Motor neuronal activity varies least among individuals when it matters most for behavior

Cullins, Miranda J.; Shaw, Kendrick M.; Gill, Jeffrey P.; Chiel, Hillel J.

doi:10.1152/jn.00729.2014

Cited by 26 publications

(29 citation statements)

References 93 publications

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“…As a first step toward locating the bursts of identified motor neurons and their firing frequencies, individual spikes were detected and grouped into spike trains using manually specified window discriminators, which captured signal peaks on a given channel occurring within a given amplitude range and time window. Individual motor neurons can be identified from extracellular nerve signals in this system because of their reliable relative amplitudes and phase of activity (Morton and Chiel, 1993b;Lu et al, 2013Lu et al, , 2015McManus et al, 2014;Cullins et al, 2015b) (see Table 1). The spike amplitude of some neurons, especially B8a/b and B4/B5, can vary when these neurons activate at high frequencies due to spike collisions seen in the extracellular nerve recordings (Morton and Chiel, 1993b;Warman and Chiel, 1995), so we designed the window discriminators to account for this variability.…”

Section: Discussionmentioning

confidence: 99%

“…The much larger forces animals generate on their own when swallowing tough foods in their natural habitat have not been measured, nor have the neural correlates of adaptation to high loads. Recent studies of the biomechanics of feeding (Neustadter et al, 2002(Neustadter et al, , 2007Kehl et al, 2019), modeling (Neustadter et al, 2002;Sutton et al, 2004a), and neural control (McManus et al, 2014;Cullins et al, 2015b;Lu et al, 2015) have provided further insights into the behavioral roles of individual neurons, suggesting that it might now be possible to relate behavior to neural activity despite the high variability.…”

Section: Introductionmentioning

confidence: 99%

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Rapid Adaptation to Changing Mechanical Load by Ordered Recruitment of Identified Motor Neurons

Gill

Chiel

2020

eNeuro

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As they interact with their environment and encounter challenges, animals adjust their behavior on a moment-to-moment basis to maintain task fitness. This dynamic process of adaptive motor control occurs in the nervous system, but an understanding of the body's biomechanics is essential to properly interpret the behavioral outcomes. To study how animals respond to changing task conditions, we used a model system in which the functional roles of identified neurons and the relevant biomechanics are well understood and can be studied in intact behaving animals: feeding in the marine mollusc Aplysia. We monitored the motor neuronal output of the feeding circuitry as intact animals fed on uniform food stimuli under unloaded and loaded conditions, and we measured the force of retraction during loaded swallows. We observed a previously undescribed pattern of force generation, which can be explained within the appropriate biomechanical context by the activity of just a few key, identified motor neurons. We show that, when encountering load, animals recruit identified retractor muscle motor neurons for longer and at higher frequency to increase retraction force duration. Our results identify a mode by which animals robustly adjust behavior to their environment which is experimentally tractable to further mechanistic investigation. Significance Statement Understanding adaptive motor control requires studying the brain and body together during behavior. Studying motor control systems at the level of individual neurons in intact animals is challenging. The Aplysia feeding system has individual neurons that can be identified from animal to animal and well-studied biomechanics. Prior work showed that animals respond adaptively to changing mechanical load, but did not measure or did not find strong neural correlates. As animals generate increasing force on food, we find that the increased activity and size-ordered recruitment of identified motor neurons allows animals to adapt their behavior. This is the first demonstration of a relationship between identified motor neurons and adaptive motor behavior in intact behaving Aplysia in response to changing mechanical load.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Rapid Adaptation to Changing Mechanical Load by Ordered Recruitment of Identified Motor Neurons

Gill

Chiel

2020

eNeuro

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“…Within these “motor equivalent” solutions, there may be some that are less desirable than others for any number of reasons, including energetics, stability, and generalizability across tasks. However, finding optimal solutions may be challenging, as muscle activation patterns have complex and nonlinear relationships to biomechanical functions (Cullins et al, 2014). …”

Section: Neuromechanical Principles Underlying Motor Module Organizationmentioning

confidence: 99%

“…In contrast, the solutions showed high variability in the “don’t care” region late in the stance phase, during which the model leg continued to move backwards but was no longer able to exert force (Beer et al, 1999). For example, distributions of motor neuron activation duration varies from one individual to another in Aplysia feeding behavior, but when motor neuron duration and timing play a critical role in a behavior such as closing its grasper to retract food, the distributions become similar across all individuals (Cullins et al, 2014). In contrast, there is high variability in the duration of motor neuron activity to close the grasper if the animal fails to grasp food, as the motor neuronal activity is no longer functionally relevant.…”

Section: Neuromechanical Principles Underlying Motor Module Organizationmentioning

confidence: 99%

Neuromechanical Principles Underlying Movement Modularity and Their Implications for Rehabilitation

Ting

Chiel

Trumbower

et al. 2015

Neuron

355

317

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Summary Neuromechanical principles define the properties and problems that shape neural solutions for movement. Although the theoretical and experimental evidence is debated, we present arguments for consistent structures in motor patterns, i.e. motor modules, that are neuromechanical solutions for movement particular to an individual and shaped by evolutionary, developmental, and learning processes. As a consequence, motor modules may be useful in assessing sensorimotor deficits specific to an individual, and define targets for the rational development of novel rehabilitation therapies that enhance neural plasticity and sculpt motor recovery. We propose that motor module organization is disrupted and may be improved by therapy in spinal cord injury, stroke, and Parkinson’s disease. Recent studies provide insights into the yet unknown underlying neural mechanisms of motor modules, motor impairment and motor learning, and may lead to better understanding of the causal nature of modularity and its underlying neural substrates.

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“…For example, during locomotion, each step may vary within and across individuals, even when behavior is normalized by step cycle duration [13]. Our previous work demonstrated that motor components that matter for effective behavior show less individuality [14]. Is sensory feedback the mechanism for reducing individuality?…”

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confidence: 99%

Sensory Feedback Reduces Individuality by Increasing Variability within Subjects

et al. 2015

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Summary Behavioral variability is ubiquitous [1–6], yet variability is more than just noise. Indeed, humans exploit their individual motor variability to improve tracing and reaching tasks [7]. What controls motor variability? Increasing the variability of sensory input, or applying force perturbations during a task, increases task variability [8,9]. Sensory feedback may also increase task-irrelevant variability [9,10]. In contrast, sensory feedback during locust flight or to multiple cortical areas just prior to task performance decreases variability during task-relevant motor behavior [11,12]. Thus, how sensory feedback affects both task-relevant and task-irrelevant motor outputs must be understood. Furthermore, since motor control is studied in populations, the effects of sensory feedback on variability must also be understood within and across subjects. For example, during locomotion, each step may vary within and across individuals, even when behavior is normalized by step cycle duration [13]. Our previous work demonstrated that motor components that matter for effective behavior show less individuality [14]. Is sensory feedback the mechanism for reducing individuality? We analyzed durations and relative timings of motor pools within swallowing motor patterns in the presence and absence of sensory feedback, and related these motor program components to behavior. Here, at the level of identified motor neurons, we show that sensory feedback to motor program components highly correlated with behavioral efficacy reduces variability across subjects, but – surprisingly – increases variability within subjects. By controlling intrinsic, individual differences in motor neuronal activity, sensory feedback provides each subject access to a common solution space.

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Motor neuronal activity varies least among individuals when it matters most for behavior

Cited by 26 publications

References 93 publications

Rapid Adaptation to Changing Mechanical Load by Ordered Recruitment of Identified Motor Neurons

Rapid Adaptation to Changing Mechanical Load by Ordered Recruitment of Identified Motor Neurons

Neuromechanical Principles Underlying Movement Modularity and Their Implications for Rehabilitation

Sensory Feedback Reduces Individuality by Increasing Variability within Subjects

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