Review
Neurosciences
Stefanie Perl, Anika Luettig, Rudiger Koehling, Angelika Richter
Summary: This review provides an overview of DBS research in animal models of dystonia, discussing the research aims, opportunities and limitations of different animal models, and technical challenges.
NEUROBIOLOGY OF DISEASE
(2022)
Article
Neurosciences
Vinith Johnson, Robert Wilt, Roee Gilron, Juan Anso, Randy Perrone, Martijn Beudel, Dan Pina-Fuentes, Jeremy Saal, Jill L. Ostrem, Ian Bledsoe, Philip Starr, Simon Little
Summary: The study utilized a novel, sensing-enabled deep brain stimulator device implanted in a patient with cervical dystonia to record neural data and conduct a proof-of-principle trial. It found that low-frequency oscillations are related to dystonia and demonstrated the potential for a novel adaptive stimulation strategy.
EXPERIMENTAL NEUROLOGY
(2021)
Article
Clinical Neurology
Daniel T. Corp, Christopher J. Greenwood, Jordan Morrison-Ham, Jaakko Pullinen, Georgia M. McDowall, Ellen F. P. Younger, Hyder A. Jinnah, Michael D. Fox, Juho Joutsa
Summary: This study identified cases of lesion-induced dystonia from published literature and classified patients into subgroups based on lesion location and body regions affected by dystonia. Significant differences were found between these subgroups on a range of dystonia symptoms.
Article
Cell Biology
Ahmed Jorge, Witold J. Lipski, Dengyu Wang, Donald J. Crammond, Robert S. Turner, R. Mark Richardson
Summary: This study provides evidence for the involvement of the subthalamic nucleus (STN) in speech production and highlights the unique connections between the inferior frontal gyms and the STN. The findings suggest that these connections may be specific to humans and have evolved alongside the development of speech.
Article
Neurosciences
Marco Heerdegen, Monique Zwar, Denise Franz, Julia Hoernschemeyer, Valentin Neubert, Franz Plocksties, Christoph Niemann, Dirk Timmermann, Christian Bahls, Ursula van Rienen, Maria Paap, Stefanie Perl, Anika Luettig, Angelika Richter, Rudiger Koehling
Summary: DBS can increase cortico-striatal evoked responses in healthy tissue, but not in dystonic tissue. It also enhances inhibitory control in dystonic tissue and decreases inhibitory control in healthy tissue, suggesting modulation of presynaptic mechanisms.
NEUROBIOLOGY OF DISEASE
(2021)
Article
Multidisciplinary Sciences
Estefania Hernandez-Martin, Maral Kasiri, Sumiko Abe, Jennifer Maclean, Joffre Olaya, Mark Liker, Jason Chu, Terence D. Sanger
Summary: The rate model of basal ganglia function predicts that muscle activity in dystonia is due to disinhibition of thalamus resulting from decreased inhibitory input from pallidum. We seek to test this hypothesis in children with dyskinetic cerebral palsy undergoing evaluation for deep brain stimulation (DBS) to analyze movement-related activity in different brain regions. The results revealed prominent beta-band frequency peaks in the globus pallidus interna (GPi), ventral oralis anterior/posterior (VoaVop) subnuclei of the thalamus, and subthalamic nucleus (STN) during movement but not at rest.
Article
Multidisciplinary Sciences
Sebastian Loens, Julius Verrel, Vera-Maria Herrmann, Amrei Kienzle, Elinor Tzvi, Anne Weissbach, Johanna Junker, Alexander Muenchau, Tobias Baeumer
Summary: The study found that motor sequence learning is impaired in cervical dystonia patients overall, and unlike healthy controls, patients did not show a learning effect in the first part of the experiment. However, visuomotor adaptation and eyeblink conditioning were normal in these patients.
SCIENTIFIC REPORTS
(2021)
Article
Clinical Neurology
Luka Milosevic, Suneil K. Kalia, Mojgan Hodaie, Andres M. Lozano, Milos R. Popovic, William D. Hutchison, Milad Lankarany
Summary: This study investigates the brain-region-specific and frequency-dependent effects of deep brain stimulation on neuronal activity. The results show that higher stimulation frequencies lead to neuronal suppression, while site-specific responses are influenced by local neuroanatomical properties and short-term synaptic plasticity.
Review
Neurosciences
Maja Klarendic, Diego Kaski
Summary: DBS treatment is widely used for movement disorders and other neurological and psychiatric conditions, with effects on eye movements dependent on stimulation location and underlying pathology. Understanding how DBS affects eye movements can provide insights into neural circuits involved in complex eye movement control. Further research is needed to explore the potential effects of DBS on eye movements with less common stimulation targets.
EUROPEAN JOURNAL OF NEUROSCIENCE
(2021)
Article
Neurosciences
Clayton S. Bingham, Cameron C. McIntyre
Summary: This study used biophysical models to investigate the recruitment pathways and conduction latencies of the hyperdirect pathway (HDP) in response to subthalamic deep brain stimulation (DBS). The results suggest that HDP activation is influenced by complex axonal branching in the subthalamic nucleus (STN). These findings provide valuable information for linking HDP activation with evoked potentials (EPs) recorded in clinical experiments.
JOURNAL OF NEUROPHYSIOLOGY
(2022)
Review
Cell Biology
Juan Wang, Xiaoting Wang, Hui Li, Limin Shi, Ning Song, Junxia Xie
Summary: In this review, the latest information related to movement disorders and modulations in Parkinson's disease (PD) is provided, with a focus on brain regions and neuronal circuits. Updates on deep brain stimulation (DBS) and other factors for motor improvement in PD are also discussed.
AGEING RESEARCH REVIEWS
(2023)
Review
Physiology
Denise Franz, Angelika Richter, Ruediger Koehling
Summary: Deep brain stimulation (DBS) has become the standard treatment for movement disorders, but there are still unanswered questions about the pathomechanisms of dystonia and the mechanisms of DBS on neuronal circuitry. Lack of knowledge limits therapeutic effect and makes it difficult to predict outcomes for individual dystonia patients. Electrophysiological biomarkers may offer a promising option for personalized DBS treatment.
PFLUGERS ARCHIV-EUROPEAN JOURNAL OF PHYSIOLOGY
(2023)
Article
Multidisciplinary Sciences
Taku Matsuda, Ryoma Morigaki, Yuki Matsumoto, Hideo Mure, Kazuhisa Miyake, Masahito Nakataki, Masafumi Harada, Yasushi Takagi
Summary: This study aimed to investigate the correlations between motor symptoms and obsessive-compulsive symptoms, as well as between the volumes of basal ganglia components and obsessive-compulsive symptoms. The results revealed a positive correlation between obsessive-compulsive symptoms and the volumes of the nucleus accumbens, while motor symptoms showed a negative correlation. This highlights the potential pathogenesis of obsessive-compulsive disorder and dystonia.
SCIENTIFIC REPORTS
(2022)
Article
Biochemistry & Molecular Biology
Costanza Gianni, Claudia Piervincenzi, Daniele Belvisi, Silvia Tommasin, Maria Ilenia De Bartolo, Gina Ferrazzano, Nikolaos Petsas, Giorgio Leodori, Nicoletta Fantoni, Antonella Conte, Alfredo Berardelli, Patrizia Pantano
Summary: This study investigated the microstructural damage of white matter bundles connecting subcortical and cortical regions in patients with cervical dystonia and blepharospasm. The results showed significant differences in diffusion tensor imaging metrics between the patient groups and healthy subjects, suggesting a common pathology in these two types of dystonia.
Article
Neurosciences
Lisa Rauschenberger, Christopher Guettler, Jens Volkmann, Andrea A. Kuehn, Chi Wang Ip, Roxanne Lofredi
Summary: Intracerebral recordings and animal models have made significant contributions to neurophysiological research of movement disorders.
EXPERIMENTAL NEUROLOGY
(2022)
Article
Behavioral Sciences
Maria Teresa Faria, Susana Rodrigues, Manuel Campelo, Duarte Dias, Ricardo Rego, Helena Rocha, Francisca Sa, Marta Tavares-Silva, Roberto Pinto, Goncalo Pestana, Ana Oliveira, Jorge Pereira, Joao Paulo Silva Cunha, Francisco Rocha-Goncalves, Hernani Goncalves, Elisabete Martins
Summary: This study highlights the greater impact of FBTCS on autonomic cardiac function in patients with refractory epilepsy compared to other types of seizures, with a significant reduction in vagal tonus that may be associated with increased risk of SUDEP.
EPILEPSY & BEHAVIOR
(2022)
Article
Computer Science, Artificial Intelligence
Hendrik Burwinkel, Holger Matz, Stefan Saur, Christoph Hauger, Michael Trost, Nino Hirnschall, Oliver Findl, Nassir Navab, Seyed-Ahmad Ahmadi
Summary: Cataract surgery is the most frequently performed ophthalmic surgery in the world, aiming to restore the optical system of the eye by replacing the damaged lens with an artificial intraocular lens (IOL). Recent efforts have been made to predict IOL specifications using machine learning methods, and the proposal of OpticNet, a novel optical refraction network, demonstrates improved performance and physical consistency in predictions compared to current state-of-the-art methods.
MEDICAL IMAGE ANALYSIS
(2022)
Article
Oncology
Maria Kawula, Dinu Purice, Minglun Li, Gerome Vivar, Seyed-Ahmad Ahmadi, Katia Parodi, Claus Belka, Guillaume Landry, Christopher Kurz
Summary: The aim of this study was to investigate the impact of state-of-the-art 3D U-Net-generated organ delineations on dose optimization in radiation therapy for prostate cancer patients. The study found no strong statistically significant correlation between geometric and dosimetric metrics. It highlighted the importance of adding dosimetric analysis to the standard geometric evaluation.
RADIATION ONCOLOGY
(2022)
Article
Clinical Neurology
Seyed-Ahmad Ahmadi, Johann Frei, Gerome Vivar, Marianne Dieterich, Valerie Kirsch
Summary: This study developed a novel open-source segmentation approach for inner ear total fluid space (TFS) using deep learning. The model demonstrated high accuracy, robustness, and fast prediction times. It can be seamlessly integrated with existing tools for automatic endolymphatic hydrops (ELH) segmentation.
FRONTIERS IN NEUROLOGY
(2022)
Article
Neurosciences
Cammille C. Go, Huseyin O. Taskin, Seyed-Ahmad Ahmadi, Giulia Frazzetta, Laura Cutler, Saguna Malhotra, Jessica I. W. Morgan, Virginia L. Flanagin, Geoffrey K. Aguirre
Summary: This study aims to characterize the form and magnitude of nystagmus induced at 3T magnetic field. Eye movements of 42 subjects were measured, and persistent nystagmus was observed in subjects in a 3T magnetic field, with the amplitude of nystagmus correlated with the roll angle of the vestibular system.
Article
Medicine, General & Internal
Maria do Carmo Vilas-Boas, Pedro Filipe Pereira Fonseca, Ines Martins Sousa, Marcio Neves Cardoso, Joao Paulo Silva Cunha, Teresa Coelho
Summary: This study aims to quantitatively characterize the gait pattern of patients with V30M ATTRv amyloidosis, providing information for better understanding, diagnosis, and disease progression evaluation. The results showed delayed toe-off, excessive pelvic rotation, hip extension and external transverse rotation, as well as knee flexion in patients, along with reduced ground reaction forces. These gait anomalies are not clinically quantified, and gait analysis may contribute to the assessment of disease progression, in addition to clinical evaluation.
JOURNAL OF CLINICAL MEDICINE
(2022)
Article
Toxicology
Tobias Zellner, Katrin Romanek, Christian Rabe, Sabrina Schmoll, Stefanie Geith, Eva-Carina Heier, Raphael Stich, Hendrik Burwinkel, Matthias Keicher, David Bani-Harouni, Nassir Navab, Seyed-Ahmad Ahmadi, Florian Eyer
Summary: This study aims to develop a machine-learning based computer-aided diagnosis system for predicting poisons based on patient's symptoms. The system shows high accuracy in predicting poisons and outperforms other methods and medical doctors.
CLINICAL TOXICOLOGY
(2023)
Article
Computer Science, Artificial Intelligence
Anees Kazi, Luca Cosmo, Seyed-Ahmad Ahmadi, Nassir Navab, Michael M. M. Bronstein
Summary: Graph deep learning is a powerful machine learning concept that generalizes deep neural architectures to non-euclidean structured data. This method has shown promising results in various applications. However, current graph neural network architectures often assume a known and fixed underlying graph, which may not be true in practice. To address this limitation, we introduce a Differentiable Graph Module (DGM) that predicts edge probabilities in the graph for optimal downstream tasks. We evaluate our model in healthcare, brain imaging, computer graphics, and computer vision domains and demonstrate its significant improvement over baselines in both transductive and inductive settings, achieving state-of-the-art results.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2023)
Article
Computer Science, Software Engineering
David Narciso, Miguel Melo, Susana Rodrigues, Joao Paulo Cunha, Jose Vasconcelos-Raposo, Maximino Bessa
Summary: This study compares the effectiveness of virtual environment (VE) and real environment (RE) in training firefighters. The results indicate that participants in the VE experienced less physiological stress, had better knowledge transfer, but the overall effectiveness was lower than the RE.
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
(2023)
Proceedings Paper
Computer Science, Artificial Intelligence
Jianning Li, Jana Fragemann, Seyed-Ahmad Ahmadi, Jens Kleesiek, Jan Egger
Summary: The reconstruction loss and the Kullback-Leibler divergence (KLD) loss in a variational autoencoder (VAE) often have opposing effects, making it difficult to achieve a balance between the two. This paper proposes a two-stage method for training a VAE that solves this problem by decoupling the KLD loss from the decoder. Experimental results show that the proposed method achieves a good balance between the Gaussian assumption of the latent space and reconstruction error, without requiring specific tuning of hyperparameters. The method is evaluated using a medical dataset for skull reconstruction and shape completion, demonstrating promising generative capabilities.
MEDICAL APPLICATIONS WITH DISENTANGLEMENTS, MAD 2022
(2023)
Article
Clinical Neurology
Mathias Kunz, Philipp Karschnia, Ingo Borggraefe, Soheyl Noachtar, Joerg-Christian Tonn, Christian Vollmar
Summary: This study aimed to investigate the effectiveness and safety of repeated epilepsy surgery in patients with persistent or recurrent seizures. The results showed that 71% of patients had improved seizure control after reoperation. Additionally, the incidence of perioperative complications was low, with no fatalities.
JOURNAL OF NEUROSURGERY
(2023)
Proceedings Paper
Engineering, Electrical & Electronic
Duarte Dias, Joana Silva, Nuno Oliveira, Joao Massano, Joao Paulo Silva Cunha
Summary: PDapp is an application system that combines mHealth features with the iHandU appcessory to help manage Parkinson's disease. The mobile application allows patients to manage medication, perform symptom tests, and communicate with clinicians, while a specialized web dashboard enables clinicians to monitor patient history. The iHandU appcessory measures wrist rigidity, bradykinesia, and tremor. The system design and functionalities were developed jointly with clinicians, receiving positive feedback and proving suitable for patient use.
2022 IEEE 21ST MEDITERRANEAN ELECTROTECHNICAL CONFERENCE (IEEE MELECON 2022)
(2022)
Meeting Abstract
Clinical Neurology
E. Lopes, C. Caldeiras, M. Rito, C. Chamadoira, A. Santos, J. P. S. Cunha, R. Rego
Correction
Clinical Neurology
Maria do Carmo Vilas-Boas, Ana Patricia Rocha, Marcio Neves Cardoso, Jose Maria Fernandes, Teresa Coelho, Joao Paulo Silva Cunha
FRONTIERS IN NEUROLOGY
(2022)
Meeting Abstract
Toxicology
Tobias Zellner, Hendrik Burwinkel, Matthias Keicher, David Bani-Harouni, Nassir Navab, Seyed-Ahmad Ahmadi, Florian Eyer
CLINICAL TOXICOLOGY
(2022)
Article
Neurosciences
Jose Sanchez-Bornot, Roberto C. Sotero, J. A. Scott Kelso, Ozguer Simsek, Damien Coyle
Summary: This study proposes a multi-penalized state-space model for analyzing unobserved dynamics, using a data-driven regularization method. Novel algorithms are developed to solve the model, and a cross-validation method is introduced to evaluate regularization parameters. The effectiveness of this method is validated through simulations and real data analysis, enabling a more accurate exploration of cognitive brain functions.
