A Comparison of Head Movement Classification Methods.

To understand human behavior, it is essential to study it in the context of natural movement in immersive, three-dimensional environments. Virtual reality (VR), with head-mounted displays, offers an unprecedented compromise between ecological validity and experimental control. However, such technological advancements mean that new data streams will become more widely available, and therefore, a need arises to standardize methodologies by which these streams are analyzed. One such data stream is that of head position and rotation tracking, now made easily available from head-mounted systems. The current study presents five candidate algorithms of varying complexity for classifying head movements. Each algorithm is compared against human rater classifications and graded based on the overall agreement as well as biases in metrics such as movement onset/offset time and movement amplitude. Finally, we conclude this article by offering recommendations for the best practices and considerations for VR researchers looking to incorporate head movement analysis in their future studies.

Hardware Implementation of an Adaptive Data Acquisition System for Real-World EEG.

Collecting EEG involves digitizing a very small signal across a vast potential dynamic range, particularly within real-world neuroimaging conditions, where noise can be especially prominent. Conventional methods require highresolution, power-hungry data acquisition systems (DAQs), creating limits on usable time before manual interaction is necessary for recharge. Here, we discuss continued work on an alternative DAQ approach capable of acquiring high resolution data with ultra-low power use by adjusting parameters of the analog front end (AFE) in real time to allow use of low-resolution ADCs. This work compares signal quality of a hardware implementation of our adaptive AFE DAQ to that of an industry standard DAQ. Results demonstrate successful reconstruction of signals in both clean and noisy EEG monitoring environments at low bit-depths while maintaining high correlation and low standard deviation of error. This suggests promise for a fully integrated implementation with substantially lower power consumption.

The effect of micro-ECoG substrate footprint on the meningeal tissue response.

OBJECTIVE: There is great interest in designing implantable neural electrode arrays that maximize function while minimizing tissue effects and damage. Although it has been shown that substrate geometry plays a key role in the tissue response to intracortically implanted, penetrating neural interfaces, there has been minimal investigation into the effect of substrate footprint on the tissue response to surface electrode arrays. This study investigates the effect of micro-electrocorticography (micro-ECoG) device geometry on the longitudinal tissue response. APPROACH: The meningeal tissue response to two micro-ECoG devices with differing geometries was evaluated. The first device had each electrode site and trace individually insulated, with open regions in between, while the second device had a solid substrate, in which all 16 electrode sites were embedded in a continuous insulating sheet. These devices were implanted bilaterally in rats, beneath cranial windows, through which the meningeal tissue response was monitored for one month after implantation. Electrode site impedance spectra were also monitored during the implantation period. MAIN RESULTS: It was observed that collagenous scar tissue formed around both types of devices. However, the distribution of the tissue growth was different between the two array designs. The mesh devices experienced thick tissue growth between the device and the cranial window, and minimal tissue growth between the device and the brain, while the solid device showed the opposite effect, with thick tissue forming between the brain and the electrode sites. SIGNIFICANCE: These data suggest that an open architecture device would be more ideal for neural recording applications, in which a low impedance path from the brain to the electrode sites is critical for maximum recording quality.

A chronic window imaging device for the investigation of in vivo peripheral nerves.

Chronic imaging of the peripheral nervous system with contemporary techniques requires repetitive surgical procedures to reopen an area of interest in order to see underlying biological processes over time. The recurrence of surgical openings on an animal increases trauma, stress, and risk of infection. Such effects can greatly lessen the physiological relevance of any data recorded in this manner. In order to bypass repetitive surgery, a Peripheral Nerve Window (PNW) device has been created for chronic in vivo imaging purposes. Intravital imaging window devices have been used previously to image parts of the rodent model such as the brain, spinal cord, and mammary tissue, but currently have not been used in the peripheral nervous system because of lack of bone anchoring and access to deep nerve tissue. We demonstrate a novel surgical technique in a rat which transposes the sciatic nerve above the surrounding muscle tissue allowing the PNW access to an 8mm section of the nerve. Subsequent days of observation revealed increased vasculature development primarily around the nerve, showing that this preparation can be used to image nerve tissue and surrounding vasculature for up to one week post-implantation.