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Timo Roine

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5 papers

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YNICL Journal 2026 Journal Article

Association of acute blood biomarkers with diffusion tensor imaging and outcome in patients with traumatic brain injury presenting with GCS of 13–15

Malla Mononen
Mehrbod Mohammadian
Iftakher Hossain
Timo Roine
Olli Tenovuo
Kaj Blennow
Jessica Gill
Mark van Gils

The aim of the study was to assess the association between blood-based biomarkers of different cellular origins and later white matter integrity, measured using post-acute diffusion tensor metrics, and their relation to outcome in patients presenting with Glasgow Coma Scale of 13-15 after traumatic brain injury (TBI). Admission plasma samples for glial fibrillary acidic protein (GFAP), interleukin 10 (IL-10), heart fatty-acid binding protein (H-FABP), S100 calcium-binding protein B (S100B), total tau (T-tau), and amyloid beta 40 and 42 (Aβ40 and Aβ42) were taken for 92 patients. Diffusion-weighted magnetic resonance imaging (DW-MRI) and outcome evaluation was done ≥ 90 days post-injury. Outcome was assessed using Glasgow Outcome Scale-Extended (GOSE) and dichotomized as complete (GOSE 8) and incomplete (GOSE < 8) recovery. Mean fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were calculated from the skeletonized white matter tracts of the whole brain. IL-10 and T-tau showed significant weak-moderate negative correlations with FA, and significant positive correlations with MD and RD in incompletely recovered patients. GFAP showed significant weak positive correlations with MD and RD, while its correlation with FA was slightly below significance threshold after correction for multiple comparison in incompletely recovered patients. Similar trends were observed in the whole cohort and in the CT-positive cohort, although these did not reach statistical significance. Higher acute levels of GFAP, IL-10 and T-tau may be associated with the development of axonal injury. If validated in future studies, these biomarkers may help identify patients who require closer follow-up and DW-MRI.

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YNIMG Journal 2025 Journal Article

Predictive modeling of TMS-evoked responses: Unraveling instantaneous excitability states

Oskari Ahola
Lisa Haxel
Maria Ermolova
Dania Humaidan
Tuomas P. Mutanen
Mikael Laine
Matilda Makkonen
Elena Ukharova

Transcranial magnetic stimulation (TMS) combined with electroencephalography (EEG) and electromyography (EMG) provides a unique window into instantaneous cortical and corticospinal excitability states. We investigated 50 healthy participants to determine how fluctuations in pre-stimulus brain activity influence single-trial TMS-evoked potentials (TEPs) and motor-evoked potentials (MEPs). We developed a novel automated source-level TEP extraction method using individualized spatiotemporal priors that is robust against poor single-trial signal-to-noise ratios (SNRs) and ongoing oscillations. TEP and MEP amplitudes were predicted with linear mixed-effects models based on pre-stimulation EEG band-powers (theta to gamma), while accounting for temporal drifts (within-session trends), coil control, and inter-subject differences. We found that higher pre-stimulus sensorimotor alpha, beta, and gamma power were each associated with larger TEPs, indicating a more excitable cortical state. Increases in alpha and gamma power immediately before stimulation specifically predicted larger MEPs, reflecting increased corticospinal excitability. These results reveal relationships between ongoing oscillatory brain states and TMS response amplitudes, identifying EEG biomarkers of high- and low-excitability states. In conclusion, our study demonstrates the feasibility of single-trial source-level TMS-EEG analysis and shows that spontaneous alpha-, beta-, and gamma-band oscillations modulate motor cortical and corticospinal responsiveness. These findings can contribute to EEG-informed, brain-state-dependent TMS protocols in optimizing neuromodulatory interventions in clinical and research applications.

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YNICL Journal 2024 Journal Article

Working memory related functional connectivity in adult ADHD and its amenability to training: A randomized controlled trial

Tuija Tolonen
Sami Leppämäki
Timo Roine
Kimmo Alho
Pekka Tani
Anniina Koski
Matti Laine
Juha Salmi

BACKGROUND: Working memory (WM) deficits are among the most prominent cognitive impairments in attention deficit hyperactivity disorder (ADHD). While functional connectivity is a prevailing approach in brain imaging of ADHD, alterations in WM-related functional brain networks and their malleability by cognitive training are not well known. We examined whole-brain functional connectivity differences between adults with and without ADHD during n-back WM tasks and rest at pretest, as well as the effects of WM training on functional and structural brain connectivity in the ADHD group. METHODS: Forty-two adults with ADHD and 36 neurotypical controls performed visuospatial and verbal n-back tasks during functional magnetic resonance imaging (fMRI). In addition, seven-minute resting state fMRI data and diffusion-weighted MR images were collected from all participants. The adults with ADHD continued into a 5-week randomized controlled WM training trial (experimental group training on a dual n-back task, n = 21; active control group training on Bejeweled II video game, n = 21), followed by a posttraining MRI. Brain connectivity was examined with Network-Based Statistic. RESULTS: At the pretest, adults with ADHD had decreased functional connectivity compared with the neurotypical controls during both n-back tasks in networks encompassing fronto-parietal, temporal, occipital, cerebellar, and subcortical brain regions. Furthermore, WM-related connectivity in widespread networks was associated with performance accuracy in a continuous performance test. Regarding resting state connectivity, no group differences or associations with task performance were observed. WM training did not modulate functional or structural connectivity compared with the active controls. CONCLUSION: Our results indicate large-scale abnormalities in functional brain networks underlying deficits in verbal and visuospatial WM commonly faced in ADHD. Training-induced plasticity in these networks may be limited.

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YNICL Journal 2023 Journal Article

A comparison of diffusion tensor imaging tractography and constrained spherical deconvolution with automatic segmentation in traumatic brain injury

Jussi Tallus
Mehrbod Mohammadian
Timo Kurki
Timo Roine
Jussi P. Posti
Olli Tenovuo

Detection of microstructural white matter injury in traumatic brain injury (TBI) requires specialised imaging methods, of which diffusion tensor imaging (DTI) has been extensively studied. Newer fibre alignment estimation methods, such as constrained spherical deconvolution (CSD), are better than DTI in resolving crossing fibres that are ubiquitous in the brain and may improve the ability to detect microstructural injuries. Furthermore, automatic tract segmentation has the potential to improve tractography reliability and accelerate workflow compared to the manual segmentation commonly used. In this study, we compared the results of deterministic DTI based tractography and manual tract segmentation with CSD based probabilistic tractography and automatic tract segmentation using TractSeg. 37 participants with a history of TBI (with Glasgow Coma Scale 13-15) and persistent symptoms, and 41 healthy controls underwent deterministic DTI-based tractography with manual tract segmentation and probabilistic CSD-based tractography with TractSeg automatic segmentation.Fractional anisotropy (FA) and mean diffusivity of corpus callosum and three bilateral association tracts were measured. FA and MD values derived from both tractography methods were generally moderately to strongly correlated. CSD with TractSeg differentiated the groups based on FA, while DTI did not. CSD and TractSeg-based tractography may be more sensitive in detecting microstructural changes associated with TBI than deterministic DTI tractography. Additionally, CSD with TractSeg was found to be applicable at lower b-value and number of diffusion-encoding gradients data than previously reported.

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YNICL Journal 2017 Journal Article

High angular resolution diffusion-weighted imaging in mild traumatic brain injury

Mehrbod Mohammadian
Timo Roine
Jussi Hirvonen
Timo Kurki
Henna Ala-Seppälä
Janek Frantzén
Ari Katila
Anna Kyllönen

We sought to investigate white matter abnormalities in mild traumatic brain injury (mTBI) using diffusion-weighted magnetic resonance imaging (DW-MRI). We applied a global approach based on tract-based spatial statistics skeleton as well as constrained spherical deconvolution tractography. DW-MRI was performed on 102 patients with mTBI within two months post-injury and 30 control subjects. A robust global approach considering only the voxels with a single-fiber configuration was used in addition to global analysis of the tract skeleton and probabilistic whole-brain tractography. In addition, we assessed whether the microstructural parameters correlated with age, time from injury, patient's outcome and white matter MRI hyperintensities. We found that whole-brain global approach restricted to single-fiber voxels showed significantly decreased fractional anisotropy (FA) (p = 0.002) and increased radial diffusivity (p = 0.011) in patients with mTBI compared with controls. The results restricted to single-fiber voxels were more significant and reproducible than those with the complete tract skeleton or the whole-brain tractography. FA correlated with patient outcomes, white matter hyperintensities and age. No correlation was observed between FA and time of scan post-injury. In conclusion, the global approach could be a promising imaging biomarker to detect white matter abnormalities following traumatic brain injury.

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