Optimal Control of Natural Eye-Head Movements Minimizes the Impact of Noise

Sağlam, Murat; Lehnen, Nadine; Glasauer, Stefan

doi:10.1523/jneurosci.3721-11.2011

Cited by 43 publications

(48 citation statements)

References 31 publications

(53 reference statements)

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“…The observed ACF irr (1) was, however, smaller than 0.4. This could be because some of the assumptions made (see MATERIALS AND METHODS) were violated and/or because the model does not include the effects of online corrections during the movement, but it could also be related to the fact that there are optimal combinations of eye and head movement that minimize gaze variability (Saglam et al 2011) and effort (Kardamakis and Moschovakis 2009). The eye and head contributions are therefore not truly task irrelevant.…”

Section: Resultsmentioning

confidence: 99%

Random walk of motor planning in task-irrelevant dimensions

Beers

Brenner

Smeets

2013

Journal of Neurophysiology

111

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The movements that we make are variable. It is well established that at least a part of this variability is caused by noise in central motor planning. Here, we studied how the random effects of planning noise translate into changes in motor planning. Are the random effects independently added to a constant mean end point, or do they accumulate over movements? To distinguish between these possibilities, we examined repeated, discrete movements in various tasks in which the motor output could be decomposed into a task-relevant and a task-irrelevant component. We found in all tasks that the task-irrelevant component had a positive lag 1 autocorrelation, suggesting that the random effects of planning noise accumulate over movements. In contrast, the task-relevant component always had a lag 1 autocorrelation close to zero, which can be explained by effective trial-by-trial correction of motor planning on the basis of observed motor errors. Accumulation of the effects of planning noise is consistent with current insights into the stochastic nature of synaptic plasticity. It leads to motor exploration, which may subserve motor learning and performance optimization.

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Section: Resultsmentioning

confidence: 99%

Random walk of motor planning in task-irrelevant dimensions

Beers

Brenner

Smeets

2013

Journal of Neurophysiology

111

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“…Here we recapitulate the information about subjects and experimental procedure that were previously explained and reported in detail [16,26]. Five patients with complete chronic bilateral vestibular loss (aged 45.4 ± 7.1 years, mean ± SD; three women; operated on for vestibular schwannoma bilaterally several years prior to the study), nine patients with adultonset slowly progressive cerebellar ataxia (aged 56.7 ± 12.6 years; six women; diagnosed with sporadic adult late-onset ataxia of unknown etiology (7 patients), spino-cerebellar ataxia type 2 (patient 3, Table 1), and a form of a non-identified genetic ataxia (patient 4, Table 1)), and ten healthy subjects aged 39.7 ± 6.3 years (one woman) gave their written informed consent to the study, that was performed in accordance with the Declaration of Helsinki, and approved by the ethics committee of the Medical Faculty of Ludwig-Maximilians-University Munich.…”

Section: Methodsmentioning

confidence: 99%

“…Data were analyzed offline in MATLAB R (The Mathworks Inc., USA). Details about the analysis were explained elsewhere [16,26]. Data were initially low-pass filtered with a Gaussian filter (20 Hz).…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Gaze stabilization in chronic vestibular-loss and in cerebellar ataxia: Interactions of feedforward and sensory feedback mechanisms

Sağlam¹,

Lehnen²

2014

VES

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During gaze shifts, humans can use visual, vestibular, and proprioceptive feedback, as well as feedforward mechanisms, for stabilization against active and passive head movements. The contributions of feedforward and sensory feedback control, and the role of the cerebellum, are still under debate. To quantify these contributions, we increased the head moment of inertia in three groups (ten healthy, five chronic vestibular-loss and nine cerebellar-ataxia patients) while they performed large gaze shifts to flashed targets in darkness. This induces undesired head oscillations. Consequently, both active (desired) and passive (undesired) head movements had to be compensated for to stabilize gaze. All groups compensated for active and passive head movements, vestibular-loss patients less than the other groups (P < 0.001, passive/active compensatory gains: vestibular-loss 0.23 ± 0.09/0.43 ± 0.12, healthy 0.80 ± 0.17/0.83 ± 0.15, cerebellar-ataxia 0.68 ± 0.17/0.77 ± 0.30, mean ± SD). The compensation gain ratio against passive and active movements was smaller than one in vestibular-loss patients (0.54 ± 0.10, P = 0.001). Healthy and cerebellar-ataxia patients did not differ in active and passive compensation. In summary, vestibular-loss patients can better stabilize gaze against active than against passive head movements. Therefore, feedforward mechanisms substantially contribute to gaze stabilization. Proprioception alone is not sufficient (gain 0.2). Stabilization against active and passive head movements was not impaired in our cerebellar ataxia patients.

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“…In a recent study, it has been proposed that humans move their head and eyes in the most optimal way in order to reduce the noise impact [16]. Many current eye-tracking and gaze estimation techniques are influenced by the natural head movements [3], thus limiting their usability.…”

Section: B Natural Head Movementsmentioning

confidence: 99%

The head mouse — Head gaze estimation "In-the-Wild" with low-cost inertial sensors for BMI use

Sim¹,

Gavriel²,

Abbott³

et al. 2013

2013 6th International IEEE/EMBS Conference on Neural Engineering (NER)

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We present a wearable head-tracking device using inexpensive inertial sensors as an alternative head movement tracking system. This can be used as indicator of human movement intentions for Brain-Machine Interface (BMI) applications. Our system is capable of tracking head movements at high rates (100 Hz) and achieves R 2 = 0.99 with a 2.5 • RMSE against a ground-truth motion tracking system. The system tracks head movements over periods in the order of tens of minutes with little drift. The accuracy and precision of our system, together with its low response latency of ≈ 20 ms make it an unconventional but effective system for human-computer interfacing: the "head mouse" controls the mouse cursor on a display based on head orientation alone, so that it matches the centre of a straight-onward looking user. Our head mouse is suitable for amputees and spinal chord injury patients who have lost control of their upper extremities. We show that naive test subjects are capable to write text using our system and an on-screen keyboard at a rate of 4.65 words/minute, compared to able bodied users using a physical computer mouse which reached 7.85 words/minute. Crucially we measure the natural head movements of able bodied computer users, and show that our approach falls within the range of natural head movement parameters.

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Optimal Control of Natural Eye-Head Movements Minimizes the Impact of Noise

Cited by 43 publications

References 31 publications

Random walk of motor planning in task-irrelevant dimensions

Random walk of motor planning in task-irrelevant dimensions

Gaze stabilization in chronic vestibular-loss and in cerebellar ataxia: Interactions of feedforward and sensory feedback mechanisms

The head mouse — Head gaze estimation "In-the-Wild" with low-cost inertial sensors for BMI use

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Optimal Control of Natural Eye-Head Movements Minimizes the Impact of Noise

Cited by 43 publications

References 31 publications

Random walk of motor planning in task-irrelevant dimensions

Random walk of motor planning in task-irrelevant dimensions

Gaze stabilization in chronic vestibular-loss and in cerebellar ataxia: Interactions of feedforward and sensory feedback mechanisms

The head mouse &#x2014; Head gaze estimation &#x0022;In-the-Wild&#x0022; with low-cost inertial sensors for BMI use

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The head mouse — Head gaze estimation "In-the-Wild" with low-cost inertial sensors for BMI use