Pyramidal cell types drive functionally distinct cortical activity patterns during decision-making

Understanding how cortical circuits generate complex behavior requires investigating the cell types that comprise them. Functional differences across pyramidal neuron (PyN) types have been observed within cortical areas, but it is not known whether these local differences extend throughout the cortex, nor whether additional differences emerge when larger-scale dynamics are considered. We used genetic and retrograde labeling to target pyramidal tract, intratelencephalic and corticostriatal projection neurons and measured their cortex-wide activity. Each PyN type drove unique neural dynamics, both at the local and cortex-wide scales. Cortical activity and optogenetic inactivation during an auditory decision task revealed distinct functional roles. All PyNs in parietal cortex were recruited during perception of the auditory stimulus, but, surprisingly, pyramidal tract neurons had the largest causal role. In frontal cortex, all PyNs were required for accurate choices but showed distinct choice tuning. Our results reveal that rich, cell-type-specific cortical dynamics shape perceptual decisions

Single-trial neural dynamics are dominated by richly varied movements.

When experts are immersed in a task, do their brains prioritize task-related activity? Most efforts to understand neural activity during well-learned tasks focus on cognitive computations and task-related movements. We wondered whether task-performing animals explore a broader movement landscape and how this impacts neural activity. We characterized movements using video and other sensors and measured neural activity using widefield and two-photon imaging. Cortex-wide activity was dominated by movements, especially uninstructed movements not required for the task. Some uninstructed movements were aligned to trial events. Accounting for them revealed that neurons with similar trial-averaged activity often reflected utterly different combinations of cognitive and movement variables. Other movements occurred idiosyncratically, accounting for trial-by-trial fluctuations that are often considered 'noise'. This held true throughout task-learning and for extracellular Neuropixels recordings that included subcortical areas. Our observations argue that animals execute expert decisions while performing richly varied, uninstructed movements that profoundly shape neural activity

Cortex-wide decision circuits are shaped by distinct classes of excitatory pyramidal neurons

Understanding how cortical circuits generate complex behavior requires investigating the cell types that comprise them. Here, much effort has been focused on inhibitory neuron types but the functional roles of distinct classes of excitatory pyramidal neurons (PyNs) are less well un-derstood. We, therefore, used widefield imaging to measure the cortex-wide activity of distinct PyN types and investigated their functional role in mice that performed an auditory decision-making task. We used two mouse lines, expressing the calcium indicator GCaMP6s in two major PyN types: FezF2 for pyramidal-tract (PT) and PlexinD1 for intratelencephalic (IT) neurons. Using dimen-sionality-reduction methods, we isolated cortex-wide activity patterns of PT and IT neurons and compared them to EMX mice with GCaMP6s-expression in all PyNs. We found major PyN-spe-cific differences in complexity and spatial layout of cortical activity patterns, both at the local and mesoscale, suggesting the existence of specialized subcircuits. We also found PyN-specific functional differences during decision-making. Sensory responses were largest in sensory, parietal and frontal cortex but each PyN type showed pronounced dif-ferences in cortical localization and spatial specificity. The same was true for choice-related ac-tivity: A choice decoder revealed ramping, contralateral choice-selective activity in parts of frontal cortex of EMX and PT mice whereas IT mice showed ipsilateral choice signals. Using an inter-sectional viral strategy, we found that this inverse choice tuning in IT was most pronounced in corticostriatal projection (CStr) neurons. Lastly, we used optogenetic inhibition to causally test the importance of PyN-types for decision-making. Inactivating parietal cortex disrupted sensory processing, with the strongest effect in PT neurons. In frontal cortex all PyN-types reduced ani-mal performance, suggesting that they are equally involved in choice formation and execution. Our work reveals PyN-specific, cortex-wide dynamics and strongly supports the view that local circuits throughout the cortex perform parallel computations, even within the same cortical layer

Engaged decision-makers align spontaneous movements to stereotyped task demands

Neural activity during sensory-guided decision-making is strongly modulated by animal movements. Although the impact of movements on neural activity is now well-documented, the relationship between these movements and behavioral performance remains unclear. To understand this relationship, we first tested whether the magnitude of animal movements (assessed with posture analysis of 28 individual body parts) was correlated with performance on a perceptual decision-making task. No strong relationship was present, suggesting that task performance is not affected by the magnitude of movements. We then tested if performance instead depends on movement timing and trajectory. We partitioned the movements into two groups: task-aligned movements that were well predicted by task events (such as the onset of the sensory stimulus or choice) and task independent movement (TIM) that occurred independently of task events. TIM had a reliable, inverse correlation with performance in head-restrained mice and freely moving rats. This argues that certain movements, defined by their timing and trajectories relative to task events, might indicate periods of engagement or disengagement in the task. To confirm this, we compared TIM to the latent behavioral states recovered by a hidden Markov model with Bernoulli generalized linear model observations (GLM-HMM) and found these, again, to be inversely correlated. Finally, we examined the impact of these behavioral states on neural activity measured with widefield calcium imaging. The engaged state was associated with widespread increased activity, particularly during the delay period. However, a linear encoding model could account for more overall variance in neural activity in the disengaged state. Our analyses demonstrate that this is likely because uninstructed movements had a greater impact on neural activity during disengagement. Taken together, these 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

Engaged decision-makers align spontaneous movements to stereotyped task demands

Neural activity during sensory-guided decision-making is strongly modulated by animal movements. Although the impact of movements on neural activity is now well-documented, the relationship between these movements and behavioral performance remains unclear. To understand this relationship, we first tested whether the magnitude of animal movements (assessed with posture analysis of 28 individual body parts) was correlated with performance on a perceptual decision-making task. No strong relationship was present, suggesting that task performance is not affected by the magnitude of movements. We then tested if performance instead depends on movement timing and trajectory. We partitioned the movements into two groups: task-aligned movements that were well predicted by task events (such as the onset of the sensory stimulus or choice) and task independent movement (TIM) that occurred independently of task events. TIM had a reliable, inverse correlation with performance in head-restrained mice and freely moving rats. This argues that certain movements, defined by their timing and trajectories relative to task events, might indicate periods of engagement or disengagement in the task. To confirm this, we compared TIM to the latent behavioral states recovered by a hidden Markov model with Bernoulli generalized linear model observations (GLM-HMM) and found these, again, to be inversely correlated. Finally, we examined the impact of these behavioral states on neural activity measured with widefield calcium imaging. The engaged state was associated with widespread increased activity, particularly during the delay period. However, a linear encoding model could account for more overall variance in neural activity in the disengaged state. Our analyses demonstrate that this is likely because uninstructed movements had a greater impact on neural activity during disengagement. Taken together, these 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

Chronic, cortex-wide imaging of specific cell populations during behavior.

Measurements of neuronal activity across brain areas are important for understanding the neural correlates of cognitive and motor processes such as attention, decision-making and action selection. However, techniques that allow cellular resolution measurements are expensive and require a high degree of technical expertise, which limits their broad use. Wide-field imaging of genetically encoded indicators is a high-throughput, cost-effective and flexible approach to measure activity of specific cell populations with high temporal resolution and a cortex-wide field of view. Here we outline our protocol for assembling a wide-field macroscope setup, performing surgery to prepare the intact skull and imaging neural activity chronically in behaving, transgenic mice. Further, we highlight a processing pipeline that leverages novel, cloud-based methods to analyze large-scale imaging datasets. The protocol targets laboratories that are seeking to build macroscopes, optimize surgical procedures for long-term chronic imaging and/or analyze cortex-wide neuronal recordings. The entire protocol, including steps for assembly and calibration of the macroscope, surgical preparation, imaging and data analysis, requires a total of 8 h. It is designed to be accessible to laboratories with limited expertise in imaging methods or interest in high-throughput imaging during behavior

Chronic, cortex-wide imaging of specific cell populations during behavior

Measurements of neuronal activity across brain areas are important for understanding the neural correlates of cognitive and motor processes such as attention, decision-making and action selection. However, techniques that allow cellular resolution measurements are expensive and require a high degree of technical expertise, which limits their broad use. Wide-field imaging of genetically encoded indicators is a high-throughput, cost-effective and flexible approach to measure activity of specific cell populations with high temporal resolution and a cortex-wide field of view. Here we outline our protocol for assembling a wide-field macroscope setup, performing surgery to prepare the intact skull and imaging neural activity chronically in behaving, transgenic mice. Further, we highlight a processing pipeline that leverages novel, cloud-based methods to analyze large-scale imaging datasets. The protocol targets laboratories that are seeking to build macroscopes, optimize surgical procedures for long-term chronic imaging and/or analyze cortex-wide neuronal recordings. The entire protocol, including steps for assembly and calibration of the macroscope, surgical preparation, imaging and data analysis, requires a total of 8 h. It is designed to be accessible to laboratories with limited expertise in imaging methods or interest in high-throughput imaging during behavior

Pyramidal cell types drive functionally distinct cortical activity patterns during decision-making

Understanding how cortical circuits generate complex behavior requires investigating the cell types that comprise them. Functional differences across pyramidal neuron (PyN) types have been observed within cortical areas, but it is not known whether these local differences extend throughout the cortex, nor whether additional differences emerge when larger-scale dynamics are considered. We used genetic and retrograde labeling to target pyramidal tract, intratelencephalic and corticostriatal projection neurons and measured their cortex-wide activity. Each PyN type drove unique neural dynamics, both at the local and cortex-wide scales. Cortical activity and optogenetic inactivation during an auditory decision task revealed distinct functional roles. All PyNs in parietal cortex were recruited during perception of the auditory stimulus, but, surprisingly, pyramidal tract neurons had the largest causal role. In frontal cortex, all PyNs were required for accurate choices but showed distinct choice tuning. Our results reveal that rich, cell-type-specific cortical dynamics shape perceptual decisions