Detection Of Neuronal Signals Research Articles

Enhancement of weak signal detection in the Hodgkin–Huxley neuron subjected to electromagnetic fluctuation

Nervous cells are inevitably more or less exposed in a noisy electromagnetic environment. Therefore, how to detect weak target signal in noisy electromagnetic environment is an interesting and urgent problem in neuroscience. However, effects of stochastic electromagnetic fluctuation in neuronal signal detection have never been studied in detail. Based on an improved Hodgkin–Huxley (HH) neuron model subjected to electromagnetic fluctuation modeled with sine-Wiener bounded noise, the responses of HH neuron to sub-threshold periodic input signal are investigated by calculating the Fourier coefficient Q for measuring efficacy of neuronal weak signal detection. Numerical simulations reveal magnetic flux noise-induced enhancement of weak signal detection. Furthermore, magnetic flux noise-induced multi-resonance may imply the enhancement of complex electromagnetic environmental adaptability of neurons. Additionally, the results obtained also imply that too strength electromagnetic radiation may impair the capacity of neuron in response to external stimuli. However, magnetic flux noise with appropriate strength can partly recover the impaired efficacy.

A Magnetically Assembled High-Aspect-Ratio Needle Electrode for Recording Neuronal Activity.

Microelectrode devices, which enable the detection of neuronal signals in brain tissues, have made significant contributions in the field of neuroscience and the brain-machine interfaces. To further develop such microelectrode devices, the following requirements must be met: i) a fine needle's diameter (<30µm) to reduce damage to tissues; ii) a long needle (e.g., ≈1 mm for rodents and ≈2 mm for macaques); and iii) multiple electrodes to achieve high spatial recording (<100 µm in pitch). In order to meet these requirements, this study herein reports an assembly technique for high-aspect-ratio microneedles, which employs a magnet. The assembly is demonstrated, in which nickel wires of length 750 µm and diameter 25 µm are produced on a silicon substrate. The impedance magnitude of the assembled needle-like electrode measured at 1 kHz is 5.6 kΩ, exhibiting output and input signal amplitudes of 96.7% at 1 kHz. To confirm the recording capability of the fabricated device, neuronal signal recordings are performed using mouse cerebra in vivo. The packaged single microneedle electrode penetrates the barrel field in the primary somatosensory cortex of the mouse and enables the detection of evoked neuronal activity of both local field potentials and action potentials.

Biocompatibility of a Magnetic Tunnel Junction Sensor Array for the Detection of Neuronal Signals in Culture.

Magnetoencephalography has been established nowadays as a crucial in vivo technique for clinical and diagnostic applications due to its unprecedented spatial and temporal resolution and its non-invasive methods. However, the innate nature of the biomagnetic signals derived from active biological tissue is still largely unknown. One alternative possibility for in vitro analysis is the use of magnetic sensor arrays based on Magnetoresistance. However, these sensors have never been used to perform long-term in vitro studies mainly due to critical biocompatibility issues with neurons in culture. In this study, we present the first biomagnetic chip based on magnetic tunnel junction (MTJ) technology for cell culture studies and show the biocompatibility of these sensors. We obtained a full biocompatibility of the system through the planarization of the sensors and the use of a three-layer capping of SiO2/Si3N4/SiO2. We grew primary neurons up to 20 days on the top of our devices and obtained proper functionality and viability of the overlying neuronal networks. At the same time, MTJ sensors kept their performances unchanged for several weeks in contact with neurons and neuronal medium. These results pave the way to the development of high performing biomagnetic sensing technology for the electrophysiology of in vitro systems, in analogy with Multi Electrode Arrays.

Research on the synchronous detection of neuronal signals under a nerve stimulation system control.

Deep brain stimulation (DBS) provides a recognized research intervention for neurological disease currently. However, there is a lack of traditional electrical stimulator to observe neuronal firing activity synchronously. The aim of the present study was to realize concurrent detection of neuronal signals better under a nerve stimulation system control. Herein, we designed an integrated software, which could control not only neuro-stimulator but also detection instrument at the same time. Moreover, the actual stimulation signals applied to the experiment object could be collected back to data acquisition card and in consistent with the electrophysiological signals. As to basic performance of self-building stimulator, the accuracy of output square signal was verified to be greater than 99.05 % with the change of voltage amplitude. Practicably, combined with homemade microelectrode array (MEA) detecting device, medial forebrain bundle (MFB) DBS effects were observed significantly through the changes of electrophysiological signals in caudate putamen (CPu) of Sprague-Dawley (SD) rat, and the signal-to-noise ratio (SNR) was 5:1 after stimulation. Therefore, the comprehensive nerve stimulation system, which consists of neuro-stimulator and integrated software, could be widely used in the field of neuroscience research with high precision and synchronization.

Stochastic resonance induced by exogenous noise in a model of a neuronal network

This study investigates the possibility of using exogenous noise to restore the processing performances of neuronal systems where the endogenous noise is reduced due to the ageing or to degenerative diseases. This idea is based on the assumption, supported by theoretical studies, that the endogenous noise has a positive role in neuronal signal detection and that its reduction impairs the system function. Results, obtained on a two-layers feedforward network, show the onset of the Stochastic Resonance (SR) behavior, as long as the exogenous noise is properly tailored and filtered. The amount of noise to be furnished from the outside to optimize the system performance depends on the residual level of endogenous noise, indicating that both kinds of noise cooperate to the signal detection. These results support potentially new bioengineering applications where exogenous noise is furnished to enhance signal detectability.

Flavopiridol reduces the impedance of neural prostheses in vivo without affecting recording quality

We hypothesized that re-entry into the cell cycle may be associated with reactive gliosis surrounding neural prostheses, and that administration of a cell cycle inhibitor (flavopiridol) at the time of surgery would reduce this effect. We investigated the effects of flavopiridol on recording quality and impedance over a 28-day time period and conducted histology at 3 and 28 days post-implantation. Flavopiridol reduced the expression of a cell cycle protein (cyclin D1) in microglia surrounding probes at the 3-day time point. Impedance at 1kHz was decreased by drug administration across the study period compared to vehicle controls. Correlations between recording (SNR, units) and impedance metrics revealed a small, but statistically significant, inverse relationship between these variables. However, the relationship between impedance and recording quality was not sufficiently strong for flavopiridol to result in an improvement in SNR or the number of units detected. Our data indicate that flavopiridol is an effective, easily administered treatment for reducing impedance in vivo, potentially through inhibiting microglial encapsulation of implanted devices. This strategy may be useful in stimulation applications, where reduced impedance is desirable for achieving activation thresholds and prolonging the lifetime of the implanted power supply. While improvements in recording quality were not observed, a combination of flavopiridol with a second strategy which enhances neuronal signal detection may enhance these results in future studies.

Stochastic Resonance in Continuous and Spiking Neuron Models With Levy Noise

Levy noise can help neurons detect faint or subthreshold signals. Levy noise extends standard Brownian noise to many types of impulsive jump-noise processes found in real and model neurons as well as in models of finance and other random phenomena. Two new theorems and the ItO calculus show that white Levy noise will benefit subthreshold neuronal signal detection if the noise process's scaled drift velocity falls inside an interval that depends on the threshold values. These results generalize earlier "forbidden interval" theorems of neuronal "stochastic resonance" (SR) or noise-injection benefits. Global and local Lipschitz conditions imply that additive white Levy noise can increase the mutual information or bit count of several feedback neuron models that obey a general stochastic differential equation (SDE). Simulation results show that the same noise benefits still occur for some infinite-variance stable Levy noise processes even though the theorems themselves apply only to finite-variance Levy noise. The proves the two ItO-theoretic lemmas that underlie the new Levy noise-benefit theorems.

Dynamics of cortical neurovascular coupling analyzed by simultaneous DC-magnetoencephalography and time-resolved near-infrared spectroscopy

Functional magnetic resonance imaging (fMRI) visualizes activated brain areas with a high spatial resolution. The activation signal is determined by the local change of cerebral blood oxygenation, blood volume and blood flow which serve as surrogate marker for the neuronal signal itself. Here, the complex coupling between these parameters and the electrophysiologic activity is characterized non-invasively in humans during a simple motor task using simultaneously DC-magnetoencephalography (DC-MEG), for the detection of neuronal signals, and time-resolved near-infrared spectroscopy (trNIRS), for cortical metabolic/vascular responses: over the left primary motor cortex hand area of healthy subjects DC-fields and trNIRS parameters followed closely the 30 s motor task cycles, i.e., finger movements of the right hand alternating with rest. In subjects showing a sufficient signal-to-noise ratio the analysis of variance of photon time of flight proved that the task-related trNIRS changes originated from the cortex. While onset and relaxation started simultaneously, trNIRS signals reached 50% of the maximum level 1–4 s later than the DC-MEG-signals. The non-invasive ‘dual’ setup helps to characterize simultaneously the two complementary aspects of the ‘hemodynamic inverse problem’, i.e., the coupling of neuronal and vascular/metabolic signals, in healthy subjects and provides a new analysis perspective for pathophysiological coupling concepts in diverse diseases, e.g., in stroke, hypertension and Alzheimer’s disease.

Measurement of brain activity by near-infrared light

We review our most recent results on near-IR studies of human brain activity, which have been evolving in two directions: detection of neuronal signals and measurements of functional hemodynamics. We discuss results obtained so far, describing in detail the techniques we developed for detecting neuronal activity, and presenting results of a study that, as we believe, confirms the feasibility of neuronal signal detection. We review our results on near-IR measurements of cerebral hemodynamics, which are performed simultaneously with functional magnetic resonance imaging (MRI) These results confirm the cerebral origin of hemodynamic signals measured by optical techniques on the surface of the head. We also show how near-IR methods can be used to study the underlying physiology of functional MRI signals.