Two distinct layer-specific dynamics of cortical ensembles during learning of a motor task

Corticothalamic neurons in motor cortex have a permissive role in motor execution

The primary motor cortex (M1) is a central hub for motor learning and execution. M1 is composed of heterogeneous cell types with varying relationships to movement. Here, we tagged active neurons at different stages of motor task performance in mice and characterized cell type composition. We identified corticothalamic neurons (M1CT) as consistently enriched with training progression. Using two-photon calcium imaging, we found that M1CT activity is largely suppressed during movement, and this negative correlation augments with training. Increasing M1CT activity through closed-loop optogenetic manipulations during forelimb movement significantly hinders execution, an effect that became stronger with training. Similar manipulations, however, had little effect on locomotion. In contrast, M1 corticospinal neurons positively correlate with movement, with an increase during training. We uncovered that M1CT neurons suppress corticospinal activity via feedforward inhibition, also scaling with training. These results identify a permissive role of corticothalamic neurons in movement execution through disinhibition of corticospinal neurons.

Whether or not to act is determined by distinct signals from motor thalamus and orbitofrontal cortex to secondary motor cortex

"To act or not to act" is a fundamental decision made in daily life. However, it is unknown how the relevant signals are transmitted to the secondary motor cortex (M2), which is the cortical origin of motor initiation. Here, we found that in a decision-making task in male mice, inputs from the thalamus to M2 positively regulated the action while inputs from the lateral part of the orbitofrontal cortex (LO) negatively regulated it. The motor thalamus that received the basal ganglia outputs transmitted action value-related signals to M2 regardless of whether the animal acted or not. By contrast, a large subpopulation of LO inputs showed decreased activity before and during the action, regardless of the action value. These results suggest that M2 integrates the positive signal of the action value from the motor thalamus with the negative action-biased signal from the LO to finally determine whether to act or not.

Laminar Architecture of a Decision Circuit in Orbitofrontal Cortex

During economic choice, different neurons in orbitofrontal cortex (OFC) encode individual offer values, the binary choice outcome, and the chosen value. Previous work suggests that these cell groups form a decision circuit, but the anatomical organization of this circuit is poorly understood. Using calcium imaging, we recorded from layer 2/3 (L2/3) and layer 5 (L5) of mice choosing between juice flavors. Decision variables were differentially represented across layers: juice-specific offer values and their spatial configuration were predominant in L2/3, while spatial offer values, chosen side, and chosen value were predominant in L5. Within each layer, functional cell groups were organized in clusters. The temporal dynamics of neural signals in the two layers indicated a combination of feed-forward and feed-back processes, and pointed to L5 as the locus for winner-take-all value comparison. These results reveal that economic decisions rely on a complex architecture distributed across layers of OFC.

Tooth loss-associated neuroplasticity of mastication-related motor cortical neurons

OBJECTIVES

The cerebral cortex contains neurons that play a pivotal role in controlling rhythmic masticatory jaw movements. However, the population characteristics of individual cortical neuronal activity during mastication and the impact of tooth loss on these characteristics remain unclear. Thus, in this study, we aimed to determine the activity patterns of mastication-related motor cortical neurons elicited during mastication and examine the effects of tooth extraction on neuronal activity using two-photon Ca2+ imaging in head-restrained awake mice.

METHODS

GCaMP6f-expressing adeno-associated virus serotype 1 was injected into the left motor cortex (centered 2 mm anterior and 2 mm lateral to the bregma) and electromyography (EMG) electrodes were implanted into the right masseter and digastric muscles of 6-8-week-old C57BL/6j mice. Three weeks after surgery, in vivo two-photon Ca2+ imaging of layer (L) 2/3 neurons and simultaneous EMG recordings were performed during the masticatory sequence.

RESULTS

Mastication induced a remarkable increase in the power and frequency of Ca2+ responses and correlated with majority of the mastication-related motor cortical L2/3 neuronal activity. These mastication-related changes correlated with the activity of neurons with low baseline activity that occurred before mastication. Extraction of the right upper three molars caused clear neuroplastic changes in the mastication-induced Ca2+ activity of L2/3 neurons.

CONCLUSIONS

Our in vivo imaging study provides new insights into the neuronal basis of tooth loss-induced cortical neuroplasticity, and suggests a possible therapeutic approach for oral sensorimotor dysfunction.

VTA projections to M1 are essential for reorganization of layer 2-3 network dynamics underlying motor learning

The primary motor cortex (M1) is crucial for motor skill learning. Previous studies demonstrated that skill acquisition requires dopaminergic VTA (ventral-tegmental area) signaling in M1, however little is known regarding the effect of these inputs at the neuronal and network levels. Using dexterity task, calcium imaging, chemogenetic inhibiting, and geometric data analysis, we demonstrate VTA-dependent reorganization of M1 layer 2-3 during motor learning. While average activity and average functional connectivity of layer 2-3 network remain stable during learning, activity kinetics, correlational configuration of functional connectivity, and average connectivity strength of layer 2-3 neurons gradually transform towards an expert configuration. Additionally, sensory tone representation gradually shifts to success-failure outcome signaling. Inhibiting VTA dopaminergic inputs to M1 during learning, prevents all these changes. Our findings demonstrate dopaminergic VTA-dependent formation of outcome signaling and new connectivity configuration of the layer 2-3 network, supporting reorganization of the M1 network for storing new motor skills.

Site-specific seeding of Lewy pathology induces distinct pre-motor cellular and dendritic vulnerabilities in the cortex

Circuit-based biomarkers distinguishing the gradual progression of Lewy pathology across synucleinopathies remain unknown. Here, we show that seeding of α-synuclein preformed fibrils in mouse dorsal striatum and motor cortex leads to distinct prodromal-phase cortical dysfunction across months. Our findings reveal that while both seeding sites had increased cortical pathology and hyperexcitability, distinct differences in electrophysiological and cellular ensemble patterns were crucial in distinguishing pathology spread between the two seeding sites. Notably, while beta-band spike-field-coherence reflected a significant increase beginning in Layer-5 and then spreading to Layer-2/3, the rate of entrainment and the propensity of stochastic beta-burst dynamics was markedly seeding location-specific. This beta dysfunction was accompanied by gradual superficial excitatory ensemble instability following cortical, but not striatal, preformed fibrils injection. We reveal a link between Layer-5 dendritic vulnerabilities and translaminar beta event dysfunction, which could be used to differentiate symptomatically similar synucleinopathies.

Millisecond-scale motor coding precedes sensorimotor learning in songbirds

A key goal of the nervous system in young animals is to learn motor skills. Songbirds learn to sing as juveniles, providing a unique opportunity to identify the neural correlates of skill acquisition. Prior studies have shown that spike rate variability in vocal motor cortex decreases substantially during song acquisition, suggesting a transition from rate-based neural control to the millisecond-precise motor codes known to underlie adult vocal performance. By distinguishing how the ensemble of spike patterns fired by cortical neurons (the "neural vocabulary") and the relationship between spike patterns and song acoustics (the "neural code") change during song acquisition, we quantified how vocal control changes across learning in juvenile Bengalese finches. We found that despite the expected drop in rate variability (a learning-related change in spike vocabulary), the precision of the neural code in the youngest singers is the same as in adults, with 1-2 ms variations in spike timing transduced into quantifiably different behaviors. In contrast, fluctuations in firing rates on longer timescales fail to affect the motor output in both juvenile and adult animals. The consistent presence of millisecond-scale motor coding during changing levels of spike rate and behavioral variability suggests that learning-related changes in cortical activity reflect the brain's changing its spiking vocabulary to better match the underlying motor code, rather than a change in the precision of the code itself.

Dynamic lateralization in contralateral-projecting corticospinal neurons during motor learning

Understanding the adaptability of the motor cortex in response to bilateral motor tasks is crucial for advancing our knowledge of neural plasticity and motor learning. Here we aim to investigate the dynamic lateralization of contralateral-projecting corticospinal neurons (cpCSNs) during such tasks. Utilizing in vivo two-photon calcium imaging, we observe cpCSNs in mice performing a "left-right" lever-press task. Our findings reveal heterogeneous populational dynamics in cpCSNs: a marked decrease in activity during ipsilateral motor learning, in contrast to maintained activity during contralateral motor learning. Notably, individual cpCSNs show dynamic shifts in engagement with ipsilateral and contralateral movements, displaying an evolving pattern of activation over successive days. It suggests that cpCSNs exhibit adaptive changes in activation patterns in response to ipsilateral and contralateral movements, highlighting a flexible reorganization during motor learning This reconfiguration underscores the dynamic nature of cortical lateralization in motor learning and offers insights for neuromotor rehabilitation.

ARViS: a bleed-free multi-site automated injection robot for accurate, fast, and dense delivery of virus to mouse and marmoset cerebral cortex

Genetically encoded fluorescent sensors continue to be developed and improved. If they could be expressed across multiple cortical areas in non-human primates, it would be possible to measure a variety of spatiotemporal dynamics of primate-specific cortical activity. Here, we develop an Automated Robotic Virus injection System (ARViS) for broad expression of a biosensor. ARViS consists of two technologies: image recognition of vasculature structures on the cortical surface to determine multiple injection sites without hitting them, and robotic control of micropipette insertion perpendicular to the cortical surface with 50 μm precision. In mouse cortex, ARViS sequentially injected virus solution into 100 sites over a duration of 100 min with a bleeding probability of only 0.1% per site. Furthermore, ARViS successfully achieved 266-site injections over the frontoparietal cortex of a female common marmoset. We demonstrate one-photon and two-photon calcium imaging in the marmoset frontoparietal cortex, illustrating the effective expression of biosensors delivered by ARViS.

Dynamics of directional motor tuning in the primate premotor and primary motor cortices during sensorimotor learning

Sensorimotor learning requires reorganization of neuronal activity in the premotor cortex (PM) and primary motor cortex (M1). To reveal PM- and M1-specific reorganization in a primate, we conducted calcium imaging in common marmosets while they learned a two-target reaching (pull/push) task after mastering a one-target reaching (pull) task. Throughout learning of the two-target reaching task, the dorsorostral PM (PMdr) showed peak activity earlier than the dorsocaudal PM (PMdc) and M1. During learning, the reaction time in pull trials increased and correlated strongly with the peak timing of PMdr activity. PMdr showed decreasing representation of newly introduced (push) movement, whereas PMdc and M1 maintained high representation of pull and push movements. Many task-related neurons in PMdc and M1 exhibited a strong preference to either movement direction. PMdc neurons dynamically switched their preferred direction depending on their performance in push trials in the early learning stage, whereas M1 neurons stably retained their preferred direction and high similarity of preferred direction between neighbors. These results suggest that in primate sensorimotor learning, dynamic directional motor tuning in PMdc converts the sensorimotor association formed in PMdr to the stable and specific motor representation of M1.

Cortico-basal ganglia plasticity in motor learning

One key function of the brain is to control our body's movements, allowing us to interact with the world around us. Yet, many motor behaviors are not innate but require learning through repeated practice. Among the brain's motor regions, the cortico-basal ganglia circuit is particularly crucial for acquiring and executing motor skills, and neuronal activity in these regions is directly linked to movement parameters. Cell-type-specific adaptations of activity patterns and synaptic connectivity support the learning of new motor skills. Functionally, neuronal activity sequences become structured and associated with learned movements. On the synaptic level, specific connections become potentiated during learning through mechanisms such as long-term synaptic plasticity and dendritic spine dynamics, which are thought to mediate functional circuit plasticity. These synaptic and circuit adaptations within the cortico-basal ganglia circuitry are thus critical for motor skill acquisition, and disruptions in this plasticity can contribute to movement disorders.

Decoding Continuous Forelimb Kinematics in Mice Using Single-Photon Calcium Imaging

In the natural environment, most spontaneous behaviors involve compound movements consisting of tightly coupled sequences of sub-movements. Motor commands are issued from motor cortex to downstream areas and effectors, suggesting that the neural representations in the primary motor cortex for different sub-movements should be separable. Previous research has limited insights into how neural system regulates the interplay between the sequential nature and separability of such representations. In this study, we categorized forelimb behaviors during the mouse water-reaching task, employing single-photon calcium signals to classify forelimb postures. We discovered distinct neural patterns associated with different actions during the mouse water-reaching task. The frame-by-frame prediction of water-reaching trajectories revealed the overall continuity of neural changes during the grasping action. By utilizing different time windows for neural decoding of forepaws states, we speculated on the potential temporal overlap of neural patterns during continuous movements. This overlap may underlie the rapid and smooth transitions between sub-movements.

Activity-Dependent Remodeling of Corticostriatal Axonal Boutons During Motor Learning

Motor skill learning induces long-lasting synaptic plasticity at not only the inputs, such as dendritic spines1-4, but also at the outputs to the striatum of motor cortical neurons5,6. However, very little is known about the activity and structural plasticity of corticostriatal axons during learning in the adult brain. Here, we used longitudinal in vivo two-photon imaging to monitor the activity and structure of thousands of corticostriatal axonal boutons in the dorsolateral striatum in awake mice. We found that learning a new motor skill induces dynamic regulation of axonal boutons. The activities of motor corticostriatal axonal boutons exhibited selectivity for rewarded movements (RM) and un-rewarded movements (UM). Strikingly, boutons on the same axonal branches showed diverse responses during behavior. Motor learning significantly increased the fraction of RM boutons and reduced the heterogeneity of bouton activities. Moreover, motor learning-induced profound structural dynamism in boutons. By combining structural and functional imaging, we identified that newly formed axonal boutons are more likely to exhibit selectivity for RM and are stabilized during motor learning, while UM boutons are selectively eliminated. Our results highlight a novel form of plasticity at corticostriatal axons induced by motor learning, indicating that motor corticostriatal axonal boutons undergo dynamic reorganization that facilitates the acquisition and execution of motor skills.

Refinement of efficient encodings of movement in the dorsolateral striatum throughout learning

The striatum is required for normal action selection, movement, and sensorimotor learning. Although action-specific striatal ensembles have been well documented, it is not well understood how these ensembles are formed and how their dynamics may evolve throughout motor learning. Here we used longitudinal 2-photon Ca2+ imaging of dorsal striatal neurons in head-fixed mice as they learned to self-generate locomotion. We observed a significant activation of both direct- and indirect-pathway spiny projection neurons (dSPNs and iSPNs, respectively) during early locomotion bouts and sessions that gradually decreased over time. For dSPNs, onset- and offset-ensembles were gradually refined from active motion-nonspecific cells. iSPN ensembles emerged from neurons initially active during opponent actions before becoming onset- or offset-specific. Our results show that as striatal ensembles are progressively refined, the number of active nonspecific striatal neurons decrease and the overall efficiency of the striatum information encoding for learned actions increases.

A combinatorial neural code for long-term motor memory

Motor skill repertoire can be stably retained over long periods, but the neural mechanism underlying stable memory storage remains poorly understood. Moreover, it is unknown how existing motor memories are maintained as new motor skills are continuously acquired. Here we tracked neural representation of learned actions throughout a significant portion of a mouse's lifespan, and we show that learned actions are stably retained in motor memory in combination with context, which protects existing memories from erasure during new motor learning. We used automated home-cage training to establish a continual learning paradigm in which mice learned to perform directional licking in different task contexts. We combined this paradigm with chronic two-photon imaging of motor cortex activity for up to 6 months. Within the same task context, activity driving directional licking was stable over time with little representational drift. When learning new task contexts, new preparatory activity emerged to drive the same licking actions. Learning created parallel new motor memories while retaining the previous memories. Re-learning to make the same actions in the previous task context re-activated the previous preparatory activity, even months later. At the same time, continual learning of new task contexts kept creating new preparatory activity patterns. Context-specific memories, as we observed in the motor system, may provide a solution for stable memory storage throughout continual learning. Learning in new contexts produces parallel new representations instead of modifying existing representations, thus protecting existing motor repertoire from erasure.

Top-Down and Bottom-Up Mechanisms of Motor Recovery Poststroke

Stroke remains a leading cause of disability. Motor recovery requires the interaction of top-down and bottom-up mechanisms, which reinforce each other. Injury to the brain initiates a biphasic neuroimmune process, which opens a window for spontaneous recovery during which the brain is particularly sensitive to activity. Physical activity during this sensitive period can lead to rapid recovery by potentiating anti-inflammatory and neuroplastic processes. On the other hand, lack of physical activity can lead to early closure of the sensitive period and downstream changes in muscles, such as sarcopenia, muscle stiffness, and reduced cardiovascular capacity, and blood flow that impede recovery.

Selective plasticity of layer 2/3 inputs onto distal forelimb controlling layer 5 corticospinal neurons with skilled grasp motor training

Layer 5 neurons of the neocortex receive their principal inputs from layer 2/3 neurons. We seek to identify the nature and extent of the plasticity of these projections with motor learning. Using optogenetic and viral intersectional tools to selectively stimulate distinct neuronal subsets in rat primary motor cortex, we simultaneously record from pairs of corticospinal neurons associated with distinct features of motor output control: distal forelimb vs. proximal forelimb. Activation of Channelrhodopsin2-expressing layer 2/3 afferents onto layer 5 in untrained animals produces greater monosynaptic excitation of neurons controlling the proximal forelimb. Following skilled grasp training, layer 2/3 inputs onto corticospinal neurons controlling the distal forelimb associated with skilled grasping become significantly stronger. Moreover, peak excitatory response amplitude nearly doubles while latency shortens, and excitatory-to-inhibitory latencies become significantly prolonged. These findings demonstrate distinct, highly segregated, and cell-specific plasticity of layer 2/3 projections during skilled grasp motor learning.

Specific connectivity optimizes learning in thalamocortical loops

Thalamocortical loops have a central role in cognition and motor control, but precisely how they contribute to these processes is unclear. Recent studies showing evidence of plasticity in thalamocortical synapses indicate a role for the thalamus in shaping cortical dynamics through learning. Since signals undergo a compression from the cortex to the thalamus, we hypothesized that the computational role of the thalamus depends critically on the structure of corticothalamic connectivity. To test this, we identified the optimal corticothalamic structure that promotes biologically plausible learning in thalamocortical synapses. We found that corticothalamic projections specialized to communicate an efference copy of the cortical output benefit motor control, while communicating the modes of highest variance is optimal for working memory tasks. We analyzed neural recordings from mice performing grasping and delayed discrimination tasks and found corticothalamic communication consistent with these predictions. These results suggest that the thalamus orchestrates cortical dynamics in a functionally precise manner through structured connectivity.

3D fluorescence imaging through scattering medium using transport of intensity equation and iterative phase retrieval

In this paper, we have proposed a method of three-dimensional (3D) fluorescence imaging through a scattering medium. The proposed method combines the numerical digital phase conjugation propagation after measurement of the complex amplitude distribution of scattered light waves by the transport of intensity equation (TIE) with followed iterative phase retrieval to achieve 3D fluorescence imaging through a scattering medium. In the experiment, we present the quantitative evaluation of the depth position of fluorescent beads. In addition, for time-lapse measurement, cell division of tobacco-cultured cells was observed. Numerical results presented the effective range of the phase amount in the scattering medium. From these results, the proposed method is capable of recovering images degraded by a thin scattering phase object beyond a small phase change approximation.

Cx3cr1 deficiency interferes with learning- and direct current stimulation-mediated neuroplasticity of the motor cortex

Microglia are essential contributors to synaptic transmission and stability and communicate with neurons via the fractalkine pathway. Transcranial direct current stimulation [(t)DCS], a form of non-invasive electrical brain stimulation, modulates cortical excitability and promotes neuroplasticity, which has been extensively demonstrated in the motor cortex and for motor learning. The role of microglia and their fractalkine receptor CX3CR1 in motor cortical neuroplasticity mediated by DCS or motor learning requires further elucidation. We demonstrate the effects of pharmacological microglial depletion and genetic Cx3cr1 deficiency on the induction of DCS-induced long-term potentiation (DCS-LTP) ex vivo. The relevance of microglia-neuron communication for DCS response and structural neuroplasticity underlying motor learning are assessed via 2-photon in vivo imaging. The behavioural consequences of impaired CX3CR1 signalling are investigated for both gross and fine motor learning. We show that DCS-mediated neuroplasticity in the motor cortex depends on the presence of microglia and is driven in part by CX3CR1 signalling ex vivo and provide the first evidence of microglia interacting with neurons during DCS in vivo. Furthermore, CX3CR1 signalling is required for motor learning and underlying structural neuroplasticity in concert with microglia interaction. Although we have recently demonstrated the microglial response to DCS in vivo, we now provide a link between microglial integrity and neuronal activity for the expression of DCS-dependent neuroplasticity. In addition, we extend the knowledge on the relevance of CX3CR1 signalling for motor learning and structural neuroplasticity. The underlying molecular mechanisms and the potential impact of DCS in rescuing CX3CR1 deficits remain to be addressed in the future.

How deep is the brain? The shallow brain hypothesis

Deep learning and predictive coding architectures commonly assume that inference in neural networks is hierarchical. However, largely neglected in deep learning and predictive coding architectures is the neurobiological evidence that all hierarchical cortical areas, higher or lower, project to and receive signals directly from subcortical areas. Given these neuroanatomical facts, today's dominance of cortico-centric, hierarchical architectures in deep learning and predictive coding networks is highly questionable; such architectures are likely to be missing essential computational principles the brain uses. In this Perspective, we present the shallow brain hypothesis: hierarchical cortical processing is integrated with a massively parallel process to which subcortical areas substantially contribute. This shallow architecture exploits the computational capacity of cortical microcircuits and thalamo-cortical loops that are not included in typical hierarchical deep learning and predictive coding networks. We argue that the shallow brain architecture provides several critical benefits over deep hierarchical structures and a more complete depiction of how mammalian brains achieve fast and flexible computational capabilities.

Regulation of lipid synthesis in myelin modulates neural activity and is required for motor learning

Brain function relies on both rapid electrical communication in neural circuitry and appropriate patterns or synchrony of neural activity. Rapid communication between neurons is facilitated by wrapping nerve axons with insulation by a myelin sheath composed largely of different lipids. Recent evidence has indicated that the extent of myelination of nerve axons can adapt based on neural activity levels and this adaptive myelination is associated with improved learning of motor tasks, suggesting such plasticity may enhance effective learning. In this study, we examined whether another aspect of myelin plasticity-changes in myelin lipid synthesis and composition-may also be associated with motor learning. We combined a motor learning task in mice with in vivo two-photon imaging of neural activity in the primary motor cortex (M1) to distinguish early and late stages of learning and then probed levels of some key myelin lipids using mass spectrometry analysis. Sphingomyelin levels were elevated in the early stage of motor learning while galactosylceramide levels were elevated in the middle and late stages of motor learning, and these changes were correlated across individual mice with both learning performance and neural activity changes. Targeted inhibition of oligodendrocyte-specific galactosyltransferase expression, the enzyme that synthesizes myelin galactosylceramide, impaired motor learning. Our results suggest regulation of myelin lipid composition could be a novel facet of myelin adaptations associated with learning.

Layer 5 Intratelencephalic Neurons in the Motor Cortex Stably Encode Skilled Movement

The primary motor cortex (M1) and the dorsal striatum play a critical role in motor learning and the retention of learned behaviors. Motor representations of corticostriatal ensembles emerge during motor learning. In the coordinated reorganization of M1 and the dorsal striatum for motor learning, layer 5a (L5a) which connects M1 to the ipsilateral and contralateral dorsal striatum, should be a key layer. Although M1 L5a neurons represent movement-related activity in the late stage of learning, it is unclear whether the activity is retained as a memory engram. Here, using Tlx3-Cre male transgenic mice, we conducted two-photon calcium imaging of striatum-projecting L5a intratelencephalic (IT) neurons in forelimb M1 during late sessions of a self-initiated lever-pull task and in sessions after 6 d of nontraining following the late sessions. We found that trained male animals exhibited stable motor performance before and after the nontraining days. At the same time, we found that M1 L5a IT neurons strongly represented the well-learned forelimb movement but not uninstructed orofacial movements. A subset of M1 L5a IT neurons consistently coded the well-learned forelimb movement before and after the nontraining days. Inactivation of M1 IT neurons after learning impaired task performance when the lever was made heavier or when the target range of the pull distance was narrowed. These results suggest that a subset of M1 L5a IT neurons continuously represent skilled movement after learning and serve to fine-tune the kinematics of well-learned movement.SIGNIFICANCE STATEMENT Motor memory persists even when it is not used for a while. IT neurons in L5a of the M1 gradually come to represent skilled forelimb movements during motor learning. However, it remains to be determined whether these changes persist over a long period and how these neurons contribute to skilled movements. Here, we show that a subset of M1 L5a IT neurons retain information for skilled forelimb movements even after nontraining days. Furthermore, suppressing the activity of these neurons during skilled forelimb movements impaired behavioral stability and adaptability. Our results suggest the importance of M1 L5a IT neurons for tuning skilled forelimb movements over a long period.

Activity-dependent organization of prefrontal hub-networks for associative learning and signal transformation

Associative learning is crucial for adapting to environmental changes. Interactions among neuronal populations involving the dorso-medial prefrontal cortex (dmPFC) are proposed to regulate associative learning, but how these neuronal populations store and process information about the association remains unclear. Here we developed a pipeline for longitudinal two-photon imaging and computational dissection of neural population activities in male mouse dmPFC during fear-conditioning procedures, enabling us to detect learning-dependent changes in the dmPFC network topology. Using regularized regression methods and graphical modeling, we found that fear conditioning drove dmPFC reorganization to generate a neuronal ensemble encoding conditioned responses (CR) characterized by enhanced internal coactivity, functional connectivity, and association with conditioned stimuli (CS). Importantly, neurons strongly responding to unconditioned stimuli during conditioning subsequently became hubs of this novel associative network for the CS-to-CR transformation. Altogether, we demonstrate learning-dependent dynamic modulation of population coding structured on the activity-dependent formation of the hub network within the dmPFC.

Cerebellar climbing fibers multiplex movement and reward signals during a voluntary movement task in mice

Cerebellar climbing fibers convey sensorimotor information and their errors, which are used for motor control and learning. Furthermore, they represent reward-related information. Despite such functional diversity of climbing fiber signals, it is still unclear whether each climbing fiber conveys the information of single or multiple modalities and how the climbing fibers conveying different information are distributed over the cerebellar cortex. Here we perform two-photon calcium imaging from cerebellar Purkinje cells in mice engaged in a voluntary forelimb lever-pull task and demonstrate that climbing fiber responses in 68% of Purkinje cells can be explained by the combination of multiple behavioral variables such as lever movement, licking, and reward delivery. Neighboring Purkinje cells exhibit similar climbing fiber response properties, form functional clusters, and share noise fluctuations of responses. Taken together, individual climbing fibers convey behavioral information on multiplex variables and are spatially organized into the functional modules of the cerebellar cortex.

Altered Thalamocortical Signaling in a Mouse Model of Parkinson's Disease

Activation of the primary motor cortex (M1) is important for the execution of skilled movements and motor learning, and its dysfunction contributes to the pathophysiology of Parkinson's disease (PD). A well-accepted idea in PD research, albeit not tested experimentally, is that the loss of midbrain dopamine leads to decreased activation of M1 by the motor thalamus. Here, we report that midbrain dopamine loss altered motor thalamus input in a laminar- and cell type-specific fashion and induced laminar-specific changes in intracortical synaptic transmission. Frequency-dependent changes in synaptic dynamics were also observed. Our results demonstrate that loss of midbrain dopaminergic neurons alters thalamocortical activation of M1 in both male and female mice, and provide novel insights into circuit mechanisms for motor cortex dysfunction in a mouse model of PD.SIGNIFICANCE STATEMENT Loss of midbrain dopamine neurons increases inhibition from the basal ganglia to the motor thalamus, suggesting that it may ultimately lead to reduced activation of primary motor cortex (M1). In contrast with this line of thinking, analysis of M1 activity in patients and animal models of Parkinson's disease report hyperactivation of this region. Our results are the first report that midbrain dopamine loss alters the input-output function of M1 through laminar and cell type specific effects. These findings support and expand on the idea that loss of midbrain dopamine reduces motor cortex activation and provide experimental evidence that reconciles reduced thalamocortical input with reports of altered activation of motor cortex in patients with Parkinson's disease.

Specific patterns of neural activity in the hippocampus after massed or distributed spatial training

Training with long inter-session intervals, termed distributed training, has long been known to be superior to training with short intervals, termed massed training. In the present study we compared c-Fos expression after massed and distributed training protocols in the Morris water maze to outline possible differences in the learning-induced pattern of neural activation in the dorsal CA1 in the two training conditions. The results demonstrate that training and time lags between learning opportunities had an impact on the pattern of neuronal activity in the dorsal CA1. Mice trained with the distributed protocol showed sustained neuronal activity in the postero-distal component of the dorsal CA1. In parallel, in trained mice we found more active cells that tended to constitute spatially restricted clusters, whose degree increased with the increase in the time lags between learning trials. Moreover, activated cell assemblies demonstrated increased stability in their spatial organization after distributed as compared to massed training or control condition. Finally, using a machine learning algorithm we found that differences in the number of c-Fos positive cells and their location in the dorsal CA1 could be predictive of the training protocol used. These results suggest that the topographic organization and the spatial location of learning activated cell assemblies might be critical to promote the increased stability of the memory trace induced by distributed training.

Cell-type-specific plasticity shapes neocortical dynamics for motor learning

Neocortical spiking dynamics control aspects of behavior, yet how these dynamics emerge during motor learning remains elusive. Activity-dependent synaptic plasticity is likely a key mechanism, as it reconfigures network architectures that govern neural dynamics. Here, we examined how the mouse premotor cortex acquires its well-characterized neural dynamics that control movement timing, specifically lick timing. To probe the role of synaptic plasticity, we have genetically manipulated proteins essential for major forms of synaptic plasticity, Ca2+/calmodulin-dependent protein kinase II (CaMKII) and Cofilin, in a region and cell-type-specific manner. Transient inactivation of CaMKII in the premotor cortex blocked learning of new lick timing without affecting the execution of learned action or ongoing spiking activity. Furthermore, among the major glutamatergic neurons in the premotor cortex, CaMKII and Cofilin activity in pyramidal tract (PT) neurons, but not intratelencephalic (IT) neurons, is necessary for learning. High-density electrophysiology in the premotor cortex uncovered that neural dynamics anticipating licks are progressively shaped during learning, which explains the change in lick timing. Such reconfiguration in behaviorally relevant dynamics is impeded by CaMKII manipulation in PT neurons. Altogether, the activity of plasticity-related proteins in PT neurons plays a central role in sculpting neocortical dynamics to learn new behavior.

Learning in a sensory cortical microstimulation task is associated with elevated representational stability

Sensory cortical representations can be highly dynamic, raising the question of how representational stability impacts learning. We train mice to discriminate the number of photostimulation pulses delivered to opsin-expressing pyramidal neurons in layer 2/3 of primary vibrissal somatosensory cortex. We simultaneously track evoked neural activity across learning using volumetric two-photon calcium imaging. In well-trained animals, trial-to-trial fluctuations in the amount of photostimulus-evoked activity predicted animal choice. Population activity levels declined rapidly across training, with the most active neurons showing the largest declines in responsiveness. Mice learned at varied rates, with some failing to learn the task in the time provided. The photoresponsive population showed greater instability both within and across behavioral sessions among animals that failed to learn. Animals that failed to learn also exhibited a faster deterioration in stimulus decoding. Thus, greater stability in the stimulus response is associated with learning in a sensory cortical microstimulation task.

Distinct frequencies balance segregation with interaction between different memory types within a prefrontal circuit

Once formed, the fate of memory is uncertain. Subsequent offline interactions between even different memory types (actions versus words) modify retention.^1,2,3,4,5,6 These interactions may occur due to different oscillations functionally linking together different memory types within a circuit.^{7,8,9,10,11,12,13} With memory processing driving the circuit, it may become less susceptible to external influences.¹⁴ We tested this prediction by perturbing the human brain with single pulses of transcranial magnetic stimulation (TMS) and simultaneously measuring the brain activity changes with electroencephalography (EEG^15,16,17). Stimulation was applied over brain areas that contribute to memory processing (dorsolateral prefrontal cortex, DLPFC; primary motor cortex, M1) at baseline and offline, after memory formation, when memory interactions are known to occur.^1,4,6,10,18 The EEG response decreased offline (compared with baseline) within the alpha/beta frequency bands when stimulation was applied to the DLPFC, but not to M1. This decrease exclusively followed memory tasks that interact, revealing that it was due specifically to the interaction, not task performance. It remained even when the order of the memory tasks was changed and so was present, regardless of how the memory interaction was produced. Finally, the decrease within alpha power (but not beta) was correlated with impairment in motor memory, whereas the decrease in beta power (but not alpha) was correlated with impairment in word-list memory. Thus, different memory types are linked to different frequency bands within a DLPFC circuit, and the power of these bands shapes the balance between interaction and segregation between these memories.

Motor training promotes both synaptic and intrinsic plasticity of layer V pyramidal neurons in the primary motor cortex

Layer V neurons in the primary motor cortex (M1) are important for motor skill learning. Since pretreatment of either CNQX or APV in rat M1 layer V impaired rotor rod learning, we analysed training-induced synaptic plasticity by whole-cell patch-clamp technique in acute brain slices. Rats trained for 1 day showed a decrease in small inhibitory postsynaptic current (mIPSC) frequency and an increase in the paired-pulse ratio of evoked IPSCs, suggesting a transient decrease in presynaptic GABA release in the early phase. Rats trained for 2 days showed an increase in miniature excitatory postsynaptic current (mEPSC) amplitudes/frequency and elevated AMPA/NMDA ratios, suggesting a long-term strengthening of AMPA receptor-mediated excitatory synapses. Importantly, rotor rod performance in trained rats was correlated with the mean mEPSC amplitude and the frequency obtained from that animal. In current-clamp analysis, 1-day-trained rats transiently decreased the current-induced firing rate, while 2-day-trained rats returned to pre-training levels, suggesting dynamic changes in intrinsic properties. Furthermore, western blot analysis of layer V detected decreased phosphorylation of Ser^408-409 in GABA_A receptor β₃ subunits in 1-day-trained rats, and increased phosphorylation of Ser⁸³¹ in AMPA receptor GluA1 subunits in 2-day-trained rats. Finally, live-imaging analysis of Thy1-YFP transgenic mice showed that the training rapidly recruited a substantial number of spines for long-term plasticity in M1 layer V neurons. Taken together, these results indicate that motor training induces complex and diverse plasticity in M1 layer V pyramidal neurons. KEY POINTS: Here we examined motor training-induced synaptic and intrinsic plasticity of layer V pyramidal neurons in the primary motor cortex. The training reduced presynaptic GABA release in the early phase, but strengthened AMPA receptor-mediated excitatory synapses in the later phase: acquired motor performance after training correlated with the strength of excitatory synapses rather than inhibitory synapses. As to the intrinsic property, the training transiently decreased the firing rate in the early phase, but returned to pre-training levels in the later phase. Western blot analysis detected decreased phosphorylation of Ser^408-409 in GABA_A receptor β₃ subunits in the acute phase, and increased phosphorylation of Ser⁸³¹ in AMPA receptor GluA1 subunits in the later phase. Live-imaging analysis of Thy1-YFP transgenic mice showed rapid and long-term spine plasticity in M1 layer V neurons, suggesting training-induced increases in self-entropy per spine.

Organization of Cortical and Thalamic Input to Inhibitory Neurons in Mouse Motor Cortex

Intracortical inhibition in motor cortex (M1) regulates movement and motor learning. If cortical and thalamic inputs target different inhibitory cell types in different layers, then these afferents may play different roles in regulating M1 output. Using mice of both sexes, we quantified input to two main classes of M1 interneurons, parvalbumin+ (PV+) cells and somatostatin+ (SOM+) cells, using monosynaptic rabies tracing. We then compared anatomic and functional connectivity based on synaptic strength from sensory cortex and thalamus. Functionally, each input innervated M1 interneurons with a unique laminar profile. Different interneuron types were excited in a distinct, complementary manner, suggesting feedforward inhibition proceeds selectively via distinct circuits. Specifically, somatosensory cortex (S1) inputs primarily targeted PV+ neurons in upper layers (L2/3) but SOM+ neurons in middle layers (L5). Somatosensory thalamus [posterior nucleus (PO)] inputs targeted PV+ neurons in middle layers (L5). In contrast to sensory cortical areas, thalamic input to SOM+ neurons was equivalent to that of PV+ neurons. Thus, long-range excitatory inputs target inhibitory neurons in an area and a cell type-specific manner, which contrasts with input to neighboring pyramidal cells. In contrast to feedforward inhibition providing generic inhibitory tone in cortex, circuits are selectively organized to recruit inhibition matched to incoming excitatory circuits.SIGNIFICANCE STATEMENT M1 integrates sensory information and frontal cortical inputs to plan and control movements. Although inputs to excitatory cells are described, the synaptic circuits by which these inputs drive specific types of M1 interneurons are unknown. Anatomical results with rabies tracing and physiological quantification of synaptic strength shows that two main classes of inhibitory cells (PV+ and SOM+ interneurons) both receive substantial cortical and thalamic input, in contrast to interneurons in sensory areas (where thalamic input strongly prefers PV+ interneurons). Further, each input studied targets PV+ and SOM+ interneurons in a different fashion, suggesting that separate, specific circuits exist for recruitment of feedforward inhibition.

Clinical neuroscience and neurotechnology: An amazing symbiosis

In the last decades, clinical neuroscience found a novel ally in neurotechnologies, devices able to record and stimulate electrical activity in the nervous system. These technologies improved the ability to diagnose and treat neural disorders. Neurotechnologies are concurrently enabling a deeper understanding of healthy and pathological dynamics of the nervous system through stimulation and recordings during brain implants. On the other hand, clinical neurosciences are not only driving neuroengineering toward the most relevant clinical issues, but are also shaping the neurotechnologies thanks to clinical advancements. For instance, understanding the etiology of a disease informs the location of a therapeutic stimulation, but also the way stimulation patterns should be designed to be more effective/naturalistic. Here, we describe cases of fruitful integration such as Deep Brain Stimulation and cortical interfaces to highlight how this symbiosis between clinical neuroscience and neurotechnology is closer to a novel integrated framework than to a simple interdisciplinary interaction.

Non-rigid Registration for Two-photon Imaging Using Triangulation and Piecewise Affine Transformation

Accurate and efficient non-rigid registration is important to investigate neural mechanisms in multi-session two-photon (2p) imaging across a few days. The 2p imaging recordings from different sessions usually possess certain complex misalignment or huge data variance due to relocation errors during experimental operations or brain recovery. Most of the reported neural image registration tools were able to solve the registration problem in the same session with small deformation. However, the registration of neural images across multi-sessions remains a challenge. In this study, we report the development of a non-rigid registration method for 2p imaging in mice based on image triangulation and piecewise affine transformation (TPAT) technologies. The TPAT method supported both automatic and semi-automatic operation types, and both showed great performance in the benchmark test of non-rigid neural image registration. The proposed method constitutes a step forward in promoting and accelerating discoveries from multi-session 2p imaging research.

Ca2+ imaging with two-photon microscopy to detect the disruption of brain function in mice administered neonicotinoid insecticides

Neonicotinoid pesticides are a class of insecticides that reportedly have harmful effects on bees and dragonflies, causing a reduction in their numbers. Neonicotinoids act as neuroreceptor modulators, and some studies have reported their association with neurodevelopmental disorders. However, the precise effect of neonicotinoids on the central nervous system has not yet been identified. Herein, we conducted in vivo Ca²⁺ imaging using a two-photon microscope to detect the abnormal activity of neuronal circuits in the brain after neonicotinoid application. The oral administration of acetamiprid (ACE) (20 mg/kg body weight (BW) in mature mice with a quantity less than the no-observed-adverse-effect level (NOAEL) and a tenth or half of the median lethal dose (LD₅₀) of nicotine (0.33 or 1.65 mg/kg BW, respectively), as a typical nicotinic acetylcholine receptor (nAChR) agonist, increased anxiety-like behavior associated with altered activities of the neuronal population in the somatosensory cortex. Furthermore, we detected ACE and its metabolites in the brain, 1 h after ACE administration. The results suggested that in vivo Ca²⁺ imaging using a two-photon microscope enabled the highly sensitive detection of neurotoxicant-mediated brain disturbance of nerves.

Deep-learning two-photon fiberscopy for video-rate brain imaging in freely-behaving mice

Scanning two-photon (2P) fiberscopes (also termed endomicroscopes) have the potential to transform our understanding of how discrete neural activity patterns result in distinct behaviors, as they are capable of high resolution, sub cellular imaging yet small and light enough to allow free movement of mice. However, their acquisition speed is currently suboptimal, due to opto-mechanical size and weight constraints. Here we demonstrate significant advances in 2P fiberscopy that allow high resolution imaging at high speeds (26 fps) in freely-behaving mice. A high-speed scanner and a down-sampling scheme are developed to boost imaging speed, and a deep learning (DL) algorithm is introduced to recover image quality. For the DL algorithm, a two-stage learning transfer strategy is established to generate proper training datasets for enhancing the quality of in vivo images. Implementation enables video-rate imaging at ~26 fps, representing 10-fold improvement in imaging speed over the previous 2P fiberscopy technology while maintaining a high signal-to-noise ratio and imaging resolution. This DL-assisted 2P fiberscope is capable of imaging the arousal-induced activity changes in populations of layer2/3 pyramidal neurons in the primary motor cortex of freely-behaving mice, providing opportunities to define the neural basis of behavior.

Elucidation of the neurological effects of clothianidin exposure at the no-observed-adverse-effect level (NOAEL) using two-photon microscopy in vivo imaging

Neonicotinoid pesticides (NNs) cause behavioral abnormalities in mammals, raising concerns about their effects on neural circuit activity. We herein examined the neurological effects of the NN clothianidin (CLO) by in vivo Ca²⁺ imaging using two-photon microscopy. Mice were fed the no-observed-adverse-effect-level (NOAEL) dose of CLO for 2 weeks and their neuronal activity in the primary somatosensory cortex (S1) was observed weekly for 2 weeks. CLO exposure caused a sustained influx of Ca²⁺ in neurons in the S1 2/3 layers, indicating hyperactivation of neurons. In addition, microarray gene expression analysis suggested the induction of neuroinflammation and changes in synaptic activity. These results demonstrate that exposure to the NOAEL dose of CLO can overactivate neurons and disrupt neuronal homeostasis.

The primary motor cortex: the hub of motor learning in rodents

The primary motor cortex, a dynamic center for overall motion control and decision making, undergoes significant alterations upon neural stimulation. Over the last few decades, data from numerous studies using rodent models have improved our understanding of the morphological and functional plasticity of the primary motor cortex. In particular, spatially specific formation of dendritic spines and their maintenance during distinct behaviors is considered crucial for motor learning. However, whether the modifications of specific synapses are associated with motor learning should be studied further. In this review, we summarized the findings of prior studies on the features and dynamics of the primary motor cortex in rodents.

Operating principles of the cerebral cortex as a six-layered network in primates: beyond the classic canonical circuit model

The cerebral cortex performs its computations with many six-layered fundamental units, collectively spreading along the cortical sheet. What is the local network structure and the operating dynamics of such a fundamental unit? Previous investigations of primary sensory areas revealed a classic "canonical" circuit model, leading to an expectation of similar circuit organization and dynamics throughout the cortex. This review clarifies the different circuit dynamics at play in the higher association cortex of primates that implements computation for high-level cognition such as memory and attention. Instead of feedforward processing of response selectivity through Layers 4 to 2/3 that the classic canonical circuit stipulates, memory recall in primates occurs in Layer 5/6 with local backward projection to Layer 2/3, after which the retrieved information is sent back from Layer 6 to lower-level cortical areas for further retrieval of nested associations of target attributes. In this review, a novel "dynamic multimode module (D3M)" in the primate association cortex is proposed, as a new "canonical" circuit model performing this operation.

Long-Range Monosynaptic Inputs Targeting Apical and Basal Dendrites of Primary Motor Cortex Deep Output Neurons

The primary motor cortex (M1) integrates various long-range signals from other brain regions for the learning and execution of goal-directed movements. How the different inputs target the distinct apical and basal dendrites of M1 pyramidal neurons is crucial in understanding the functions of M1, but the detailed connectivity pattern is still largely unknown. Here, by combining cre-dependent rabies virus tracing, layer-specific chemical retrograde tracing, optogenetic stimulation, and electrophysiological recording, we mapped all long-range monosynaptic inputs to M1 deep output neurons in layer 5 (L5) in mice. We revealed that most upstream areas innervate both dendritic compartments concurrently. These include the sensory cortices, higher motor cortices, sensory and motor thalamus, association cortices, as well as many subcortical nuclei. Furthermore, the dichotomous inputs arise mostly from spatially segregated neuronal subpopulations within an upstream nucleus, and even in the case of an individual cortical layer. Therefore, these input areas could serve as both feedforward and feedback sources albeit via different subpopulations. Taken together, our findings revealed a previously unknown and highly intricate synaptic input pattern of M1L5 neurons, which implicates that the dendritic computations carried out by these neurons during motor execution or learning are far more complicated than we currently understand.

Increasing human motor skill acquisition by driving theta-gamma coupling

Skill learning is a fundamental adaptive process, but the mechanisms remain poorly understood. Some learning paradigms, particularly in the memory domain, are closely associated with gamma activity that is amplitude modulated by the phase of underlying theta activity, but whether such nested activity patterns also underpin skill learning is unknown. Here, we addressed this question by using transcranial alternating current stimulation (tACS) over sensorimotor cortex to modulate theta–gamma activity during motor skill acquisition, as an exemplar of a non-hippocampal-dependent task. We demonstrated, and then replicated, a significant improvement in skill acquisition with theta–gamma tACS, which outlasted the stimulation by an hour. Our results suggest that theta–gamma activity may be a common mechanism for learning across the brain and provides a putative novel intervention for optimizing functional improvements in response to training or therapy.

Motor training improves coordination and anxiety in symptomatic Mecp2-null mice despite impaired functional connectivity within the motor circuit

Rett syndrome (RTT) is a severe neurodevelopmental disorder caused by loss of function of the X-linked methyl-CpG–binding protein 2 (MECP2). Several case studies report that gross motor function can be improved in children with RTT through treadmill walking, but whether the MeCP2-deficient motor circuit can support actual motor learning remains unclear. We used two-photon calcium imaging to simultaneously observe layer (L) 2/3 and L5a excitatory neuronal activity in the motor cortex (M1) while mice adapted to changing speeds on a computerized running wheel. Despite circuit hypoactivity and weakened functional connectivity across L2/3 and L5a, the Mecp2-null circuit’s firing pattern evolved with improved performance over 2 weeks. Moreover, trained mice became less anxious and lived 20% longer than untrained mice. Because motor deficits and anxiety are core symptoms of RTT, which is not diagnosed until well after symptom onset, these results underscore the benefit of motor learning.

Stimulus-dependent representational drift in primary visual cortex

To produce consistent sensory perception, neurons must maintain stable representations of sensory input. However, neurons in many regions exhibit progressive drift across days. Longitudinal studies have found stable responses to artificial stimuli across sessions in visual areas, but it is unclear whether this stability extends to naturalistic stimuli. We performed chronic 2-photon imaging of mouse V1 populations to directly compare the representational stability of artificial versus naturalistic visual stimuli over weeks. Responses to gratings were highly stable across sessions. However, neural responses to naturalistic movies exhibited progressive representational drift across sessions. Differential drift was present across cortical layers, in inhibitory interneurons, and could not be explained by differential response strength or higher order stimulus statistics. However, representational drift was accompanied by similar differential changes in local population correlation structure. These results suggest representational stability in V1 is stimulus-dependent and may relate to differences in preexisting circuit architecture of co-tuned neurons.

Twist-free ultralight two-photon fiberscope enabling neuroimaging on freely rotating/walking mice

Lightweight and head-mountable scanning nonlinear fiberscope technologies offer an exciting opportunity for enabling mechanistic exploration of ensemble neural activities with subcellular resolution on freely behaving rodents. The tether of the fiberscope, consisting of an optical fiber and scanner drive wires, however, restricts the mouse's movement and consequently precludes free rotation and limits the freedom of walking. Here we present the first twist-free two-photon fiberscope technology for enabling neuroimaging on freely rotating/walking mice. The technology equips a scanning fiberscope with active rotational tracking and compensation capabilities through an optoelectrical commutator (OEC) to allow the animal to rotate and walk in arbitrary patterns during two-photon fluorescence (TPF) imaging of neural activities. The OEC provides excellent optical coupling stability (<±1% fluctuation during rotation) and an extremely high torque sensitivity (<8 mN · m). In addition, the new technology is equipped with a custom grating and prism to effectively manage the temporal properties of the femtosecond excitation pulses through the fiber-optic system, which improved neuroimaging signal by more than 2X. This TPF fiberscope imaging platform has been tested for in vivo imaging, and the results demonstrate that it enables reliable recording of calcium dynamics of more than 50 neurons simultaneously in the motor cortices of freely behaving mice in a twist-free fashion. With active tracking function of the OEC enabled, we observed considerable increase in both behavior and neural activities in the motor cortices of the mice during freely behaving neuroimaging experiments.

Dendritic calcium signals in rhesus macaque motor cortex drive an optical brain-computer interface

Calcium imaging is a powerful tool for recording from large populations of neurons in vivo. Imaging in rhesus macaque motor cortex can enable the discovery of fundamental principles of motor cortical function and can inform the design of next generation brain-computer interfaces (BCIs). Surface two-photon imaging, however, cannot presently access somatic calcium signals of neurons from all layers of macaque motor cortex due to photon scattering. Here, we demonstrate an implant and imaging system capable of chronic, motion-stabilized two-photon imaging of neuronal calcium signals from macaques engaged in a motor task. By imaging apical dendrites, we achieved optical access to large populations of deep and superficial cortical neurons across dorsal premotor (PMd) and gyral primary motor (M1) cortices. Dendritic signals from individual neurons displayed tuning for different directions of arm movement. Combining several technical advances, we developed an optical BCI (oBCI) driven by these dendritic signalswhich successfully decoded movement direction online. By fusing two-photon functional imaging with CLARITY volumetric imaging, we verified that many imaged dendrites which contributed to oBCI decoding originated from layer 5 output neurons, including a putative Betz cell. This approach establishes new opportunities for studying motor control and designing BCIs via two photon imaging.

Cortical ensembles selective for context

Neural processing of sensory information is strongly influenced by context. For instance, cortical responses are reduced to predictable stimuli, while responses are increased to novel stimuli that deviate from contextual regularities. Such bidirectional modulation based on preceding sensory context is likely a critical component or manifestation of attention, learning, and behavior, yet how it arises in cortical circuits remains unclear. Using volumetric two-photon calcium imaging and local field potentials in primary visual cortex (V1) from awake mice presented with visual "oddball" paradigms, we identify both reductions and augmentations of stimulus-evoked responses depending, on whether the stimulus was redundant or deviant, respectively. Interestingly, deviance-augmented responses were limited to a specific subset of neurons mostly in supragranular layers. These deviance-detecting cells were spatially intermixed with other visually responsive neurons and were functionally correlated, forming a neuronal ensemble. Optogenetic suppression of prefrontal inputs to V1 reduced the contextual selectivity of deviance-detecting ensembles, demonstrating a causal role for top-down inputs. The presence of specialized context-selective ensembles in primary sensory cortex, modulated by higher cortical areas, provides a circuit substrate for the brain's construction and selection of prediction errors, computations which are key for survival and deficient in many psychiatric disorders.

Pain induces stable, active microcircuits in the somatosensory cortex that provide a therapeutic target

Sustained neuropathic pain from injury or inflammation remains a major burden for society. Rodent pain models have informed some cellular mechanisms increasing neuronal excitability within the spinal cord and primary somatosensory cortex (S1), but how activity patterns within these circuits change during pain remains unclear. We have applied multiphoton in vivo imaging and holographic stimulation to examine single S1 neuron activity patterns and connectivity during sustained pain. Following pain induction, there is an increase in synchronized neuronal activity and connectivity within S1, indicating the formation of pain circuits. Artificially increasing neuronal activity and synchrony using DREADDs reduced pain thresholds. The expression of N-type voltage-dependent Ca²⁺ channel subunits in S1 was increased after pain induction, and locally blocking these channels reduced both the synchrony and allodynia associated with inflammatory pain. Targeting these S1 pain circuits, via inhibiting N-type Ca²⁺ channels or other approaches, may provide ways to reduce inflammatory pain.

Intrinsic Disruption of the M1 Cortical Network in a Mouse Model of Parkinson's Disease

BACKGROUND

Parkinson's disease (PD) disrupts motor performance by affecting the basal ganglia system. Yet, despite the critical position of the primary motor cortex in linking basal ganglia computations with motor performance, its contribution to motor disability in PD is largely unknown. The objective of this study was to characterize the role of the primary motor cortex in PD-related motor disability.

METHODS

Two-photon calcium imaging and optogenetic stimulation of primary motor cortex neurons was done during performance of a dexterous reach-to-grasp motor task in control and 6-hydroxydopamine-induced PD mice.

RESULTS

Experimental PD disrupted performance of the reach-to-grasp motor task and especially initiation of the task, which was partially restored by optogenetic activation of the primary motor cortex. Two-photon calcium imaging during task performance revealed experimental-PD affected the primary motor cortex in a cell-type-specific manner. It suppressed activation of output layer 5 pyramidal tract neurons, with greater effects on freeze versus nonfreeze trials. In contrast, it did not attenuate the initial movement-related activation response of layer 2/3 pyramidal neurons while diminishing the late inhibitory phase of their response. At the network level, experimental PD disrupted movement-related population dynamics of the layer 5 pyramidal tract network while almost not affecting the dynamics of the layer 2/3 neuronal population. It also disrupted short- and long-term robustness and stability of the pyramidal tract subnetwork, with reduced intertrial temporal accuracy and diminished reproducibility of motor parameter encoding and temporal recruitment of the output pyramidal tract neurons over repeated daily sessions.

CONCLUSIONS

Experimental PD disrupts both external driving and intrinsic properties of the primary motor cortex. Motor disability in experimental PD results primarily from the inability to generate robust and stable output motor sequences in the parkinsonian primary motor cortex output layer 5 pyramidal tract subnetwork. © 2021 International Parkinson and Movement Disorder Society.

The Quest for the Hippocampal Memory Engram: From Theories to Experimental Evidence

More than a century after Richard Semon's theoretical proposal of the memory engram, technological advancements have finally enabled experimental access to engram cells and their functional contents. In this review, we summarize theories and their experimental support regarding hippocampal memory engram formation and function. Specifically, we discuss recent advances in the engram field which help to reconcile two main theories for how the hippocampus supports memory formation: The Memory Indexing and Cognitive Map theories. We also highlight the latest evidence for engram allocation mechanisms through which memories can be linked or separately encoded. Finally, we identify unanswered questions for future investigations, through which a more comprehensive understanding of memory formation and retrieval may be achieved.