Securing Implantable Medical Devices Using Ultrasound Waves

Modern Implantable Medical Devices (IMDs) are vulnerable to security attacks because of their wireless connectivity to the outside world. One of the main security challenges is establishing trust between the IMD and an external reader/programmer in order to facilitate secure communication. Numerous device-pairing schemes have been proposed to address this specific challenge. However, they alone cannot protect against a battery-depletion attack in which the adversary is able to keep the IMD occupied with continuous authentication requests until the battery empties. As a result, energy harvesting has been employed as an ancillary mechanism for implementing Zero-Power Defense (ZPD) functionality in order to protect against such a low-cost attack. In this paper, we propose SecureEcho, a device-pairing scheme based on MHz-range ultrasound that establishes trust between the IMD and an external reader. In addition, SecureEcho achieves ZPD without requiring any energy harvesting, which significantly reduces the design complexity. We also provide a proof-of-concept implementation and a first ever security evaluation of the ultrasound channel, which proves that it is infeasible for the attacker to eavesdrop or insert messages even from a range of a few millimeters.Quantum & Computer EngineeringComputer EngineeringElectronicsBio-Electronic

WhiskEras: A New Algorithm for Accurate Whisker Tracking

Rodents engage in active touch using their facial whiskers: they explore their environment by making rapid back-and-forth movements. The fast nature of whisker movements, during which whiskers often cross each other, makes it notoriously difficult to track individual whiskers of the intact whisker field. We present here a novel algorithm, WhiskEras, for tracking of whisker movements in high-speed videos of untrimmed mice, without requiring labeled data. WhiskEras consists of a pipeline of image-processing steps: first, the points that form the whisker centerlines are detected with sub-pixel accuracy. Then, these points are clustered in order to distinguish individual whiskers. Subsequently, the whiskers are parameterized so that a single whisker can be described by four parameters. The last step consists of tracking individual whiskers over time. We describe that WhiskEras performs better than other whisker-tracking algorithms on several metrics. On our four video segments, WhiskEras detected more whiskers per frame than the Biotact Whisker Tracking Tool. The signal-to-noise ratio of the output of WhiskEras was higher than that of Janelia Whisk. As a result, the correlation between reflexive whisker movements and cerebellar Purkinje cell activity appeared to be stronger than previously found using other tracking algorithms. We conclude that WhiskEras facilitates the study of sensorimotor integration by markedly improving the accuracy of whisker tracking in untrimmed mice.Computer EngineeringBio-Electronic

Swept-3-D Ultrasound Imaging of the Mouse Brain Using a Continuously Moving 1-D-Array - Part II: Functional Imaging

Functional ultrasound (fUS) using a 1-D-array transducer normally is insufficient to capture volumetric functional activity due to being restricted to imaging a single brain slice at a time. Typically, for volumetric fUS, functional recordings are repeated many times as the transducer is moved to a new location after each recording, resulting in a nonunique average mapping of the brain response and long scan times. Our objective was to perform volumetric 3-D fUS in an efficient and cost-effective manner. This was achieved by mounting a 1-D-array transducer to a high-precision motorized linear stage and continuously translating over the mouse brain in a sweeping manner. We show how the speed at which the 1-D-array is translated over the brain affects the sampling of the hemodynamic response (HR) during visual stimulation as well as the quality of the resulting power Doppler image (PDI). Functional activation maps were compared between stationary recordings, where only one functional slice is obtained for every recording, and our swept-3-D method, where volumetric fUS was achieved in a single functional recording. The results show that the activation maps obtained with our method closely resemble those obtained during a stationary recording for that same location, while our method is not restricted to functional imaging of a single slice. Lastly, a mouse brain subvolume of 6 mm is scanned at a volume rate of 1.5 s per volume, with a functional PDI reconstructed every 200\mu \text{m} , highlighting swept-3-D's potential for volumetric fUS. Our method provides an affordable alternative to volumetric fUS using 2-D-matrix transducers, with a high SNR due to using a fully sampled 1-D-array transducer, and without the need to repeat functional measurements for every 2-D slice, as is most often the case when using a 1-D-array. This places our swept-3-D method as a potentially valuable addition to conventional 2-D fUS, especially when investigating whole-brain functional connectivity, or when shorter recording durations are desired.Signal Processing System

BrainFrame: A node-level heterogeneous accelerator platform for neuron simulations

Objective. The advent of high-performance computing (HPC) in recent years has led to its increasing use in brain studies through computational models. The scale and complexity of such models are constantly increasing, leading to challenging computational requirements. Even though modern HPC platforms can often deal with such challenges, the vast diversity of the modeling field does not permit for a homogeneous acceleration platform to effectively address the complete array of modeling requirements. Approach. In this paper we propose and build BrainFrame, a heterogeneous acceleration platform that incorporates three distinct acceleration technologies, an Intel Xeon-Phi CPU, a NVidia GP-GPU and a Maxeler Dataflow Engine. The PyNN software framework is also integrated into the platform. As a challenging proof of concept, we analyze the performance of BrainFrame on different experiment instances of a state-of-the-art neuron model, representing the inferior-olivary nucleus using a biophysically-meaningful, extended Hodgkin-Huxley representation. The model instances take into account not only the neuronal-network dimensions but also different network-connectivity densities, which can drastically affect the workload's performance characteristics. Main results. The combined use of different HPC technologies demonstrates that BrainFrame is better able to cope with the modeling diversity encountered in realistic experiments while at the same time running on significantly lower energy budgets. Our performance analysis clearly shows that the model directly affects performance and all three technologies are required to cope with all the model use cases. Significance. The BrainFrame framework is designed to transparently configure and select the appropriate back-end accelerator technology for use per simulation run. The PyNN integration provides a familiar bridge to the vast number of models already available. Additionally, it gives a clear roadmap for extending the platform support beyond the proof of concept, with improved usability and directly useful features to the computational-neuroscience community, paving the way for wider adoption.Computer Engineerin

NINscope, a versatile miniscope for multi-region circuit investigations

Miniaturized fluorescence microscopes (miniscopes) have been instrumental to monitor neural signals during unrestrained behavior and their open-source versions have made them affordable. Often, the footprint and weight of open-source miniscopes is sacrificed for added functionality. Here, we present NINscope: a light-weight miniscope with a small footprint that integrates a high-sensitivity image sensor, an inertial measurement unit and an LED driver for an external optogenetic probe. We use it to perform the first concurrent cellular resolution recordings from cerebellum and cerebral cortex in unrestrained mice, demonstrate its optogenetic stimulation capabilities to examine cerebello-cerebral or cortico-striatal connectivity, and replicate findings of action encoding in dorsal striatum. In combination with cross-platform acquisition and control software, our miniscope is a versatile addition to the expanding tool chest of open-source miniscopes that will increase access to multi-region circuit investigations during unrestrained behavior.Education and Student Affair

Four-dimensional computational ultrasound imaging of brain hemodynamics

Four-dimensional ultrasound imaging of complex biological systems such as the brain is technically challenging because of the spatiotemporal sampling requirements. We present computational ultrasound imaging (cUSi), an imaging method that uses complex ultrasound fields that can be generated with simple hardware and a physical wave prediction model to alleviate the sampling constraints. cUSi allows for high-resolution four-dimensional imaging of brain hemodynamics in awake and anesthetized mice.Computer EngineeringSignal Processing System

Purkinje Cell Activity Resonation Generates Rhythmic Behaviors at the Preferred Frequency of 8 Hz

Neural activity exhibits oscillations, bursts, and resonance, enhancing responsiveness at preferential frequencies. For example, theta-frequency bursting and resonance in granule cells facilitate synaptic transmission and plasticity mechanisms at the input stage of the cerebellar cortex. However, whether theta-frequency bursting of Purkinje cells is involved in generating rhythmic behavior has remained neglected. We recorded and optogenetically modulated the simple and complex spike activity of Purkinje cells while monitoring whisker movements with a high-speed camera of awake, head-fixed mice. During spontaneous whisking, both simple spike activity and whisker movement exhibit peaks within the theta band. Eliciting either simple or complex spikes at frequencies ranging from 0.5 to 28 Hz, we found that 8 Hz is the preferred frequency around which the largest movement is induced. Interestingly, oscillatory whisker movements at 8 Hz were also generated when simple spike bursting was induced at 2 and 4 Hz, but never via climbing fiber stimulation. These results indicate that 8 Hz is the resonant frequency at which the cerebellar-whisker circuitry produces rhythmic whisking.Computer EngineeringBio-Electronic