Category: Brain

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AI Brain Parkinson's

Neural Network assesses sleep patterns for passive Parkinson’s diagnosis

MIT’s Dina Katabi has developed a non-contact, neural network-based system to detect Parkinson’s disease while a person is sleeping.

By assessing nocturnal breathing patterns, the series of algorithms detects, and tracks the progression of, the disease — every night, at home.

A device in the bedroom emits radio signals, analyzes their reflections off the surrounding environment, and extracts breathing patterns, without bodily contact. The breathing signal is then fed to the neural network to assess Parkinson’s Disease in a passive manner.

Current diagnosis methods are invasive, expensive, and must be done at specialized centers, making frequent testing almost impossible.

Katabi said that a relationship between Parkinson’s and breathing was noted in 1817, motivating her to explore this form of detection, and that respiratory symptoms manifest years before motor symptoms.

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BCI Brain

First US patient receives Synchron endovascular BCI implant

On July 6, 2022, Mount Sinai’s Shahram Majidi threaded Synchron‘s 1.5-inch-long, wire and electrode implant into a blood vessel in the brain of a patient with ALS. The goal is for the patient, who cannot speak or move, to be able to surf the web and communicate via email and text, with his thoughts.

Four patients in Australia have already received the Synchron implant. They have not had side effects, and have been able to send WhatsApp messages and make online purchases.

The “Stentrode” device can be inserted into the brain without cutting through a person’s skull or damaging tissue. An incision is made in the neck, and the stentrode is fed, via catheter, through the jugular vein, into a blood vessel within the motor cortex. As the catheter is removed, the stentrode opens and begins to fuse with the outer edges of the vessel. The procedure takes a few minutes.

A second procedure connects the stentrode to a computing device in the patient’s chest, with a wire. A surgeon creates a tunnel for the wire and a pocket for the device underneath the patient’s skin, similar to a pacemaker procedure. The stentrode reads neuron signals, and the computing device amplifies them and sends them to a computer or phone via Bluetooth.

Synchron aims to shrink the size of its devices, and increase their computing power. It hopes to be able to place numerous stentrodes in different parts of the brain, allowing the patient toperform more functions.

The company was founded by Dr. Thomas Oxley, who will be a featured speaker at ApplySci’s Deep Tech Health + Neurotech conference at MIT on September 30, 2022.

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Babies Brain Sensors

Sensor jumpsuit monitors infant motor abilities


Sampsa Vanhatalo, Manu Airaksinen and University of Helsinki colleagues have developed MAIJU (Motor Assessment of Infants with a Jumpsuit,) a wearable onesie with multiple movement sensors which they believe is able to predict a child’s neurological development.

In a recent study, 5 to 19 month-old infants were monitored using MAIJU during spontaneous playtime. Initially, infant postures and movements were identified visually from a video using a motility description scheme. This was used to train an algorithm to recognize the same postures and movements for every second of each child’s playtime, making it possible to assess her or him in a natural environment.

The goal is the earliest possible detection of neurodevelopmental delays, for earlier intervention. and better outcomes, as therapies would be a part of the child’s everyday life and environment.

The researcher believe that their technology could be automized and effectively adapted to help older children and seniors.

Click to view University of Helsinki video

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Giovanni Traverso – MIT |  George Church – Harvard, MIT | Kerri Dugan – DARPA |  Emery Brown – Harvard |  Bakul Patel – Google |  Nathan Intrator – Neurosteer|  Ramita Tandon – Walgreens |  Ellen Roche – MIT |  Shaun Patel – REACT Neuro | Tom Oxley – Synchron |  Elizabeth Ankudowich – NIH |  Cris De Luca – Sanofi Ventures |  Mary Lou Jepsen – Openwater |  Bob Langer – MIT

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Brain Parkinson's

Joe Wang developed, closed-loop, levadopa delivery/monitoring system for Parkinson’s disease

Early Parkinson’s Disease patients benefit significantly from levodopa, to replace dopamine to restore normal motor function. As PD progresses, the brain loses more dopamine-producing cells, which causes motor complications and unpredictable responses to levodopa. Doses must be increased over time, and given at shorter intervals. Regimens are different for each person and may vary from day-to-day.

Currently, clinicians assess levodopa’s benefit by patient testimony and clinical exam, making it difficult to determine optimal treatment. Novel levodopa delivery strategies and wearable sensors that track symptoms and disease progression have been created, but levodopa levels in the body have not been monitored in real time.

Joe Wang and colleagues have developed a closed loop levodopa delivery system. A network of physical and chemical sensors monitor levodopa levels and inform a delivery device, guided by algorithms, creating a personalized regimen. This can finally optimize the therapeutic management of Parkinson’s Disease.

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Brain Sensors

Carbon nanotube sensor precisely measures dopamine

Ruhr University professor Sebastian Kruss, with Max Planck researchers Sofia Elizarova and James Daniel, has developed a sensor that can visualize the release of dopamine from nerve cells with unprecedented resolution. The team used modified carbon nanotubes that glow brighter in the presence of the messenger substance dopamine.

Eizarova said that the sensor “provides new insights into the plasticity and regulation of dopamine signals. In the long term, they could also facilitate progress in the treatment of diseases such as Parkinson’s.”

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Brain

Univ. of Reading study links Alzheimer’s disease to blood brain barrier damage

The “Lipid Invasion Model” argues that lipids entering the brain due to blood brain barrier damage is the determining cause of the Alzheimer’s Disease. The presence of excess lipids in the brain cells of Alzheimer’s patients is an element of Alois Alzheimer’s 1906 research, but little has been published about this connection since.

The hypothesis, published in the Journal of Alzheimer’s Disease Reports, could impact diagnosis and treatment, and supports lifestyle changes (ie diet for cholesterol management) to reduce risk.

According to Post Doc Jonathan Rudge, invading lipids can result in brain shrinkage, and amyloid plaque and tau tangle development.

The new study follows 10 years of research and suggests that risk factors associated with Alzheimer’s Disease are the same factors that damage the blood brain barrier—advanced age, head injury, hypertension, smoking, obesity, diabetes, chronic sleep deprivation and stress.

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Autism Brain MRI

Prenatal MRI study suggests autism differences may begin in the womb

A small Boston Children’s Hospital study led by Assistant Professor Emi Takahashi and postdoc Alpen Ortug showed increased volume of the insular lobe as a potential strong prenatal MRI biomarker that could predict the emergence of ASD later in life. It revealed significant differences in brain structures at 25 weeks’ gestation between children who were later diagnosed with ASD and those who were not.

If validated, this could enable earlier treatment after birth, which could improve outcomes. Early treatment has been shown to improve language and cognitive abilities, but current diagnostic tools can only identify the disorder around 18 months of age.

39 fetal MRI brain scans at 25 weeks’ gestation taken at Boston Children’s Hospital were analyzed. 9 children were later diagnosed with ASD, 20 were neurotypical and 10 did not have ASD but had other conditions also observed in the children with ASD.

An atlas-based automated anatomical labeling method was used to segment the scans and compare brain regions between the different groups. The insular lobe was found to have significantly larger volume in the ASD group compared with the other 3 control groups.

The findings align with studies that have reported changes in the insular cortex in adults with autism, and suggests these differences may begin in the womb. The scans from children with ASD also showed a significantly larger amygdala and hippocampal commissure compared with children who had other health conditions but not ASD.

According to Ortug, “to the best of our knowledge, this is the first attempt to semi-automatically segment the brain regions in the prenatal stage in patients who are diagnosed with autism later and compare different groups of controls.”

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Brain

Stanford study: High dose magnetic stimulation eases severe depression

Nolan Williams, Alan Schatzberg, and Stanford colleagues have published a small, double blind study showing that high dose, noninvasive, magnetic brain stimulation alleviated depression symptoms in 80% of participants.

Stanford accelerated intelligent neuromodulation therapy (SAINT) is an intensive, individualized form of transcranial magnetic stimulation. Effects were seen within days and lasted months. Side effects included fatigue and headaches.

29 people with treatment-resistant depression participated. Half received SAINT, and half received a placebo procedure. After five days, 78.6% of the participants in the treatment group had eased symptoms.

See CBS Sunday Morning video describing patient experiences with SAINT

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Brain

Passive EEG assessment detects cognitive decline early

George Sothart and University of Bath colleagues have developed a new, EEG + game memory assessment technique which could enable the earlier diagnosis of Alzheimer’s disease, the underlying cause of around 60% of dementia cases..

The need for early diagnosis tools to help doctors to prescribe lifestyle interventions to slow the rate of cognitive decline is obvious. This tool could also help identify dementia patients for clinical trials.

“Fastball EEG” is passive. The person performing the test is not given priorinstructions prior to the task, as dementia patients may struggle to follow complex directions, and is not asked to reflect on, respond to or remember any items. She or he simply watches a screen of flashing images.

Two discrete frequency responses are captured, reflecting the participant’s periodic neural responses to the stimuli. The first reflects visual processing; the second mirrors the brain’s response to previously seen images and reflects recognition memory. Analyzing the EEG spectrum at the second, slower frequency can quantify the patient’ memory response.

Fastball EEG was studied in 20 patients with Alzheimer’s disease, 20 healthy older adults and 20 healthy younger adults. For both the recognition and repetition conditions, Fastball EEG detected significantly impaired recognition memory in Alzheimer’s disease patients compared with healthy older control subjects. There were no differences between the two groups under the control condition, where image recognition was not included. The Fastball test could also discriminate Alzheimer’s disease patients from healthy older adult controls, with an accuracy of 86%. No significant performance differences were seen between older and younger healthy controls.

After the Fastball task, participants completed a forced-choice task, in which they had to identify a previously seen image from two alternatives. Here, the researchers observed little difference between Alzheimer’s disease patients and controls, suggesting that Fastball was more sensitive to memory performance than this behavioral recognition test.

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Brain

Apple partners with UCLA, Biogen for iPhone mental/cognitive health monitoring


The Apple/UCLA project “Seabreeze” and Apple/Biogen project “Pi” represent a further move into iPhone health monitoring.

According to the Wall Street Journal, Apple is attempting to develop an algorithm to identify depression and cognitive decline from sleep patterns, mobility, and how one uses the phone — for example, how often they look at its clock.

This follows a study that Apple Did with Eli Lilly, which showed that MCI and early dementia patients typed slowly, used devices erratically, sent fewer texts, and used “helper apps” often.

A recent Apple/Duke study analyzed kids phone use to understand emotions and behavior that could be associated with autism.

Mindstrong Health and others have been evaluating phone use to detect mental illness for years, and Mindstrong has recently moved into therapy and psychiatry offerings, based on phone based digital phenotyping, which could be where Apple is headed with these new projects.

The very earliest stages of mental and cognitive wellness changes could be missed using phone data alone, but could still be detected with EEG or other brain signal monitoring technology.

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BCI Brain

Nurmikko’s Neurograins can enable unprecedented brain signal recording detail, new therapies


Arto Nurmikko and Brown colleagues have developed BCI system which employs a coordinated network of independent, wireless microscale neural sensors, to record and stimulate brain activity. “Neurograins” independently record electrical pulses made by firing neurons and send the signals wirelessly to a central hub, which coordinates and processes the signals.

In a recent Nature paper, the team demonstrated the use of 50 autonomous neurograins to record neural activity in a rodent. They believe that this can enable a future system of unprecedented brain signal recording detail, and new therapies for brain diseases and spine injuries.

According to Nurmikko, “one of the big challenges in the field of brain-computer interfaces is engineering ways of probing as many points in the brain as possible. Up to now, most BCIs have been monolithic devices — a bit like little beds of needles. Our team’s idea was to break up that monolith into tiny sensors that could be distributed across the cerebral cortex. That’s what we’ve been able to demonstrate here.”

48 neurograins were placed on a rodent’s cerebral cortex, and successfully recorded characteristic neural signals associated with spontaneous brain activity. The team also tested the devices’ ability to stimulate the brain with electrical pulses.

The size of the animal’s brain limited the team to 48 neurograins for this study, but the data suggest that the current configuration of the system could support up to 770. Ultimately, the team envisions scaling up to many thousands of neurograins, which would provide a currently unattainable picture of brain activity.

Click to view Professor Nurmikko discussing Brain Computer Interfaces at the 2019 ApplySci conference at Harvard Medical School.

June us at the 14th Wearable Tech + Digital Health + Neurotech Boston conference, on April 8, 2022 at MIT.

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BCI Brain Sensors

Polymer improves medical implants, could enable brain-computer interface

David Martin and University of Delaware colleagues have developed a bio-synthetic coating for electronic components that could avoid the scarring (and signal disruption) caused by traditional microelectric materials. The PEDOT polymer improved the performance of medical implants by reducing their opposition to an electric current.

Pedot film was used with an antibody to stimulate blood vessel growth after injury, and could be used to detect early stages of tumor growth. The polymers could also help sense or treat brain or nervous system disorders, while versions could theoretically attach peptides, antibodies and DNA.

The team believes that materials, when inserted, could connect brains to a computer.