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SpikeDeeptector: a deep-learning based method for detection of neural spiking activity

Posted on September 19, 2019October 9, 2020 By jannis No Comments on SpikeDeeptector: a deep-learning based method for detection of neural spiking activity
SpikeDeeptector: a deep-learning based method for detection of neural spiking activity
scientific publication

Journal of Neural Engineering: https://iopscience.iop.org/article/10.1088/1741-2552/ab1e63 In electrophysiology, microelectrodes are the primary source for recording neural data (single unit activity). These microelectrodes can be implanted individually or in the form of arrays containing dozens to hundreds of channels. Recordings of some channels contain neural activity, which are often contaminated with noise. Another fraction of channels does … Read More “SpikeDeeptector: a deep-learning based method for detection of neural spiking activity” »

SfN: Universal Spikedeeptector

Posted on September 19, 2019October 9, 2020 By jannis No Comments on SfN: Universal Spikedeeptector
SfN: Universal Spikedeeptector
Conference participation, scientific publication

State-of-the-art microelectrode array technology enables simultaneous, large-scale single unit recordings from hundreds of channels. Identification of channels recording neural data as compared to noise is the first step for all further analyses. Automatizing this process aims at minimizing the human involvement and time for manual curation. In our previous study, we introduced the “SpikeDeeptector” (SD), … Read More “SfN: Universal Spikedeeptector” »

SfN 2019: Universal Spikedeeptector

Posted on September 19, 2019October 9, 2020 By jannis No Comments on SfN 2019: Universal Spikedeeptector
SfN 2019: Universal Spikedeeptector
Conference participation, scientific publication

State-of-the-art microelectrode array technology enables simultaneous, large-scale single unit recordings from hundreds of channels. Identification of channels recording neural data as compared to noise is the first step for all further analyses. Automatizing this process aims at minimizing the human involvement and time for manual curation. In our previous study, we introduced the “SpikeDeeptector” (SD), … Read More “SfN 2019: Universal Spikedeeptector” »

SfN2018: Temporal stabilized arm movement for efficient neuroprosthetic control by individuals with tetraplegia

Posted on October 31, 2018October 9, 2020 By jannis No Comments on SfN2018: Temporal stabilized arm movement for efficient neuroprosthetic control by individuals with tetraplegia
SfN2018: Temporal stabilized arm movement for efficient neuroprosthetic control by individuals with tetraplegia
scientific publication

The generation of discrete movement with distinct and stable time courses characterizes each human movement and reflect the need to perform catching and interception tasks and for timed action sequences, incorporating dynamically changing environmental constraints. Exo-AnzugSeveral lines of evidence suggest neuronal mechanism for the initiation of movements i.e. in the supplementary motor area (SMA) and the premotor cortex and for movement planning mechanism generating velocity profiles satisfying time constraints.
In order to meet the requirements of on-line evolving trajectories we propose a model, based on dynamical systems which describes goal directed trajectories in humans and generates trajectories for redundant anthropomorphic robotic arms. The analysis of the attractor dynamics based on the qualitative comparison with measurements of resulting trajectories taken from arm movement experiments with humans created a framework able to reproduce and to generate naturalistic human like arm trajectories.

Read More “SfN2018: Temporal stabilized arm movement for efficient neuroprosthetic control by individuals with tetraplegia” »

SfN2018: Temporal stabilized arm movement for efficient neuroprosthetic control by individuals with tetraplegia

Posted on October 31, 2018December 30, 2021 By jannis
SfN2018: Temporal stabilized arm movement for efficient neuroprosthetic control by individuals with tetraplegia
Conference participation, scientific publication

The generation of discrete movement with distinct and stable time courses characterizes each human movement and reflect the need to perform catching and interception tasks and for timed action sequences, incorporating dynamically changing environmental constraints. Exo-AnzugSeveral lines of evidence suggest neuronal mechanism for the initiation of movements i.e. in the supplementary motor area (SMA) and the premotor cortex and for movement planning mechanism generating velocity profiles satisfying time constraints.
In order to meet the requirements of on-line evolving trajectories we propose a model, based on dynamical systems which describes goal directed trajectories in humans and generates trajectories for redundant anthropomorphic robotic arms. The analysis of the attractor dynamics based on the qualitative comparison with measurements of resulting trajectories taken from arm movement experiments with humans created a framework able to reproduce and to generate naturalistic human like arm trajectories.

Read More “SfN2018: Temporal stabilized arm movement for efficient neuroprosthetic control by individuals with tetraplegia” »

Matlab Robot Simulator

Posted on December 26, 2017December 30, 2021 By jannis
Matlab Robot Simulator
software released

Matlab simulator implementing the closed form solution for the inverse kinematics problem for multi redundant open chain manipulators. Download-Link: Download MRobot

Low dimensional representation of human arm movement for efficient neuroprosthetic control by individuals with tetraplegia

Posted on September 21, 2017October 9, 2020 By jannis No Comments on Low dimensional representation of human arm movement for efficient neuroprosthetic control by individuals with tetraplegia
Low dimensional representation of human arm movement for efficient neuroprosthetic control by individuals with tetraplegia
Conference participation, scientific publication

KUKAMenschCropOver the last decades the generation mechanism and the representation of goal- directed movements has been a topic of intensive neurophysiological research. The investigation in the motor, premotor, and parietal areas led to the discovery that the direction of hand’s movement in space was encoded by populations of neurons in these areas together with many other movement parameters. These distributions of population activation reflect how movements are prepared ahead of movement initiation, as revealed by activity induced by cues that precede the imperative signal (Georgopoulos, 1991).

Inspired by those findings a model based on dynamical systems was proposed both, to model goal directed trajectories in humans and to generate trajectories for redundant anthropomorphic robotic arms. The analysis of the attractor dynamics based on the qualitative comparison with measurements of resulting trajectories taken from arm movement experiments with humans (Grimme u. a., 2012) created a framework able to reproduce and to generate naturalistic human like arm trajectories (Iossifidis und Rano, 2013; Iossifidis, Schöner u. a., 2006).

Read More “Low dimensional representation of human arm movement for efficient neuroprosthetic control by individuals with tetraplegia” »

SfN 2017: Low dimensional representation of human arm movement for efficient neuroprosthetic control by individuals with tetraplegia

Posted on September 21, 2017October 9, 2020 By jannis No Comments on SfN 2017: Low dimensional representation of human arm movement for efficient neuroprosthetic control by individuals with tetraplegia
SfN 2017: Low dimensional representation of human arm movement for efficient neuroprosthetic control by individuals with tetraplegia
Conference participation, scientific publication

KUKAMenschCropOver the last decades the generation mechanism and the representation of goal- directed movements has been a topic of intensive neurophysiological research. The investigation in the motor, premotor, and parietal areas led to the discovery that the direction of hand’s movement in space was encoded by populations of neurons in these areas together with many other movement parameters. These distributions of population activation reflect how movements are prepared ahead of movement initiation, as revealed by activity induced by cues that precede the imperative signal (Georgopoulos, 1991).

Inspired by those findings a model based on dynamical systems was proposed both, to model goal directed trajectories in humans and to generate trajectories for redundant anthropomorphic robotic arms. The analysis of the attractor dynamics based on the qualitative comparison with measurements of resulting trajectories taken from arm movement experiments with humans (Grimme u. a., 2012) created a framework able to reproduce and to generate naturalistic human like arm trajectories (Iossifidis und Rano, 2013; Iossifidis, Schöner u. a., 2006).

Read More “SfN 2017: Low dimensional representation of human arm movement for efficient neuroprosthetic control by individuals with tetraplegia” »

MINT TAG 2015: From Brain To Machine and Back

Posted on July 2, 2016October 9, 2020 By jannis No Comments on MINT TAG 2015: From Brain To Machine and Back
MINT TAG 2015: From Brain To Machine and Back
invited talk, press release

Eingeladener Vortrag beim MINT TAG 2015: https://kt-essen.lms.schulon.org/mod/resource/view.php?id=1496 Was ist Denken? Wie entsteht es? Und warum kann der Mensch es so gut und Maschinen – trotz Computerisierung – nicht? Die neuronalen Strukturen bilden die Basis des Denkens beim Menschen. Jedoch erst die Einheit von Geist und Körper, die Fähigkeit zu komplexen Bewegungen und die stete Interaktion … Read More “MINT TAG 2015: From Brain To Machine and Back” »

MINT TAG 2015: Vom Gehirn zur Maschine

Posted on December 28, 2015October 9, 2020 By jannis No Comments on MINT TAG 2015: Vom Gehirn zur Maschine
MINT TAG 2015: Vom Gehirn zur Maschine
invited talk, press release
Eingeladener Vortrag beim MINT TAG 2015:
https://kt-essen.lms.schulon.org/mod/resource/view.php?id=1496

Was ist Denken? Wie entsteht es? Und warum kann der Mensch es so gut und Maschinen – trotz Computerisierung – nicht?

Die neuronalen Strukturen bilden die Basis des Denkens beim Menschen. Jedoch erst die Einheit von Geist und Körper, die Fähigkeit zu komplexen Bewegungen und die stete Interaktion mit der Umwelt erzeugt kognitive Funktionen. Anhand zahlreicher Beispiele illustriert dieser interessante Vortrag die Zusammenhänge zwischen neuronalen Strukturen, Denken und Kognition vor dem Hintergrund der Evolution bei Mensch und Maschine.

Read More “MINT TAG 2015: Vom Gehirn zur Maschine” »

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Recent Posts

  • (no title) June 18, 2026
  • New journal article: Predicting Muscle Activity from Upper Limb Kinematics with LSTM Networks June 7, 2026
  • New preprint: The Spatial and Temporal Resolution of Motor Intention in Multi-Target Prediction June 7, 2026
  • New paper: Performance Boundaries for BCIs Using Error-Related Potentials and Reinforcement Learning June 7, 2026
  • New paper: Distributional Properties of ReLU-Activations in Neural Networks That Learn by Memorization June 7, 2026

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