EEG identifies cognitive motor dissociation

Nicholas Schiff and Weill Cornell colleagues have developed an EEG-based method for measuring the delay in brain processing of continuous natural speech in patients with severe brain injury. Study results correlated with fMRI obtained evidence, commonly used to identify the capacity to perform cognitively demanding tasks. EEG can be used for long periods, and is cheaper and more accessible than fMRI.

This type of monitoring can identify patients with severe brain injury who have preserved high-level cognition despite showing limited or no consciousness.

According to Schiff: “This approach may be a more effective and efficient method for initially identifying patients with severe brain injuries who are very aware but are otherwise unable to respond, a condition called cognitive motor dissociation.”

Join ApplySci at the 10th Wearable Tech + Digital Health + Neurotech Silicon Valley conference on February 21-22 at Stanford University — Featuring:  Zhenan BaoChristof KochVinod KhoslaWalter Greenleaf – Nathan IntratorJohn MattisonDavid EaglemanUnity Stoakes Shahin Farshchi Emmanuel Mignot Michael Snyder Joe Wang – Josh Duyan – Aviad Hai Anne Andrews Tan Le – Anima Anandkumar – Hugo Mercier

Implanted vagus nerve stimulator partially reverses vegetative state

A person described as being in a vegetative state for 15 years showed partial signs of consciousness after a vagus nerve stimulator was implanted.  University de Lyon’s Angele Sirigu led the research. This challenges the belief that those unconscious for more than 12 months could not be revived.   It also poses a potential challenge to the vegetative diagnosis, and diagnosis in disorders of consciousness generally.

After one month of VNS, the patient’s attention, movements, and brain activity significantly improved, and he began responding to simple orders that were impossible before.

Brain-activity recordings revealed major changes. A theta EEG signal (to distinguish between a vegetative and minimally conscious state) increased significantly in those areas of the brain involved in movement, sensation, and awareness. The brain’s functional connectivity also increased. A PET scan showed increases in metabolic activity in both cortical and subcortical regions of the brain.

The team is now planning a large  study to confirm and extend the therapeutic potential of VNS for patients in a vegetative or minimally conscious state.

Join ApplySci at Wearable Tech + Digital Health + Neurotech Silicon Valley on February 26-27, 2018 at Stanford University, featuring:  Vinod KhoslaJustin SanchezBrian OtisBryan JohnsonZhenan BaoNathan IntratorCarla PughMark Kendall

Ultrasound stimulates thalamus, patient regains consciousness

Martin Monti and UCLA colleagues have used sonic stimulation to excite thalamus neurons,  enabling a patient to recover from a coma, non-invasively.

Previously, deep brain stimulation, which carries significant risk, as electrodes are implanted inside thalamus, was the only way to attempt to achieve this.

The thalamus  was targeted with a low-intensity focused ultrasound, creating a sphere of acoustic energy, aimed at different brain regions to excite tissue.  The low-energy device was activated next to the patient’s head for 30 seconds, 10 times, in 10 minutes.

Before the procedure, the patient showed minimal signs of being conscious and of understanding speech. He could perform limited movements when asked.

His responses grew measurably the day after the treatment.  After 3 days, he regained full consciousness and full language comprehension.  He was able to communicate by nodding his head “yes” or shaking his head “no.” He made a fist-bump gesture to say goodbye to a doctor.

Professor Paul Vespa will test the procedure on several patients at the David Geffen School of Medicine this fall.

Wearable Tech + Digital Health + NeuroTech Silicon Valley – February 7-8 @ Stanford University – Featuring:   Vinod KhoslaTom InselZhenan BaoPhillip Alvelda – Nathan IntratorJohn RogersMary Lou JepsenVivek WadhwaMiguel Nicolelis