Monday January 20, 2020

Contagious yawning: Why we yawn when someone else does? Read to find out

The findings of Research on why is yawning so so contagious?

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Why we yawn when someone else does?
Why we yawn when someone else does? Pixabay
  • Contagious yawning is triggered involuntarily when we observe another person yawn, it is a common form of Echophenomena
  • The  Research findings showed that our urge to yawn is increased if we are instructed to resist yawning
  • Echophenomena isn’t just a human trait, it is found in chimpanzees and dogs too

New York, USA, September 3, 2017:  Ever wondered why even if we are not tired, we yawn if someone else does? Why is yawning so contagious?

It is because the human propensity for contagious yawning is triggered automatically by primitive reflexes in a brain area responsible for motor function, a research suggests.

Contagious yawning is triggered involuntarily when we observe another person yawn – it is a common form of Echophenomena -the automatic imitation of another’s words (echolalia) or actions (echopraxia).

The  Research findings showed that our urge to yawn is increased if we are instructed to resist yawning. And no matter how hard we try to stifle a yawn, it might change how we yawn but it won’t alter our propensity to yawn.

Also Read: Ever wondered why you Itch when another person scratches in front of you?

“This research has shown that the ‘urge’  is increased by trying to stop yourself. Using electrical stimulation we were able to increase excitability and in doing so increase the propensity for contagious yawning,” said Georgina Jackson, a Professor at the University of Nottingham.

“The findings may be important in understanding the association between motor excitability and the occurrence of Echophenomena in a wide range of conditions linked to increased cortical excitability and/or decreased physiological inhibition such as epilepsy, dementia, autism, and Tourette syndrome,” added Stephen Jackson, a Professor at the University.

For the study, published in the journal Current Biology, the team used transcranial magnetic stimulation (TMS) to analyze volunteers who viewed video clips showing someone else yawning and were instructed to either resist yawning or to allow themselves to yawn.

“If we can understand how alterations in cortical excitability give rise to neural disorders we can potentially reverse them. We are looking for potential non-drug, personalized treatments, using TMS that might be effective in modulating imbalances in the brain networks,” Jackson said.

Echophenomena isn’t just a human trait, it is found in chimpanzees and dogs too. (IANS)

Next Story

Researchers Develop AI Tool To Detect Mental Health Issues

Tracking changes in clinical states is important to detect if there is a change that shows whether the condition has improved or worsened that would warrant the need for changing treatment

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The USC Signal Analysis and Interpretation Lab (SAIL), which has long applied artificial intelligence (AI) and machine learning to identify and classify video, audio and physiological data, partnered with researchers to analyse voice data from patients being treated for serious mental illnesses. Pixabay

Researchers, including one of Indian-origin, have developed an artificial intelligence (AI) tool that can accurately detect changes in clinical states in voice data of patients with bipolar, schizophrenia and depressive disorders as accurately as attending doctors.

“Machine learning allowed us to illuminate the various clinically-meaningful dimensions of language use and vocal patterns of the patients over time and personalised at each individual level,” said Indian-origin researcher and study senior author Shri Narayanan from University of Southern California (USC) in the US.

The USC Signal Analysis and Interpretation Lab (SAIL), which has long applied artificial intelligence and machine learning to identify and classify video, audio and physiological data, partnered with researchers to analyse voice data from patients being treated for serious mental illnesses.

For the results, the researchers used the ‘MyCoachConnect’ interactive voice and mobile tool, created and hosted on the Chorus platform to provide voice diaries related to their mental health states.

SAIL team then collaborated with researchers to apply artificial intelligence to listen to hundreds of voicemails using custom software to detect changes in patients’ clinical states. According to the study, the AI was able to match clinicians’ ratings of their patients.

Tracking changes in clinical states is important to detect if there is a change that shows whether the condition has improved or worsened that would warrant the need for changing treatment, the researchers said.

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Researchers, including one of Indian-origin, have developed an artificial intelligence (AI) tool that can accurately detect changes in clinical states in voice data of patients with bipolar, schizophrenia and depressive disorders as accurately as attending doctors. Pixabay

This project builds on SAIL’s body of work in behavioural machine intelligence to analyse psychotherapy sessions to detect empathy of addiction counselors-in-training in order to improve their chances of better outcomes, in addition to the Lab’s work analysing language for cognitive diagnoses and legal processes.

ALSO READ: Here’s How Fitbit Smartwatch May Help You Predict Flu in Real-Time

“Our approach builds on that fundamental technique to hear what people are saying about using the modern AI. We hope this will help us better understand how our patients are doing and transform mental health care to be more personalised and proactive to what an individual needs,” said study lead author Armen Arevian. (IANS)