conclusions: The current study indicates that MEG-recorded 40-Hz-ASSRs constitute a potential biomarker for predicting transition to psychosis in CHR-P participants.

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Section: Discussioncontrasting

confidence: 98%

40 Hz Auditory Steady-State Responses Predict Transition to Psychosis in Clinical-High-Risk Participants: A MEG Study

Grent-‘t-Jong

Gajwani

Groß

et al. 2020

Preprint

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“…Most of the studies examined multiple cognitive domains and used neuropsychological batteries: BACS [ 44 , 59 , 69 , 70 ], WAIS [ 75 ], ADAS-cog subscale [ 55 ], MATRICS MCCB [ 76 ], or different subtests from various batteries like WAIS [ 73 , 74 ] and PEBL [ 71 ]. Three of the studies evaluated only global cognitive functioning [ 59 , 61 , 69 ]. In contrast, some studies targeted at specific functions, e.g., short-term and working memory, applying digit span [ 72 ] or phonological awareness measured by a Spoonerism task [ 62 ].…”

Section: Resultsmentioning

confidence: 99%

“…The main ASSR outcome measures were power and phase synchronization/consistency; two studies provided signal-to-noise ratio evaluations [ 60 , 62 ], and one study provided individual gamma peak frequencies [ 58 ]. Most studies focused on the evaluation of the response during the entire stimulation duration [ 43 , 55 , 59 , 62 , 63 , 64 , 65 , 66 , 67 , 69 , 72 , 75 ]. Rass et al, Sun et al, and Gaskins et al did not include the early response (0–100 ms) part [ 60 , 73 , 74 , 76 ].…”

Section: Resultsmentioning

confidence: 99%

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Gamma-Range Auditory Steady-State Responses and Cognitive Performance: A Systematic Review

2021

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The auditory steady-state response (ASSR) is a result of entrainment of the brain’s oscillatory activity to the frequency and phase of temporally modulated stimuli. Gamma-range ASSRs are utilized to observe the dysfunctions of brain-synchronization abilities in neuropsychiatric and developmental disorders with cognitive symptoms. However, the link between gamma-range ASSRs and cognitive functioning is not clear. We systematically reviewed existing findings on the associations between gamma-range ASSRs and cognitive functions in patients with neuropsychiatric or developmental disorders and healthy subjects. The literature search yielded 1597 articles. After excluding duplicates and assessing eligibility, 22 articles were included. In healthy participants, the gamma-range ASSR was related to cognitive flexibility and reasoning as measured by complex tasks and behavioral indicators of processing speed. In patients with schizophrenia, the studies that reported correlations found a higher ASSR to be accompanied by better performance on short-term memory tasks, long-term/semantic memory, and simple speeded tasks. The main findings indicate that individual differences in the gamma-range ASSR reflect the level of attentional control and the ability to temporary store and manipulate the information, which are necessary for a wide range of complex cognitive activities, including language, in both healthy and impaired populations.

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“…Magnetic resonance spectroscopy (MRS), which is based on NRM principles, is widely being used along with magnetic resonance imaging (MRI) to acquire detailed information about the tissue structures for medical diagnosis [7][8][9]. MRS non-invasively provides information on the brain's metabolites concentrations, which aids the early detection of neurodegenerative diseases [10][11][12] The current developed techniques and software packages for MRS signal processing retain significant variance in the absolute metabolite quantification. Magnetic resonance (MR) spectra analysis methods can be classified as either black box (data-driven) or basis sets methods [8].…”

Section: Introductionmentioning

confidence: 99%

A Novel Data-Driven Magnetic Resonance Spectroscopy Signal Analysis Framework to Quantify Metabolite Concentration

et al. 2020

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Developing tools for precise quantification of brain metabolites using magnetic resonance spectroscopy (MRS) is an active area of research with broad application in non-invasive neurodegenerative disease studies. The tools are mainly developed based on black box (data-driven), or basis sets approaches. In this study, we offer a multi-stage framework that integrates data-driven and basis sets methods. We first use truncated Hankel singular value decomposition (HSVD) to decompose free induction decay (FID) signals into single tone FIDs, as the data-driven stage. Subsequently, single tone FIDs are clustered into basis sets while using initialized K-means with prior knowledge of the metabolites, as the basis set stage. The generated basis sets are fitted with the magnetic resonance (MR) spectra while using a linear constrained least square, and then the metabolite concentration is calculated. Prior to using our proposed multi-stage approach, a sequence of preprocessing blocks: water peak removal, phase correction, and baseline correction (developed in house) are used.

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Relationship of auditory electrophysiological responses to magnetic resonance spectroscopy metabolites in Early Phase Psychosis

Cited by 13 publications

References 70 publications

40 Hz Auditory Steady-State Responses Predict Transition to Psychosis in Clinical-High-Risk Participants: A MEG Study

40 Hz Auditory Steady-State Responses Predict Transition to Psychosis in Clinical-High-Risk Participants: A MEG Study

Gamma-Range Auditory Steady-State Responses and Cognitive Performance: A Systematic Review

A Novel Data-Driven Magnetic Resonance Spectroscopy Signal Analysis Framework to Quantify Metabolite Concentration

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