Dopamine is essential for striatal function and learning. Striatal dopamine release can be triggered by dopamine cell firing, but also by coordinated cholinergic interneuron activity, which stimulates dopamine release via presynaptic nicotinic acetylcholine receptors on dopamine axons. While acetylcholine-dependent dopamine release is well-documented ex vivo and under artificial optogenetic stimulation in vivo, its role during natural behavior has remained unclear. One possible endogenous driver of acetylcholine-dependent dopamine release is thalamic input, which provides strong excitatory drive to cholinergic interneurons. To examine whether thalamic input provokes acetylcholine-dependent dopamine release during behavior, we performed simultaneous fiber photometry recordings of striatal dopamine (GRAB-rDA3m) and thalamic axon activity (gCaMP8m) in the dorsomedial (DMS) and dorsolateral striatum (DLS) of mice learning the accelerating rotarod, a striatal-dependent task that demands precise and effortful motor control. Recordings were obtained on- and off-task and across days of training to capture the full arc of learning. Dopamine transients in DMS, but not DLS, were frequently coupled to peaks in thalamic axon activity via an acetylcholine-dependent mechanism. The occurrence of these thalamic-evoked DMS dopamine transients depended on learning, task engagement, and the recent history of dopamine activity, but did not contribute to motor error signals. Together, these findings establish thalamic input as a physiological driver of acetylcholine-dependent dopamine release in DMS. Moreover, they reveal that striatal sensitivity to this local release mechanism is dynamically gated by dopaminergic history, providing a compelling framework for understanding how local and soma-triggered dopamine signals are coordinated to support learning.

High-resolution extracellular electrophysiology is the gold standard for recording spikes from distributed neural populations and is especially powerful when combined with optogenetics for manipulation of specific cell types with high temporal resolution. We integrated these approaches into prototype Neuropixels Opto probes, which combine electronic and photonic circuits. These devices pack 960 electrical recording sites and two sets of 14 light emitters onto a 70-μm-wide, 1-cm-long shank, allowing spatially addressable optogenetic stimulation with blue and red light. In mouse cortex, Neuropixels Opto probes delivered high-quality recordings together with spatially addressable optogenetics, differentially activating or silencing neurons at distinct cortical depths. In the mouse striatum and other deep structures, Neuropixels Opto probes delivered efficient optotagging, facilitating the identification of two cell types in parallel. Neuropixels Opto probes represent a promising tool for recording, identifying and manipulating neuronal populations.

Although learning in response to extrinsic reinforcement is theorized to be driven by dopamine signals that encode the difference between expected and experienced rewards, skills that enable verbal or musical expression can be learned without extrinsic reinforcement. Instead, spontaneous execution of these skills is thought to be intrinsically reinforcing. Whether dopamine signals similarly guide learning of these intrinsically reinforced behaviours is unknown. In juvenile zebra finches learning from an adult tutor, dopamine signalling in a song-specialized basal ganglia region is required for successful song copying, a spontaneous, intrinsically reinforced process. Here we show that dopamine dynamics in the song basal ganglia faithfully track the learned quality of juvenile song performance on a rendition-by-rendition basis. Furthermore, dopamine release in the basal ganglia is driven not only by inputs from midbrain dopamine neurons classically associated with reinforcement learning but also by song premotor inputs, which act by means of local cholinergic signalling to elevate dopamine during singing. Although both cholinergic and dopaminergic signalling are necessary for juvenile song learning, only dopamine tracks the learned quality of song performance. Therefore, dopamine dynamics in the basal ganglia encode performance quality during self-directed, long-term learning of natural behaviours.

Basal Ganglia Advances is a collection highlighting research on the structure, function, and disorders of the basal ganglia. It features studies spanning neuroscience, clinical insights, and computational models, serving as a hub for advances in movement, cognition, and behavior.

Recent advances in the field of Voltage Imaging, with a special focus on new constructs and novel implementations.

Work related to place tuning, spatial navigation, orientation and direction. Mainly includes articles on connectivity in the hippocampus, retrosplenial cortex, and related areas.

High-resolution extracellular electrophysiology is the gold standard for recording spikes from distributed neural populations and is especially powerful when combined with optogenetics for manipulation of specific cell types with high temporal resolution. We integrated these approaches into prototype Neuropixels Opto probes, which combine electronic and photonic circuits. These devices pack 960 electrical recording sites and two sets of 14 light emitters onto a 70-μm-wide, 1-cm-long shank, allowing spatially addressable optogenetic stimulation with blue and red light. In mouse cortex, Neuropixels Opto probes delivered high-quality recordings together with spatially addressable optogenetics, differentially activating or silencing neurons at distinct cortical depths. In the mouse striatum and other deep structures, Neuropixels Opto probes delivered efficient optotagging, facilitating the identification of two cell types in parallel. Neuropixels Opto probes represent a promising tool for recording, identifying and manipulating neuronal populations.

Dopamine is essential for striatal function and learning. Striatal dopamine release can be triggered by dopamine cell firing, but also by coordinated cholinergic interneuron activity, which stimulates dopamine release via presynaptic nicotinic acetylcholine receptors on dopamine axons. While acetylcholine-dependent dopamine release is well-documented ex vivo and under artificial optogenetic stimulation in vivo, its role during natural behavior has remained unclear. One possible endogenous driver of acetylcholine-dependent dopamine release is thalamic input, which provides strong excitatory drive to cholinergic interneurons. To examine whether thalamic input provokes acetylcholine-dependent dopamine release during behavior, we performed simultaneous fiber photometry recordings of striatal dopamine (GRAB-rDA3m) and thalamic axon activity (gCaMP8m) in the dorsomedial (DMS) and dorsolateral striatum (DLS) of mice learning the accelerating rotarod, a striatal-dependent task that demands precise and effortful motor control. Recordings were obtained on- and off-task and across days of training to capture the full arc of learning. Dopamine transients in DMS, but not DLS, were frequently coupled to peaks in thalamic axon activity via an acetylcholine-dependent mechanism. The occurrence of these thalamic-evoked DMS dopamine transients depended on learning, task engagement, and the recent history of dopamine activity, but did not contribute to motor error signals. Together, these findings establish thalamic input as a physiological driver of acetylcholine-dependent dopamine release in DMS. Moreover, they reveal that striatal sensitivity to this local release mechanism is dynamically gated by dopaminergic history, providing a compelling framework for understanding how local and soma-triggered dopamine signals are coordinated to support learning.

Improving nitrogen use efficiency (NUE) in wheat is critical for addressing the dual challenges of global food security and environmental sustainability. Globally, only 42%-47% of applied nitrogen (N) fertilisers taken up by crops, with remainder lost to the environment, driving soil and water pollution, greenhouse gas emissions, and ecological imbalances. This review provides a comprehensive synthesis and integrative framework- integrating agronomic practices, advanced remote sensing and genomic approaches to enhance wheat NUE. We first examine the physiological basis of NUE, emphasising the synergy between photosynthetic carbon assimilation and N metabolism, the critical role of Rubisco in carbon-nitrogen coupling, and the temporal dynamics of N uptake, transport, and remobilisation throughout the wheat growth cycle. The temporal mismatch between source-sink N partitioning during grain filling emerges as a major physiological constraint limiting NUE in modern high-yielding varieties. We then explore transformative advances in remote sensing technologies, highlighting the paradigm shift from traditional vegetation indices to physiological sensing approaches. Through integration of multispectral imaging, LiDAR, thermal infra-red sensing, and solar-induced chlorophyll fluorescence, coupled with three-dimensional radiative transfer models and machine learning algorithms, these technologies enable non-destructive, real-time monitoring of crop N status while overcoming spectral-structural ambiguity and saturation limitations. From a genomic perspective, we synthesise recent progress in quantitative trait loci mapping and genome-wide association studies (GWAS), identifying key genetic loci controlling root architecture, N uptake transporters (NRT/AMT families), and grain filling efficiency. Multi-omics integration-spanning genomics, transcriptomics, and metabolomics-reveals temporal genetic networks distinguishing short-term nitrogen signalling responses from long-term adaptive remodelling, with genes such as TaNAC2-5A, TaNPF6.2, and QMrl-7B emerging as promising targets for molecular breeding. High-throughput phenotyping platforms enable time-series GWAS analysis, capturing developmental dynamics and genotype × environment interactions that traditional approaches miss. Finally, we discuss sustainable N management strategies, including enhanced efficiency fertilisers, precision application technologies, and soil health optimisation. By integrating these multidisciplinary approaches within a Genotype × Environment × Management framework, this review provides a roadmap for developing climate-smart, N-efficient wheat varieties and precision N management systems that simultaneously enhance productivity, reduce environmental footprints, and ensure sustainable agricultural intensification.