Chronic pain frequently co-occurs with depression, forming a vicious cycle that mutually exacerbates both. Although the medial shell of nucleus accumbens (NAcMed) is known to modulate both pain and affective states, the distinct roles of D1- and D2-dopamine receptor-expressing medium spiny neurons (D1- and D2-MSNs) within the NAcMed, as well as their respective circuits, in chronic pain and comorbid depression remain poorly defined. We observed decreased activity in both MSN subtypes during chronic pain and comorbid depression. Notably, activation of D1-MSNs alleviated depressive-like behaviors, whereas activation of D2-MSNs produced analgesic effects. Furthermore, we identified two parallel neural circuits: the NAcMed→mediodorsal thalamus pathway, which preferentially modulates depressive-like behaviors, and the NAcMed→lateral hypothalamus pathway, which selectively relieves pain. These findings delineate a circuit-specific dichotomy in which NAcMed and NAcMed govern distinct affective and sensory dimensions of chronic pain-depression comorbidity, providing circuit-specific targets for potential treatment.

The substantia nigra pars reticulata (SNr) is a primary output for basal ganglia signaling. It plays an important role in the control of movement, integrating inputs from upstream structures in the basal ganglia, before sending organized projections to a range of targets in the midbrain, brainstem, and thalamus. Here, we present a detailed in silico model of the mouse SNr, including its major afferent inputs. The electrophysiological and morphological properties of SNr neurons are characterized in acute brain slices via whole cell patch-clamp recordings and morphological reconstruction. Using reconstructed morphologies, multicompartmental models of single neurons are instantiated within the NEURON simulation environment and populated with relevant modeled ion channels. Model parameters are optimized via an evolutionary algorithm, such that simulated neurons faithfully reproduce recorded electrophysiological behavior. Using the simulation infrastructure software , single neuron models are incorporated into a circuit-level model, where the sparse connectivity within the SNr is recreated. We simulate the mouse SNr at scale, featuring realistic volumes and neuronal density. The unique synaptic properties and activity patterns of different afferent sources are captured in silico. Born out of ex vivo data, our model reproduces in vivo firing patterns. Our simulations suggest that paradoxical activity increases in response to experimental inhibition can be explained by lateral connectivity. In addition, our model predicts the functional implications of characteristic short-term synaptic plasticity in the indirect pathway of the basal ganglia. The model can be extended to include additional inputs and be connected with existing models of upstream basal ganglia nuclei to further explore circuit dynamics.

Striatal output is dynamically modulated by cholinergic interneurons (CINs), the primary source of acetylcholine in the striatum. CINs have been classically viewed as a random and homogeneous population, but recent evidence suggests heterogeneity in their anatomical and functional organization. Here, using systematic mapping and quantitative spatial analyses, we found that-contrary to current dogma-CINs exhibited striking enrichment and nonrandom clustering in the striosome compartment, particularly in the lateral striatum. Similar analyses carried out for parvalbumin- and somatostatin-expressing interneurons revealed that compartmental organization is interneuron specific. The strong "striosome preference" exhibited by CINs was confined within striosome borders, not extending to the surrounding matrix. We further found that striosome and matrix CINs differed in their expression levels of phospho-S6 ribosomal protein-Ser240/244 and choline acetyltransferase, suggesting functional differences, and clustered CINs differed from unclustered CINs in their intrinsic membrane properties. Finally, CINs expressing Lhx6, which defines a distinct γ-aminobutyric acid (GABA) coreleasing population, were notably absent from regions where highly clustered striosomal CINs appeared. Collectively, our findings uncover important dimensions of CIN organization, suggesting that modulation of regional and compartmental striatal output may depend upon the spatial-functional heterogeneity of CINs.

Precisely neuromodulating deep brain regions could bring transformative advancements in both neuroscience and treatment. We demonstrate that non-invasive transcranial ultrasound stimulation (TUS) can selectively modulate deep brain activity and affect learning and decision making, comparable to deep brain stimulation (DBS). We tested whether TUS could causally influence neural and behavioural responses by targeting the nucleus accumbens (NAcc) using a reinforcement learning task. Twenty-six healthy adults completed a within-subject TUS-fMRI experiment with three conditions: TUS to the NAcc, dorsal anterior cingulate cortex (dACC), or Sham. After TUS, participants performed a probabilistic learning task during fMRI. TUS-NAcc altered BOLD responses to reward expectation in the NAcc and surrounding areas. It also affected reward-related behaviours, including win-stay strategy use, learning rate following rewards, learning curves, and repetition rates of rewarded choices. DBS-NAcc perturbed the same features, confirming target engagement. These findings establish TUS as a viable approach for non-invasive deep-brain neuromodulation.

Interval timing is an evolutionarily well-preserved function that presents similar behavioral signatures across different species. However, the neural basis of interval timing remains an open question. For instance, although dopamine has been implicated as a vital component of the internal clock, its precise role is debated due to equivocal findings from various methodologies and their interpretations. We tested this question by optogenetically exciting versus inhibiting tyrosine hydroxylase-positive (TH+) neurons of the substantia nigra pars compacta while male mice produced at least a 3-second-long interval by depressing a lever for reward. Excitation of TH+ neurons shifted their timing behavior to the right, while inhibition led to a shift to the left. Our drift-diffusion-timing model-based analysis of the behavioral data clearly showed that TH+ neuron excitation and inhibition heightened and lowered the timing threshold, respectively, without affecting the rate of temporal integration (i.e., clock speed). Our work attributes a clear mechanistic role (i.e., threshold setting) to nigrostriatal dopaminergic function as part of the internal clock. Despite the ubiquity of time experience, how the brain perceives time is unresolved. Dopamine is a key neuromodulator system involved in subjective time experience. For instance, the time sense is disrupted in conditions characterized by dopaminergic dysfunction (e.g., Parkinson's disease, schizophrenia). However, the mechanistic role of dopamine in the operation of the internal clock is debated. We resolve this debate by optogenetically upregulating and downregulating the nigrostriatal dopamine in mice and evaluating the behavioral outcomes under a computational framework that assumes that the brain times by accumulating brain signals up to a threshold. Our results showed that modulating the nigrostriatal dopamine system alters the level to which the brain integrates clock signals (temporal caution) without altering the clock speed.

Being able to switch from established choices to new alternatives when conditions change - behavioral flexibility - is essential for survival. Cholinergic signaling in the striatum contributes to such flexible behavior, yet the timing and spatial organization of acetylcholine release during contingency changes remain unclear, limiting conceptual understanding of its role in behavioral flexibility. Using a genetically encoded acetylcholine sensor and 2-photon imaging in the dorsal striatum of behaving mice, we visualized acetylcholine dynamics during acquisition and reversal learning in a virtual reality Y-maze. Rewarded outcomes evoked phasic decreases in acetylcholine, whereas unexpected non-reward following reversal triggered widespread increases that predicted lose-shift behavior. Targeted inhibition of cholinergic interneurons reduced this adaptive response. Spatial analysis revealed heterogeneous, temporally distinct signals forming functionally diverse microdomains. These findings suggest that widespread and focal acetylcholine release during unexpected outcomes promotes adaptive response shifts, offering a mechanistic framework for understanding disorders such as addiction and obsessive-compulsive rituals.

Primary sensory neurons convert external stimuli into electrical signals, yet how heterogeneous neurons encode distinct sensations remains unclear. In vivo dorsal root ganglia (DRG) imaging with genetically-encoded Ca indicators (GECIs) enables mapping of neuronal activity from over 1800 neurons per DRG in live mice, offering high spatial and populational resolution. However, GECIs' slow Ca response kinetics limit the temporal accuracy of neuronal electrical dynamics. Genetically-encoded voltage indicators (GEVIs) provide real-time voltage tracking but often lack the brightness and dynamic range required for in vivo use. Here, we used soma-targeted ASAP4.4-Kv, a bright and fast positively tuned GEVI, to dissect temporal dynamics of DRG neuron responses to mechanical, thermal, or chemical stimulation in live male and female mice. ASAP4.4-Kv revealed previously unrecognized cell-to-cell electrical synchronization and robust dynamic transformations in sensory coding following tissue injury. Combining GEVI and GECI imaging empowers spatiotemporal analysis of sensory signal processing and integration mechanisms in vivo.

The basal ganglia (BG) are a collection of subcortical nuclei involved in motor control, sensorimotor integration, and procedural learning. They play a key role in the acquisition and adaptation of movements, a process driven by dopamine-dependent plasticity at cortico-striatal projections, which serve as BG input. However, BG output is not necessary for executing many well-learned movements. This raises a fundamental question: How can plasticity at BG input contribute to the acquisition and adaptation of movements which execution does not require BG output? Existing models of BG function often neglect the feedback dynamics within cortico-BG-thalamo-cortical circuitry and do not capture the interaction between the cortex and BG in movement generation and adaptation. In this work, we address the above question in a theoretical model of the BG-thalamo-cortical multiregional network, incorporating anatomical, physiological, and behavioral evidence. We examine how its dynamics influence the execution and reward-based adaptation of reaching movements. We demonstrate how the BG-thalamo-cortical network can shape cortical motor output through the combination of three mechanisms: i) the diverse dynamics emerging from its closed-loop architecture, ii) attractor dynamics driven by recurrent cortical connections, and iii) reinforcement learning via dopamine-dependent cortico-striatal plasticity. Our study highlights the role of the cortico-BG-thalamo-cortical feedback in efficient visuomotor adaptation. It also suggests a mechanism for early-stage acquisition of reaching movements through motor babbling. More generally, our model explains how the BG-cortical network refines motor output through its intricate closed-loop dynamics and dopamine-dependent plasticity at cortico-striatal synapses.