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A sizable fraction of granule cells convey information about the expectation of reward, with different populations responding to reward delivery, anticipation and omission, with some responses evolving over time with learning. Reward response in granule cells Classical theories suggest that granule cells in the cerebellum carry sensory and motor signals, enabling downstream Purkinje cells to sense fine contextual changes relating to movement. Using two-photon calcium imaging in behaving mice, Liqun Luo and colleagues also show that a sizable fraction of granule cells convey information about the expectation of reward. Different populations responded to reward delivery, anticipation and omission and some responses evolved over time with learning. The discovery of reward-related signals in granule cells has implications for both models of sensorimotor learning and of cognitive processing in the cerebellum. The human brain contains approximately 60 billion cerebellar granule cells 1 , which outnumber all other brain neurons combined. Classical theories posit that a large, diverse population of granule cells allows for highly detailed representations of sensorimotor context, enabling downstream Purkinje cells to sense fine contextual changes 2 , 3 , 4 , 5 , 6 . Although evidence suggests a role for the cerebellum in cognition 7 , 8 , 9 , 10 , granule cells are known to encode only sensory 11 , 12 , 13 and motor 14 context. Here, using two-photon calcium imaging in behaving mice, we show that granule cells convey information about the expectation of reward. Mice initiated voluntary forelimb movements for delayed sugar-water reward. Some granule cells responded preferentially to reward or reward omission, whereas others selectively encoded reward anticipation. Reward responses were not restricted to forelimb movement, as a Pavlovian task evoked similar responses. Compared to predictable rewards, unexpected rewards elicited markedly different granule cell activity despite identical stimuli and licking responses. In both tasks, reward signals were widespread throughout multiple cerebellar lobules. Tracking the same granule cells over several days of learning revealed that cells with reward-anticipating responses emerged from those that responded at the start of learning to reward delivery, whereas reward-omission responses grew stronger as learning progressed. The discovery of predictive, non-sensorimotor encoding in granule cells is a major departure from the current understanding of these neurons and markedly enriches the contextual information available to postsynaptic Purkinje cells, with important implications for cognitive processing in the cerebellum.

Unlike most vertebrate limbs, the axolotl limb regenerates the skeleton after amputation. Dermal and interstitial fibroblasts have been thought to provide sources for skeletal regeneration, but it has been unclear whether preexisting stem cells or dedifferentiation of fibroblasts formed the blastema. Gerber et al. developed transgenic reporter animals to compare periskeletal cell and fibroblast contributions to regeneration. Callus-forming periskeletal cells extended existing bone, but fibroblasts built new limb segments. Single-cell transcriptomics and Brainbow-based lineage tracing revealed the lack of a preexisting stem cell. Instead, the heterogeneous population of fibroblasts lost their adult features to form a multipotent skeletal progenitor expressing the embryonic limb program. Science , this issue p. eaaq0681 Deconstructing cell composition, reconstructing lineage relationships, and tracing tissue reprogramming in limb regeneration are explored. Amputation of the axolotl forelimb results in the formation of a blastema, a transient tissue where progenitor cells accumulate prior to limb regeneration. However, the molecular understanding of blastema formation had previously been hampered by the inability to identify and isolate blastema precursor cells in the adult tissue. We have used a combination of Cre-loxP reporter lineage tracking and single-cell messenger RNA sequencing (scRNA-seq) to molecularly track mature connective tissue (CT) cell heterogeneity and its transition to a limb blastema state. We have uncovered a multiphasic molecular program where CT cell types found in the uninjured adult limb revert to a relatively homogenous progenitor state that recapitulates an embryonic limb bud–like phenotype including multipotency within the CT lineage. Together, our data illuminate molecular and cellular reprogramming during complex organ regeneration in a vertebrate.

How the motor cortex controls movement remains a fundamental question in neuroscience. Although somatosensory input is thought to influence motor cortex activity and the execution of voluntary movements, its role in driving motor cortex activity during voluntary behavior remains unclear. To address this, we performed whole-cell recordings from motor cortex neurons in mice during self-initiated, voluntary forelimb movements, either with intact somatosensory input or transection of the sensory nerves innervating the forelimb. In the absence of somatosensation, mice were still able to perform forelimb movements, including reaches, but these movements were significantly slower and more prolonged. Membrane potential recordings showed that cortical state changes were centrally generated, whereas external somatosensory input drives motor cortical activity before movement onset, curtails synaptic input during reaching to a hyperpolarized reversal potential value, and shapes membrane potential dynamics correlated with limb kinematics. Together, these findings demonstrate that somatosensory inputs play a central role in shaping motor cortex activity and its control of limb movement.

The brainstem is a key centre in the control of body movements. Although the precise nature of brainstem cell types and circuits that are central to full-body locomotion are becoming known 1 – 5 , efforts to understand the neuronal underpinnings of skilled forelimb movements have focused predominantly on supra-brainstem centres and the spinal cord 6 – 12 . Here we define the logic of a functional map for skilled forelimb movements within the lateral rostral medulla (latRM) of the brainstem. Using in vivo electrophysiology in freely moving mice, we reveal a neuronal code with tuning of latRM populations to distinct forelimb actions. These include reaching and food handling, both of which are impaired by perturbation of excitatory latRM neurons. Through the combinatorial use of genetics and viral tracing, we demonstrate that excitatory latRM neurons segregate into distinct populations by axonal target, and act through the differential recruitment of intra-brainstem and spinal circuits. Investigating the behavioural potential of projection-stratified latRM populations, we find that the optogenetic stimulation of these populations can elicit diverse forelimb movements, with each behaviour stably expressed by individual mice. In summary, projection-stratified brainstem populations encode action phases and together serve as putative building blocks for regulating key features of complex forelimb movements, identifying substrates of the brainstem for skilled forelimb behaviours. This study reveals a functional map for skilled forelimb movements within the lateral rostral medulla of the brainstem on the basis of the identification of specific neuronal populations by axonal targets.

Skeletal muscle is a very dynamic tissue, thus accurate quantification of skeletal muscle stiffness throughout its functional range is crucial to improve the physical functioning and independence following pathology. Shear wave elastography (SWE) is an ultrasound-based technique that characterizes tissue mechanical properties based on the propagation of remotely induced shear waves. The objective of this study is to validate SWE throughout the functional range of motion of skeletal muscle for three ultrasound transducer orientations. We hypothesized that combining traditional materials testing (MTS) techniques with SWE measurements will show increased stiffness measures with increasing tensile load, and will correlate well with each other for trials in which the transducer is parallel to underlying muscle fibers. To evaluate this hypothesis, we monitored the deformation throughout tensile loading of four porcine brachialis whole-muscle tissue specimens, while simultaneously making SWE measurements of the same specimen. We used regression to examine the correlation between Young′s modulus from MTS and shear modulus from SWE for each of the transducer orientations. We applied a generalized linear model to account for repeated testing. Model parameters were estimated via generalized estimating equations. The regression coefficient was 0.1944, with a 95% confidence interval of (0.1463–0.2425) for parallel transducer trials. Shear waves did not propagate well for both the 45° and perpendicular transducer orientations. Both parallel SWE and MTS showed increased stiffness with increasing tensile load. This study provides the necessary first step for additional studies that can evaluate the distribution of stiffness throughout muscle.

Using two-photon imaging of neuronal activity in mouse motor cortex during the acquisition of a self-initiated lever-pull task, Masamizu and colleagues demonstrate that learning is accompanied by a reorganization of ensemble activity in layer 5a. This reorganization correlates with an increase in ensemble prediction of task accuracy. The authors also find that no such changes take place in layer 2/3. The primary motor cortex (M1) possesses two intermediate layers upstream of the motor-output layer: layer 2/3 (L2/3) and layer 5a (L5a). Although repetitive training often improves motor performance and movement coding by M1 neuronal ensembles, it is unclear how neuronal activities in L2/3 and L5a are reorganized during motor task learning. We conducted two-photon calcium imaging in mouse M1 during 14 training sessions of a self-initiated lever-pull task. In L2/3, the accuracy of neuronal ensemble prediction of lever trajectory remained unchanged globally, with a subset of individual neurons retaining high prediction accuracy throughout the training period. However, in L5a, the ensemble prediction accuracy steadily improved, and one-third of neurons, including subcortical projection neurons, evolved to contribute substantially to ensemble prediction in the late stage of learning. The L2/3 network may represent coordination of signals from other areas throughout learning, whereas L5a may participate in the evolving network representing well-learned movements.

The hippocampus is a mammalian brain structure that expresses spatial representations 1 and is crucial for navigation 2 , 3 . Navigation, in turn, intricately depends on locomotion; however, current accounts suggest a dissociation between hippocampal spatial representations and the details of locomotor processes. Specifically, the hippocampus is thought to represent mainly higher-order cognitive and locomotor variables such as position, speed and direction of movement 4 – 7 , whereas the limb movements that propel the animal can be computed and represented primarily in subcortical circuits, including the spinal cord, brainstem and cerebellum 8 – 11 . Whether hippocampal representations are actually decoupled from the detailed structure of locomotor processes remains unknown. To address this question, here we simultaneously monitored hippocampal spatial representations and ongoing limb movements underlying locomotion at fast timescales. We found that the forelimb stepping cycle in freely behaving rats is rhythmic and peaks at around 8 Hz during movement, matching the approximately 8 Hz modulation of hippocampal activity and spatial representations during locomotion 12 . We also discovered precisely timed coordination between the time at which the forelimbs touch the ground (‘plant’ times of the stepping cycle) and the hippocampal representation of space. Notably, plant times coincide with hippocampal representations that are closest to the actual position of the nose of the rat, whereas between these plant times, the hippocampal representation progresses towards possible future locations. This synchronization was specifically detectable when rats approached spatial decisions. Together, our results reveal a profound and dynamic coordination on a timescale of tens of milliseconds between central cognitive representations and peripheral motor processes. This coordination engages and disengages rapidly in association with cognitive demands and is well suited to support rapid information exchange between cognitive and sensory–motor circuits. Experiments in rats show that spatial representations in the hippocampus are closely coordinated with the forelimb stepping cycle, particularly when spatial decisions are approaching, and provide insight into how this synchronization supports information processing.

Inhibitory neuron activity is found to be relatively stable during motor learning whereas excitatory neuron activity is much more dynamic — the results indicate that a large number of neurons exhibit activity changes early on during motor learning, but this population is refined with subsequent practice. Motor cortex change during learning How the brain learns to make adaptive body movements is a central question in systems neuroscience. Motor learning is thought to drive dramatic plasticity in motor circuits, but the extent of this plasticity in large neuronal populations is unclear. Takaki Komiyama and colleagues used techniques including a genetically encoded calcium indicator and chronic in vivo two-photon imaging in the motor cortex during a two-week forelimb motor learning task in mice, and found that inhibitory neuron activity is relatively stable during motor learning while excitatory neuron plasticity is much more dynamic. The results indicate that a large number of neurons exhibit activity level changes early on during motor learning, but this population is refined with subsequent practice. The motor cortex is capable of reliably driving complex movements 1 , 2 yet exhibits considerable plasticity during motor learning 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 . These observations suggest that the fundamental relationship between motor cortex activity and movement may not be fixed but is instead shaped by learning; however, to what extent and how motor learning shapes this relationship are not fully understood. Here we addressed this issue by using in vivo two-photon calcium imaging 11 to monitor the activity of the same population of hundreds of layer 2/3 neurons while mice learned a forelimb lever-press task over two weeks. Excitatory and inhibitory neurons were identified by transgenic labelling 12 , 13 . Inhibitory neuron activity was relatively stable and balanced local excitatory neuron activity on a movement-by-movement basis, whereas excitatory neuron activity showed higher dynamism during the initial phase of learning. The dynamics of excitatory neurons during the initial phase involved the expansion of the movement-related population which explored various activity patterns even during similar movements. This was followed by a refinement into a smaller population exhibiting reproducible spatiotemporal sequences of activity. This pattern of activity associated with the learned movement was unique to expert animals and not observed during similar movements made during the naive phase, and the relationship between neuronal activity and individual movements became more consistent with learning. These changes in population activity coincided with a transient increase in dendritic spine turnover in these neurons. Our results indicate that a novel and reproducible activity–movement relationship develops as a result of motor learning, and we speculate that synaptic plasticity within the motor cortex underlies the emergence of reproducible spatiotemporal activity patterns for learned movements. These results underscore the profound influence of learning on the way that the cortex produces movements.

Peripheral nerve transfer is an effective surgical method in restoring motor functions of upper limb after peripheral nerve injuries. However, the outcome of individual function recovery is less predictable. It is crucial to access the long-term evaluation of function improvement. Here, we developed a fully implantable multisite optogenetic stimulation system, which is tailored for wireless, reprogrammable and long-term function evaluation of peripheral nerve plexus with sub nerve resolution. In Thy1-ChR2-EYFP mice, our system induced distinct compound muscle action potentials and forelimb movements when illuminating different nerve fascicles. Furthermore, we applied the system on a nerve transfer mice model after traumatic brain injury and discovered innervation pattern of the transferred and adjacent nerves to multiple muscles consecutively within 12 weeks after surgery. Our system enabled refined evaluation of electrophysiological and motor functions of peripheral nerve plexus, shining light upon personalized diagnosis and treatment after nerve injuries or surgeries. Peripheral nerve transfer can restore motor functions of the upper limbs after peripheral nerve injuries. Here, the authors developed an implantable multisite optogenetic stimulation system for wireless evaluation of peripheral nerve plexus with sub nerve resolution.

Synapse structure in memory: plasticity and stability Connections between neurons are thought to be remodelled when we learn new tasks or acquire new information. However, this plasticity must also occur against a backdrop of stable memory maintenance. In mice, a paradigm of either enhanced sensory experience or specific motor learning produced new putative neuronal connections that remained stable alongside developmentally preserved connections much later in life. This suggests that learning can produce changes in the neuronal connectivity that can be stable for the lifetime of the network. Connections between neurons are thought to be remodelled when we learn new tasks or acquire new information; however, it is unclear how neural circuits undergo continuous synaptic changes during learning while maintaining lifelong memories. Here, by following post-synaptic dendritic spines in the mouse cortex, it is shown that a small fraction of new spines induced by novel experience are preserved and provide a structural basis for lifelong memory retention. Changes in synaptic connections are considered essential for learning and memory formation 1 , 2 , 3 , 4 , 5 , 6 . However, it is unknown how neural circuits undergo continuous synaptic changes during learning while maintaining lifelong memories. Here we show, by following postsynaptic dendritic spines over time in the mouse cortex 7 , 8 , that learning and novel sensory experience lead to spine formation and elimination by a protracted process. The extent of spine remodelling correlates with behavioural improvement after learning, suggesting a crucial role of synaptic structural plasticity in memory formation. Importantly, a small fraction of new spines induced by novel experience, together with most spines formed early during development and surviving experience-dependent elimination, are preserved and provide a structural basis for memory retention throughout the entire life of an animal. These studies indicate that learning and daily sensory experience leave minute but permanent marks on cortical connections and suggest that lifelong memories are stored in largely stably connected synaptic networks.