An information theoretic method to resolve millisecond-scale spike timing precision in a comprehensive motor program

Flight power muscles have a coordinated, causal role in controlling hawkmoth pitch turns

Flying insects solve a daunting control problem of generating a patterned and precise motor program to stay airborne and generate agile maneuvers. In this motor program, each muscle encodes information about movement in precise spike timing down to the millisecond scale. Whereas individual muscles share information about movement, we do not know whether they have separable effects on an animal's motion, or whether muscles functionally interact such that the effects of any muscle's timing depend heavily on the state of the entire musculature. To answer these questions, we performed spike-resolution electromyography and electrical stimulation in the hawkmoth Manduca sexta during tethered flapping. We specifically explored how flight power muscles contribute to pitch control. Combining correlational study of visually induced turns with causal manipulation of spike timing, we discovered likely coordination patterns for pitch turns, and investigated whether these patterns can drive pitch control. We observed significant timing change of the main downstroke muscles, the dorsolongitudinal muscles (DLMs), associated with pitch turns. Causally inducing this timing change in the DLMs with electrical stimulation produced a consistent, mechanically relevant feature in pitch torque, establishing that power muscles in M. sexta have a control role in pitch. Because changes were evoked in only the DLMs, however, these pitch torque features left large unexplained variation. We found this unexplained variation indicates significant functional overlap in pitch control such that precise timing of one power muscle does not produce a precise turn, demonstrating the importance of coordination across the entire motor program for flight.

Temporal resolution of spike coding in feedforward networks with signal convergence and divergence

Convergent and divergent structures in the networks that make up biological brains are found across many species and brain regions at various spatial scales. Neurons in these networks fire action potentials, or "spikes", whose precise timing is becoming increasingly appreciated as large sources of information about both sensory input and motor output. While previous theories on coding in convergent and divergent networks have largely neglected the role of precise spike timing, our model and analyses place this aspect at the forefront. For a suite of stimuli with different timescales, we demonstrate that structural bottlenecks- small groups of neurons post-synaptic to network convergence - have a stronger preference for spike timing codes than expansion layers created by structural divergence. Additionally, we found that a simple network model based on convergence and divergence ratios of a hawkmoth (Manduca sexta) nervous system can reproduce the relative contribution of spike timing information in its motor output, providing testable predictions on optimal temporal resolutions of spike coding across the moth sensory-motor pathway at both the single-neuron and population levels. Our simulations and analyses suggest a relationship between the level of convergent/divergent structure present in a feedforward network and the loss of stimulus information encoded by its population spike trains as their temporal resolution decreases, which could be tested experimentally across diverse neural systems in future studies. We further show that this relationship can be generalized across different spike-generating models and measures of coding capacity, implying a potentially fundamental link between network structure and coding strategy using spikes.

Myomatrix arrays for high-definition muscle recording

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.