Cholinergic interneurons (CINs) are essential elements of striatal circuits and functions. Although acetylcholine signaling via muscarinic receptors (mAChRs) has been well studied, more recent data indicate that postsynaptic nicotinic receptors (nAChRs) located on striatal GABAergic interneurons (GINs) are equally critical. One example is that CIN stimulation induces large disynaptic inhibition of striatal projection neurons (SPNs) mediated by nAChR activation of GINs. Although these circuits are ideally positioned to modulate striatal output, the neurons involved are not definitively identified because of an incomplete mapping of CINs-GINs interconnections. Here, we show that CINs modulate four GINs populations via an intricate mechanism involving co-activation of presynaptic and postsynaptic mAChRs and nAChRs. Using optogenetics, we demonstrate the participation of tyrosine hydroxylase-expressing GINs in the disynaptic inhibition of SPNs via heterotypic electrical coupling with neurogliaform interneurons. Altogether, our results highlight the importance of CINs in regulating GINs microcircuits via complex synaptic/heterosynaptic mechanisms.

Voltage imaging has emerged as a powerful tool for recording membrane potential changes in living cells, offering a direct measurement of rapid neuronal events with high temporal precision. Since the brain is a three-dimensional circuit, it is essential to record signals across a volume. However, achieving effective three-dimensional voltage imaging over large neuronal populations remains challenging due to the need for high imaging speed, high signal-to-noise ratio, and extensive volume coverage. In this study, we demonstrate in vivo three-dimensional voltage imaging in larval zebrafish using oblique plane microscopy and QFDBD-QUAS-driven expression of the genetically encoded voltage indicator Ace-mNeon2-Kv2.1, achieving volumetric imaging rates of up to 200 volumes per second (VPS). This approach enables dye-free voltage imaging, simplifying experimental workflows and improving the reproducibility of in vivo voltage imaging experiments for investigating neuronal circuit dynamics in the living zebrafish animal model.

The neurotransmitter acetylcholine (ACh) is essential in both the central and peripheral nervous systems. Recent studies highlight the significance of interactions between ACh and various neuromodulators in regulating complex behaviors. The ability to simultaneously image ACh and other neuromodulators can provide valuable information regarding the mechanisms underlying these behaviors. Here we developed a series of red fluorescent G-protein-coupled receptor activation-based ACh sensors, with a wide detection range and expanded spectral profile. The high-affinity sensor rACh1h reliably detects ACh release in various brain regions, including the nucleus accumbens, amygdala, hippocampus and cortex. Moreover, rACh1h can be coexpressed with green fluorescent sensors to record ACh release together with other neurochemicals in various behavioral contexts using fiber photometry, mesoscopic imaging and two-photon imaging with high spatiotemporal resolution.

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.

Indirect treatment comparisons (ITCs), as outlined in NICE and ISPOR guidance, require careful evaluation of cross-trial heterogeneity to ensure valid comparisons, particularly in rare diseases with limited evidence. C3 glomerulopathy (C3G) is an ultra-rare, complement-mediated kidney disease with high unmet need, making appropriate application of ITC frameworks especially critical. This appraisal evaluates the feasibility of applying ITC principles to compare Phase III trials of iptacopan (APPEAR-C3G) and pegcetacoplan (VALIANT) in the absence of head-to-head evidence. Feasibility of an ITC in C3G was assessed through critical appraisal of APPEAR-C3G and VALIANT randomized controlled trials, focusing on alignment of eligibility criteria, baseline characteristics and outcome definitions, in line with NICE DSU TSD-18, CHTE2020 and ISPOR guidance. A systematic literature review (SLR) was then conducted to identify published ITCs comparing iptacopan and pegcetacoplan in C3G, which were evaluated for methodological rigor, transparency and credibility according to NICE and ISPOR recommendations. Substantial heterogeneity was observed between APPEAR-C3G and VALIANT. Overlap was limited to small subpopulations, with imbalances in baseline characteristics, differences in end point reporting, and noncomparable placebo responses. These issues indicate that anchored ITCs are not feasible using currently available data without extensive adjustments that conflict with NICE and ISPOR guidance. The SLR identified one ITC poster with limited methodology comparing these trials. However, when the results were subsequently published in a manuscript, crucial methodological details including justification of effect modifiers, modeling diagnostics, analytic procedures, were still unavailable. Other concerns, such as using standard matching-adjusted indirect comparison methodology in the presence of substantial cross-trial heterogeneity, and the resulting limited ESS observed frequently in rare diseases, were confirmed, thus undermining credibility of conclusions. ITCs in C3G face significant methodological challenges due to pronounced trial heterogeneity and small sample sizes inherent to this ultra-rare disease. These limitations complicate the conduct and interpretation of arising ITCs, highlighting the need for transparent and methodologically robust approaches. Consequently, payers, decision makers, and HTA bodies should interpret existing C3G ITCs with caution. These findings inform broader application of ITC methods in rare diseases, identifying areas for future evidence generation and analytical innovation.

Spinocerebellar ataxia type 10 (SCA10 or ATX-ATXN10) is typically attributed to large intronic ATTCT repeat expansions in ATXN10, yet interpretation is complicated by repeat interruptions, reduced penetrance, and assay limitations.

ObjectiveAs large language models (LLMs) enter clinical decision support, concerns persist about sociodemographic bias. We assessed whether LLM recommendations for dizziness vary by patient descriptors and clinical detail.MethodsWe conducted a cross-randomized in-silico vignette study. One hundred synthetic emergency department dizziness cases were created using established diagnostic frameworks including the TiTrATE paradigm, SAEM GRACE-3 guidelines, and Bárány Society diagnostic criteria. Each vignette was tested in a neutral form and with 33 sociodemographic descriptor variants (34 total). Twelve instruction-tuned LLMs from multiple model families were evaluated. Models answered five binary clinical decision questions addressing etiology classification, triage disposition, neuroimaging, bedside vestibular examination, and mental health referral. Each model-vignette-descriptor combination was repeated 10 times, yielding 2,040,000 responses. Sociodemographic bias was quantified as descriptor-specific percentage-point deviations from neutral control recommendations with 95% confidence intervals.ResultsSociodemographic descriptors influenced LLM recommendations, with the largest differences observed for mental health referral decisions in diagnostically ambiguous cases. Referral likelihood was lower for Black transgender women (-12.2 pp; 95% CI -14.0 to -10.3), Black patients experiencing homelessness (-9.1 pp; -11.0 to -7.3), and patients experiencing homelessness (-7.7 pp; -9.5 to -5.9). Differences were attenuated when vignettes contained clearer diagnostic information. Other effects were smaller, including increased neuroimaging recommendations for low-income descriptors (+4.0 pp; 95% CI 2.1-5.8).ConclusionLLM clinical recommendations varied by sociodemographic descriptors, particularly under diagnostic uncertainty. More detailed clinical information reduced these disparities, suggesting structured inputs may mitigate bias in clinical AI systems.