brain mapping Archives - Amazing Health Advances

Robot Reduces Need for Open Brain Surgery to Map Epileptic Seizures

The AHA! Team — Fri, 03 Jan 2025 07:38:39 +0000

Debbe Geiger via Duke Health – A Medical Advance for People with Epilepsy. A robotic device is allowing doctors to pinpoint the origins of a person’s seizures through minimally invasive surgery. The device, in use at Duke and some epilepsy centers across the country, allows neurosurgeons to implant hundreds of recording electrodes into the brain through about 10 to 20 small incisions. The procedure is highly precise, and it takes less time than traditional surgical options for seizure localization. People also recover faster and have less pain. Diagnosing the Origin of Epilepsy Seizures When medications fail to stop epileptic seizures, a person’s best hope for gaining control of their seizures is often epilepsy surgery. That can only happen if doctors can identify the area of the brain responsible for the seizures and remove it safely. To identify that spot, neurosurgeons may perform a craniotomy, creating a large opening in the skull, and then place a plastic grid of electrodes on the surface of the brain to record seizures and identify where they originate. However, the electrodes can’t access the folds or the parts of the brain between the two hemispheres and its deep structures. Shorter, More Precise Brain Mapping The team at Duke’s epilepsy center has another tool in their arsenal. Robot-assisted stereoelectroencephalography (SEEG) is a minimally invasive procedure that rapidly places thin electrode wires in precise locations to map the brain and identify seizure origins. A 3D reconstruction of the brain guides where the dozen or more electrodes will be placed. The neurosurgeon uses a robotic arm to make small, two- or three-millimeter holes in the scalp through which the rigid electrode wire is passed. As opposed to grid electrodes, which sit on the surface of the brain, the wires are placed into the brain tissue with robotic assistance. The procedure takes about two to three hours. “The robot improves the efficiency of the procedure, and it reduces some of the possibility for human error. Depending on the patient’s condition, robot-assisted SEEG can be very useful for localizing seizures in a way that is more comfortable for patients,” said Duke neurosurgeon Derek Southwell, MD, PhD, of the Duke Comprehensive Epilepsy Center. Due to its minimally invasive nature, placing depth electrodes this way is much better tolerated by patients than placing grid electrodes. Once the seizure origin is identified, the electrodes are removed, and people recover quickly. That is a huge benefit over recuperating from a craniotomy. The procedure is also better for cases where the exact location of the seizure cannot be identified, or the seizure origin is in a part of the brain that is inoperable. To read the original article click here.

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How Neurofeedback Can Help Treat Depression, Anxiety, Addiction & PTSD

AHA Publisher — Fri, 18 Sep 2020 07:00:07 +0000

Makram Leaf via Dr. Caroline Leaf – For many people, brain maps can be quite alien and strange. What are they telling us? What do they mean? Do all these shapes and colors and symbols mean there is something terribly wrong with me? It certainly doesn’t help when you read sensationalist headlines like “This is your brain on drugs!” or “This is what happens to your brain when you are stressed!”, which only serve to make us more nervous about what is happening between our ears. In this week’s blog and podcast, I speak with UCLA-trained neuroscientist, top performance coach and founder of The Peak Brain Institute Dr. Andrew Hill about what brain scans an tell us about our brain, the role they play in neurofeedback therapy, how neurofeedback and brain scans can boost our performance and help treat depression, anxiety, addiction and PTSD, the myth of the normal brain, how to biohack sleep, and so much more! As humans, we tend to exhibit similar behaviors within a bell curve or range. When the core functions of the brain get out of this range, it can cause all sorts of mental and physical health issues. Brain maps like QEEGs (which is what Andrew uses at his institute and what I used in my most recent clinical trials) allow us to compare a set of brain waves to a referenced database. These images show the ways your brain is different; they are not a diagnostic tool, but a way of exploring your mind and generating ideas about what may be going on in your life and what to change. It is important to remember that there is no such thing as a normal brain. We are all different, so when we look at a brain map we should not wonder why we are not closer to the average. People are generally similar within a bell curve; brain maps are yard sticks, not value labels. It is not about trying to map you onto a “normal” brain; at the end of the day, only you are your own true comparison, which is why seeing how your brain maps change over time is far more important that comparing your brain to someone else’s. At The Peak Brain Institute, Andrew teaches people how to read their unique brain maps and make changes in their lives. He gives them agency and perspective and shows them how to use the information because only the person who is suffering truly knows what they need to do to change. Andrew is passionate about empowering people to take back control of their lives, and believes that the locus of control should always be internal. One of the main ways the Peak Brain Institute helps teach people how to change their brains and behavior is through something called neurofeedback therapy. As Andrew points out, neurofeedback is a process in which simple auditory and visual feedback guide your brain gradually to make more or less of specific brainwave frequency bands, and/or to enhance connectivity between two regions of the brain. These frequencies and connectivity guide much of our mental behavior—as we adjust them, we adjust the corresponding behaviors. Neurofeedback is based on receiving positive input when you want the brain to do more of something by measuring what is going on in your head. With this encouraging reinforcement, the brain starts to lean into the change. You don’t notice this change as much at first, but over time you will feel better and better. This is like an iterative training session or workout for the brain—you tune into the process to get more positive effects and reduce any negative side-effects. This kind of training can help with our performance and creativity by boosting alpha and theta energy in the brain. It can also help with PTSD, anxiety and depression. In addition, neurofeedback can help with common issues like sleep deprivation and unhealthy eating habits. As Andrew points out, if we want to be healthier, we should always start with the routine things. The best place to start biohacking your body and increasing your performance and health is with the things you do every day, like sleeping, eating and exercising. When it comes to sleep, the fear of not sleeping often creates a larger issue over time than the sleep loss itself, and can become a major issue in people’s lives, as I discussed in a recent blogand podcast. Trying get more deep sleep can really make a difference in your life. You can start doing this by: Fasting before bed. Don’t eat for at least 3-4 hours before bed, so that there is no insulin in the bloodstream, which will suppress the growth hormones that are released during sleep (this is especially true for women). Maintaining your schedule. It is important to try to get up around the same time 7 days a week—crazy schedules can throw our sleeping patterns off for weeks. Exercising before you eat. Fasted workouts can really help improve sleeping patterns and overall health. Tracking your sleeping habits. Use devices like the Oura Ring to monitor how much deep sleep you get. To read the original article click here. For more articles from Dr. Leaf click here.

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Dementia Spreads Via Connected Brain Networks

AHA Publisher — Fri, 18 Oct 2019 07:00:40 +0000

University of California – San Francisco via EurekAlert – Brain maps allow individualized predictions of frontotemporal dementia progression. In a new study, UC San Francisco scientists used maps of brain connections to predict how brain atrophy would spread in individual patients with frontotemporal dementia (FTD), adding to growing evidence that the loss of brain cells associated with dementia spreads via the synaptic connections between established brain networks. The results advance scientists’ knowledge of how neurodegeneration spreads and could lead to new clinical tools to evaluate how well novel treatments slow or block the predicted trajectory of these diseases. “Knowing how dementia spreads opens a window onto the biological mechanisms of the disease — what parts of our cells or neural circuits are most vulnerable,” said study lead author Jesse Brown, PhD, an assistant professor of neurology at the UCSF Memory and Aging Center and UCSF Weill Institute for Neurosciences. “You can’t really design a treatment until you know what you’re treating.” FTD, the most common form of dementia in people under the age of 60, comprises a group of neurodegenerative conditions with diverse linguistic and behavioral symptoms. As in Alzheimer’s disease, the diversity of FTD symptoms reflects significant differences in how the neurodegenerative disease spreads through patients’ brains. This variability makes it difficult for scientists searching for cures to pin down the biological drivers of brain atrophy and for clinical trials to evaluate whether a novel treatment is making a difference in the progression of a patient’s disease. Previous research by the study’s senior author, William Seeley, MD, a professor of neurology and pathology at the Memory and Aging Center and Weill Institute, set off a sea change in dementia research by showing that patterns of brain atrophy in many forms of dementia map closely onto well-known brain networks — groups of functionally related brain regions that work cooperatively via their synaptic connections, sometimes over long distances. In other words, Seeley’s work proposed that neurodegenerative diseases don’t spread evenly in all directions like a tumor, but can jump from one part of the brain to another along the anatomical circuits that wire these networks together. In their new study — published October 14 in Neuron — Brown, Seeley and colleagues provided further evidence supporting this idea by examining how well neural network maps based on brain scans in healthy individuals could predict the spread of brain atrophy in FTD patients over the course of a year. The researchers recruited 42 patients at the UCSF Memory and Aging Center with behavioral variant fronto-temporal dementia (bvFTD), a form of FTD that causes patients to exhibit inappropriate social behaviors, and 30 patients with semantic variant primary progressive aphasia (svPPA), a form of FTD that mainly impacts patients’ language abilities. In their first visits to UCSF, each of these patients underwent a “baseline” MRI scan to assess the extent of existing brain degeneration and then had a follow-up scan about a year later to measure how their disease had progressed. The researchers first estimated where the brain atrophy seen in each patient’s baseline scans had begun, based on the hypothesis that brain degeneration begins in some particularly vulnerable location, then spreads out to anatomically connected brain regions. To do this, the researchers built standardized maps of the main functional partners of 175 different brain regions based on functional MRI (fMRI) scans of 75 healthy adults. They then identified which of these networks best matched the pattern of brain atrophy seen in a given FTD patient’s baseline brain scans, and defined that network’s central hub as the likely epicenter of the patient’s degeneration. They then used the same standardized connectivity maps to predict where the patient’s brain atrophy was most likely to have spread in the follow-up scans done one year later, and compared the accuracy of these predictions to others that didn’t take functional network connectivity into account. They found that two particular connectivity measures significantly improved their predictions of a given brain region’s chances of developing brain atrophy between the baseline and follow-up brain scans. One, called “shortest path to the epicenter,” captured the number of synaptic “steps” that region was from the estimated disease epicenter — essentially the number of links in the neural chain connecting the two areas — while the other, called “nodal hazard,” represented how many regions connected to a given region were already experiencing significant atrophy. “It’s like with an infectious disease, where your chances of becoming infected can be predicted by how many degrees of separation you have from ‘Patient Zero’ but also by how many people in your immediate social network are already sick,” Brown said. The researchers showed that on average these two measures of network connectivity did better at predicting the spread of disease to a new brain region than its simple straight-line distance from a patient’s existing atrophy. In many cases the disease completely bypassed brain areas that were adjacent but not anatomically connected to already-atrophied regions, instead jumping to more functionally linked regions. Although this method shows great promise, the researchers emphasize that it is not yet ready for clinical use. They hope to improve the accuracy of their predictions by — among other approaches — using individualized network maps for each patient rather than using average connectivity maps, and by developing more specialized prediction models for particular subtypes of FTD. In addition to the biological insights the discovery provides about the mechanisms of spreading brain atrophy in FTD, which will inform ongoing efforts to develop treatments, the researchers also hope the findings will lead to improved metrics for evaluating therapies already entering clinical trials — for instance by giving trial scientists early insights into whether the treatment is altering a predicted course of disease progression. Researchers could also use better predictions of how atrophy will spread through the brain to help prepare patients and their families for the symptoms they are likely to experience as their disease progresses. “We are excited about this result because it represents an important first step toward a more precision medicine type of approach to predicting progression and measuring treatment effects in neurodegenerative disease,” Seeley said. In the future, Brown said, scientists might be able to develop therapies that specifically target the likely next site of disease and perhaps prevent atrophy from spreading from one region to another. “Just like epidemiologists rely on models of how infectious diseases spread to develop interventions targeted to key hubs or choke points,” Brown said. “Neurologists need to understand the underlying biological mechanisms of neurodegeneration to develop ways of slowing or halting the spread of the disease.” To read the original article click here.

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