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Gene therapy with AAV vectors carrying genes for neuropeptide Y and its receptor Y2 has been shown to inhibit seizures in multiple animal models of epilepsy. It is however unknown how the AAV serotype or the sequence order of these two transgenes in the expression cassette affects the actual parenchymal gene expression levels and the seizure-suppressant efficacy. To address these questions, we compared three viral vector serotypes (AAV1, AAV2 and AAV8) and two transgene sequence orders (NPY-IRES-Y2 and Y2-IRES-NPY) in a rat model of acutely induced seizures. Wistar male rats were injected bilaterally with viral vectors and 3 weeks later acute seizures were induced by a subcutaneous injection of kainate. The latency until 1st motor seizure, time spent in motor seizure and latency to status epilepticus were measured to evaluate the seizure-suppressing efficacy of these vectors compared to an empty cassette control vector. Based on the results, the effect of the AAV1-NPY-IRES-Y2 vector was further investigated by in vitro electrophysiology, and its ability to achieve transgene overexpression in resected human hippocampal tissue was evaluated. The AAV1-NPY-IRES-Y2 proved to be better to any other serotype or gene sequence considering both transgene expression and ability to suppress induced seizures in rats. The vector also demonstrated transgene-induced decrease of glutamate release from excitatory neuron terminals and significantly increased both NPY and Y2 expression in resected human hippocampal tissue from patients with drug-resistant temporal lobe epilepsy. These results validate the feasibility of NPY/Y2 receptor gene therapy as a therapeutic opportunity in focal epilepsies.

A major goal of neuroscience is to reveal mechanisms supporting collaborative actions of neurons in local and larger-scale networks. However, no clear overall principle of operation has emerged despite decades-long experimental efforts. Here, we used an unbiased method to extract and identify the dynamics of local postsynaptic network states contained in the cortical field potential. Field potentials were recorded by depth electrodes targeting a wide selection of cortical regions during spontaneous activities, and sensory, motor, and cognitive experimental tasks. Despite different architectures and different activities, all local cortical networks generated the same type of dynamic confined to one region only of state space. Surprisingly, within this region, state trajectories expanded and contracted continuously during all brain activities and generated a single expansion followed by a contraction in a single trial. This behavior deviates from known attractors and attractor networks. The state-space contractions of particular subsets of brain regions cross-correlated during perceptive, motor, and cognitive tasks. Our results imply that the cortex does not need to change its dynamic to shift between different activities, making task-switching inherent in the dynamic of collective cortical operations. Our results provide a mathematically described general explanation of local and larger scale cortical dynamic.

IntroductionOne outstanding challenge for machine learning in diagnostic biomedical imaging is algorithm interpretability. A key application is the identification of subtle epileptogenic focal cortical dysplasias (FCDs) from structural MRI. FCDs are difficult to visualise on structural MRI but are often amenable to surgical resection. We aimed to develop an open-source, interpretable, surface-based machine-learning algorithm to automatically identify FCDs on heterogeneous structural MRI data from epilepsy surgery centres worldwide.MethodsThe Multi-centre Epilepsy Lesion Detection (MELD) Project collated and harmonised a retrospective MRI cohort of 1015 participants, 618 patients with focal FCD-related epilepsy and 397 controls, from 22 epilepsy centres worldwide. We created a neural network for FCD detection based on 33 surface-based features. The network was trained and cross-validated on 50% of the total cohort and tested on the remaining 50% as well as on 2 independent test sites. Multidimensional feature analysis and integrated gradient saliencies were used to interrogate network performance.ResultsOur pipeline outputs individual patient reports, which identify the location of predicted lesions, alongside their imaging features and relative saliency to the classifier. Overall, after including a border-zone around lesions, the developed MELD FCD surface-based algorithm had a sensitivity of 67% and a specificity of 54% on the withheld test cohort, and a sensitivity of 85% on a restricted subcohort of seizure free patients with FCD type IIB who had T1 and FLAIR MRI data.ConclusionsThis multicentre, multinational study with open access protocols and code has developed a robust and interpretable machine-learning algorithm for automated detection of focal cortical dysplasias, giving physicians greater confidence in the identification of subtle MRI lesions.HighlightsThis large, multi-centre, multi-scanner neuroimaging cohort captures the heterogeneity of histopathological subtypes and imaging features of patients with FCD.We developed a robust and interpretable surface-based algorithm which detects FCDs with a sensitivity of 67% and a specificity of 54%.The algorithm generates individual patient reports that “open the AI black-box” highlighting predicted lesion locations, alongside the imaging features and their relative saliency to the classifier.

Synaptic vesicle glycoprotein-2 (SV2) is a family of proteins consisting of SV2A, SV2B, and SV2C. This protein family has attracted attention in recent years after SV2A was shown to be an epileptic drug target and a perhaps a biomarker of synaptic density. So far, the anatomical localization of these proteins in the rodent and human brain have been reported, but co-expression of SV2 genes on a cellular level, their expressions in the human brain, comparison to radioligand binding, any possible regulation in epilepsy are not known. We have here analyzed the expression of SV2 genes in neuronal subtypes in the temporal neocortex in selected specimens by using single nucleus-RNA sequencing, and performed quantitative PCR in populations of temporal lobe epilepsy (TLE) patients and healthy controls. [3H]-UCB-J autoradiography was performed to analyze the correlation between the mRNA transcript and binding capacity to SV2A. Our data showed that the SV2A transcript is expressed in all glutamatergic and GABAergic cortical subtypes, while SV2B expression is restricted to only the glutamatergic neurons and SV2C has very limited expression in a small subgroup of GABAergic interneurons. The level of [3H]-UCB-J binding and the concentration of SV2A mRNA is strongly correlated in each patient, and the expression is lower in the TLE patients. There is no relationship between SV2A expression and age, sex, seizure frequency, duration of epilepsy, or whether patients were recently treated with levetiracetam or not. Collectively, these findings point out a neuronal subtype-specific distribution of the expression of the three SV2 genes, and the lower levels of both radioligand binding and expression further emphasize the significance of these proteins in this disease.

In recent years, gene therapy has resurged as a potential treatment for an increasing number of medical diseases including those affecting the central nervous system (CNS), which is discussed in this review. Clinical trials have revealed promising results particularly in gene therapy for Parkinson's disease with upregulation of dopamine synthesis or downregulation of huntingtin synthesis in Huntington's disease. Gene therapy for spinal motor atrophy has received FDA approval this year. The biggest success is seen in ophthalmology, where gene therapy has been FDA/EU-approved for retinitis pigmentosa, sparking further hope of use for other CNS diseases in a near future.

Psychotic symptoms have been linked to salience abnormalities in the brain reward system, perhaps caused by a dysfunction of the dopamine neurotransmission in striatal regions. Blocking dopamine D2 receptors dampens psychotic symptoms and normalises reward disturbances, but a direct relationship between D2 receptor blockade, normalisation of reward processing and symptom improvement has not yet been demonstrated. The current study examined the association between blockade of D2 receptors in the caudate nucleus, alterations in reward processing and the psychopathology in a longitudinal study of antipsychotic-naïve first-episode schizophrenia patients.Twenty-two antipsychotic-naïve first-episode schizophrenia patients (10 males, mean age 23.3) and 23 healthy controls (12 males, mean age 23.5) were examined with single-photon emission computed tomography using 123I-labelled iodobenzamide. Reward disturbances were measured with functional magnetic resonance imaging (fMRI) using a modified version of the monetary-incentive-delay task. Patients were assessed before and after 6 weeks of treatment with amisulpride.In line with previous results, patients had a lower fMRI response at baseline (0.2 ± 0.5 v. 0.7 ± 0.6; p = 0.008), but not at follow-up (0.5 ± 0.6 v. 0.6 ± 0.7), and a change in the fMRI signal correlated with improvement in Positive and Negative Syndrome Scale positive symptoms (ρ = -0.435, p = 0.049). In patients responding to treatment, a correlation between improvement in the fMRI signal and receptor occupancy was found (ρ = 0.588; p = 0.035).The results indicate that salience abnormalities play a role in the reward system in schizophrenia. In patients responding to a treatment-induced blockade of dopamine D2 receptors, the psychotic symptoms may be ameliorated by normalising salience abnormalities in the reward system.

During prolonged starvation, brain energy requirements are covered in part by the metabolism of ketone bodies. It is unknown whether short-term starvation of a few days' duration may lead to reduced brain glucose metabolism due to the change toward ketone body consumption. In the present study we measured the cerebral metabolism of glucose and ketone bodies in nine healthy volunteers before and after 3.5 days of starvation. Regional glucose metabolism was measured by dynamic positron emission tomography using [18F]2-fluoro-2-deoxy-D-glucose. The mean value of K*1 in gray and white matter increased by 12% (p < 0.05), whereas k*2 and k*3 were unchanged compared with control values. Regional glucose metabolism in cortical gray matter was reduced by 26% from 0.294 ± 0.054 to 0.217 ± 0.040 μmol g−1 min−1 (p < 0.001). White matter glucose metabolism decreased by 27% (p < 0.02). The decrease was uniform in gray and white matter with regional decreases ranging from 24 to 30%. A determination using Fick's principle confirmed the reduction in glucose metabolism yielding a decrease of 24% from 0.307 ± 0.050 to 0.233 ± 0.073 μmol g−1 min−1 (p < 0.05), whereas CBF did not change (0.57 ± 0.07 vs. 0.57 ± 0.06 ml g−1 min−1). The global net uptake of β-hydroxybutyrate increased 13-fold from 0.012 ± 0.024 to 0.155 ± 0.140 μmol g−1 min−1 (p < 0.05). Net uptake of acetoacetate and net efflux of lactate and pyruvate did not change significantly during starvation. The present study shows that the human brain adapts to the changes in energy supply as early as 3 days following initiation of starvation, at which time ketone bodies account for approximately one-fourth of the cerebral energy requirements.