Comparative evaluation of approaches in T.4.1-4.3 and working definition of adaptive module

The goal of this deliverable is two-fold: (1) to present and compare different approaches towards learning and encoding movements us- ing dynamical systems that have been developed by the AMARSi partners (in the past during the first 6 months of the project), and (2) to analyze their suitability to be used as adaptive modules, i.e. as building blocks for the complete architecture that will be devel- oped in the project. The document presents a total of eight approaches, in two groups: modules for discrete movements (i.e. with a clear goal where the movement stops) and for rhythmic movements (i.e. which exhibit periodicity). The basic formulation of each approach is presented together with some illustrative simulation results. Key character- istics such as the type of dynamical behavior, learning algorithm, generalization properties, stability analysis are then discussed for each approach. We then make a comparative analysis of the different approaches by comparing these characteristics and discussing their suitability for the AMARSi project

On the interaction of gamma-rhythmic neuronal populations

Local gamma-band (~30-100Hz) oscillations in the brain, produced by feedback inhibition on a characteristic timescale, appear in multiple areas of the brain and are associated with a wide range of cognitive functions. Some regions producing gamma also receive gamma-rhythmic input, and the interaction and coordination of these rhythms has been hypothesized to serve various functional roles. This thesis consists of three stand-alone chapters, each of which considers the response of a gamma-rhythmic neuronal circuit to input in an analytical framework. In the first, we demonstrate that several related models of a gamma-generating circuit under periodic forcing are asymptotically drawn onto an attracting invariant torus due to the convergence of inhibition trajectories at spikes and the convergence of voltage trajectories during sustained inhibition, and therefore display a restricted range of dynamics. In the second, we show that a model of a gamma-generating circuit under forcing by square pulses cannot maintain multiple stably phase-locked solutions. In the third, we show that a separation of time scales of membrane potential dynamics and synaptic decay causes the gamma model to phase align its spiking such that periodic forcing pulses arrive under minimal inhibition. When two of these models are mutually coupled, the same effect causes excitatory pulses from the faster oscillator to arrive at the slower under minimal inhibition, while pulses from the slower to the faster arrive under maximal inhibition. We also show that such a time scale separation allows the model to respond sensitively to input pulse coherence to an extent that is not possible for a simple one-dimensional oscillator. We draw on a wide range of mathematical tools and structures including return maps, saltation matrices, contraction methods, phase response formalism, and singular perturbation theory in order to show that the neuronal mechanism of gamma oscillations is uniquely suited to reliably phase lock across brain regions and facilitate the selective transmission of information

Principles for Making Half-center Oscillators and Rules for Torus Bifurcation in Neuron Models

In this modelling work, we adopted geometric slow-fast dissection and parameter continuation approach to study the following three topics: 1. Principles for making the half-center oscillator, a ubiquitous building block for many rhythm-generating neural networks. 2. Causes of a novel electrical behavior of neurons, amplitude modulation, from the view of dynamical systems; 3. Explanation and predictions for two common types of chaotic dynamics in single neuron model. To make our work as general as possible, we used and built both exemplary biologically plausible Hodgkin-Huxley type neuron models and reduced phenomenological neuron models

A Physical Unclonable Function Based on Inter-Metal Layer Resistance Variations and an Evaluation of its Temperature and Voltage Stability

Keying material for encryption is stored as digital bistrings in non-volatile memory (NVM) on FPGAs and ASICs in current technologies. However, secrets stored this way are not secure against a determined adversary, who can use probing attacks to steal the secret. Physical Unclonable functions (PUFs) have emerged as an alternative. PUFs leverage random manufacturing variations as the source of entropy for generating random bitstrings, and incorporate an on-chip infrastructure for measuring and digitizing the corresponding variations in key electrical parameters, such as delay or voltage. PUFs are designed to reproduce a bitstring on demand and therefore eliminate the need for on-chip storage. In this dissertation, I propose a kind of PUF that measures resistance variations in inter-metal layers that define the power grid of the chip and evaluate its temperature and voltage stability. First, I introduce two implementations of a power grid-based PUF (PG-PUF). Then, I analyze the quality of bit strings generated without considering environmental variations from the PG-PUFs that leverage resistance variations in: 1) the power grid metal wires in 60 copies of a 90 nm chip and 2) in the power grid metal wires of 58 copies of a 65 nm chip. Next, I carry out a series of experiments in a set of 63 chips in IBM\u27s 90 nm technology at 9 TV corners, i.e., over all combination of 3 temperatures: -40oC, 25oC and 85oC and 3 voltages: nominal and +/-10% of the nominal supply voltage. The randomness, uniqueness and stability characteristics of bitstrings generated from PG-PUFs are evaluated. The stability of the PG-PUF and an on-chip voltage-to-digital (VDC) are also evaluated at 9 temperature-voltage corners. I introduce several techniques that have not been previously described, including a mechanism to eliminate voltage trends or \u27bias\u27 in the power grid voltage measurements, as well as a voltage threshold, Triple-Module-Redundancy (TMR) and majority voting scheme to identify and exclude unstable bits