Analog VLSI-Based Modeling of the Primate Oculomotor System

One way to understand a neurobiological system is by building a simulacrum that replicates its behavior in real time using similar constraints. Analog very large-scale integrated (VLSI) electronic circuit technology provides such an enabling technology. We here describe a neuromorphic system that is part of a long-term effort to understand the primate oculomotor system. It requires both fast sensory processing and fast motor control to interact with the world. A one-dimensional hardware model of the primate eye has been built that simulates the physical dynamics of the biological system. It is driven by two different analog VLSI chips, one mimicking cortical visual processing for target selection and tracking and another modeling brain stem circuits that drive the eye muscles. Our oculomotor plant demonstrates both smooth pursuit movements, driven by a retinal velocity error signal, and saccadic eye movements, controlled by retinal position error, and can reproduce several behavioral, stimulation, lesion, and adaptation experiments performed on primates

Neuromorphic analogue VLSI

Neuromorphic systems emulate the organization and function of nervous systems. They are usually composed of analogue electronic circuits that are fabricated in the complementary metal-oxide-semiconductor (CMOS) medium using very large-scale integration (VLSI) technology. However, these neuromorphic systems are not another kind of digital computer in which abstract neural networks are simulated symbolically in terms of their mathematical behavior. Instead, they directly embody, in the physics of their CMOS circuits, analogues of the physical processes that underlie the computations of neural systems. The significance of neuromorphic systems is that they offer a method of exploring neural computation in a medium whose physical behavior is analogous to that of biological nervous systems and that operates in real time irrespective of size. The implications of this approach are both scientific and practical. The study of neuromorphic systems provides a bridge between levels of understanding. For example, it provides a link between the physical processes of neurons and their computational significance. In addition, the synthesis of neuromorphic systems transposes our knowledge of neuroscience into practical devices that can interact directly with the real world in the same way that biological nervous systems do

Unanesthetized Auditory Cortex Exhibits Multiple Codes for Gaps in Cochlear Implant Pulse Trains

Cochlear implant listeners receive auditory stimulation through amplitude-modulated electric pulse trains. Auditory nerve studies in animals demonstrate qualitatively different patterns of firing elicited by low versus high pulse rates, suggesting that stimulus pulse rate might influence the transmission of temporal information through the auditory pathway. We tested in awake guinea pigs the temporal acuity of auditory cortical neurons for gaps in cochlear implant pulse trains. Consistent with results using anesthetized conditions, temporal acuity improved with increasing pulse rates. Unlike the anesthetized condition, however, cortical neurons responded in the awake state to multiple distinct features of the gap-containing pulse trains, with the dominant features varying with stimulus pulse rate. Responses to the onset of the trailing pulse train (Trail-ON) provided the most sensitive gap detection at 1,017 and 4,069 pulse-per-second (pps) rates, particularly for short (25 ms) leading pulse trains. In contrast, under conditions of 254 pps rate and long (200 ms) leading pulse trains, a sizeable fraction of units demonstrated greater temporal acuity in the form of robust responses to the offsets of the leading pulse train (Lead-OFF). Finally, TONIC responses exhibited decrements in firing rate during gaps, but were rarely the most sensitive feature. Unlike results from anesthetized conditions, temporal acuity of the most sensitive units was nearly as sharp for brief as for long leading bursts. The differences in stimulus coding across pulse rates likely originate from pulse rate-dependent variations in adaptation in the auditory nerve. Two marked differences from responses to acoustic stimulation were: first, Trail-ON responses to 4,069 pps trains encoded substantially shorter gaps than have been observed with acoustic stimuli; and second, the Lead-OFF gap coding seen for <15 ms gaps in 254 pps stimuli is not seen in responses to sounds. The current results may help to explain why moderate pulse rates around 1,000 pps are favored by many cochlear implant listeners

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 Präzedenz Effektes, der Menschen in die Lage versetzt, akustische Echos während der Lokalisation von Schallquellen zu unterdrücken. Sie enthält ein Modell zur Echo-Unterdrückung während 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 Wüstenrennmaus gewonnen. Die dabei erstmalig an der Wüstenrennmaus 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 für die Echounterdrückung 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 präzise Hyperpolarisation der zugrundeliegende physiologische Mechanismus dieses Verhaltens ist. Die entwickelte Neuronale Modellarchitektur modelliert das Innenohr und fünf 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 präzise räumlich-zeitliche Interaktion einzelner Aktionspotentiale (Spikes) für die Kodierung und Verarbeitung neuronaler Informationen. Die Basis dafür 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 räumlichen Koinzidenz sowie der präzisen lokalen Inhibition. Es besteht ausschließlich aus Elementen einer eigens entwickelten Neuronalen Basisbibliothek (NBL) die speziell für die Modellierung verschiedenster Spike- Interaktionsmodelle entworfen wurde. Diese Bibliothek erweitert die kommerziell verfügbare 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 Oberfläche ermöglicht strukturelle sowie parametrische Modifikationen und ist in der Lage, den Zeitverlauf mikroskopischer Zellpotentiale aber auch makroskopischer Spikemuster während 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 räumlich und zeitlich verteilte Spikemuster, anstatt sequentieller binärer Werte zur Informationsrepräsentation 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 Potentialverläufe. 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 rühren, biologische Prinzipien der Schallverarbeitung zu erforschen und für technische Systeme während der Interaktion mit dem Menschen nutzbar zu machen. Zusätzlich werden fünf Gründe für die Nutzung von Spike-Interaktionsmodellen angeführt sowie deren neuartiger Charakter beschrieben. Kapitel 2 führt die biologischen Prinzipien der Schallquellenlokalisation und den psychoakustischen Präzedenz Effekt ein. Aktuelle Hypothesen zur Entstehung dieses Effektes werden anhand ausgewählter experimenteller Ergebnisse verschiedener Forschungsgruppen diskutiert. Kapitel 3 beschreibt die entwickelte Neuronale Basisbibliothek und führt die einzelnen neuronalen Simulationselemente ein. Es erklärt die zugrundeliegenden mathematischen Funktionen der dynamischen Komponenten und beschreibt deren generelle Einsetzbarkeit zur dynamischen Simulation spikebasierter Neuronaler Netzwerke. Kapitel 4 enthält ein speziell entworfenes Modell des auditorischen Hirnstammes beginnend mit den Filterkaskaden zur Simulation des Innenohres, sich fortsetzend über 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 enthält grundlegende Hinweise zur Nutzung der Simulationsumgebung. Kapitel 5 besteht aus drei Abschnitten, wobei der erste Abschnitt die Experimentalbedingungen und Ergebnisse der eigens durchgeführten Tierversuche beschreibt. Der zweite Abschnitt stellt die Ergebnisse von 104 Modellversuchen zur Simulationen psycho-akustischer Effekte dar, welche u.a. die Fähigkeit des Modells zur Nachbildung des Präzedenz Effektes testen. Schließlich beschreibt der letzte Abschnitt die Ergebnisse der 54 unter realen Umweltbedingungen durchgeführten Experimente. Dabei kamen Signale zur Anwendung, welche in normalen sowie besonders stark verhallten Räumen aufgezeichnet wurden. Kapitel 6 vergleicht diese Ergebnisse mit anderen biologisch motivierten und technischen Verfahren zur Echounterdrückung und Schallquellenlokalisation und führt den aktuellen Status der Hardwareimplementierung ein. Kapitel 7 enthält schließlich eine kurze Zusammenfassung und einen Ausblick auf weitere Forschungsobjekte und geplante Aktivitäten. Diese Arbeit möchte zur Entwicklung der Computational Neuroscience beitragen, indem sie versucht, in einem speziellen Anwendungsfeld die Lücke zwischen biologischen Erkenntnissen, rechentechnischen Modellen und Hardware Engineering zu schließen. Sie empfiehlt ein neues räumlich-zeitliches Paradigma der dynamischen Informationsverarbeitung zur Erschließung biologischer Prinzipien der Informationsverarbeitung für 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

Hearing the light: neural and perceptual encoding of optogenetic stimulation in the central auditory pathway

Optogenetics provides a means to dissect the organization and function of neural circuits. Optogenetics also offers the translational promise of restoring sensation, enabling movement or supplanting abnormal activity patterns in pathological brain circuits. However, the inherent sluggishness of evoked photocurrents in conventional channelrhodopsins has hampered the development of optoprostheses that adequately mimic the rate and timing of natural spike patterning. Here, we explore the feasibility and limitations of a central auditory optoprosthesis by photoactivating mouse auditory midbrain neurons that either express channelrhodopsin-2 (ChR2) or Chronos, a channelrhodopsin with ultra-fast channel kinetics. Chronos-mediated spike fidelity surpassed ChR2 and natural acoustic stimulation to support a superior code for the detection and discrimination of rapid pulse trains. Interestingly, this midbrain coding advantage did not translate to a perceptual advantage, as behavioral detection of midbrain activation was equivalent with both opsins. Auditory cortex recordings revealed that the precisely synchronized midbrain responses had been converted to a simplified rate code that was indistinguishable between opsins and less robust overall than acoustic stimulation. These findings demonstrate the temporal coding benefits that can be realized with next-generation channelrhodopsins, but also highlight the challenge of inducing variegated patterns of forebrain spiking activity that support adaptive perception and behavior

Central nervous system microstimulation: Towards selective micro-neuromodulation

Electrical stimulation technologies capable of modulating neural activity are well established for neuroscientific research and neurotherapeutics. Recent micro-neuromodulation experimental results continue to explain neural processing complexity and suggest the potential for assistive technologies capable of restoring or repairing of basic function. Nonetheless, performance is dependent upon the specificity of the stimulation. Increasingly specific stimulation is hypothesized to be achieved by progressively smaller interfaces. Miniaturization is a current focus of neural implants due to improvements in mitigation of the body's foreign body response. It is likely that these exciting technologies will offer the promise to provide large-scale micro-neuromodulation in the future. Here, we highlight recent successes of assistive technologies through bidirectional neuroprostheses currently being used to repair or restore basic brain functionality. Furthermore, we introduce recent neuromodulation technologies that might improve the effectiveness of these neuroprosthetic interfaces by increasing their chronic stability and microstimulation specificity. We suggest a vision where the natural progression of innovative technologies and scientific knowledge enables the ability to selectively micro-neuromodulate every neuron in the brain

Real-time FGPA implementation of a neuromorphic pitch detection system

This thesis explores the real-time implementation of a biologically inspired pitch detection system in digital electronics. Pitch detection is well understood and has been shown to occur in the initial stages of the auditory brainstem. By building such a system in digital hardware we can prove the feasibility of implementing neuromorphic systems using digital technology. This research not only aims to prove that such an implementation is possible but to investigate ways of achieving efficient and effective designs. We aim to achieve this complexity reduction while maintaining the fine granularity of the signal processing inherent in neural systems. By producing an efficient design we present the possibility of implementing the system within the available resources, thus producing a demonstrable system. This thesis presents a review of computational models of all the components within the pitch detection system. The review also identifies key issues relating to the efficient implementation and development of the pitch detection system. Four investigations are presented to address these issues for optimal neuromorphic designs of neuromorphic systems. The first investigation aims to produce the first-ever digital hardware implementation of the inner hair cell. The second investigation develops simplified models of the auditory nerve and the coincidence cell. The third investigation aims to reduce the most complex stage of the system, the stellate chopper cell array. Finally, we investigate implementing a large portion of the pitch detection system in hardware. The results contained in this thesis enable us to understand the feasibility of implementing such systems in real-time digital hardware. This knowledge may help researchers to make design decisions within the field of digital neuromorphic systems

Signal Transmission in the Auditory System

Contains table of contents for Section 3, an introduction and reports on seven research projects.National Institutes of Health Grant P01-DC-00119National Institutes of Health Grant R01-DC-00194National Institutes of Health Grant R01 DC00238National Institutes of Health Grant R01-DC02258National Institutes of Health Grant T32-DC00038National Institutes of Health Grant P01-DC00361National Institutes of Health Grant 2RO1 DC00235National Institutes of Health Contract N01-DC2240