A Teensy microcontroller-based interface for optical imaging camera control during behavioral experiments

Beta-frequency sensory stimulation enhances gait rhythmicity through strengthened coupling between striatal networks and stepping movement

Stepping movement is delta (1-4 Hz) rhythmic and depends on sensory inputs. In addition to delta rhythms, beta (10-30 Hz) frequency dynamics are also prominent in the motor circuits and are coupled to neuronal delta rhythms both at the network and the cellular levels. Since beta rhythms are broadly supported by cortical and subcortical sensorimotor circuits, we explore how beta-frequency sensory stimulation influences delta-rhythmic stepping movement, and dorsal striatal circuit regulation of stepping. We delivered audiovisual stimulation at 10 Hz or 145 Hz to mice voluntarily locomoting, while simultaneously recording stepping movement, striatal cellular calcium dynamics and local field potentials (LFPs). We found that 10 Hz, but not 145 Hz stimulation prominently entrained striatal LFPs. Even though sensory stimulation at both frequencies promoted locomotion and desynchronized striatal network, only 10 Hz stimulation enhanced the delta rhythmicity of stepping movement and strengthened the coupling between stepping and striatal LFP delta and beta oscillations. These results demonstrate that higher frequency sensory stimulation can modulate lower frequency dorsal striatal neural dynamics and improve stepping rhythmicity, highlighting the translational potential of non-invasive beta-frequency sensory stimulation for improving gait.

Printed circuit boards: system automation and alternative matrix for biosensing

Circuit integration has revolutionized the diagnostic sector by improving the sensing ability and rapidity of biosensors. Bioelectronics has led to the development of point-of-care (PoC) devices, offering superior performance compared with conventional biosensing systems. These devices have lower production costs, are smaller, and have greater reproducibility, enabling the construction of compact sensing modules. Flexible upgrades to the fabrication pattern of the printed circuit board (PCB) remains the most reliable and consistent means so far, offering portability, wearability, a lower detection limit, and smart output integration to these devices. This review summarizes the advances in PCB technology for biosensing devices for introducing automation and their emerging application as an alternative matrix material for detecting various analytes.

The autism spectrum disorder risk gene NEXMIF over-synchronizes hippocampal CA1 network and alters neuronal coding

Mutations in autism spectrum disorder (ASD) risk genes disrupt neural network dynamics that ultimately lead to abnormal behavior. To understand how ASD-risk genes influence neural circuit computation during behavior, we analyzed the hippocampal network by performing large-scale cellular calcium imaging from hundreds of individual CA1 neurons simultaneously in transgenic mice with total knockout of the X-linked ASD-risk gene NEXMIF (neurite extension and migration factor). As NEXMIF knockout in mice led to profound learning and memory deficits, we examined the CA1 network during voluntary locomotion, a fundamental component of spatial memory. We found that NEXMIF knockout does not alter the overall excitability of individual neurons but exaggerates movement-related neuronal responses. To quantify network functional connectivity changes, we applied closeness centrality analysis from graph theory to our large-scale calcium imaging datasets, in addition to using the conventional pairwise correlation analysis. Closeness centrality analysis considers both the number of connections and the connection strength between neurons within a network. We found that in wild-type mice the CA1 network desynchronizes during locomotion, consistent with increased network information coding during active behavior. Upon NEXMIF knockout, CA1 network is over-synchronized regardless of behavioral state and fails to desynchronize during locomotion, highlighting how perturbations in ASD-implicated genes create abnormal network synchronization that could contribute to ASD-related behaviors.

Development of a palm-sized bioelectronic sensing device for protein detection in milk samples

The present study relates a portable optical sensing device supported by a small single-board (SBC) computer. The electronic architectural avenue connects the SBC with a camera, LED lights and a monitor. A 'sensor integration unit' has been linked with the device where the biological reactions were performed and assessed based on the concentration-dependent optical signal outputs. This setup can detect the generation of colors and distinguish their changes in the RGB intensity scale with an accuracy of a single pixel unit. A predefined range of values was obtained and fed to the device that can quantitatively sense the molecule of interest on the sensing matrix. The device has a touchscreen interactive panel that allows users to manually set experimental conditions and connect the entire measurement process to the cloud storage for backup information. We have considered detecting Alkaline Phosphatase (ALP) quantitatively from standard solutions as well as in milk samples as a proof-of-concept protein molecule. The device has shown exceptional analytical performance for lower and higher concentration ranges (0-100 U/mL and 100-1000 U/mL) with correlation coefficient values of 0.99. The detection limit of ALP was determined to be 0.1 U/mL, and the average time of a sample assessment was recorded to be 15 s. The device has also been tested against ALP-spiked milk samples to check its effectiveness and commercial viability. The outcome of the real-time assessment was sensitive and efficient, indicating its direct commercial and clinical importance towards colorimetric detection for diverse macromolecules.

The TeensyTap Framework for Sensorimotor Synchronization Experiments

Synchronizing movements with an external periodic stimulus, such as tapping your foot along with a metronome, is a remarkable human skill called sensorimotor synchronization. A growing body of literature investigates this process, but experiments require collecting responses with high temporal reliability, which often requires specialized hardware. The current article presents and validates TeensyTap, an inexpensive, highly functional framework with excellent timing performance. The framework uses widely available, low-cost hardware and consists of custom-written open-source software and communication protocols. TeensyTap allows running complete experiments through a graphical user interface and can simultaneously present a pacing signal (metronome), measure movements using a force-sensitive resistor, and deliver auditory feedback, with optional experimenter-specified artificial feedback delays. Movement data is communicated to a computer and saved for offline analysis in a format that allows it to be easily imported into spreadsheet programs. The present work also reports a validation experiment showing that timing performance of TeensyTap is highly accurate, ranking it among the gold standard tools available in the field. Metronome pacing signals are presented with millisecond accuracy, feedback sounds are delivered on average 2 ms following the subjects' taps, and the timing log files produced by the device are unbiased and accurate to within a few milliseconds. The framework allows for a range of experimental questions to be addressed and, since it is open source and transparent, researchers with some technical expertise can easily adapt and extend it to accommodate a host of possible future experiments that have yet to be imagined.