Automated video-based heart rate tracking for the anesthetized and behaving monkey

Froesel, Mathilda; Goudard, Quentin; Hauser, Marc D.; Gacoin, Maëva; Hamed, Suliann Ben

doi:10.1038/s41598-020-74954-5

Cited by 17 publications

(15 citation statements)

References 62 publications

(64 reference statements)

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“…As a result, it was not possible to analyse whether gaze is spontaneously affected by the different stimulus categories. It was, however, possible to analyse heart-rate variation using a video-based method developed by our team (Froesel et al, 2020). Figure 5 focuses on heart rate variation in response to the auditory sound categories in the different blocked conditions.…”

Section: Resultsmentioning

confidence: 99%

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Neural correlates of audio-visual integration of socially meaningful information in macaque monkeys

Froesel

Gacoin

Clavagnier

et al. 2021

Preprint

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Social interactions rely on the ability to interpret semantic and emotional information, often from multiple sensory modalities. In human and nonhuman primates, both the auditory and visual modalities are used to generate and interpret communicative signals. In individuals with autism, not only are there deficits in social communication, but in the integration of audio-visual information. At present, we know little about the neural mechanisms that subserve the interpretation of complex social events, including the audio-visual integration that is often required with accompanying communicative signals. Based on heart rate estimates and fMRI in two macaque monkeys (Macaca mulatta), we show that individuals systematically associate affiliative facial expressions or social scenes with corresponding affiliative vocalizations, aggressive facial expressions or social scenes with corresponding aggressive vocalizations and escape visual scenes with scream vocalizations. In contrast, vocalizations that are incompatible with the visual information are fully suppressed, suggesting top-down regulation over the processing of sensory input. The process of binding audio-visual semantic and contextual information relies on a core functional network involving the superior temporal sulcus (STS) and lateral sulcus (LS). Peak activations in both sulci co-localize with face or voice patches that have been previously described. While all of these regions of interest (ROIs) respond to both auditory and visual information, LS ROIs have a preference for auditory and audio-visual congruent stimuli while STS ROIs equally respond to auditory, visual and audio-visual congruent stimuli. To further specify the cortical network involved in the control of this semantic association, we performed a whole brain gPPI functional connectivity analysis on the LS and STS cumulated ROIs. This gPPI analysis highlights a functional network connected to the LS and STS, involving the anterior cingulate cortex (ACC), area 46 in the dorsolateral prefrontal cortex (DLPFC), the orbitofrontal cortex (OFC), the intraparietal sulcus (IPS), the insular cortex and subcortically, the amygdala and the hippocampus. Comparing human and macaque results, we propose that the integration of audio-visual information for congruent, meaningful social events involves homologous neural circuitry, specifically, an emotional network composed of the STS, LS, ACC, OFC, and limbic areas, including the amygdala, and an attentional network including the STS, LS, IPS and DLPFC. As such, these networks are critical to the amodal representation of social meaning, thereby providing an explanation for some of deficits observed in autism.

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Section: Resultsmentioning

confidence: 99%

“…During each run of acquisition, videos of the faces of monkeys S and T were recorded in order to track heart rate variations (HRV) as a function of blocked conditions and blocks (Froesel et al, 2020). We focus on heart rate variations between auditory congruent and incongruent stimuli.…”

Section: Methodsmentioning

confidence: 99%

Neural correlates of audio-visual integration of socially meaningful information in macaque monkeys

Froesel

Gacoin

Clavagnier

et al. 2021

Preprint

Self Cite

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“…Although not feasible for many sites, additional physiological measures such as respiration and heart rate, but also body motion could add useful information in the analyses and for the interpretation of the results. Some automated video-based heart rate tracking are now available and could be used across centers ( Froesel et al, 2020 ).…”

Section: Discussionmentioning

confidence: 99%

“…For some localizer data, heart rate can be an important metadata to track. Automated video-based heart rate tracking methods are now available and could be used across centers ( Froesel et al, 2020 ). As larger cohorts of animals start to participate in experiments across multiple sites, it would be highly beneficial to acquire blood samples for genetic analysis.…”

Section: Figmentioning

confidence: 99%

Common functional localizers to enhance NHP & cross-species neuroscience imaging research

et al. 2021

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Functional localizers are invaluable as they can help define regions of interest, provide cross-study comparisons, and most importantly, allow for the aggregation and meta-analyses of data across studies and laboratories. To achieve these goals within the non-human primate (NHP) imaging community, there is a pressing need for the use of standardized and validated localizers that can be readily implemented across different groups. The goal of this paper is to provide an overview of the value of localizer protocols to imaging research and we describe a number of commonly used or novel localizers within NHPs, and keys to implement them across studies. As has been shown with the aggregation of resting-state imaging data in the original PRIME-DE submissions, we believe that the field is ready to apply the same initiative for task-based functional localizers in NHP imaging. By coming together to collect large datasets across research group, implementing the same functional localizers, and sharing the localizers and data via PRIME-DE, it is now possible to fully test their robustness, selectivity and specificity. To do this, we reviewed a number of common localizers and we created a repository of well-established localizer that are easily accessible and implemented through the PRIME-RE platform.

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“… Balakrishnan et al (2013) take just an RGB video as input and are able to detect heart rate and beat lengths by monitoring the subtle head movements. Heart rate can also be measured through videos using DeepPhys ( Chen and McDuff, 2018 ) and Eulerian video magnification (EVM) combined with wavelet transformation ( Froesel et al, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

Early Prediction of Hemodynamic Shock in Pediatric Intensive Care Units With Deep Learning on Thermal Videos

et al. 2022

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Shock is one of the major killers in intensive care units, and early interventions can potentially reverse it. In this study, we advance a noncontact thermal imaging modality for continuous monitoring of hemodynamic shock working on 1,03,936 frames from 406 videos recorded longitudinally upon 22 pediatric patients. Deep learning was used to preprocess and extract the Center-to-Peripheral Difference (CPD) in temperature values from the videos. This time-series data along with the heart rate was finally analyzed using Long-Short Term Memory models to predict the shock status up to the next 6 h. Our models achieved the best area under the receiver operating characteristic curve of 0.81 ± 0.06 and area under the precision-recall curve of 0.78 ± 0.05 at 5 h, providing sufficient time to stabilize the patient. Our approach, thus, provides a reliable shock prediction using an automated decision pipeline that can provide better care and save lives.

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Automated video-based heart rate tracking for the anesthetized and behaving monkey

Cited by 17 publications

References 62 publications

Neural correlates of audio-visual integration of socially meaningful information in macaque monkeys

Neural correlates of audio-visual integration of socially meaningful information in macaque monkeys

Common functional localizers to enhance NHP & cross-species neuroscience imaging research

Early Prediction of Hemodynamic Shock in Pediatric Intensive Care Units With Deep Learning on Thermal Videos

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