Category Archives: Brain

EEG determines SSRI effectiveness in depression

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UT Southwestern researchers are using EEG to determine whether an SSRI would effectively treat a person’s depression.

Part of the EMBARC project, the study tracked 300 depressed patients who were given an 8 week course of an SSRI or a placebo. EEG recordings were taken before and after the trial. Higher rACC theta activity before treatment corresponded with greater treatment response to the antidepressant.

 EMBARC director Madhukar Trivedi hopes that the EEG test, combined with his previous blood-biomarker guided drug choice work will dramatically improve accuracy in predicting whether common antidepressants will work for a patient.


Join ApplySci at the 9th Wearable Tech + Digital Health + Neurotech Boston conference on September 24, 2018 at the MIT Media Lab.  Speakers include Roz Picard – George Church – Poppy Crum – Nathan Intrator – Roozbeh Ghaffari – John Mattison

Gait sensor could detect Alzheimer’s, identify fall risk

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Newcastle University’s Lynn Rochester has studied the use of wearable sensors to identify walking characteristics as clinical biomarkers for Alzheimer’s Disease.  The same sensors can detect gait changes that require intervention to prevent falls and prolong independence.

According to Rochester, “free-living gait analysis at home is particularly useful as it allows objective observation of an individual’s day-to-day activity. It also has the benefit of providing continuous data over a prolonged time that may be more sensitive than one-off assessments.”

She believes that continuous walking sensors could make clinical trials more efficient, and support clinician decisions.


Join ApplySci at the 9th Wearable Tech + Digital Health + Neurotech Boston conference on September 24 2018 at the MIT Media Lab

DARPA’s Justin Sanchez on driving and reshaping biotechnology | ApplySci @ Stanford

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DARPA Biological Technologies Office Director Dr. Justin Sanchez on driving and reshaping biotechnology.  Recorded at ApplySci’s Wearable Tech + Digital Health + Neurotech Silicon Valley conference on February 26-27, 2018 at Stanford University.


Join ApplySci at the 9th Wearable Tech + Digital Health + Neurotech Boston conference on September 25, 2018 at the MIT Media Lab

Brain sensor monitors cytokines

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Macquarie University’s Kaixin Zhang and Ewa Goldys have developed a sensor that detects cytokines in the living brain.

The signaling molecules, secreted by glia cells, affect mood, cognition and behavior.

The optical fiber sensor’s surface is treated with a capture protein that monitors the release of cytokine molecules in discrete and targeted parts of the brain.  The goal is to understand cytokine secretion, neural circuits, and how they work together in brain health and disease.


Join ApplySci at the 9th Wearable Tech + Digital Health + Neurotech Boston conference on September 25, 2018 at the MIT Media Lab

TMS + VR for sensory, motor skill recovery after stroke

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EPFL’s Michela Bassolino has used transcranial magnetic stimulation to create hand sensations when combined with VR.

By stimulating the motor cortex,  subjects’ hand muscles  were activated, and involuntary short movements were induced.

In a recent study, when subjects observed a virtual hand moving at the same time and in a similar manner to their own during TMS, they felt that a virtual hand was a controllable body part.

25 of 32 participants experienced the effect within two minutes of stimulation. Bassolino believes that the effect may also be achieved through less immersive video.

The technology could  help patients recover sensory and motor skills after a stroke — and also be used as a gaming enhancement.


Join ApplySci at the 9th Wearable Tech + Digital Health + Neurotech Boston conference on September 25, 2018 at the MIT Media Lab

Brain scans, spinal fluid Alzheimer’s biomarkers

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Clifford Jack and Mayo Clinic colleagues have proposed a biomarker, not behavior, based standard for Alzheimer’s disease diagnosis.

Instead of defining the disease through symptoms such as memory or thinking problems, the researchers focus on biological changes, including brain plaques and tangles, determined by brain scans and spinal fluid tests.

The new approach can help researchers study patients with normal brain function who are likely to develop dementia, and help avoid misdiagnosis.  Up to 30 per cent of behavior-based, Alzheimer’s diagnosed patients do not have the disease, with memory or thinking problems caused by something else.


Join ApplySci at the 9th Wearable Tech + Digital Health + Neurotech Boston conference on September 25, 2018 at the MIT Media Lab

Bone-conduction headset for voice-free communication

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MIT’s Arnav Kapur has created a device that senses and interprets neuromuscular signals created when we subvocalize. AlterEgo rests on the ear and extends across the jaw.  A pad sticks beneath the lower lip, and another below the chin. It senses jaw and facial tissue bone-conduction, undetectable by humans.

 Two bone-conduction headphones pick up inner ear vibrations, and four electrodes detect neuromuscular signals. Algorithms determine what a wearer is subvocalizing, and can report silently back. This enables communication with out speaking.

In studies,  researchers interacted with a computer to solve problems; a participant asked a computer the time and got an accurate response; and  another played a game of chess with a colleague.

Click to view MIT Media Lab video


Join ApplySci at the 9th Wearable Tech + Digital Health + Neurotech Boston conference on September 25, 2018 at the MIT Media Lab