Summary Engaged decision-makers align spontaneous movements www.biorxiv.org
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Engaged decision-makers show inversely correlated movement timing and trajectory with performance, while task-independent movements indicate engagement and increased neural activity, highlighting the need for further research on the causal link between movements, internal states, and neural activity.
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Key Points
- Engaged decision-makers align spontaneous movements to task demands.
- Movement timing and trajectory, specifically task-aligned movements and task independent movements (TIM), were inversely correlated with performance.
- TIM represents movements that occur independently of task events and indicate periods of engagement or disengagement in the task.
- TIM is informative about the internal state of engagement and has a major impact on neural activity.
- Uninstructed movements have a major impact on neural activity, particularly in primary sensory cortices.
- TIM was inversely related to decision-making performance in head-fixed mice and freely moving rats.
- Neural activity was higher in the engaged state compared to the disengaged state, particularly during the delay period.
- The magnitude of task-independent movements (TIM) was inversely related to performance, indicating that movements independent of task events were associated with a distracted state.
Summaries
90 word summary
Engaged decision-makers align movements to task demands, with movement timing and trajectory inversely correlated with performance. Task-independent movements (TIM) indicate engagement or disengagement, with increased neural activity during engaged states. Uninstructed movements impact neural activity during disengaged states. TIM is inversely related to decision-making performance and internal states of engagement. Widefield calcium imaging reveals higher neural activity in engaged states, particularly during the delay period. Further research is needed on subcortical structures, manipulation experiments, and cell-type specific measurements to establish a causal link between movements, internal states, and neural activity.
173 word summary
Engaged decision-makers align spontaneous movements to task demands, with movement timing and trajectory inversely correlated with performance. Task-independent movements (TIM) indicated periods of engagement or disengagement in the task, with the engaged state associated with increased neural activity during the delay period. Uninstructed movements had a greater impact on neural activity during the disengaged state. TIM was found to be inversely related to decision-making performance in mice and rats, and closely related to internal states of engagement. Widefield calcium imaging revealed higher neural activity in the engaged state, particularly during the delay period, with uninstructed movements accounting for more cortical activity in the disengaged state. The study emphasizes the importance of further research on subcortical structures, manipulation experiments, and cell-type specific measurements to establish a causal link between movements, internal states, and neural activity. The imaging setup used two lenses and fluorescence captured using excitation light at two different wavelengths, with data aligned and preprocessed using image registration and singular value decomposition. A linear encoding model was used to analyze the neural data.
404 word summary
Engaged decision-makers align spontaneous movements to task demands. The study aimed to understand the relationship between animal movements and behavioral performance during sensory-guided decision-making. The researchers found that movement timing and trajectory, specifically task-aligned movements and task independent movements (TIM), were inversely correlated with performance. TIM indicated periods of engagement or disengagement in the task. The engaged state was associated with increased neural activity, particularly during the delay period. Uninstructed movements had a greater impact on neural activity during the disengaged state. Overall, the findings suggest that TIM is informative about the internal state of engagement and that movements and state together have a major impact on neural activity.
Animals constantly make spontaneous movements, even in uncluttered environments, which have a major impact on neural activity. However, the relationship between these uninstructed movements and decision-making performance is poorly understood. Previous studies have shown that the timing of movements changes as animals transition from novices to experts. Higher levels of task-relevant motor variability have also been associated with faster learning. To uncover this relationship, the researchers developed a new method called TIM to quantify movement variance. They found that TIM was inversely related to decision-making performance in mice and rats. The researchers also used a hidden Markov model to uncover internal states of engagement during decision-making, finding that TIM was closely related to these states. Pupil diameter showed a weak correlation with decision-making performance compared to TIM.
The researchers also analyzed neural activity during decision-making using widefield calcium imaging. They found that neural activity was higher in the engaged state compared to the disengaged state, particularly during the delay period. Uninstructed movements accounted for more cortical activity in the disengaged state. The study also found that the magnitude of task-independent movements (TIM) was inversely related to performance, indicating a distracted state. The temporal alignment of stereotyped movement patterns, rather than their frequency, was predictive of task engagement. The study calls for further research on subcortical structures, manipulation experiments, and cell-type specific measurements to establish a causal link between movements, internal states, and neural activity.
The imaging setup used a camera with two lenses and fluorescence was captured using excitation light at two different wavelengths. The imaging data was aligned to a common coordinate framework and preprocessed using image registration and singular value decomposition. A linear encoding model was used to analyze the neural data, which included task- and movement-related variables. The model was fit using
785 word summary
Engaged decision-makers align spontaneous movements to task demands. The study aimed to understand the relationship between animal movements and behavioral performance during sensory-guided decision-making. The researchers found that the magnitude of animal movements did not strongly correlate with task performance. However, they discovered that movement timing and trajectory, specifically task-aligned movements and task independent movements (TIM), were inversely correlated with performance. TIM, which represents movements that occur independently of task events, indicated periods of engagement or disengagement in the task. The researchers confirmed this by comparing TIM to latent behavioral states recovered by a hidden Markov model. They found that TIM was highest when animals were disengaged. Additionally, they examined the impact of these behavioral states on neural activity and found that the engaged state was associated with increased activity, particularly during the delay period. However, uninstructed movements had a greater impact on neural activity during the disengaged state. Overall, the findings suggest that TIM is informative about the internal state of engagement and that movements and state together have a major impact on neural activity.
Animals make spontaneous movements constantly, even in uncluttered environments. These uninstructed movements have a major impact on neural activity, particularly in primary sensory cortices. However, the relationship between uninstructed movements and decision-making performance is poorly understood. Previous studies have shown that the timing of movements changes as animals transition from novices to experts. Higher levels of task-relevant motor variability have also been associated with faster learning. The timing and preponderance of movements might fluctuate within an experimental session. It is unclear how to quantify movement data to uncover the relationship between movements and decision-making performance.
To address these questions, the researchers developed a new method to quantify movement variance called Task Independent Movements (TIM). They found that TIM was inversely related to decision-making performance in head-fixed mice and freely moving rats. They also used a generalized linear model coupled with a hidden Markov model to uncover the internal states of engagement during decision-making. The engaged state was associated with strong reliance on sensory stimuli, while the disengaged states showed weaker dependence. The researchers found that TIM was closely related to these behavioral states. Additionally, they analyzed pupil diameter as a metric of arousal and found a weak correlation with decision-making performance compared to TIM.
Finally, the researchers analyzed neural activity measured with widefield calcium imaging during decision-making. They found that neural activity was higher in the engaged state compared to the disengaged state, particularly during
Differences in how the brain encodes task variables, instructed movements, and uninstructed movements were explored in this study. Linear encoding models were fitted to neural data for each state, including engaged and disengaged states. The models accounted for considerable variance in each state. Neural activity was found to differ between engaged and disengaged states, with elevated activity in the engaged state, particularly during the delay period. Uninstructed movements accounted for more cortical activity in the disengaged state compared to the engaged state. This suggests that uninstructed movements have a larger impact on neural activity when animals are disengaged. The study also found a link between decision-making performance, internal state, and animal movements. The magnitude of task-independent movements (TIM) was inversely related to performance, indicating that movements independent of task events were associated with a distracted state. The findings suggest that the temporal alignment of stereotyped movement patterns, rather than their frequency, is predictive of task engagement. The study also compared its results to previous research on movements and neural activity, highlighting the relationship between movements and cognition. The authors noted that movements should be considered based on their relationship to task events to determine their impact on cognition. The study calls for further research on subcortical structures, manipulation experiments to establish a causal link between movements and internal state, and cell-type specific measurements. The authors also emphasize the need for studies in other animal species to better understand the relationship between movements, internal states, and neural activity. Overall, the study provides insights into the relationship between movements, internal states, and decision-making performance.
The imaging setup used a camera with two lenses, and fluorescence was captured using excitation light at two different wavelengths. The imaging data was aligned to a common coordinate framework and preprocessed using image registration and singular value decomposition. A linear encoding model was used to analyze the neural data, which included task- and movement-related variables. The model was fit using ridge regression, and the regularization penalty was determined using marginal maximum likelihood estimation. The encoding model was fit separately for engaged and disengaged trials, and sessions with insufficient trial numbers were discarded. The summary also includes a list of references.
The summary is organized into separate paragraphs to distinguish distinct ideas.