2026
Zabbah, Sajjad; Alexander, Nicholas A; Mohammadi, Yousef; Mariola, Alberto; Seymour, Robert A; Puvvada, Sahitya; Barnes, Gareth R; Bach, Dominik R.
An integrated virtual reality platform for naturalistic neuroimaging with magnetoencephalography Journal Article
In: bioRxiv, 2026.
@article{Zabbah2026.01.28.701672,
title = {An integrated virtual reality platform for naturalistic neuroimaging with magnetoencephalography},
author = {Sajjad Zabbah and Nicholas A Alexander and Yousef Mohammadi and Alberto Mariola and Robert A Seymour and Sahitya Puvvada and Gareth R Barnes and Dominik R. Bach},
url = {https://www.biorxiv.org/content/early/2026/01/30/2026.01.28.701672},
doi = {10.64898/2026.01.28.701672},
year = {2026},
date = {2026-01-01},
journal = {bioRxiv},
publisher = {Cold Spring Harbor Laboratory},
abstract = {Studying the brain in motion promises deep insights into the neural circuits that support complex, real-world behaviour. In humans, wearable optically pumped magnetometers (OPMs) enable magnetoencephalography (MEG) with millisecond temporal resolution and millimetre spatial precision during movement. Integrating this technology with virtual reality (VR) could enable fully naturalistic experimental paradigms, but magnetic interference from existing head-mounted displays (HMDs) prevents reliable whole-brain MEG recordings. Here, we present and validate a VR system that integrates with wearable, OPM-based MEG. At its core is a purpose-designed HMD with minimal ferromagnetic material, resulting in magnetic flux density two orders of magnitude lower than consumer-grade alternatives at comparable resolution and weight. Using phantom measurements and established perceptual and cognitive benchmark tasks across participants, we demonstrate robust stimulus-induced neuronal activity at both sensor and source level. Crucially, these sources span the entire brain, including visual, motor and prefrontal cortices, as well as hippocampus. Our proposed VR system is straightforward to produce, readily extendable, and enables whole-brain MEG during immersive, naturalistic behaviours.Competing Interest StatementThe authors have declared no competing interest.European Research Council, https://ror.org/0472cxd90, ERC-2018 CoG-816564 ActionContraThreatWellcome Trust, 226793/Z/22/ZMinistry of Culture and Science of the State of North Rhine-Westphalia, Germany, iBehave, PB22-063A InVirtuo 4.0},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Studying the brain in motion promises deep insights into the neural circuits that support complex, real-world behaviour. In humans, wearable optically pumped magnetometers (OPMs) enable magnetoencephalography (MEG) with millisecond temporal resolution and millimetre spatial precision during movement. Integrating this technology with virtual reality (VR) could enable fully naturalistic experimental paradigms, but magnetic interference from existing head-mounted displays (HMDs) prevents reliable whole-brain MEG recordings. Here, we present and validate a VR system that integrates with wearable, OPM-based MEG. At its core is a purpose-designed HMD with minimal ferromagnetic material, resulting in magnetic flux density two orders of magnitude lower than consumer-grade alternatives at comparable resolution and weight. Using phantom measurements and established perceptual and cognitive benchmark tasks across participants, we demonstrate robust stimulus-induced neuronal activity at both sensor and source level. Crucially, these sources span the entire brain, including visual, motor and prefrontal cortices, as well as hippocampus. Our proposed VR system is straightforward to produce, readily extendable, and enables whole-brain MEG during immersive, naturalistic behaviours.Competing Interest StatementThe authors have declared no competing interest.European Research Council, https://ror.org/0472cxd90, ERC-2018 CoG-816564 ActionContraThreatWellcome Trust, 226793/Z/22/ZMinistry of Culture and Science of the State of North Rhine-Westphalia, Germany, iBehave, PB22-063A InVirtuo 4.0
2025
Bhatti, Faraz Ahmad; Riaz, Qaiser; Krüger, Björn
Beyond Falls: A Hybrid CNN–LSTM–Attention Framework for Pre-, Transition-, and Post-Fall Detection with Wearable Inertial Sensors Journal Article
In: IEEE Access, 2025.
@article{Bhatti2025,
title = {Beyond Falls: A Hybrid CNN–LSTM–Attention Framework for Pre-, Transition-, and Post-Fall Detection with Wearable Inertial Sensors},
author = {Faraz Ahmad Bhatti and Qaiser Riaz and Björn Krüger},
doi = {10.1109/ACCESS.2025.3641198},
year = {2025},
date = {2025-12-05},
urldate = {2025-12-02},
journal = {IEEE Access},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Moontaha, Sidratul; Cavalier, Constanze; Esser, Birgitta; Jordan, Arthur; Goebel, Ines; Anders, Christoph; Mimi, Afsana; Krüger, Björn; Surges, Rainer; Arnrich, Bert
EPIStress: A multimodal dataset of Physiological signals to measure cognitive stress in epilepsy patients Journal Article
In: Scientific Data, vol. 12, iss. 1, no. 1867, 2025, ISBN: 2052-4463.
@article{Moontaha2025,
title = {EPIStress: A multimodal dataset of Physiological signals to measure cognitive stress in epilepsy patients},
author = {Sidratul Moontaha and Constanze Cavalier and Birgitta Esser and Arthur Jordan and Ines Goebel and Christoph Anders and Afsana Mimi and Björn Krüger and Rainer Surges and Bert Arnrich},
url = {https://doi.org/10.1038/s41597-025-06328-3},
doi = {10.1038/s41597-025-06328-3},
isbn = {2052-4463},
year = {2025},
date = {2025-11-28},
urldate = {2025-12-01},
journal = {Scientific Data},
volume = {12},
number = {1867},
issue = {1},
abstract = {Epilepsy patients commonly report stress as a frequent seizure trigger; however, the objective seizure-stress relationship is unclear due to self-report biases and difficulty in objective quantification of stress. This work presents a dataset from twenty epilepsy patients undergoing cognitive stress elicitation protocols, participating in laboratory experiments with computer-based tasks at predefined difficulty levels, and in situational experiments by independently choosing tasks with at least two difficulty levels. Physiological signals from wearable electroencephalography, photoplethysmography, acceleration, electrodermal activity, and temperature sensors were recorded. The task-related perceived cognitive stress was collected using two 5-point Likert scales of self-reported mental workload and stress, contrasted by a pairwise NASA-TLX questionnaire. Additionally, the dataset includes a patient-reported list of seizure-provoking and -inhibiting factors. Results illustrated individual and heterogeneous responses to cognitive tasks, with some modalities yielding statistically significant features, while others demonstrated expected directional trends. The findings support the validity and suitability of the proposed dataset for cognitive stress detection and the potential to map seizure-related factors to cognitive stress events.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Epilepsy patients commonly report stress as a frequent seizure trigger; however, the objective seizure-stress relationship is unclear due to self-report biases and difficulty in objective quantification of stress. This work presents a dataset from twenty epilepsy patients undergoing cognitive stress elicitation protocols, participating in laboratory experiments with computer-based tasks at predefined difficulty levels, and in situational experiments by independently choosing tasks with at least two difficulty levels. Physiological signals from wearable electroencephalography, photoplethysmography, acceleration, electrodermal activity, and temperature sensors were recorded. The task-related perceived cognitive stress was collected using two 5-point Likert scales of self-reported mental workload and stress, contrasted by a pairwise NASA-TLX questionnaire. Additionally, the dataset includes a patient-reported list of seizure-provoking and -inhibiting factors. Results illustrated individual and heterogeneous responses to cognitive tasks, with some modalities yielding statistically significant features, while others demonstrated expected directional trends. The findings support the validity and suitability of the proposed dataset for cognitive stress detection and the potential to map seizure-related factors to cognitive stress events.
Steininger, Melissa; Marquardt, Alexander; Perusquía-Hernández, Monica; Lehnort, Marvin; Otsubo, Hiromu; Dollack, Felix; Kruijff, Ernst; Krüger, Björn; Kiyokawa, Kiyoshi; Riecke, Bernhard E.
The Awe-some Spectrum: Self-Reported Awe Varies by Eliciting Scenery and Presence in Virtual Reality, and the User's Nationality Proceedings Article
In: 2025 IEEE International Symposium on Mixed and Augmented Reality (ISMAR), pp. 1267-1277, 2025.
@inproceedings{steininger2025c,
title = {The Awe-some Spectrum: Self-Reported Awe Varies by Eliciting Scenery and Presence in Virtual Reality, and the User's Nationality},
author = {Melissa Steininger and Alexander Marquardt and Monica Perusquía-Hernández and Marvin Lehnort and Hiromu Otsubo and Felix Dollack and Ernst Kruijff and Björn Krüger and Kiyoshi Kiyokawa and Bernhard E. Riecke},
doi = {10.1109/ISMAR67309.2025.00132},
year = {2025},
date = {2025-11-11},
urldate = {2025-10-01},
booktitle = {2025 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)},
pages = {1267-1277},
abstract = {Awe is a multifaceted emotion often associated with the perception of vastness, that challenges existing mental frameworks. Despite its growing relevance in affective computing and psychological research, awe remains difficult to elicit and measure.
This raises the research questions of how awe can be effectively elicited, which factors are associated with the experience of awe, and whether it can reliably be measured using biosensors.
For this study, we designed ten immersive Virtual Reality (VR) scenes with dynamic transitions from narrow to vast environments. These scenes were used to explore how awe relates to environmental features (abstract, human-made, nature), personality traits, and country of origin. We collected skin conductance, respiration data, and self-reported awe and presence from participants from Germany, Japan, and Jordan.
Our results indicate that self-reported awe varies significantly across countries and scene types. In particular, a scene depicting outer space elicited the strongest awe. Scenes that elicited high self-reported awe also induced a stronger sense of presence. However, we found no evidence that awe ratings are correlated with physiological responses.
These findings challenge the assumption that awe is reliably reflected in autonomic arousal and underscore the importance of cultural and perceptual context.
Our study offers new insights into how immersive VR can be designed to elicit awe, and suggests that subjective reports—rather than physiological signals—remain the most consistent indicators of emotional impact.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Awe is a multifaceted emotion often associated with the perception of vastness, that challenges existing mental frameworks. Despite its growing relevance in affective computing and psychological research, awe remains difficult to elicit and measure.
This raises the research questions of how awe can be effectively elicited, which factors are associated with the experience of awe, and whether it can reliably be measured using biosensors.
For this study, we designed ten immersive Virtual Reality (VR) scenes with dynamic transitions from narrow to vast environments. These scenes were used to explore how awe relates to environmental features (abstract, human-made, nature), personality traits, and country of origin. We collected skin conductance, respiration data, and self-reported awe and presence from participants from Germany, Japan, and Jordan.
Our results indicate that self-reported awe varies significantly across countries and scene types. In particular, a scene depicting outer space elicited the strongest awe. Scenes that elicited high self-reported awe also induced a stronger sense of presence. However, we found no evidence that awe ratings are correlated with physiological responses.
These findings challenge the assumption that awe is reliably reflected in autonomic arousal and underscore the importance of cultural and perceptual context.
Our study offers new insights into how immersive VR can be designed to elicit awe, and suggests that subjective reports—rather than physiological signals—remain the most consistent indicators of emotional impact.
This raises the research questions of how awe can be effectively elicited, which factors are associated with the experience of awe, and whether it can reliably be measured using biosensors.
For this study, we designed ten immersive Virtual Reality (VR) scenes with dynamic transitions from narrow to vast environments. These scenes were used to explore how awe relates to environmental features (abstract, human-made, nature), personality traits, and country of origin. We collected skin conductance, respiration data, and self-reported awe and presence from participants from Germany, Japan, and Jordan.
Our results indicate that self-reported awe varies significantly across countries and scene types. In particular, a scene depicting outer space elicited the strongest awe. Scenes that elicited high self-reported awe also induced a stronger sense of presence. However, we found no evidence that awe ratings are correlated with physiological responses.
These findings challenge the assumption that awe is reliably reflected in autonomic arousal and underscore the importance of cultural and perceptual context.
Our study offers new insights into how immersive VR can be designed to elicit awe, and suggests that subjective reports—rather than physiological signals—remain the most consistent indicators of emotional impact.
Goekay, Uzay; Spurio, Federico; Bach, Dominik R.; Gall, Juergen
Skeleton Motion Words for Unsupervised Skeleton-Based Temporal Action Segmentation Proceedings Article
In: Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), pp. 12101-12111, 2025.
@inproceedings{Gokay_2025_ICCV,
title = {Skeleton Motion Words for Unsupervised Skeleton-Based Temporal Action Segmentation},
author = {Uzay Goekay and Federico Spurio and Dominik R. Bach and Juergen Gall},
year = {2025},
date = {2025-10-01},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
pages = {12101-12111},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Katzner, Steffen; Rose, Tobias; Tchumatchenko, Tatjana; Busse, Laura
The Role of Layer 6 Corticothalamic Circuits in Vision: Plasticity, Sensory Processing, and Behavior Journal Article
In: Annual Review of Vision Science, 2025.
@article{Katzner2025The,
title = {The Role of Layer 6 Corticothalamic Circuits in Vision: Plasticity, Sensory Processing, and Behavior},
author = {Steffen Katzner and Tobias Rose and Tatjana Tchumatchenko and Laura Busse},
url = {https://doi.org/10.1146/annurev-vision-101322-012348},
doi = {10.1146/annurev-vision-101322-012348},
year = {2025},
date = {2025-09-01},
journal = {Annual Review of Vision Science},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Hosseini, Mahan; Klein, Ines; Wunderle, Veronika; Semmler, Carolin; Kuzu, Taylan D.; Kramer, Ann-Kathrin; Tolve, Marianna; Mardare, Vlad; Galvao, Ana; Haustein, Moritz; Grefkes, Christian; Korotkova, Tatiana; Büschges, Ansgar; Fink, Gereon R.; Weiss, Peter H.; Daun, Silvia; Gatto, Graziana
AutoGaitA: A versatile quantitative framework for kinematic analyses across species, perturbations and behaviours Journal Article
In: bioRxiv, pp. 2024.04.14.589409, 2025, ISSN: 2692-8205.
@article{Hosseini2025,
title = {AutoGaitA: A versatile quantitative framework for kinematic analyses across species, perturbations and behaviours},
author = {Mahan Hosseini and Ines Klein and Veronika Wunderle and Carolin Semmler and Taylan D. Kuzu and Ann-Kathrin Kramer and Marianna Tolve and Vlad Mardare and Ana Galvao and Moritz Haustein and Christian Grefkes and Tatiana Korotkova and Ansgar Büschges and Gereon R. Fink and Peter H. Weiss and Silvia Daun and Graziana Gatto},
url = {https://www.biorxiv.org/content/10.1101/2024.04.14.589409v2 https://www.biorxiv.org/content/10.1101/2024.04.14.589409v2.abstract},
doi = {10.1101/2024.04.14.589409},
issn = {2692-8205},
year = {2025},
date = {2025-08-01},
journal = {bioRxiv},
pages = {2024.04.14.589409},
publisher = {Cold Spring Harbor Laboratory},
institution = {bioRxiv},
abstract = {Individual behaviours require the nervous system to execute specialised motor programs, each characterised by unique patterns of coordinated movements across body parts. Deep learning approaches for body-posture tracking have facilitated the analysis of such motor programs. However, translating the resulting time-stamped coordinate datasets into meaningful kinematic representations of motor programs remains a long-standing challenge. We developed the versatile quantitative framework AutoGaitA (Automated Gait Analysis), a Python toolbox that enables comparisons of motor programs at multiple levels of granularity and across tracking methods, species and behaviours. AutoGaitA allowed us to demonstrate that flies, mice, and humans, despite divergent biomechanics, converge on the age-dependent loss of propulsive strength, and that, in mice, locomotor programs adapt as an integrated function of both age and task difficulty. AutoGaitA represents a truly universal framework for robust analyses of motor programs and changes thereof in health and disease, and across species and behaviours. ### Competing Interest Statement The authors have declared no competing interest. Deutsche Forschungsgemeinschaft, SFB 1451 Project-ID 431549029-INF, 431549029-Z02, 328 431549029-Z03},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Individual behaviours require the nervous system to execute specialised motor programs, each characterised by unique patterns of coordinated movements across body parts. Deep learning approaches for body-posture tracking have facilitated the analysis of such motor programs. However, translating the resulting time-stamped coordinate datasets into meaningful kinematic representations of motor programs remains a long-standing challenge. We developed the versatile quantitative framework AutoGaitA (Automated Gait Analysis), a Python toolbox that enables comparisons of motor programs at multiple levels of granularity and across tracking methods, species and behaviours. AutoGaitA allowed us to demonstrate that flies, mice, and humans, despite divergent biomechanics, converge on the age-dependent loss of propulsive strength, and that, in mice, locomotor programs adapt as an integrated function of both age and task difficulty. AutoGaitA represents a truly universal framework for robust analyses of motor programs and changes thereof in health and disease, and across species and behaviours. ### Competing Interest Statement The authors have declared no competing interest. Deutsche Forschungsgemeinschaft, SFB 1451 Project-ID 431549029-INF, 431549029-Z02, 328 431549029-Z03
Mustafa, Sarah Al-Haj; Jansen, Anna; Steininger, Melissa; Müllers, Johannes; Surges, Rainer; Wrede, Randi; Krüger, Björn; Helmstaedter, Christoph
Eyes on Cognition: Exploring Oculomotor Correlates of Cognitive Function in Patients with Epilepsy Journal Article
In: Epilepsy & Behavior, vol. 173, iss. December 2025, no. 110562, 2025.
@article{alhaj2025,
title = {Eyes on Cognition: Exploring Oculomotor Correlates of Cognitive Function in Patients with Epilepsy},
author = {Sarah Al-Haj Mustafa and Anna Jansen and Melissa Steininger and Johannes Müllers and Rainer Surges and Randi Wrede and Björn Krüger and Christoph Helmstaedter},
doi = {10.1016/j.yebeh.2025.110562},
year = {2025},
date = {2025-06-30},
urldate = {2025-06-30},
journal = {Epilepsy & Behavior},
volume = {173},
number = {110562},
issue = {December 2025},
abstract = {Objective
This study investigates the relationship between eye tracking parameters and cognitive performance during the Trail Making Test (TMT) in individuals with epilepsy and healthy controls. By analyzing ocular behaviors such as saccade velocity, fixation duration, and pupil diameter, we aim to determine how these metrics reflect executive functioning and attentional control.
Methods
A sample of 95 participants with epilepsy and 34 healthy controls completed the TMT while their eye movements were recorded. Partial correlations, controlling for age, sex, education, medication count, seizure status and epilepsy duration, examined associations between eye tracking measures and cognitive performance derived from EpiTrack and TMT performance.
Results In the patient group, faster TMT-A performance was associated with shorter fix- ation durations (r = 0.31},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Objective
This study investigates the relationship between eye tracking parameters and cognitive performance during the Trail Making Test (TMT) in individuals with epilepsy and healthy controls. By analyzing ocular behaviors such as saccade velocity, fixation duration, and pupil diameter, we aim to determine how these metrics reflect executive functioning and attentional control.
Methods
A sample of 95 participants with epilepsy and 34 healthy controls completed the TMT while their eye movements were recorded. Partial correlations, controlling for age, sex, education, medication count, seizure status and epilepsy duration, examined associations between eye tracking measures and cognitive performance derived from EpiTrack and TMT performance.
Results In the patient group, faster TMT-A performance was associated with shorter fix- ation durations (r = 0.31
This study investigates the relationship between eye tracking parameters and cognitive performance during the Trail Making Test (TMT) in individuals with epilepsy and healthy controls. By analyzing ocular behaviors such as saccade velocity, fixation duration, and pupil diameter, we aim to determine how these metrics reflect executive functioning and attentional control.
Methods
A sample of 95 participants with epilepsy and 34 healthy controls completed the TMT while their eye movements were recorded. Partial correlations, controlling for age, sex, education, medication count, seizure status and epilepsy duration, examined associations between eye tracking measures and cognitive performance derived from EpiTrack and TMT performance.
Results In the patient group, faster TMT-A performance was associated with shorter fix- ation durations (r = 0.31
Yao, Mingchen; Nagamori, Akira; Maçãs, Sandrina Campos; Azim, Eiman; Sharpee, Tatyana; Goulding, Martyn; Golomb, David; Gatto, Graziana
The spinal premotor network driving scratching flexor and extensor alternation Journal Article
In: Cell Reports, vol. 44, no. 6, 2025, ISSN: 22111247.
@article{Yao2025,
title = {The spinal premotor network driving scratching flexor and extensor alternation},
author = {Mingchen Yao and Akira Nagamori and Sandrina Campos Maçãs and Eiman Azim and Tatyana Sharpee and Martyn Goulding and David Golomb and Graziana Gatto},
url = {https://www.cell.com/action/showFullText?pii=S2211124725006163 https://www.cell.com/action/showAbstract?pii=S2211124725006163 https://www.cell.com/cell-reports/abstract/S2211-1247(25)00616-3},
doi = {10.1016/j.celrep.2025.115845},
issn = {22111247},
year = {2025},
date = {2025-06-01},
journal = {Cell Reports},
volume = {44},
number = {6},
publisher = {Elsevier B.V.},
abstract = {Rhythmic motor behaviors are generated by neural networks termed central pattern generators (CPGs). Although locomotor CPGs have been extensively characterized, it remains unknown how the neuronal populations composing them interact to generate adaptive rhythms in mammals. We explored the cooperation dynamics among the three main populations of ipsilaterally projecting spinal CPG neurons—V1, V2a, and V2b neurons—in scratch reflex rhythmogenesis. Individual ablation of the three neuronal populations reduced the oscillation frequency. Activation of excitatory V2a neurons enhanced the oscillation frequency, while activating inhibitory V1 neurons suppressed movement. Building on these findings, we developed a neuromechanical model made of self-oscillating flexor and extensor modules coupled via inhibition. Rhythm frequency is increased by strong intra-module inhibition and facilitation mechanisms in excitatory neurons and decreased by strong inter-module inhibition. In sum, we describe how genetically identified neuron types and the strengths of their synaptic connections drive scratch rhythmogenesis.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Rhythmic motor behaviors are generated by neural networks termed central pattern generators (CPGs). Although locomotor CPGs have been extensively characterized, it remains unknown how the neuronal populations composing them interact to generate adaptive rhythms in mammals. We explored the cooperation dynamics among the three main populations of ipsilaterally projecting spinal CPG neurons—V1, V2a, and V2b neurons—in scratch reflex rhythmogenesis. Individual ablation of the three neuronal populations reduced the oscillation frequency. Activation of excitatory V2a neurons enhanced the oscillation frequency, while activating inhibitory V1 neurons suppressed movement. Building on these findings, we developed a neuromechanical model made of self-oscillating flexor and extensor modules coupled via inhibition. Rhythm frequency is increased by strong intra-module inhibition and facilitation mechanisms in excitatory neurons and decreased by strong inter-module inhibition. In sum, we describe how genetically identified neuron types and the strengths of their synaptic connections drive scratch rhythmogenesis.
Tolve, Marianna; Tutas, Janine; Özer-Yildiz, Ebru; Klein, Ines; Petzold, Anne; Fritz, Veronika J.; Overhoff, Melina; Silverman, Quinn; Koletsou, Ellie; Liebsch, Filip; Schwarz, Guenter; Korotkova, Tatiana; Valtcheva, Silvana; Gatto, Graziana; Kononenko, Natalia L.
The endocytic adaptor AP-2 maintains Purkinje cell function by balancing cerebellar parallel and climbing fiber synapses Journal Article
In: Cell Reports, vol. 44, no. 2, pp. 2024.06.02.596459, 2025, ISSN: 22111247.
@article{Tolve2025,
title = {The endocytic adaptor AP-2 maintains Purkinje cell function by balancing cerebellar parallel and climbing fiber synapses},
author = {Marianna Tolve and Janine Tutas and Ebru Özer-Yildiz and Ines Klein and Anne Petzold and Veronika J. Fritz and Melina Overhoff and Quinn Silverman and Ellie Koletsou and Filip Liebsch and Guenter Schwarz and Tatiana Korotkova and Silvana Valtcheva and Graziana Gatto and Natalia L. Kononenko},
url = {https://www.biorxiv.org/content/10.1101/2024.06.02.596459v2 https://www.biorxiv.org/content/10.1101/2024.06.02.596459v2.abstract},
doi = {10.1016/j.celrep.2025.115256},
issn = {22111247},
year = {2025},
date = {2025-06-01},
journal = {Cell Reports},
volume = {44},
number = {2},
pages = {2024.06.02.596459},
publisher = {Cold Spring Harbor Laboratory},
institution = {bioRxiv},
abstract = {The loss of cerebellar Purkinje cells is a hallmark of neurodegenerative movement disorders, but the mechanisms remain enigmatic. We show that endocytic adaptor protein complex 2 (AP-2) is crucial for Purkinje cell survival. Using mouse genetics, viral tracing, calcium imaging, and kinematic analysis, we demonstrate that loss of the AP-2 μ subunit in Purkinje cells leads to early-onset ataxia and progressive degeneration. Synaptic dysfunction, marked by an overrepresentation of parallel fibers (PFs) over climbing fibers (CFs), precedes Purkinje cell loss. Mechanistically, AP-2 interacts with the PF-enriched protein GRID2IP, and its loss triggers GRID2IP degradation and glutamate δ2 receptor (GLURδ2) accumulation, leading to an excess of PFs while CFs are reduced. The overrepresentation of PFs increases Purkinje cell network activity, which is mitigated by enhancing glutamate clearance with ceftriaxone. These findings highlight the role of AP-2 in regulating GRID2IP levels in Purkinje cells to maintain PF-CF synaptic balance and prevent motor dysfunction.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The loss of cerebellar Purkinje cells is a hallmark of neurodegenerative movement disorders, but the mechanisms remain enigmatic. We show that endocytic adaptor protein complex 2 (AP-2) is crucial for Purkinje cell survival. Using mouse genetics, viral tracing, calcium imaging, and kinematic analysis, we demonstrate that loss of the AP-2 μ subunit in Purkinje cells leads to early-onset ataxia and progressive degeneration. Synaptic dysfunction, marked by an overrepresentation of parallel fibers (PFs) over climbing fibers (CFs), precedes Purkinje cell loss. Mechanistically, AP-2 interacts with the PF-enriched protein GRID2IP, and its loss triggers GRID2IP degradation and glutamate δ2 receptor (GLURδ2) accumulation, leading to an excess of PFs while CFs are reduced. The overrepresentation of PFs increases Purkinje cell network activity, which is mitigated by enhancing glutamate clearance with ceftriaxone. These findings highlight the role of AP-2 in regulating GRID2IP levels in Purkinje cells to maintain PF-CF synaptic balance and prevent motor dysfunction.
Greß, Hannah; Demidova, Elena; Meier, Michael; Krüger, Björn
SecureNeuroAI: Advanced Security Framework for AI-Powered Multimodal Real-Time Detection of Medical Seizure Events Proceedings Article
In: Ohm, Marc (Ed.): Proceedings of the 15th graduate workshop of the special interest group Security - Intrusion Detection and Response (SIDAR) of the German Informatics Society (GI) (SPRING 2025), pp. 22-24, GI SIG SIDAR, Nuremberg, April, 2025, ISSN: 2190-846X.
@inproceedings{Greß2025,
title = {SecureNeuroAI: Advanced Security Framework for AI-Powered Multimodal Real-Time Detection of Medical Seizure Events},
author = {Hannah Greß and Elena Demidova and Michael Meier and Björn Krüger},
editor = {Marc Ohm},
url = {https://fg-sidar.gi.de/publikationen/sidar-reports},
issn = {2190-846X},
year = {2025},
date = {2025-05-12},
urldate = {2025-05-12},
booktitle = {Proceedings of the 15th graduate workshop of the special interest group Security - Intrusion Detection and Response (SIDAR) of the German Informatics Society (GI) (SPRING 2025)},
pages = {22-24},
publisher = {GI SIG SIDAR},
address = {Nuremberg, April},
abstract = {In today's interconnected world, medical devices are increasingly equipped with novel digital technologies and AI-powered methods to improve the users' quality of life.
Despite the increased possibilities and features these devices offer due to the technical progress, cyberattacks on medical devices will increase as well with possibly severe outcomes for the patients.
At the same time, AI-based technologies could help to detect and mitigate these attacks on medical systems and their data in real-time.
Therefore, our project "SecureNeuroAI" aims to detect epileptic seizures using multimodal sensor data and AI models while also considering possible cyberattacks on this system resulting in an IT-secure system.
Our results will serve as an example for future AI-supported medical devices and systems to enhance their security and to strengthen their trustworthiness towards their (future) users.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
In today's interconnected world, medical devices are increasingly equipped with novel digital technologies and AI-powered methods to improve the users' quality of life.
Despite the increased possibilities and features these devices offer due to the technical progress, cyberattacks on medical devices will increase as well with possibly severe outcomes for the patients.
At the same time, AI-based technologies could help to detect and mitigate these attacks on medical systems and their data in real-time.
Therefore, our project "SecureNeuroAI" aims to detect epileptic seizures using multimodal sensor data and AI models while also considering possible cyberattacks on this system resulting in an IT-secure system.
Our results will serve as an example for future AI-supported medical devices and systems to enhance their security and to strengthen their trustworthiness towards their (future) users.
Despite the increased possibilities and features these devices offer due to the technical progress, cyberattacks on medical devices will increase as well with possibly severe outcomes for the patients.
At the same time, AI-based technologies could help to detect and mitigate these attacks on medical systems and their data in real-time.
Therefore, our project "SecureNeuroAI" aims to detect epileptic seizures using multimodal sensor data and AI models while also considering possible cyberattacks on this system resulting in an IT-secure system.
Our results will serve as an example for future AI-supported medical devices and systems to enhance their security and to strengthen their trustworthiness towards their (future) users.
Khan, Umar; Riaz, Qaiser; Hussain, Mehdi; Zeeshan, Muhammad; Krüger, Björn
Towards Effective Parkinson’s Monitoring: Movement Disorder Detection and Symptom Identification Using Wearable Inertial Sensors Journal Article
In: Algorithms, vol. 18, no. 4, 2025, ISSN: 1999-4893.
@article{2025-khan,
title = {Towards Effective Parkinson’s Monitoring: Movement Disorder Detection and Symptom Identification Using Wearable Inertial Sensors},
author = {Umar Khan and Qaiser Riaz and Mehdi Hussain and Muhammad Zeeshan and Björn Krüger},
url = {https://www.mdpi.com/1999-4893/18/4/203},
doi = {10.3390/a18040203},
issn = {1999-4893},
year = {2025},
date = {2025-04-04},
urldate = {2025-01-01},
journal = {Algorithms},
volume = {18},
number = {4},
abstract = {Parkinson’s disease lacks a cure, yet symptomatic relief can be achieved through various treatments. This study dives into the critical aspect of anomalous event detection in the activities of daily living of patients with Parkinson’s disease and the identification of associated movement disorders, such as tremors, dyskinesia, and bradykinesia. Utilizing the inertial data acquired from the most affected upper limb of the patients, this study aims to create an optimal pipeline for Parkinson’s patient monitoring. This study proposes a two-stage movement disorder detection and classification pipeline for binary classification (normal or anomalous event) and multi-label classification (tremors, dyskinesia, and bradykinesia), respectively. The proposed pipeline employs and evaluates manual feature crafting for classical machine learning algorithms, as well as an RNN-CNN-inspired deep learning model that does not require manual feature crafting. This study also explore three different window sizes for signal segmentation and two different auto-segment labeling approaches for precise and correct labeling of the continuous signal. The performance of the proposed model is validated on a publicly available inertial dataset. Comparisons with existing works reveal the novelty of our approach, covering multiple anomalies (tremors, dyskinesia, and bradykinesia) and achieving 93.03% recall for movement disorder detection (binary) and 91.54% recall for movement disorder classification (multi-label). We believe that the proposed approach will advance the field towards more effective and comprehensive solutions for Parkinson’s detection and symptom classification.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Parkinson’s disease lacks a cure, yet symptomatic relief can be achieved through various treatments. This study dives into the critical aspect of anomalous event detection in the activities of daily living of patients with Parkinson’s disease and the identification of associated movement disorders, such as tremors, dyskinesia, and bradykinesia. Utilizing the inertial data acquired from the most affected upper limb of the patients, this study aims to create an optimal pipeline for Parkinson’s patient monitoring. This study proposes a two-stage movement disorder detection and classification pipeline for binary classification (normal or anomalous event) and multi-label classification (tremors, dyskinesia, and bradykinesia), respectively. The proposed pipeline employs and evaluates manual feature crafting for classical machine learning algorithms, as well as an RNN-CNN-inspired deep learning model that does not require manual feature crafting. This study also explore three different window sizes for signal segmentation and two different auto-segment labeling approaches for precise and correct labeling of the continuous signal. The performance of the proposed model is validated on a publicly available inertial dataset. Comparisons with existing works reveal the novelty of our approach, covering multiple anomalies (tremors, dyskinesia, and bradykinesia) and achieving 93.03% recall for movement disorder detection (binary) and 91.54% recall for movement disorder classification (multi-label). We believe that the proposed approach will advance the field towards more effective and comprehensive solutions for Parkinson’s detection and symptom classification.
Tutas, Janine; Tolve, Marianna; Özer-Yildiz, Ebru; Ickert, Lotte; Klein, Ines; Silverman, Quinn; Liebsch, Filip; Dethloff, Frederik; Giavalisco, Patrick; Endepols, Heike; Georgomanolis, Theodoros; Neumaier, Bernd; Drzezga, Alexander; Schwarz, Guenter; Thorens, Bernard; Gatto, Graziana; Frezza, Christian; Kononenko, Natalia L.
Autophagy regulator ATG5 preserves cerebellar function by safeguarding its glycolytic activity Journal Article
In: Nature Metabolism 2025, pp. 1–24, 2025, ISSN: 2522-5812.
@article{Tutas2025,
title = {Autophagy regulator ATG5 preserves cerebellar function by safeguarding its glycolytic activity},
author = {Janine Tutas and Marianna Tolve and Ebru Özer-Yildiz and Lotte Ickert and Ines Klein and Quinn Silverman and Filip Liebsch and Frederik Dethloff and Patrick Giavalisco and Heike Endepols and Theodoros Georgomanolis and Bernd Neumaier and Alexander Drzezga and Guenter Schwarz and Bernard Thorens and Graziana Gatto and Christian Frezza and Natalia L. Kononenko},
url = {https://www.nature.com/articles/s42255-024-01196-4},
doi = {10.1038/s42255-024-01196-4},
issn = {2522-5812},
year = {2025},
date = {2025-01-01},
journal = {Nature Metabolism 2025},
pages = {1–24},
publisher = {Nature Publishing Group},
abstract = {Dysfunctions in autophagy, a cellular mechanism for breaking down components within lysosomes, often lead to neurodegeneration. The specific mechanisms underlying neuronal vulnerability due to autophagy dysfunction remain elusive. Here we show that autophagy contributes to cerebellar Purkinje cell (PC) survival by safeguarding their glycolytic activity. Outside the conventional housekeeping role, autophagy is also involved in the ATG5-mediated regulation of glucose transporter 2 (GLUT2) levels during cerebellar maturation. Autophagy-deficient PCs exhibit GLUT2 accumulation on the plasma membrane, along with increased glucose uptake and alterations in glycolysis. We identify lysophosphatidic acid and serine as glycolytic intermediates that trigger PC death and demonstrate that the deletion of GLUT2 in ATG5-deficient mice mitigates PC neurodegeneration and rescues their ataxic gait. Taken together, this work reveals a mechanism for regulating GLUT2 levels in neurons and provides insights into the neuroprotective role of autophagy by controlling glucose homeostasis in the brain. Tutas et al. show an unconventional role for autophagy in the regulation of glycolytic flux in cerebellar Purkinje cells by maintaining the levels of the glucose transporter GLUT2.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Dysfunctions in autophagy, a cellular mechanism for breaking down components within lysosomes, often lead to neurodegeneration. The specific mechanisms underlying neuronal vulnerability due to autophagy dysfunction remain elusive. Here we show that autophagy contributes to cerebellar Purkinje cell (PC) survival by safeguarding their glycolytic activity. Outside the conventional housekeeping role, autophagy is also involved in the ATG5-mediated regulation of glucose transporter 2 (GLUT2) levels during cerebellar maturation. Autophagy-deficient PCs exhibit GLUT2 accumulation on the plasma membrane, along with increased glucose uptake and alterations in glycolysis. We identify lysophosphatidic acid and serine as glycolytic intermediates that trigger PC death and demonstrate that the deletion of GLUT2 in ATG5-deficient mice mitigates PC neurodegeneration and rescues their ataxic gait. Taken together, this work reveals a mechanism for regulating GLUT2 levels in neurons and provides insights into the neuroprotective role of autophagy by controlling glucose homeostasis in the brain. Tutas et al. show an unconventional role for autophagy in the regulation of glycolytic flux in cerebellar Purkinje cells by maintaining the levels of the glucose transporter GLUT2.
Bach, Dominik R.
Experiment-based calibration in psychology: Foundational and data-generating model Journal Article
In: Journal of Mathematical Psychology, vol. 127, pp. 102950, 2025, ISSN: 0022-2496.
@article{BACH2025102950,
title = {Experiment-based calibration in psychology: Foundational and data-generating model},
author = {Dominik R. Bach},
url = {https://www.sciencedirect.com/science/article/pii/S0022249625000513},
doi = {https://doi.org/10.1016/j.jmp.2025.102950},
issn = {0022-2496},
year = {2025},
date = {2025-01-01},
journal = {Journal of Mathematical Psychology},
volume = {127},
pages = {102950},
abstract = {Experiment-based calibration is a novel method for measurement validation, which – unlike classical validity metrics – does not require stable between-person variance. In this approach, the latent variable to be measured is manipulated by an experiment, and its predicted scores – termed standard scores – are compared against the measured scores. Previous work has shown that under plausible boundary conditions, the correlation between standard and measured scores – termed retrodictive validity – is informative about measurement accuracy, i.e. combined trueness and precision. Here, I expand these findings in several directions. First, I formalise the approach in a probability-theoretic framework with the concept of a standardised calibration space. Second, I relate this framework to classical validity theory and show that the boundary conditions in fact apply to any form of criterion validity, including classical convergent validity. Thus, I state precise and empirically quantifiable boundary conditions under which criterion validity metrics are informative on validity. Third, I relate these boundary conditions to confounding variables, i.e. correlated latent variables. I show that in the limit, calibration will converge on the latent variable that is most closely related to the standard. Finally, I provide a framework for modelling the data-generating process with Markov kernels, and identify sufficient conditions under which the data generation model results in a calibration space. In sum, this article provides a formal probability-theoretic framework for experiment-based calibration and facilitates modelling and empirical assessment of the data generating processes.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Experiment-based calibration is a novel method for measurement validation, which – unlike classical validity metrics – does not require stable between-person variance. In this approach, the latent variable to be measured is manipulated by an experiment, and its predicted scores – termed standard scores – are compared against the measured scores. Previous work has shown that under plausible boundary conditions, the correlation between standard and measured scores – termed retrodictive validity – is informative about measurement accuracy, i.e. combined trueness and precision. Here, I expand these findings in several directions. First, I formalise the approach in a probability-theoretic framework with the concept of a standardised calibration space. Second, I relate this framework to classical validity theory and show that the boundary conditions in fact apply to any form of criterion validity, including classical convergent validity. Thus, I state precise and empirically quantifiable boundary conditions under which criterion validity metrics are informative on validity. Third, I relate these boundary conditions to confounding variables, i.e. correlated latent variables. I show that in the limit, calibration will converge on the latent variable that is most closely related to the standard. Finally, I provide a framework for modelling the data-generating process with Markov kernels, and identify sufficient conditions under which the data generation model results in a calibration space. In sum, this article provides a formal probability-theoretic framework for experiment-based calibration and facilitates modelling and empirical assessment of the data generating processes.
Bergmann, Cornelius; Mousaei, Kanaan; Rizzoli, Silvio O.; Tchumatchenko, Tatjana
How energy determines spatial localisation and copy number of molecules in neurons Journal Article
In: Nature Communications, 2025.
@article{Bergmann2025_energy,
title = {How energy determines spatial localisation and copy number of molecules in neurons},
author = {Cornelius Bergmann and Kanaan Mousaei and Silvio O. Rizzoli and Tatjana Tchumatchenko},
doi = {10.1038/s41467-025-56640-0},
year = {2025},
date = {2025-01-01},
journal = {Nature Communications},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Brochard, Jules; Dayan, Peter; Bach, Dominik R.
Critical intelligence: Computing defensive behaviour Journal Article
In: Neuroscience & Biobehavioral Reviews, vol. 174, pp. 106213, 2025, ISSN: 0149-7634.
@article{BROCHARD2025106213,
title = {Critical intelligence: Computing defensive behaviour},
author = {Jules Brochard and Peter Dayan and Dominik R. Bach},
url = {https://www.sciencedirect.com/science/article/pii/S0149763425002131},
doi = {https://doi.org/10.1016/j.neubiorev.2025.106213},
issn = {0149-7634},
year = {2025},
date = {2025-01-01},
urldate = {2025-01-01},
journal = {Neuroscience & Biobehavioral Reviews},
volume = {174},
pages = {106213},
abstract = {Characterising the mechanisms underlying naturalistic defensive behavior remains a significant challenge. While substantial progress has been made in unravelling the neural basis of tightly constrained behaviors, a critical gap persists in our comprehension of the circuits that implement algorithms capable of generating the diverse defensive responses observed outside experimental restrictions. Recent advancements in neuroscience technology now allow for an unprecedented examination of naturalistic behaviour. To help provide a theoretical grounding for this nascent experimental programme, we summarise the main computational and statistical challenges of defensive decision making, encapsulated in the concept of critical intelligence. Next, drawing from an extensive literature in biology, machine learning, and decision theory, we explore a range of candidate solutions to these challenges. While the proposed solutions offer insights into potential adaptive strategies, they also present inherent trade-offs and limitations in their applicability across different biological contexts. Ultimately, we propose series of experiments designed to differentiate between these candidate solutions, providing a roadmap for future investigations into the fundamental defensive algorithms utilized by biological agents and their neural implementation. Thus, our work aims to provide a roadmap towards broader understanding of how complex defensive behaviors are orchestrated in the brain, with implications for both neuroscience research and the development of more sophisticated artificial intelligence systems.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Characterising the mechanisms underlying naturalistic defensive behavior remains a significant challenge. While substantial progress has been made in unravelling the neural basis of tightly constrained behaviors, a critical gap persists in our comprehension of the circuits that implement algorithms capable of generating the diverse defensive responses observed outside experimental restrictions. Recent advancements in neuroscience technology now allow for an unprecedented examination of naturalistic behaviour. To help provide a theoretical grounding for this nascent experimental programme, we summarise the main computational and statistical challenges of defensive decision making, encapsulated in the concept of critical intelligence. Next, drawing from an extensive literature in biology, machine learning, and decision theory, we explore a range of candidate solutions to these challenges. While the proposed solutions offer insights into potential adaptive strategies, they also present inherent trade-offs and limitations in their applicability across different biological contexts. Ultimately, we propose series of experiments designed to differentiate between these candidate solutions, providing a roadmap for future investigations into the fundamental defensive algorithms utilized by biological agents and their neural implementation. Thus, our work aims to provide a roadmap towards broader understanding of how complex defensive behaviors are orchestrated in the brain, with implications for both neuroscience research and the development of more sophisticated artificial intelligence systems.
Bergmann, Cornelius; Mousaei, Kanaan; Rizzoli, Silvio O; Tchumatchenko, Tatjana
How energy determines spatial localisation and copy number of molecules in neurons Journal Article
In: Nature Communications, vol. 16, no. 1, pp. 1424, 2025.
@article{bergmann2025energy,
title = {How energy determines spatial localisation and copy number of molecules in neurons},
author = {Cornelius Bergmann and Kanaan Mousaei and Silvio O Rizzoli and Tatjana Tchumatchenko},
year = {2025},
date = {2025-01-01},
journal = {Nature Communications},
volume = {16},
number = {1},
pages = {1424},
publisher = {Nature Publishing Group UK London},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Eggl, Maximilian F; Wagle, Surbhit; Filling, Jean P; Chater, Thomas E; Goda, Yukiko; Tchumatchenko, Tatjana
SpyDen: simplifying molecular and structural analysis across spines and dendrites Journal Article
In: Bioinformatics, vol. 41, no. 7, pp. btaf339, 2025, ISSN: 1367-4811.
@article{10.1093/bioinformatics/btaf339,
title = {SpyDen: simplifying molecular and structural analysis across spines and dendrites},
author = {Maximilian F Eggl and Surbhit Wagle and Jean P Filling and Thomas E Chater and Yukiko Goda and Tatjana Tchumatchenko},
url = {https://doi.org/10.1093/bioinformatics/btaf339},
doi = {10.1093/bioinformatics/btaf339},
issn = {1367-4811},
year = {2025},
date = {2025-01-01},
journal = {Bioinformatics},
volume = {41},
number = {7},
pages = {btaf339},
abstract = {Investigating the molecular composition of different neural compartments such as axons, dendrites, or synapses is critical for understanding learning and memory. State-of-the-art microscopy techniques now resolve individual molecules and pinpoint their position with a micrometer or nanometre resolution across hundreds of micrometres, allowing the labelling of multiple structures of interest simultaneously. Algorithmically, tracking individual molecules across hundreds of micrometres and determining whether they are inside a particular cellular compartment can be challenging. Historically, microscopy images are annotated manually, often using multiple software packages to detect fluorescence puncta and quantify cellular compartments of interest. Advanced ANN-based automated tools, while powerful, often can only help with selected parts of the data analysis, may be optimized for specific spatial resolutions, cell preparations, and may not be fully open source and open access to be sufficiently customizable.Thus, we developed SpyDen, a Python package based upon three principles: (i) ease of use for multi-task scenarios, (ii) open-source accessibility and data export to a standard, open data format, (iii) the ability to edit any software-generated annotation and generalize across spatial resolutions. SpyDen operates on 2D microscopy time-series data, offering robust temporal tracking and spatial analysis capabilities. Equipped with a graphical user interface and accompanied by video tutorials, SpyDen provides a collection of powerful algorithms that can be used for neurite and synapse detection, fluorescent puncta, and intensity analysis. We validated SpyDen using expert annotation across numerous use cases to prove a powerful, integrated platform for efficient and reproducible molecular imaging analysis.SpyDen is available on https://github.com/meggl23/SpyDen while the compiled executables can be found at https://gin.g-node.org/CompNeuroNetworks/SpyDenTrainedNetwork.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Investigating the molecular composition of different neural compartments such as axons, dendrites, or synapses is critical for understanding learning and memory. State-of-the-art microscopy techniques now resolve individual molecules and pinpoint their position with a micrometer or nanometre resolution across hundreds of micrometres, allowing the labelling of multiple structures of interest simultaneously. Algorithmically, tracking individual molecules across hundreds of micrometres and determining whether they are inside a particular cellular compartment can be challenging. Historically, microscopy images are annotated manually, often using multiple software packages to detect fluorescence puncta and quantify cellular compartments of interest. Advanced ANN-based automated tools, while powerful, often can only help with selected parts of the data analysis, may be optimized for specific spatial resolutions, cell preparations, and may not be fully open source and open access to be sufficiently customizable.Thus, we developed SpyDen, a Python package based upon three principles: (i) ease of use for multi-task scenarios, (ii) open-source accessibility and data export to a standard, open data format, (iii) the ability to edit any software-generated annotation and generalize across spatial resolutions. SpyDen operates on 2D microscopy time-series data, offering robust temporal tracking and spatial analysis capabilities. Equipped with a graphical user interface and accompanied by video tutorials, SpyDen provides a collection of powerful algorithms that can be used for neurite and synapse detection, fluorescent puncta, and intensity analysis. We validated SpyDen using expert annotation across numerous use cases to prove a powerful, integrated platform for efficient and reproducible molecular imaging analysis.SpyDen is available on https://github.com/meggl23/SpyDen while the compiled executables can be found at https://gin.g-node.org/CompNeuroNetworks/SpyDenTrainedNetwork.
2024
Kremers, Leon; Rose, Tobias
Feedback needs experience Journal Article
In: Neuron, 2024.
@article{Kremers2024Feedback,
title = {Feedback needs experience},
author = {Leon Kremers and Tobias Rose},
url = {https://doi.org/10.1016/j.neuron.2024.09.016},
doi = {10.1016/j.neuron.2024.09.016},
year = {2024},
date = {2024-10-01},
journal = {Neuron},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Bauer, Joel; Lewin, Uwe; Herbert, Elizabeth; Gjorgjieva, Julijana; Schoonover, Carl E.; Fink, Andrew J. P.; Rose, Tobias; Bonhoeffer, Tobias; Hübener, Mark
Sensory experience steers representational drift in mouse visual cortex Journal Article
In: Nature Communications, 2024.
@article{Bauer2024Sensory,
title = {Sensory experience steers representational drift in mouse visual cortex},
author = {Joel Bauer and Uwe Lewin and Elizabeth Herbert and Julijana Gjorgjieva and Carl E. Schoonover and Andrew J. P. Fink and Tobias Rose and Tobias Bonhoeffer and Mark Hübener},
url = {https://doi.org/10.1038/s41467-024-53326-x},
doi = {10.1038/s41467-024-53326-x},
year = {2024},
date = {2024-10-01},
journal = {Nature Communications},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Pronold, Jari; Meegen, Alexander; Shimoura, Renan O; Vollenbröker, Hannah; Senden, Mario; Hilgetag, Claus C; Bakker, Rembrandt; Albada, Sacha J.
Multi-scale spiking network model of human cerebral cortex Journal Article
In: Cereb Cortex, vol. 34, no. 10, pp. bhae409, 2024, ISSN: 1460-2199.
@article{Pronold24_409,
title = {Multi-scale spiking network model of human cerebral cortex},
author = {Jari Pronold and Alexander Meegen and Renan O Shimoura and Hannah Vollenbröker and Mario Senden and Claus C Hilgetag and Rembrandt Bakker and Sacha J. Albada},
url = {http://dx.doi.org/10.1093/cercor/bhae409},
doi = {10.1093/cercor/bhae409},
issn = {1460-2199},
year = {2024},
date = {2024-10-01},
urldate = {2024-10-01},
journal = {Cereb Cortex},
volume = {34},
number = {10},
pages = {bhae409},
publisher = {Oxford University Press (OUP)},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Trevisan, Alexandra J.; Han, Katie; Chapman, Phillip; Kulkarni, Anand S.; Hinton, Jennifer M.; Ramirez, Cody; Klein, Ines; Gatto, Graziana; Gabitto, Mariano I.; Menon, Vilas; Bikoff, Jay B.
The transcriptomic landscape of spinal V1 interneurons reveals a role for En1 in specific elements of motor output Journal Article
In: bioRxiv, pp. 2024.09.18.613279, 2024.
@article{Trevisan2024,
title = {The transcriptomic landscape of spinal V1 interneurons reveals a role for En1 in specific elements of motor output},
author = {Alexandra J. Trevisan and Katie Han and Phillip Chapman and Anand S. Kulkarni and Jennifer M. Hinton and Cody Ramirez and Ines Klein and Graziana Gatto and Mariano I. Gabitto and Vilas Menon and Jay B. Bikoff},
url = {https://www.biorxiv.org/content/10.1101/2024.09.18.613279v1 https://www.biorxiv.org/content/10.1101/2024.09.18.613279v1.abstract},
doi = {10.1101/2024.09.18.613279},
year = {2024},
date = {2024-09-01},
journal = {bioRxiv},
pages = {2024.09.18.613279},
publisher = {Cold Spring Harbor Laboratory},
institution = {bioRxiv},
abstract = {Neural circuits in the spinal cord are composed of diverse sets of interneurons that play crucial roles in shaping motor output. Despite progress in revealing the cellular architecture of the spinal cord, the extent of cell type heterogeneity within interneuron populations remains unclear. Here, we present a single-nucleus transcriptomic atlas of spinal V1 interneurons across postnatal development. We find that the core molecular taxonomy distinguishing neonatal V1 interneurons perdures into adulthood, suggesting conservation of function across development. Moreover, we identify a key role for En1, a transcription factor that marks the V1 population, in specifying one unique subset of V1Pou6f2 interneurons. Loss of En1 selectively disrupts the frequency of rhythmic locomotor output but does not disrupt flexion/extension limb movement. Beyond serving as a molecular resource for this neuronal population, our study highlights how deep neuronal profiling provides an entry point for functional studies of specialized cell types in motor output. ### Competing Interest Statement The authors have declared no competing interest.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Neural circuits in the spinal cord are composed of diverse sets of interneurons that play crucial roles in shaping motor output. Despite progress in revealing the cellular architecture of the spinal cord, the extent of cell type heterogeneity within interneuron populations remains unclear. Here, we present a single-nucleus transcriptomic atlas of spinal V1 interneurons across postnatal development. We find that the core molecular taxonomy distinguishing neonatal V1 interneurons perdures into adulthood, suggesting conservation of function across development. Moreover, we identify a key role for En1, a transcription factor that marks the V1 population, in specifying one unique subset of V1Pou6f2 interneurons. Loss of En1 selectively disrupts the frequency of rhythmic locomotor output but does not disrupt flexion/extension limb movement. Beyond serving as a molecular resource for this neuronal population, our study highlights how deep neuronal profiling provides an entry point for functional studies of specialized cell types in motor output. ### Competing Interest Statement The authors have declared no competing interest.
Jiang, Han-Jia; Qi, Guanxiao; Duarte, Renato; Feldmeyer, Dirk; Albada, Sacha J.
A layered microcircuit model of somatosensory cortex with three interneuron types and cell-type-specific short-term plasticity Journal Article
In: Cereb Cortex, vol. 34, no. 9, pp. bhae378, 2024, ISSN: 1460-2199.
@article{Jiang24_378,
title = {A layered microcircuit model of somatosensory cortex with three interneuron types and cell-type-specific short-term plasticity},
author = {Han-Jia Jiang and Guanxiao Qi and Renato Duarte and Dirk Feldmeyer and Sacha J. Albada},
url = {http://dx.doi.org/10.1093/cercor/bhae378},
doi = {10.1093/cercor/bhae378},
issn = {1460-2199},
year = {2024},
date = {2024-09-01},
urldate = {2024-09-01},
journal = {Cereb Cortex},
volume = {34},
number = {9},
pages = {bhae378},
publisher = {Oxford University Press (OUP)},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Mancinelli, Federico; Sporrer, Juliana K.; Myrov, Vladislav; Melinscak, Filip; Zimmermann, Josua; Liu, Huaiyu; Bach, Dominik R.
Dimensionality and optimal combination of autonomic fear-conditioning measures in humans Journal Article
In: Behavior Research Methods, vol. 56, no. 6, pp. 6119–6129, 2024, ISSN: 1554-3528.
@article{Mancinelli2024,
title = {Dimensionality and optimal combination of autonomic fear-conditioning measures in humans},
author = {Federico Mancinelli and Juliana K. Sporrer and Vladislav Myrov and Filip Melinscak and Josua Zimmermann and Huaiyu Liu and Dominik R. Bach},
url = {https://doi.org/10.3758/s13428-024-02341-3},
doi = {10.3758/s13428-024-02341-3},
issn = {1554-3528},
year = {2024},
date = {2024-09-01},
journal = {Behavior Research Methods},
volume = {56},
number = {6},
pages = {6119–6129},
abstract = {Fear conditioning, also termed threat conditioning, is a commonly used learning model with clinical relevance. Quantification of threat conditioning in humans often relies on conditioned autonomic responses such as skin conductance responses (SCR), pupil size responses (PSR), heart period responses (HPR), or respiration amplitude responses (RAR), which are usually analyzed separately. Here, we investigate whether inter-individual variability in differential conditioned responses, averaged across acquisition, exhibits a multi-dimensional structure, and the extent to which their linear combination could enhance the precision of inference on whether threat conditioning has occurred. In a mega-analytic approach, we re-analyze nine data sets including 256 individuals, acquired by the group of the last author, using standard routines in the framework of psychophysiological modeling (PsPM). Our analysis revealed systematic differences in effect size between measures across datasets, but no evidence for a multidimensional structure across various combinations of measures. We derive the statistically optimal weights for combining the four measures and subsets thereof, and we provide out-of-sample performance metrics for these weights, accompanied by bias-corrected confidence intervals. We show that to achieve the same statistical power, combining measures allows for a relevant reduction in sample size, which in a common scenario amounts to roughly 24%. To summarize, we demonstrate a one-dimensional structure of threat conditioning measures, systematic differences in effect size between measures, and provide weights for their optimal linear combination in terms of maximal retrodictive validity.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Fear conditioning, also termed threat conditioning, is a commonly used learning model with clinical relevance. Quantification of threat conditioning in humans often relies on conditioned autonomic responses such as skin conductance responses (SCR), pupil size responses (PSR), heart period responses (HPR), or respiration amplitude responses (RAR), which are usually analyzed separately. Here, we investigate whether inter-individual variability in differential conditioned responses, averaged across acquisition, exhibits a multi-dimensional structure, and the extent to which their linear combination could enhance the precision of inference on whether threat conditioning has occurred. In a mega-analytic approach, we re-analyze nine data sets including 256 individuals, acquired by the group of the last author, using standard routines in the framework of psychophysiological modeling (PsPM). Our analysis revealed systematic differences in effect size between measures across datasets, but no evidence for a multidimensional structure across various combinations of measures. We derive the statistically optimal weights for combining the four measures and subsets thereof, and we provide out-of-sample performance metrics for these weights, accompanied by bias-corrected confidence intervals. We show that to achieve the same statistical power, combining measures allows for a relevant reduction in sample size, which in a common scenario amounts to roughly 24%. To summarize, we demonstrate a one-dimensional structure of threat conditioning measures, systematic differences in effect size between measures, and provide weights for their optimal linear combination in terms of maximal retrodictive validity.
Rostami, Vahid; Rost, Thomas; Schmitt, Felix Johannes; Albada, Sacha Jennifer; Riehle, Alexa; Nawrot, Martin Paul
Spiking attractor model of motor cortex explains modulation of neural and behavioral variability by prior target information Journal Article
In: Nature Communications, vol. 15, no. 1, pp. 6304, 2024.
@article{rostami2024spiking,
title = {Spiking attractor model of motor cortex explains modulation of neural and behavioral variability by prior target information},
author = {Vahid Rostami and Thomas Rost and Felix Johannes Schmitt and Sacha Jennifer Albada and Alexa Riehle and Martin Paul Nawrot},
year = {2024},
date = {2024-01-01},
journal = {Nature Communications},
volume = {15},
number = {1},
pages = {6304},
publisher = {Nature Publishing Group UK London},
keywords = {},
pubstate = {published},
tppubtype = {article}
}