Altered amplitude of low frequency fluctuations in schizophrenia patients with persistent auditory verbal hallucinations

Alonso-Solís, Anna; Vives-Gilabert, Yolanda; Portella, Marı́a J.; Rabella, Mireia; Grasa, Eva; Roldán, Alexandra; Keymer-Gausset, Alejandro; Molins, Conrad; Núñez-Marín, Fidel; Gómez‐Anson, Beatriz; Álvarez, Enric; Corripio, Iluminada

doi:10.1016/j.schres.2017.01.042

Cited by 47 publications

(28 citation statements)

References 42 publications

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“…Looking at the frequency profile of these cluster pairs we can see that, cluster pairs 7 and 8 are in the high-pass group while pairs 4 and 6 are in the band-pass group. This seems in line with some previous studies where it was reported that in activity space SZs have higher power at higher frequencies compared to TCs (Abigail G. Garrity , et al, 2007;Alonso-Solis, et al, 2017). Unlike these studies, we have found alterations in the frequency profile of connectivity instead of activity.…”

Section: Sz Connectivity Patterns Have Higher Frequencies Compared Tosupporting

confidence: 93%

“…This observation has been reported in other studies as well (Alonso-Solis, et al, 2017;Calhoun, et al, 2012;Hare, et al, 2017;Hoptman, et al, 2010). On the other hand, Alonso-Solis et al report that ALFF for SZ is higher than that of TCs in insula (Alonso-Solis, et al, 2017). So it seems reasonable to think that the relationship between ALFF differences in SZs and TCs are different for different regions.…”

Section: Schizophrenia-related Findingssupporting

confidence: 72%

“…In addition, Fryer et al used voxel wise amplitude of low-frequency fluctuations (ALFF) between frequencies 0.01-0.08 to find that SZs have lower ALFF compared to TCs especially in posterior cortex, occipital and cerebellar lobes (Fryer, et al, 2016). This observation has been reported in other studies as well (Alonso-Solis, et al, 2017;Calhoun, et al, 2012;Hare, et al, 2017;Hoptman, et al, 2010). On the other hand, Alonso-Solis et al report that ALFF for SZ is higher than that of TCs in insula (Alonso-Solis, et al, 2017).…”

Section: Schizophrenia-related Findingsmentioning

confidence: 87%

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A unified approach for characterizing static/dynamic connectivity frequency profiles using filter banks

Faghiri

Iraji

Damaraju

et al. 2019

Preprint

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Studying dynamic functional connectivity (dFC) has been the focus of many studies in recent years. The most commonly used estimator for dFC uses a sliding window in combination with a connectivity estimator such as Pearson correlation. Here, we propose a new approach to estimate connectivity while preserving its full frequency range and subsequently examine both static and dynamic connectivity in one unified approach. This approach which we call filter banked connectivity (FBC), implements frequency tiling directly in the connectivity domain contrary to other studies where frequency tiling is done in the activity domain. This leads to more accurate modeling, and a unified approach to capture connectivity ranging from static to highly dynamic, avoiding the need to pick a specific band as in a sliding window approach.First, we demonstrated that our proposed approach, can estimate connectivity at frequencies that sliding window approach fails. Next we evaluated the ability of the approach to identify group differences by using the FBC approach to estimate dFNC in a resting fMRI data set including schizophrenia patients (SZ, n=151) and typical controls (TC, n=163). To summarize the results, we used k-means to cluster the FBC values into different clusters. Some states showed very weak low frequency strength and as such SWPC was not well suited to capture them. Additionally, we found that SZs tend to spend more time in states exhibiting higher frequencies and engaging the default mode network and its anticorrelations with other networks compared to TCs which spent more time in lower frequency states which primarily includes strong intercorrelations within the sensorimotor domains. In summary, the proposed approach offers a novel way to estimate connectivity while unifying static and dynamic connectivity analyses and can provide additional otherwise missed information about the frequency profile of connectivity patterns.

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Section: Sz Connectivity Patterns Have Higher Frequencies Compared Tosupporting

confidence: 93%

Section: Schizophrenia-related Findingssupporting

confidence: 72%

Section: Schizophrenia-related Findingsmentioning

confidence: 87%

See 1 more Smart Citation

A unified approach for characterizing static/dynamic connectivity frequency profiles using filter banks

Faghiri

Iraji

Damaraju

et al. 2019

Preprint

View full text Add to dashboard Cite

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“…In previous models including the “memory intrusion”, “self-monitoring”, “two hit bottom-up and top-down”, and hybrid models, language, auditory, and memory brain networks were closely associated with AVH in patients with schizophrenia ( 4 ). The superior temporal gyrus (STG) (auditory cortex), Broca’s area (speech production), Wernicke’s area (language comprehension), hippocampus (memory retrieval), and putamen (initiating language representations) are the key areas responsible for AVH in schizophrenia, and showed functional alterations in previous brain imaging studies ( 5 – 18 ). Although aberrant FC associated with AVH has been reported in these regions in many resting-state fMRI studies ( 6 , 7 , 15 , 16 , 19 – 25 ), the interactions between these regions have not been described completely.…”

Section: Introductionmentioning

confidence: 99%

Altered Effective Connectivity in Schizophrenic Patients With Auditory Verbal Hallucinations: A Resting-State fMRI Study With Granger Causality Analysis

et al. 2020

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Purpose Auditory verbal hallucinations (AVH) are among the most common and prominent symptoms of schizophrenia. Although abnormal functional connectivity associated with AVH has been reported in multiple regions, the changes in information flow remain unclear. In this study, we aimed to elucidate causal influences related to AVH in key regions of auditory, language, and memory networks, by using Granger causality analysis (GCA). Patients and Methods Eighteen patients with schizophrenia with AVH and eighteen matched patients without AVH who received resting-state fMRI scans were enrolled in the study. The bilateral superior temporal gyrus (STG), Broca’s area, Wernicke’s area, putamen, and hippocampus were selected as regions of interest. Results Granger causality (GC) increased from Broca’s area to the left STG, and decreased from the right homolog of Wernicke’s area to the right homolog of Broca’s area, and from the right STG to the right hippocampus in the AVH group compared with the non-AVH group. Correlation analysis showed that the normalized GC ratios from the left STG to Broca’s area, from the left STG to the right homolog of Broca’s area, and from the right STG to the right homolog of Broca’s area were negatively correlated with severity of AVH, and the normalized GC ratios from Broca’s area to the left hippocampus and from Broca’s area to the right STG were positively correlated with severity of AVH. Conclusion Our findings indicate a causal influence of pivotal regions involving the auditory, language, and memory networks in schizophrenia with AVH, which provide a deeper understanding of the neural mechanisms underlying AVH.

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“…The neural activation in the visual cortex has been found to be related to ALFF at around 0.034 Hz (Kiviniemi et al, ), implying that ALFF represents regional spontaneous neuronal activity. On the basis of neuro‐electrophysiological findings, ALFF is considered to be biologically or physiologically significant in healthy brain (Mohamed, Yousem, Tekes, Browner, & Calhoun, ) and also involved in the pathogenesis of schizophrenia as reported by an increasing number of recent studies (Alonso‐Solis et al, ; Chyzhyk, Grana, Ongur, & Shinn, ; Fu et al, ; Li, Lei et al, ; Lian et al, ; Lui et al, ; Sui et al, ; Yu et al, ; Zhang et al, ). Previous studies have observed a marked attenuation of ALFF in the postcentral gyrus and parahippocampus and an augmentation in the putamen in medication‐naïve first‐episode schizophrenia patients relative to a healthy population (Cui et al, ), as well as abnormal ALFF within resting‐state networks (Cui, Liu et al, ).…”

Section: Introductionmentioning

confidence: 99%

Prediction of early response to overall treatment for schizophrenia: A functional magnetic resonance imaging study

et al. 2019

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Introduction Treatment response at an early stage of schizophrenia is of considerable value with regard to future management of the disorder; however, there are currently no biomarkers that can inform physicians about the likelihood of response. Objects We aim to develop and validate regional brain activity derived from functional magnetic resonance imaging (fMRI) as a potential signature to predict early treatment response in schizophrenia. Methods Amplitude of low‐frequency fluctuation (ALFF) was measured at the start of the first/single episode resulting in hospitalization. Inpatients were included in a principal dataset ( n = 79) and a replication dataset ( n = 44). Two groups of healthy controls ( n = 87; n = 106) were also recruited for each dataset. The clinical response was assessed at discharge from the hospital. The predictive capacity of normalized ALFF in patients by healthy controls, ALFF ratio , was evaluated based on diagnostic tests and clinical correlates. Results In the principal dataset, responders exhibited increased baseline ALFF in the left postcentral gyrus/inferior parietal lobule relative to non‐responders. ALFF ratio of responders before treatment was significantly higher than that of non‐responders ( p < 0.001). The area under the receiver operating characteristic curve was 0.746 for baseline ALFF ratio to distinguish responders from non‐responders, and the sensitivity, specificity, and accuracy were 72.7%, 68.6%, and 70.9%, respectively. Similar results were found in the independent replication dataset. Conclusions Baseline regional activity of the brain seems to be predictive of early response to treatment for schizophrenia. This study shows that psycho‐neuroimaging holds promise for influencing the clinical treatment and management of schizophrenia.

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Altered amplitude of low frequency fluctuations in schizophrenia patients with persistent auditory verbal hallucinations

Cited by 47 publications

References 42 publications

A unified approach for characterizing static/dynamic connectivity frequency profiles using filter banks

A unified approach for characterizing static/dynamic connectivity frequency profiles using filter banks

Altered Effective Connectivity in Schizophrenic Patients With Auditory Verbal Hallucinations: A Resting-State fMRI Study With Granger Causality Analysis

Prediction of early response to overall treatment for schizophrenia: A functional magnetic resonance imaging study

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