James Ashe

Cortical control of motor sequences

The neural substrate of sequence learning is well known. However, we lack a clear understanding of the detailed functional properties of many of the areas involved. The reason for this discrepancy lies, in part, in the fact that two types of processes, implicit and explicit, subserve motor sequence learning, and these often interact with each other. The most significant recent advances have been the elucidation of the very complex relationships between medial motor areas and the temporal and ordinal control of sequences, and the demonstration that motor cortex is an important site for sequence storage and production. The challenge for the future will be to develop a coherent and internally consistent theory of sequence control.

On the relations between single cell activity in the motor cortex and the direction and magnitude of three-dimensional static isometric force

The role of the motor cortex in the control of both the direction and magnitude of dynamic force, when both are allowed to vary in 3D, is not known. We recorded the activity of 504 cells in the motor cortex of two monkeys during a behavioral task in which the subjects used a manipulandum to vary both the direction and magnitude of isometric force in 3D space. The majority (86%) of cells active in the task related to the direction, a tiny number (2.5%) to the magnitude, and a moderate number (11.5%) to both the direction and magnitude of dynamic force output. Finally, we compared neural activity in the same population of neurons during dynamic and static force output and found that the relations to direction and magnitude were very similar in both epochs. Our results indicate that during dynamic force production, cells in the motor cortex are primarily concerned with specifying the direction of force. The magnitude signal is not prominent in motor cortex neurons, and in general, magnitude and direction of force are specified together. Furthermore, the data suggest that the control of static and dynamic motor systems is based, to a great extent, on a common control process.

The Evaluation of Preprocessing Choices in Single-Subject BOLD fMRI Using NPAIRS Performance Metrics

This work proposes an alternative to simulation-based receiver operating characteristic (ROC) analysis for assessment of fMRI data analysis methodologies. Specifically, we apply the rapidly developing nonparametric prediction, activation, influence, and reproducibility resampling (NPAIRS) framework to obtain cross-validation-based model performance estimates of prediction accuracy and global reproducibility for various degrees of model complexity. We rely on the concept of an analysis chain meta-model in which all parameters of the preprocessing steps along with the final statistical model are treated as estimated model parameters. Our ROC analog, then, consists of plotting prediction vs. reproducibility results as curves of model complexity for competing meta-models. Two theoretical underpinnings are crucial to utilizing this new validation technique. First, we explore the relationship between global signal-to-noise and our reproducibility estimates as derived previously. Second, we submit our model complexity curves in the prediction versus reproducibility space as reflecting classic bias-variance tradeoffs. Among the particular analysis chains considered, we found little impact in performance metrics with alignment, some benefit with temporal detrending, and greatest improvement with spatial smoothing.

Anticipatory activity in primary motor cortex codes memorized movement sequences.

Movement sequences, defined both by the component movements and by the serial order in which they are produced, are fundamental building blocks of motor behavior. The serial order of sequence production is strongly encoded in medial motor areas. It is not known to what extent sequences are further elaborated or encoded in primary motor cortex. Here, we describe cells in the primary motor cortex of the monkey that show anticipatory activity exclusively related to a specific memorized sequence of upcoming movements. In addition, the injection of muscimol, a GABA agonist, into motor cortex resulted in an increase in the error rate during sequence production, without concomitant effects on nonsequenced motor performance. Our results challenge the role of medial motor areas in the control of well-practiced movement sequences and suggest that motor cortex contains a complete apparatus for the planning and production of this complex behavior.

Motor cortical activity preceding a memorized movement trajectory with an orthogonal bend

Two monkeys were trained to make an arm movement with an orthogonal bend, first up and then to the left (⌝), following a waiting period. They held a two-dimensional manipulandum over a spot of light at the center of a planar working surface. When this light went off, the animals were required to hold the manipulandum there for 600–700 ms and then move the handle up and to the left to receive a liquid reward. There were no external signals concerning the “go” time or the trajectory of the movement. It was hypothesized that during that period signs of directional processing relating to the upcoming movement would be identified in the motor cortex. Following 20 trials of the memorized movement trajectory, 40 trials of visually triggered movements in radially arranged directions were performed. The activity of 137 single cells in the motor cortex was recorded extracellularly during performance of the task. It was found that 62.8% of the cells changed activity during the memorized waiting period. During the waiting period, the population vector (Georgopoulos et al. 1983, 1984) began to grow approximately 130 ms after the center light was turned off; it pointed first in the direction of the second part of the memorized movement (←) and then rotated clockwise towards the direction of the initial part of the movement (↑). These findings indicate processing of directional information during the waiting period preceding the memorized movement. This conclusion was supported by the results of experiments in ten human subjects, who performed the same memorized movement (⌝). In 10% of the trials a visual stimulus was shown in radially arranged directions in which the subjects had to move; this stimulus was shown at 0, 200, and 400 ms from the time the center light was turned off. We found that as the interval increased the reaction time shortened for the visual stimulus that was in the same direction as the upward component of the memorized movement.

Neural correlates of encoding and expression in implicit sequence learning

In the domain of motor learning it has been difficult to separate the neural substrate of encoding from that of change in performance. Consequently, it has not been clear whether motor effector areas participate in learning or merely modulate changes in performance. Here, using a variant of the serial reaction time task that dissociated these two factors, we report that encoding during procedural motor learning does engage cortical motor areas and can be characterized by distinct early and late encoding phases. The highest correlation between activation and subsequent changes in motor performance was seen in the motor cortex during early encoding, and in the basal ganglia during the late encoding phase. Our results show that rapid encoding during procedural motor learning involves several distinct processes, and is represented primarily within motor system structures.

The Effect of Stimulus-Response Compatibility on Cortical Motor Activation

Stimulus-response compatibility (SRC) is a general term describing the relationship between a triggering stimulus and its associated motor response. The relationship between stimulus and response can be manipulated at the level of the set of stimulus and response characteristics (set-level) or at the level of the mapping between the individual elements of the stimulus and response sets (element-level). We used functional magnetic resonance imaging (fMRI) to investigate the effects of SRC on functional activation in cortical motor areas. Using behavioral tasks to separately evaluate set- and element-level compatibility, and their interaction, we measured the volume of functional activation in 11 cortical motor areas, in the anterior frontal cortex, and in the superior temporal lobe. Element-level compatibility effects were associated with significant activation in the pre-supplementary motor area (preSMA), the dorsal (PMd) and ventral (PMv) premotor areas, and the parietal areas (inferior, superior, intraparietal sulcus, precuneus). The activation was lateralized to the right hemisphere for most of the areas. Set-level compatibility effects resulted in significant activation in the inferior frontal gyri, anterior cingulate and cingulate motor areas, the PMd, PMv, preSMA, the parietal areas (inferior, superior, intraparietal sulcus, precuneus), and in the superior temporal lobe. Activation in the majority of these areas was lateralized to the left hemisphere. Finally, there was an interaction between set and element-level compatibility in the middle and superior frontal gyri, in an area co-extensive with the dorsolateral prefrontal cortex, suggesting that this area provided the neural substrate for common processing stages, such as working memory and attention, which are engaged when both levels of SRC are manipulated at once.

Differential Effect of Reward and Punishment on Procedural Learning

Reward and punishment are potent modulators of associative learning in instrumental and classical conditioning. However, the effect of reward and punishment on procedural learning is not known. The striatum is known to be an important locus of reward-related neural signals and part of the neural substrate of procedural learning. Here, using an implicit motor learning task, we show that reward leads to enhancement of learning in human subjects, whereas punishment is associated only with improvement in motor performance. Furthermore, these behavioral effects have distinct neural substrates with the learning effect of reward being mediated through the dorsal striatum and the performance effect of punishment through the insula. Our results suggest that reward and punishment engage separate motivational systems with distinctive behavioral effects and neural substrates.

Effects of movement predictability on cortical motor activation

Humans have the ability to make motor responses to unpredictable visual stimuli, and do so as a matter of course on a daily basis. We used functional magnetic resonance imaging (fMRI) to examine the neural substrate of this behavior in six cortical motor areas. We found that five of these areas (premotor, cingulate, supplementary motor area, pre-supplementary motor area, and superior parietal lobule) showed increased activation in association with an unpredictable behavior compared to a predictable one; only the motor cortex remained unchanged. There was also a quantitative relation between the response time and functional activation in the premotor and cingulate cortex. There was less activation across all the motor areas with repetition of the motor tasks. With the exception of the pre-supplementary motor area, all areas were significantly lateralized, with a greater volume of activation in the hemisphere contralateral to the performing hand. In addition, a left hemisphere dominance was found in the activation of motor cortex and supplementary motor areas. Our results suggest that activation in motor areas is differentially and quantitatively related to higher order aspects of motor behavior such as movement predictability.

High Accuracy Decoding of Movement Target Direction in Non-Human Primates Based on Common Spatial Patterns of Local Field Potentials

Background The current development of brain-machine interface technology is limited, among other factors, by concerns about the long-term stability of single- and multi-unit neural signals. In addition, the understanding of the relation between potentially more stable neural signals, such as local field potentials, and motor behavior is still in its early stages. Methodology/Principal Findings We tested the hypothesis that spatial correlation patterns of neural data can be used to decode movement target direction. In particular, we examined local field potentials (LFP), which are thought to be more stable over time than single unit activity (SUA). Using LFP recordings from chronically implanted electrodes in the dorsal premotor and primary motor cortex of non-human primates trained to make arm movements in different directions, we made the following observations: (i) it is possible to decode movement target direction with high fidelity from the spatial correlation patterns of neural activity in both primary motor (M1) and dorsal premotor cortex (PMd); (ii) the decoding accuracy of LFP was similar to the decoding accuracy obtained with the set of SUA recorded simultaneously; (iii) directional information varied with the LFP frequency sub-band, being greater in low (0.3–4 Hz) and high (48–200 Hz) frequency bands than in intermediate bands; (iv) the amount of directional information was similar in M1 and PMd; (v) reliable decoding was achieved well in advance of movement onset; and (vi) LFP were relatively stable over a period of one week. Conclusions/Significance The results demonstrate that the spatial correlation patterns of LFP signals can be used to decode movement target direction. This finding suggests that parameters of movement, such as target direction, have a stable spatial distribution within primary motor and dorsal premotor cortex, which may be used for brain-machine interfaces.