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ABSTRACT: Laser Speckle Contrast Imaging (LSCI) is a wide field of view, non scanning optical technique for observing blood flow. Speckles are produced when coherent light scattered back from biological tissue is diffracted through the limiting aperture of focusing optics. Mobile scatterers cause the speckle pattern to blur; a model can be constructed by inversely relating the degree of blur, termed speckle contrast to the scatterer speed. In tissue, red blood cells are the main source of moving scatterers. Therefore, blood flow acts as a virtual contrast agent, outlining blood vessels. The spatial resolution (~ 10 ìm) and temporal resolution (10 ms to 10 s) of LSCI can be tailored to the application. Restricted by the penetration depth of light, LSCI can only visualize superficial blood flow. Additionally, due to its non scanning nature, LSCI is unable to provide depth resolved images. The simple setup and non-dependence on exogenous contrast agents have made LSCI a popular tool for studying vascular structure and blood flow dynamics. We discuss the theory and practice of LSCI and critically analyze its merit in major areas of application such as retinal imaging, imaging of skin perfusion as well as imaging of neurophysiology.
IEEE reviews in biomedical engineering. 01/2013;
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ABSTRACT: Laser speckle contrast imaging (LSCI) is a full field optical imaging technique, capable of imaging blood flow without the introduction of any exogenous dyes. Spatial and temporal resolution in LSCI images depend on how pixels are chosen from the raw image stack for contrast processing. However, all processing schemes are based on isotropic treatment of the spatial neighborhood about each pixel, restricting further improvement in spatiotemporal resolution and image quality. We present a novel spatiotemporal processing scheme for LSCI where the spatial neighborhood is anisotropic, that is, restricted along a specific direction that matches direction of blood flow. The technique allows for a significant increase in temporal resolution, from conventionally used 40 or 80 frames to just three frames; while simultaneously achieving 23% and 47% higher signal-to-noise ratios over concurrent spatiotemporal schemes, when imaging rapid and slow functional changes in blood flow, respectively. We present the concept, justification, and performance evaluation of the novel scheme and demonstrate its suitability for imaging rapid changes in blood flow. Anisotropic LSCI was able to monitor the heart rate associated fluctuations in intravascular blood flow and showed them to be as high as 28% of the mean.
IEEE transactions on bio-medical engineering 01/2012; 59(5):1272-80. · 2.15 Impact Factor
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ABSTRACT: Electrocorticographic (ECoG) signals have emerged as a prominent neural interface signal modality due to their high bandwidth and availability in human subjects. We present a system for wireless recording of micro-ECoG activity in a primate performing reach-to-grasp movements. The system is comprised of a head-mounted interface, off-the-shelf receiver module, and custom software written in Labview for real-time data monitoring and storage. The head-mounted interface is composed of a custom-designed VLSI neural recording front, a commercially available FSK transmitter module, a digital interface, and a battery. The system offers a fixed gain of 40 dB, programmable bandwidth settings in the 0.1 Hz to 8.2 kHz range, digital gain of 1-16, and ADC resolution of 8-12 bits. The interface consumes 6.7 mA of current from a 3.7 V battery and transmits digitized data at 1 Mbps rate. The system offers less than 0.25% dropped packets at 3m non-line-of-sight distance. We then used the wirelessly recorded ECoG signal from the dorsal premotor cortex region to decode the movement state of the animal. The ECoG spectral features could decode the movement state, achieving close to 70% accuracy as early as 100 ms prior to actual movement onset. Our system offers a new avenue for future ECoG-based brain-machine interface systems.
Biomedical Circuits and Systems Conference (BioCAS), 2011 IEEE; 12/2011
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ABSTRACT: The use of neural signals for prosthesis control is an emerging frontier of research to restore lost function to amputees and the paralyzed. Electrocorticography (ECoG) brain-machine interfaces (BMI) are an alternative to EEG and neural spiking and local field potential BMI approaches. Conventional ECoG BMIs rely on spectral analysis at specific electrode sites to extract signals for controlling prostheses. We compare traditional features with information about the connectivity of an ECoG electrode network. We use time-varying dynamic Bayesian networks (TV-DBN) to determine connectivity between ECoG channels in humans during a motor task. We show that, on average, TV-DBN connectivity decreases from baseline preceding movement and then becomes negative, indicating an alteration in the phase relationship between electrode pairs. In some subjects, this change occurs preceding and during movement, before changes in low or high frequency power. We tested TV-DBN output in a hand kinematic decoder and obtained an average correlation coefficient (r(2)) between actual and predicted joint angle of 0.40, and as high as 0.66 in one subject. This result compares favorably with spectral feature decoders, for which the average correlation coefficient was 0.13. This work introduces a new feature set based on connectivity and demonstrates its potential to improve ECoG BMI accuracy.
IEEE transactions on neural systems and rehabilitation engineering: a publication of the IEEE Engineering in Medicine and Biology Society 11/2011; 20(2):143-52. · 2.42 Impact Factor
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ABSTRACT: This paper uses an entropy based metric to study the somatosensory evoked potential (SEP) in rodents afflicted with focal demyelination spinal cord injury (SCI). It has been shown that amplitude characteristics of the SEP signal are a strong indicator of the integrity of the spinal cord sensory pathways. Compared to conventional correlation based metrics, the metric used in this paper exploits the amplitude histogram of SEP signals to provide a robust assessment of the different degrees of demyelination in the spinal cord. Results are presented using actual SEP signals collected on rodents with various levels of SCI.
Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE; 10/2010
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ABSTRACT: Imaging in awake, behaving animals is an emerging field that offers the advantage of being able to study physiological processes and structures in a more natural state than what is possible in tissue slices or even in anesthetized animals. To date, most imaging in awake animals has used optical fiber bundles or electrical cables to transfer signals to traditional imaging-system components. However, the fibers or cables tether the animal and greatly limit the kind and duration of animal behavior that can be studied using imaging methods. We present an integrated imaging microscope (IIM) that incorporates all aspects of an imaging system - illumination, optics and photodetection - into a small footprint device, occupying under 4 cm<sup>3</sup> and weighing 5.4 g, that can be attached to the skull for imaging the brain in mobile rats. Power supply and image storage sufficient for ~7 hour operation at 15 frames/s was implemented on a backpack weighing 11.5 g. We implemented several optical techniques including reflectance, spectroscopy, speckle and fluorescence with the IIM, imaged vessels down to 15-20 μm in diameter and obtained, to the best of our knowledge, the worlds first cortical images from an untethered, freely-moving rat.
Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE; 10/2010
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ABSTRACT: The intricate coupling between electrical and chemical activity in neural pathways of the central nervous system, and the implication of this coupling in neuropathologies, such as Parkinson's disease, motivates simultaneous monitoring of neurochemical and neuropotential signals. However, to date, neurochemical sensing has been lacking in integrated clinical instrumentation as well as in brain-computer interfaces (BCI). Here, we present an integrated system capable of continuous acquisition of data modalities in awake, behaving subjects. It features one channel each of a configurable neuropotential and a neurochemical acquisition system. The electrophysiological channel is comprised of a 40-dB gain, fully differential amplifier with tunable bandwidth from 140 Hz to 8.2 kHz. The amplifier offers input-referred noise below 2 mu V <sub>rms</sub> for all bandwidth settings. The neurochemical module features a picoampere sensitivity potentiostat with a dynamic range spanning six decades from picoamperes to microamperes. Both systems have independent on-chip, configurable DeltaSigma analog-to-digital converters (ADCs) with programmable digital gain and resolution. The system was also interfaced to a wireless power harvesting and telemetry module capable of powering up the circuits, providing clocks for ADC operation, and telemetering out the data at up to 32 kb/s over 3.5 cm with a bit-error rate of less than 10<sup>-5</sup>. Characterization and experimental results from the electrophysiological and neurochemical modules as well as the full system are presented.
IEEE Transactions on Biomedical Circuits and Systems 01/2010; · 2.03 Impact Factor
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ABSTRACT: The ability to observe functional and morphological changes in the brain is critical in understanding behavioral and developmental neuroscience. With advances in electronics and miniaturization, electrophysiological recordings from awake, behaving animals has allowed investigators to perform a multitude of behavioral studies by observing changes as an animal is engaged in certain tasks. Imaging offers advantages of observing structure as well as function, and the ability to monitor activity over large areas. However, imaging from an awake, behaving animal has not been explored well. We present the design and characterization of a miniaturized epi-illuminated optical system that is part of a larger goal to perform optical imaging in awake, behaving animals. The system comprises of a tunable light source and imaging optics in a small footprint of 18 mm diameter, 18 mm height and weight 5.7 grams. It offers a spatial illumination non-uniformity of 3.2% over a maximum field of view of 1.5 mm times 1.5 mm, negligible temporal illumination and temperature variation and controllable magnification. Uncorrected radial distortion was 5.3% (corrected to 1.8%) and the spatial frequency response was comparable to a reference system. The system was used to image cortical vasculature in an anesthetized rat.
Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE; 10/2009
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ABSTRACT: Cardiac arrest (CA) can produce complex changes in somatosensory evoked potentials (SSEPs). Somatosensory evoked potentials (SSEPs) indicate the intactness of somatosensory pathways and are commonly used for brain function monitoring during surgeries. Multiresolution biorthogonal wavelet analysis was applied to SSEPs recorded during established CA experiments and post-CA long-term recovery periods in rats. Our results showed that during the first 4 hours after CA, the amplitudes of SSEP, defined here as the difference between the amplitudes of P23 and N20, decreased greatly while the inter-peak latencies between N20 and P23 increased greatly. In the long-term recovery period (within 72 hours), both the amplitudes of SSEPs and the interpeak latencies returned to the baseline. Our results suggest that the changes of SSEPs may represent the post-CA neurological injuries and recovery in the somatosensory afferent pathways. The results here lay ground work for establishing the relationship between SSEPs and post-CA neurological injuries and functional outcomes as well as deploying SSEP in clinical settings to monitor patients resuscitated from CA in the future.
Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE; 10/2009
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ABSTRACT: While great advances have been made in optimizing fabrication process technologies for solid state image sensors, the need remains to be able to fabricate high quality photosensors in standard CMOS processes. The quality metrics depend on both the pixel architecture and the photosensitive structure. This paper presents a comparison of three photodiode structures in terms of spectral sensitivity, noise and dark current. The three structures are n<sup>+</sup>/p-sub, n-well/p-sub and p<sup>+</sup>/n-well/p-sub. All structures were fabricated in a 0.5 mum 3-metal, 2-poly, n-well process and shared the same pixel and readout architectures. Two pixel structures were fabricated-the standard three transistor active pixel sensor, where the output depends on the photodiode capacitance, and one incorporating an in-pixel capacitive transimpedance amplifier where the output is dependent only on a designed feedback capacitor. The n-well /p-sub diode performed best in terms of sensitivity (an improvement of 3.5 times and 1.6 times over the n<sup>+</sup>/p-sub and p<sup>+</sup>/n-well/p-sub diodes, respectively) and signal-to-noise ratio (1. 5times and 1.2 times improvement over the n<sup>+</sup>/p-sub and p<sup>+</sup>/n-well/p-sub diodes, respectively) while the p<sup>+</sup>/n-well/p-sub diode had the minimum (33% compared to other two structures) dark current for a given sensitivity.
IEEE Sensors Journal 08/2009; · 1.52 Impact Factor
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ABSTRACT: In this paper, spectral coherence (SC) is used to study the somatosensory evoked potential (SEP) signals in rodent model before and after spinal cord injury (SCI). The SC technique is complemented with the Basso, Beattie, and Bresnahan (BBB) behavior analysis method to help us assess the status of the motor recovery. SC can be used to follow the effects of SCI without any preinjury baseline information. In this study, adult female Fischer rats received contusion injury at T8 level with varying impact heights using the standard New York University impactor. The results show that the average SC between forelimb and hindlimb SEP signals before injury was relatively high ( > or =0.7). Following injury, the SC between the forelimb and hindlimb SEP signals dropped to various levels ( < or =0.7) corresponding to the severity of SCI. The SC analysis gave normalized quantifiable results for the evaluation of SCI and recovery thereafter using the forelimb signals as an effective control, without the need of any baseline data. This technique solves the problems associated with the commonly used time-domain analysis like the need of a trained neurophysiologist to interpret the data and the need for baseline data. We believe that both SC and BBB may provide a comprehensive and complementary picture of the health status of the spinal cord after injury. The presented method is applicable to SCIs not affecting the forelimb SEP signals.
IEEE transactions on bio-medical engineering 05/2009; 56(8):1971-9. · 2.15 Impact Factor
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ABSTRACT: Electrical activity in the brain spans a wide range of spatial and temporal scales, requiring simultaneous recording of multiple modalities of neurophysiological signals in order to capture various aspects of brain state dynamics. Here, we present a 16-channel neural interface integrated circuit fabricated in a 0.5 mum 3M2P CMOS process for selective digital acquisition of biopotentials across the spectrum of neural signal modalities in the brain, ranging from single spike action potentials to local field potentials (LFP), electrocorticograms (ECoG), and electroencephalograms (EEG). Each channel is composed of a tunable bandwidth, fixed gain front-end amplifier and a programmable gain/resolution continuous-time incremental DeltaSigma analog-to-digital converter (ADC). A two-stage topology for the front-end voltage amplifier with capacitive feedback offers independent tuning of the amplifier bandpass frequency corners, and attains a noise efficiency factor (NEF) of 2.9 at 8.2 kHz bandwidth for spike recording, and a NEF of 3.2 at 140 Hz bandwidth for EEG recording. The amplifier has a measured midband gain of 39.6 dB, frequency response from 0.2 Hz to 8.2 kHz, and an input-referred noise of 1.94 mu V <sub>rms</sub> while drawing 12.2 muA of current from a 3.3 V supply. The lower and higher cutoff frequencies of the bandpass filter are adjustable from 0.2 to 94 Hz and 140 Hz to 8.2 kHz, respectively. At 10-bit resolution, the ADC has an SNDR of 56 dB while consuming 76 muW power. Time-modulation feedback in the ADC offers programmable digital gain (1-4096) for auto-ranging, further improving the dynamic range and linearity of the ADC. Experimental recordings with the system show spike signals in rat somatosensory cortex as well as alpha EEG activity in a human subject.
IEEE Transactions on Biomedical Circuits and Systems 03/2009; · 2.03 Impact Factor
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ABSTRACT: Neurological complications after cardiac arrest (CA) can be fatal. Although hypothermia has been shown to be beneficial, understanding the mechanism and establishing neurological outcomes remains challenging because effects of CA and hypothermia are not well characterized. This paper aims to analyze EEG (and the alpha-rhythms) using multiscale entropy (MSE) to demonstrate the ability of MSE in tracking changes due to hypothermia and compare MSE during early recovery with long-term neurological examinations. Ten Wistar rats, upon post-CA resuscitation, were randomly subjected to hypothermia (32 degrees C-34 degrees C, N = 5) or normothermia (36.5 degrees C-37.5 degrees C, N = 5). EEG was recorded and analyzed using MSE during seven recovery phases for each experiment: baseline, CA, and five early recovery phases (R1-R5). Postresuscitation neurological examination was performed at 6, 24, 48, and 72 h to obtain neurological deficit scores (NDSs). Results showed MSE to be a sensitive marker of changes in alpha-rhythms. Significant difference (p < 0.05) was found between the MSE for two groups during recovery, suggesting that MSE can successfully reflect temperature modulation. A comparison of short-term MSE and long-term NDS suggested that MSE could be used for predicting favorability of long-term outcome. These experiments point to the role of cortical rhythms in reporting early neurological response to ischemia and therapeutic hypothermia.
IEEE transactions on bio-medical engineering 02/2009; 56(4):1023-31. · 2.15 Impact Factor
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ABSTRACT: We present an optimal method for decoding the activity of primary motor cortex (M1) neurons in a non-human primate during
finger movements. The method is based on the maximum likelihood (ML) inference. Each neuron’s activation is first quantified
by the change in firing rate before and after finger movement. We then estimate the probability density function of this activation
given finger movement. Based on the ML criterion, we choose finger movements to maximize the likelihood. With as few as 20–25
randomly selected neurons, the proposed method decoded single finger movements with 99% accuracy. Since the training and decoding
procedures in the proposed method are simple and computationally efficient, the method can be extended for real-time neuroprosthetic
control of a dexterous hand.
12/2008: pages 448-451;
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ABSTRACT: Implantable brain-machine interfaces for disease diagnosis and motor prostheses control require low-power acquisition of neuropotentials spanning a wide range of amplitudes and frequencies. Here, we present a 16-channel VLSI neuropotential acquisition system with tunable gain and bandwidth, and variable rate digital transmission over an inductive link which further supplies power. The neuropotential interface chip is composed of an amplifier, incremental ADC and bit-serial readout circuitry. The front-end amplifier has a midband gain of 40 dB and offers NEF of less than 3 for all bandwidth settings. It also features adjustable low-frequency cut-off from 0.2 to 94 Hz, and independent high-frequency cut-off from 140 Hz to 8.2 kHz. The Gm-C incremental DeltaSigma ADC offers digital gain up to 4096 and 8-12 bits resolution. The interface circuit is powered by a telemetry chip which harvests power through inductive coupling from a 4 MHz link, provides a 1 MHz clock for ADC operation and transmits the bit-serial data of the neurpotential interface across 4 cm at up to 32 kbps with a BER less than 10<sup>-5</sup>. Experimental EEG recordings using the neuropotential interface and wireless module are presented.
Biomedical Circuits and Systems Conference, 2008. BioCAS 2008. IEEE; 12/2008
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ABSTRACT: In this paper, the derivative of the instantaneous phase of electroencephalographic (EEG) signals is used as a basis for monitoring of global cerebral ischemia. Visual and quantitative results were obtained from six rodents that were subject to 3, 5 and 7 minutes of global ischemic brain injury by asphyxic cardiac arrest. Results show that the variations in the instantaneous phase are capable of amplifying the variations during the various stages of the recovery process and may serve as a novel analytical approach to grade and classify brain rhythms during global ischemic brain injury and recovery.
Conference proceedings: ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference 02/2008; 2008:4182-5.
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ABSTRACT: Graded spinal cord injury was induced in rats using the NY-Impactor. Somatosensory evoked potentials (SEPs), in response to stimuli to the nerves in the limbs, were recorded from the cranium. These signals were analyzed using spectral coherence analysis. Results obtained from 15 rats show information that was missed when other techniques are used.
Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE; 09/2007
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ABSTRACT: In neuroprosthetic systems, decoding based on a sparse population of task-related neurons is impractical because micro-electrode arrays often drift gradually in the cortex. Since the neuronal population being recorded from is dynamic, it is favorable to have a larger number of neurons containing information relevant to movement decoding and to decrease the relative importance of individual neurons. We have shown that a feature space comprised of neural firing rates from planning as well as movement periods exists in a broader distribution of neurons, as compared to a feature space that is derived from the movement period alone. For this study, spike train data from 297 neurons located in Ml and PM areas was analyzed to validate the hypothesis. The data was from a rhesus monkey performing reach to grasp task with measured wrist supination/pronation. Artificial neural networks were used to model encoding of wrist angle, and a sensitivity analysis was performed to attribute the relative importance of the input neurons. A classifier trained on only the least important neurons, as determined by their relative contribution to the decoded variable, had an average 20% better decoding accuracy when the new method of feature selection was used. This indicates that there is valuable information content within the distributed neuronal population.
Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE; 09/2007
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ABSTRACT: High-resolution cerebral vasculature imaging has applications ranging from intraoperative procedures to basic neuroscience research. Laser speckle, with spatial contrast processing, has recently been used to map cerebral blood flow. We present an application of the technique using temporal contrast processing to image cerebral vascular structures with a field of view a few millimeters across and approximately 20 microm resolution through a thinned skull. We validate the images using fluorescent imaging and demonstrate a factor of 2-4 enhancement in contrast-to-noise ratios over reflectance imaging using white or spectrally filtered green light. The contrast enhancement enables the perception of approximately 10%-30% more vascular structures without the introduction of any contrast agent.
Applied Optics 09/2007; 46(22):5340-6. · 1.41 Impact Factor
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ABSTRACT: Non invasive brain-computer interfaces (BCI) allow people to communicate by modulating features of their electroencephalogram (EEG). Spatiotemporal filtering has a vital role in multi-class, EEG based BCI. In this study, we used a novel combination of principle component analysis, independent component analysis and dipole source localization to design a spatiotemporal multiple source tuning (SPAMSORT) filter bank, each channel of which was tuned to the activity of an underlying dipole source. Changes in the event-related spectral perturbation (ERSP) were measured and used to train a linear support vector machine to classify between four classes of motor imagery tasks (left hand, right hand, foot and tongue) for one subject. ERSP values were significantly (p<0.01) different across tasks and better (p<0.01) than conventional spatial filtering methods (large Laplacian and common average reference). Classification resulted in an average accuracy of 82.5%. This approach could lead to promising BCI applications such as control of a prosthesis with multiple degrees of freedom
Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE; 10/2006
