Tag: Featured

In a small study, USC’s Dong Song demonstrated the efficacy of an implantable “memory prosthesis.”   Dr. Song presented his work at the Society for Neuroscience conference in Washington this week.

20 volunteers had the device implanted at the same time as electrodes for epilepsy treatment, a procedure which they had already planned.

The “prosthesis” collected brain activity data during tests designed to stimulate  short-term memory or working memory. The researchers then determined and used optimal memory performance patterns to stimulate the brain during later tests.

They claimed that the procedure improved short-term memory by  approximately 15 percent, and working memory by 25 percent. When the brain was stimulated randomly, performance worsened.

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 – Tony Chahine – Shahin Farshchi – Ambar Bhattacharyya – Adam D’Augelli

Registration rates increase November 17th, 2017

MIT’s Ed Boyden and Paris Descartes University’s Valentina Emiliani have developed a new optogenetic technique, combined with new opsins, that stimulates individual cells with precise control over both the timing and location of the activation.

This will allow the study of how individual cells, and connections among those cells, generate specific behaviors such as initiating a movement or learning a new skill.

The study‘s lead authors are Or Shemesh from MIT and Dimitrii Tanese and Valeria Zampini from CNRS.

Neuropixels, developed by HHMI’s Tim Harris, are electrodes that record brain activity from hundreds of neurons. Previously, it was not possible to measure the joint activity of individual neurons distributed across brain regions. Recording methods could either resolve the activity of individual neurons or monitor multiple brain regions.

UCL, Allen Institute for Brain Science, IMEC researchers collaborated on the study. The team is now developing a four-shank probe with a smaller base, for chronic recordings, and optrodes that combine recording with optical stimulation, for optogenetic experiments.

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 – Tony Chahine

Registration rates increase November 10th.

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