Not all pre-registrations are equal

There is growing recognition that troubling numbers of experiments fail to replicate in fields relevant to Neuropsychopharmacology, from neuroimaging [1] to animal behaviour [2]. We believe a counteraction to this, led by pharmacology, is increased emphasis on the distinction between exploratory and confirmatory scientific practices [3]. Exploratory research, where multiple methodologies and analyses are trialled, is vital for discovery. In contrast, confirmatory research requires that this flexibility is minimised to address a well-specified research question. We aim to highlight problems that arise when this boundary is blurred, and how a new vista of publishing formats generally help by nailing down this distinction. However, some formats can allow problematic flexibility to re-enter under a confirmatory guise

Understanding psychiatric risk from DLG2 haploinsufficiency CNVs through the phenotyping of a Dlg2+/- rat model

Copy number variants at the 11q14.1 locus are associated with multiple psychiatric conditions (e.g. Kirov et al., 2012; Gao et al., 2018). The candidate gene within this CNV, which is either completely deleted or duplicated, is DLG2 (coding PSD-93). PSD-93, a synaptic scaffold protein, stabilises effectors in the postsynaptic density of excitatory synapses. If PSD-93 content is altered key synaptic processes may be disrupted. Phenotyping a rat model heterozygous for Dlg2 (+/-), which models the deletion CNV in patients, can help isolate endophenotypes with cross-disorder relevance. At the protein level Dlg2+/- rats show a decrease in PSD-93 without changes to PSD-95 or NR1 expression. Ex-vivo structural MRI scans were analysed for white matter abnormalities and differences in grey matter volume; however no genotype effects were seen. Behavioural phenotyping was conducted using assays relevant to symptom domains seen in 11q14.1 deletion syndromes including anxiety, social behaviour, PCP-hyperlocomotion, and sensorimotor gating. Memory and learning in a battery of object recognition tasks and water-maze reference memory were assessed as an index of cognitive ability. Hedonic responses to stimuli, appetitive conditioning, and motivation to work for reward were assessed to capture reward processing. Finally, a novel paradigm to assess the propensity towards hallucinations and delusions in rodents was conducted. Dlg2+/- rats performed as wild-types on almost all measured domains and tasks. In many cases this presents a departure from findings with Dlg2 homozygous (-/-) knockout mice who demonstrate increased anxiety and deficient social behaviour. With the caveats of drawing conclusions across species and experiments, this highlights the importance of using the most clinically valid (i.e. heterozygous) models when characterising the effects of CNVs. Dlg2+/- rats showed a potentiated and sustained locomotor response to the psychostimulant PCP, showing that although its effects are subtle, deleting one copy of Dlg2 in a rat model does result in a compromised system with a possible psychosis susceptibility

Behavioral training rescues motor deficits in Cyfip1 haploinsufficiency mouse model of Autism Spectrum Disorders

Deletions in the 15q11.2 region of the human genome are associated with neurobehavioral deficits, and motor development delay, as well as in some cases, symptoms of autism or schizophrenia. The cytoplasmic FMRP-interacting protein 1 (CYFIP1) is one of the four genes contained within this locus and has been associated with other genetic forms of autism spectrum disorders (ASD). In mice, Cyfip1 haploinsufficiency leads to alteration of dendritic spine morphology and defects in synaptic plasticity, two pathophysiological hallmarks of mouse models of ASD. At the behavioral level, however, Cyfip1 haploinsufficiency leads to minor phenotypes, not directly relevant for 15q11.2 deletion syndrome or ASD. A fundamental question is whether neuronal phenotypes caused by the mutation of Cyfip1 are relevant for the human condition. Here, we describe a synaptic cluster of ASD-associated proteins centered on CYFIP1 and the adhesion protein Neuroligin-3. Cyfip1 haploinsufficiency in mice led to decreased dendritic spine density and stability associated with social behavior and motor learning phenotypes. Behavioral training early in development resulted in alleviating the motor learning deficits caused by Cyfip1 haploinsufficiency. Altogether, these data provide new insight into the neuronal and behavioral phenotypes caused by Cyfip1 mutation and proof-of-concept for the development of a behavioral therapy to treat phenotypes associated with 15q11.2 syndromes and ASD

The Role of Electric Vehicle Charging Technologies in the Decarbonisation of the Energy Grid

Vehicle-to-grid (V2G) has been identified as a key technology to help reduce carbon emissions from the transport and energy sectors. However, the benefits of this technology are best achieved when multiple variables are considered in the process of charging and discharging an electric vehicle. These variables include vehicle behaviour, building energy demand, renewable energy generation, and grid carbon intensity. It is expected that the transition to electric mobility will add pressure to the energy grid. Using the batteries of electric vehicles as energy storage to send energy back to the grid during high-demand, carbon-intensive periods will help to reduce the impact of introducing electric vehicles and minimise carbon emissions of the system. In this paper, the authors present a method and propose a V2G control scheme integrating one year of historical vehicle and energy datasets, aiming towards carbon emissions reduction through increased local consumption of renewable energy, offset of vehicle charging demand to low carbon intensity periods, and offset of local building demand from peak and carbon-intensive periods through storage in the vehicle battery. The study included assessment of strategic location and the number of chargers to support a fleet of five vehicles to make the transition to electric mobility and integrate vehicle-to-grid without impacting current service provision. The authors found that the proposed V2G scheme helped to reduce the average carbon intensity per kilowatt (gCO2/kWh) in simulation scenarios, despite the increased energy demand from electric vehicles charging. For instance, in one of the tested scenarios V2G reduced the average carbon intensity per kilowatt from 223.8 gCO2/kWh with unmanaged charging to 218.9 gCO2/kWh using V2G

Where Will You Park? Predicting Vehicle Locations for Vehicle-to-Grid

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). Vehicle‐to‐grid services draw power or curtail demand from electric vehicles when they are connected to a compatible charging station. In this paper, we investigated automated machine learning for predicting when vehicles are likely to make such a connection. Using historical data collected from a vehicle tracking service, we assessed the technique's ability to learn and predict when a fleet of 48 vehicles was parked close to charging stations and compared this with two moving average techniques. We found the ability of all three approaches to predict when individual vehicles could potentially connect to charging stations to be comparable, resulting in the same set of 30 vehicles identified as good candidates to participate in a vehicle‐to‐grid service. We concluded that this was due to the relatively small feature set and that machine learning techniques were likely to outperform averaging techniques for more complex feature sets. We also explored the ability of the approaches to predict total vehicle availability and found that automated machine learning achieved the best performance with an accuracy of 91.4%. Such technology would be of value to vehicle‐to‐grid aggregation services

We got the power: Predicting available capacity for vehicle-to-grid services using a deep recurrent neural network

© 2021 Elsevier Ltd Vehicle-to-grid (V2G) services utilise a population of electric vehicle batteries to provide the aggregated capacity required to participate in power and energy markets. Such participation relies on the prediction of available capacity to support the reliable delivery of agreed reserves at a future time. In this work real historical trip data from a fleet of vehicles belonging to the University of Nottingham was used and a simulation developed to show how battery state-of-charge and available capacity would vary if these trips were taken in electric vehicles that were charged at simulated charging station locations. A time series forecasting neural network was developed to predict aggregated available capacity for the next 24-h period given input data from the previous 24 h and its increased predictive capability over a regression model trained using automated machine learning was demonstrated. The simulations were then extended to include delivery of reserves to satisfy the needs of simulated market events and the ability of the model to successfully adapt its predictions to such events was demonstrated. The authors conclude that this ability is of critical importance to the viability and success of future V2G services by supporting trading and vehicle utilisation decisions for multiple market events

Behavioural and molecular characterisation of the Dlg2 haploinsufficiency rat model of genetic risk for psychiatric disorder

Genetic studies implicate disruption to the DLG2 gene in copy number variants as increasing risk for schizophrenia, autism spectrum disorders and intellectual disability. To investigate psychiatric endophenotypes associated with DLG2 haploinsufficiency (and concomitant PSD-93 protein reduction) a novel clinically relevant Dlg2+/− rat was assessed for abnormalities in anxiety, sensorimotor gating, hedonic reactions, social behaviour, and locomotor response to the N-Methyl-D-aspartic acid receptor antagonist phencyclidine. Dlg gene and protein expression were also investigated to assess model validity. Reductions in PSD-93 messenger RNA and protein were observed in the absence of compensation by other related genes or proteins. Behaviourally Dlg2+/− rats show a potentiated locomotor response to phencyclidine, as is typical of psychotic disorder models, in the absence of deficits in the other behavioural phenotypes assessed here. This shows that the behavioural effects of Dlg2 haploinsufficiency may specifically relate to psychosis vulnerability but are subtle, and partially dissimilar to behavioural deficits previously reported in Dlg2+/− mouse models demonstrating issues surrounding the comparison of models with different aetiology and species. Intact performance on many of the behavioural domains assessed here, such as anxiety and reward processing, will remove these as confounds when continuing investigation into this model using more complex cognitive tasks