Current
Research Projects
Joint Action Science and Technology (JAST)
financed by the European Commission, FP6
IST-2-003747-IP.
The JAST consortium brings together research groups from cognitive
science and robotics. The main objective is to build jointly acting autonomous
systems that work intelligently on mutual tasks. To realise this objective,
JAST exploits a prototypical research paradigm in which two autonomous agents
(human-human, robot-human, robot-robot) perform a
single construction task. The different experimental groups involved cover in
their research all aspects of joint action including the perceptual, reasoning
and motor level. The results of the neuro-cognitive experiments are used by our group to develop
integrative cognitive models for joint action. They are based on the
theoretical framework of dynamical systems and dynamic fields. Dr. Estela Bicho’s
group at the Department of Industrial Electronics,
For a recent video of the
Consortium leader: Dr. Harold Bekkering, Donders Institute for Brain,
Cognition and Behaviour, Centre for Cognition Radboud
University Nijmegen, The Netherlands
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Analysis of pattern formation in dynamic fields with
bi-stable elements
financed by the Portuguese Science
Foundation (FCT)
The main
objective is to analytically and numerically investigate a class of integro-differential equations which consists of bi-stable
elements and linear spatial interactions. In a certain parameter regime, these
equations show the same dynamics of pattern formation like the “classical”
dynamic fields of Amari type. In general, however,
the dynamics differs systematically from conceptually related systems (e.g., Amari, RD-systems), which makes the system attractive for
certain applications. Of particular interest are the dependence of the shape of
localized patterns on the initial state, the robustness of stationary pulse
solutions against perturbations of the interaction symmetry and the
co-existence of multiple pulse solutions.
Learning to read the motor intention of others: towards socially intelligent robots,
financed by FCT (POCI/V.5/A0119/2005)
The main objective of the project is to further develop our dynamic field
model for action understanding which we have originally proposed in the contetxt of goal-directed imitation. To this end,
we analyze and interpret
neural data recorded in dedicated monkey experiments by our
partners at the University of Parma, Italy. The STS-PF/PFG-F5 mirror circuit is considered to play a fundamental
role in the capacity to understand and imitate actions of others. The defining functional characteristic of
mirror neurons is that they become active not only when the monkey executes a
particular motor act (like grasping, holding or placing an object) but also when it observes another
individual (monkey or human) performing a similar motor act. Recent findings by
Fogassi and colleagues (Science, 308: 662-667,
2005) show that neurons in the
monkey's inferior parietal lobule, while coding a specific motor act, show
markedly different activation patterns depending upon the final goal of the action
sequence in which the act is embedded. Our working hypothesis for the modeling the
intention reading capacity is that neurons in parietal cortex are organized in
chains of motor acts dedicated to achieve certain action goals. Important cues
for triggering the motor chains are visual inputs representing object
properties or observed motor acts (e.g., the first primitive of a chain).
The emphasis of the project is on the developmental aspect: we apply
learning dynamics to establish during “practice” connections between dynamics
field representations which eventually build the goal-directed chains.
Project partners:
Dr. Leonardo Fogassi and Dr. Pier F. Ferrari, University of
Parma, Italy
Dr. Albert Mukovskiy, Institute of Higher Nervous Activity and
Neurophysiology, Russ. Acad.
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Modeling
the dynamics of activity patterns in primary visual cortex
financed by CRUP:
Acções Integradas Luso-Alemãs
The primary visual cortex is the most intensively
investigated cortical tissue in neurobiology. However, its contribution to
sensation is still under debate. Dirk Jancke and
colleagues (Nature 438: 423-426,
2004) have recently demonstrated the
impact of spatio-temporal patterns of subthreshold synaptic potentials on early cortical
processing and hence its potential contribution on the shaping of perception.
Our goal in this project is to identify the neuronal
interactions underlying these spatio-temporal
patterns through dynamical models adapted to data from optical imaging and
single unit recordings. The data will be interpreted quantitatively using a
dynamic neural field approach that provides theoretically meaningful parameters
(average coupling strengths, time constants etc.) directly linked to
the functional cortical architecture. By
systematically adapting these models to the experimental data using
evolutionary algorithms, we may identify these model parameters. Mathematical
analysis of the resulting model may reveal its principle information processing
capabilities.
A second goal of
the project is to link the neuronal and the perceptual level. Following our
previous work we use the dynamic field models to hypothesize about neural
processing mechanisms underlying systematic localization errors which occur
with objects in motion (e.g., line motion, Fröhlich
effect, flash-lag effect, representational momentum).
Project partners:
Dr. Dirk Jancke,
Neurobiology, Ruhr-University
Dr. Christian Igel,
Neuroinformatics, Ruhr-University