Volitional Control of Neural Activity Relies on the Natural Motor Repertoire

Hwang, Eun Jung; Bailey, Paul; Andersen, Richard A.

doi:10.1016/j.cub.2013.01.027

Cited by 75 publications

(102 citation statements)

References 35 publications

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“…In addition to the inputs associated with the global reward signal, cortical neurons receive strong synaptic inputs from surrounding neurons. Consistent with this, non-target neurons whose activity is highly correlated with that of the target neuron tend to change their firing rate with the target neuron 9,10 . However, individual neurons recorded from the same electrode can be separately controlled in SNOC 2,3,9,11 .…”

supporting

confidence: 52%

Reward-timing-dependent bidirectional modulation of cortical microcircuits during optical single-neuron operant conditioning

et al. 2014

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Animals rapidly adapt to environmental change. To reveal how cortical microcircuits are rapidly reorganized when an animal recognizes novel reward contingency, we conduct twophoton calcium imaging of layer 2/3 motor cortex neurons in mice and simultaneously reinforce the activity of a single cortical neuron with water delivery. Here we show that when the target neuron is not relevant to a pre-trained forelimb movement, the mouse increases the target neuron activity and the number of rewards delivered during 15-min operant conditioning without changing forelimb movement behaviour. The reinforcement bidirectionally modulates the activity of subsets of non-target neurons, independent of distance from the target neuron. The bidirectional modulation depends on the relative timing between the reward delivery and the neuronal activity, and is recreated by pairing reward delivery and photoactivation of a subset of neurons. Reward-timing-dependent bidirectional modulation may be one of the fundamental processes in microcircuit reorganization for rapid adaptation.

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confidence: 52%

Reward-timing-dependent bidirectional modulation of cortical microcircuits during optical single-neuron operant conditioning

et al. 2014

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“…Previous studies have shown that there are two general categories of learning mechanism for single neurons in BMIs (18). For an individual neuron mechanism, each neuron is separately manipulated to produce a particular response pattern independent of the activity of its neighbors.…”

Section: Discussionmentioning

confidence: 99%

“…Second, the BMI application induced learning-related changes in the saccade system. Learning can produce changes in reach areas, but how learning-related changes occur at the level of LIP neuronal ensembles is still unclear (17,18).Here, we show that the intended eye movement activity can be used to accurately position a cursor on a computer screen. These results suggest that an eye movement BMI can be used as a prosthetic to assist locked-in patients who cannot produce eye movements.…”

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confidence: 92%

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Brain–machine interface for eye movements

Graf

Andersen

2014

Proc. Natl. Acad. Sci. U.S.A.

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A number of studies in tetraplegic humans and healthy nonhuman primates (NHPs) have shown that neuronal activity from reachrelated cortical areas can be used to predict reach intentions using brain-machine interfaces (BMIs) and therefore assist tetraplegic patients by controlling external devices (e.g., robotic limbs and computer cursors). However, to our knowledge, there have been no studies that have applied BMIs to eye movement areas to decode intended eye movements. In this study, we recorded the activity from populations of neurons from the lateral intraparietal area (LIP), a cortical node in the NHP saccade system. Eye movement plans were predicted in real time using Bayesian inference from small ensembles of LIP neurons without the animal making an eye movement. Learning, defined as an increase in the prediction accuracy, occurred at the level of neuronal ensembles, particularly for difficult predictions. Population learning had two components: an update of the parameters of the BMI based on its history and a change in the responses of individual neurons. These results provide strong evidence that the responses of neuronal ensembles can be shaped with respect to a cost function, here the prediction accuracy of the BMI. Furthermore, eye movement plans could be decoded without the animals emitting any actual eye movements and could be used to control the position of a cursor on a computer screen. These findings show that BMIs for eye movements are promising aids for assisting paralyzed patients.learning | lateral intraparietal area | brain-machine interface | eye movements | saccades B rain-machine interfaces (BMIs) have been successfully used to predict reaches and arm movements (1-7). However, little effort has been concentrated on building a BMI based on eye movements. This gap is surprising because the motor and neuronal mechanisms of eye movements are very well understood and arguably simpler than those of arm movements. Specifically, eye movements are rapid and ballistic. The lateral intraparietal cortex (LIP) is ideally suited to be the site for a BMI based on eye movements (8). LIP neurons are known to encode eye movement plans, among other signals such as eye position (9-16). We recently showed that eye movement plans can be accurately predicted from the responses of populations of LIP neurons using Bayesian inference (16). The aim of the present study was twofold. First, a BMI was used with small neuronal ensembles of LIP neurons to predict, in real time, eye movement plans without the animals actually making eye movements. Second, the BMI application induced learning-related changes in the saccade system. Learning can produce changes in reach areas, but how learning-related changes occur at the level of LIP neuronal ensembles is still unclear (17,18).Here, we show that the intended eye movement activity can be used to accurately position a cursor on a computer screen. These results suggest that an eye movement BMI can be used as a prosthetic to assist locked-in patients who cannot produce eye mov...

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“…Several of these central areas are thought to form and anticipate a reliable motor percept (Hauschild et al 2012;Kawato and Wolpert 1998;Mulliken et al 2008;Wolpert et al 1998), even in the absence of active efferent commands from ongoing movements ). In particular, in the parietal areas, the separation between sensory input and abstract planning has been demonstrated across several contexts (Andersen and Buneo 2002;Hwang et al 2013;Torres et al 2013c). Based on this prior research, we examine here velocity-dependent parameters from the continuous flow of natural, unconstrained hand motions.…”

mentioning

confidence: 99%

Strategies to develop putative biomarkers to characterize the female phenotype with autism spectrum disorders

Torres

Isenhower

Yanovich

et al. 2013

Journal of Neurophysiology

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Torres EB, Isenhower RW, Yanovich P, Rehrig G, Stigler K, Nurnberger J, José JV. Strategies to develop putative biomarkers to characterize the female phenotype with autism spectrum disorders. J Neurophysiol 110: 1646 -1662, 2013. First published July 17, 2013 doi:10.1152/jn.00059.2013.-Current observational inventories used to diagnose autism spectrum disorders (ASD) apply similar criteria to females and males alike, despite developmental differences between the sexes. Recent work investigating the chronology of diagnosis in ASD has raised the concern that females run the risk of receiving a delayed diagnosis, potentially missing a window of opportunity for early intervention. Here, we retake this issue in the context of the objective measurements of natural behaviors that involve decisionmaking processes. Within this context, we quantified movement variability in typically developing (TD) individuals and those diagnosed with ASD across different ages. We extracted the latencies of the decision movements and velocity-dependent parameters as the hand movements unfolded for two movement segments within the reach: movements intended toward the target and withdrawing movements that spontaneously, without instruction, occurred incidentally. The stochastic signatures of the movement decision latencies and the percent of time to maximum speed differed between males and females with ASD. This feature was also observed in the empirically estimated probability distributions of the maximum speed values, independent of limb size. Females with ASD showed different dispersion than males with ASD. The distinctions found for females with ASD were better appreciated compared with those of TD females. In light of these results, behavioral assessment of autistic traits in females should be performed relative to TD females to increase the chance of detection.

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Volitional Control of Neural Activity Relies on the Natural Motor Repertoire

Cited by 75 publications

References 35 publications

Reward-timing-dependent bidirectional modulation of cortical microcircuits during optical single-neuron operant conditioning

Reward-timing-dependent bidirectional modulation of cortical microcircuits during optical single-neuron operant conditioning

Brain–machine interface for eye movements

Strategies to develop putative biomarkers to characterize the female phenotype with autism spectrum disorders

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