During locomotion, the coordinated activity of dozens of muscles shapes the kinematic features of each stride, including systematic changes in limb movement across walking speed. Motor units, each of which consists of a single motor neuron and the muscle fibers it innervates, contribute to the total activation of each muscle through their recruitment and firing rate when active. However, it remains unknown how the nervous system controls locomotor speed by changing the firing of individual motor units. To address this, we combined quantitative behavioral analysis of mouse locomotion with single motor unit recordings from the lateral and long heads of the triceps brachii, which drive monoarticular extension of the elbow and biarticular movements of the elbow and shoulder, respectively. In contrast to prior studies employing bulk EMG to examine muscle activity, our recordings revealed the diversity of spike patterning across motor units as well as systematic differences in motor unit activity across muscles and locomotor speeds. First, motor unit activity differed significantly across the lateral and long heads, suggesting differential control of these two closely apposed elbow extensor muscles. Second, we found that individual units were recruited probabilistically (during only a subset of strides), showing that the highly repeatable bulk EMG signals observed across strides in fact reflect stochastically varying subsets of individual motor units. Finally, although recruitment probability and firing rate both increased at faster walking speeds, increases in recruitment were proportionally larger than rate changes, and recruitment of individual units accompanied changes in limb kinematics. Together, these results reveal how the firing of individual motor units varies systematically across muscles and walking speeds to produce flexible locomotor behavior.

Neurons coordinate their activity to produce an astonishing variety of motor behaviors. Our present understanding of motor control has grown rapidly thanks to new methods for recording and analyzing populations of many individual neurons over time. In contrast, current methods for recording the nervous system’s actual motor output – the activation of muscle fibers by motor neurons – typically cannot detect the individual electrical events produced by muscle fibers during natural behaviors and scale poorly across species and muscle groups. Here we present a novel class of electrode devices (‘Myomatrix arrays’) that record muscle activity at unprecedented resolution across muscles and behaviors. High-density, flexible electrode arrays allow for stable recordings from the muscle fibers activated by a single motor neuron, called a ‘motor unit,’ during natural behaviors in many species, including mice, rats, primates, songbirds, frogs, and insects. This technology therefore allows the nervous system’s motor output to be monitored in unprecedented detail during complex behaviors across species and muscle morphologies. We anticipate that this technology will allow rapid advances in understanding the neural control of behavior and identifying pathologies of the motor system.

Each faculty search for new academic colleagues consumes significant time and energy for all parties involved, from the applicants to the search committee, other engaged colleagues, and leadership that aid in negotiations along the way. The goal here is to present specific approaches employed in a recent search process that were designed to contribute to an inclusive search process. Challenges and opportunities presented by performing the search during a global pandemic are incorporated. The detailed description of each step in the search should both be helpful to those planning their own faculty searches and to applicants who will benefit from seeing the process demystified. A case study on an inclusive faculty hiring process at Emory University provides advice for institutions creating their own hiring panels and workflows.

When junior researchers Kyle Thomas and Karena Nguyen joined a search committee, they came up with a way to put equity and inclusion centre stage. When junior researchers Kyle Thomas and Karena Nguyen joined a search committee, they came up with a way to put equity and inclusion centre stage.

As social robots continue to show promise as assistive technologies, the exploration of appropriate and impactful robot behaviors is key to their eventual success. Teens are a unique population given their vulnerability to stress leading to both mental and physical illness. Much of teen stress stems from school, making the school environment an ideal location for a stress reducing technology. The goal of this mixed-methods study was to understand teens' operation of, and responsiveness to, a robot only capable of movement compared to a robot only capable of speech. Stemming from a human-centered approach, we introduce a Participatory Wizard of Oz (PWoz) interaction method that engaged teens as operators, users, and witnesses in a uniquely transparent interaction. In this paper, we illustrate the use of the PWoz interaction method as well as how it helps identify engaging robot interactions. Using this technique, we present results from a study with 62 teens that includes details of the complexity of teen stress and a significant reduction in negative attitudes toward robots after interactions. We analyzed the teens' interactions with both the verbal and non-verbal robots and identified strong themes of (1) authenticity, (2) empathy, (3) emotional engagement, and (4) imperfection creates connection. Finally, we reflect on the benefits and limitations of the PWoz method and our study to identify next steps toward the design and development of our social robot.

Wearable sweat sensors rely either on electronics for electrochemical detection or on colorimetry for visual readout. Non-ideal form factors represent disadvantages of the former, while semiquantitative operation and narrow scope of measurable biomarkers characterize the latter. Here, we introduce a battery-free, wireless electronic sensing platform inspired by biofuel cells that integrates chronometric microfluidic platforms with embedded colorimetric assays. The resulting sensors combine advantages of electronic and microfluidic functionality in a platform that is significantly lighter, cheaper, and smaller than alternatives. A demonstration device simultaneously monitors sweat rate/loss, pH, lactate, glucose, and chloride. Systematic studies of the electronics, microfluidics, and integration schemes establish the key design considerations and performance attributes. Two-day human trials that compare concentrations of glucose and lactate in sweat and blood suggest a potential basis for noninvasive, semi-quantitative tracking of physiological status.

The effects of cilium length on the dynamics of cilia motion were investigated by high-speed video microscopy of uniciliate mutants of the swimming alga, Chlamydomonas reinhardtii. Cells with short cilia were obtained by deciliating cells via pH shock and allowing cilia to reassemble for limited times. The frequency of cilia beating was estimated from motion of the cell body and of the cilium. Key features of the ciliary waveform were quantified from polynomial curves fitted to the cilium in each image frame. Most notably, periodic beating did not emerge until the cilium reached a critical length between 2-4 µm. Surprisingly, in cells that exhibited periodic beating, the frequency of beating was similar for all lengths with only a slight decrease in frequency as length increased from 4 µm to the normal length of 10-12 µm. The waveform average curvature (rad/µm) was also conserved as the cilium grew. The mechanical metrics of ciliary propulsion: force, torque, and power all increased in proportion to length. Mechanical efficiency of beating appeared to be maximal at the normal wild-type length of 10-12 μm. These quantitative features of ciliary behavior illuminate the biophysics of cilia motion and, in future studies, may help distinguish competing hypotheses of the underlying mechanism of oscillation.