Nexstim (Finland)

This research addresses the challenge of camera calibration and distortion parameter prediction from a single image using deep learning models. The main contributions of this work are: (1) demonstrating that a deep learning model, trained on a mix of real and synthetic images, can accurately predict camera and lens parameters from a single image, and (2) developing a comprehensive synthetic dataset using the AILiveSim simulation platform. This dataset includes variations in focal length and lens distortion parameters, providing a robust foundation for model training and testing. The training process predominantly relied on these synthetic images, complemented by a small subset of real images, to explore how well models trained on synthetic data can perform calibration tasks on real-world images. Traditional calibration methods require multiple images of a calibration object from various orientations, which is often not feasible due to the lack of such images in publicly available datasets. A deep learning network based on the ResNet architecture was trained on this synthetic dataset to predict camera calibration parameters following the Brown-Conrady lens model. The ResNet architecture, adapted for regression tasks, is capable of predicting continuous values essential for accurate camera calibration in applications such as autonomous driving, robotics, and augmented reality.

Corticospinal excitability (CSE) is modulated by stroke-induced lesions affecting the brain. This modulation is known to be dependent on the timing of the evaluation, and strongest abnormalities are often found in the acute stage. Our study aimed to characterize changes in CSE asymmetry between the affected and the unaffected hemisphere (AH and UH) during the first month after stroke onset and at 6 month follow-up. Neuronavigated transcranial magnetic stimulation (nTMS) was used to assess the CSE of the abductor pollicis brevis (APB) muscle of the hand and tibialis anterior (TA) muscle of the leg in 16 patients over 5 time-points. AH excitability recovered significantly during 6 months, whereas interhemispheric asymmetry remained significant up to 1 month post-stroke in the APB muscle. Greater initial CSE was associated with good motor function at 6 months. The motor cortical excitatory recovery initiated within week of the stroke and was most prominent within 1 month after stroke onset. Lesion size correlated with CSE of the UH at 10days, while overall severity of the symptoms correlated inversely with CSE of the AH. This study demonstrates the quick improvement in the CSE via estimation of interhemispheric asymmetry; however, the recovery in the asymmetry continues to normalize even after reaching the threshold for normal values in CSE.

Background: The muscle representations in non-primary motor area (NPMA) are located in the dorsal premotor area (PMd) and in the border region between the premotor area and the supplementary motor area (SMA).Objective: We characterized the plasticity of intracortical inhibitory and excitatory circuits in muscle representations in primary motor cortex (M1) and in NPMA related to acquired fine motor skills. We compared local cortical inhibition and facilitation balance in M1 and in NPMA between control subjects (n = 6) and right-handed string-instrument players (n = 5).Methods: Navigated transcranial magnetic stimulation (TMS) was used to compare motor thresholds (MTs), motor evoked potentials (MEPs), short-interval intracortical inhibition (SICI) and intracortical facilitation (ICF) in non-dominant hand muscle representations in M1 and NPMA.Results: String-instrument players showed reduced SICI in M1 in the actively used left hand abductor digiti minimi (ADM) muscle representation at 3 ms inter-stimulus interval (ISI) with a conditioning stimulus (CS) intensity of 80% of MT and increased SICI in NPMA in ADM representation at 2 ms ISI and CS intensity of 50% of MT in comparison with controls. No differences between string-instrument players and controls were found for the SICI in the left hand opponens pollicis (OP) muscle representation, which is a muscle not intensively trained in string-instrument players.Conclusions: These preliminary results indicate that the stronger inhibition in motor representations outside M1 in string-instrument players may be crucial when accurate movements of single muscles must be performed. In contrast, weaker inhibition in M1 in string-instrument players may benefit the performance of fast finger movements.

Objective: To determine whether neuro-navigated 1hz rTMS targeted to the non-lesioned hemisphere (NLH) combined with task-oriented occupational therapy (OT) can improve motor function of arm and hand in patients with subacute stroke. Methods: 30 patients (3-9 months post-stroke) were randomly assigned to sham (n=10) or active 1hz rTMS (n=20) targeted to the wrist extensor representation in the NLH. Patients completed 3 visits per week for 6 weeks that included: 20min pre-functional OT, neuro-navigated 1hz rTMS or sham, and 60 min upper-limb task-oriented OT. Patients returned for 1 week, 1 month, and 6 month follow-up visits. Groups were well matched at baseline but there was a trend toward more severe impairment in the active treatment group on the Upper Extremity Fugl Meyer (UEFM) (23.8±10.2, active; 31.5±15.3, sham: p=0.11). Results: Patients receiving active rTMS prior to OT made significantly greater gains on the UEFM by 6 months post-intervention than patients receiving sham stimulation (change in UEFM 14.4 ± 10.0 vs. 4.1 ± 5.5; p=0.013). On ANOVA differences were significant for group, time and group x time (F=5.73, df=2, p=0.006). Individuals receiving active rTMS were significantly more likely to exceed the published minimal clinical important difference (MCID) on the UEFM at 6 months post (88% vs. 38%, p = 0.002). Similar trends at 1 week and 1 month post were not statistically significant. Ceiling effects were unlikely. Conclusion: These findings suggest neuro-navigated 1hz rTMS paired with task-oriented OT is more likely to promote clinically important improvements than OT alone. Of note is the finding that significant improvements in impairment were seen 6 months following therapy, suggesting non-invasive brain stimulation as an adjuvant to therapy promotes lasting motor improvement.

Navigated transcranial magnetic stimulation (nTMS) is increasingly used in presurgical brain mapping. Preoperative nTMS results correlate well with direct cortical stimulation (DCS) data in the identification of the primary motor cortex. Repetitive nTMS can also be used for mapping of speech-sensitive cortical areas. The current cohort study compares the safety and effectiveness of preoperative nTMS with DCS mapping during awake surgery for the identification of language areas in patients with left-sided cerebral lesions. Twenty patients with tumors in or close to left-sided language eloquent regions were examined by repetitive nTMS before surgery. During awake surgery, language-eloquent cortex was identified by DCS. nTMS results were compared for accuracy and reliability with regard to DCS by projecting both results into the cortical parcellation system. Presurgical nTMS maps showed an overall sensitivity of 90.2%, specificity of 23.8%, positive predictive value of 35.6%, and negative predictive value of 83.9% compared with DCS. For the anatomic Broca's area, the corresponding values were a sensitivity of 100%, specificity of 13.0%, positive predictive value of 56.5%, and negative predictive value of 100%, respectively. Good overall correlation between repetitive nTMS and DCS was observed, particularly with regard to negatively mapped regions. Noninvasive inhibition mapping with nTMS is evolving as a valuable tool for preoperative mapping of language areas. Yet its low specificity in posterior language areas in the current study necessitates further research to refine the methodology.

Alzheimer's disease (AD) is the most common form of old age dementia, and mild cognitive impairment (MCI) often precedes AD. In our previous study (Julkunen et al. 2008), we found that the combination of transcranial magnetic stimulation (TMS) and electroencephalography (EEG) was able to find distinct differences in AD and MCI patients as compared to controls. Here, we reanalyzed the small sample data from our previous study with the aim to test the sensitivity of the TMS-EEG characteristics to discriminate control subjects (n = 4) from MCI (n = 5) and AD (n = 5) subjects. Furthermore, we investigated how the TMS-EEG response characteristics related to the scores of the dementia rating scales used to evaluate the severity of cognitive decline in these subjects. We found that the TMS-EEG response P30 amplitude correlated with cognitive decline and showed good specificity and sensitivity in identifying healthy subjects from those with MCI or AD. Given the small sample size, further studies may be needed to confirm the results.