Nature neuroscience最新文献

Brain function requires a constant supply of glucose. However, the brain has no known energy stores, except for glycogen granules in astrocytes. In the present study, we report that continuous oligodendroglial lipid metabolism provides an energy reserve in white matter tracts. In the isolated optic nerve from young adult mice of both sexes, oligodendrocytes survive glucose deprivation better than astrocytes. Under low glucose, both axonal ATP levels and action potentials become dependent on fatty acid β-oxidation. Importantly, ongoing oligodendroglial lipid degradation feeds rapidly into white matter energy metabolism. Although not supporting high-frequency spiking, fatty acid β-oxidation in mitochondria and oligodendroglial peroxisomes protects axons from conduction blocks when glucose is limiting. Disruption of the glucose transporter GLUT1 expression in oligodendrocytes of adult mice perturbs myelin homeostasis in vivo and causes gradual demyelination without behavioral signs. This further suggests that the imbalance of myelin synthesis and degradation can underlie myelin thinning in aging and disease.

Understanding the dynamical transformation of neural activity to behavior requires new capabilities to nonlinearly model, dissociate and prioritize behaviorally relevant neural dynamics and test hypotheses about the origin of nonlinearity. We present dissociative prioritized analysis of dynamics (DPAD), a nonlinear dynamical modeling approach that enables these capabilities with a multisection neural network architecture and training approach. Analyzing cortical spiking and local field potential activity across four movement tasks, we demonstrate five use-cases. DPAD enabled more accurate neural–behavioral prediction. It identified nonlinear dynamical transformations of local field potentials that were more behavior predictive than traditional power features. Further, DPAD achieved behavior-predictive nonlinear neural dimensionality reduction. It enabled hypothesis testing regarding nonlinearities in neural–behavioral transformation, revealing that, in our datasets, nonlinearities could largely be isolated to the mapping from latent cortical dynamics to behavior. Finally, DPAD extended across continuous, intermittently sampled and categorical behaviors. DPAD provides a powerful tool for nonlinear dynamical modeling and investigation of neural–behavioral data.

Learning to predict threat is essential, but equally important—yet often overlooked—is learning about the absence of threat. Here, by recording neural activity in two nucleus accumbens (NAc) glutamatergic afferents during aversive and neutral cues, we reveal sex-biased encoding of threat cue discrimination. In male mice, NAc afferents from the ventral hippocampus are preferentially activated by threat cues. In female mice, these ventral hippocampus–NAc projections are activated by both threat and nonthreat cues, whereas NAc afferents from medial prefrontal cortex are more strongly recruited by footshock and reliably discriminate threat from nonthreat. Chemogenetic pathway-specific inhibition identifies a double dissociation between ventral hippocampus–NAc and medial prefrontal cortex–NAc projections in cue-mediated suppression of reward-motivated behavior in male and female mice, despite similar synaptic connectivity. We suggest that these sex biases may reflect sex differences in behavioral strategies that may have relevance for understanding sex differences in risk of psychiatric disorders.

Neurovascular coupling links brain activity to local changes in blood flow, forming the basis for non-invasive brain mapping. Using multiscale imaging, we investigated how vascular activity spatially relates to neuronal activity elicited by single whiskers across different columns and layers of mouse cortex. Here we show that mesoscopic hemodynamic signals quantitatively reflect neuronal activity across space but are composed of a highly heterogeneous pattern of responses across individual vessel segments that is poorly predicted by local neuronal activity. Rather, this heterogeneity is dependent on vessel directionality, specifically in thalamocortical input layer 4, where capillaries respond preferentially to neuronal activity patterns along their downstream perfusion domain. Thus, capillaries fine-tune blood flow based on distant activity and encode laminar-specific activity patterns. These findings imply that vascular anatomy sets a resolution limit on functional imaging signals, where individual blood vessels inaccurately report neuronal activity in their immediate vicinity but, instead, integrate activity patterns along the vascular arbor.

Memory consolidation assimilates recent experiences into long-term memory. This process requires the replay of learned sequences, although the content of these sequences remains controversial. Recent work has shown that the statistics of replay deviate from those of experience: stimuli that are experientially salient may be either recruited or suppressed from sharp-wave ripples. In this study, we found that this phenomenon can be explained parsimoniously and biologically plausibly by a Hebbian spike-time-dependent plasticity rule at inhibitory synapses. Using models at three levels of abstraction—leaky integrate-and-fire, biophysically detailed and abstract binary—we show that this rule enables efficient generalization, and we make specific predictions about the consequences of intact and perturbed inhibitory dynamics for network dynamics and cognition. Finally, we use optogenetics to artificially implant non-generalizable representations into the network in awake behaving mice, and we find that these representations also accumulate inhibition during sharp-wave ripples, experimentally validating a major prediction of our model. Our work outlines a potential direct link between the synaptic and cognitive levels of memory consolidation, with implications for both normal learning and neurological disease.

Aging is a complex biological process and represents the largest risk factor for neurodegenerative disorders. The risk for neurodegenerative disorders is also increased in individuals with psychiatric disorders. Here, we characterized age-related transcriptomic changes in the brain by profiling ~800,000 nuclei from the orbitofrontal cortex from 87 individuals with and without psychiatric diagnoses and replicated findings in an independent cohort with 32 individuals. Aging affects all cell types, with LAMP5⁺LHX6⁺ interneurons, a cell-type abundant in primates, by far the most affected. Disrupted synaptic transmission emerged as a convergently affected pathway in aged tissue. Age-related transcriptomic changes overlapped with changes observed in Alzheimer’s disease across multiple cell types. We find evidence for accelerated transcriptomic aging in individuals with psychiatric disorders and demonstrate a converging signature of aging and psychopathology across multiple cell types. Our findings shed light on cell-type-specific effects and biological pathways underlying age-related changes and their convergence with effects driven by psychiatric diagnosis.