No abstract

The brain needs to track body energy state to optimize physiology and behavior. Important information about current and future energy states is contained in minute-to-minute fluctuations in blood glucose. However, it is unclear whether brain glucose sensors are capable of responding to this temporal structure to extract such information. In behaving mammals, hypothalamic hypocretin/orexin neurons (HONs) control arousal and are proposed to sense energy balance, yet recent studies show that HON activity varies rapidly (over seconds) with locomotion. It remains unknown if and how HONs reflect blood glucose fluctuations. Here, for the first time, we co-monitored HON activity and blood glucose in behaving mice, uncovering inhibition of HONs by rising blood glucose. Surprisingly, peak HON signals (population waves) anticipated peak glucose deviations by several minutes. In multivariate analysis of diverse HON activity correlates (locomotion, metabolic variables), the glucose temporal gradient (negative first derivative) emerged as prime predictor of HON population activity on the minute timescales, thereby explaining this anticipatory response. Furthermore, 2-photon imaging of >900 individual HONs revealed parallel communication of absolute blood glucose values and their derivatives in distinct HON subsets. Thus, HONs transmit multiplexed slowly and rapidly changing information, and, in the slow bandwidth, extract temporal features from blood glucose dynamics that suggest a hybrid of anticipatory and proportional logic in brain responses to blood glucose.

Significance Anxiety disorders are among the most prevalent mental illnesses worldwide. Despite significant advances in their treatment, many patients remain treatment resistant. Thus, new treatment modalities and targets are much needed. Therefore, we developed a deep brain stimulation therapy that targets a recently identified anxiety center in the lateral hypothalamus. We show that this therapy rapidly silences anxiety-implicated neurons and immediately relieves diverse anxiety symptoms in a variety of stressful situations. This therapeutic effect occurs without acute or chronic side effects that are typical of many existing treatments, such as physical sedation or memory deficits. These findings identify a clinically applicable new therapeutic strategy for helping patients to manage treatment-resistant anxiety.

Vagus nerve stimulation (VNS) is a neuromodulation therapy for a broad and rapidly expanding set of neurologic conditions. Classically used to treat epilepsy and depression, VNS has recently received FDA approval for stroke rehabilitation and is under preclinical and clinical investigation for other neurologic indications. Despite benefits across a diverse range of neurological disorders, the mechanism through which VNS influences central nervous system circuitry is not well described, limiting therapeutic optimization. A deeper understanding of the influence of VNS on neural circuits and activity is needed to maximize the use of VNS therapy across a broad range of neurologic conditions.To investigate how VNS can influence the neurons and circuits that underlie behavior, we paired VNS with upper limb movement in mice learning a skilled motor task. We leveraged genetic tools to perform optogenetic circuit dissection, as well as longitudinal in vivo imaging of calcium activity in cortical neurons to understand the effect of VNS on neural function. We found that VNS robustly enhanced motor learning when temporally paired with successful movement outcome, while randomly applied VNS impaired learning. This suggests that temporally-precise VNS may act through augmenting outcome cues, such as reinforcement signals. Within motor cortex, VNS paired with movement outcome selectively modulates the neural population that represents outcome, but not other movement-related neurons, across both acute and behaviorally-relevant timescales. Phasic cholinergic signaling from basal forebrain is required both for VNS-driven improvements in motor learning and the effects on neural activity in M1. These results indicate that VNS enhances motor learning through precisely-timed phasic cholinergic signaling to reinforce outcome, resulting in the recruitment of specific, behaviorally-relevant cortical circuits. A deeper understanding of the mechanisms of VNS on neurons, circuits and behavior provides new opportunities to optimize VNS to treat neurologic conditions.

Novel technology and stimulation paradigms allow for closed-loop implementation of neurostimulation systems with unprecedented spatiotemporal precision. In turn, precise, closed-loop neurostimulation appears to preferentially drive neural plasticity in motor networks, promoting neural repair. Recent clinical studies demonstrate that electrical stimulation can drive neural plasticity in damaged motor circuits, leading to meaningful functional improvement for users. Future advances in these areas hold promise for the treatment of a wide range of motor systems disorders.