Recent advances in optical neuroimaging systems as a functional interface enhance our understanding of neuronal activity in the brain. High density diffuse optical topography (HD-DOT) uses multi-distance overlapped channels to improve the spatial resolution of images comparable to functional magnetic resonance imaging (fMRI). The topology of the source and detector (SD) array directly impacts the quality of the hemodynamic reconstruction in HD-DOT imaging modality. In this work, the effect of different SD configurations on the quality of cerebral hemodynamic recovery is investigated by presenting a simulation setup based on the analytical approach. Given that the SD arrangement determines the elements of the Jacobian matrix, we conclude that the more individual components in this matrix, the better the retrieval quality. The results demonstrate that the multi-distance multi-directional (MDMD) arrangement produces more unique elements in the Jacobian array. Consequently, the inverse problem can accurately retrieve the brain activity of diffuse optical topography data.
Introduction: Drugs of abuse, including cocaine, affect different brain regions and lead to pathological memories. These abnormal memories may occur due to the changes in synaptic transmissions or variations in synaptic properties of neurons. It has been shown that cocaine inhibits delayed rectifying potassium currents in affected regions of the brain and can have a role in the formation of pathological memories. Purpose: This study investigates how the change in the conductance of delayed rectifying potassium channels can affect the produced action potentials using a computational model. Methods: We present a computational model with different channels and receptors, including sodium, potassium, calcium, NMDARs, and AMPARs, which can produce burst-type action potentials. In the simulations, by changing the delayed rectifying potassium conductance bifurcation diagram is calculated. Conclusion: Results show that for a specific range of potassium conductance, a chaotic regime emerges in produced action potentials. These chaotic oscillations may play a role in inducing abnormal memories.
Portable and wireless functional near-infrared spectroscopy is a growing field of research for real-time monitoring of brain functions. The most critical challenges in this field are the use of low-power and calibrated circuits. A novel transmitter architecture is proposed to overcome these barriers. This transmitter is low power, capable of being calibrated against process variation, and has a better phase noise and spurious-free dynamic range (SFDR) at the antenna. Besides that, the transmitter can be calibrated, which is not seen in similar research. In this transmitter, injection locking and frequency calibration lead to having an optimal and low-power circuit. The circuit is capable of transmitting data with BFSK and OOK modulations in the frequency band of the medical implant communication service (MICS). The transmitter is designed and simulated in a typical CMOS 0.18-μm technology with a 1-V power supply. The transmitter's power consumption is around 146 and 123 μW, equal to 5.92 nJ/bit and 246-630 pJ/bit for BFSK and OOK modulations, respectively. The signal's phase noise at the antenna is almost À109 dBc/Hz at 1-MHz frequency offset.
Introduction: Functional Near-Infrared Spectroscopy (fNIRS) is an imaging method in which light source and detector are installed on the head; consequently, re-emission of light from human skin contains information about cerebral hemodynamic alteration. The spatial probability distribution profile of photons penetrating tissue at a source spot, scattering into the tissue, and being released at an appropriate detector position, represents the spatial sensitivity. Method: Modeling light propagation in a human head is essential for quantitative near-infrared spectroscopy and optical imaging. The specific form of the distribution of light is obtained using the theory of perturbation. Analytical solution of the perturbative Diffusion Equation (DE) and Finite Element Method (FEM) in a Slab media (similar to the human head) makes it possible to study light propagation due to absorption and scattering of brain tissue. Results: The simulation result indicates that sensitivity is slowly decreasing in the deep area, and the sensitivity below the source and detector is the highest. The depth sensitivity and computation time of both Analytical and FEM methods are compared. The simulation time of the analytical approach is four orders of magnitude faster than the FEM. Conclusion: In this paper, an analytical solution and FEM methods performance when applied to the diffusion equation for heterogeneous media with a single spherical defect are compared. The depth sensitivity, along with the computation time of simulation, has been investigated for both methods. For simple and Slab-like human brain models, the analytical solution is the right candidate. Whenever the brain model is sophisticated, it is possible to use FEM methods, but it costs higher computation time.
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