Electrophysiology has proven invaluable to record neural activity, and the development of Neuropixels probes dramatically increased the number of recorded neurons. These probes are often implanted acutely, but acute recordings cannot be performed in freely moving animals and the recorded neurons cannot be tracked across days. To study key behaviors such as navigation, learning, and memory formation, the probes must be implanted chronically. An ideal chronic implant should (1) allow stable recordings of neurons for weeks; (2) allow reuse of the probes after explantation; (3) be light enough for use in mice. Here, we present the "Apollo Implant", an open-source and editable device that meets these criteria and accommodates up to two Neuropixels 1.0 or 2.0 probes. The implant comprises a "payload" module which is attached to the probe and is recoverable, and a "docking" module which is cemented to the skull. The design is adjustable, making it easy to change the distance between probes, the angle of insertion, and the depth of insertion. We tested the implant across eight labs in head-fixed mice, freely moving mice, and freely moving rats. The number of neurons recorded across days was stable, even after repeated implantations of the same probe. The Apollo implant provides an inexpensive, lightweight, and flexible solution for reusable chronic Neuropixels recordings.

Head direction (HD) neurons, signalling facing direction, generate a signal that is primarily anchored to the outside world by visual inputs. We investigated the route for visual landmark information into the HD system in rats. There are two candidates: an evolutionarily older, larger subcortical retino-tectal pathway and a more recently evolved, smaller cortical retino-geniculo-striate pathway. We disrupted the cortical pathway by lesioning the dorsal lateral geniculate thalamic nuclei bilaterally, and recorded HD cells in the postsubicular cortex as rats foraged in a visual-cue-controlled enclosure. In lesioned rats we found the expected number of postsubicular HD cells. Although directional tuning curves were broader across a trial, this was attributable to the increased instability of otherwise normal-width tuning curves. Tuning curves were also poorly responsive to polarizing visual landmarks and did not distinguish cues based on their visual pattern. Thus, the retino-geniculo-striate pathway is not crucial for the generation of an underlying, tightly tuned directional signal but does provide the main route for vision-based anchoring of the signal to the outside world, even when visual cues are high in contrast and low in detail. KEY POINTS: Head direction (HD) cells indicate the facing direction of the head, using visual landmarks to distinguish directions. In rats, we investigated whether this visual information is routed through the thalamus to the visual cortex or arrives via the superior colliculus, which is a phylogenetically older and (in rodents) larger pathway. We lesioned the thalamic dorsal lateral geniculate nucleus (dLGN) in rats and recorded the responsiveness of cortical HD cells to visual cues. We found that cortical HD cells had normal tuning curves, but these were slightly more unstable during a trial. Most notably, HD cells in dLGN-lesioned animals showed little ability to distinguish highly distinct cues and none to distinguish more similar cues. These results suggest that directional processing of visual landmarks in mammals requires the geniculo-cortical pathway, which raises questions about when and how visual directional landmark processing appeared during evolution.

This study aimed to describe the relationship between blood and CSF volumes in different compartments on baseline CT after aSAH, assess if they independently predict long-term outcome, and explore their interaction with age. CT scans from patients participating in a prospective multicenter randomized controlled trial of patients with aSAH were segmented for blood and CSF volumes. The primary outcomes were the mRS, and the Subarachnoid Hemorrhage Outcome Tool (SAHOT) at day 28 and 180. Univariate regressions were conducted to identify significant predictors of poor outcomes, followed by principal component analysis to explore correlations between imaging variables and WFNS. A multivariate predictive model was then developed and optimized using stepwise regression. CT scans from 97 patients with a median delay from symptom onset of 271 min (131–547) were analyzed. Univariate analysis showed only WFNS, and total blood volume (TBV) were significant predictors of both short and long-term outcome with WFNS more predictive of mRS and TBV more predictive of SAHOT. Principal component analysis showed strong dependencies between the imaging predictors. Multivariate ordinal regression showed models with WFNS alone were most predictive of day 180 mRS and models with TBV alone were most predictive of SAHOT. TBV was the most significant measured imaging predictor of poor long-term outcome after aSAH. All these imaging predictors are correlated, however, and may have multiple complex interactions necessitating larger datasets to detect if they provide any additional predictive value for long-term outcome.

Purpose Cerebral vasospasm following aneurysmal subarachnoid hemorrhage (aSAH) is a significant complication associated with poor neurological outcomes. We present a novel, semi-automated pipeline, implemented in the open-source medical imaging analysis software ITK-SNAP, to segment subarachnoid blood volume from initial CT head (CTH) scans and use this to predict future radiological vasospasm. Methods 42 patients were admitted between February 2020 and December 2021 to our tertiary neurosciences center, and whose initial referral CTH scan was used for this retrospective cohort study. Blood load was segmented using a semi-automated random forest classifier and active contour evolution implemented in ITK-SNAP. Clinical data were extracted from electronic healthcare records in order to fit models aimed at predicting radiological vasospasm risk. Results Semi-automated segmentations demonstrated excellent agreement with manual, expert-derived volumes (mean Dice coefficient = 0.92). Total normalized blood volume, extracted from CTH images at first presentation, was significantly associated with greater odds of later radiological vasospasm, increasing by approximately 7% for each additional cm 3 of blood (OR = 1.069, 95% CI: 1.021–1.120; p < .005). Greater blood volume was also significantly associated with vasospasm of a higher Lindegaard ratio, of longer duration, and a greater number of discrete episodes. Total blood volume predicted radiological vasospasm with a greater accuracy as compared to the modified Fisher scale (AUC = 0.86 vs 0.70), and was of independent predictive value. Conclusion Semi-automated methods provide a plausible pipeline for the segmentation of blood from CT head images in aSAH, and total blood volume is a robust, extendable predictor of radiological vasospasm, outperforming the modified Fisher scale. Greater subarachnoid blood volume significantly increases the odds of subsequent vasospasm, its time course and its severity.

Glioma Epileptiform Activity and Progression Are Driven by IGSF3-Mediated Potassium Dysregulation Curry RN, Aiba I, Meyer J, Lozzi B, Ko Y, McDonald MF, Rosenbaum A, Cervantes A, Huang-Hobbs E, Cocito C, Greenfield JP, Jalali A, Gavvala J, Mohila C, Harmanci AS, Noebels J, Rao G, Deneen B. Neuron. 2023;111(5): 682-695. doi: 10.1016/j.neuron.2023.01.013 Seizures are a frequent pathophysiological feature of malignant glioma. Recent studies implicate peritumoral synaptic dysregulation as a driver of brain hyperactivity and tumor progression; however, the molecular mechanisms that govern these phenomena remain elusive. Using scRNA-seq and intraoperative patient ECoG recordings, we show that tumors from seizure patients are enriched for gene signatures regulating synapse formation. Employing a human-to-mouse in vivo functionalization pipeline to screen these genes, we identify IGSF3 as a mediator of glioma progression and dysregulated neural circuitry that manifests as spreading depolarization (SD). Mechanistically, we discover that IGSF3 interacts with Kir4.1 to suppress potassium buffering and found that seizure patients exhibit reduced expression of potassium handlers in proliferating tumor cells. In vivo imaging reveals that dysregulated synaptic activity emanates from the tumor-neuron interface, which we confirm in patients. Our studies reveal that tumor progression and seizures are enabled by ion dyshomeostasis and identify SD as a driver of disease.

In recent years, there has been a significant increase in preclinical studies to test genetic therapies for epilepsy. Some of these therapies have advanced to clinical trials and are being tested in patients with monogenetic or focal refractory epilepsy. This article provides an overview of the current state of preclinical studies that show potential for clinical translation. Specifically, we focus on genetic therapies that have demonstrated a clear effect on seizures in animal models and have the potential to be translated to clinical settings. Both therapies targeting the cause of the disease and those that treat symptoms are discussed. We believe that the next few years will be crucial in determining the potential of genetic therapies for treating patients with epilepsy.

Winner of the NANSIG essay competition 2020. Over the past years, the number of neuroscience papers involving big data or machine learning has risen supra-linearly -- both in absolute numbers and as a proportion. In this paper, I propose that the drive of big data will stimulate significant change in neuroscience over the next decade -- changes that need to occur if neuroscience is to maximise the potential big data holds.