Category Archives: Brain

Phone camera + machine learning detect concussion

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Shwetak Patel and UW colleagues have developed PupilScreen, an app that uses a phone’s camera to detect concussion from the pupil.

The phone’s video camera and flash check the eye for its pupillary light reflex, measures size changes associated with concussion.  Machine learning algorithms confirm the diagnosis.

Hospitals typically use a pen light to check for concussions, which is much less accurate than a pupillometer.

PupilScreen was tested on  48 healthy and tbi patients. The team reported that it “diagnosed brain injuries with almost perfect accuracy using the app’s output alone.”

Click to view University of Washington video


Stanford professor Jamshid Ghajar will discuss the rapid concussion detection and treatment platform SyncThink at ApplySci’s Wearable Tech + Digital Health + Neurotech Boston conference, on September 19th at the MIT Media Lab.


Join ApplySci at Wearable Tech + Digital Health + NeuroTech Boston on September 19, 2017 at the MIT Media Lab – featuring  Joi Ito – Ed Boyden – Roz Picard – George Church – Nathan Intrator –  Tom Insel – John Rogers – Jamshid Ghajar – Riccardo Sabatini – Phillip Alvelda – Michael Weintraub – Nancy Brown – Steve Kraus – Bill Geary – Mary Lou Jepsen


ANNOUNCING WEARABLE TECH + DIGITAL HEALTH + NEUROTECH SILICON VALLEY – FEBRUARY 26 -27, 2018 @ STANFORD UNIVERSITY –  FEATURING:  ZHENAN BAO – JUSTIN SANCHEZ – BRYAN JOHNSON – NATHAN INTRATOR – VINOD KHOSLA

Detecting dementia with automated speech analysis

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WinterLight Labs is developing speech analyzing algorithms to detect and monitor dementia and aphasia.  A one minute speech sample is used to determine the lexical diversity, syntactic complexity, semantic content, and articulation associated with these conditions.

Clinicians currently conduct similar tests by interviewing patients and writing their impressions on paper.

The company believes that their automated system could inform clinical trials, medical care, and speech training.

If the platform could be used with mobile phones, the potential for widespread early detection is obvious.  Unfortunately, detection, even early detection, does not at this point translate into a cure.  ApplySci looks forward to the day when advanced neurodegenerative disease monitoring will be used to track progress toward healthy brain functioning.


Join ApplySci at Wearable Tech + Digital Health + NeuroTech Boston on September 19, 2017 at the MIT Media Lab – featuring  Joi Ito – Ed Boyden – Roz Picard – George Church – Nathan Intrator –  Tom Insel – John Rogers – Jamshid Ghajar – Riccardo Sabatini – Phillip Alvelda – Michael Weintraub – Nancy Brown – Steve Kraus – Bill Geary – Mary Lou Jepsen


ANNOUNCING WEARABLE TECH + DIGITAL HEALTH + NEUROTECH SILICON VALLEY – FEBRUARY 26 -27, 2018 @ STANFORD UNIVERSITY –  FEATURING:  ZHENAN BAO – JUSTIN SANCHEZ – BRYAN JOHNSON – NATHAN INTRATOR – VINOD KHOSLA

Robotic, in-vivo neuron recording

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Ed Boyden and MIT colleagues have developed a robotic system capable of monitoring specific neurons.

An algorithm based on multiple image processing methods analyzes microscope images and guides a robotic arm to within 25 microns of a target cell. The system then relies on both imagery and impedance, which more accurately detects contact between the pipette and the target cell than either signal alone. Two-photon microscopy sends infrared light into the brain, lighting up cells that have been engineered to express a fluorescent protein. This enables the targeting of and recording from interneurons and excitatory neurons. With an approximate 20 per cent success rate, the robotic system performs similarly to scientists who perform the process manually.

Studying how single neurons  interact with other cells for cognition, sensory perception, and other brain functions could tell us how neural circuits are affected by disorders such as autism, Alzheimer’s and schizophrenia.

See autopatcher.org for additional details.

Professor Boyden will discuss his research at Wearable Tech + Digital Health + Neurotech Boston, on September 19th at the MIT Media Lab.


Join ApplySci at Wearable Tech + Digital Health + NeuroTech Boston on September 19, 2017 at the MIT Media Lab – featuring  Joi Ito – Ed Boyden – Roz Picard – George Church – Nathan Intrator –  Tom Insel – John Rogers – Jamshid Ghajar – Phillip Alvelda – Michael Weintraub – Nancy Brown – Steve Kraus – Bill Geary – Mary Lou Jepsen

Registration rates increase Friday, September 1st.


ANNOUNCING WEARABLE TECH + DIGITAL HEALTH + NEUROTECH SILICON VALLEY – FEBRUARY 26 -27, 2018 @ STANFORD UNIVERSITY –  FEATURING:  ZHENAN BAO – JUSTIN SANCHEZ – BRYAN JOHNSON – NATHAN INTRATOR – VINOD KHOSLA

Google incorporates depression screening in search

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Google has introduced a new depression screening feature.  When the word “depression” is used in search, mobile users are offered a PHQ-9 questionnaire, which recognizes symptoms. A “Knowledge Panel” containing information and potential treatments appears on top of the page.

The goal is self awareness, and encouragement to seek help when needed.

Another company dedicated to improving brain health through mobile technology is Mindstrong Health.  The startup is developing clinically validated, phone-based mental illness screening, monitoring and treatment methods.  Co-founder Tom Insel will discuss their work at ApplySci’s upcoming Wearable Tech + Digital Health + Neurotech conference, on September 19th at the MIT Media Lab.


Join ApplySci at Wearable Tech + Digital Health + NeuroTech Boston on September 19, 2017 at the MIT Media Lab – featuring  Joi Ito – Ed Boyden – Roz Picard – George Church – Nathan Intrator –  Tom Insel – John Rogers – Jamshid Ghajar – Phillip Alvelda – Michael Weintraub – Nancy Brown – Steve Kraus – Bill Geary – Mary Lou Jepsen

Registration rates increase Friday, August 25th.


ANNOUNCING WEARABLE TECH + DIGITAL HEALTH + NEUROTECH SILICON VALLEY – FEBRUARY 26 -27, 2018 @ STANFORD UNIVERSITY –  FEATURING:  ZHENAN BAO – JUSTIN SANCHEZ – BRYAN JOHNSON – NATHAN INTRATOR – VINOD KHOSLA

Retina scan + curcumin for early Alzheimer’s detection

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In a recent study, Maya Koronyo-Hamaoui and Keith Black at Cedars-Sinai  used a retina scan to detect amyloid-beta deposits, a predictor of Alzheimer’s disease, up to 20 years before symptoms.

16 Alzheimer’s patients drank a curcumin solution, which caused amyloid plaque in the retina to “light up” and be detected. Another key finding was the discovery of amyloid plaques in peripheral regions of the retina, which correlated with plaque amount in specific areas of the brain.

Keith Black presented this research at ApplySci’s April, 2016 Wearable Tech + Digital Health + Neurotech conference in San Francisco.  His dedication to finding non-invasive, more humane tests and treatments for brain diseases was apparent throughout his talk.  May his vision of  early detection, leading to early medical and lifestyle changes to impact the course of the disease, be widely adopted.


Join ApplySci at Wearable Tech + Digital Health + NeuroTech Boston on September 19, 2017 at the MIT Media Lab – featuring  Joi Ito – Ed Boyden – Roz Picard – George Church – Nathan Intrator –  Tom Insel – John Rogers – Jamshid Ghajar – Phillip Alvelda – Michael Weintraub – Nancy Brown – Steve Kraus – Bill Geary – Mary Lou Jepsen

Registration rates increase Friday, August 25th.


ANNOUNCING WEARABLE TECH + DIGITAL HEALTH + NEUROTECH SILICON VALLEY – FEBRUARY 26 -27, 2018 @ STANFORD UNIVERSITY

Machine learning for early Alzheimer’s diagnosis

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Anant Madabhushi and Case Western colleagues have used machine learning to diagnose Alzheimer’s disease via imaging data in a small study.  The goal is early intervention, which could potentially extend independence.

149 patients were analyzed using a Cascaded Multi-view Canonical Correlation (CaMCCo) algorithm, which integrates MRI scans, features of the hippocampus, glucose metabolism rates in the brain, proteomics, genomics, and MCI.

Parameters that distinguish between healthy and unhealthy subjects were selected first. The algorithm then selected, from the unhealthy variables, those that best distinguish who has mild cognitive impairment and who has Alzheimer’s disease.

This is an admirable attempt to diagnose a disease which currently has no cure.  ApplySci hopes that we will soon be able to combine early detection with a truly effective treatment.  Millions around the world are waiting.


Join ApplySci at Wearable Tech + Digital Health + NeuroTech Boston on September 19, 2017 at the MIT Media Lab – featuring  Joi Ito – Ed Boyden – Roz Picard – George Church – Nathan Intrator –  Tom Insel – John Rogers – Jamshid Ghajar – Phillip Alvelda – Michael Weintraub – Nancy Brown – Steve Kraus – Bill Geary – Mary Lou Jepsen

Registration rates increase Friday, August 18th.


ANNOUNCING WEARABLE TECH + DIGITAL HEALTH + NEUROTECH SILICON VALLEY – FEBRUARY 26 -27, 2018 @ STANFORD UNIVERSITY

Alzheimer’s diagnosis disputed in up to 50% of PET study subjects

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James Hendrix and Alzheimer’s Association colleagues are conducting a study to see how PET scans could change the nature of Alzheimer’s diagnosis and treatment.

4,000 of 18,000 subjects have been tested to date, with a stunning result showing that a significant portion of people with mild cognitive impairment or dementia who are taking medication for Alzheimer’s may not actually have the disease.

The PET scan determines if  MCI or dementia  patient brains contain the amyloid plaques that are one of the two hallmarks of Alzheimer’s disease. Among the 4,000 people tested, 54.3 percent of MCI patients and 70.5 percent of dementia patients had the plaques. A positive test for amyloid does not mean someone has Alzheimer’s disease, though their presence is thought to precede the disease and increase the risk of progression. A negative test means a person does not have the disease.

After seeing the PET imaging results, doctors changed their care plans for two-thirds of the patients in the study. According to Hendrix, “We thought we would be able to see about a 30 percent change, but we’re getting a 66 percent change, so it’s huge. We see high percentages of people who are on a drug and didn’t need to be on those drugs.”


Join ApplySci at Wearable Tech + Digital Health + NeuroTech Boston on September 19, 2017 at the MIT Media Lab – featuring  Joi Ito – Ed Boyden – Roz Picard – George Church – Nathan Intrator –  Tom Insel – John Rogers – Jamshid Ghajar – Phillip Alvelda – Michael Weintraub – Nancy Brown – Steve Kraus – Bill Geary – Mary Lou Jepsen – Daniela Rus

Registration rates increase Friday, July 28th.


ANNOUNCING WEARABLE TECH + DIGITAL HEALTH + NEUROTECH SILICON VALLEY – FEBRUARY 26 -27, 2018 @ STANFORD UNIVERSITY

 

AI used to study brain blood flow ties to Schizophrenia

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Mina Gheiratmand,  Serdar Dursun, and University of Alberta colleagues used IBM AI tools to try to  identify schizophrenic traits based on a person’s brain blood flow.

95 participant  fMRI images of schizophrenia-diagnosed and healthy patient brains were analyzed.  The researchers claimed to accurately diagnose patients, based on blood flow, 74% of the time. They also claimed to be able to measure the severity of symptoms.

A much larger sample size will be required to determine the validity of this approach to understanding a disease that so little is known about.  ApplySci applauds this perhaps promising attempt.

Direct brain path for sight, sound via implanted microscope

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Rice University’s Jacob Robinson, with Yale and Columbia colleagues, are developing FlatScope — a flat, brain implanted microscope that monitors and triggers neurons which are modified to be fluorescent when active.

While capturing greater detail than current brain probes, the microscope also goes through deep levels that illustrate  sensory input processing — which they hope to be able to control.

Aiming to produce a super high-resolution neural interface, FlatScope is a part of  DARPA’s NESD program, founded by Phillip Alvelda, and now led by Brad Ringeisen.


Phillip Alvelda will be a featured speaker at ApplySci’s Wearable Tech + Digital Health + NeuroTech Boston conference on September 19, 2017 at the MIT Media Lab.  Other speakers include:  Joi Ito – Ed Boyden – Roz Picard – George Church – Nathan Intrator –  Tom Insel – John Rogers – Jamshid Ghajar  – Michael Weintraub – Nancy Brown – Steve Kraus – Bill Geary – Mary Lou Jepsen – Daniela Rus

Registration rates increase Friday, July 21st

EEG detects infant pain

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Caroline Hartley and Oxford colleagues studied 72 infants during painful medical procedures.  Using EEG, they found a signature change in brain activity about a half-second after a painful stimulus. They seek to understand its use in monitoring and managing infant pain, as well as  the use of EEG in adult pain treatment.

EEG is more precise than current heart rate, oxygen saturation level, and facial expression pain assessment, which are affected by other stressful, non-painful events.

In one experiment, 11 out of 12 infants had a decreased pain-related EEG signal after doctors applied a topical anesthetic to their feet.  A new study uses EEG to test the efficacy of morphine in infants, whose skin and intestines absorb drugs differently than adults.

EEG is being miniaturized by companies such as Neurosteer, making it an increasingly viable option for continuous pain, attention, and consciousness monitoring and treatment optimization.


Join ApplySci at Wearable Tech + Digital Health + NeuroTech Boston on September 19, 2017 at the MIT Media Lab – featuring  Joi Ito – Ed Boyden – Roz Picard – George Church – Nathan Intrator –  Tom Insel – John Rogers – Jamshid Ghajar – Phillip Alvelda – Michael Weintraub – Nancy Brown – Steve Kraus – Bill Geary