Neuronal assembly dynamics in supervised and unsupervised learning scenarios

The dynamic formation of groups of neurons—neuronal assemblies—is believed to mediate cognitive phenomena at many levels, but their detailed operation and mechanisms of interaction are still to be uncovered. One hypothesis suggests that synchronized oscillations underpin their formation and functioning, with a focus on the temporal structure of neuronal signals. In this context, we investigate neuronal assembly dynamics in two complementary scenarios: the first, a supervised spike pattern classification task, in which noisy variations of a collection of spikes have to be correctly labeled; the second, an unsupervised, minimally cognitive evolutionary robotics tasks, in which an evolved agent has to cope with multiple, possibly conflicting, objectives. In both cases, the more traditional dynamical analysis of the system’s variables is paired with information-theoretic techniques in order to get a broader picture of the ongoing interactions with and within the network. The neural network model is inspired by the Kuramoto model of coupled phase oscillators and allows one to fine-tune the network synchronization dynamics and assembly configuration. The experiments explore the computational power, redundancy, and generalization capability of neuronal circuits, demonstrating that performance depends nonlinearly on the number of assemblies and neurons in the network and showing that the framework can be exploited to generate minimally cognitive behaviors, with dynamic assembly formation accounting for varying degrees of stimuli modulation of the sensorimotor interactions

Digital PLL for ISM applications

In modern transceivers, a low power PLL is a key block. It is known that with the evolution of technology, lower power and high performance circuitry is a challenging demand. In this thesis, a low power PLL is developed in order not to exceed 2mW of total power consumption. It is composed by small area blocks which is one of the main demands. The blocks that compose the PLL are widely abridged and the final solution is shown, showing why it is employed. The VCO block is a Current-Starved Ring Oscillator with a frequency range from 400MHz to 1.5GHz, with a 300μW to approximately 660μW power consumption. The divider is composed by six TSPC D Flip-Flop in series, forming a divide-by-64 divider. The Phase-Detector is a Dual D Flip-Flop detector with a charge pump. The PLL has less than a 2us lock time and presents a output oscillation of 1GHz, as expected. It also has a total power consumption of 1.3mW, therefore fulfilling all the specifications. The main contributions of this thesis are that this PLL can be applied in ISM applications due to its covering frequency range and low cost 130nm CMOS technology

Phase noise reduction techniques for RF signal generator

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Impact of the Flicker Noise on the Ring Oscillator-based TRNGs

Ring Oscillators (RO) are often used in true random number generators (TRNG). Their jittered clock signal, used as randomness source, originates from thermal and flicker noises. While thermal noise jitter is generally used as the main source of randomness, flicker noise jitter is not due to its autocorrelation. This work aims at qualitatively settling the issue of the influence of flicker noise in TRNGs, as its impact increases in newer technology nodes. For this, we built a RO behavioural model, which generates time series equivalent to a jittered RO signal. It is then used to generate the output of an elementary RO-TRNG. Despite general expectations, the autocorrelation inside the output bit stream is reduced when the amplitude of flicker noise increases. The model shows that this effect is caused by the sampling of the jittered signal by the second oscillator, which hides the behaviour of the absolute jitter, causes resetting of the perceived phase, and suppresses any memory effect. The inclusion of flicker noise as a legitimate noise source can increase the TRNG output bit rate by a factor of four for the same output entropy rate. This observation opens new perspectives towards more efficient stochastic models of the RO-TRNGs

A New Approach for Determining Phase Response Curves Reveals that Purkinje Cells Can Act as Perfect Integrators

Cerebellar Purkinje cells display complex intrinsic dynamics. They fire spontaneously, exhibit bistability, and via mutual network interactions are involved in the generation of high frequency oscillations and travelling waves of activity. To probe the dynamical properties of Purkinje cells we measured their phase response curves (PRCs). PRCs quantify the change in spike phase caused by a stimulus as a function of its temporal position within the interspike interval, and are widely used to predict neuronal responses to more complex stimulus patterns. Significant variability in the interspike interval during spontaneous firing can lead to PRCs with a low signal-to-noise ratio, requiring averaging over thousands of trials. We show using electrophysiological experiments and simulations that the PRC calculated in the traditional way by sampling the interspike interval with brief current pulses is biased. We introduce a corrected approach for calculating PRCs which eliminates this bias. Using our new approach, we show that Purkinje cell PRCs change qualitatively depending on the firing frequency of the cell. At high firing rates, Purkinje cells exhibit single-peaked, or monophasic PRCs. Surprisingly, at low firing rates, Purkinje cell PRCs are largely independent of phase, resembling PRCs of ideal non-leaky integrate-and-fire neurons. These results indicate that Purkinje cells can act as perfect integrators at low firing rates, and that the integration mode of Purkinje cells depends on their firing rate

System level performance and yield optimisation for analogue integrated circuits

Advances in silicon technology over the last decade have led to increased integration of analogue and digital functional blocks onto the same single chip. In such a mixed signal environment, the analogue circuits must use the same process technology as their digital neighbours. With reducing transistor sizes, the impact of process variations on analogue design has become prominent and can lead to circuit performance falling below specification and hence reducing the yield.This thesis explores the methodology and algorithms for an analogue integrated circuit automation tool that optimizes performance and yield. The trade-offs between performance and yield are analysed using a combination of an evolutionary algorithm and Monte Carlo simulation. Through the integration of yield parameter into the optimisation process, the trade off between the performance functions can be better treated that able to produce a higher yield. The results obtained from the performance and variation exploration are modelled behaviourally using a Verilog-A language. The model has been verified with transistor level simulation and a silicon prototype.For a large analogue system, the circuit is commonly broken down into its constituent sub-blocks, a process known as hierarchical design. The use of hierarchical-based design and optimisation simplifies the design task and accelerates the design flow by encouraging design reuse.A new approach for system level yield optimisation using a hierarchical-based design is proposed and developed. The approach combines Multi-Objective Bottom Up (MUBU) modelling technique to model the circuit performance and variation and Top Down Constraint Design (TDCD) technique for the complete system level design. The proposed method has been used to design a 7th order low pass filter and a charge pump phase locked loop system. The results have been verified with transistor level simulations and suggest that an accurate system level performance and yield prediction can be achieved with the proposed methodology

Dopamiinin hapettumisen lukija-anturirajapinta 65 nm CMOS teknologialla

Sensing and monitoring of neural activities within the central nervous system has become a fast-growing area of research due to the need to understand more about how neurons communicate. Several neurological disorders such as Parkinson’s disease, Schizophrenia, Alzeihmers and Epilepsy have been reported to be associated with imbalance in the concentration of neurotransmitters such as glutamate and dopamine [1] - [5]. Hence, this thesis proposes a solution for the measurement of dopamine concentration in the brain during neural communication. The proposed design of the dopamine oxidation readout sensor interface is based on a mixed-signal front-end architecture for minimizing noise and high resolution of detected current signals. The analog front-end is designed for acquisition and amplification of current signals resulting from oxidation and reduction at the biosensor electrodes in the brain. The digital signal processing (DSP) block is used for discretization of detected dopamine oxidation and reduction current signals that can be further processed by an external system. The results from the simulation of the proposed design show that the readout circuit has a current resolution of 100 pA and can detect minimum dopamine concentration of 10 μMol based on measured data from novel diamond-like carbon electrodes [6]. Higher dopamine concentration can be detected from the sensor interface due to its support for a wide current range of 1.2 μA(±600 nA). The digital code representation of the detected dopamine has a resolution of 14.3-bits with RMS conversion error of 0.18 LSB which results in an SNR of 88 dB at full current range input. However, the attained ENOB is 8-bits due to the effect of nonlinearity in the oscillator based ADC. Nonetheless, the achieved resolution of the readout circuit provides good sensitivity of released dopamine in the brain which is useful for further understanding of neurotransmitters and fostering research into improved treatments of related neurodegenerative diseases.Keskushermoston aktiivisuuden havainnointi ja tarkkailu on muodostunut tärkeäksi tutkimusalaksi, sillä tarve ymmärtää neuronien viestintää on kasvanut. Monien hermostollisten sairauksien kuten Parkinsonin taudin, skitsofrenian, Alzheimerin taudin ja epilepsian on huomattu aiheuttavan muutoksia välittäjäaineiden, kuten glutamaatin ja dopamiinin, pitoisuuksissa [1] - [5]. Aiheeseen liittyen tässä työssä esitetään ratkaisu dopamiinipitoisuuden mittaamiseksi aivoista. Esitetty dopamiinipitoisuuden lukijapiiri perustuu sekamuotoiseen etupäärakenteeseen, jolla saavutetaan matala kohinataso ja hyvä tarkkuus signaalien ilmaisemisessa. Suunniteltu analoginen etupää kykenee lukemaan ja vahvistamaan dopamiinipitoisuuden muutosten aiheuttamia virran muutoksia aivoihin asennetuista elektrodeista. Digitaalisen signaalinkäsittelyn avulla voidaan havaita dopamiinin hapettumis-ja pelkistymisvirtasignaalit, ja välittää ne edelleen ulkoisen järjestelmän muokattavaksi. Simulaatiotulokset osoittavat, että suunniteltu piiri saavuttaa 100 pA virran erottelukyvyn. Simuloinnin perustuessa hiilipohjaisiin dopamiinielektrodeihin piiri voi havaita 10 μMol dopamiinipitoisuuden [6]. Myös suurempia dopamiinipitoisuuksia voidaan havaita, sillä etupäärajapinta tukee 1.2 μA(±600 nA) virta-aluetta. Digitaalinen esitysmuoto tukee 14.3 bitin esitystarkkuutta 0.18 bitin RMS virheellä saavuttaen 88 dB dynaamisen virta-alueen. Saavutettu ENOB (tehollinen bittimäärä) on kuitenkin 8 bittiä oskillaattoripohjaisen ADC:n (analogia-digitaalimuuntimen) epälineaarisuuden takia. Saavutettu tarkkuus tuottaa hyvän herkkyyden dopamiinin havaitsemiseksi ja hyödyttää siten välittäjäainetutkimusta ja uusien hoitomuotojen kehittämistä hermostollisiin sairauksiin

Design and modelling of clock and data recovery integrated circuit in 130 nm CMOS technology for 10 Gb/s serial data communications

This thesis describes the design and implementation of a fully monolithic 10 Gb/s phase and frequency-locked loop based clock and data recovery (PFLL-CDR) integrated circuit, as well as the Verilog-A modeling of an asynchronous serial link based chip to chip communication system incorporating the proposed concept. The proposed design was implemented and fabricated using the 130 nm CMOS technology offered by UMC (United Microelectronics Corporation). Different PLL-based CDR circuits topologies were investigated in terms of architecture and speed. Based on the investigation, we proposed a new concept of quarter-rate (i.e. the clocking speed in the circuit is 2.5 GHz for 10 Gb/s data rate) and dual-loop topology which consists of phase-locked and frequency-locked loop. The frequency-locked loop (FLL) operates independently from the phase-locked loop (PLL), and has a highly-desired feature that once the proper frequency has been acquired, the FLL is automatically disabled and the PLL will take over to adjust the clock edges approximately in the middle of the incoming data bits for proper sampling. Another important feature of the proposed quarter-rate concept is the inherent 1-to-4 demultiplexing of the input serial data stream. A new quarter-rate phase detector based on the non-linear early-late phase detector concept has been used to achieve the multi-Giga bit/s speed and to eliminate the need of the front-end data pre-processing (edge detecting) units usually associated with the conventional CDR circuits. An eight-stage differential ring oscillator running at 2.5 GHz frequency center was used for the voltage-controlled oscillator (VCO) to generate low-jitter multi-phase clock signals. The transistor level simulation results demonstrated excellent performances in term of locking speed and power consumption. In order to verify the accuracy of the proposed quarter-rate concept, a clockless asynchronous serial link incorporating the proposed concept and communicating two chips at 10 Gb/s has been modelled at gate level using the Verilog-A language and time-domain simulated

Contribution à la modélisation comportementale des circuits radio-fréquence

Avec les nouvelles tendances que sont les System-on-Chip (SoC) et les ASIC mixtes, les outils de CAO analogiques doivent évoluer pour permettre une conception hiérarchique, basée sur la réutilisation de blocs, utilisant largement la modélisation comportementale des circuits. L'avènement des langages de description standards pour les circuits analogiques et mixtes (VHDL-AMS par exemple) ouvre la voie à l'amélioration attendue mais il reste à développer divers outils et méthodes. Les travaux présentés dans ce mémoire apportent une contribution à la modélisation comportementale des circuits analogiques et mixtes en termes de méthodologie et de développement de bibliothèques de modèles standards. Ainsi, nous proposons une méthode systématique de modélisation comportementale, une bibliothèque de modèles pour les circuits RF et une étude du bruit de phase aboutissant à une modélisation de ce phénomène dans les oscillateurs.The new tendencies in electronic system design are the development of System-on-Chip (SoC) and mixed ASIC. The CAD tools should evolve to allow a hierarchical design, based on the re-use of blocks and the behavioral modeling of circuits. The development of standard description languages for analogue and mixed systems (VHDL-AMS for example) opens the way to the expected improvement, but different methods and tools should be developed. This work presents a contribution to the behavioral modeling of analogue and mixed circuits in terms of methodology and development of standard model libraries. We propose a systematic method of behavioral modeling, a library of models for RF circuits and a study of the phase noise effect in oscillators ending in the behavioral modeling of this phenomenon

Algorithms and architectures for the multirate additive synthesis of musical tones

In classical Additive Synthesis (AS), the output signal is the sum of a large number of independently controllable sinusoidal partials. The advantages of AS for music synthesis are well known as is the high computational cost. This thesis is concerned with the computational optimisation of AS by multirate DSP techniques. In note-based music synthesis, the expected bounds of the frequency trajectory of each partial in a finite lifecycle tone determine critical time-invariant partial-specific sample rates which are lower than the conventional rate (in excess of 40kHz) resulting in computational savings. Scheduling and interpolation (to suppress quantisation noise) for many sample rates is required, leading to the concept of Multirate Additive Synthesis (MAS) where these overheads are minimised by synthesis filterbanks which quantise the set of available sample rates. Alternative AS optimisations are also appraised. It is shown that a hierarchical interpretation of the QMF filterbank preserves AS generality and permits efficient context-specific adaptation of computation to required note dynamics. Practical QMF implementation and the modifications necessary for MAS are discussed. QMF transition widths can be logically excluded from the MAS paradigm, at a cost. Therefore a novel filterbank is evaluated where transition widths are physically excluded. Benchmarking of a hypothetical orchestral synthesis application provides a tentative quantitative analysis of the performance improvement of MAS over AS. The mapping of MAS into VLSI is opened by a review of sine computation techniques. Then the functional specification and high-level design of a conceptual MAS Coprocessor (MASC) is developed which functions with high autonomy in a loosely-coupled master- slave configuration with a Host CPU which executes filterbanks in software. Standard hardware optimisation techniques are used, such as pipelining, based upon the principle of an application-specific memory hierarchy which maximises MASC throughput