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Category: Conference participation

BCCN23: Investigation of the Interplay of Model-Based and Model-Free Learning Using Reinforcement Learning

Posted on September 27, 2023September 28, 2023 By jannis
Conference participation, scientific publication

Investigation of the Interplay of Model-Based and Model-Free Learning Using Reinforcement Learning The reward prediction error hypothesis of dopamine in the brain states that activity of dopaminergic neurons in certain brain regions correlates with the reward prediction error that corresponds to the temporal difference error, often used as a learning signal in model free reinforcement … Read More “BCCN23: Investigation of the Interplay of Model-Based and Model-Free Learning Using Reinforcement Learning” »

Meet Iossifidis Lab at Bernstein Conference 2023

Posted on September 26, 2023September 28, 2023 By jannis
Meet Iossifidis Lab at Bernstein Conference 2023
Conference participation, press release, scientific publication

Iossifidis Lab is participating with 4 publications at the Bernstein Conference 2023 in Berlin. Meet us from 27.09 to 29.09.2023 at the Humboldt Universität zu Berlin and Charité

BCCN23: Exploring Error-related Potentials in Adaptive Brain-Machine Interfaces: Challenges and Investigation of Occurrence and Detection Ratios

Posted on September 26, 2023September 28, 2023 By jannis
Conference participation, scientific publication

Non-invasive techniques like EEG can record error-related potentials (ErrPs), neural signals associated with error processing and awareness. ErrPs are generated in response to self-made and external errors, including those produced by the BMI. Since ErrPs are implicitly elicited and don’t add extra workload for the subject, they serve as a natural and intrinsic feedback source … Read More “BCCN23: Exploring Error-related Potentials in Adaptive Brain-Machine Interfaces: Challenges and Investigation of Occurrence and Detection Ratios” »

SfN: Universal Spikedeeptector

Posted on September 19, 2019October 9, 2020 By jannis No Comments on 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
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, 2018December 30, 2021 By jannis
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” »

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
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
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” »

ICRA2013:Closed Form Solution for Inverse Kinematical Mapping for Redundant Open Chain Manipulators (submitted)

Posted on October 3, 2013October 9, 2020 By jannis No Comments on ICRA2013:Closed Form Solution for Inverse Kinematical Mapping for Redundant Open Chain Manipulators (submitted)
Conference participation, scientific publication

In the current work a closed form solution for a multi redundant open chain manipulator is presented. Exploiting the geometrical properties of the open chain we derive first ananalytic solution for the seven degree of freedom arm. And introduce then a methodology to incorporate additional degree of freedoms in the chain preserving the closed form … Read More “ICRA2013:Closed Form Solution for Inverse Kinematical Mapping for Redundant Open Chain Manipulators (submitted)” »

ICRA2013:Closed Form Solution for Inverse Kinematical Mapping for Redundant Open Chain Manipulators(submitted)

Posted on October 3, 2013October 9, 2020 By jannis No Comments on ICRA2013:Closed Form Solution for Inverse Kinematical Mapping for Redundant Open Chain Manipulators(submitted)
ICRA2013:Closed Form Solution for Inverse Kinematical Mapping for Redundant Open Chain Manipulators(submitted)
Conference participation, scientific publication

In the current work a closed form solution for a multi redundant open chain manipulator is presented. Exploiting the geometrical properties of the open chain we derive first an analytic solution for the seven degree of freedom arm. And introduce then a methodology to incorporate additional degree of freedoms in the chain preserving the closed … Read More “ICRA2013:Closed Form Solution for Inverse Kinematical Mapping for Redundant Open Chain Manipulators(submitted)” »

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Recent Posts

  • BCCN23: Investigation of the Interplay of Model-Based and Model-Free Learning Using Reinforcement Learning September 27, 2023
  • Meet Iossifidis Lab at Bernstein Conference 2023 September 26, 2023
  • BCCN23: The link between muscle activity and upper limb kinematics September 26, 2023
  • BCCN23: Variability study of human hand motion during 3D center-out tasks captured for the diagnosis of movement disorders September 26, 2023
  • BCCN23: Exploring Error-related Potentials in Adaptive Brain-Machine Interfaces: Challenges and Investigation of Occurrence and Detection Ratios September 26, 2023

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