Neuroscientists aim to understand how the primary motor cortex (M1) can regulate precise movements while supporting behavioral exploration that encounters consistent errors. While consistency in the environment can help animals learn and automate highly reliable actions, they must remain flexible to adapt to environmental changes. In a new report now published in Nature Communications, Sravani Kondapavulur and a research team in neural engineering, at the University of California, San Francisco, U.S., developed a reach-to-grasp task in rats to monitor the neural variability of the primary motor cortex (M1) and dorsolateral striatum (DLS) regions. The results indicated how the motor and striatal areas transitioned between two modes by generating a reliable neural pattern for automatic and precise movements, compared to variable neural patterning observed during behavioral exploration.
How do movement circuits in our brain support both automatic action and flexible movement exploration?
In this work, primary author and MD Ph.D. candidate Sravani Kondapavulur, along with the research team of Associate Professor Karunesh Ganguly at UCSF, described the movement circuits underlying behavioral flexibility in our brain. "Every day, most people use learned movements to accomplish daily tasks, such as turning on lights in a room or reaching for and grasping a coffee mug from a cabinet," she said.
"These movements are often automatic—produced in a fast, accurate, and consistent manner without much overt thought. Yet, a skill should also remain flexible to readily adjust to changes in the environment, such as moving to a different home with alternate light switch and cabinet placement." Since the process of automatic action and flexible movement are facilitated by circuits in our brain, Kondapavulur et al sought to examine the underlying mechanisms of the process in an animal model. "We first overtrained rats to reach and grasp for a food reward in a singular location. We then moved the reward to a second, nearby location and observed how they re-learned where to retrieve the pellet," she said.
Experimental food reward relocation
During the experiments, the team was specifically interested in the underlying role of M1 (primary motor cortex) and DLS (dorsolateral striatum) to modify skills, while still largely maintaining the original action. They accomplished this by "recording brain activity from both the primary motor area (M1) and the downstream motor area (DLS)." Kondapavulur further evaluated their findings: "We found that re-learning was a multi-day process, with many errors of reaching to the old location early on." She continued, "interestingly, on the day with the greatest breakdown of automatic movement errors," they noticed "a switch in M1 and DLS brain activity from consistent patterns during the task, to significantly increased variability from trial to trial."
The team notably observed a close association between the established behavioral exploration; transitioning from the highly predictable ensemble activation in the two neural regions of interest, to a variable state in both regions. Kondapavulur et al. continued the experiments for subsequent days to highlight how modifying an automatic skill was a multi-day process.
Re-establishing behavioral flexibility, in time
The scientists next sought to understand the neural correlates of re-establishing behavioral flexibility. They observed a loss of the previously stable neural spiking behavior relationship across the two regions, and increased neural variability, which coincided with goal-directed behavioral explorations, and behavioral changes during the switch process. According to Kondapavulur et al, while examining a potential link between variable neural activity and the process of behavioral exploration, they showed how the "timing of maximal 'communication' between the two regions was no longer consistently associated with timing of the reaching behavior." Further experiments from stimulation in M1 showed that "consistent versus variable timing of electrical activity in the primary motor area could produce correspondingly consistent and variable movements."
Shared neural activity
In its neural architecture, the primary motor cortex and dorsolateral striatum regions (M1 and DLS) are structurally monosynaptically connected; while DLS also receives inputs from a variety of other cortical and subcortical regions. Kondapavulur et al therefore explored if, despite the loss of consistent timing to the task, the population spiking remained correlated to each other in the two regions. They accomplished this by examining cross-area communication between the two neural regions and how the areas changed during variable sessions via canonical correlation analysis to represent maximally correlated activity across areas, to identify shared neural activity. They found that while communication axes could still be identified during the variable state, the maximum shared activity was no longer consistently reach-related, also demonstrating time-related variability.
Outlook
The team wrote: "We found that transitioning from automatic, consistent movements to enable flexible exploration involved a transition from consistent to variable motor area activity." They found the outcome to be significant since "it demonstrates another distinct method of movement learning, separate from novel skill learning, such as playing the piano, when compared to the process of adaptation, i.e., updating fast movements in the face of errors."
In this way, Sravani Kondapavulur and colleagues sought to understand the underlying basis of behavioral flexibility during automatic performance of a complex motor skill. They showed that neural regions of the primary motor cortex (M1) in tandem with dorsolateral striatum (DLS) regions enabled flexible transitions between behaviorally rigid and exploratory states. The team explored the behavioral flexibility of reach and grasp with a rodent model at a new location in a multiday process. The work outlined the relation of a motor skill and a habit to show how automaticity or unconscious performance of an action were applicable to both instances. The outcomes support the underlying basis of motor brain activity during the proposed actions.
More information:
Sravani Kondapavulur et al, Transition from predictable to variable motor cortex and striatal ensemble patterning during behavioral exploration, Nature Communications (2022). DOI: 10.1038/s41467-022-30069-1
Andrew J. Peters et al, Emergence of reproducible spatiotemporal activity during motor learning, Nature (2014). DOI: 10.1038/nature13235
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