Elias Manjarrez

Resonant Magnetic Field Sensors Based On MEMS Technology.

Microelectromechanical systems (MEMS) technology allows the integration of magnetic field sensors with electronic components, which presents important advantages such as small size, light weight, minimum power consumption, low cost, better sensitivity and high resolution. We present a discussion and review of resonant magnetic field sensors based on MEMS technology. In practice, these sensors exploit the Lorentz force in order to detect external magnetic fields through the displacement of resonant structures, which are measured with optical, capacitive, and piezoresistive sensing techniques. From these, the optical sensing presents immunity to electromagnetic interference (EMI) and reduces the read-out electronic complexity. Moreover, piezoresistive sensing requires an easy fabrication process as well as a standard packaging. A description of the operation mechanisms, advantages and drawbacks of each sensor is considered. MEMS magnetic field sensors are a potential alternative for numerous applications, including the automotive industry, military, medical, telecommunications, oceanographic, spatial, and environment science. In addition, future markets will need the development of several sensors on a single chip for measuring different parameters such as the magnetic field, pressure, temperature and acceleration.

Effects of auditory noise on the psychophysical detection of visual signals: Cross-modal stochastic resonance

Harper [D.W. Harper, Signal detection analysis of effect of white noise intensity on sensitivity to visual flicker, Percept. Mot. Skills 48 (1979) 791-798] demonstrated that the visual flicker sensitivity was an inverted U-like function of the intensity of different levels of auditory noise from 50 to 90dB (SPL), without concomitant changes in the response bias. The aim of the present study was to extend these observations in the context of the stochastic resonance, a counterintuitive phenomenon in which a particular level of noise enhances the response of a nonlinear system to a weak input signal. We show psychophysical evidence in a yes-no paradigm for the existence of a stochastic resonance-like phenomenon in the auditory-visual interactions. We show that the detection of a weak visual signal was an inverted U-like function of the intensity of different levels of auditory noise. Nevertheless, for a strong visual signal the auditory noise acts in detriment of the ability of visual detection. Our results suggest that auditory noise could be employed in vision rehabilitation interventions in order to improve the detection of weak visual signals.

Internal stochastic resonance in the coherence between spinal and cortical neuronal ensembles in the cat.

Internal stochastic resonance is a phenomenon in which the coherence of a non-linear system is enhanced by the presence of a particular, non-zero level of noise generated by internal or external sources without a periodic input signal. The aim of this study was to demonstrate the experimental occurrence of internal stochastic resonance in the coherence between spinal and cortical neuronal ensembles. Simultaneous recordings of spinal and cortical evoked potentials were made in the somatosensory system of the anaesthetized cat. Evoked potentials were produced by input noise introduced in the tactile stimulation of the hindpaw skin. Coherence between the spinal and cortical evoked activity recorded during different levels of input noise was calculated. All animals showed distinct internal stochastic resonance like behavior. We found that the mean coherence was an inverted U-like function of the level of input noise with a mean coherence peak of 0.43. To our knowledge, this is the first documented evidence of such phenomenon in an in vivo preparation of the central nervous system.

Stochastic resonance in human electroencephalographic activity elicited by mechanical tactile stimuli

Stochastic resonance (SR) is a phenomenon in which the response of a non-linear system to a weak input signal is optimized by the presence of noise. The aim of this study was to demonstrate the experimental occurrence of SR in electroencephalographic (EEG) activity elicited by mechanical tactile stimuli. Our experiments show that EEG responses evoked by mechanical tactile stimuli in the region overlying the somatosensory cortical area were optimized by the addition of certain noise amplitudes. All subjects showed distinct SR behavior. The signal-to-noise ratio (SNR) of the response evoked by mechanical indentations of the skin was an inverted U-like function of the input noise. As the noise amplitude increased, SNR values became larger. A maximum value was reached with a particular noise amplitude value. Beyond such peak, with higher noise amplitudes, the curve subsided gradually. To our knowledge, this is the first documented evidence that such remarkable phenomenon embodies electrical processes of the human brain. Such behavior might explain related findings described in psychophysical studies.

Improved Sensorimotor Performance via Stochastic Resonance

Several studies about noise-enhanced balance control in humans support the hypothesis that stochastic resonance can enhance the detection and transmission in sensorimotor system during a motor task. The purpose of the present study was to extend these findings in a simpler and controlled task. We explored whether a particular level of a mechanical Gaussian noise (0–15 Hz) applied on the index finger can improve the performance during compensation for a static force generated by a manipulandum. The finger position was displayed on a monitor as a small white point in the center of a gray circle. We considered a good performance when the subjects exhibited a low deviation from the center of this circle and when the performance had less variation over time. Several levels of mechanical noise were applied on the manipulandum. We compared the performance between zero noise (ZN), optimal noise (ON), and high noise (HN). In all subjects (8 of 8) the data disclosed an inverted U-like graph between the inverse of the mean variation in position and the input noise level. In other words, the mean variation was significantly smaller during ON than during ZN or HN. The findings suggest that the application of a tactile-proprioceptive noise can improve the stability in sensorimotor performance via stochastic resonance. Possible explanations for this improvement in motor precision are an increase of the peripheral receptors sensitivity and of the internal stochastic resonance, causing a better sensorimotor integration and an increase in corticomuscular synchronization.

Modulation of synaptic transmission from segmental afferents by spontaneous activity of dorsal horn spinal neurones in the cat

1 We examined, in the anaesthetised cat, the influence of the neuronal ensembles producing spontaneous negative cord dorsum potentials (nCDPs) on segmental pathways mediating primary afferent depolarisation (PAD) of cutaneous and group I muscle afferents and on Ia monosynaptic activation of spinal motoneurones. 2 The intraspinal distribution of the field potentials associated with the spontaneous nCDPs indicated that the neuronal ensembles involved in the generation of these potentials were located in the dorsal horn of lumbar segments, in the same region of termination of low‐threshold cutaneous afferents. 3 During the occurrence of spontaneous nCDPs, transmission from low‐threshold cutaneous afferents to second order neurones in laminae III‐VI, as well as transmission along pathways mediating PAD of cutaneous and Ib afferents, was facilitated. PAD of Ia afferents was instead inhibited. 4 Monosynaptic reflexes of flexors and extensors were facilitated during the spontaneous nCDPs. The magnitude of the facilitation was proportional to the amplitude of the ‘conditioning’ spontaneous nCDPs. This led to a high positive correlation between amplitude fluctuations of spontaneous nCDPs and fluctuations of monosynaptic reflexes. 5 Stimulation of low‐threshold cutaneous afferents transiently reduced the probability of occurrence of spontaneous nCDPs as well as the fluctuations of monosynaptic reflexes. 6 It is concluded that the spontaneous nCDPs were produced by the activation of a population of dorsal horn neurones that shared the same functional pathways and involved the same set of neurones as those responding monosynaptically to stimulation of large cutaneous afferents. The spontaneous activity of these neurones was probably the main cause of the fluctuations of the monosynaptic reflexes observed under anaesthesia and could provide a dynamic linkage between segmental sensory and motor pathways.

Propagation of Sinusoidal Electrical Waves along the Spinal Cord during a Fictive Motor Task

We present for the first time direct electrophysiological evidence of the phenomenon of traveling electrical waves produced by populations of interneurons within the spinal cord. We show that, during a fictive rhythmic motor task, scratching, an electrical field potential of spinal interneurons takes the shape of a sinuous wave, “sweeping” the lumbosacral spinal cord rostrocaudally with a mean speed of ∼0.3 m/s. We observed that traveling waves and scratching have the same cycle duration and that duration of the flexor phase, but not of the extensor phase, is highly correlated with the cycle duration of the traveling waves. Furthermore, we found that the interneurons from the deep dorsal horn and the intermediate nucleus can generate the spinal traveling waves, even in the absence of motoneuronal activity. These findings show that the sinusoidal field potentials generated during fictive scratching could be a powerful tool to disclose the organization of central pattern generator networks.

Sleep Deprivation and Oxidative Stress in Animal Models: A Systematic Review

Because the function and mechanisms of sleep are partially clear, here we applied a meta-analysis to address the issue whether sleep function includes antioxidative properties in mice and rats. Given the expansion of the knowledge in the sleep field, it is indeed ambitious to describe all mammals, or other animals, in which sleep shows an antioxidant function. However, in this paper we reviewed the current understanding from basic studies in two species to drive the hypothesis that sleep is a dynamic-resting state with antioxidative properties. We performed a systematic review of articles cited in Medline, Scopus, and Web of Science until March 2015 using the following search terms: Sleep or sleep deprivation and oxidative stress, lipid peroxidation, glutathione, nitric oxide, catalase or superoxide dismutase. We found a total of 266 studies. After inclusion and exclusion criteria, 44 articles were included, which are presented and discussed in this study. The complex relationship between sleep duration and oxidative stress is discussed. Further studies should consider molecular and genetic approaches to determine whether disrupted sleep promotes oxidative stress.

Analytical Modeling for the Bending Resonant Frequency of Sensors Based on Micro and Nanoresonators With Complex Structural Geometry

Micro- and nanoresonator sensors have important applications such as in chemical and biological sensing, environmental control, monitoring of viscosity and magnetic fields, and inertial forces detection. However, most of these resonators are designed as complex structures that complicate the estimation of their resonant frequencies (generally of the bending or torsional mode). In this paper, we present an analytical model to estimate the resonant frequency of the first bending mode of micro- and nanoresonators based on a beam system under different load types. This system is constructed of beams with different cross sections joined through a series-parallel arrangement. The analytical model is derived using the Rayleigh and Macaulay methods, as well as the Euler-Bernoulli beam theory. In addition, we determined the deflection function of the beam system, which can be used to establish its bending structural response under several load types. We applied the model to both a silicon microresonator (with a thickness of 5 μ m) for an experimental magnetic field sensor developed in our laboratory and for a polycrystalline silicon nanoresonator (with a thickness of 160 nm) of a mass sensor reported in the literature. The results of our analytical model have a comparable agreement with those obtained from the finite-element models (FEMs) and with the experimental measurements. Our analytical model can be useful in the mechanical design of micro- and nanoresonators with complex structural configurations.

Computing the center of mass for traveling alpha waves in the human brain.

The phenomenon of traveling waves of the brain is an intriguing area of research, and its mechanisms and neurobiological bases have been unknown since the 1950s. The present study offers a new method to compute traveling alpha waves using the center of mass algorithm. Electroencephalographic alpha waves are oscillations with a characteristic frequency range and reactivity to closed eyes. Several lines of evidence derived from qualitative observations suggest that the alpha waves represent a spreading wave process with specific trajectories in the human brain. We found that during a certain alpha wave peak recorded with 30 electrodes the trajectory starts and ends in distinct regions of the brain, mostly frontal-occipital, frontal-frontal, or occipital-frontal, but the position of the trajectory at the time in which the maximal positivity of the alpha wave occurs has a definite position near the central regions. Thus we observed that the trajectory always crossed around the central zones, traveling from one region to another region of the brain. A similar trajectory pattern was observed for different alpha wave peaks in one alpha burst, and in different subjects, with a mean velocity of 2.1+/-0.29 m/s. We found that all our results were clear and reproducible in all of the subjects. To our knowledge, the present method documents the first explicit description of a spreading wave process with a singular pattern in the human brain in terms of the center of mass algorithm.