Computational Primitives for Cost-Benefit Decision-Making DOI

Lara I. Rakocevic,

Luis D. Davila,

Cory N. Heaton

et al.

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

Published: Dec. 15, 2024

Summary Cost-benefit decision-making is a critical process performed by all organisms, including humans. Various factors, risk 1,2 , uncertainty 3 age 4 sex 5 and neuropsychiatric disorders 6 can alter decision-making. To explore cost-benefit in humans, we developed comprehensive task analysis framework that presents participants with series of approach-avoid trade-offs across variety contexts. With this system, found decisions humans are made using set computational strategies may be used for integrating costs rewards, which term ‘decision-making primitives’. We further show these primitives rodents performing similar 7 . find utilization both shifts based on factors like hunger sex, individuals use differently. additionally demonstrate naturally-inspired neural network architecture generates output overlaps human rodent performance over non-constrained network. This novel conceptual framework, isolating discrete primitives’, has potential to help us identify how different brain regions give rise behavior, as well facilitate better diagnosis development artificial intelligence systems

Language: Английский

Simple Behavioral Analysis (SimBA) as a platform for explainable machine learning in behavioral neuroscience DOI
Nastacia L. Goodwin,

Jia Jie Choong,

Sophia Hwang

et al.

Nature Neuroscience, Journal Year: 2024, Volume and Issue: 27(7), P. 1411 - 1424

Published: May 22, 2024

Language: Английский

Citations

68
Open-source tools for behavioral video analysis: Setup, methods, and best practices DOI Creative Commons
Kevin Luxem, Jennifer J. Sun,

Sean P Bradley

et al.

eLife, Journal Year: 2023, Volume and Issue: 12

Published: March 22, 2023

Recently developed methods for video analysis, especially models pose estimation and behavior classification, are transforming behavioral quantification to be more precise, scalable, reproducible in fields such as neuroscience ethology. These tools overcome long-standing limitations of manual scoring frames traditional ‘center mass’ tracking algorithms enable analysis at scale. The expansion open-source acquisition has led new experimental approaches understand behavior. Here, we review currently available discuss how set up these labs recording. We also best practices developing using methods, including community-wide standards critical needs the open sharing datasets code, widespread comparisons better documentation users. encourage broader adoption continued development tools, which have tremendous potential accelerating scientific progress understanding brain

Language: Английский

Citations

51
Mimicking opioid analgesia in cortical pain circuits DOI Creative Commons
Justin G. James, Nora M. McCall,

Alex Hsu

et al.

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

Published: April 29, 2024

The anterior cingulate cortex plays a pivotal role in the cognitive and affective aspects of pain perception. Both endogenous exogenous opioid signaling within mitigate cortical nociception, reducing unpleasantness. However, specific functional molecular identities cells mediating analgesia remain elusive. Given complexity as sensory emotional experience, richness ethological pain-related behaviors, we developed standardized, deep-learning platform for deconstructing behavior dynamics associated with component mice-LUPE (Light aUtomated Pain Evaluator). LUPE removes human bias quantification accelerated analysis from weeks to hours, which leveraged discover that morphine altered attentional motivational behaviors akin humans. Through activity-dependent genetics single-nuclei RNA sequencing, identified ensembles nociceptive neuron-types expressing mu-opioid receptors. Tuning receptor expression these bidirectionally modulated analgesia. Moreover, employed synthetic promoter-driven approach cell-type optical chemical genetic viral therapies mimic morphine's pain-relieving effects cingulate, without reinforcement. This offers novel strategy precision management by targeting key circuit on-demand, non-addictive, effective

Language: Английский

Citations

4
Vestibular circuit stimulation for retuning locomotor dynamics in Parkinson's disease DOI Creative Commons
Johannes Hartig, Maximilian Friedrich, Jérémy Signoret-Genest

et al.

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 10, 2025

Abstract Postural and locomotor dysfunction represent axial symptoms of Parkinson’s disease (PD), remaining poorly treated by medication deep brain stimulation. Non-invasive neuromodulation the vestibular system, centered on nucleus complex (VNC), offers a novel therapeutic avenue. However, underlying circuits remain ill-explored. In this study, we found that VNC in mice feeds extensive Vglut2-defined projections into striato-thalamo-subthalamic caudal medulla motor hubs, but not mesencephalic region. Optoactivation excitatory neurons below threshold for promoted activity these basal ganglia-brainstem axis targets. Unbiased analysis pose dynamics revealed global enhancement behavioural transitions locomotion, confirmed regular kinematic analyses. Therapeutically, it enabled resynchronization naturalistic gait patterns improved performance, capacity, parkinsonian mice. Our data identify circuit processes retuning context PD.

Language: Английский

Citations

0
vmTracking enables highly accurate multi-animal pose tracking in crowded environments DOI Creative Commons
Hirotsugu Azechi, Susumu Takahashi

PLoS Biology, Journal Year: 2025, Volume and Issue: 23(2), P. e3003002 - e3003002

Published: Feb. 10, 2025

In multi-animal tracking, addressing occlusion and crowding is crucial for accurate behavioral analysis. However, in situations where generate complex interactions, achieving pose tracking remains challenging. Therefore, we introduced virtual marker (vmTracking), which uses markers individual identification. Virtual are labels derived from conventional markerless tools, such as DeepLabCut (maDLC) Social LEAP Estimate Animal Poses (SLEAP). Unlike physical markers, exist only within the video attribute features to individuals, enabling consistent identification throughout entire while keeping animals reality. Using these cues, annotations were applied videos, was conducted with single-animal (saDLC) SLEAP’s method. vmTracking minimized manual corrections annotation frames needed training, efficiently tackling crowding. Experiments multiple mice, fish, human dancers confirmed vmTracking’s variability applicability. These findings could enhance precision reliability of methods used analysis naturalistic social behaviors animals, providing a simpler yet more effective solution.

Language: Английский

Citations

0
Temporal action localisation in video data containing rabbit behavioural patterns DOI Creative Commons

Semyon E. Ilin,

Julia Borodacheva,

Ildar Shamsiev

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Feb. 17, 2025

Language: Английский

Citations

0
The utility of animal models to inform the next generation of human space exploration DOI Creative Commons

Isla Duporge,

Talmo Pereira, Santiago Castiello

et al.

npj Microgravity, Journal Year: 2025, Volume and Issue: 11(1)

Published: Feb. 22, 2025

Language: Английский

Citations

0
Computer vision for primate behavior analysis in the wild DOI
Richard Vogg, Timo Lüddecke, Jonathan Henrich

et al.

Nature Methods, Journal Year: 2025, Volume and Issue: unknown

Published: April 10, 2025

Language: Английский

Citations

0
Aligning brain and behavior DOI
Henry H. Yin

Current Opinion in Behavioral Sciences, Journal Year: 2025, Volume and Issue: 62, P. 101487 - 101487

Published: March 5, 2025

Language: Английский

Citations

0
The MacqD deep-learning-based model for automatic detection of socially housed laboratory macaques DOI Creative Commons

Genevieve Jiawei Moat,

Maxime Gaudet-Trafit,

J. Lawrence Paul

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: April 7, 2025

Abstract Despite advancements in video-based behaviour analysis and detection models for various species, existing methods are suboptimal to detect macaques complex laboratory environments. To address this gap, we present MacqD, a modified Mask R-CNN model incorporating SWIN transformer backbone enhanced attention-based feature extraction. MacqD robustly detects their home-cage under challenging scenarios, including occlusions, glass reflections, overexposure light. evaluate compare its performance against pre-existing macaque models, collected analysed video frames from 20 caged rhesus at Newcastle University, UK. Our results demonstrate MacqD’s superiority, achieving median F1-score of 99% with single the focal cage (surpassing next-best by 21%) 90% two macaques. Generalisation tests on different set same animal facility yielded F1-scores 95% 15%) 81% alternative approach 39% ). Finally, was applied videos paired another resulted 90%, reflecting strong generalisation capacity. This study highlights effectiveness accurately detecting across diverse settings.

Language: Английский

Citations

0