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Vu, M.-A.

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

2 recordsLinked to original sources

Inherited input and local transformations shape the spatiotemporal organization of pathway specific striatal signals for motivated behavior

Adaptive behavior requires neural circuits to link sensory events with their location, predictive value, and temporal relationship to outcomes. Although striatal circuits are implicated in this process, it remains unclear how motivationally relevant signals are organized across striatal regions and direct- and indirect-pathway spiny projection neurons, and which components reflect afferent input versus local transformations. Using striatum-wide calcium recordings during visual conditioning in mice, we found that learned cue value, reward proximity, cue location, and lick-related behavior were encoded in distinct regions and time windows. These signals included both pathway-convergent representations and pathway-opponent dynamics. Striatum-wide measurements of glutamatergic input targeted to each SPN subtype revealed that rapid cue-location and lick-related signals were present in afferent input to both pathways, consistent with inherited representations. In contrast, pathway-opponent pDMS value signals and dSPN-selective pVLS ramping were absent from corresponding glutamatergic input dynamics, indicating local striatal transformations. These findings reveal region-specific input-output transformations that organize striatal signals for distinct components of motivated behavior.

neuroscience↗

A convergent depression vulnerability pathway encoded by emergent spatiotemporal dynamics

Fluctuations in brain local field potential (LFP) oscillations reflect emergent network-level signals that mediate behavior. Cracking the code whereby these LFP oscillations coordinate in time and space (spatiotemporal dynamics) to represent complex behaviors would provide fundamental insights into how the brain signals emotional processes at the network level. Here we use machine learning to integrate LFP activity acquired concurrently from seven cortical and subcortical brain regions into an analytical model that predicts the emergence of depression-related behavioral dysfunction across individual mice subjected to chronic social defeat stress. We uncover a spatiotemporal dynamic network in which activity originates in prefrontal cortex (PFC) and nucleus accumbens (NAc, ventral striatum), relays through amygdala and ventral tegmental area (VTA), and converges in ventral hippocampus (VHip). The activity of this network correlates with acute threat responses and brain-wide cellular firing, and it is enhanced in three independent molecular-, physiological-, and behavioral-based models of depression vulnerability. Finally, we use two antidepressant manipulations to demonstrate that this vulnerability network is biologically distinct from the networks that signal behavioral dysfunction after stress. Thus, corticostriatal to VHip-directed spatiotemporal dynamics organized at the network level are a novel convergent depression vulnerability pathway.

neuroscience↗