Hypothalamic CRH neurons represent physiological memory of positive and negative experience.

Recalling a salient experience provokes specific behaviors and changes in the physiology or internal state. Relatively little is known about how physiological memories are encoded. We examined the neural substrates of physiological memory by probing CRHPVN neurons of mice, which control the endocrine response to stress. Here we show these cells exhibit contextual memory following exposure to a stimulus with negative or positive valence. Specifically, a negative stimulus invokes a two-factor learning rule that favors an increase in the activity of weak cells during recall. In contrast, the contextual memory of positive valence relies on a one-factor rule to decrease activity of CRHPVN neurons. Finally, the aversive memory in CRHPVN neurons outlasts the behavioral response. These observations provide information about how specific physiological memories of aversive and appetitive experience are represented and demonstrate that behavioral readouts may not accurately reflect physiological changes invoked by the memory of salient experiences.

Windows into stress: a glimpse at emerging roles for CRHPVN neurons.

The corticotropin-releasing hormone cells in the paraventricular nucleus of the hypothalamus (CRHPVN) control the slow endocrine response to stress. The synapses on these cells are exquisitely sensitive to acute stress, leveraging local signals to leave a lasting imprint on this system. Additionally, recent work indicates that these cells also play key roles in the control of distinct stress and survival behaviors. Here we review these observations and provide a perspective on the role of CRHPVN neurons as integrative and malleable hubs for behavioral, physiological, and endocrine responses to stress.

Complications of Deep Brain Stimulation for Parkinson Disease and Relationship between Micro-electrode tracks and hemorrhage: Systematic Review and Meta-Analysis.

BACKGROUND: Deep brain stimulation is a common treatment for Parkinson's disease (PD). Despite strong efficacy in well-selected patients, complications can occur. Intraoperative micro-electrode recording (MER) can enhance efficacy by improving lead accuracy. However, there is controversy as to whether MER increases risk of hemorrhage. OBJECTIVES: To provide a comprehensive systematic review and meta-analysis reporting complication rates from deep brain stimulation in PD. We also interrogate the association between hemorrhage and MER. METHODS: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were implemented while querying the Pubmed, Embase, and Cochrane databases. All included studies were randomized controlled trials and prospective case series with 5 or more patients. Primary outcomes included rates of overall revision, infection, lead malposition, surgical site and wound complications, hardware-related complications, and seizure. The secondary outcome was the relationship between number of MER tracks and hemorrhage rate. RESULTS: 262 articles with 21,261 patients were included in the analysis. Mean follow-up was 25.8 months (range 0-133). Complication rates were: revision 4.9%, infection 4.2%, lead malposition 3.3%, surgical site complications 2.8%, hemorrhage 2.4%, hardware-related complications 2.4%, and seizure 1.9%. While hemorrhage rate did not increase with single-track MER (odds ratio, 3.49; P = 0.29), there was a significant non-linear increase with each additional track. CONCLUSION: Infection and lead malposition were the most common complications. Hemorrhage risk increases with more than one MER track. These results highlight the challenge of balancing surgical accuracy and perioperative risk.

Particle-swarm based modelling reveals two distinct classes of CRHPVN neurons.

Electrophysiological recordings can provide detailed information of single neurons' dynamical features and shed light on their response to stimuli. Unfortunately, rapidly modelling electrophysiological data for inferring network-level behaviours remains challenging. Here, we investigate how modelled single neuron dynamics leads to network-level responses in the paraventricular nucleus of the hypothalamus (PVN), a critical nucleus for the mammalian stress response. Recordings of corticotropin releasing hormone neurons from the PVN (CRHPVN ) were performed using whole-cell current-clamp. These, neurons, which initiate the endocrine response to stress, were rapidly and automatically fit to a modified adaptive exponential integrate-and-fire model (AdEx) with particle swarm optimization (PSO). All CRHPVN neurons were accurately fit by the AdEx model with PSO. Multiple sets of parameters were found that reliably reproduced current-clamp traces for any single neuron. Despite multiple solutions, the dynamical features of the models such as the rheobase, fixed points, and bifurcations, were shown to be stable across fits. We found that CRHPVN neurons can be divided into two subtypes according to their bifurcation at the onset of firing: CRHPVN -integrators and CRHPVN -resonators. The existence of CRHPVN -resonators was then directly confirmed in a follow-up patch-clamp hyperpolarization protocol which readily induced post-inhibitory rebound spiking in 33% of patched neurons. We constructed networks of CRHPVN model neurons to investigate the network level responses of CRHPVN neurons. We found that CRHPVN -resonators maintain baseline firing in networks even when all inputs are inhibitory. The dynamics of a small subset of CRHPVN neurons may be critical to maintaining a baseline firing tone in the PVN. KEY POINTS: Corticotropin-releasing hormone neurons (CRHPVN ) in the paraventricular nucleus of the hypothalamus act as the final neural controllers of the stress response. We developed a computational modelling platform that uses particle swarm optimization to rapidly and accurately fit biophysical neuron models to patched CRHPVN neurons. A model was fitted to each patched neuron without the use of dynamic clamping, or other procedures requiring sophisticated inputs and fitting algorithms. Any neuron undergoing standard current clamp step protocols for a few minutes can be fitted by this procedure The dynamical analysis of the modelled neurons shows that CRHPVN neurons come in two specific 'flavours': CRHPVN -resonators and CRHPVN -integrators. We directly confirmed the existence of these two classes of CRHPVN neurons in subsequent experiments. Network simulations show that CRHPVN -resonators are critical to retaining the baseline firing rate of the entire network of CRHPVN neurons as these cells can fire rebound spikes and bursts in the presence of strong inhibitory synaptic input.

Early and isolated breast cancer metastasis to the pituitary: A case report and systematic review.

Background: Pituitary metastases (PMs) arising from breast cancer tend to occur many years following initial diagnosis, and after other systemic metastasis have been identified. Survival is generally considered to be poor. However, there are cases where patients present with an isolated metastatic lesion in the pituitary. Survival in this subset of patients has not been evaluated. We present a case of isolated PM that presented two years after initial diagnosis of breast cancer. We performed a systematic review of 38 breast cancer patients with PM. We report presentation, treatment strategy, and outcomes of breast cancer metastasis to the pituitary and highlight cases of isolated PM. Case Description: A 39 year old female presented with complaints of headache and polydipsia two years after diagnosis with breast cancer. Systemic workup was unremarkable, but brain imaging identified an isolated PM. Transsphenoidal debulking was performed with adjuvant radiation therapy (RT) targeted to the sellar region. Unfortunately, she passed away 9 months later from systemic progression. Conclusion: A total of 38 patients were included systematic review. Of these, 13 had isolated PM. Prevalent signs/ symptoms included visual disturbance, diabetes insipidus (DI), and hypothalamic dysfunction. Patients treated with surgical resection and adjuvant chemotherapy (ChT), or RT had better survival than those treated with resection alone. Patients that receive treatment for isolated PM may survive for many years without progression or recurrence.

A versatile computational algorithm for time-series data analysis and machine-learning models.

Here we introduce Local Topological Recurrence Analysis (LoTRA), a simple computational approach for analyzing time-series data. Its versatility is elucidated using simulated data, Parkinsonian gait, and in vivo brain dynamics. We also show that this algorithm can be used to build a remarkably simple machine-learning model capable of outperforming deep-learning models in detecting Parkinson's disease from a single digital handwriting test.

Paraventricular nucleus CRH neurons encode stress controllability and regulate defensive behavior selection.

In humans and rodents, the perception of control during stressful events has lasting behavioral consequences. These consequences are apparent even in situations that are distinct from the stress context, but how the brain links prior stressful experience to subsequent behaviors remains poorly understood. By assessing innate defensive behavior in a looming-shadow task, we show that the initiation of an escape response is preceded by an increase in the activity of corticotropin-releasing hormone (CRH) neurons in the paraventricular nucleus (PVN) of the hypothalamus (CRHPVN neurons). This anticipatory increase is sensitive to stressful stimuli that have high or low levels of outcome control. Specifically, experimental stress with high outcome control increases CRHPVN neuron anticipatory activity, which increases escape behavior in an unrelated context. By contrast, stress with no outcome control prevents the emergence of this anticipatory activity and decreases subsequent escape behavior. These observations indicate that CRHPVN neurons encode stress controllability and contribute to shifts between active and passive innate defensive strategies.

Social transmission and buffering of synaptic changes after stress.

Stress can trigger enduring changes in neural circuits and synapses. The behavioral and hormonal consequences of stress can also be transmitted to others, but whether this transmitted stress has similar effects on synapses is not known. We found that authentic stress and transmitted stress in mice primed paraventricular nucleus of the hypothalamus (PVN) corticotropin-releasing hormone (CRH) neurons, enabling the induction of metaplasticity at glutamate synapses. In female mice that were subjected to authentic stress, this metaplasticity was diminished following interactions with a naive partner. Transmission from the stressed subject to the naive partner required the activation of PVN CRH neurons in both subject and partner to drive and detect the release of a putative alarm pheromone from the stressed mouse. Finally, metaplasticity could be transmitted sequentially from the stressed subject to multiple partners. Our findings demonstrate that transmitted stress has the same lasting effects on glutamate synapses as authentic stress and reveal an unexpected role for PVN CRH neurons in transmitting distress signals among individuals.