Biology subjects

MELLOR, J. R.

Publications and source records attributed to MELLOR, J. R..

3 recordsLinked to original sources

bioRxiv2025

Navigating uncertainty: reward location variability induces reorganization of hippocampal spatial representations

Navigating uncertainty is crucial for survival, with the location and availability of reward varying in different and unsignalled ways. Hippocampal place cell populations over-represent salient locations in an animals environment, including those associated with rewards; however, how the spatial uncertainties impact the cognitive map is unclear. We report a virtual spatial navigation task designed to test the impact of different levels and types of uncertainty about reward on place cell populations. When the reward location changed on a trial-by-trial basis, inducing expected uncertainty, a greater proportion of place cells followed along, and the reward and the track end became anchors of a warped spatial metric. When the reward location then unexpectedly moved, the fraction of reward place cells that followed was greater when starting from a state of expected, compared to low, uncertainty. Overall, we show that different forms of potentially interacting uncertainty generate remapping in parallel, task-relevant, reference frames.

neuroscience↗

bioRxiv2024

Analysis of Hippocampal Synaptic Function in a Rodent Model of Early Life Stress

BackgroundEarly life stress (ELS) is an important risk factor in the aetiology of depression. Developmental glucocorticoid exposure impacts multiple brain regions with the hippocampus being particularly vulnerable. Hippocampal mediated behaviours are dependent upon the ability of neurones to undergo long-term potentiation (LTP), an N-methyl-D-aspartate receptor (NMDAR) mediated process. In this study we investigated the effect of ELS upon hippocampal NMDAR function. MethodsHooded Long-Evans rat pups (n=82) were either undisturbed or maternally separated for 180 minutes per day (MS180) between post-natal day (PND) 1 and PND14. Model validation consisted of sucrose preference (n=18) and novelty supressed feeding (NSFT, n=34) tests alongside assessment of corticosterone (CORT) and paraventricular nucleus (PVN) cFos reactivity to stress and hippocampal neurogenesis (all n=18). AMPA/NMDA ratios (n=19), miniEPSC currents (n=19) and LTP (n=15) were assessed in whole-cell patch clamp experiments in CA1 pyramidal neurones. ResultsMS180 animals showed increased feeding latency in the NSFT alongside increased overall CORT in the restraint stress experiment and increased PVN cFos expression in males but no changes in neurogenesis or sucrose preference. MS180 was associated with a lower AMPA/NMDA ratio with no change in miniEPSC amplitude or area. There was no difference in short- or long-term potentiation between MS180 and control animals nor were there any changes during the induction protocol. ConclusionsThe MS180 model showed a behavioural phenotype consistent with previous work. MS180 animals showed increased NMDAR function with preliminary evidence suggesting that this was not concurrent with an increase in LTP.

neuroscience↗

bioRxiv2019

A Bayesian predictive approach for dealing with pseudoreplication

Pseudoreplication occurs when the number of measured values or data points exceeds the number of genuine replicates, and when the statistical analysis treats all data points as independent and thus fully contributing to the result. By artificially inflating the sample size, pseudoreplication contributes to irreproducibility, and it is a pervasive problem in biological research. In some fields, more than half of published experiments have pseudoreplication - making it one of the biggest threats to inferential validity. Researchers may be reluctant to use appropriate statistical methods if their hypothesis is about the pseudoreplicates and not the genuine replicates; for example, when an intervention is applied to pregnant female rodents (genuine replicates) but the hypothesis is about the effect on the multiple offspring (pseudoreplicates). We propose using a Bayesian predictive approach, which enables researchers to make valid inferences about biological entities of interest, even if they are pseudoreplicates, and show the benefits of this approach using two in vivo data sets.

neuroscience↗