A5064900588- EEG and Brain-Computer Interfaces
- Neural dynamics and brain function
- Neuroscience and Neural Engineering
- Muscle activation and electromyography studies
- Motor Control and Adaptation
- Action Observation and Synchronization
- Advanced Memory and Neural Computing
- Neural and Behavioral Psychology Studies
- Stroke Rehabilitation and Recovery
- Functional Brain Connectivity Studies
- Tactile and Sensory Interactions
- Prosthetics and Rehabilitation Robotics
- Visual perception and processing mechanisms
- Non-Invasive Vital Sign Monitoring
- Child and Animal Learning Development
- Hand Gesture Recognition Systems
- Balance, Gait, and Falls Prevention
- Musculoskeletal pain and rehabilitation
- Vestibular and auditory disorders
- stochastic dynamics and bifurcation
- Neuroscience, Education and Cognitive Function
- Interactive and Immersive Displays
- Neural Networks and Applications
- Opinion Dynamics and Social Influence
- Atomic and Subatomic Physics Research
University of Freiburg
2013-2024
Bernstein Center for Computational Neuroscience Freiburg
2013-2024
Imperial College London
2012-2022
Brain (Germany)
2018
University of California, Irvine
2004-2005
German Cancer Research Center
1999-2002
DKFZ-ZMBH Alliance
1999
Heidelberg University
1999
The BCI Competition IV stands in the tradition of prior Competitions that aim to provide high quality neuroscientific data for open access scientific community. As experienced already competitions not only scientists from narrow field compete, but scholars with a broad variety backgrounds and nationalities. They include specialists as well students. goals all have always been challenge respect novel paradigms complex data. We report on following challenges: (1) asynchronous data, (2)...
Brain activity can be used as a control signal for brain-machine interfaces (BMIs). A powerful and widely acknowledged BMI approach, so far only applied in invasive recording techniques, uses neuronal signals related to limb movements equivalent, multidimensional of an external effector. Here, we investigated whether this approach is also applicable noninvasive techniques. To end, recorded whole-head MEG during center-out with the hand found significant power modulation between rest movement...
Recent studies showed that the low-frequency component of local field potentials (LFPs) in monkey motor cortex carries information about parameters voluntary arm movements. Here, we studied how different signal components LFP time and frequency domains are modulated during center-out Analysis LFPs domain amplitude a slow complex waveform beginning shortly before onset movement is with direction movement. Examining domain, found direction-dependent modulations occur three ranges, which...
When we have learned a motor skill, such as cycling or ice-skating, can rapidly generalize to novel tasks, motorcycling rollerblading [1Bernstein N.A. The Co-ordination and Regulation of Movements. Pergamon Press, Oxford, NY1967Google Scholar, 2Poggio T. Bizzi E. Generalization in vision control.Nature. 2004; 431: 768-774Crossref PubMed Scopus (234) Google 3Abeele S. Bock O. Mechanisms for sensorimotor adaptation rotated visual input.Exp. Brain Res. 2001; 139: 248-253Crossref (64) 4Bock...
The availability of efficient and reliable simulation tools is one the mission-critical technologies in fast-moving field computational neuroscience. Research indicates that higher brain functions emerge from large complex cortical networks their interactions. number elements (neurons) combined with high connectivity (synapses) biological network specific type interactions impose severe constraints on explorable system size previously have been hard to overcome. Here we present a collection...
Information about arm movement direction in neuronal activity of the cerebral cortex can be used for control mediated by a brain–machine interface (BMI). Here we provide topographic analysis information related to that extracted from single trials electrocorticographic (ECoG) signals recorded human frontal and parietal based on precise assignment ECoG recording channels subjects' individual cortical anatomy function. To this aim, each electrode contact was identified structural MRI scans...
Picking up an empty milk carton that we believe to be full is a familiar example of adaptive control, because the adaptation process estimating carton's weight must proceed simultaneously with control moving desired location. Here show motor system initially generates highly variable behavior in such unpredictable tasks but eventually converges stereotyped patterns responses predicted by simple optimality principle. These results suggest can become specifically tuned identify task-specific...
Brain-computer interfaces (BCIs) require demanding numerical computations to transfer brain signals into control driving an external actuator. Increasing the computational performance of BCI algorithms carrying out these calculations enables faster reaction user inputs and allows using more decoding algorithms. Here we introduce a modular extensible software architecture with multi-threaded signal processing pipeline suitable for applications. The load latency (the time that system needs...
Humans seek advice, via social interaction, to improve their decisions. While interaction is often reciprocal, the role of reciprocity in influence unknown. Here, we tested hypothesis that our on others affects how much are influenced by them. Participants first made a visual perceptual estimate and then shared with an alleged partner. Then, alternating trials, participant either revised decisions or observed partner theirs. We systematically manipulated partner's susceptibility from...
Neurotechnology attempts to develop supernumerary limbs, but can the human brain deal with complexity control an extra limb and yield advantages from it? Here, we analyzed neuromechanics manipulation abilities of two polydactyly subjects who each possess six fingers on their hands. Anatomical MRI finger (SF) revealed that it is actuated by muscles nerves, fMRI identified a distinct cortical representation SF. In both subjects, SF was able move independently other fingers. Polydactyly were...
Recent developments in neural interfaces enable the real-time and non-invasive tracking of motor neuron spiking activity. Such novel could provide a promising basis for human augmentation by extracting potentially high-dimensional control signals directly from nervous system. However, it is unclear how flexibly humans can activity individual neurons to effectively increase number degrees freedom available coordinate multiple effectors simultaneously. Here, we provided subjects (N = 7) with...
The striatum is a site of integration neural pathways involved in reinforcement learning. Traditionally, inputs from cerebral cortex are thought to be reinforced by dopaminergic afferents signaling the occurrence biologically salient sensory events. Here, we detail an alternative route for short-latency sensory-evoked input requiring neither dopamine nor cortex. Using intracellular recording techniques, measured subthreshold spiny projection neurons (SPNs) urethane-anesthetized rats....
A brain-machine interface (BMI) can be used to control movements of an artificial effector, e.g. arm prosthesis, by motor cortical signals that the equivalent corresponding body part, movements. This approach has been successfully applied in monkeys and humans accurately extracting parameters from spiking activity multiple single neurons. We show same realized using brain measured directly surface human cortex electrocorticography (ECoG). Five subjects, implanted with ECoG implants for...
Background Brain-machine interfaces (BMIs) can translate the neuronal activity underlying a user's movement intention into movements of an artificial effector. In spite continuous improvements, errors in decoding are still major problem current BMI systems. If difference between decoded and intended becomes noticeable, it may lead to execution error. Outcome errors, where subjects fail reach certain goal, also present during online operation. Detecting such be beneficial for operation: (i)...
We show that when learning a motor skill humans are using information about the environment from an increasingly longer amount of movement path ahead to improve performance. Crucial features behavioral performance can be captured by modeling data with receding horizon optimal control model.