Internal Models in Biological Control

McNamee, Daniel; Wolpert, Daniel M.

doi:10.1146/annurev-control-060117-105206

Cited by 174 publications

(145 citation statements)

References 134 publications

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“…At one extreme, Lum et al (2005) have suggested that variability may be a trial-and-error process for finding successful behaviors. At the other, McNamee and Wolpert (2019) have proposed that animals may develop internal computational models of the biomechanics governing their own bodies and the environment so as to generate optimal behavior. The results of this paper suggest a different framework in which behavior is constantly shaped by sensory feedback, and animals use this to find a "good enough" solution to most problems (Loeb, 2012).…”

Section: Discussionmentioning

confidence: 99%

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%

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

Gill

Chiel

2020

eNeuro

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“…Internal models of target motion are necessary to overcome visual delays inherent to the visuomotor system but also for instances of target occlusion and interceptive movements (Becker and Fuchs, 1985;Bosco et al, 2015). These internal models are useful as they allow the brain to minimize prediction error and behave optimally in the environment (McNamee and Wolpert, 2019). Notably, the eye position signals decoded from visual areas such as MT, MST, VIP, and LIP lead the current eye position, indicating a predictive process based on an efference copy of eye position (Dowiasch et al, 2016).…”

Section: Underlying Neurophysiology For Predictionmentioning

confidence: 99%

Predicted Position Error Triggers Catch-Up Saccades during Sustained Smooth Pursuit

Nachmani

Coutinho

Khan

et al. 2019

eNeuro

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For humans, visual tracking of moving stimuli often triggers catch-up saccades during smooth pursuit. The switch between these continuous and discrete eye movements is a trade-off between tolerating sustained position error (PE) when no saccade is triggered or a transient loss of vision during the saccade due to saccadic suppression. de Brouwer et al. (2002b) demonstrated that catch-up saccades were less likely to occur when the target re-crosses the fovea within 40-180 ms. To date, there is no mechanistic explanation for how the trigger decision is made by the brain. Recently, we proposed a stochastic decision model for saccade triggering during visual tracking (Coutinho et al., 2018) that relies on a probabilistic estimate of predicted PE (PE pred). Informed by model predictions, we hypothesized that saccade trigger time length and variability will increase when pre-saccadic predicted errors are small or visual uncertainty is high (e.g., for blurred targets). Data collected from human participants performing a double step-ramp task showed that large pre-saccadic PE pred (Ͼ10°) produced short saccade trigger times regardless of the level of uncertainty while saccade trigger times preceded by small PE pred (Ͻ10°) significantly increased in length and variability, and more so for blurred targets. Our model also predicted increased signal-dependent noise (SDN) as retinal slip (RS) increases; in our data, this resulted in longer saccade trigger times and more smooth trials without saccades. In summary, our data supports our hypothesized predicted error-based decision process for coordinating saccades during smooth pursuit.

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“…The production of desired movements with a novel tool involves forming the internal representation of mechanical properties of the tool interacting with the body, which is so called the internal model . Our finding of the incomplete adaptation to novel dynamics of the piano key in patients with FTSD therefore suggests an impairment of updating the internal model of the piano‐key dynamics.…”

Section: Discusssionmentioning

confidence: 84%

“…A key skill indispensable for the dexterous use of various tools is a flexible adaptation to novel mechanical dynamics emerging from contact of a body with the tool. Successful adaptation requires representing mechanical properties of the object based on somatosensory afferent information, which enables the nervous system to elicit motor commands necessary for the production of desired movements, so called internal models . However, some neurological disorders such as cerebellar ataxia and Huntington's disease impair the formation of such representation, which prevents an adaptation to novel dynamics in dexterous tool use.…”

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confidence: 99%

Aberrant Somatosensory–Motor Adaptation in Musicians' Dystonia

et al. 2020

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A BS TRACT: Background: Some forms of movement disorders are characterized by task-specific manifestations of symptoms. However, its underlying mechanisms are poorly understood. Here we addressed this issue through a novel motor adaptation experimental paradigm. Methods: Pianists with and without focal task-specific dystonia learned to play the piano with a key whose weight can be modified by a novel robot system. Results: The result clearly demonstrated a significantly larger error between the target and produced keystroke velocities in the patients than the controls following a repetition of keystrokes of the weighted key. This adaptation failure was not correlated with the variability of timing and velocity of the keystroke when the patients were playing unloaded piano keys, which suggests distinct effects of focal task-specific dystonia on motor adaptation and fine motor control. Immediately after a repetition of the strikes of the heavy key with keeping the fingers adducted, the error of the keystroke velocity when striking the key with the fingers more abducted was maintained in both the patients and controls. This generalization of the adaptation across different hand postures suggests that motor memory of dynamics of the piano key is independent of biomechanical properties of the hand. Importantly, a lack of difference in the finger muscular strength between the groups indicated that the adaptation failure was not attributed to deficit of muscular strength in the patients. Conclusions: These findings suggest that task-specific manifestation of dystonic movements in focal task-specific dystonia is associated with malfunctions of internal representation of mechanical properties of a well-trainedtool.

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Internal Models in Biological Control

Cited by 174 publications

References 134 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

Predicted Position Error Triggers Catch-Up Saccades during Sustained Smooth Pursuit

Aberrant Somatosensory–Motor Adaptation in Musicians' Dystonia

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