Category: Brain

David Brent and PIttsburgh and Carnegie Mellon colleagues used machine learning to identify suicidal thoughts in subjects based on fMRI scans.

In a recent study, 18 suicidal participants and 18 members of a control group  were presented with three lists of 10 words related to suicide, positive, or negative effects. Previously mapped neural signatures  showing  brain patterns of emotions like “shame” and “anger” were incorporated.

5 brain locations, and 6 words, were distinguished suicidal patients from the controls. Using those locations and words,  a machine-learning classifier was trained and able to identify 15 of the 17 suicidal patients and 16 of 17 control subjects.

Suicidal patients were divided into those that had attempted suicide (9) and those that had not (8). Another classifier was then able to identify 16 of the 17 patients.

If healthy patients and those with suicidal thoughts are proven to have such different reactions to words, this work could impact therapy and, it is our hope, prevent lost lives.

Join ApplySci at Wearable Tech + Digital Health + Neurotech Silicon Valley on February 26-27, 2018 at Stanford University. Speakers include:  Vinod Khosla – Justin Sanchez – Brian Otis – Bryan Johnson – Zhenan Bao – Nathan Intrator – Carla Pugh – Jamshid Ghajar – Mark Kendall – Robert Greenberg – Darin Okuda – Jason Heikenfeld – Bob Knight – Phillip Alvelda – Paul Nuyujukian –  Peter Fischer

Recorded at ApplySci’s Wearable Tech + Digital Health + Neurotech conference on September 19th at the MIT Media Lab.

Join ApplySci at Wearable Tech + Digital Health + Neurotech Silicon Valley on February 26-27, 2018 at Stanford University. Speakers include:  Vinod Khosla – Justin Sanchez – Brian Otis – Bryan Johnson – Zhenan Bao – Nathan Intrator – Carla Pugh – Jamshid Ghajar – Mark Kendall – Robert Greenberg – Darin Okuda – Jason Heikenfeld – Bob Knight – Phillip Alvelda

Christof Koch and Allen Institute colleagues  have created 3D computer reconstructions of living human brain cells using discarded surgical tissue.  As the tissue is still alive when it reaches the lab, the virtual cells are able to capture electrical signals, in addition to cell shape and anatomy.

This is the first time that scientists have been able to study the electrical behavior of living brain cells in humans.

Koch believes that this will enhance our understanding of how brain diseases, including Alzheimer’s and schizophrenia, impact the behavior of brain cells.

The institute has captured electrical data from 300 living neurons, taken from 36 patient brains.  100 cells have been reconstructed in 3D.  Genetic information about some of the cells will eventually be added to the database.

Click to view the  Allen Institute video.

Join ApplySci at Wearable Tech + Digital Health + Neurotech Silicon Valley on February 26-27, 2018 at Stanford University. Speakers include:  Vinod Khosla – Justin Sanchez – Brian Otis – Bryan Johnson – Zhenan Bao – Nathan Intrator – Carla Pugh – Jamshid Ghajar – Mark Kendall – Robert Greenberg – Darin Okuda – Jason Heikenfeld – Bob Knight

Neurodegenerative disease cases have, unfortunately, far outpaced the number of neurologists able to diagnose and treat patients, particularly in rural areas. A recent study highlighted 20 states that were or would become “dementia neurology deserts,”

Remote tele-neurology is being introduced to fill the gap.

The American Academy of Neurology has announced a new curriculum to train students and providers to use video conferencing, sensors, and text and image communication tools to connect  with patients. Five training areas, developed by the University of Missouri, are the focus: technology; legal and ethical issues; “webside” manners; privacy; and, of course, neurology expertise

The University of Texas, Vanderbilt University, and Tufts Medical Center are already using teleneurology..

Join ApplySci at Wearable Tech + Digital Health + Neurotech Silicon Valley on February 26-27, 2018 at Stanford University, featuring:  Vinod Khosla – Justin Sanchez – Brian Otis – Bryan Johnson – Zhenan Bao – Nathan Intrator – Carla Pugh – Jamshid Ghajar – Mark Kendall – Robert Greenberg – Darin Okuda – Jason Heikenfeld

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

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