Updated August 4, 2020
Estimation Statistics
eNeuro encourages authors to add estimation statistics to their analyses when appropriate. Below, we feature papers that did so, along with an author's response to the query: What value was added to your analysis or perspective through the addition of estimation statistics? For more information read Estimation for Better Inference in Neuroscience.
JNK Signaling Regulates Cellular Mechanics of Cortical Interneuron Migration
"Converting to estimation statistics was relatively simple once we familiarized ourselves with the process. There was remarkable consistency between the p values that we obtained from standard T tests and estimation statistical analyses. Graphical representation of the data with Gardner-Altman plots allowed us to visualize individual data points, mean differences, and confidence intervals between our comparisons, which was far superior to the use of histograms. Altogether, converting to estimation stats gave us greater confidence in our data." - Eric Tucker
Research Spotlight
Hierarchical Compression Reveals Sub-Second to Day-Long Structure in Larval Zebrafish Behavior
Behaviour is dynamic and evolves over multiple timescales from sub-second reflexes to 24-hour sleep/wake cycles. Describing these dynamics is a critical task in neuroscience, as they provide insight into how the brain controls behaviour. Ghosh & Rihel develop computational methods to capture these dynamics and leverage their approach to uncover both fast and slow patterns in larval zebrafish behaviour.
Circuit-Specific Dendritic Development in the Piriform Cortex
During development, brain circuits need to effectively wire sensory circuits from the periphery with associative circuits representing processed higher order information. On the dendritic tree of neurons in the primary olfactory or piriform cortex, peripheral sensory circuits and internal associative circuits are spatially segregated. Moreno-Velasquez et al. utilise this clear wiring pattern to characterise mechanisms of dendritic growth underlying effective sensory and associative wiring.
Huntington’s disease (HD) is a neurodegenerative disease that primarily affects the striatum, resulting in debilitating motor symptoms. Glutamate toxicity has been heavily implicated in striatal cell death in the HD brain. However, HD is becoming increasingly recognized as a brain-wide disease, yet we have a relatively poor understanding of how the HD-causing mutation impacts cellular function outside the striatum. Wilkie et al. demonstrate that at an early stage of disease progression in a mouse model of HD, excessive amounts of glutamate accumulate in the hippocampus during neural activity. Ceftraixone, a drug previously shown to reduce striatal glutamate toxicity and provide benefit to motor function in HD mice, was without effect on glutamate levels in the hippocampus and negatively impacted hippocampal synaptic plasticity. These data highlight the complexity of HD and the importance of understanding HD neurobiology from a brain-wide perspective.
Also of Interest
Scientific Hypothesis-Testing Strengthens Neuroscience Research
The statistical p value is commonly used to express the significance of research findings. But a single p value cannot meaningfully represent a study involving multiple tests of a given hypothesis. I report a survey that confirms that a large fraction of neuroscience work published in The Journal of Neuroscience does involve multiple-testing procedures. As readers, we normally evaluate the strength of a hypothesis-testing study by “combining,” in an ill-defined intellectual way, the outcomes of multiple experiments that test it. We assume that conclusions that are supported by the combination of multiple outcomes are likely to be stronger and more reliable than those that rest on single outcomes. Yet there is no standard, objective process for taking multiple outcomes into account when evaluating such studies. Here, I propose to adapt methods normally used in meta-analysis across studies to help rationalize this process. This approach offers many direct and indirect benefits for neuroscientists’ thinking habits and communication practices.
Multi-Dimensional Tuning in Motor Cortical Neurons During Active Behavior
Motor cortex across taxa receives highly integrated, multi-modal information and has been implicated in both execution and acquisition of complex motor skills, yet studies of motor cortex typically employ restricted behavioral paradigms that target select movement parameters, preventing wider assessment of the diverse sensorimotor factors that can affect motor cortical activity. Recording in AId of freely behaving juvenile songbirds that are actively engaged in sensorimotor learning offers unique advantages for elucidating the functional role of motor cortical neurons. The results demonstrate that a diverse array of factors modulate motor cortical activity and lay important groundwork for future investigations of how multi-modal information is integrated in motor cortical regions to contribute to learning and execution of complex motor skills.
The causes of Autism Spectrum Disorders remain elusive. In this study, we investigate the combined effect of mutations in two genes associated with ASD: Nlgn3 and Cyfip1, and the effect of the social environment, on phenotypes relevant for ASD. We show that when both mutations are present the behaviour can be restored, emphasising the importance of considering gene interactions. We also show sex differences in behaviour, suggesting that female subjects should be included in the studies of ASD. We show that wild type animals can exhibit phenotypes associated with ASD as a result of being housed with their mutant littermates, highlighting the necessity to re-evaluate the use of wild type animals as controls to define phenotypic traits of mouse models.
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