Research

Year: 2023

Stettler, M., Lappe, A., Taubert, N. & Giese, M. A. (2023). Multi-Domain Norm-referenced Encoding Enables Data Efficient Transfer Learning of Facial Expression Recognition..
Multi-Domain Norm-referenced Encoding Enables Data Efficient Transfer Learning of Facial Expression Recognition
Abstract:

People can innately recognize human facial expressions in unnatural forms, such as when depicted on the unusual faces drawn in cartoons or when applied to an animal’s features. However, current machine learning algorithms struggle with out-of-domain transfer in facial expression recognition (FER). We propose a biologically-inspired mechanism for such transfer learning, which is based on norm-referenced encoding, where patterns are encoded in terms of difference vectors relative to a domain-specific reference vector. By incorporating domain-specific reference frames, we demonstrate high data efficiency in transfer learning across multiple domains. Our proposed architecture provides an explanation for how the human brain might innately recognize facial expressions on varying head shapes (humans, monkeys, and cartoon avatars) without extensive training. Norm-referenced encoding also allows the intensity of the expression to be read out directly from neural unit activity, similar to face-selective neurons in the brain. Our model achieves a classification accuracy of 92.15% on the FERG dataset with extreme data efficiency. We train our proposed mechanism with only 12 images, including a single image of each class (facial expression) and one image per domain (avatar). In comparison, the authors of the FERG dataset achieved a classification accuracy of 89.02% with their FaceExpr model, which was trained on 43,000 images.

Type of Publication: Misc
Full text: Online version
St-Amand, J. & Giese, M. A. (2023). Variable Selection in GPDMs Using the Information Bottleneck Method. 37th Conference on Neural Information Processing Systems (NeurIPS 2023)..
Variable Selection in GPDMs Using the Information Bottleneck Method
Abstract:

Accurate real-time models of human motion are important for applications in areas such as cognitive science and robotics. Neural networks are often the favored choice, yet their generalization properties are limited, particularly on small data sets. This paper utilizes the Gaussian process dynamical model (GPDM) as an alternative. Despite their successes in various motion tasks, GPDMs face challenges like high computational complexity and the need for many hyperparameters. This work addresses these issues by integrating the information bottleneck (IB) framework with GPDMs. The IB approach aims to optimally balance data fit and generalization through measures of mutual information. Our technique uses IB variable selection as a component of GPLVM back-constraints to reduce parameter count and to select features for latent space optimization, resulting in improved model accuracy.

Type of Publication: Article
Journal: 37th Conference on Neural Information Processing Systems (NeurIPS 2023).
Year: 2023
Full text: PDF | Online version
Kumar, P., Taubert, N., Raman, R., Bognár, A., Nejad, G. G., Vogels, R. et al. (2023). Neurodynamical Model of the Visual Recognition of Dynamic Bodily Actions from Silhouettes. , 533-544.
Neurodynamical Model of the Visual Recognition of Dynamic Bodily Actions from Silhouettes
Abstract:

For social species, including primates, the recognition of dynamic body actions is crucial for survival. However, the detailed neural circuitry underlying this process is currently not well understood. In monkeys, body-selective patches in the visual temporal cortex may contribute to this processing. We propose a physiologically-inspired neural model of the visual recognition of body movements, which combines an existing image-computable model (`ShapeComp') that produces high-dimensional shape vectors of object silhouettes, with a neurodynamical model that encodes dynamic image sequences exploiting sequence-selective neural fields. The model successfully classifies videos of body silhouettes performing different actions. At the population level, the model reproduces characteristics of macaque single-unit responses from the rostral dorsal bank of the Superior Temporal Sulcus (Anterior Medial Upper Body (AMUB) patch). In the presence of time gaps in the stimulus videos, the predictions made by the model match the data from real neurons. The underlying neurodynamics can be analyzed by exploiting the framework of neural field dynamics.

Authors: Kumar, Prerana; Taubert, Nick; Raman, Rajani Bognár, Anna Nejad, Ghazaleh Ghamkhari Vogels, Rufin Giese, Martin A.
Type of Publication: Article
Seemann, J., Traschütz, A., Ilg, W. & Synofzik, M. (2023). 4‐Aminopyridine improves real‐life gait performance in SCA27B on a single‐subject level: a prospective n‐of‐1 treatment. Journal of Neurology (published online 13 July 2023).
4‐Aminopyridine improves real‐life gait performance in SCA27B on a single‐subject level: a prospective n‐of‐1 treatment
Authors: Seemann, Jens; Traschütz, Andreas Ilg, Winfried; Synofzik, Matthis
Research Areas: Uncategorized
Type of Publication: Article
Full text: PDF
Stettler, M., Lappe, A., Siebert, R., Taubert, N., Thier, P. & Giese, M. A (2023). Norm-referenced encoding of facial expressions facilitates transfer learning to novel head shapes. 2023 Neuroscience Meeting Planner . Washington, D.C..
Norm-referenced encoding of facial expressions facilitates transfer learning to novel head shapes
Authors: Stettler, Michael; Lappe, Alexander; Siebert, Ramona Taubert, Nick; Thier, Peter Giese, Martin A.
Research Areas: Uncategorized
Type of Publication: In Collection
JRESEARCH_BOOK_TITLE: 2023 Neuroscience Meeting Planner
Organization: Society for Neuroscience
Address: Washington, D.C.
Peng, L., Lappe, A., Wen, S., Giese, M. A. & Thier, P (2023). Task-dependent switching of the tuning properties of F5 mirror neuron. Proceedings of the European Conference on Visual Perception (ECVP) .
Task-dependent switching of the tuning properties of F5 mirror neuron
Authors: Peng, Lilei Lappe, Alexander; Wen, Shengjun Giese, Martin A.; Thier, Peter
Research Areas: Uncategorized
Type of Publication: In Collection
Ilg, W., Milne, S., Schmitz-Hübsch, T., Alcock, L., Beichert, L., Bertini, E. et al. (2023). Quantitative Gait and Balance Outcomes for Ataxia Trials: Consensus Recommendations by the Ataxia Global Initiative Working Group on Digital-Motor Biomarkers. The Cerebellum, 23, 24.
Quantitative Gait and Balance Outcomes for Ataxia Trials: Consensus Recommendations by the Ataxia Global Initiative Working Group on Digital-Motor Biomarkers
Authors: Ilg, Winfried; Milne, Sarah Schmitz-Hübsch, Tanja Alcock, Lisa Beichert, Lukas Bertini, Enrico Ibrahim, Norlinah Dawes, Helen Gomez, Christopher Hanagasi, Hasmet Kinnunen, Kirsi Minnerop, Martina Németh, Andrea Newman, Jane Ng, Yi Shiau Rentz, Clara Samanci, Bedia Shah, Vrutang Summa, Susanna Horak, Fay
Type of Publication: Article
Full text: PDF
Seemann, J., Loris, T., Weber, L., Synofzik, M., Giese, M. A. & Ilg, W. (2023). One Hip Wonder: 1D-CNNs Reduce Sensor Requirements for Everyday Gait Analysis. Accepted for ICANN 2023.
One Hip Wonder: 1D-CNNs Reduce Sensor Requirements for Everyday Gait Analysis
Abstract:

Abstract. Wearable inertial measurement units (IMU) enable largescale multicenter studies of everyday gait analysis in patients with rare neurodegenerative diseases such as cerebellar ataxia. To date, the quantity of sensors used in such studies has involved a trade-off between data quality and clinical feasibility. Here, we apply machine learning techniques to potentially reduce the number of sensors required for real-life gait analysis from three sensors to a single sensor on the hip. We trained 1D-CNNs on constrained walking data from individuals with cerebellar ataxia and healthy controls to generate synthetic foot data and predict gait features from a single sensor and tested them in free walking conditions, including the everyday life of unseen subjects. We compare 14 stride-based gait features (e.g. stride length) with three sensors (two on the feet and one on the hip) with our approach estimating the same features based on raw IMU-data from a single sensor placed on the hip. Leveraging layer-wise relevance propagation (LRP) and transfer learning, we determine driving elements of the input signals to predict individuals’ gait features. Our approach achieved a relative error (

Authors: Seemann, Jens; Loris, Tim Weber, Lukas Synofzik, Matthis Giese, Martin A.; Ilg, Winfried
Type of Publication: Article
Full text: PDF
Lang, J., Giese, M. A., Ilg, W. & Otte, S. (2023). Generating Sparse Counterfactual Explanations For Multivariate Time Series. Accepted for ICANN 2023.
Generating Sparse Counterfactual Explanations For Multivariate Time Series
Abstract:

Since neural networks play an increasingly important role in critical sectors, explaining network predictions has become a key research topic. Counterfactual explanations can help to understand why classifier models decide for particular class assignments and, moreover, how the respective input samples would have to be modified such that the class prediction changes. Previous approaches mainly focus on image and tabular data. In this work we propose SPARCE, a generative adversarial network (GAN) architecture that generates SPARse Counterfactual Explanations for multivariate time series. Our approach provides a custom sparsity layer and regularizes the counterfactual loss function in terms of similarity, sparsity, and smoothness of trajectories. We evaluate our approach on real-world human motion datasets as well as a synthetic time series interpretability benchmark. Although we make significantly sparser modifications than other approaches, we achieve comparable or better performance on all metrics. Moreover, we demonstrate that our approach predominantly modifies salient time steps and features, leaving non-salient inputs untouched.

Authors: Lang, Jana Giese, Martin A.; Ilg, Winfried; Otte, Sebastian
Type of Publication: Article
Full text: PDF | Online version
Klein, C. S., Hollmann, K., K\"uhnhausen, J., Alt, A. K., Pascher, A., Ilg, W. et al. (2023). Smart Sensory Technology in Tele-Psychotherapy of Children and Adolescents with Obsessive-Compulsive Disorder (OCD): A Feasibility Study, SSRN.
Smart Sensory Technology in Tele-Psychotherapy of Children and Adolescents with Obsessive-Compulsive Disorder (OCD): A Feasibility Study
Abstract:

Background: Telemedicine interventions support behavioral state-of-the-art treatment of obsessive-compulsive disorder (OCD) as therapy can be delivered in the patients' home environment, allowing for more ecologically valid symptom actualization and access to experts even in rural areas. Sensors to indicate a patient´s emotional state and gaze direction during exposures with response prevention help to adapt therapy individually and to prevent avoidance behavior. This study will investigate the feasibility and acceptability of sensor-based telemedical treatment for children with OCD in the home setting. Methods: We plan to develop the therapy system with 10 healthy children and 5-10 children with OCD, aged 12-18 years, and then to evaluate it by treating 20 children with OCD of the same age group in 14 weekly therapy sessions via teleconference. We will use eye trackers to record the patient´s gaze and pupillometry, while the heart rate is captured by an ECG chest belt to identify stress responses. Inertial sensors capture movements to detect behavioral patterns. An app is used to record the children's self-rated symptoms and emotional state on a daily basis. Pre- and post-study questionnaires on obsessive-compulsive symptoms, feasibility and acceptance of the therapy by children, parents and therapists will be evaluated. Conclusion: We expect this therapeutic approach to show good feasibility and significant symptom reduction, as well as improvement for psychotherapeutic interventions through direct feedback of physiological responses within therapy sessions. We will further explore the underlying mechanisms in OCD treatment before applying them to other disorders.

Authors: Klein, Carolin S. Hollmann, Karsten K\"uhnhausen, Jan Alt, Annika K. Pascher, Anja Ilg, Winfried; Thierfelder, Annika; Giese, Martin A.; Passon, Helene Ernst, Christian Matthias Kasneci, Enkelejda Severitt, Björn Holderried, Martin Bethge, Wolfgang Lautenbacher, Heinrich Wörz, Ursula Primbs, Jonas Menth, Michael Gawrilow, Caterina Conzelmann, Annette Barth, Gottfried M. Renner, Tobias J.
Type of Publication: Technical Report
Institution: SSRN
Type of Publication: preprint
Full text: Online version
Bognár, A., Mukovskiy, A., Nejad, G. G., Taubert, N., Stettler, M., Martini, L. M. et al (2023). Simultaneous recordings from posterior and anterior body responsive regions in the macaque Superior Temporal Sulcus . VSS 2023, May 19-24 2023, St. Pete Beach, Florida.
Simultaneous recordings from posterior and anterior body responsive regions in the macaque Superior Temporal Sulcus
Authors: Bognár, A. Mukovskiy, Albert; Nejad, G. Ghamkhari Taubert, Nick; Stettler, Michael; Martini, Lucas M.; Raman, R. Giese, Martin A.; Vogels, R.
Type of Publication: In Collection
Bognár, A., Mukovskiy, A., Nejad, G. G., Taubert, N., Stettler, M., Martini, L. M. et al (2023). Feature selectivity of body-patch neurons assessed with a large set of monkey avatars . 13th Annual Meeting on PrimateNeurobiology, Apr.26-28 2023, Göttingen Primate Center..
Feature selectivity of body-patch neurons assessed with a large set of monkey avatars
Authors: Bognár, A. Mukovskiy, Albert; Nejad, G. Ghamkhari Taubert, Nick; Stettler, Michael; Martini, Lucas M.; Raman, R. Giese, Martin A.; Vogels, R.
Type of Publication: In Collection
Ilg, W., Lassmann, C. & Haeufle, D (2023). Neuro-muscular modeling predicts subtle gait changes in early spastic paraplegia . International Symposium on Posture and Gait Research, JULY 9 – 13, BRISBANE, AUSTRALIA.
Neuro-muscular modeling predicts subtle gait changes in early spastic paraplegia
Authors: Ilg, Winfried; Lassmann, Christian Haeufle, Daniel
Research Areas: Uncategorized
Type of Publication: In Collection
Seemann, J., Ilg, W., Giese, M. A. & Synofzik, M (2023). Context-sensitive longitudinal analysis of real-life walking reveals one-year change in degenerative cerebellar disease . International Symposium on Posture and Gait Research, JULY 9 – 13, BRISBANE, AUSTRALIA.
Context-sensitive longitudinal analysis of real-life walking reveals one-year change in degenerative cerebellar disease
Abstract:

BACKGROUND AND AIM: With disease-modifying drugs on the horizon for degenerative ataxias, ecologically valid motor biomarkers are highly warranted, which detect longitudinal changes in short, trial-like time-frames. In this observational study, we aim to unravel biomarkers of ataxic gait which are sensitive for longitudinal changes in real life by using wearable sensors. We hypothesize that, gait measures captured in patients' real life could be more sensitive to progression in short, trial-like time-frames compared to lab-based gait assessments and clinical rating scales. However, in real life walking, gait measures are substantially influenced by contextual and environmental factors, as it has been shown in healthy subjects as well as for different patient populations. Thus, we introduce a context-sensitive matching procedure of individual walking bouts to reveal disease-related rather than purely context-driven longitudinal changes in variability measures. METHODS: We assessed longitudinal gait changes of 24 subjects with degenerative cerebellar disease (SARA:9.4±4.1) at baseline and 1-year and 2-year follow-up assessment by 3 body-worn inertial sensors in two conditions: (1) laboratory-based walking; (2) real-life walking during everyday living. In the real-life walking condition, a context-sensitive analysis was performed by selecting comparable walking bouts according to macroscopic gait characteristics namely bout length and number of turns within a two-minutes time interval. Movement analysis focussed on measures of spatio-temporal variability, in particular lateral step deviation (LD) and a compound measure of spatial variability (SPcmp). RESULTS: Cross-sectional analyses revealed high correlation to ataxia severity (SARA) and patients subjective balance confidence (ABC Scale) in both conditions (r > 0.8). While clinical ataxia score and gait measure in lab-based gait assessments identified changes after two years only (SARA: rprb = 0.71; LD: rprb = 0.67) in real life gait assessment the features of lateral step deviation and a compound measure of spatial step variability identified changes already prb after one year with high effect sizes (LD: rprb = 0.66; SPcmp: rprb = 0.68) and increased effect sizes after two years (LD: rprb = 0.77; SPcmp: rprb = 0.82). CONCLUSIONS: Utilizing a context-sensitive matching procedure, real-life gait measures capture longitudinal change within short trial-like time frames like 1 year with high effect size. In contrast, clinical scores like the SARA as well as lab-based gait measures show longitudinal change only after two years. Thus, features of real-life gait constitute promising biomarkers for upcoming therapeutical trials, delivering ecologically validity as well as increased effect sizes in comparison with clinical scores and lab-based gait assessment.

Authors: Seemann, Jens; Ilg, Winfried; Giese, Martin A.; Synofzik, Matthis
Research Areas: Uncategorized
Type of Publication: In Collection
Ilg, W., Seemann, J., Sarvestan, J., Din, S. D., Synofzik, M. & Alcock, L (2023). Inertial sensors on the feet, rather than lumbar sensor only, increase sensitivity of spatio- temporal gait measures to longitudinal progression in ataxia. . International Symposium on Posture and Gait Research, JULY 9 – 13, BRISBANE, AUSTRALIA.
Inertial sensors on the feet, rather than lumbar sensor only, increase sensitivity of spatio- temporal gait measures to longitudinal progression in ataxia.
Authors: Ilg, Winfried; Seemann, Jens; Sarvestan, Javad Din, Silvia Del Synofzik, Matthis Alcock, Lisa
Research Areas: Uncategorized
Type of Publication: In Collection
Full text: PDF
Seemann, J., Loris, T., Weber, L., Giese, M. A. & Ilg, W (2023). Can machine learning techniques reduce the number of inertial sensors in real life gait analysis? . International Symposium on Posture and Gait Research, JULY 9 – 13, BRISBANE, AUSTRALIA.
Can machine learning techniques reduce the number of inertial sensors in real life gait analysis?
Abstract:

BACKGROUND AND AIM: The optimal number of inertial sensors for real-life gait analysis is a trade-off between data quality and patient convenience and feasibility. One-sensor systems have proven to deliver reliable information for average values of gait speed or step length. However, for the ataxic-sensitive measures of spatio-temporal gait variability, these systems reported less reliability and less sensitivity compared to 3 sensor systems including two sensors at the feet. Here, we investigate the potential of machine learning techniques to predict gait features based on 1 sensor only, which could increase the clinical feasibility of instrumented gait analysis in real-life recordings of cerebellar ataxic patients. METHODS: We recorded gait data from 44 healthy controls and 55 cerebellar patients at baseline, 1-year and 2-years follow-up assessments by 3 Opal APDM inertial sensors. These data successful identified longitudinal changes in gait variability measures for cerebellar patients (e.g. stride length variability, effect size: 0.53) Utilising 1D convolutional neural networks (1D-CNN) we predicted 14 gait parameters from stride based triaxial IMU data in two conditions with different input dimensions: using raw data from the pelvis sensor only (1S) in comparison to the complete set of all three sensors (3S). Thus, in the supervised training phase of both conditions, we used stride based gait features previously determined by the 3 sensors algorithm from APDM as ground truth. Aim in both approaches is to individualize the learned mappings for a new unseen patient based on a small amount of recorded gait samples with 3 sensors in the lab and to use transfer learning for the characterisation of real-life data. RESULTS: First results deliver a low (

Authors: Seemann, Jens; Loris, Tim Weber, Lukas Giese, Martin A.; Ilg, Winfried
Research Areas: Uncategorized
Type of Publication: In Collection
Full text: PDF
Rens, G., Bognár, A., Raman, R., Taubert, N., Li, B., Giese, M. A. et al (2023). Similarity in monkey fMRI activation patterns for human and monkey faces but not bodies . 13th Annual Meeting on PrimateNeurobiology, Apr.26-28 2023, Göttingen Primate Center..
Similarity in monkey fMRI activation patterns for human and monkey faces but not bodies
Authors: Rens, G. Bognár, A. Raman, R. Taubert, Nick; Li, B. Giese, Martin A.; Gelder, B. De
Research Areas: Uncategorized
Type of Publication: In Collection

Year: 2022

Primbs, J., Ilg, W., Thierfelder, A., Severitt, B., Hohnecker, C. S., Alt, A. K. et al. (2022). The SSTeP-KiZ System—Secure Real-Time Communication Based on Open Web Standards for Multimodal Sensor-Assisted Tele-Psychothera. Sensors, 22(24), 9589.
The SSTeP-KiZ System—Secure Real-Time Communication Based on Open Web Standards for Multimodal Sensor-Assisted Tele-Psychothera
Abstract:

In this manuscript, we describe the soft- and hardware architecture as well as the implementation of a modern Internet of Medical Things (IoMT) system for sensor-assisted telepsychotherapy. It enables telepsychotherapy sessions in which the patient exercises therapy-relevant behaviors in their home environment under the remote supervision of the therapist. Wearable sensor information (electrocardiogram (ECG), movement sensors, and eye tracking) is streamed in real time to the therapist to deliver objective information about specific behavior-triggering situations and the stress level of the patients. We describe the IT infrastructure of the system which uses open standards such as WebRTC and OpenID Connect (OIDC). We also describe the system’s security concept, its container-based deployment, and demonstrate performance analyses. The system is used in the ongoing study SSTeP-KiZ (smart sensor technology in telepsychotherapy for children and adolescents with obsessive-compulsive disorder) and shows sufficient technical performance.

Authors: Primbs, Jonas Ilg, Winfried; Thierfelder, Annika; Severitt, Björn Hohnecker, Carolin Sarah Alt, Annika Kristin Pascher, Anja Wörz, Ursula Lautenbacher, Heinrich Hollmann, Karsten Barth, Gottfried Maria Renner, Tobias Menth, Michael
Type of Publication: Article
Full text: PDF | Online version
Benali, A., Tsutsui, K.-I., Sekino, M. & Pfeiffer, F. (2022). Brain Stimulation: From Basic Research to Clinical Use. FRONTIERS EBOOK.
Brain Stimulation: From Basic Research to Clinical Use
Abstract:

The aim of this Research Topic was to show how broad the field of brain stimulation has become recently, including basic research and clinical application. Numerous brain stimulation methods are being investigated to serve as neuromodulatory techniques, treating a variety of neuropsychiatric or neurological disorders (Antal et al., 2022; Camacho-Conde et al., 2022; Siebner et al., 2022). They can be divided into noninvasive and invasive methods. Non-invasive brain stimulation includes transcranial magnetic stimulation (TMS), transcranial direct current stimulation (tDCS) and transcranial alternating current stimulation (tACS), transcranial electrical stimulation (tES) and non-invasive vagus nerve stimulation (VNS). Invasive brain stimulation consists of intracortical microstimulation (ICMS) and deep brain stimulation (DBS)

Authors: Benali, Alia; Tsutsui, Ken-Ichiro Sekino, Masaki Pfeiffer, Friederike
Type of Publication: Book
Publisher: FRONTIERS EBOOK
Editor: Benali, A., Tsutsui, K-I., Sekino, M., Pfeiffer, F.
Month: Dec. 2022
ISBN: 978-2-83250-757-5
Full text: PDF | Online version
Cabaraux, P., Agrawal, S. K., Cai, H., Calabro, R. S., Cassali, C., Ilg, W. et al. (2022). Consensus Paper: Ataxic Gait. Cerebellum, 21(2).
Consensus Paper: Ataxic Gait
Abstract:

The aim of this consensus paper is to discuss the roles of the cerebellum in human gait, as well as its assessment and therapy. Cerebellar vermis is critical for postural control. The cerebellum ensures the mapping of sensory information into temporally relevant motor commands. Mental imagery of gait involves intrinsically connected fronto-parietal networks comprising the cerebellum. Muscular activities in cerebellar patients show impaired timing of discharges, affecting the patterning of the synergies subserving locomotion. Ataxia of stance/gait is amongst the first cerebellar deficits in cerebellar disorders such as degenerative ataxias and is a disabling symptom with a high risk of falls. Prolonged discharges and increased muscle coactivation may be related to compensatory mechanisms and enhanced body sway, respectively. Essential tremor is frequently associated with mild gait ataxia. There is growing evidence for an important role of the cerebellar cortex in the pathogenesis of essential tremor. In multiple sclerosis, balance and gait are affected due to cerebellar and spinal cord involvement, as a result of disseminated demyelination and neurodegeneration impairing proprioception. In orthostatic tremor, patients often show mild-to-moderate limb and gait ataxia. The tremor generator is likely located in the posterior fossa. Tandem gait is impaired in the early stages of cerebellar disorders and may be particularly useful in the evaluation of pre-ataxic stages of progressive ataxias. Impaired inter-joint coordination and enhanced variability of gait temporal and kinetic parameters can be grasped by wearable devices such as accelerometers. Kinect is a promising low cost technology to obtain reliable measurements and remote assessments of gait. Deep learning methods are being developed in order to help clinicians in the diagnosis and decision-making process. Locomotor adaptation is impaired in cerebellar patients. Coordinative training aims to improve the coordinative strategy and foot placements across strides, cerebellar patients benefiting from intense rehabilitation therapies. Robotic training is a promising approach to complement conventional rehabilitation and neuromodulation of the cerebellum. Wearable dynamic orthoses represent a potential aid to assist gait. The panel of experts agree that the understanding of the cerebellar contribution to gait control will lead to a better management of cerebellar ataxias in general and will likely contribute to use gait parameters as robust biomarkers of future clinical trials.

Authors: Cabaraux, P. Agrawal, S. K. Cai, H. Calabro, R. S. Cassali, C. Ilg, Winfried; Damm, L. Doss, S. Habas, C. Horn, A. K. E. Louis, E. D. Mitoma, H. Monaco, V. Petracca, M. Ranavolo, R. Rao, A. K. Ruggieri, S. Schirinzi, T. Serrao, M. Summa, S. Strupp, M. Surgent, O. Synofzik, M. Tao, S. Terasi, H. Torres‑Russotto, D. Travers, B. Roper, J. A. Manto, M.
Research Areas: Uncategorized
Type of Publication: Article
Full text: PDF | Online version
Ilg, W., M\"uller, B., Faber, J., van Gaalen, J., Hengel, H., Vogt, I. R. et al (2022). Digital gait biomarkers, but not clinical ataxia scores, allow to capture 1-year longitudinal change in Spinocerebellar ataxia type 3 (SCA3) . MedRxiv Preprint.
Digital gait biomarkers, but not clinical ataxia scores, allow to capture 1-year longitudinal change in Spinocerebellar ataxia type 3 (SCA3)
Abstract:

Measures of step variability and body sway during gait have shown to correlate with clinical ataxia severity in several cross-sectional studies. However, to serve as a valid progression biomarker, these gait measures have to prove their sensitivity to robustly capture longitudinal change, ideally within short time-frames (e.g. one year). We present the first multi-center longitudinal gait analysis study in spinocerebellar ataxias (SCAs). We performed a combined cross-sectional (n=28) and longitudinal (1-year interval, n=17) analysis in SCA3 subjects (including 7 pre-ataxic mutation carriers). Longitudinal analysis revealed significant change in gait measures between baseline and 1-year follow-up, with high effect sizes (stride length variability: p=0.01, effect size rprb=0.66; lateral sway: p=0.007, rprb=0.73). Sample size estimation for lateral sway reveals a required cohort size of n=43 for detecting a 50% reduction of natural progression, compared to n=240 for the clinical ataxia score SARA. These measures thus present promising motor biomarkers for upcoming interventional studies.

Authors: Ilg, Winfried; M\"uller, Björn Faber, Jennifer van Gaalen, Judith Hengel, Holger Vogt, Ina R. Hennes, Guido van de Warrenburg, Bart Klockgether, Thomas Schoels, Ludger Synofzik, Matthis
Type of Publication: In Collection
Full text: PDF | Online version
Thierfelder, A., Seemann, J., John, N., Harmuth, F., Giese, M. A., Sch\"ule, R. et al. (2022). Real-Life Turning Movements Capture Subtle Longitudinal and Preataxic Changes in Cerebellar Ataxia. Movement Disorders.
Real-Life Turning Movements Capture Subtle Longitudinal and Preataxic Changes in Cerebellar Ataxia
Abstract:

ABSTRACT: Background: Clinical and regulatory acceptance of upcoming molecular treatments in degenerative ataxias might greatly benefit from ecologically valid endpoints that capture change in ataxia severity in patients’ real life. Objectives: This longitudinal study aimed to unravel quantitative motor biomarkers in degenerative ataxias in real-life turning movements that are sensitive for changes both longitudinally and at the preataxic stage. Methods: Combined cross-sectional (n = 30) and longitudinal (n = 14, 1-year interval) observational study in degenerative cerebellar disease (including eight preataxic mutation carriers) compared to 23 healthy controls. Turning movements were assessed by three body-worn inertial sensors in three conditions: (1) instructed laboratory assessment, (2) supervised free walking, and (3) unsupervised real-life movements. Results: Measures that quantified dynamic balance during turning—lateral velocity change (LVC) and outward acceleration—but not general turning measures such as speed, allowed differentiating ataxic against healthy subjects in real life (effect size δ = 0.68), with LVC also differentiating preataxic against healthy subjects (δ = 0.53). LVC was highly correlated with clinical ataxia severity (scale for the assessment and rating of ataxia [SARA] score, effect size ρ = 0.79) and patient reported balance confidence (activity-specific balance confidence scale [ABC] score, ρ = 0.66). Moreover, LVC in real life—but not general turning measures or the SARA score—allowed detecting significant longitudinal change in 1-year follow-up with high effect size (rprb = 0.66). Conclusions: Measures of turning allow capturing specific changes of dynamic balance in degenerative ataxia in real life, with high sensitivity to longitudinal differences

Authors: Thierfelder, Annika; Seemann, Jens; John, Natalie Harmuth, Florian Giese, Martin A.; Sch\"ule, Rebecca Schöls, Ludger Timmann, Dagmar Synofzik, Matthis Ilg, Winfried
Research Areas: Uncategorized
Type of Publication: Article
Full text: PDF | Online version
Heinrich, T., Lappe, A. & Hanke, F. D. (2022). Beyond the classic sensory systems: Characteristics of the sense of time of harbor seals (Phoca vitulina) assessed in a visual temporal discrimination and a bisection task. The Anatomical Record, 305(3), 704-714.
Beyond the classic sensory systems: Characteristics of the sense of time of harbor seals (Phoca vitulina) assessed in a visual temporal discrimination and a bisection task
Abstract:

Abstract Beyond the classic sensory systems, the sense of time is most likely involved from foraging to navigation. As a prerequisite for assessing the role time is playing in different behavioral contexts, we further characterized the sense of time of a harbor seal in this study. Supra-second time intervals were presented to the seal in a temporal discrimination and a temporal bisection task. During temporal discrimination, the seal needed to discriminate between a standard time interval (STI) and a longer comparison interval. In the bisection task, the seal learnt to discriminate two STIs. Subsequently, it indicated its subjective perception of test time intervals as resembling either the short or long STI more. The seal, although unexperienced regarding timing experiments, learnt both tasks fast. Depending on task, time interval or duration ratio, it achieved a high temporal sensitivity with Weber fractions ranging from 0.11 to 0.26. In the bisection task, the prerequisites for the Scalar Expectancy Theory including a constant Weber fraction, the bisection point lying close to the geometric mean of the STIs, and no significant influence of the STI pair condition on the probability of a long response were met for STIs with a ratio of 1:2, but not with a ratio of 1:4. In conclusion, the harbor seal's sense of time allows precise and complex judgments of time intervals. Cross-species comparisons suggest that principles commonly found to govern timing performance can also be discerned in harbor seals.

Authors: Heinrich, Tamara Lappe, Alexander; Hanke, Frederike D.
Type of Publication: Article
Full text: PDF | Online version
Laßmann, C., Ilg, W., Rattay, T. W., Schöls, L., Giese, M. A. & Haeufle, D. (2022). Dysfunctional neuro-muscular1 mechanisms explain gradual gait2 changes in prodromal spastic3 paraplegia. medRxiv 2022.
Dysfunctional neuro-muscular1 mechanisms explain gradual gait2 changes in prodromal spastic3 paraplegia
Abstract:

In Hereditary Spastic Paraplegia (HSP) type 4 (SPG4) a length-dependent axonal degeneration in the cortico-spinal tract leads to progressing symptoms of hyperreflexia, muscle weakness, and spasticity of lower extremities. Even before the manifestation of spastic gait, in the prodromal phase, axonal degeneration leads to subtle gait changes. These gait changes – depicted by digital gait recording – are related to disease severity in prodromal and early-to-moderate manifest SPG4 subjects. We hypothesize that dysfunctional neuro-muscular mechanisms such as hyperreflexia and muscle weakness explain these disease severity-related gait changes of prodromal and early-to-moderate manifest SPG4 subjects. We test our hypothesis in computer simulation with a neuro-muscular model of human walking. We introduce neuro-muscular dysfunction by gradually increasing sensory-motor reflex sensitivity based on increased velocity feedback and gradually increasing muscle weakness by reducing maximum isometric force. By increasing hyperreflexia of plantarflexor and dorsiflexor muscles, we found gradual muscular and kinematic changes in neuro-musculoskeletal simulations that are comparable to subtle gait changes found in prodromal SPG4 subjects. Predicting kinematic changes of prodromal and early-to-moderate manifest SPG4 subjects by gradual alterations of sensory-motor reflex sensitivity allows us to link gait as a directly accessible performance marker to emerging neuro-muscular changes for early therapeutic interventions.

Authors: Laßmann, Christian; Ilg, Winfried; Rattay, Tim W. Schöls, Ludger Giese, Martin A.; Haeufle, Daniel
Type of Publication: Article
Full text: PDF
Ilg, W., M\"uller, B., Faber, J., van Gaalen, J., Hengel, H., Vogt, I. R. et al. (2022). Digital gait biomarkers, but not clinical ataxia scores, allow to capture 1-year longitudinal change in Spinocerebellar ataxia type 3 (SCA3). accepted in Movement Disorders 2022.
Digital gait biomarkers, but not clinical ataxia scores, allow to capture 1-year longitudinal change in Spinocerebellar ataxia type 3 (SCA3)
Abstract:

Measures of step variability and body sway during gait have shown to correlate with clinical ataxia severity in several cross-sectional studies. However, to serve as a valid progression biomarker, these gait measures have to prove their sensitivity to robustly capture longitudinal change, ideally within short time-frames (e.g. one year). We present the first multi-center longitudinal gait analysis study in spinocerebellar ataxias (SCAs). We performed a combined cross-sectional (n=28) and longitudinal (1-year interval, n=17) analysis in SCA3 subjects (including 7 pre-ataxic mutation carriers). Longitudinal analysis revealed significant change in gait measures between baseline and 1-year follow-up, with high effect sizes (stride length variability: p=0.01, effect size rprb=0.66; lateral sway: p=0.007, rprb=0.73). Sample size estimation for lateral sway reveals a required cohort size of n=43 for detecting a 50% reduction of natural progression, compared to n=240 for the clinical ataxia score SARA. These measures thus present promising motor biomarkers for upcoming interventional studies.

Authors: Ilg, Winfried; M\"uller, Björn Faber, Jennifer van Gaalen, Judith Hengel, Holger Vogt, Ina R. Hennes, Guido van de Warrenburg, Bart Klockgether, Thomas Schöls, Ludger Synofzik, Matthis
Type of Publication: Article
Full text: PDF
Laßmann, C., Ilg, W., Schneider, M., Völker, M., Haeufle, D., Sch\"ule, R. et al. (2022). Specific gait changes in prodromal hereditary spastic paraplegia type 4 - preSPG4 study. accepted in Movement Disorders 2022.
Specific gait changes in prodromal hereditary spastic paraplegia type 4 - preSPG4 study
Abstract:

Background: In hereditary spastic paraplegia type 4 (SPG4), subclinical gait changes might occur years before patients realize gait disturbances. The prodromal phase of neurodegenerative disease is of particular interest to halt disease progression by future interventions before impairment has manifested. Objectives: Identification of specific movement abnormalities before manifestation of gait impairment and quantification of disease progression in the prodromal phase. Methods: 70 subjects participated in gait assessment, including 30 prodromal SPAST mutation carriers, 17 patients with mild-to-moderate manifest SPG4, and 23 healthy controls. Gait was assessed by an infrared-camera-based motion capture system to analyze features like range of motion and continuous angle trajectories. Those features were correlated with disease severity as assessed by the Spastic Paraplegia Rating Scale (SPRS) and neurofilament light chain (NfL) as a fluid biomarker indicating neurodegeneration. Results: Compared to healthy controls, we found an altered gait pattern in prodromal mutation carriers during the swing phase in segmental angles of the lower leg (p

Authors: Laßmann, Christian; Ilg, Winfried; Schneider, Marc Völker, Maximilian Haeufle, Daniel Sch\"ule, Rebecca Giese, Martin A.; Synofzik, Matthis Schöls, Ludger Rattay, Tim W.
Type of Publication: Article
Full text: PDF
Kumar, P., Taubert, N., Raman, R., Vogels, R., de Gelder, B. & Giese, M. A (2022). Neural model for the representation of static and dynamic bodies in cortical body patches . VSS 2022.
Neural model for the representation of static and dynamic bodies in cortical body patches
Authors: Kumar, Prerana; Taubert, Nick; Raman, Rajani Vogels, Rufin de Gelder, Beatrice Giese, Martin A.
Type of Publication: In Collection
Mukovskiy, A., Hovaidi-Ardestani, M., Salatiello, A., Stettler, M., Vogels, R. & Giese, M. A (2022). Neurophysiologically-inspired computational model of the visual recognition of social behavior and intent . FENS Forum, Paris.
Neurophysiologically-inspired computational model of the visual recognition of social behavior and intent
Abstract:

AIMS: Humans recognize social interactions and intentions from videos of moving abstract stimuli, including simple geometric figures (Heider {&} Simmel, 1944). The neural machinery supporting such social interaction perception is completely unclear. Here, we present a physiologically plausible neural model of social interaction recognition that identifies social interactions in videos of simple geometric figures and fully articulating animal avatars, moving in naturalistic environments. METHODS: We generated the trajectories for both geometric and animal avatars using an algorithm based on a dynamical model of human navigation (Hovaidi-Ardestani, et al., 2018, Warren, 2006). Our neural recognition model combines a Deep Neural Network, realizing a shape-recognition pathway (VGG16), with a top-level neural network that integrates RBFs, motion energy detectors, and dynamic neural fields. The model implements robust tracking of interacting agents based on interaction-specific visual features (relative position, speed, acceleration, and orientation). RESULTS: A simple neural classifier, trained to predict social interaction categories from the features extracted by our neural recognition model, makes predictions that resemble those observed in previous psychophysical experiments on social interaction recognition from abstract (Salatiello, et al. 2021) and naturalistic videos. CONCLUSION: The model demonstrates that recognition of social interactions can be achieved by simple physiologically plausible neural mechanisms and makes testable predictions about single-cell and population activity patterns in relevant brain areas. Acknowledgments: ERC 2019-SyG-RELEVANCE-856495, HFSP RGP0036/2016, BMBF FKZ 01GQ1704, SSTeP-KiZ BMG: ZMWI1-2520DAT700, and NVIDIA Corporation.

Authors: Mukovskiy, Albert; Hovaidi-Ardestani, Mohammad Salatiello, Alessandro; Stettler, Michael; Vogels, Rufin Giese, Martin A.
Type of Publication: In Collection
Giese, M. A., BOGNÁR, A. & Vogels, R (2022). Physiologically-inspired neural model for anorthoscopic perception .
Physiologically-inspired neural model for anorthoscopic perception
Authors: Giese, Martin A.; BOGNÁR, A. Vogels, Rufin
Type of Publication: In Collection
St-Amand, J., Taubert, N., Gizzi, L. & Giese, M. A (2022). A Hierarchical Gaussian Process Control Algorithm for Bimanual Coordination with Hand Rehabilitation Devices .
A Hierarchical Gaussian Process Control Algorithm for Bimanual Coordination with Hand Rehabilitation Devices
Authors: St-Amand, Jesse; Taubert, Nick; Gizzi, Leonardo Giese, Martin A.
Type of Publication: In Collection
Full text: PDF
Siebert, R., Stettler, M., Taubert, N., Dicke, P., Giese, M. A. & Thier, P (2022). Encoding of dynamic facial expressions in the macaque superior temporal sulcus . Society for Neuroscience.
Encoding of dynamic facial expressions in the macaque superior temporal sulcus
Authors: Siebert, Ramona Stettler, Michael; Taubert, Nick; Dicke, Peter Giese, Martin A.; Thier, Peter
Type of Publication: In Collection
Mukovskiy, A., Hovaidi-Ardestani, M., Salatiello, A., Stettler, M., Vogels, R. & Giese, M. A (2022). Physiologically-inspired neural model for social interaction recognition from abstract and naturalistic videos . VSS Annual Meeting 2022.
Physiologically-inspired neural model for social interaction recognition from abstract and naturalistic videos
Authors: Mukovskiy, Albert; Hovaidi-Ardestani, Mohammad Salatiello, Alessandro; Stettler, Michael; Vogels, Rufin Giese, Martin A.
Type of Publication: In Collection
Chiovetto, E., Salatiello, A., D'Avella, A. & Giese, M. A. (2022). Toward a unifying framework for the modeling and identification of motor primitives. Frontiers in computational neuroscience, 16 926345.
Toward a unifying framework for the modeling and identification of motor primitives
Abstract:

A large body of evidence suggests that human and animal movements, despite their apparent complexity and flexibility, are remarkably structured. Quantitative analyses of various classes of motor behaviors consistently identify spatial and temporal features that are invariant across movements. Such invariant features have been observed at different levels of organization in the motor system, including the electromyographic, kinematic, and kinetic levels, and are thought to reflect fixed modules-named motor primitives-that the brain uses to simplify the construction of movement. However, motor primitives across space, time, and organization levels are often described with ad-hoc mathematical models that tend to be domain-specific. This, in turn, generates the need to use model-specific algorithms for the identification of both the motor primitives and additional model parameters. The lack of a comprehensive framework complicates the comparison and interpretation of the results obtained across different domains and studies. In this work, we take the first steps toward addressing these issues, by introducing a unifying framework for the modeling and identification of qualitatively different classes of motor primitives. Specifically, we show that a single model, the anechoic mixture model, subsumes many popular classes of motor primitive models. Moreover, we exploit the flexibility of the anechoic mixture model to develop a new class of identification algorithms based on the Fourier-based Anechoic Demixing Algorithm (FADA). We validate our framework by identifying eight qualitatively different classes of motor primitives from both simulated and experimental data. We show that, compared to established model-specific algorithms for the identification of motor primitives, our flexible framework reaches overall comparable and sometimes superior reconstruction performance. The identification framework is publicly released as a MATLAB toolbox (FADA-T, https://tinyurl.com/compsens) to facilitate the identification and comparison of different motor primitive models.

Authors: Chiovetto, Enrico Salatiello, Alessandro; d'Avella, Andrea Giese, Martin A.
Type of Publication: Article
Full text: PDF
Ramachandra, V., Giese, M. A. & Benali, A. (2022). The Effects of Low-Intensity Repetitive Transcranial Magnetic Stimulation on White Matter Plasticity and Depression. .
The Effects of Low-Intensity Repetitive Transcranial Magnetic Stimulation on White Matter Plasticity and Depression
Authors: Ramachandra, Vishnudev Giese, Martin A.; Benali, Alia
Type of Publication: Article
Full text: PDF | Online version
Hörner, M., Groh, J., Klein, D., Ilg, W., Schöls, L., Santos, S. D. et al. (2022). CNS-associated T-lymphocytes in a mouse model of Hereditary Spastic Paraplegia type 11 (SPG11) are therapeutic targets for established immunomodulators.. accepted in Experimental Neurology.
CNS-associated T-lymphocytes in a mouse model of Hereditary Spastic Paraplegia type 11 (SPG11) are therapeutic targets for established immunomodulators.
Authors: Hörner, M. Groh, J. Klein, D. Ilg, Winfried; Schöls, L. Santos, S. Dos Bergmann, A. Klebe, S. Cauhape, M. Branchu, J. Hachimi, K. El Stevanin, G. Darios, F. Martini, R.
Research Areas: Uncategorized
Type of Publication: Article
Thierfelder, A., Primbs, J., Severitt, B., Hohnecker, C. S., K\"uhnhausen, J., Alt, A. K. et al. (2022). Multimodal sensor-based identification of stress and compulsive actions in children with obsessive-compulsive disorder for telemedical treatment. 44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
Multimodal sensor-based identification of stress and compulsive actions in children with obsessive-compulsive disorder for telemedical treatment
Abstract:

In modern psychotherapy, digital health technology offers advanced and personalized therapy options, increasing availability as well as ecological validity. These aspects have proven to be highly relevant for children and adolescents with obsessive-compulsive disorder (OCD). Exposure and Response Prevention therapy, which is the state-of-the-art treatment for OCD, builds on the reconstruction of everyday life exposure to anxious situations. However, while compulsive behavior predominantly occurs in home environments, exposure situations during therapy are limited to clinical settings. Telemedical treatment allows to shift from this limited exposure reconstruction to exposure situations in real life. In the SSTeP KiZ study (smart sensor technology in telepsychotherapy for children and adolescents with OCD), we combine video therapy with wearable sensors delivering physiological and behavioral measures to objectively determine the stress level of patients. The setup allows to gain information from exposure to stress in a realistic environment both during and outside of therapy sessions. In a first pilot study, we explored the sensitivity of individual sensor modalities to different levels of stress and anxiety. For this, we captured the obsessive-compulsive behavior of five adolescents with an ECG chest belt, inertial sensors capturing hand movements, and an eye tracker. Despite their prototypical nature, our results deliver strong evidence that the examined sensor modalities yield biomarkers allowing for personalized detection and quantification of stress and anxiety. This opens up future possibilities to evaluate the severity of individual compulsive behavior based on multi-variate state classification in real-life situations.

Authors: Thierfelder, Annika; Primbs, Jonas Severitt, Björn Hohnecker, Carolin Sarah K\"uhnhausen, Jan Alt, Annika Kristin Pascher, Anja Wörz, Ursula Passon, Helene Seemann, Jens; Ernst, Christian Lautenbacher, Heinrich Holderried, Martin Kasneci, Enkelejda Giese, Martin A.; Bulling, Andreas Menth, Michael Barth, Gottfried Maria Ilg, Winfried; Hollmann, Karsten Renner, Tobias Johann
Research Areas: Uncategorized
Type of Publication: Article
Full text: PDF | Online version

Year: 2021

Benali, A., Li, B., Ramachandra, V., Oeltermann, A., Giese, M. A. & Schwarz, C (2021). Deciphering the dynamics of neuronal activity evoked by transcranial magnetic stimulation.. Brain Stimulation 14 (6) , 1745. Elsevier.
Deciphering the dynamics of neuronal activity evoked by transcranial magnetic stimulation.
Abstract:

Transcranial magnetic stimulation (TMS), a non-invasive method for stimulating the brain, has been used for more than 35 years. Since then, there have been many human studies using sophisticated methods to infer how TMS interacts with the brain. However, these methods have their limitations, e.g. recording of EEG potentials, which are summation potentials from many cells and generated across many cortical layers, make it very difficult to localize the origin of the potentials and relate it to TMS induced effects. However, this is necessary to build accurate models that predict TMS action in the human brain. In recent years, we have developed a method that allows us to demonstrate nearly the direct effect of a TMS pulse at the cellular level. We transferred a TMS stimulation protocol from humans to a rat model. In this way, we were able to gain direct access to neurons activated by TMS, thereby reducing the parameter space by many factors. Our data show that a single TMS pulse affects cortical neurons for more than 300 ms. In addition to temporal dynamics, there are also spatial effects. These effects arise at both local and global scale after a single TMS pulse. The local effect occurs in the motor cortex and is very short-lived. It is characterized by a high-frequency neuronal discharge and is reminiscent of the I-wave patterns described in humans at the level of the spinal cord. The global effect occurs in many cortical and subcortical areas in both hemispheres and is characterized by an alternation of excitation and inhibition. Both effects either occur together or only the global effect is present. Next, we are planning to correlate these neurometric data with induced electric field modeling to create detailed TMS-triggered neuronal excitation models that could help us better understand cortical TMS interference.

Authors: Benali, Alia; Li, Bingshuo Ramachandra, Vishnudev Oeltermann, Axel Giese, Martin A.; Schwarz, Cornelius
Type of Publication: In Collection
Full text: PDF | Online version
Lang, J., Giese, M. A., Synofzik, M., Ilg, W. & Otte, S. (2021). Early Recognition of Ball Catching Success in Clinical Trials with RNN-Based Predictive Classification.. - ICANN 2021 30th International Conference on Artificial Neural Networks.
Early Recognition of Ball Catching Success in Clinical Trials with RNN-Based Predictive Classification.
Abstract:

Motor disturbances can affect the interaction with dynamic objects, such as catching a ball. A classification of clinical catching trials might give insight into the existence of pathological alterations in the relation of arm and ball movements. Accurate, but also early decisions are required to classify a catching attempt before the catcher's first ball contact. To obtain clinically valuable results, a significant decision confidence of at least 75% is required. Hence, three competing objectives have to be optimized at the same time: accuracy, earliness and decision-making confidence. Here we propose a coupled classification and prediction approach for early time series classification: a predictive, generative recurrent neural network (RNN) forecasts the next data points of ball trajectories based on already available observations; a discriminative RNN continuously generates classification guesses based on the available data points and the unrolled sequence predictions. We compare our approach, which we refer to as predictive sequential classification (PSC), to state-of-the-art sequence learners, including various RNN and temporal convolutional network (TCN) architectures. On this hard real-world task we can consistently demonstrate the superiority of PSC over all other models in terms of accuracy and confidence with respect to earliness of recognition. Specifically, PSC is able to confidently classify the success of catching trials as early as 123 milliseconds before the first ball contact. We conclude that PSC is a promising approach for early time series classification, when accurate and confident decisions are required.

Authors: Lang, Jana Giese, Martin A.; Synofzik, M. Ilg, Winfried; Otte, S.
Research Areas: Uncategorized
Type of Publication: Article
Full text: PDF | Online version
Taubert, N., Stettler, M., Siebert, R., Spadacenta, S., Sting, L., Dicke, P. et al. (2021). Shape-invariant encoding of dynamic primate facial expressions in human perception. eLife.
Shape-invariant encoding of dynamic primate facial expressions in human perception
Abstract:

Dynamic facial expressions are crucial for communication in primates. Due to the difficulty to control shape and dynamics of facial expressions across species, it is unknown how species-specific facial expressions are perceptually encoded and interact with the representation of facial shape. While popular neural network models predict a joint encoding of facial shape and dynamics, the neuromuscular control of faces evolved more slowly than facial shape, suggesting a separate encoding. To investigate these alternative hypotheses, we developed photo-realistic human and monkey heads that were animated with motion capture data from monkeys and humans. Exact control of expression dynamics was accomplished by a Bayesian machine-learning technique. Consistent with our hypothesis, we found that human observers learned cross-species expressions very quickly, where face dynamics was represented largely independently of facial shape. This result supports the co-evolution of the visual processing and motor control of facial expressions, while it challenges appearance-based neural network theories of dynamic expression recognition.

Authors: Taubert, Nick; Stettler, Michael; Siebert, R. Spadacenta, S. Sting, L. Dicke, P. Thier, P. Giese, Martin A.
Research Areas: Uncategorized
Type of Publication: Article
Full text: PDF | Online version
Giese, M. A., Mukovskiy, A., Hovaidi-Ardestani, M., Salatiello, A. & Stettler, M. (2021). Neurophysiologically-inspired model for social interactions recognition from abstract and naturalistic stimuli. VSS 2021.
Neurophysiologically-inspired model for social interactions recognition from abstract and naturalistic stimuli
Research Areas: Uncategorized
Type of Publication: Article
Salatiello, A. & Giese, M. A. (2021). Continuous Decoding of Daily-Life Hand Movements from Forearm Muscle Activity for Enhanced Myoelectric Control of Hand Prostheses.. Proceedings of the 2021 IEEE International Joint Conference on Neural Networks, 1-8.
Continuous Decoding of Daily-Life Hand Movements from Forearm Muscle Activity for Enhanced Myoelectric Control of Hand Prostheses.
Abstract:

State-of-the-art motorized hand prostheses are endowed with actuators able to provide independent and proportional control of as many as six degrees of freedom (DOFs). The control signals are derived from residual electromyographic (EMG) activity, recorded concurrently from relevant forearm muscles. Nevertheless, the functional mapping between forearm EMG activity and hand kinematics is only known with limited accuracy. Therefore, no robust method exists for the reliable computation of control signals for the independent and proportional actuation of more than two DOFs. A common approach to deal with this limitation is to preprogram the prostheses for the execution of a restricted number of behaviors (e.g., pinching, grasping, and wrist rotation) that are activated by the detection of specific EMG activation patterns. However, this approach severely limits the range of activities users can perform with the prostheses during their daily living. In this work, we introduce a novel method, based on a long short-term memory (LSTM) network, to map forearm EMG activity onto hand kinematics online. Critically, unlike previous research efforts that tend to focus on simple and highly controlled motor tasks, we tested our method on a dataset of daily living activities (ADLs): the KIN-MUS UJI dataset. To the best of our knowledge, ours is the first reported work on the prediction of hand kinematics that uses this challenging dataset. Remarkably, we show that our network is able to generalize to novel untrained ADLs. Our results suggest that the presented method is suitable for the generation of control signals for the independent and proportional actuation of the multiple DOFs of state-of-the-art hand prostheses.

Research Areas: Uncategorized
Type of Publication: Article
Full text: PDF | Online version
Thierfelder, A., Seemann, J., John, N., Giese, M. A., Schöls, L., Timman, D. et al. (2021). Turning movements in real life capture subtle longitudinal and preataxic changes in cerebellar ataxia. bioRxiv.
Turning movements in real life capture subtle longitudinal and preataxic changes in cerebellar ataxia
Abstract:

OBJECTIVES Clinical and regulatory acceptance of upcoming molecular treatments in degenerative ataxias might greatly benefit from ecologically valid endpoints which capture change in ataxia severity in patients’ real life. This longitudinal study aimed to unravel quantitative motor biomarkers in degenerative ataxias in real life turning movements which are sensitive for changes both longitudinally and at the preataxic stage.

Authors: Thierfelder, Annika; Seemann, Jens; John, N. Giese, Martin A.; Schöls, L. Timman, D. Synofzik, M. Ilg, Winfried
Research Areas: Uncategorized
Type of Publication: Article
Full text: Online version
Benali, A., Pfeiffer, F. & Tsutsui, K.-I. (2021). Brain Stimulation: From Basic Research to Clinical Use. .
Brain Stimulation: From Basic Research to Clinical Use
Abstract:

Originating in basic research, as a basis for understanding the function of brain areas, brain stimulation is currently employed for the treatment of many brain disorders including Parkinson's Disease, Epilepsy, and Depression. However, the available techniques for brain stimulation can differ, in the degree of surgical intervention: Invasive Brain Stimulation (IBS) techniques such as Deep Brain Stimulation (DBS) and Intracortical Microstimulation (ICMS) that require extensive surgical intervention for placement of electrodes, or Non-Invasive Brain Stimulation (NIBS) techniques, for example, Transcranial Magnetic Stimulation (TMS) and Transcranial Electrical Current Stimulation (tES) that require minimal or no intervention. With the development of thin movable electrodes having superior biocompatibility, some of the side effects related to the invasive procedure of IBS will very likely to be overcome. Likewise, advances in NIBS techniques related to spatial and temporal precision have closed the gap to its invasive counterparts. In parallel, considerable progress is being made in research laboratories using brain stimulation techniques to gain deeper insights into brain functions, and underlying neural and glial mechanisms, which in turn increase the efficacy of brain stimulation in treatments. Therefore, the therapeutic potential of stimulation techniques is not yet completed exhausted. However, the question remains, can the results from basic research be transferred easily to treatment of patients? By looking at the successes achieved in the past years, the answer to this question should be yes. Well-described animal models, good theoretical and anatomical models are essential for such translations. The proposed research topic aims to gather more evidence on the role of BS as a tool to better understand the physiological mechanisms of the brain, by studying the temporal and spatial dynamics of cortical and subcortical activations, and to discuss challenges and develop strategies for innovative therapeutic procedures. This Research Topic welcomes Original Research, Perspectives, Systematic Reviews, and Meta-Analyses covering the following topics: - Basic research models, theoretical models, preclinical or clinical applications of cortical and subcortical stimulation using TMS, tES, ICMS, and DBS in animal models and humans - Translational articles dealing with the effects of neuromodulation on the biochemistry of brain tissues, as well as those focusing on modeling strategies and closed-loop technologies - Neurophysiological studies in animal models and humans focusing on the mechanisms leading to altered cortical excitability, plasticity, and connectivity, or new experimental models aimed at understanding changes in cellular processes induced by electrical or inductive stimulation of neurons.

Authors: Benali, Alia; Pfeiffer, Friederike Tsutsui, Ken-Ichiro
Type of Publication: Article
Full text: Online version
Benali, A., Tsutsui, K.-I., Pfeiffer, F. & Sekino, M. (2021). Brain Stimulation: From Basic Research to Clinical Use. Frontiers in Human Neuroscience Brain Imaging and Stimulation. Retrieved from https://www.frontiersin.org/research-topics/18713/brain-stimulation-from-basic-research-to-clinical-use.
Brain Stimulation: From Basic Research to Clinical Use
Abstract:

Originating in basic research, as a basis for understanding the function of brain areas, brain stimulation is currently employed for the treatment of many brain disorders including Parkinson's Disease, Epilepsy, and Depression. However, the available techniques for brain stimulation can differ, in the degree of surgical intervention: Invasive Brain Stimulation (IBS) techniques such as Deep Brain Stimulation (DBS) and Intracortical Microstimulation (ICMS) that require extensive surgical intervention for placement of electrodes, or Non-Invasive Brain Stimulation (NIBS) techniques, for example, Transcranial Magnetic Stimulation (TMS) and Transcranial Electrical Current Stimulation (tES) that require minimal or no intervention. With the development of thin movable electrodes having superior biocompatibility, some of the side effects related to the invasive procedure of IBS will very likely to be overcome. Likewise, advances in NIBS techniques related to spatial and temporal precision have closed the gap to its invasive counterparts. In parallel, considerable progress is being made in research laboratories using brain stimulation techniques to gain deeper insights into brain functions, and underlying neural and glial mechanisms, which in turn increase the efficacy of brain stimulation in treatments. Therefore, the therapeutic potential of stimulation techniques is not yet completed exhausted. However, the question remains, can the results from basic research be transferred easily to treatment of patients? By looking at the successes achieved in the past years, the answer to this question should be yes. Well-described animal models, good theoretical and anatomical models are essential for such translations. The proposed research topic aims to gather more evidence on the role of BS as a tool to better understand the physiological mechanisms of the brain, by studying the temporal and spatial dynamics of cortical and subcortical activations, and to discuss challenges and develop strategies for innovative therapeutic procedures. This Research Topic welcomes Original Research, Perspectives, Systematic Reviews, and Meta-Analyses covering the following topics: - Basic research models, theoretical models, preclinical or clinical applications of cortical and subcortical stimulation using TMS, tES, ICMS, and DBS in animal models and humans - Translational articles dealing with the effects of neuromodulation on the biochemistry of brain tissues, as well as those focusing on modeling strategies and closed-loop technologies - Neurophysiological studies in animal models and humans focusing on the mechanisms leading to altered cortical excitability, plasticity, and connectivity, or new experimental models aimed at understanding changes in cellular processes induced by electrical or inductive stimulation of neurons.

Authors: Benali, Alia; Tsutsui, Ken-Ichiro Pfeiffer, F. Sekino, Masaki
Type of Publication: Electronic Article
Journal: Frontiers in Human Neuroscience Brain Imaging and Stimulation
Full text: Online version
Kumar, P., Taubert, N., Raman, R., Vogels, R., de Gelder, B. & Giese, M. A (2021). Physiologically-inspired neural model for the visual recognition of dynamic bodies . Neuroscience 2021.
Physiologically-inspired neural model for the visual recognition of dynamic bodies
Authors: Kumar, Prerana; Taubert, Nick; Raman, Rajani Vogels, Rufin de Gelder, Beatrice Giese, Martin A.
Type of Publication: In Collection
Kumar, P., Taubert, N., Stettler, M., Vogels, R., de Gelder, B. & Giese, M. A (2021). Neurodynamical model for the visual recognition of dynamic bodies . ECVP 2021.
Neurodynamical model for the visual recognition of dynamic bodies
Authors: Kumar, Prerana; Taubert, Nick; Stettler, Michael; Vogels, Rufin de Gelder, Beatrice Giese, Martin A.
Type of Publication: In Collection
Kumar, P., Taubert, N., Stettler, M., Vogels, R., de Gelder, B. & Giese, M. A (2021). Neurodynamical model for the visual recognition of dynamic bodies . CNS 2021.
Neurodynamical model for the visual recognition of dynamic bodies
Authors: Kumar, Prerana; Taubert, Nick; Stettler, Michael; Vogels, Rufin de Gelder, Beatrice Giese, Martin A.
Type of Publication: In Collection
Giese, M. A., Mukovskiy, A., Hovaidi-Ardestani, M., Salatiello, A. & Stettler, M (2021). Neurophysiologically-inspired model for social interactions recognition from abstract and naturalistic stimuli. VSS 2021, May 21-26 .
Neurophysiologically-inspired model for social interactions recognition from abstract and naturalistic stimuli
Type of Publication: In Collection
Mukovskiy, A., Ardestani, M. H., Salatiello, A., Stettler, M. & Giese, M. A (2021). Physiologically-inspired neural model for social interactions recognition from abstract and naturalistic stimuli. Göttingen Meeting of the German Neuroscience Society 2021, Germany .
Physiologically-inspired neural model for social interactions recognition from abstract and naturalistic stimuli
Type of Publication: In Collection
Taubert, N. & Giese, M. A. (2021). Hierarchical Deep Gaussian Processes Latent Variable Model via Expectation Propagation. Artificial Neural Networks and Machine Learning – ICANN 2021 30th International Conference on Artificial Neural Networks, Bratislava, Slovakia, September 14-17, 2021, Proceedings, Part I. Springer, Berlin.
Hierarchical Deep Gaussian Processes Latent Variable Model via Expectation Propagation
Type of Publication: Article
Full text: PDF

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