My dementia research progress
Our research progress has now slowed down, having copied the brain hippocampal spatiotemporal neural codes, from people with no history of the dementia symptoms into the implant model. The model predicted a 100 percent memory recall. However, transferring the data to patients with dementia, using their own brain hippocampal spatiotemporal neural codes then download onto the implant. This model only predicts memory recall of 30 percent.
We are now involved in trying to find out why the patient’s own brain hippocampal spatiotemporal neural code does not recall memory in the same way as the model from people that have no history of dementia.
Objective: Is to demonstrate here the first successful implementation in humans of a proof-of-concept system for restoring and improving memory function via facilitation of memory encoding using the patient’s own hippocampal spatiotemporal neural codes for memory retention.
However, we have fallen 70% short of the objective, as the model only predicts a memory recall of 30% using the patent’s own Brain Hippocampal Spatiotemporal Neural Code, which the hippocampus encodes memory items via spatiotemporal firing of neural ensembles the underline the successful encoding of short-term memory, a nonlinear multi-input, multi-output.
We have undertaken a significant amount of in-depth investigative research, trying to find which of the neural firing code is missing. To establish what is causing the model to malfunction.
In the process of running, the model to make sure the input data used is accurate. If the input data is accurate, then we will conduct an in-depth analysis of Brain’s firing patterns and which regions of the brain shrink and how it affected memory loss.
The main areas that may be affected are Hippocampus, Thalamus, Amygdala, and Frontal. Researchers also continue to debate whether depression causes the brain to shrink, and the problem is that we cannot find any substantiating research study to verify the amount of shrinkage taking place.
Now a new study in mice shows that microglia may be critical players in memory retention. If the same effect showed up in humans, it means that this is another area that needs further investigation in our research study.
Researchers have also recently shown that microglia are involved in maintaining connections between the nerve cells known as synapses. These are vital communication junctions in order to allow brain cells to talk to each other and transmit brain signals. Specifically, during brain development, microglia actively, this helps to shape the circuity that makes the brain work efficiently.
Now were start to understand the complexities in establishing the proof-of-concept for the system of restoring and improving memory recall. It a challenging, but with proper research, we will get there in the end.
How to get the brain to remember which way to go
According to our model predictions, we can retrieve 30% of memory loss, which can help a patient remember their house number and zip code but not its location.
Medtech is developing a new spatial navigation algorithm to help the patient navigate back to their home location.
The model is incorporating a technique, known as brainwaves aid navigation, which is to become a finite element of the MedTech model update.
This technique based on research that found that the brain appears to implement a GPS for spatial navigation; however, it not fully understood how it works. Although scientist now suggests that rhythmic fluctuations in the brain activity, so-called theta oscillations, play a role in this process.
The reactivation of the brain activity for different object-location pairs occurred at different points of time during the theta cycle. Therefore, theta oscillations may coordinate the reactivation of different memories, what more, may help distinguish between competing memories.
Subsequently, the MedTech model will be designed to record neuronal activity during a navigation task in virtual reality.
The house number and zip code can trigger spatial navigation to locate operations in a virtual environment, as the brain reactivates the location-specific activity patterns.
Should the Medtech models be able to distinguish between competing memories? It would be a significant step forward in disorientation and short-term memory loss; although it is essential to gain a full understanding of the underlying neuronal mechanism.
This technique could benefit patients suffering from neurodegenerative disorders in the future.
A team headed by Dr. Lukas Kunz, Universitätsklinikum Freiburg, and Professor Nikolai Axmacher, Head of the Department of Neuropsychology at Ruhr-Universität Bochum, published their findings on 3 July 2019.
Dementia: 30% improvement in memory recall…
The model predicted a significant improvement of 30% in memory recall. Trying to recover more than 30% is proving more challenging, and further research is necessary.
The implant has state-of-the-art iteration mathematical modeling techniques, with an embedded learning algorithm. It also has a multi-site spatiotemporal code designed to mimic specific memory-related neural ensemble firing patterns. It can restore, and improve function via facilitation of memory encoding using the patient’s own hippocampal spatiotemporal neural codes.
Neuroscience Research Study
Read more> research paper:
Open sharing of scientific data and standard methods will allow researchers to collaborate on this project and accelerate the understanding of recalling short-term memories…
Helping dementia patient’s to recuperate, Short-Term Memories:
This research study’s goals, are to assist people diagnosed in the early stages of dementia, regenerate lost memories.
The study focuses on an area of the brain, known as the hippocampus and hippocampal, these are essential for the consolidation of both short-term and long-term memories. This study’s focal point is on short-term memories.
We want to help dementia patients get their memory back and regain, their independence, and the ability to take care of themselves.
Timely diagnosis is essential, as treatments and interventions are more effective in the first stages of the disease. However, early diagnosis of memory loss has proven to be challenging.
All short-term memory first encoded into a temporary memory store called short-term memory. Short-term memories decay quickly, (1min) and only have a capacity of three or four bits at a time.
Researches have identified that short-term memory can hold 7+/-2 bits of information. They have also demonstrated that short-term memory can hold whatever is rehearsed into 1.5 to 2 seconds. Lager amounts of information can use a process known as chunking.
If a group of more significant bits of information is placed into manageable chunks, for instance, consider a challenging letter sequence: C, I, A, A, B, C, F, B,I, which can be chucked into the easily too memorized: CIA, ABC, FBI.
To retrieve short-term memories, MedTech has designed an intelligent prototype implant to regenerate short-term memories. It is a tiny human implant the size of a grain of rice and as thick as a piece of paper.
Incorporated into implant we used artificial intelligence mathematical modeling techniques, with an embedded learning algorithm. It also has a multi-site spatiotemporal code designed to mimic specific memory-related neural ensemble firing patterns. This can restore, and improve function via facilitation of memory encoding using the patient’s own hippocampal spatiotemporal neural codes.
Incorporated into this tiny implant, MedTech is using artificial intelligence modeling techniques, along with vectors and embedded learning algorithms.
MedTech has added a multi-site spatiotemporal code designed to mimic specific memory-related neural ensemble firing patterns. Which can restore, and improve function via facilitation of memory encoding using the patient’s own hippocampal spatiotemporal neural codes?
Using Artificial Intelligence in this tiny implants,’ this software allows MedTech to use a series of processes by which the hippocampus encodes memory items via spatiotemporal by the firing of neural ensembles that underlie the successful encoding of short-term memory.
Encoding short-term is an essential first step in the development of a neural human prosthetic implant for regaining memory, which utilizes the information content of the hippocampal neural ensembles like dementia.
This is an important first step in the development of a neural human prosthetic implant for regaining memory which utilizes the information content of the hippocampal neural ensembles like dementia.
Acknowledgments & References
Lucia M Li, David W Carmichael, Romy Lorenz, Robert Leech, Adam Hampshire, John C Rothwell, David J Sharp, Externally induced frontoparietal- Synchronization modulates network dynamics and enhance working memory performance. small study, published in the journal eLife. Professor S Daivd Sharp Neurologist in Imperial’s Department of medicine. Ryan Leach of Loyola University; Matthew McCurdy of UIC; along with Laura Matzen and Michael Trumbo of Sandia National Laboratories are co-authors of the paper. Funding: The research was supported by a National Institute on Aging grant (P30AG022849) provided through the Midwest Roybal Center for Health Promotion and Translation.Source: Brian Flood – University of Chicago at Illinois Publisher: Organized by NeuroscienceNews.com.Image Source: NeuroscienceNews.com image is credited to UIC. Original Research: Open access research in Journal of Gerontology: Psychological Sciences and Social Sciences. The results were presented at the 2019 meeting of the American Association for the Advancement of Science. Chemicals ‘repair damaged neurons in mice’ The results were presented at the 2019 meeting of the American Association for the Advancement of Science. Professor Duran has studied the hippocampus – the area that deals with memory – for 40 years. Wake Forest Baptist Medical Center, Winston-Salem, NC, United States of America. 2 University of Southern
Benjamin Franc, M.D., from UCSF, approached Dr. Sohn and University of California, Berkeley, undergraduate student Yiming Ding through the Big Data in Radiology (BDRAD) research group, a multidisciplinary team of physicians and engineers focusing on radiological data science. Dr. Franc was interested in applying deep learning, statistics from the World Health Organization.
Sixth generation cybernetic heart research…
I’ve just completed the design of my sixth generation cybernetic heart concept. Which is built on a completely new research method? This micro-pulsing system is not just innovative, it also a technology breakthrough.
This new design: It’s miniature; compared to the older, fifth-generation cybernetic heart, mainly suitable for adult use. The sixth-generation cybernetic heart is designed to fit teenagers left heart ventricle.
This heart implant is designed, to transform the lives of 122.796 patients, who wait for heart transplantation.
How does it work?
The device’s tiny micro-pulse tube is inserted via a small insertion into the groin. Then maneuver carefully into the patient’s aortic valve.
Once in position, a valve is triggered to expand it to replace the patient’s Aortic valve, securing the implant in place.
The lightweight tubular design, with a valve in the side, that opens to allow oxygenated blood flow in from the hearts right ventricle.
A micro-pulsing system propels an internal slider. This inner slide, now full of compressed blood pressure, which has built up to 120/80 mmHg, releases the Aortic Value allowing the blood to flow around the body.
The device uses artificial intelligence software to calculate or recalibrate a person’s bpm heart rate, based on a person, age or when their fitness levels change.
Inserted into the implant is a tiny 5G SIM card, which transmits, the patient’s heart rhythmic pulses. There’s, also an alarm system that is triggered shows the device has a malfunction.
The device continually transmits data, which is appertaining to its performance. This data is constantly monitored by a remote cardiac unit 24/7. This cardiac unit also introduces upgrades, to the device software management system.
However, this surgical implant, will not be suitable for all patients that are awaiting heart transplantation surgery.
This will be dependent on the amount of damage inflicted on the heart muscles by the patient’s prior cardiac arrests.