The blinking eye: A window into tinnitus

Tinnitus is a prevalent untreatable audiological disorder, charaterized by the perception of phantom sound. Despite longstanding research with animals, its underlying pathophysiology remains poorly understood. The obstacle in progressing in the field may lie in both the current species of choice and the available measurements of tinnitus for animals. To provide fresh impetus, we developed a novel tinnitus-verification technique applicable to rhesus monkeys. Tinnitus was induced via salicylate administration in two rhesus monkeys, and was confirmed by applying a specific eye-blinking procedure: Blinks, as monitored using EMG, were triggered via puffs of air towards the cheek, and their modulation was studied as a function of preceding tones with various frequency and intensity conditions. The advantage in using a tactile reflex-inducing stimulus lies in its non-auditory modality, bypassing potential confounding factors of hearing loss and hyperacusis. Interference effects on the blink modulation pattern was interpreted as tinnitus, and the interfering frequency of the preceding interfering tone as tinnitus frequency. A cross-validation in a sample of tinnitus patients revealed interfering effects of the preceding tone at the specific frequency range corresponding to their own tinnitus frequency, as independently determined by audiologists. This interference effect increased as a function of their individual tinnitus loudness. In conclusion, the present work demonstrates a considerable transferability of our newly established tinnitus-verification technique from non-human primates to human tinnitus patients.

Automatic Recognition of Communication Signal Modulation Based on the Multiple-Parallel Complex Convolutional Neural Network

This paper implements a deep learning-based modulation pattern recognition algorithm for communication signals using a convolutional neural network architecture as a modulation recognizer. In this paper, a multiple-parallel complex convolutional neural network architecture is proposed to meet the demand of complex baseband processing of all-digital communication signals. The architecture learns the structured features of the real and imaginary parts of the baseband signal through parallel branches and fuses them at the output according to certain rules to obtain the final output, which realizes the fitting process to the complex numerical mapping. By comparing and analyzing several commonly used time-frequency analysis methods, a time-frequency analysis method that can well highlight the differences between different signal modulation patterns is selected to convert the time-frequency map into a digital image that can be processed by a deep network. In order to fully extract the spatial and temporal characteristics of the signal, the CLP algorithm of the CNN network and LSTM network in parallel is proposed. The CNN network and LSTM network are used to extract the spatial features and temporal features of the signal, respectively, and the fusion of the two features as well as the classification is performed. Finally, the optimal model and parameters are obtained through the design of the modulation recognizer based on the convolutional neural network and the performance analysis of the convolutional neural network model. The simulation experimental results show that the improved convolutional neural network can produce certain performance gains in radio signal modulation style recognition. This promotes the application of machine learning algorithms in the field of radio signal modulation pattern recognition.

Neuronal Actions of Transspinal Stimulation on Locomotor Networks and Reflex Excitability During Walking in Humans With and Without Spinal Cord Injury

This study investigated the neuromodulatory effects of transspinal stimulation on soleus H-reflex excitability and electromyographic (EMG) activity during stepping in humans with and without spinal cord injury (SCI). Thirteen able-bodied adults and 5 individuals with SCI participated in the study. EMG activity from both legs was determined for steps without, during, and after a single-pulse or pulse train transspinal stimulation delivered during stepping randomly at different phases of the step cycle. The soleus H-reflex was recorded in both subject groups under control conditions and following single-pulse transspinal stimulation at an individualized exactly similar positive and negative conditioning-test interval. The EMG activity was decreased in both subject groups at the steps during transspinal stimulation, while intralimb and interlimb coordination were altered only in SCI subjects. At the steps immediately after transspinal stimulation, the physiological phase-dependent EMG modulation pattern remained unaffected in able-bodied subjects. The conditioned soleus H-reflex was depressed throughout the step cycle in both subject groups. Transspinal stimulation modulated depolarization of motoneurons over multiple segments, limb coordination, and soleus H-reflex excitability during assisted stepping. The soleus H-reflex depression may be the result of complex spinal inhibitory interneuronal circuits activated by transspinal stimulation and collision between orthodromic and antidromic volleys in the peripheral mixed nerve. The soleus H-reflex depression by transspinal stimulation suggests a potential application for normalization of spinal reflex excitability after SCI.

Characterization of Tiled Architecture for C-Band 1-Bit Beam-Steering Transmitarray

A new implementation of a beam-steering transmitarray is proposed based on the tiled array architecture. Each pixel of the transmitarray is manufactured as a standalone unit which can be hard-wired for specific transmission characteristics. A set of complementary units, providing reciprocal phase-shifts, can be assembled in a prescribed spatial phase-modulation pattern to perform beam steering and beam forming in a broad spatial range. A compact circuit model of the tiled unit cell is proposed and characterized with full-wave electromagnetic simulations. Waveguide measurements of a prototype unit cell have been carried out. A design example of a tiled 10 × 10-element 1-bit beam-steering transmitarray is presented and its performance benchmarked against the conventional single-panel, i.e., unibody, counterpart. Prototypes of the tiled and single-panel C-band transmitarrays have been fabricated and tested, demonstrating their close performance, good agreement with simulations and a weak effect of fabrication tolerances. The proposed transmitarray antenna configuration has great potential for fifth-generation (5G) communication systems.

Intelligent modulation recognition algorithm for optical communication

In order to improve the modulation recognition algorithm effect of an optical communication system, an improved modulation recognition algorithm technology based on wavelet transform on the time-varying optical communication system is designed. Firstly, considering the time-varying effect of noise on the communication system, wavelet transform is introduced to pre-process the signal of the optical communication system, extracting the characteristic number of modulation recognition of optical communication system, and a classifier of modulation recognition is established by data mining technology to realize modulation recognition technology of optical communication system. Finally, several typical modulation modes of the optical communication system are tested by simulated experiments. In this paper, several typical modulation modes are identified accurately, and real-time on-line analysis of modulation recognition is realized. In the optical communication system, the recognition accuracy of the modulation pattern is higher than other modulation recognition technologies, which has high practical application value.