7 research outputs found
Large scale retinal modeling for the design of new generation retinal prostheses
With the help of modern technology, blindness caused by retinal diseases such as age-related macular degeneration or retinitis pigmentosa is now considered reversible. Scientists from various fields such as Neuroscience, Electrical Engineering, Computer Science, and Bioscience have been collaborating to design and develop retinal prostheses, with the aim of replacing malfunctioning parts of the retina and restoring vision in the blind. Human trials conducted to test retinal prostheses have yielded encouraging results, showing the potential of this approach in vision recovery. However, a retinal prosthesis has several limitations with regard to its hardware and biological functions, and several attempts have been made to overcome these limitations.
This thesis focuses on the biological aspects of retinal prostheses: the biological processes occurring inside the retina and the limitations of retinal prostheses corresponding to those processes have been analysed. Based on these analyses, three major findings regarding information processing inside the retina have been presented and these findings have been used to conceptualise retinal prostheses that have the characteristics of asymmetrical and separate pathway stimulations. In the future, when nanotechnology gains more popularity and is completely integrated inside the prosthesis, this concept can be utilized to restore useful visual information such as colour, depth, and contrast to achieve high-quality vision in the blind
Large scale retinal modeling for the design of new generation retinal prostheses
With the help of modern technology, blindness caused by retinal diseases such as age-related macular degeneration or retinitis pigmentosa is now considered reversible. Scientists from various fields such as Neuroscience, Electrical Engineering, Computer Science, and Bioscience have been collaborating to design and develop retinal prostheses, with the aim of replacing malfunctioning parts of the retina and restoring vision in the blind. Human trials conducted to test retinal prostheses have yielded encouraging results, showing the potential of this approach in vision recovery. However, a retinal prosthesis has several limitations with regard to its hardware and biological functions, and several attempts have been made to overcome these limitations.
This thesis focuses on the biological aspects of retinal prostheses: the biological processes occurring inside the retina and the limitations of retinal prostheses corresponding to those processes have been analysed. Based on these analyses, three major findings regarding information processing inside the retina have been presented and these findings have been used to conceptualise retinal prostheses that have the characteristics of asymmetrical and separate pathway stimulations. In the future, when nanotechnology gains more popularity and is completely integrated inside the prosthesis, this concept can be utilized to restore useful visual information such as colour, depth, and contrast to achieve high-quality vision in the blind
The role of direction-selective visual interneurons T4 and T5 in Drosophila orientation behavior
In order to safely move through the environment, visually-guided animals
use several types of visual cues for orientation. Optic flow provides faithful
information about ego-motion and can thus be used to maintain a straight
course. Additionally, local motion cues or landmarks indicate potentially
interesting targets or signal danger, triggering approach or avoidance, respectively.
The visual system must reliably and quickly evaluate these cues
and integrate this information in order to orchestrate behavior. The underlying
neuronal computations for this remain largely inaccessible in higher
organisms, such as in humans, but can be studied experimentally in more
simple model species. The fly Drosophila, for example, heavily relies on
such visual cues during its impressive flight maneuvers. Additionally, it is
genetically and physiologically accessible. Hence, it can be regarded as an
ideal model organism for exploring neuronal computations during visual
processing.
In my PhD studies, I have designed and built several autonomous virtual
reality setups to precisely measure visual behavior of walking flies. The
setups run in open-loop and in closed-loop configuration. In an open-loop
experiment, the visual stimulus is clearly defined and does not depend on
the behavioral response. Hence, it allows mapping of how specific features
of simple visual stimuli are translated into behavioral output, which can
guide the creation of computational models of visual processing. In closedloop
experiments, the behavioral response is fed back onto the visual stimulus,
which permits characterization of the behavior under more realistic
conditions and, thus, allows for testing of the predictive power of the computational
models.
In addition, Drosophila’s genetic toolbox provides various strategies for
targeting and silencing specific neuron types, which helps identify which
cells are needed for a specific behavior. We have focused on visual interneuron
types T4 and T5 and assessed their role in visual orientation behavior.
These neurons build up a retinotopic array and cover the whole visual field
of the fly. They constitute major output elements from the medulla and have
long been speculated to be involved in motion processing.
This cumulative thesis consists of three published studies: In the first
study, we silenced both T4 and T5 neurons together and found that such flies
were completely blind to any kind of motion. In particular, these flies could
not perform an optomotor response anymore, which means that they lost
their normally innate following responses to motion of large-field moving
patterns. This was an important finding as it ruled out the contribution
of another system for motion vision-based behaviors. However, these flies
were still able to fixate a black bar. We could show that this behavior is
mediated by a T4/T5-independent flicker detection circuitry which exists in
parallel to the motion system.
In the second study, T4 and T5 neurons were characterized via twophoton
imaging, revealing that these cells are directionally selective and
have very similar temporal and orientation tuning properties to directionselective
neurons in the lobula plate. T4 and T5 cells responded in a
contrast polarity-specific manner: T4 neurons responded selectively to ON
edge motion while T5 neurons responded only to OFF edge motion. When
we blocked T4 neurons, behavioral responses to moving ON edges were
more impaired than those to moving OFF edges and the opposite was true
for the T5 block. Hence, these findings confirmed that the contrast polarityspecific
visual motion pathways, which start at the level of L1 (ON) and L2
(OFF), are maintained within the medulla and that motion information is
computed twice independently within each of these pathways.
Finally, in the third study, we used the virtual reality setups to probe the
performance of an artificial microcircuit. The system was equipped with a
camera and spherical fisheye lens. Images were processed by an array of
Reichardt detectors whose outputs were integrated in a similar way to what
is found in the lobula plate of flies. We provided the system with several rotating
natural environments and found that the fly-inspired artificial system
could accurately predict the axes of rotation
The role of direction-selective visual interneurons T4 and T5 in Drosophila orientation behavior
In order to safely move through the environment, visually-guided animals
use several types of visual cues for orientation. Optic flow provides faithful
information about ego-motion and can thus be used to maintain a straight
course. Additionally, local motion cues or landmarks indicate potentially
interesting targets or signal danger, triggering approach or avoidance, respectively.
The visual system must reliably and quickly evaluate these cues
and integrate this information in order to orchestrate behavior. The underlying
neuronal computations for this remain largely inaccessible in higher
organisms, such as in humans, but can be studied experimentally in more
simple model species. The fly Drosophila, for example, heavily relies on
such visual cues during its impressive flight maneuvers. Additionally, it is
genetically and physiologically accessible. Hence, it can be regarded as an
ideal model organism for exploring neuronal computations during visual
processing.
In my PhD studies, I have designed and built several autonomous virtual
reality setups to precisely measure visual behavior of walking flies. The
setups run in open-loop and in closed-loop configuration. In an open-loop
experiment, the visual stimulus is clearly defined and does not depend on
the behavioral response. Hence, it allows mapping of how specific features
of simple visual stimuli are translated into behavioral output, which can
guide the creation of computational models of visual processing. In closedloop
experiments, the behavioral response is fed back onto the visual stimulus,
which permits characterization of the behavior under more realistic
conditions and, thus, allows for testing of the predictive power of the computational
models.
In addition, Drosophila’s genetic toolbox provides various strategies for
targeting and silencing specific neuron types, which helps identify which
cells are needed for a specific behavior. We have focused on visual interneuron
types T4 and T5 and assessed their role in visual orientation behavior.
These neurons build up a retinotopic array and cover the whole visual field
of the fly. They constitute major output elements from the medulla and have
long been speculated to be involved in motion processing.
This cumulative thesis consists of three published studies: In the first
study, we silenced both T4 and T5 neurons together and found that such flies
were completely blind to any kind of motion. In particular, these flies could
not perform an optomotor response anymore, which means that they lost
their normally innate following responses to motion of large-field moving
patterns. This was an important finding as it ruled out the contribution
of another system for motion vision-based behaviors. However, these flies
were still able to fixate a black bar. We could show that this behavior is
mediated by a T4/T5-independent flicker detection circuitry which exists in
parallel to the motion system.
In the second study, T4 and T5 neurons were characterized via twophoton
imaging, revealing that these cells are directionally selective and
have very similar temporal and orientation tuning properties to directionselective
neurons in the lobula plate. T4 and T5 cells responded in a
contrast polarity-specific manner: T4 neurons responded selectively to ON
edge motion while T5 neurons responded only to OFF edge motion. When
we blocked T4 neurons, behavioral responses to moving ON edges were
more impaired than those to moving OFF edges and the opposite was true
for the T5 block. Hence, these findings confirmed that the contrast polarityspecific
visual motion pathways, which start at the level of L1 (ON) and L2
(OFF), are maintained within the medulla and that motion information is
computed twice independently within each of these pathways.
Finally, in the third study, we used the virtual reality setups to probe the
performance of an artificial microcircuit. The system was equipped with a
camera and spherical fisheye lens. Images were processed by an array of
Reichardt detectors whose outputs were integrated in a similar way to what
is found in the lobula plate of flies. We provided the system with several rotating
natural environments and found that the fly-inspired artificial system
could accurately predict the axes of rotation
SpiNNaker - A Spiking Neural Network Architecture
20 years in conception and 15 in construction, the SpiNNaker project has delivered the world’s largest neuromorphic computing platform incorporating over a million ARM mobile phone processors and capable of modelling spiking neural networks of the scale of a mouse brain in biological real time. This machine, hosted at the University of Manchester in the UK, is freely available under the auspices of the EU Flagship Human Brain Project. This book tells the story of the origins of the machine, its development and its deployment, and the immense software development effort that has gone into making it openly available and accessible to researchers and students the world over. It also presents exemplar applications from ‘Talk’, a SpiNNaker-controlled robotic exhibit at the Manchester Art Gallery as part of ‘The Imitation Game’, a set of works commissioned in 2016 in honour of Alan Turing, through to a way to solve hard computing problems using stochastic neural networks. The book concludes with a look to the future, and the SpiNNaker-2 machine which is yet to come
SpiNNaker - A Spiking Neural Network Architecture
20 years in conception and 15 in construction, the SpiNNaker project has delivered the world’s largest neuromorphic computing platform incorporating over a million ARM mobile phone processors and capable of modelling spiking neural networks of the scale of a mouse brain in biological real time. This machine, hosted at the University of Manchester in the UK, is freely available under the auspices of the EU Flagship Human Brain Project. This book tells the story of the origins of the machine, its development and its deployment, and the immense software development effort that has gone into making it openly available and accessible to researchers and students the world over. It also presents exemplar applications from ‘Talk’, a SpiNNaker-controlled robotic exhibit at the Manchester Art Gallery as part of ‘The Imitation Game’, a set of works commissioned in 2016 in honour of Alan Turing, through to a way to solve hard computing problems using stochastic neural networks. The book concludes with a look to the future, and the SpiNNaker-2 machine which is yet to come