Integration of continuous-time dynamics in a spiking neural network simulator

Contemporary modeling approaches to the dynamics of neural networks consider two main classes of models: biologically grounded spiking neurons and functionally inspired rate-based units. The unified simulation framework presented here supports the combination of the two for multi-scale modeling approaches, the quantitative validation of mean-field approaches by spiking network simulations, and an increase in reliability by usage of the same simulation code and the same network model specifications for both model classes. While most efficient spiking simulations rely on the communication of discrete events, rate models require time-continuous interactions between neurons. Exploiting the conceptual similarity to the inclusion of gap junctions in spiking network simulations, we arrive at a reference implementation of instantaneous and delayed interactions between rate-based models in a spiking network simulator. The separation of rate dynamics from the general connection and communication infrastructure ensures flexibility of the framework. We further demonstrate the broad applicability of the framework by considering various examples from the literature ranging from random networks to neural field models. The study provides the prerequisite for interactions between rate-based and spiking models in a joint simulation

Peak polarity selector Patent

Peak polarity selector for monitoring waveform

Wearable Platform for Automatic Recognition of Parkinson Disease by Muscular Implication Monitoring

The need for diagnostic tools for the characterization of progressive movement disorders - as the Parkinson Disease (PD) - aiming to early detect and monitor the pathology is getting more and more impelling. The parallel request of wearable and wireless solutions, for the real-time monitoring in a non-controlled environment, has led to the implementation of a Quantitative Gait Analysis platform for the extraction of muscular implications features in ordinary motor action, such as gait. The here proposed platform is used for the quantification of PD symptoms. Addressing the wearable trend, the proposed architecture is able to define the real-time modulation of the muscular indexes by using 8 EMG wireless nodes positioned on lower limbs. The implemented system “translates” the acquisition in a 1-bit signal, exploiting a dynamic thresholding algorithm. The resulting 1-bit signals are used both to define muscular indexes both to drastically reduce the amount of data to be analyzed, preserving at the same time the muscular information. The overall architecture has been fully implemented on Altera Cyclone V FPGA. The system has been tested on 4 subjects: 2 affected by PD and 2 healthy subjects (control group). The experimental results highlight the validity of the proposed solution in Disease recognition and the outcomes match the clinical literature results

An optical NMR spectrometer for Larmor-beat detection and high-resolution POWER NMR

Optical nuclear magnetic resonance (ONMR) is a powerful probe of electronic properties in III-V semiconductors. Larmor-beat detection (LBD) is a sensitivity optimized, time-domain NMR version of optical detection based on the Hanle effect. Combining LBD ONMR with the line-narrowing method of POWER (perturbations observed with enhanced resolution) NMR further enables atomically detailed views of local electronic features in III-Vs. POWER NMR spectra display the distribution of resonance shifts or line splittings introduced by a perturbation, such as optical excitation or application of an electric field, that is synchronized with a NMR multiple-pulse time-suspension sequence. Meanwhile, ONMR provides the requisite sensitivity and spatial selectivity to isolate local signals within macroscopic samples. Optical NMR, LBD, and the POWER method each introduce unique demands on instrumentation. Here, we detail the design and implementation of our system, including cryogenic, optical, and radio-frequency components. The result is a flexible, low-cost system with important applications in semiconductor electronics and spin physics. We also demonstrate the performance of our systems with high-resolution ONMR spectra of an epitaxial AlGaAs/GaAs heterojunction. NMR linewidths down to 4.1 Hz full width at half maximum were obtained, a 10^3-fold resolution enhancement relative any previous optically detected NMR experiment

Behavioural simulation of mixed analogue/digital circuits.

Continuing improvements in integrated circuit technology have made possible the implementation of complex electronic systems on a single chip. This often requires both analogue and digital signal processing. It is essential to simulate such IC's during the design process to detect errors at an early stage. Unfortunately, the simulators that are currently available are not well-suited to large mixed-signal circuits. This thesis describes the design and development of a new methodology for simulating analogue and digital components in a single, integrated environment. The methodology represents components as behavioural models that are more efficient than the circuit models used in conventional simulators. The signals that flow between models are all represented as piecewise-linear (PWL) waveforms. Since models representing digital and analogue components use the same format to represent their signals, they can be directly connected together. An object-oriented approach was used to create a class hierarchy to implement the component models. This supports rapid development of new models since all models are derived from a common base class and inherit the methods and attributes defined in their parentc lassesT. he signal objectsa re implementedw ith a similar class hierarchy. The development and validation of models representing various digital, analogue and mixed-signal components are described. Comparisons are made between the accuracy and performance of the proposed methodology and several commercial simulators. The development of a Windows-based demonstrations imulation tool called POISE is also described. This permitted models to be tested independently and multiple models to be connected together to form structural models of complex circuits