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427 results on '"Mervaala, Esa"'

1. Navigated and individual [alpha]-peak-frequency-guided transcranial magnetic stimulation in male patients with t aper)

Author

Tuppurainen, Heli, Maatta, Sara, Kononen, Mervi, Julkunen, Petro, Kautiainen, Hannu, Hyvarinen, Soile, Vaurio, Olli, Joensuu, Mikko, Vanhanen, Matti, Aho-Mustonen, Kati, Mervaala, Esa, and Tiihonen, Jari

Subjects
Medical research -- Health aspects, Medicine, Experimental -- Health aspects, Schizophrenia -- Care and treatment -- Research, Depression, Mental -- Care and treatment -- Research, Psychology, Pathological -- Research -- Health aspects, Lamotrigine -- Research, Electroencephalography -- Health aspects -- Research, Health, Psychology and mental health
Abstract

Background: Previous electroencephalography (EEG) studies have indicated altered brain oscillatory [alpha]-band activity in schizophrenia, and treatment with repetitive transcranial magnetic stimulation (rTMS) using individualized [alpha]-frequency has shown therapeutic effects. Magnetic resonance imaging-based neuronavigation methods allow stimulation of a specific cortical region and improve targeting of rTMS; therefore, we sought to study the efficacy of navigated, individual [alpha]-peak-frequency-guided rTMS ([alpha]TMS) on treatment-refractory schizophrenia. Methods: We recruited medication-refractory male patients with schizophrenia or schizoaffective disorder in this double-blind, sham-controlled study. We randomized patients to a 3-week course of either active [alpha]TMS or sham stimulation applied to the left dorsolateral prefrontal cortex (DLPFC). We assessed participants with the Positive and Negative Syndrome Scale (PANSS) and the Clinical Global Impression Scale (CGI) at baseline and after treatment. We conducted a follow-up assessment with the PANSS 3 months after intervention. Results: We included 44 patients. After treatment, we observed a significantly lower PANSS total score (p = 0.029), PANSS general psychopathology score (p = 0.027) and PANSS 5-factor model cognitive-disorganized factor score (p = 0.011) in the [alpha]TMS group than the sham group. In addition, the CGI-Improvement score was significantly higher among those who received [alpha]TMS compared with sham stimulation (p = 0.048). Limitations: The limited number of study participants included only male patients. Depression was not formally evaluated. Conclusion: Navigated [alpha]TMS to the left DLPFC reduced total, general psychopathological, and cognitive-disorganized symptoms of schizophrenia. These results provide evidence for the therapeutic efficacy of individual [alpha]-peak-frequency-guided rTMS in treatment-refractory schizophrenia. Clinical trial registration: NCT01941251; ClinicalTrials.gov, Introduction Around 30% of patients with schizophrenia are mostly unresponsive to antipsychotic medication. (1) Treatment resistance usually refers to persistent positive symptoms, although negative and cognitive symptoms may be the [...]

Published
2024
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6. Navigated and individual α-peak-frequency–guided transcranial magnetic stimulation in male patients with treatment-refractory schizophrenia

Author

Tuppurainen, Heli, primary, Määttä, Sara, additional, Könönen, Mervi, additional, Julkunen, Petro, additional, Kautiainen, Hannu, additional, Hyvärinen, Soile, additional, Vaurio, Olli, additional, Joensuu, Mikko, additional, Vanhanen, Matti, additional, Aho-Mustonen, Kati, additional, Mervaala, Esa, additional, and Tiihonen, Jari, additional

Published
2024
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15. Novel LAMC3pathogenic variant enriched in Finnish population causes malformations of cortical development and severe epilepsy

Author

Saarela, Anni, Timonen, Oskari, Kirjavainen, Jarkko, Liu, Yawu, Silvennoinen, Katri, Mervaala, Esa, and Kälviäinen, Reetta

Abstract

Recessive LAMC3mutations are recognized to cause epilepsy with cortical malformations characterized by polymicrogyria and pachygyria. The objective of this study was to describe the clinical picture and epilepsy phenotype of four patients with a previously undescribed LAMC3variant. All epilepsy patients treated in Kuopio Epilepsy Center (located in Kuopio, Finland) are offered the possibility to participate in a scientific study investigating biomarkers in epilepsy (Epibiomarker study). We have collected a comprehensive database of the study population, and are currently re‐evaluating our database regarding the patients with developmental and/or epileptic encephalopathy (DEE). If the etiology of epilepsy remains unknown in the clinical setting, we are performing whole exome sequencing to recognize the genetic causes. Among our study population of 323 DEE patients we recognized three patients with similar homozygous LAMC3c.1866del (p.(Phe623Serfs*10)) frameshift variant and one patient with a compound heterozygous mutation where the same frameshift variant was combined with an intronic LAMC3c.4231‐12C>G variant on another allele. All these patients have severe epilepsy and either bilateral agyria‐pachygyria or bilateral polymicrogyria in their clinical MRI scanning. Cortical malformations involve the occipital lobes in all our patients. Epilepsy phenotype is variable as two of our patients have DEE with epileptic spasms progressing to Lennox–Gastaut syndrome and intellectual disability. The other two patients have focal epilepsy without marked cognitive deficit. The four patients are unrelated. LAMC3c.1866del p.(Phe623Serfs*10) frameshift variant is enriched in the Finnish population. Only a few patients with epilepsy caused by LAMC3homozygous or compound heterozygous mutations have been described in the literature. To our knowledge, the variants discovered in our patients have not previously been published. Clinical phenotype appears to be more varied than previously assumed and patients with a milder phenotype and normal cognition have probably remained unrecognized.

Published
2024
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21. Short‐ and long‐interval intracortical inhibition in EPM1 is related to genotype

Author

Silvennoinen, Katri, primary, Säisänen, Laura, additional, Hyppönen, Jelena, additional, Rissanen, Saara M., additional, Karjalainen, Pasi A., additional, D'Ambrosio, Sasha, additional, Jimenez‐Jimenez, Diego, additional, Zagaglia, Sara, additional, Rothwell, John C., additional, Balestrini, Simona, additional, Sisodiya, Sanjay M., additional, Julkunen, Petro, additional, Mervaala, Esa, additional, and Kälviäinen, Reetta, additional

Published
2022
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33. Deep learning enables accurate automatic sleep staging based on ambulatory forehead EEG

Author

Leino, Akseli, Korkalainen, Henri, Kalevo, Laura, Nikkonen, Sami, Kainulainen, Samu, Ryan, Alexander, Duce, Brett, Sipila, Kirsi, Ahlberg, Jari, Sahlman, Johanna, Miettinen, Tomi, Westeren-Punnonen, Susanna, Mervaala, Esa, Toyras, Juha, Myllymaa, Sami, Leppanen, Timo, Myllymaa, Katja, Clinicum, Department of Oral and Maxillofacial Diseases, HUS Head and Neck Center, Department of Oncology, and HUS Comprehensive Cancer Center

Subjects
automatic scoring, General Computer Science, General Engineering, deep learning, 217 Medical engineering, General Medicine, MODEL, ambulatory EEG, sleep staging, RELIABILITY, RECORDINGS, TO-NIGHT VARIABILITY, General Materials Science, CLINICAL POPULATION, HOME, 316 Nursing, Ambulatory EEG, electroencephalography
Abstract

We have previously developed an ambulatory electrode set (AES) for the measurement of electroencephalography (EEG), electrooculography (EOG), and electromyography (EMG). The AES has been proven to be suitable for manual sleep staging and self-application in in-home polysomnography (PSG). To further facilitate the diagnostics of various sleep disorders, this study aimed to utilize a deep learning-based automated sleep staging approach for EEG signals acquired with the AES. The present neural network architecture comprises a combination of convolutional and recurrent neural networks previously shown to achieve excellent sleep scoring accuracy with a single standard EEG channel (F4-M1). In this study, the model was re-trained and tested with 135 EEG signals recorded with AES. The recordings were conducted for subjects suspected of sleep apnea or sleep bruxism. The performance of the deep learning model was evaluated with 10-fold cross-validation using manual scoring of the AES signals as a reference. The accuracy of the neural network sleep staging was 79.7% (kappa = 0.729) for five sleep stages (W, N1, N2, N3, and R), 84.1% (kappa = 0.773) for four sleep stages (W, light sleep, deep sleep, R), and 89.1% (kappa = 0.801) for three sleep stages (W, NREM, R). The utilized neural network was able to accurately determine sleep stages based on EEG channels measured with the AES. The accuracy is comparable to the inter-scorer agreement of standard EEG scorings between international sleep centers. The automatic AES-based sleep staging could potentially improve the availability of PSG studies by facilitating the arrangement of self-administrated in-home PSGs.

Published
2022

35. Deep Learning Enables Accurate Automatic Sleep Staging Based on Ambulatory Forehead EEG

Author

Leino, Akseli, primary, Korkalainen, Henri, additional, Kalevo, Laura, additional, Nikkonen, Sami, additional, Kainulainen, Samu, additional, Ryan, Alexander, additional, Duce, Brett, additional, Sipila, Kirsi, additional, Ahlberg, Jari, additional, Sahlman, Johanna, additional, Miettinen, Tomi, additional, Westeren-Punnonen, Susanna, additional, Mervaala, Esa, additional, Toyras, Juha, additional, Myllymaa, Sami, additional, Leppanen, Timo, additional, and Myllymaa, Katja, additional

Published
2022
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38. Short‐ and long‐interval intracortical inhibition in EPM1 is related to genotype.

Author

Silvennoinen, Katri, Säisänen, Laura, Hyppönen, Jelena, Rissanen, Saara M., Karjalainen, Pasi A., D'Ambrosio, Sasha, Jimenez‐Jimenez, Diego, Zagaglia, Sara, Rothwell, John C., Balestrini, Simona, Sisodiya, Sanjay M., Julkunen, Petro, Mervaala, Esa, and Kälviäinen, Reetta

Subjects
TRANSCRANIAL magnetic stimulation, SPINOCEREBELLAR ataxia, EPILEPSY, GENOTYPES, VIMPAT
Abstract

Objective: Progressive myoclonic epilepsy type 1 (EPM1) is caused by biallelic alterations in the CSTB gene, most commonly dodecamer repeat expansions. Although transcranial magnetic stimulation (TMS)–induced long‐interval intracortical inhibition (LICI) was previously reported to be normal in EPM1, short‐interval intracortical inhibition (SICI) was reduced. We explored the association between these measures and the clinical and genetic features in a separate group of patients with EPM1. Methods: TMS combined with electromyography was performed under neuronavigation. LICI was induced with an inter‐stimulus interval (ISI) of 100 ms, and SICI with ISIs of 2 and 3 ms, and their means (mSICIs) were expressed as the ratio of conditioned to unconditioned stimuli. LICI and mSICI were compared between patients and controls. Nonparametric correlation was used to study the association between inhibition and parameters of clinical severity, including the Unified Myoclonus Rating Scale (UMRS); among patients with EPM1 due to biallelic expansion repeats, also the association with the number of repeats was assessed. Results: The study protocol was completed in 19 patients (15 with biallelic expansion repeats and 4 compound heterozygotes), and 7 healthy, age‐ and sex‐matched control participants. Compared to controls, patients demonstrated significantly less SICI (median mSICI ratio 1.18 vs 0.38; p <.001). Neither LICI nor SICI was associated with parameters of clinical severity. In participants with biallelic repeat expansions, the number of repeats in the more affected allele (greater repeat number [GRN]) correlated with LICI (rho = 0.872; p <.001) and SICI (rho = 0.689; p =.006). Significance: Our results strengthen the finding of deranged γ‐aminobutyric acid (GABA)ergic inhibition in EPM1. LICI and SICI may have use as markers of GABAergic impairment in future trials of disease‐modifying treatment in this condition. Whether a higher number of expansion repeats leads to greater GABAergic impairment warrants further study. [ABSTRACT FROM AUTHOR]

Published
2023
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