Striatal dopamine plays key roles in our normal and pathological goal-directed actions. To understand dopamine function, much attention has focused on how midbrain dopamine neurons modulate their firing patterns. However, we identify a presynaptic mechanism that triggers dopamine release directly, bypassing activity in dopamine neurons. We paired electrophysiological recordings of striatal channelrhodopsin2-expressing cholinergic interneurons with simultaneous detection of dopamine release at carbon-fiber microelectrodes in striatal slices. We reveal that activation of cholinergic interneurons by light flashes that cause only single action potentials in neurons from a small population triggers dopamine release via activation of nicotinic receptors on dopamine axons. This event overrides ascending activity from dopamine neurons and, furthermore, is reproduced by activating ChR2-expressing thalamostriatal inputs, which synchronize cholinergic interneurons in vivo. These findings indicate that synchronized activity in cholinergic interneurons directly generates striatal dopamine signals whose functions will extend beyond those encoded by dopamine neuron activity.

In this issue of Neuron, Threlfell et al. (2012) report that synchronous activation of cholinergic interneurons evokes striatal dopamine release by activating presynaptic nicotinic acetylcholine receptors. These findings call for a fundamental reevaluation of the long-standing view that dopamine and acetylcholine "feud" over control of striatal circuitry.

The present investigation had two aims: (1) to study responses of dopamine neurons to stimuli with attentional and motivational significance during several steps of learning a behavioral task, and (2) to study the activity of dopamine neurons during the performance of cognitive tasks known to be impaired after lesions of these neurons. Monkeys that had previously learned a simple reaction time task were trained to perform a spatial delayed response task via two intermediate tasks. During the learning of each new task, a total of 25% of 76 dopamine neurons showed phasic responses to the delivery of primary liquid reward, whereas only 9% of 163 neurons responded to this event once task performance was established. This produced an average population response during but not after learning of each task. Reward responses during learning were significantly more numerous and pronounced in area A10, as compared to areas A8 and A9. Dopamine neurons also showed phasic responses to the two conditioned stimuli. These were the instruction cue, which was the first stimulus in each trial and indicated the target of the upcoming arm movement (58% of 76 neurons during and 44% of 163 neurons after learning), and the trigger stimulus, which was a conditioned incentive stimulus predicting reward and eliciting a saccadic eye movement and an arm reaching movement (38% of neurons during and 40% after learning). None of the dopamine neurons showed sustained activity in the delay between the instruction and trigger stimuli that would resemble the activity of neurons in dopamine terminal areas, such as the striatum and frontal cortex. Thus, dopamine neurons respond phasically to alerting external stimuli with behavioral significance whose detection is crucial for learning and performing delayed response tasks. The lack of sustained activity suggests that dopamine neurons do not encode representational processes, such as working memory, expectation of external stimuli or reward, or preparation of movement. Rather, dopamine neurons are involved with transient changes of impulse activity in basic attentional and motivational processes underlying learning and cognitive behavior.

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.

Transport and reaction-diffusion processes in fluids are fundamentally influenced by fluctuations, which can modify the transport of momentum, particles, and other chemical species. In fluids at thermal equilibrium, these fluctuations arise from molecular thermal motion. These thermal fluctuations become particularly important for transport at mesoscopic scales, as they can be comparable with hydrodynamic transport mechanisms such as advection and viscous diffusion. While thermal fluctuations at mesoscopic scales are often assumed to be spatially uncorrelated in thermal equilibrium, the underlying fluid microstructure can generate finite-range spatial correlations. However, how such intrinsically correlated thermal fluctuations couple with hydrodynamics to influence mesoscopic transport remains poorly understood. To address this gap, we develop a fluctuating-hydrodynamic framework that incorporates spatially correlated thermal noise as a coarse-grained representation of its microscopic origin. To preserve thermal equilibrium, the fluctuation-dissipation relation requires the energy injected by the correlated thermal noise to remain balanced by viscous dissipation. Consequently, viscous dissipation inherits the same spatial correlations, thereby modifying momentum diffusion. Numerical simulations of particle diffusion show that increasing the correlation length prolongs transport persistence by nearly two orders of magnitude, thereby substantially delaying the crossover to normal diffusion relative to the white-noise limit. More generally, independently varying the correlation range and amplitude reveals that equilibrium spatial correlations can either enhance or suppress transport persistence relative to classical Brownian diffusion. These results demonstrate that intrinsic spatial correlations in equilibrium thermal fluctuations can qualitatively reshape mesoscopic transport.

Macromolecular coil-to-helix transitions simultaneously modify local geometry and persistence length, driving complex changes in overall chain size. Here, we apply the wormlike (persistent) chain model to both coil and helical fragments to examine how the degree of helicity, θ, and average helical fragment length, kh, dictate global chain dimensions. Using scaling arguments, we construct a conformational diagram comprising six distinct regimes for the end-to-end distance. We then employ a minimal coarse-grained molecular dynamics model to verify the theory. Mapping structural properties extracted from these simulations onto the proposed regime diagram enables direct quantitative comparison. This, alongside microscopic conformational analysis, corroborates our theoretical framework. We highlight that the competition between local chain compactization and increased stiffness upon helix formation produces a non-monotonic behavior of the end-to-end distance. Furthermore, to demonstrate the generality of our approach, we systematically vary the hydrogen-bonding monomer spacing m for pairs {i, i + m}. Spacings of m = 4, 5, and 6 are used as coarse-grained representations of α-, π-, and 1-7 helices, respectively. As m increases, the helix becomes locally more compact while its persistence length grows. The regime diagrams constructed for these distinct configurations, combined with robust quantitative agreement between theory and simulation, demonstrate that our framework effectively captures how variations in helix geometry and stiffness control macromolecular dimensions across the transition.

Many chemical and biological processes in molecular, soft-matter, and living systems are modeled using the low-Reynolds-number (Re ≪ 1) linearization of the incompressible Navier-Stokes equations. This approximation is justified by the assumption that viscous dissipation dominates nonlinear inertial effects across spatial scales. However, many soft-matter and biological fluids possess internal structure that modifies momentum transport across scales, potentially altering the balance between inertial and viscous effects. In Part I [J. Chem. Phys. 165, 064509 (2026)] of this series, we introduced a thermodynamically consistent fluctuating-hydrodynamic framework for structured fluids and showed that spatial correlations render viscous dissipation scale dependent. Here, we investigate the consequences of this scale dependence for the validity of the classical low-Re linearization. We show that scale-dependent viscous dissipation alters the balance between inertia and viscosity across scales, thereby invalidating the conventional low-Re justification for linearization. Direct numerical simulations in one and two dimensions confirm these predictions. In one dimension, nonlinear mode coupling accelerates the relaxation of high-wavenumber Fourier modes relative to the linearized dynamics. The same mechanism is reflected in particle transport in two dimensions: the particle velocity autocorrelation decays more slowly under the linearized dynamics, leading to diffusion coefficients that differ from the nonlinear prediction by up to 90%. These results demonstrate that a single Reynolds number is no longer sufficient to determine the validity of linearization in spatially correlated fluctuating fluids; instead, it depends on a scale-dependent spectrum of effective Reynolds numbers.