Cortical correlates of fitts' law

Multiplicative joint coding in preparatory activity for reaching sequence in macaque motor cortex

Although the motor cortex has been found to be modulated by sensory or cognitive sequences, the linkage between multiple movement elements and sequence-related responses is not yet understood. Here, we recorded neuronal activity from the motor cortex with implanted micro-electrode arrays and single electrodes while monkeys performed a double-reach task that was instructed by simultaneously presented memorized cues. We found that there existed a substantial multiplicative component jointly tuned to impending and subsequent reaches during preparation, then the coding mechanism transferred to an additive manner during execution. This multiplicative joint coding, which also spontaneously emerged in recurrent neural networks trained for double reach, enriches neural patterns for sequential movement, and might explain the linear readout of elemental movements.

Information-theory analysis of mouse string-pulling agrees with Fitts's Law: Increasing task difficulty engages multiple sensorimotor modalities in a dual oscillator behavior

Mouse string pulling, in which a mouse reels in a string with hand-over-hand movements, can provide insights into skilled motor behavior, neurological status, and cognitive function. The task involves two oscillatory movements connected by a string. The snout oscillates to track the pendulum movement of the string produced by hand-over-hand oscillations of pulling, and so the snout guides the hands to grasp the string. The present study examines the allocation of time required to pull strings of varying diameter. Movement is also described with end-point measures, string-pulling topography with 2D markerless pose estimates based on transfer learning with deep neural networks, and Mat-lab image-segmentation and heuristic algorithms for object tracking. With reduced string diameter, mice took longer to pull 60 cm long strings. They also made more pulling cycles, misses, and mouth engagements, and displayed changes in the amplitude and frequency of pull cycles. The time measures agree with Fitts's law in showing that increased task difficulty slows behavior and engages multiple compensatory sensorimotor modalities. The analysis reveals that time is a valuable resource in skilled motor behavior and information-theory can serve as a measure of its effective use.

Dual-Task Interference Slows Down Proprioception

It is well-known that multitasking impairs the performance of one or both of the concomitant ongoing tasks. Previous studies have mainly focused on how a secondary task can compromise visual or auditory information processing. However, despite dual tasking being critical to motor performance, the effects of dual-task performance on proprioceptive information processing have not been studied yet. The purpose of the present study was, therefore, to investigate whether sensorimotor task performance would be affected by the dual task and if so, in which phase of the sensorimotor task performance would this negative effect occur. The kinematic variables of passive and active knee movements elicited by the leg drop test were analyzed. Thirteen young adults participated in the study. The dual task consisted of performing serial subtractions. The results showed that the dual task increased both the reaction time to counteract passive knee-joint movements in the leg drop test and the threshold to detect those movements. The dual task did not affect the speed and time during the active knee movement and the absolute angle error between the final and the target knee angles. Furthermore, the results showed that the time to complete the sensorimotor task was prolonged in dual tasking. Our findings suggest that dual tasking reduces motor performance due to slowing down proprioceptive information processing without affecting movement execution.

Behavioral effects of continuous theta-burst stimulation in macaque parietal cortex

The neural mechanisms underlying the effects of continuous Theta-Burst Stimulation (cTBS) in humans are poorly understood. Animal studies can clarify the effects of cTBS on individual neurons, but behavioral evidence is necessary to demonstrate the validity of the animal model. We investigated the behavioral effect of cTBS applied over parietal cortex in rhesus monkeys performing a visually-guided grasping task with two differently sized objects, which required either a power grip or a pad-to-side grip. We used Fitts' law, predicting shorter grasping times (GT) for large compared to small objects, to investigate cTBS effects on two different grip types. cTBS induced long-lasting object-specific and dose-dependent changes in GT that remained present for up to two hours. High-intensity cTBS increased GTs for a power grip, but shortened GTs for a pad-to-side grip. Thus, high-intensity stimulation strongly reduced the natural GT difference between objects (i.e. the Fitts' law effect). In contrast, low-intensity cTBS induced the opposite effects on GT. Modifying the coil orientation from the standard 45-degree to a 30-degree angle induced opposite cTBS effects on GT. These findings represent behavioral evidence for the validity of the nonhuman primate model to study the neural underpinnings of non-invasive brain stimulation.

Primary motor cortical activity during unimanual movements with increasing demand on precision

In functional magnetic resonance imaging (fMRI) studies, performance of unilateral hand movements is associated with primary motor cortex activity ipsilateral to the moving hand (M1_ipsi), in addition to contralateral activity (M1_contra). The magnitude of M1_ipsi activity increases with the demand on precision of the task. However, it is unclear how demand-dependent increases in M1_ipsi recruitment relate to the control of hand movements. To address this question, we used fMRI to measure blood oxygenation level-dependent (BOLD) activity during performance of a task that varied in demand on precision. Participants (n = 23) manipulated an MRI-compatible joystick with their right or left hand to move a cursor into targets of different sizes (small, medium, large, extra large). Performance accuracy, movement time, and number of velocity peaks scaled with target size, whereas reaction time, maximum velocity, and initial direction error did not. In the univariate analysis, BOLD activation in M1_contra and M1_ipsi was higher for movements to smaller targets. Representational similarity analysis, corrected for mean activity differences, revealed multivoxel BOLD activity patterns during movements to small targets were most similar to those for medium targets and least similar to those for extra-large targets. Only models that varied with demand (target size, performance accuracy, and number of velocity peaks) correlated with the BOLD dissimilarity patterns, though differently for right and left hands. Across individuals, M1_contra and M1_ipsi similarity patterns correlated with each other. Together, these results suggest that increasing demand on precision in a unimanual motor task increases M1 activity and modulates M1 activity patterns.NEW & NOTEWORTHY Contralateral primary motor cortex (M1) predominantly controls unilateral hand movements, but the role of ipsilateral M1 is unclear. We used functional magnetic resonance imaging (fMRI) to investigate how M1 activity is modulated by unimanual movements at different levels of demand on precision. Our results show that task characteristics related to demand on precision influence bilateral M1 activity, suggesting that in addition to contralateral M1, ipsilateral M1 plays a key role in controlling hand movements to meet performance precision requirements.

Analysis of neuronal ensemble activity reveals the pitfalls and shortcomings of rotation dynamics

Back in 2012, Churchland and his colleagues proposed that "rotational dynamics", uncovered through linear transformations of multidimensional neuronal data, represent a fundamental type of neuronal population processing in a variety of organisms, from the isolated leech central nervous system to the primate motor cortex. Here, we evaluated this claim using Churchland's own data and simple simulations of neuronal responses. We observed that rotational patterns occurred in neuronal populations when (1) there was a temporal sequence in peak firing rates exhibited by individual neurons, and (2) this sequence remained consistent across different experimental conditions. Provided that such a temporal order of peak firing rates existed, rotational patterns could be easily obtained using a rather arbitrary computer simulation of neural activity; modeling of any realistic properties of motor cortical responses was not needed. Additionally, arbitrary traces, such as Lissajous curves, could be easily obtained from Churchland's data with multiple linear regression. While these observations suggest that temporal sequences of neuronal responses could be visualized as rotations with various methods, we express doubt about Churchland et al.'s bold assessment that such rotations are related to "an unexpected yet surprisingly simple structure in the population response", which "explains many of the confusing features of individual neural responses". Instead, we argue that their approach provides little, if any, insight on the underlying neuronal mechanisms employed by neuronal ensembles to encode motor behaviors in any species.

An acute bout of aerobic exercise reduces movement time in a Fitts' task

Movement time (MT) is one of the most important variables influencing the way we control our movements. A few previous studies have generally found that MT reduces with reaction time testing during exercise. However, limited evidence exists concerning change in MT following an acute bout of exercise. Our purpose was to investigate the effect of an acute bout of aerobic exercise on movement time as assessed by a Fitts’ Law task. We also sought to determine if exercise would further lower MT during the more difficult task conditions compared with rest. Nineteen (12 male, 7 female) volunteers (19–28 yrs) completed a computerized paired serial pointing task to measure movement time before and after rest (R) and an acute bout of moderate aerobic exercise (E) using a within subjects crossover design. Comparisons between exercise and rest conditions were made to determine if there were differences in movement time. Exercise significantly reduced MT compared with rest. Movement time was reduced by an average of 208 ms following exercise compared with 108 ms following rest. Exercise did not further lower MT during the more difficult task conditions. These results suggest that an acute bout of aerobic exercise reduces movement time which is an important component of motor control. Further studies are needed to determine the duration of the effect as well as the optimum duration and intensity of exercise.

Evaluation of speed-accuracy trade-off in a computer task in individuals with cerebral palsy: a cross-sectional study

BACKGROUND

Individuals with Cerebral Palsy (CP) present with sensorimotor dysfunction which make the control and execution of movements difficult. This study aimed to verify the speed-accuracy trade-off in individuals with CP.

METHODS

Forty eight individuals with CP and 48 with typical development (TD) were evaluated (32 females and 64 males with a mean age of 15.02 ± 6.37 years: minimum 7 and maximum 30 years). Participants performed the "Fitts' Reciprocal Aiming Task v.1.0 (Horizontal)" on a computer with different sizes and distance targets, composed by progressive indices of difficulty (IDs): ID2, ID4a and ID4b.

RESULTS

There were no statistical differences between the groups in relation to the slope of the curve (b1) and dispersion of the movement time (r²). However, the intercept (b0) values presented significant differences (F(1.95) = 11.3; p = .001]), with greater movement time in the CP group compared to the TD group. It means that for individuals with CP, regardless of index difficulty, found the task more difficult than for TD participants. Considering CP and TD groups, speed-accuracy trade-off was found when using different indices of difficulty (ID2 and ID4). However, when the same index of difficulty was used with a larger target and longer distance (ID4a) or with a narrow target and shorter distance (ID4b), only individuals with CP had more difficulty performing the tasks involving smaller targets. Marginally significant inverse correlations were identified between the values of b1 and age (r = -0.119, p = .052) and between r² and Gross Motor Function Classification System (r = -0.280, p = .054), which did not occur with the Manual Ability Classification System.

CONCLUSION

We conclude that the individuals with CP presented greater difficulty when the target was smaller and demanded more accuracy, and less difficulty when the task demanded speed. It is suggested that treatments should target tasks with accuracy demands, that could help in daily life tasks, since it is an element that is generally not considered by professionals during therapy.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT03002285 , retrospectively registered on 20 Dec 2016.

Advancing brain-machine interfaces: moving beyond linear state space models

Advances in recent years have dramatically improved output control by Brain-Machine Interfaces (BMIs). Such devices nevertheless remain robotic and limited in their movements compared to normal human motor performance. Most current BMIs rely on transforming recorded neural activity to a linear state space composed of a set number of fixed degrees of freedom. Here we consider a variety of ways in which BMI design might be advanced further by applying non-linear dynamics observed in normal motor behavior. We consider (i) the dynamic range and precision of natural movements, (ii) differences between cortical activity and actual body movement, (iii) kinematic and muscular synergies, and (iv) the implications of large neuronal populations. We advance the hypothesis that a given population of recorded neurons may transmit more useful information than can be captured by a single, linear model across all movement phases and contexts. We argue that incorporating these various non-linear characteristics will be an important next step in advancing BMIs to more closely match natural motor performance.

Stopping is not an option: the evolution of unstoppable motion elements (primitives)

Stopping performance is known to depend on low-level motion features, such as movement velocity. It is not known, however, whether it is also subject to high-level motion constraints. Here, we report results of 15 subjects instructed to connect four target points depicted on a digitizing tablet and stop "as rapidly as possible" upon hearing a "stop" cue (tone). Four subjects connected target points with straight paths, whereas 11 subjects generated movements corresponding to coarticulation between adjacent movement components. For the noncoarticulating and coarticulating subjects, stopping performance was not correlated or only weakly correlated with motion velocity, respectively. The generation of a straight, point-to-point movement or a smooth, curved trajectory was not disturbed by the occurrence of a stop cue. Overall, the results indicate that stopping performance is subject to high-level motion constraints, such as the completion of a geometrical plan, and that globally planned movements, once started, must run to completion, providing evidence for the definition of a motion primitive as an unstoppable motion element.

Chronic, wireless recordings of large-scale brain activity in freely moving rhesus monkeys

Advances in techniques for recording large-scale brain activity contribute to both the elucidation of neurophysiological principles and the development of brain-machine interfaces (BMIs). Here we describe a neurophysiological paradigm for performing tethered and wireless large-scale recordings based on movable volumetric three-dimensional (3D) multielectrode implants. This approach allowed us to isolate up to 1,800 units per animal and simultaneously record the extracellular activity of close to 500 cortical neurons, distributed across multiple cortical areas, in freely behaving rhesus monkeys. The method is expandable, in principle, to thousands of simultaneously recorded channels. It also allows increased recording longevity (5 consecutive years), and recording of a broad range of behaviors, e.g. social interactions, and BMI paradigms in freely moving primates. We propose that wireless large-scale recordings could have a profound impact on basic primate neurophysiology research, while providing a framework for the development and testing of clinically relevant neuroprostheses.

The activity in the contralateral primary motor cortex, dorsal premotor and supplementary motor area is modulated by performance gains

There is growing experimental evidence that the engagement of different brain areas in a given motor task may change with practice, although the specific brain activity patterns underlying different stages of learning, as defined by kinematic or dynamic performance indices, are not well understood. Here we studied the change in activation in motor areas during practice on sequences of handwriting-like trajectories, connecting four target points on a digitizing table “as rapidly and as accurately as possible” while lying inside an fMRI scanner. Analysis of the subjects' pooled kinematic and imaging data, acquired at the beginning, middle, and end of the training period, revealed no correlation between the amount of activation in the contralateral M1, PM (dorsal and ventral), supplementary motor area (SMA), preSMA, and Posterior Parietal Cortex (PPC) and the amount of practice per-se. Single trial analysis has revealed that the correlation between the amount of activation in the contralateral M1 and trial mean velocity was partially modulated by performance gains related effects, such as increased hand motion smoothness. Furthermore, it was found that the amount of activation in the contralateral preSMA increased when subjects shifted from generating straight point-to-point trajectories to their spatiotemporal concatenation into a smooth, curved trajectory. Altogether, our results indicate that the amount of activation in the contralateral M1, PMd, and preSMA during the learning of movement sequences is correlated with performance gains and that high level motion features (e.g., motion smoothness) may modulate, or even mask correlations between activity changes and low-level motion attributes (e.g., trial mean velocity).

Motor cortical control of movement speed with implications for brain-machine interface control

Motor cortex plays a substantial role in driving movement, yet the details underlying this control remain unresolved. We analyzed the extent to which movement-related information could be extracted from single-trial motor cortical activity recorded while monkeys performed center-out reaching. Using information theoretic techniques, we found that single units carry relatively little speed-related information compared with direction-related information. This result is not mitigated at the population level: simultaneously recorded population activity predicted speed with significantly lower accuracy relative to direction predictions. Furthermore, a unit-dropping analysis revealed that speed accuracy would likely remain lower than direction accuracy, even given larger populations. These results suggest that the instantaneous details of single-trial movement speed are difficult to extract using commonly assumed coding schemes. This apparent paucity of speed information takes particular importance in the context of brain-machine interfaces (BMIs), which rely on extracting kinematic information from motor cortex. Previous studies have highlighted subjects' difficulties in holding a BMI cursor stable at targets. These studies, along with our finding of relatively little speed information in motor cortex, inspired a speed-dampening Kalman filter (SDKF) that automatically slows the cursor upon detecting changes in decoded movement direction. Effectively, SDKF enhances speed control by using prevalent directional signals, rather than requiring speed to be directly decoded from neural activity. SDKF improved success rates by a factor of 1.7 relative to a standard Kalman filter in a closed-loop BMI task requiring stable stops at targets. BMI systems enabling stable stops will be more effective and user-friendly when translated into clinical applications.

Reprogramming movements: extraction of motor intentions from cortical ensemble activity when movement goals change

The ability to inhibit unwanted movements and change motor plans is essential for behaviors of advanced organisms. The neural mechanisms by which the primate motor system rejects undesired actions have received much attention during the last decade, but it is not well understood how this neural function could be utilized to improve the efficiency of brain-machine interfaces (BMIs). Here we employed linear discriminant analysis (LDA) and a Wiener filter to extract motor plan transitions from the activity of ensembles of sensorimotor cortex neurons. Two rhesus monkeys, chronically implanted with multielectrode arrays in primary motor (M1) and primary sensory (S1) cortices, were overtrained to produce reaching movements with a joystick toward visual targets upon their presentation. Then, the behavioral task was modified to include a distracting target that flashed for 50, 150, or 250 ms (25% of trials each) followed by the true target that appeared at a different screen location. In the remaining 25% of trials, the initial target stayed on the screen and was the target to be approached. M1 and S1 neuronal activity represented both the true and distracting targets, even for the shortest duration of the distracting event. This dual representation persisted both when the monkey initiated movements toward the distracting target and then made corrections and when they moved directly toward the second, true target. The Wiener filter effectively decoded the location of the true target, whereas the LDA classifier extracted the location of both targets from ensembles of 50–250 neurons. Based on these results, we suggest developing real-time BMIs that inhibit unwanted movements represented by brain activity while enacting the desired motor outcome concomitantly.