KEYWORDS: Neuroimaging, Tomography, Digital signal processing, Analog electronics, Signal processing, Signal to noise ratio, Digital electronics, Data acquisition, Brain, Visualization
Functional neuroimaging techniques are becoming mandatory tools for neuroscience research and brain disorders medical therapy, respectively. Electrical Impedance Tomography (EIT) has been impressed neuroscientists for its advantages of fast, radiation-free, and low-cost brain visualization method. Implementation of EIT on neuroimaging requires high performance data acquisition system which significantly depends on analog and digital electronic circuitry to achieve high and improve signal to noise ratio (SNR). A proposed EIT system based on high performance digital signal processor (DSP) has been successfully designed and developed for first prototype. A precise data acquisition unit that provides 24-bit 16 channels simultaneously sampling up to 100ksps was integrated into the system alongside with stable and biocompatible stimulation analog current source. Simulation of analog circuitry was constructed using PSPICE software. The proposed EIT system was designed using Cadence PCB Editor software to acquire compact integration requirements with all EIT components on a single circuit board. Evaluation of the proposed EIT system was conducted in a neural simulated environment phantom experiment. With this proposed system, EIT study on neural activity recording and neuroimaging has potentials to accelerate both in speed and performance to approach real-time imaging.
Measuring and analyzing local field potential (LFP) signals from basolateral amygdala (BLA), hippocampus (HPC) and medial prefrontal cortex (mPFC) may help understand how they communicate with each other during fear memory formation and extinction. In our research, we have formulated a computationally simple and noise immune instantaneous amplitude cross correlation technique which can deduce lead and lag of LFPs generated in BLA, HPC, and mPFC and the directionality of brain signals exchanged between regions. LFP signals are recorded using depth electrodes in the rat brain and cross correlation analysis is applied to theta wave signals after filtering. We found that rats resilient to traumatic conditions (based on post-stress rapid eye movement sleep (REM)) showed a decrease in LFP signal correlation in REM and non-REM (NREM) sleep cycles between BLA-HPC regions after shock training and one day post shock training compared to vulnerable rats that show stress-induced reductions in REM. It is presumed this difference in neural network behavior may be related to REM sleep differences between resilient and vulnerable rats and may provide clues to help understand how traumatic conditions are processed by the brain.
KEYWORDS: Algorithm development, Tomography, Reconstruction algorithms, Signal processing, Switching, Surgery, Signal to noise ratio, Neurological disorders, Multiplexers, Medical devices
Electrical impedance tomography (EIT) is a rising and emerging imaging technique with great potential in many areas, especially in functional brain imaging applications. An EIT system with high speed and accuracy can have many applications to medical devices supporting in diagnosis and treatment of neurological disorders and diseases. In this research, EIT algorithms and hardware are developed and improved to increase reconstructed images' accuracy and decrease the reconstruction time. Due to multiplexer design limitations, EIT measurements are subject to strong capacitive effects from charging and discharging in switching cycles around 300 to 400 samples per 1280 samples (in 10 milliseconds sampling). We developed an algorithm to choose data in steady-state condition only selectively. This method improves the signal-to-noise ratio and results in better reconstruction images. An algorithm to effectively synchronize the beginning points of data was developed to increase the system's speed. This presentation also presents the EIT system's hardware architecture based on Texas Instruments Fixed-Point Digital Signal Processor - TMS320VC5509A, which is low-cost, high potential in popularity the community in the future. For high operation speed, we propose the EIT system used Sitara™ AM57x processors of Texas Instruments.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.