11 research outputs found
Adaptive map alignment in the superior colliculus of the barn owl: a neuromorphic implementation
Adaptation is one of the basic phenomena of biology, while adaptability is an important
feature for neural network. Young barn owl can well adapt its visual and auditory
integration to the environmental change, such as prism wearing.
At first, a mathematical model is introduced by the related study in biological experiment.
The model well explained the mechanism of the sensory map realignment
through axongenesis and synaptogenesis. Simulation results of this model are consistent
with the biological data.
Thereafter, to test the modelâs application in hardware, the model is implemented
into a robot. Visual and auditory signals are acquired by the sensors of the robot
and transferred back to PC through bluetooth. Results of the robot experiment are
presented, which shows the SC model allowing the robot to adjust visual and auditory
integration to counteract the effects of a prism.
Finally, based on the model, a silicon Superior Colliculus is designed in VLSI circuit
and fabricated. Performance of the fabricated chip has shown the synaptogenesis
and axogenesis can be emulated in VLSI circuit. The circuit of neural model provides
a new method to update signals and reconfigure the switch network (the chip has an
automatic reconfigurable network which is used to correct the disparity between signals).
The chip is also the first Superior Colliculus VLSI circuit to emulate the sensory
map realignment
Neurocomputing systems for auditory processing
This thesis studies neural computation models and neuromorphic implementations of the auditory pathway with applications to cochlear implants and artiïŹcial auditory sensory and processing systems.
Very low power analogue computation is addressed through the design of micropower analogue building blocks and an auditory preprocessing module targeted at cochlear implants. The analogue building blocks have been fabricated
and tested in a standard Complementary Metal Oxide Silicon (CMOS) process.
The auditory pre-processing module design is based on the cochlea signal processing mechanisms and low power microelectronic design methodologies. Compared to existing preprocessing techniques used in cochlear implants, the proposed design has a wider dynamic range and lower power consumption. Furthermore, it provides the phase coding as well as the place coding information that are necessary for enhanced functionality in future cochlear implants.
The thesis presents neural computation based approaches to a number of signal-processing problems encountered in cochlear implants. Techniques that can improve the performance of existing devices are also presented. Neural network based models for loudness mapping and pattern recognition based channel selection strategies are described. Compared with stateâofâtheâart commercial cochlear implants, the thesis results show that the proposed channel selection model produces superior speech sound qualities; and the proposed loudness mapping model consumes substantially smaller amounts of memory.
Aside from the applications in cochlear implants, this thesis describes a biologically plausible computational model of the auditory pathways to the superior colliculus based on current neurophysiological ïŹndings. The model encapsulates interaural time difference, interaural spectral difference, monaural pathway and auditory space map tuning in the inferior colliculus. A biologically plausible Hebbian-like learning rule is proposed for auditory space neural map tuning, and a reinforcement learning method is used for map alignment with other sensory space maps through activity independent cues.
The validity of the proposed auditory pathway model has been veriïŹed by simulation using synthetic data. Further, a complete biologically inspired auditory simulation system is implemented in software. The system incorporates models of the external ear, the cochlea, as well as the proposed auditory pathway model. The proposed implementation can mimic the biological auditory sensory system to generate an auditory space map from 3âD sounds. A large amount of real 3-D sound signals including broadband White noise, click noise and speech are used in the simulation experiments. The eïŹect of the auditory space map developmental plasticity is examined by simulating early auditory space map formation and auditory space map alignment with a distorted visual sensory map. Detailed simulation methods, procedures and results are presented
Calibration of sound source localisation for robots using multiple adaptive filter models of the cerebellum
The aim of this research was to investigate the calibration of Sound Source Localisation (SSL) for robots using the adaptive filter model of the cerebellum and how this could be automatically adapted for multiple acoustic environments. The role of the cerebellum has mainly been identified in the context of motor control, and only in recent years has it been recognised that it has a wider role to play in the senses and cognition. The adaptive filter model of the cerebellum has been successfully applied to a number of robotics applications but so far none involving auditory sense. Multiple models frameworks such as MOdular Selection And Identification for Control (MOSAIC) have also been developed in the context of motor control, and this has been the inspiration for adaptation of audio calibration in multiple acoustic environments; again, application of this approach in the area of auditory sense is completely new. The thesis showed that it was possible to calibrate the output of an SSL algorithm using the adaptive filter model of the cerebellum, improving the performance compared to the uncalibrated SSL. Using an adaptation of the MOSAIC framework, and specifically using responsibility estimation, a system was developed that was able to select an appropriate set of cerebellar calibration models and to combine their outputs in proportion to how well each was able to calibrate, to improve the SSL estimate in multiple acoustic contexts, including novel contexts. The thesis also developed a responsibility predictor, also part of the MOSAIC framework, and this improved the robustness of the system to abrupt changes in context which could otherwise have resulted in a large performance error. Responsibility prediction also improved robustness to missing ground truth, which could occur in challenging environments where sensory feedback of ground truth may become impaired, which has not been addressed in the MOSAIC literature, adding to the novelty of the thesis. The utility of the so-called cerebellar chip has been further demonstrated through the development of a responsibility predictor that is based on the adaptive filter model of the cerebellum, rather than the more conventional function fitting neural network used in the literature. Lastly, it was demonstrated that the multiple cerebellar calibration architecture is capable of limited self-organising from a de-novo state, with a predetermined number of models. It was also demonstrated that the responsibility predictor could learn against its model after self-organisation, and to a limited extent, during self-organisation. The thesis addresses an important question of how a robot could improve its ability to listen in multiple, challenging acoustic environments, and recommends future work to develop this ability
Neural architecture for echo suppression during sound source localization based on spiking neural cell models
Zusammenfassung
Diese Arbeit untersucht die biologischen Ursachen des psycho-akustischen
PrÀzedenz Effektes, der Menschen in die Lage versetzt, akustische Echos wÀhrend
der Lokalisation von Schallquellen zu unterdrĂŒcken. Sie enthĂ€lt ein Modell zur
Echo-UnterdrĂŒckung wĂ€hrend der Schallquellenlokalisation, welches in technischen
Systemen zur Mensch-Maschine Interaktion eingesetzt werden kann.
Die Grundlagen dieses Modells wurden aus eigenen elektrophysiologischen
Experimenten an der Mongolischen WĂŒstenrennmaus gewonnen. Die dabei erstmalig an
der WĂŒstenrennmaus erzielten Ergebnisse, zeigen ein besonderes Verhalten
spezifischer Zellen im Dorsalen Kern des Lateral Lemniscus, einer dedizierten
Region des auditorischen Hirnstammes. Die dort sichtbare Langzeithemmung scheint
die Grundlage fĂŒr die EchounterdrĂŒckung in höheren auditorischen Zentren zu
sein. Das entwickelte Model war in der Lage dieses Verhalten nachzubilden, und
legt die Vermutung nahe, dass eine starke und zeitlich prÀzise Hyperpolarisation
der zugrundeliegende physiologische Mechanismus dieses Verhaltens ist.
Die entwickelte Neuronale Modellarchitektur modelliert das Innenohr und fĂŒnf
wesentliche Kerne des auditorischen Hirnstammes in ihrer Verbindungsstruktur und
internen Dynamik. Sie stellt einen neuen Typus neuronaler Modellierung dar, der
als Spike-Interaktionsmodell (SIM) bezeichnet wird. SIM nutzen die prÀzise
rĂ€umlich-zeitliche Interaktion einzelner Aktionspotentiale (Spikes) fĂŒr die
Kodierung und Verarbeitung neuronaler Informationen. Die Basis dafĂŒr bilden
Integrate-and-Fire Neuronenmodelle sowie Hebb'sche Synapsen, welche um speziell
entwickelte dynamische Kernfunktionen erweitert wurden. Das Modell ist in der
Lage, Zeitdifferenzen von 10 mykrosekunden zu detektieren und basiert auf den
Prinzipien der zeitlichen und rÀumlichen Koinzidenz sowie der prÀzisen lokalen
Inhibition.
Es besteht ausschlieĂlich aus Elementen einer eigens entwickelten Neuronalen
Basisbibliothek (NBL) die speziell fĂŒr die Modellierung verschiedenster Spike-
Interaktionsmodelle entworfen wurde. Diese Bibliothek erweitert die kommerziell
verfĂŒgbare dynamische Simulationsumgebung von MATLAB/SIMULINK um verschiedene
Modelle von Neuronen und Synapsen, welche die intrinsischen dynamischen
Eigenschaften von Nervenzellen nachbilden. Die Nutzung dieser Bibliothek
versetzt sowohl den Ingenieur als auch den Biologen in die Lage, eigene,
biologisch plausible, Modelle der neuronalen Informationsverarbeitung ohne
detaillierte Programmierkenntnisse zu entwickeln. Die grafische OberflÀche
ermöglicht strukturelle sowie parametrische Modifikationen und ist in der Lage,
den Zeitverlauf mikroskopischer Zellpotentiale aber auch makroskopischer
Spikemuster wÀhrend und nach der Simulation darzustellen.
Zwei grundlegende Elemente der Neuronalen Basisbibliothek wurden zur
Implementierung als spezielle analog-digitale Schaltungen vorbereitet.
Erste Silizium Implementierungen durch das Team des DFG Graduiertenkollegs GRK
164 konnten die Möglichkeit einer vollparallelen on line Verarbeitung von
Schallsignalen nachweisen. Durch Zuhilfenahme des im GRK entwickelten
automatisierten Layout Generators wird es möglich, spezielle Prozessoren zur
Anwendung biologischer Verarbeitungsprinzipien in technischen Systemen zu
entwickeln. Diese Prozessoren unterscheiden sich grundlegend von den klassischen
von Neumann Prozessoren indem sie rÀumlich und zeitlich verteilte Spikemuster,
anstatt sequentieller binÀrer Werte zur InformationsreprÀsentation nutzen. Sie
erweitern das digitale Kodierungsprinzip durch die Dimensionen des Raumes (2
dimensionale Nachbarschaft) der Zeit (Frequenz, Phase und Amplitude) sowie der
zeitlichen Dynamik analoger PotentialverlÀufe.
Diese Dissertation besteht aus sieben Kapiteln, welche den verschiedenen
Bereichen der Computational Neuroscience gewidmet sind.
Kapitel 1 beschreibt die Motivation dieser Arbeit welche aus der Absicht rĂŒhren,
biologische Prinzipien der Schallverarbeitung zu erforschen und fĂŒr technische
Systeme wÀhrend der Interaktion mit dem Menschen nutzbar zu machen. ZusÀtzlich
werden fĂŒnf GrĂŒnde fĂŒr die Nutzung von Spike-Interaktionsmodellen angefĂŒhrt
sowie deren neuartiger Charakter beschrieben.
Kapitel 2 fĂŒhrt die biologischen Prinzipien der Schallquellenlokalisation und
den psychoakustischen PrÀzedenz Effekt ein. Aktuelle Hypothesen zur Entstehung
dieses Effektes werden anhand ausgewÀhlter experimenteller Ergebnisse
verschiedener Forschungsgruppen diskutiert.
Kapitel 3 beschreibt die entwickelte Neuronale Basisbibliothek und fĂŒhrt die
einzelnen neuronalen Simulationselemente ein. Es erklÀrt die zugrundeliegenden
mathematischen Funktionen der dynamischen Komponenten und beschreibt deren
generelle Einsetzbarkeit zur dynamischen Simulation spikebasierter Neuronaler
Netzwerke.
Kapitel 4 enthÀlt ein speziell entworfenes Modell des auditorischen Hirnstammes
beginnend mit den Filterkaskaden zur Simulation des Innenohres, sich fortsetzend
ĂŒber mehr als 200 Zellen und 400 Synapsen in 5 auditorischen Kernen bis zum
Richtungssensor im Bereich des auditorischen Mittelhirns. Es stellt die
verwendeten Strukturen und Parameter vor und enthÀlt grundlegende Hinweise zur
Nutzung der Simulationsumgebung.
Kapitel 5 besteht aus drei Abschnitten, wobei der erste Abschnitt die
Experimentalbedingungen und Ergebnisse der eigens durchgefĂŒhrten Tierversuche
beschreibt. Der zweite Abschnitt stellt die Ergebnisse von 104 Modellversuchen
zur Simulationen psycho-akustischer Effekte dar, welche u.a. die FĂ€higkeit des
Modells zur Nachbildung des PrĂ€zedenz Effektes testen. SchlieĂlich beschreibt
der letzte Abschnitt die Ergebnisse der 54 unter realen Umweltbedingungen
durchgefĂŒhrten Experimente. Dabei kamen Signale zur Anwendung, welche in
normalen sowie besonders stark verhallten RĂ€umen aufgezeichnet wurden.
Kapitel 6 vergleicht diese Ergebnisse mit anderen biologisch motivierten und
technischen Verfahren zur EchounterdrĂŒckung und Schallquellenlokalisation und
fĂŒhrt den aktuellen Status der Hardwareimplementierung ein.
Kapitel 7 enthĂ€lt schlieĂlich eine kurze Zusammenfassung und einen Ausblick auf
weitere Forschungsobjekte und geplante AktivitÀten.
Diese Arbeit möchte zur Entwicklung der Computational Neuroscience beitragen,
indem sie versucht, in einem speziellen Anwendungsfeld die LĂŒcke zwischen
biologischen Erkenntnissen, rechentechnischen Modellen und Hardware Engineering
zu schlieĂen. Sie empfiehlt ein neues rĂ€umlich-zeitliches Paradigma der
dynamischen Informationsverarbeitung zur ErschlieĂung biologischer Prinzipien
der Informationsverarbeitung fĂŒr technische Anwendungen.This thesis investigates the biological background of the psycho-acoustical precedence effect, enabling humans to suppress echoes during the localization of sound sources. It provides a technically feasible and biologically plausible model for sound source localization under echoic conditions, ready to be used by technical systems during man-machine interactions.
The model is based upon own electro-physiological experiments in the mongolian gerbil. The first time in gerbils obtained results reveal a special behavior of specific cells of the dorsal nucleus of the lateral lemniscus (DNLL) - a distinct region in the auditory brainstem. The explored persistent inhibition effect of these cells seems to account for the base of echo suppression at higher auditory centers. The developed model proved capable to duplicate this behavior and suggests, that a strong and timely precise hyperpolarization is the basic mechanism behind this cell behavior. The developed neural architecture models the inner ear as well as five major nuclei of the auditory brainstem in their connectivity and intrinsic dynamics. It represents a new type of neural modeling described as Spike Interaction Models (SIM). SIM use the precise spatio-temporal interaction of single spike events for coding and processing of neural information. Their basic elements are Integrate-and-Fire Neurons and Hebbian synapses, which have been extended by specially designed dynamic transfer functions. The model is capable to detect time differences as small as 10 mircrosecondes and employs the principles of coincidence detection and precise local inhibition for auditory processing. It consists exclusively of elements of a specifically designed Neural Base Library (NBL), which has been developed for multi purpose modeling of Spike Interaction Models. This library extends the commercially available dynamic simulation environment of MATLAB/SIMULINK by different models of neurons and synapses simulating the intrinsic dynamic properties of neural cells. The usage of this library enables engineers as well as biologists to design their own, biologically plausible models of neural information processing without the need for detailed programming skills. Its graphical interface provides access to structural as well as parametric changes and is capable to display the time course of microscopic cell parameters as well as macroscopic firing pattern during simulations and thereafter. Two basic elements of the Neural Base Library have been prepared for implementation by specialized mixed analog-digital circuitry. First silicon implementations were realized by the team of the DFG Graduiertenkolleg GRK 164 and proved the possibility of fully parallel on line processing of sounds. By using the automated layout processor under development in the Graduiertenkolleg, it will be possible to design specific processors in order to apply theprinciples of distributed biological information processing to technical systems. These processors differ from classical von Neumann processors by the use of spatio temporal spike pattern instead of sequential binary values. They will extend the digital coding principle by the dimensions of space (spatial neighborhood), time (frequency, phase and amplitude) as well as the dynamics of analog potentials and introduce a new type of information processing.
This thesis consists of seven chapters, dedicated to the different areas of computational neuroscience.
Chapter 1: provides the motivation of this study arising from the attempt to investigate the biological principles of sound processing and make them available to technical systems interacting with humans under real world conditions. Furthermore, five reasons to use spike interaction models are given and their novel characteristics are discussed.
Chapter 2: introduces the biological principles of sound source localization and the precedence effect. Current hypothesis on echo suppression and the underlying principles of the precedence effect are discussed by reference to a small selection of physiological and psycho-acoustical experiments.
Chapter 3: describes the developed neural base library and introduces each of the designed neural simulation elements. It also explains the developed mathematical functions of the dynamic compartments and describes their general usage for dynamic simulation of spiking neural networks.
Chapter 4: introduces the developed specific model of the auditory brainstem, starting from the filtering cascade in the inner ear via more than 200 cells and 400 synapses in five auditory regions up to the directional sensor at the level of the auditory midbrain. It displays the employed parameter sets and contains basic hints for the set up and configuration of the simulation environment.
Chapter 5: consists of three sections, whereas the first one describes the set up and results of the own electro-physiological experiments. The second describes the results of 104 model simulations, performed to test the
models ability to duplicate psycho-acoustical effects like the precedence effect. Finally, the last section of this chapter contains the results of 54 real world experiments using natural sound signals, recorded under normal as well as highly reverberating conditions.
Chapter 6: compares the achieved results to other biologically motivated and technical models for echo suppression and sound source localization and introduces the current status of silicon implementation.
Chapter 7: finally provides a short summary and an outlook toward future research subjects and areas of investigation.
This thesis aims to contribute to the field of computational neuroscience by bridging the gap between biological
investigation, computational modeling and silicon engineering in a specific field of application. It suggests a new spatio-temporal paradigm of information processing in order to access the capabilities of biological systems for technical applications
Engineering derivatives from biological systems for advanced aerospace applications
The present study consisted of a literature survey, a survey of researchers, and a workshop on bionics. These tasks produced an extensive annotated bibliography of bionics research (282 citations), a directory of bionics researchers, and a workshop report on specific bionics research topics applicable to space technology. These deliverables are included as Appendix A, Appendix B, and Section 5.0, respectively. To provide organization to this highly interdisciplinary field and to serve as a guide for interested researchers, we have also prepared a taxonomy or classification of the various subelements of natural engineering systems. Finally, we have synthesized the results of the various components of this study into a discussion of the most promising opportunities for accelerated research, seeking solutions which apply engineering principles from natural systems to advanced aerospace problems. A discussion of opportunities within the areas of materials, structures, sensors, information processing, robotics, autonomous systems, life support systems, and aeronautics is given. Following the conclusions are six discipline summaries that highlight the potential benefits of research in these areas for NASA's space technology programs
26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 - Meeting Abstracts - Antwerp, Belgium. 15â20 July 2017
This work was produced as part of the activities of FAPESP Research,\ud
Disseminations and Innovation Center for Neuromathematics (grant\ud
2013/07699-0, S. Paulo Research Foundation). NLK is supported by a\ud
FAPESP postdoctoral fellowship (grant 2016/03855-5). ACR is partially\ud
supported by a CNPq fellowship (grant 306251/2014-0)