Editorial perspective: Leaving the baby in the bathwater in neurodevelopmental research

Journal of Child Psychology and Psychiatry, Journal Year: 2023, Volume and Issue: 64(8), P. 1256 - 1259

Published: Jan. 4, 2023

Neurodevelopmental conditions are characterised by differences in the way children interact with people and environments around them. Despite extensive investigation, attempts to uncover brain mechanisms that underpin neurodevelopmental have yet yield any translatable insights. We contend one key reason is psychologists cognitive neuroscientists study function taking away from their environment, into a controlled lab setting. Here, we discuss recent research has aimed take different approach, moving experimental control through isolation stimulus manipulation, towards approaches embrace measurement targeted interrogation of naturalistic, user‐defined complex, multivariate datasets. review three worked examples (of stress processing, early activity level ADHD social development autism) illustrate how these new might lead conceptual insights neurodevelopment.

Language: Английский

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ReptiLearn: An automated home cage system for behavioral experiments in reptiles without human intervention

PLoS Biology, Journal Year: 2024, Volume and Issue: 22(2), P. e3002411 - e3002411

Published: Feb. 29, 2024

Understanding behavior and its evolutionary underpinnings is crucial for unraveling the complexities of brain function. Traditional approaches strive to reduce behavioral complexity by designing short-term, highly constrained tasks with dichotomous choices in which animals respond defined external perturbation. In contrast, natural behaviors evolve over multiple time scales during actions are selected through bidirectional interactions environment without human intervention. Recent technological advancements have opened up new possibilities experimental designs that more closely mirror replacing stringent control accurate multidimensional analysis. However, these been tailored fit only a small number species. This specificity limits opportunities offered species diversity. Further, it hampers comparative analyses essential extracting overarching principles examining from an perspective. To address this limitation, we developed ReptiLearn—a versatile, low-cost, Python-based solution, optimized conducting automated long-term experiments home cage reptiles, addition, system offers unique features such as precise temperature measurement control, live prey reward dispensers, engagement touch screens, remote user-friendly web interface. Finally, ReptiLearn incorporates low-latency closed-loop feedback allowing between their environments. Thus, provides comprehensive solution researchers studying ectotherms beyond, bridging gap laboratory settings nonconventional model systems. We demonstrate capabilities automatically training lizard Pogona vitticeps on complex spatial learning task requiring association learning, displaced reversal learning.

Language: Английский

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Large-scale recording of neuronal activity in freely-moving mice at cellular resolution

Nature Communications, Journal Year: 2023, Volume and Issue: 14(1)

Published: Oct. 12, 2023

Abstract Current methods for recording large-scale neuronal activity from behaving mice at single-cell resolution require either fixing the mouse head under a microscope or attachment of device to animal’s skull. Both these options significantly affect animal behavior and hence also recorded brain patterns. Here, we introduce different method acquire snapshots cortical maps freely-moving using calcium sensor called CaMPARI. CaMPARI has unique property irreversibly changing its color green red inside active neurons when illuminated with 400 nm light. We capitalize on this demonstrate cortex-wide without any fixation, tethering, miniaturized mouse’s head. Multiple regions were while was performing battery behavioral cognitive tests. identified task-dependent patterns across motor somatosensory cortices, significant differences sub-regions cortex correlations several task parameters. This CaMPARI-based expands capabilities minimally-restrictive experimental conditions provides volumetric data that are currently not accessible otherwise.

Language: Английский

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Representing the dynamics of natural marmoset vocal behaviors in frontal cortex

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: March 17, 2024

Here we tested the respective contributions of primate premotor and prefrontal cortex to support vocal behavior. We applied a model-based GLM analysis that better accounts for inherent variance in natural, continuous behaviors characterize activity neurons throughout frontal as freely-moving marmosets engaged conversational exchanges. While analyses revealed functional clusters neural related different processes involved behavior, these did not map subfields or cortex, has been observed more conventional task-based paradigms. Our results suggest distributed organization myriad mechanisms underlying natural social interactions implications our concepts role plays governing ethological primates.

Language: Английский

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DomeVR: Immersive virtual reality for primates and rodents

PLoS ONE, Journal Year: 2025, Volume and Issue: 20(1), P. e0308848 - e0308848

Published: Jan. 16, 2025

Immersive virtual reality (VR) environments are a powerful tool to explore cognitive processes ranging from memory and navigation visual processing decision making-and do so in naturalistic yet controlled setting. As such, they have been employed across different species, by diverse range of research groups. Unfortunately, designing implementing behavioral tasks such often proves complicated. To tackle this challenge, we created DomeVR, an immersive VR environment built using Unreal Engine 4 (UE4). UE4 is game engine supporting photo-realistic graphics containing scripting language designed for use non-programmers. result, easily drag-and-drop elements. DomeVR aims make these features accessible neuroscience experiments. This includes logging synchronization system solve timing uncertainties inherent UE4; interactive GUI scientists observe subjects during experiments adjust task parameters on the fly, dome projection full immersion non-human subjects. These key modular can be added individually into other projects. Finally, present proof-of-principle data highlighting functionality three species: human, macaque mouse.

Language: Английский

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