Biology subjects

Vu, M.-A. T.

Publications and source records attributed to Vu, M.-A. T..

6 recordsLinked to original sources

bioRxiv2026

An anatomical hotspot for striatal dopamine-acetylcholine interactions during reward and movement

Dopamine (DA) and acetylcholine (ACh) are key neuromodulators that regulate striatal circuits underlying movement and reinforcement learning. Evidence suggests that DA and ACh systems interact, but where and how interactions are expressed across striatal regions in behaviorally relevant release dynamics remains unknown. We applied micro-fiber arrays to simultaneously measure striatum-wide DA and ACh in behaving mice, revealing an anatomical organization in which DA-ACh anti-correlations were concentrated in a hotspot in the anterior dorsolateral striatum (aDLS). Anti-correlations resulted from temporally coincident pairs of spontaneous and event-locked transient peak and dip events occurring in a DA[->]ACh sequence. The aDLS localized hotspot was consistently expressed within distinct signals associated with unpredicted rewards, learned and extinguished Pavlovian cues, and locomotion initiation and invigoration phases, for which we revealed novel, opposing DA-ACh dynamics. Optogenetic activation of DA neurons selectively suppressed spontaneous ACh release within the aDLS hotspot, and ex vivo recordings revealed enhanced D2-mediated ACh inhibition in aDLS relative to ventral regions, suggesting a mechanistic basis for this spatial specificity. These findings demonstrate that DA-ACh interactions during behavior are spatially organized, rather than uniformly conserved, and shape behaviorally relevant dynamics to regulate region-specific functions in learning and movement control.

neuroscience↗

bioRxiv2024

Spatially organized striatal neuromodulator release encodes trajectory errors

Goal-directed navigation requires animals to continuously evaluate their current direction and speed of travel relative to landmarks to discern whether they are approaching or deviating from their goal. Striatal dopamine and acetylcholine are powerful modulators of goal-directed behavior, but it is unclear whether and how neuromodulator dynamics at landmarks incorporate relative motion for effective behavioral guidance. Using optical measurements in mice, we demonstrate that cue-evoked striatal dopamine release encodes bi-directional trajectory errors reflecting relationships between ongoing speed and direction of locomotion and visual flow relative to optimal goal trajectories. Striatum-wide micro-fiber array recordings resolved an anatomical gradient of trajectory error signaling across the anterior-posterior axis, distinct from trajectory error independent cue signals. Dynamic regression modeling revealed that positive and negative trajectory error encoding emerges early and late respectively during learning and over different time courses in the medial and lateral striatum, enabling region specific contributions to learning. Striatal acetylcholine release also encodes trajectory errors, but encoding is more spatially restricted, opposite polarity, and delayed relative to dopamine, supporting distinct roles in modulating striatal output and behavior. Dopamine trajectory error signaling and task performance were reproduced in a reinforcement learning model incorporating a conjunctive state space representation, suggesting a potential neural substrate for trajectory error generation. Our results establish region specific neuromodulator signals positioned to guide the speed and direction of locomotion to reach goals based on environmental landmarks during navigation.

neuroscience↗

bioRxiv2024

Spatially organized striatum-wide acetylcholine dynamics for the learning and extinction of Pavlovian cues and actions

Striatal acetylcholine (ACh) signaling has been proposed to counteract reinforcement signals to promote extinction and behavioral flexibility. ACh dips to cues and rewards may open a temporal window for associative plasticity to occur, while elevations may promote extinction. Changes in multi-phasic striatal ACh signals have been widely reported during learning, but how and where signals are distributed to enable region-specific plasticity for the learning and degradation of cue-reward associations is poorly understood. We used array fiber photometry in mice to investigate how ACh release across the striatum evolves during learning and extinction of Pavlovian associations. We report a topographic organization of opposing changes in ACh release to cues, rewards, and consummatory actions across distinct striatum regions. We localized reward prediction error encoding in particular phases of the ACh dynamics to a specific region of the anterior dorsal striatum (aDS). Positive prediction errors in the aDS were expressed in ACh dips, and negative prediction errors in long latency ACh elevations. Silencing aDS ACh release impaired behavioral extinction, suggesting a role for ACh elevations in down-regulating cue-reward associations. Dopamine release in aDS dipped for cues during extinction, but glutamate input onto cholinergic interneurons did not change, suggesting an intrastriatal mechanism for the emergence of ACh elevations. Our large scale measurements indicate how and where ACh dynamics can shape region-specific plasticity to gate learning and promote extinction of Pavlovian associations.

neuroscience↗

bioRxiv2023

Targeted micro-fiber arrays for measuring and manipulating localized multi-scale neural dynamics over large, deep brain volumes during behavior

Neural population dynamics relevant for behavior vary over multiple spatial and temporal scales across 3-dimensional volumes. Current optical approaches lack the spatial coverage and resolution necessary to measure and manipulate naturally occurring patterns of large-scale, distributed dynamics within and across deep brain regions such as the striatum. We designed a new micro-fiber array and imaging approach capable of chronically measuring and optogenetically manipulating local dynamics across over 100 targeted locations simultaneously in head-fixed and freely moving mice. We developed a semi-automated micro-CT based strategy to precisely localize positions of each optical fiber. This highly-customizable approach enables investigation of multi-scale spatial and temporal patterns of cell-type and neurotransmitter specific signals over arbitrary 3-D volumes at a spatial resolution and coverage previously inaccessible. We applied this method to resolve rapid dopamine release dynamics across the striatum volume which revealed distinct, modality specific spatiotemporal patterns in response to salient sensory stimuli extending over millimeters of tissue. Targeted optogenetics through our fiber arrays enabled flexible control of neural signaling on multiple spatial scales, better matching endogenous signaling patterns, and spatial localization of behavioral function across large circuits.

neuroscience↗

bioRxiv2021

Tuned to Learn: An anticipatory hippocampal convergence state conducive to memory formation revealed during midbrain activation

The hippocampus has been a focus of memory research since H.Ms surgery in 1953 abolished his ability to form new memories, yet its mechanistic role in memory is still debated. Here, we identify a novel, systems-level candidate memory mechanism: an anticipatory hippocampal "convergence state", observed while awaiting valuable information, that both predicts later memory, and accounts for the relationship between midbrain activation and enhanced learning. To reveal this state, we leveraged endogenous neuromodulation associated with motivation: During fMRI, participants viewed trivia questions eliciting high or low curiosity, each followed seconds later by its answer. We reasoned that memory encoding success requires a convergence of factors, and as such, hippocampal states associated with remembered trials would be less variable than forgotten ones. Using a novel multivariate approach, we measured convergence by quantifying the typicality of spatially distributed patterns. We found that during anticipation of trivia answers, hippocampal states showed greater convergence under high than low curiosity. Crucially, convergence in the hippocampus increased with greater midbrain activation and uniquely accounted for the association between midbrain activation and subsequent memory recall. We propose that this novel convergence state in the hippocampus reflects a mechanism of its contribution to long term memory formation and that engagement of this convergence state completes the cascade from motivation to midbrain activity to memory enhancement.

neuroscience↗

bioRxiv2019

Brain-wide electrical spatiotemporal dynamics encode reward anticipation

Anticipation of an upcoming stimulus induces neural activity across cortical and subcortical regions and influences subsequent behavior. Nevertheless, the network mechanism whereby the brain integrates this information to signal the anticipation of rewards remains relatively unexplored. Here we employ multi-circuit electrical recordings from six brain regions as mice perform a sample-to-match task in which reward anticipation is operationalized as their progress towards obtaining a potential reward. We then use machine learning to discover the naturally occurring network patterns that integrate this neural activity across timescales. Only one of the networks that we uncovered signals responses linked to reward anticipation, specifically relative proximity and reward magnitude. Activity in this Electome (electrical functional connectivity) network is dominated by theta oscillations leading from prelimbic cortex and striatum that converge on ventral tegmental area, and by beta oscillations leading from striatum that converge on prelimbic cortex. Network activity is also synchronized with brain-wide cellular firing. Critically, this network generalizes to new groups of healthy mice, as well as a mouse line that models aberrant neural circuitry observed in brain disorders that show altered reward anticipation. Thus, our findings reveal the network-level architecture whereby the brain integrates spatially distributed activity across timescales to signal reward anticipation.

neuroscience↗