Neuron最新文献

Memories can be altered when they are recalled through the process of reconsolidation, requiring gene expression in brain cells that store these memories. How brain circuits reformat memories during recall by directing molecular signaling in specific neuronal populations is not known. Here, we show that brainstem noradrenaline projections to the amygdala, a brain region that stores aversive emotional memories, control memory reconsolidation in rats. During reconsolidation, this circuit regulates the nuclear translocation of CREB-regulated transcriptional coactivator-1 (CRTC1), a molecule important for synapse-to-nucleus transcriptional regulation, through β₂-adrenergic receptor (β₂-AR) signaling. Cell-type-specific molecular manipulations revealed that reconsolidation requires both β₂-AR signaling and CRTC1 in an anatomically and genetically defined amygdala cell population. Finally, increasing stress prior to memory recall enhanced reconsolidation, an effect that was mimicked by amygdala cell-type-specific upregulation of noradrenaline signaling. These results reveal a circuit-to-molecular pathway for state-dependent modification of emotional memories during recall.

Recurrent neural networks can generate dynamics, but in the sensory cortex, it has been unclear if any dynamic processing is supported by the dense recurrent excitatory-excitatory network. Here, we show a role for recurrent connections in the mouse visual cortex: they support powerful dynamical computations, but by filtering sequences of input instead of generating sequences. Using two-photon optogenetics, we measure neural responses to natural images and play them back, finding that responses are boosted when inputs are played back during the correct movie dynamic context-when the preceding sequence corresponds to natural vision. This sequence selectivity depends on a network mechanism: earlier input patterns produce responses in other local neurons, which interact with later input patterns. We confirm this mechanism by designing sequences of inputs that are boosted or attenuated by the network. These data suggest that recurrent cortical connections perform predictive processing, encoding the statistics of the natural world in input-output transformations.

Local dendritic computations are thought to critically influence neuronal signaling and plasticity yet remain largely unexplored in vivo due to challenges in stably imaging small structures at ultrafast timescales. We developed a 3D real-time motion correction platform for movement-stabilized, ultrafast two-photon voltage imaging. By co-labeling CA1 pyramidal neurons with voltage and calcium indicators, we simultaneously measured somato-dendritic and electro-calcium coupling at multiple dendritic sites. We characterized isolated dendritic spikes and distance-dependent backpropagation of naturally occurring and photostimulation-evoked bursts and single spikes. We found that bursts backpropagated more reliably than single spikes, validated that somato-dendritic coupling decreases with distance from soma, and showed that electro-calcium coupling decreases with increasing branch order. These findings provide in vivo evidence for distance-dependent invasion of somatic signals into dendrites, highlight the prevalence of isolated dendritic events, and show that dendritic structure isolates voltage from calcium signaling, potentially enabling unique intracellular pathways in distal dendrites.

The development of an adult brain from a single zygote requires cells and axons to organize in precise spatial patterns over long distances. Most mechanisms for positional information rely on diffusible molecular cues that move through the tissue, fundamentally limiting the pattern's ability to scale over the requisite orders of magnitude. Here, we propose a complementary mechanism in which positional information is inherited through the cell lineage, rather than transmitted through extracellular signals, thereby avoiding these scaling constraints. Analyzing brain-wide developmental expression in mouse and larval zebrafish, we find that principal eigengenes-co-expression patterns across thousands of genes-span multiple spatial scales, remain stable over development, and are conserved across species. Moreover, small subsets of genes can decode eigengenes, yielding multi-scale positional information. Together, these findings suggest a lineage-based mechanism for scalable positional information that complements diffusion-based mechanisms and offers a general framework for tissue patterning.

α-Synuclein conformational strains provide a potential explanation for the clinical and pathological differences among synucleinopathies such as Parkinson's disease and multiple system atrophy. However, how distinct α-synuclein strains arise remains unknown. Here, we observed conformational heterogeneity between individual preparations of α-synuclein pre-formed fibrils (PFFs) generated by polymerizing wild-type or A53T-mutant human α-synuclein under identical conditions. Moreover, we found that α-synuclein aggregates formed spontaneously in the brains of a transgenic synucleinopathy mouse model are conformationally diverse. Propagation of stochastically formed PFF- and brain-derived α-synuclein strains in mice initiated several distinct synucleinopathies. The conformational diversity of α-synuclein aggregates across PFF preparations and between individual mice demonstrates that α-synuclein can spontaneously form multiple self-propagating strains within an identical environment. This suggests that stochastic misfolding into distinct aggregate structures drives the emergence of α-synuclein strains and reveals that the intrinsic variability of common synucleinopathy research tools must be considered when designing and interpreting experiments.

We demonstrate a noninvasive approach for measuring transgene expression in the brains of nonhuman primates using blood-based assays with engineered reporters termed released markers of activity (RMAs). RMAs cross the blood-brain barrier via reverse transcytosis, allowing detection of brain-derived markers in the bloodstream. Using this approach, we demonstrate repeated monitoring of multiple transgenes expressed in cortical and subcortical regions over several weeks. RMAs are sufficiently sensitive to detect circuit-specific, Cre-dependent adeno-associated viral (AAV) expression, and RMA signals are correlated with histological quantification of gene expression in neural tissue. Together, these findings establish the RMA platform as a cost-efficient and repeatable tool for neuroscience studies in nonhuman primates, enabling sensitive and multiplexed measurement of brain gene expression with a simple blood test.

Drug craving persists after prolonged abstinence, posing a major challenge in treating substance use disorders. The ventral medial prefrontal cortex (vmPFC) plays a critical role in impulsivity and decision-making, making it a promising target for mitigating drug craving by orchestrating downstream brain-wide activity. However, the dynamics of vmPFC sub-circuits during the progression of drug addiction remain unclear. Here, we uncover a circuit-level mechanism by which distinct vmPFC sub-circuits, defined by cell-type-specific interneurons and projection-specific cortical outputs, differentially modulate mesolimbic pathways to drive drug-seeking behavior. Our results reveal that distinct interneuron subtypes display unique activity dynamics and exert selective modulation over projection-specific cortical outputs. Notably, parvalbumin (PV)-positive interneurons exhibit target-specific synaptic remodeling with pyramidal neurons projecting to distinct downstream targets, which is crucial for modulating mesolimbic circuits and driving persistent cocaine seeking after abstinence. These findings provide compelling insights into vmPFC microcircuit mechanisms underlying substance use disorders.