Uncovering the Shared Neural Dynamics of Animal Behavior

A Comparative Analysis of Monkey and Mouse Motor Cortex

Understanding the neural basis of behavior is a fundamental goal of neuroscience. Researchers have long sought to uncover the intricate relationship between brain activity and the actions of animals. In a groundbreaking study, scientists have now made significant progress in this endeavor by revealing the shared neural dynamics underlying motor behavior in monkeys and mice. By analyzing the activity of neurons in the motor cortex of these animals, researchers have discovered striking similarities in the patterns of brain activity that give rise to coordinated movements. This research not only sheds light on the fundamental principles of motor control but also opens up new possibilities for understanding the neural basis of behavior across species.

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Training and Behavioral Tasks

Monkeys:

The study involved training four monkeys (monkeys C, M, J, and T) to perform reaching movements using a planar manipulandum. The monkeys were trained on two different tasks: a two-dimensional center-out reaching task and a more complex random target sequential reaching task. In the center-out task, the monkeys were required to move their hand to the center of the workspace and then reach out to one of eight outer targets. An auditory cue signaled the monkeys to initiate the reach. In the random target task, the monkeys had to make four consecutive reaches to random targets within a defined workspace. The monkeys received liquid rewards for successfully completing the tasks.

Mice:

Four mice were trained to perform a forelimb reaching and pulling task. In each trial, the mice had to reach and pull a joystick positioned near their initial hand position. The joystick appeared in one of two positions, and the mice had to self-initiate a reach to the joystick and pull it inwards to receive a liquid reward. The joystick had different weights, adding an additional level of complexity to the task.

Neural Recordings

Monkeys:

The researchers implanted 96-channel Utah electrode arrays in the primary motor cortex (M1) or dorsal premotor cortex (PMd) of the monkeys. Neural activity was recorded during the behavioral tasks using the Cerebus system. The recordings were then processed and analyzed to identify putative single neurons and multi-unit activity. The researchers focused on the latent dynamics of the neural activity, which were estimated using principal component analysis (PCA) and canonical correlation analysis (CCA).

Mice:

The mice underwent a brief surgery to implant a headplate, and neural activity was recorded using a neuropixels probe. The recorded data were preprocessed and analyzed to identify putative single units in the primary motor cortex and dorsolateral striatum. Similar to the monkey study, the researchers examined the latent dynamics of the neural activity using PCA and CCA.

Aligning Latent Dynamics and Behavioral Correlation

The researchers aligned the latent dynamics of the neural activity across different animals using CCA. They found that the aligned latent dynamics were highly correlated between animals, indicating a shared neural code for motor behavior. Importantly, the strength of the correlation was significantly higher than what would be expected by chance, demonstrating the preservation of latent dynamics across animals. Furthermore, the degree of preservation of the latent dynamics was positively correlated with the similarity of behavioral performance between animals.

Decoding Analysis

To test the behavioral relevance of the aligned latent dynamics, the researchers trained recurrent neural network models to predict hand trajectories based on the latent dynamics. They found that the models trained on the aligned latent dynamics achieved high predictive accuracy for hand trajectories, even when tested on data from different animals. This demonstrated that the aligned latent dynamics contained information about the behavioral output of the animals.

Control Analyses

To ensure the robustness of their findings, the researchers conducted several control analyses. They aligned random behavioral windows and generated surrogate neural data to establish lower-bound controls. They also aligned the topological structure of the neural population activity to examine the contribution of static features to the preservation of latent dynamics. Additionally, they performed control analyses on the numbers of conditions and neurons to demonstrate the generalizability of their results.

Conclusion:

This groundbreaking study has revealed the shared neural dynamics underlying motor behavior in monkeys and mice. By aligning the latent dynamics of neural activity across animals, the researchers have demonstrated the preservation of these dynamics and their correlation with behavioral performance. These findings provide valuable insights into the fundamental principles of motor control and have implications for understanding the neural basis of behavior across species. The research opens up new avenues for investigating the neural mechanisms underlying complex behaviors and may have applications in the development of novel therapeutic strategies for motor disorders.


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