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Projects of the BCCN

Projects of the BCCN Göttingen, sorted by name.

A1 - "Realistic" Modelling of short term synaptic plasticity in neuronal networks

Erwin Neher and Marc Timme
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Sensorimotor transformations and brain-machine interfaces

Alexander Gail
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3D-Trunk

We put forward a novel design concept for building a 3-D hyper-redundant chain robot (HRCR) system, consisting of linked, identical modules and one base module.
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A2 - A theory for the origin of patterns of precisely timed spikes

Marc Timme
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A3 - Modelling calcium-dependent signal processing in motoneurons

Bernhard Keller and Annette Zippelius
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A4 - Impact of hair cell synaptic coding on auditory processing

Tobias Moser and Fred Wolf
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Action descriptions and action chaining

Robots that are supposed to operate in a dynamic real world environment will have to be able to perform complex movements. The control of the robot cannot be preprogrammed, but has to be learned, for instance by imitation, and constantly updated. The actions are represented hierarchically: Primitive actions (e.g. moving the arm in one direction) form the basis for complex tasks (e.g. fixing a screw in the wall). Here we examine, how humans perform a sequence of subtasks using a manipulandum, and how the order in which they are perform or decision processes influence the details of the movements.
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Adaptive - Fast Dynamic Walking Robot “RUNBOT”

The goal of this roject is to design a dynamic, biomechanical system for bipedal walking under neural control and learning. This has led to RunBot, which achieves a speed of about 3.5 leg-length per second and is currently the fastest planar, dynamic, biped robot, which can learn to adapt to the terrain.
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B1 - Computational role of glomerular and reciprocal synapses in the olfactory bulb for the formation of an olfactory map and olfactory learning

Detlev Schild and Reiner Kree
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B2 - Computational analysis of synchronization in cortical spike data

Theo Geisel and Stefan Treue
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B3 - Replacing mechanisms of selective attention by transcranial direct current stimulation

Walter Paulus, Jens Frahm, and Stefan Treue
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B4 - Physiology and pathology of adaptive respiratory behaviors

Mathias Dutschmann and Michael Müller
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C1 - Task-dependent allocation of resources by attention: physiology

Stefan Treue and Theo Geisel
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C2 - Task-dependent allocation of resources by attention: functional brain imaging and psychophysics

Stefan Treue and Jens Frahm
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C3 - Dynamic adaptation in decoding temporal information

Thomas Rammsayer and Michael Herrmann
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C4 - Aging effects in selective attention

Marcus Hasselhorn and Michael Herrmann
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Computer Vision and Image Analysis

Group working on computer vision and analysis of images.
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D1 - Motor learning with multiple internal models

Michael Herrmann
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D2 - Control of advanced hand prosthesis by myoelectric signals

Michael Herrmann, Horst Willburger, and Walter Paulus
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D3 - EMG triggered muscle stimulation: Neuroplastic limits of functional improvement of chronic hemiparetic stroke patients

Walter Paulus, Theo Geisel, Lüder Mosler, Jens Frahm, and Jürgen Kaus
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D4 - Towards a hybrid active/passive bipedal walking prosthesis

Michael Herrmann, Lüder Mosler, and Walter Paulus
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Decision making and Planning

The ability for decision making and planning is a major trait of higher vertebrates. We are especially interested in the link between learning and planning. Fact is that your planning at a certain level will influence what you will experience next and, hence, what you can then learn. But this process also goes the other way round. To do this in embodied (robot) systems is the goal of this project.
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Dynamics of collective behaviour in large scale self-organizing systems

Most animals usually do not live as solitary creatures. Instead they organize into social groups of sometimes large numbers, then often called a herd or a swarm. In the process of doing so each individual (“EGO”) will experience all others (“ALTER”) as being part of its own environment. A general principle for improved survival is predictive learning, which is learning to predict the near-future development of EGO’s environment. Animals/agents that have such a learning mechanism available will necessarily also try to learn predicting the behaviour of all ALTERs, creating a system where the agents will not only mutually influence each others behaviour but also each others learning.
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Goal-directed Learning (learning to achieve a goal)

How can non-goal directed signals from the environment be combined and be utilized to achieve goal directed behaviour? This is the main question this project is faced with.
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Homeostasis Learning

Adaptive neuronal systems learn to avoid a disturbance and therefore keep homeostasis are constructed and investigated in this project.
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