Lirio Onofre Baptista de Almeida

A new technique to construct a wavelet transform matching a specified signal with applications to digital, real time, spike, and overlap pattern recognition

This work describes a new and different path to create a wavelet transform that can match a specified discrete-time signal. Called Spikelet, it is designed and optimized to spike and overlap pattern recognition in the digitalized signal that comes from H1, a motion-sensitive neuron of the flys visual system. The technique proposed here and the associated algorithm, implemented in real time using a digital signal processor (DSP), are fully detailed. The results obtained matching the signal under analysis show an improvement over all other transforms, including the Daubechies transform. This reassures the efficacy of our transform. rm.

Recording from two neurons: Second-order stimulus reconstruction from spike trains and population coding

We study the reconstruction of visual stimuli from spike trains, representing the reconstructed stimulus by a Volterra series up to second order. We illustrate this procedure in a prominent example of spiking neurons, recording simultaneously from the two H1 neurons located in the lobula plate of the fly Chrysomya megacephala. The fly views two types of stimuli, corresponding to rotational and translational displacements. Second-order reconstructions require the manipulation of potentially very large matrices, which obstructs the use of this approach when there are many neurons. We avoid the computation and inversion of these matrices using a convenient set of basis functions to expand our variables in. This requires approximating the spike train four-point functions by combinations of two-point functions similar to relations, which would be true for gaussian stochastic processes. In our test case, this approximation does not reduce the quality of the reconstruction. The overall contribution to stimulus reconstruction of the second-order kernels, measured by the mean squared error, is only about 5 of the first-order contribution. Yet at specific stimulus-dependent instants, the addition of second-order kernels represents up to 100 improvement, but only for rotational stimuli. We present a perturbative scheme to facilitate the application of our method to weakly correlated neurons.

A complex biological system: the fly's visual module

Is the characterization of biological systems as complex systems in the mathematical sense a fruitful assertion? In this paper we argue in the affirmative, although obviously we do not attempt to confront all the issues raised by this question. We use the flys visual system as an example and analyse our experimental results of one particular neuron in the flys visual system from this point of view. We find that the motion-sensitive ‘H1’ neuron, which converts incoming signals into a sequence of identical pulses or ‘spikes’, encodes the information contained in the stimulus into an alphabet composed of a few letters. This encoding occurs on multilayered sets, one of the features attributed to complex systems. The conversion of intervals between consecutive occurrences of spikes into an alphabet requires us to construct a generating partition. This entails a one-to-one correspondence between sequences of spike intervals and words written in the alphabet. The alphabet dynamics is multifractal both with and without stimulus, though the multifractality increases with the stimulus entropy. This is in sharp contrast to models generating independent spike intervals, such as models using Poisson statistics, whose dynamics is monofractal. We embed the support of the probability measure, which describes the distribution of words written in this alphabet, in a two-dimensional space, whose topology can be reproduced by an M-shaped map. This map has positive Lyapunov exponents, indicating a chaotic-like encoding.

VSImG: A high frame rate bitmap based display system for neuroscience research

This paper describes a visual stimulus generator (VSImG) capable of displaying a gray-scale, 256x256x8bitmap image with a frame rate of 500Hz using a boustrophedonic scanning technique. It is designed for experiments with motion-sensitive neurons of the flys visual system, where the flicker fusion frequency of the photoreceptors can reach up to 500Hz. Devices with such a high frame rate are not commercially available, but are required, if sensory systems with high flicker fusion frequency are to be studied. The implemented hardware approach gives us complete real-time control of the displacement sequence and provides all the signals needed to drive an electrostatic deflection display. With the use of analog signals, very small high-resolution displacements, not limited by the images pixel size can be obtained. Very slow image displacements with visually imperceptible steps can also be generated. This can be of interest for other vision research experiments. Two different stimulus files can be used simultaneously, allowing the system to generate X-Y displacements on one display or independent movements on two displays as long as they share the same bitmap image.

An embedded system for real-time feedback neuroscience experiments

A complete data acquisition and signal output control system for synchronous stimuli generation, geared towards in vivo neuroscience experiments, was developed using the Terasic DE2i-150 board. All emotions and thoughts are an emergent property of the chemical and electrical activity of neurons. Most of these cells are regarded as excitable cells (spiking neurons), which produce temporally localized electric patterns (spikes). Researchers usually consider that only the instant of occurrence (timestamp) of these spikes encodes information. Registering neural activity evoked by stimuli demands timing determinism and data storage capabilities that cannot be met without dedicated hardware and a hard real-time operational system (RTOS). Indeed, research in neuroscience usually requires dedicated electronic instrumentation for studies in neural coding, brain machine interfaces and closed loop in vivo or in vitro experiments. We developed a complete embedded system solution consisting of a hardware/software co-design with the Intel Atom processor running a free RTOS and a FPGA communicating via a PCIe-to-Avalon bridge. Our system is capable of registering input event timestamps with 1{\mu}s precision and digitally generating stimuli output in hard real-time. The whole system is controlled by a Linux-based Graphical User Interface (GUI). Collected results are simultaneously saved in a local file and broadcasted wirelessly to mobile device web-browsers in an user-friendly graphic format, enhanced by HTML5 technology. The developed system is low-cost and highly configurable, enabling various neuroscience experimental setups, while the commercial off-the-shelf systems have low availability and are less flexible to adapt to specific experimental configurations.

Automated pulse discrimination of two freely-swimming weakly electric fish and analysis of their electrical behavior during dominance contest

Electric fishes modulate their electric organ discharges with a remarkable variability. Some patterns can be easily identified, such as pulse rate changes, offs and chirps, which are often associated with important behavioral contexts, including aggression, hiding and mating. However, these behaviors are only observed when at least two fish are freely interacting. Although their electrical pulses can be easily recorded by non-invasive techniques, discriminating the emitter of each pulse is challenging when physically similar fish are allowed to freely move and interact. Here we optimized a custom-made software recently designed to identify the emitter of pulses by using automated chirp detection, adaptive threshold for pulse detection and slightly changing how the recorded signals are integrated. With these optimizations, we performed a quantitative analysis of the statistical changes throughout the dominance contest with respect to Inter Pulse Intervals, Chirps and Offs dyads of freely moving Gymnotus carapo. In all dyads, chirps were signatures of subsequent submission, even when they occurred early in the contest. Although offs were observed in both dominant and submissive fish, they were substantially more frequent in submissive individuals, in agreement with the idea from previous studies that offs are electric cues of submission. In general, after the dominance is established the submissive fish significantly changes its average pulse rate, while the pulse rate of the dominant remained unchanged. Additionally, no chirps or offs were observed when two fish were manually kept in direct physical contact, suggesting that these electric behaviors are not automatic responses to physical contact.

Low-Resource Bluespec Design of a Modular Acquisition and Stimulation System for Neuroscience (Abstract Only)

We have compared two different resource arbitration architectures in our developed data acquisition and stimuli generator system for neuroscience research, entirely specified in a high-level Hardware Description Language (HDL). One of them was designed with a decoupled and latency insensitive modular approach, allowing for easier code reuse, while the other adopted a centralized scheme, constructed specifically for our application. The usage of a high-level HDL allowed straightforward and stepwise code modifications to transform one architecture into the other. Despite the logic complexity penalty of synthesizing our hardware from a highly abstract language, both architectures were implemented in a very small programmable logic device without even consuming all the hardware resources. While the decoupled design has shown more resilience to input activity bursts, the centralized one gave an economy of about 10-15% in the device logic element usage. This system is not only useful for neuroscience protocols that require timing determinism and synchronous stimuli generation, but has also demonstrated that high-level languages can be effectively used for synthesizing hardware in small programmable devices.

Modular Acquisition and Stimulation System for Timestamp-driven Neuroscience Experiments

Dedicated systems are fundamental for neuroscience experimental protocols that require timing determinism and synchronous stimuli generation. We developed a data acquisition and stimuli generator system for neuroscience research, optimized for recording timestamps from up to 6 spiking neurons and entirely specified in a high-level Hardware Description Language (HDL). Despite the logic complexity penalty of synthesizing from such a language, it was possible to implement our design in a low-cost small reconfigurable device. Under a modular framework, we explored two different memory arbitration schemes for our system, evaluating both their logic element usage and resilience to input activity bursts. One of them was designed with a decoupled and latency insensitive approach, allowing for easier code reuse, while the other adopted a centralized scheme, constructed specifically for our application. The usage of a high-level HDL allowed straightforward and stepwise code modifications to transform one architecture into the other. The achieved modularity is very useful for rapidly prototyping novel electronic instrumentation systems tailored to scientific research.

Expanding the horizontal capabilities of CRT monitors using artificial inter-pixel steps for neuroscience experiments

This article describes the development of a visual stimulus generator to be used in neuroscience experiments with invertebrates such as flies. The experiment consists in the visualization of a fixed image that is displaced horizontally according to the stimulus data. The system is capable of displaying 640x480 pixels with 256 intensity levels at 200 frames per second (FPS) on conventional raster monitors. To double the possible horizontal positioning possibilities from 640 to 1280, a novel technique is presented introducing artificial inter-pixel steps. The implementation consists in using two video frame buffers containing each a distinct view of the desired image pattern. This implementation generates a visual effect capable of doubling the horizontal positioning capabilities of the visual stimulus generator allowing more precise and movements more contiguous.

Dual-monitor deterministic hardware for visual stimuli generation in neuroscience experiments

This article describes the development of a dual-monitor visual stimulus generator that is used in neuroscience experiments with invertebrates such as flies. The experiment consists in the visualization of two fixed images that are displaced horizontally according to the stimulus data. The system was developed using off-the-shelf FPGA kits and it is capable of displaying 640x480 pixels with 256 intensity levels at 200 frames per second (FPS) on each monitor. A Raster plot of the experiment with the superimposed stimuli was generated as the result of this work. A novel architecture was developed, using the same DOT Clock for both monitors, and its implementation generates a perfect synchronism in both devices.