Researchers Uncover the Mathematics of Brain Waves

NeuroScience News
September 27, 2018

Summary: Researchers have developed a new mathematical model, which incorporates EEG data and evolutionary game theory, that bridges the gap between waves and random fluctuations in the brain.

Source: U.S Army Research Laboratory.

A U.S. Army Research Laboratory scientist has collaborated with a team of researchers from the University of North Texas to develop a new data processing technique that uses electroencephalogram, or EEG, time series variability as a measure of the state of the brain.

The researchers say such a technique has the potential to provide measures that facilitate the development of procedures to mitigate stress and the onset of conditions such as Post-Traumatic Stress Disorder in warfighters.

“The human brain is considered by many to be the most complex organ in existence, with over a billion neurons and having in excess of a trillion interconnections,” said Dr. Bruce West, senior scientist of mathematics and information science at the U.S. Army Research Office and ARL Fellow.

According to West, it is the operation of this extraordinary complex network of neurons that hosts human thinking, and through the central nervous system, enables the functioning of most, if not all, of the physiologic networks, such as the respiratory, motor control and cardiovascular.

However, according to the researchers, even with this central role the brain plays in enabling our existence, remarkably little is known about how it does what it does.

Consequently, measures for how well the brain carries out its various functions are critical surrogates for understanding, particularly for maintaining the health and wellbeing of military personnel.

A small but measureable electrical signal generated by the mammalian brain was captured in the electrocardiogram of small animals by Caton in 1875 and in human brains by Berger in 1925.

Norbert Wiener, a half century later, provided the mathematical tools believed necessary to penetrate the mysterious relations between the brain waves in EEG time series and the functioning of the brain.

According to West, progress along this path has been slow, and after over a century of data collection and analysis, there is no taxonomy of EEG patterns that delineates the correspondence between those patterns and brain activity….until now!

The technique developed by West and his academic partners generalizes Evolutionary Game Theory, a mathematical technique historically used in the formulation of decision making in war gaming.

Their findings are reported in a paper published in the August edition of Frontiers in Physiology.

In the paper, titled “Bridging Waves and Crucial Events in the Dynamics of the Brain,” West, along with Gyanendra Bohara and Paolo Grigolini of the University of North Texas, propose and successfully test a new model for the collective behavior within the brain, which bridges the gap between waves and random fluctuations in EEG data.

“The work horse of decision making within the military has historically been Game Theory, in which players cooperate or defect, and with pairwise interactions receive various payoffs so that under given conditions certain strategies always win,” West said. “When the game is extended to groups in which individual strategy choices are made sequentially and can change over time, the situation evolves offering a richer variety of outcomes including the formation of collective states in which everyone is a cooperator or a defector, resulting in a collective state.”

It turns out, West said, that the technique developed to process EEG data, the self-organized time criticality method, or SOTC method, incorporates a strategy that is an extension of Evolutionary Game Theory directly into the modeling of the brain’s dynamics.

“The collective, or critical, state of the neural network is reached spontaneously by the internal dynamics of the brain and as with all critical phenomena its emergent properties are determined by the macroscale independently of the microscale dynamics,” West said.

This macroscale can be directly accessed by the EEG spectrum.

The EEG spectrum, obtained by the SOTC method, decays like Brownian motion at high frequencies, has a peak at an intermediate frequency (alpha wave) and at low frequencies has an inverse power law.

In the case of the brain, the inverse power law has revealed that there is a broad range of time scales over which the brain is able to respond to the demands placed on it.

This spectrum suggests a flexibility in response, reflecting a potential range from concentrating on a single task for hours to rapidly countering a physical assault.

“This means that in the foreseeable future the physical training of warriors, along with the necessary monitoring of progress associated with that training, will be expanded to include the brain,” West said. “The reliable processing of brain activity, along with the interpretation of the processed EEG signal, will guide the development of reliable techniques to reduce stress, enhance situational awareness and increase the ability to deal with uncertainty, both on and off the battlefield.”

West said that the research team even speculates that such understanding of brain dynamics may provide the insight necessary to mitigate the onset of PTSD by early detection and intervention, as is routinely done for more obvious maladies.

The human brain is considered by many to be the most complex organ in existence, and Army researchers have developed a technique for its measurement in support of the wellbeing of warfighters. NeuroscienceNews.com image is credited to the U.S Army.

According to West, going forward with this research can proceed in at least two ways.

“One way is to apply these promising results to data sets of interest to the Army,” West said. “For example, quantify how the EEG records of warriors with PTSD differ from a control group of warriors and how this measure changes under different therapy and medication protocols. The other way is to refine the technique, for example, locate where on the scalp it is the most robust, while retaining sensitivity.”

However this research proceeds, these Army scientists are focused on bringing the technology to fruition to help the Soldier of the future succeed in an ever-changing world and battlefield.

Earlier this year, the research team published on work that look at the processing heart rate data and how heart rate was indirectly influenced by meditation through the dynamics of the brain. That work examined how the brain influences the operation of the body by directly measuring how the physiologic system (cardiovascular in this case) responds to changes in the brain (by means of meditation).

This current work focuses on processing EEG data and directly interpreting the dynamics of the brain; it examines how the rhythmic behavior of brain waves (alpha, beta, gamma, etc. waves) can be understood to be compatible with the fluctuations in brain wave data.

Both papers are part of an ongoing ARL-University of North Texas study to determine if the fluctuations in all the physiological systems are produced by a previously unidentified mechanism that we call crucial events.

Zombie Cells Found in Mouse Brains Prior To Mouse Cognitive Loss

Neuroscience News
September 19, 2018

Zombie cells accumulate in certain neurons prior to cognitive loss. By preventing accumulation of these cells, researchers were able to diminish apoptosis, memory loss and tau aggregation.

Source: Mayo Clinic.

ZOMBIE cells are the ones that can’t die but are equally unable to perform the functions of a normal cell. These zombie, or senescent, cells are implicated in a number of age-related diseases. And with a new letter in Nature, Mayo Clinic researchers have expanded that list.

In a mouse model of brain disease, scientists report that senescent cells accumulate in certain brain cells prior to cognitive loss. By preventing the accumulation of these cells, they were able to diminish tau protein aggregation, neuronal death and memory loss.

“Senescent cells are known to accumulate with advancing natural age and at sites related to diseases of aging, including osteoarthritis; atherosclerosis; and neurodegenerative diseases, such as Alzheimer’s and Parkinson’s,” says Darren Baker, Ph.D., a Mayo Clinic molecular biologist and senior author of the paper. “In prior studies, we have found that elimination of senescent cells from naturally aged mice extends their healthy life span.”

In the current study, the team used a model that imitates aspects of Alzheimer’s disease.

“We used a mouse model that produces sticky, cobweb like tangles of tau protein in neurons and has genetic modifications to allow for senescent cell elimination,” explains first author Tyler Bussian, a Mayo Clinic Graduate School of Biomedical Sciences student who is part of Dr. Baker’s lab. “When senescent cells were removed, we found that the diseased animals retained the ability to form memories, eliminated signs of inflammation, did not develop neurofibrillary tangles, and had maintained normal brain mass.” They also report that pharmacological intervention to remove senescent cells modulated the clumping of tau proteins.

Also, the team was able to identify the specific type of cell that became senescent, says Dr. Baker.

Also, the team was able to identify the specific type of cell that became senescent. NeuroscienceNews.com image is in the public domain.

“Two different brain cell types called ‘microglia’ and ‘astrocytes’ were found to be senescent when we looked at brain tissue under the microscope,” says Bussian. “These cells are important supporters of neuronal health and signaling, so it makes sense that senescence in either would negatively impact neuron health.”

The finding was somewhat surprising, explains Dr. Baker, because at the time their research started, a causal link between senescent cells and neurodegenerative disease had not been established.

“We had no idea whether senescent cells actively contributed to disease pathology in the brain, and to find that it’s the astrocytes and microglia that are prone to senescence is somewhat of a surprise, as well,” says Dr. Baker.

In terms of future work, Dr. Baker explains that this research lays out the best-case scenario, where prevention of damage to the brain avoided the disease state. “Clearly, this same approach cannot be applied clinically, so we are starting to treat animals after disease establishment and working on new models to examine the specific molecular alterations that occur in the affected cells,” says Dr. Baker.

Researchers Discover What May Be the Earliest Stage of Alzheimer’s

Neuroscience News

June 13, 2017

Summary: Study reports elevated amyloid plaque are not just a risk factor for Alzheimer's,

but part of the disease and the earliest precursor before symptoms appear.

Source: USC.

Clusters of a sticky protein — amyloid plaque — found in the brain signal mental decline years before symptoms appear, a new study finds.

Older adults with elevated levels of brain-clogging plaques — but otherwise normal cognition — experience faster mental decline suggestive of Alzheimer’s disease, according to a new study led by the Keck School of Medicine of USC that looked at 10 years of data.

Just about all researchers see amyloid plaques as a risk factor for Alzheimer’s.

However, this study presents the toxic, sticky protein as part of the disease — the earliest precursor before symptoms arise.

“To have the greatest impact on the disease, we need to intervene against amyloid, the basic molecular cause, as early as possible,” said Paul Aisen, senior author of the study and director of the USC Alzheimer’s Therapeutic Research Institute (ATRI) at the Keck School of Medicine. “This study is a significant step toward the idea that elevated amyloid levels are an early stage of Alzheimer’s, an appropriate stage for anti-amyloid therapy.”

Notably, the incubation period with elevated amyloid plaques — the asymptomatic stage — can last longer than the dementia stage.

“This study is trying to support the concept that the disease starts before symptoms, which lays the groundwork for conducting early interventions,” said Michael Donohue, lead author of the study and an associate professor of neurology at USC ATRI.

The researchers likened amyloid plaque in the brain to cholesterol in the blood. Both are warning signs with few outward manifestations until a catastrophic event occurs. Treating the symptoms can fend off the resulting malady — Alzheimer’s or a heart attack — the effects of which may be irreversible and too late to treat.

“We’ve learned that intervening before the heart attack is a much more powerful approach to treating the problem,” Donohue said.

Aisen, Donohue and others hope that removing amyloid at the preclinical stage will slow the onset of Alzheimer’s or even stop it.

The amyloid problem

One in three people over 65 have elevated amyloid in the brain, Aisen noted, and the study indicates that most people with elevated amyloid will progress to symptomatic Alzheimer’s within 10 years.

If Alzheimer’s prevalence estimates were to include this “preclinical stage” before symptoms arise, the number of those affected would more than double from the current estimate of 5.4 million Americans, the study stated.

Published in The Journal of the American Medical Association on June 13, the study uses 10 years of data from the Alzheimer’s Disease Neuroimaging Initiative, an exploration of the biomarkers that presage Alzheimer’s. USC ATRI is the coordinating center of this North American investigation. Aisen co-directs its clinical core.

USC plays a leading role in the only two anti-amyloid studies focused on the early, preclinical stage of sporadic Alzheimer’s: The Anti-Amyloid Treatment in Asymptomatic Alzheimer’s study (the A4 Study) and the EARLY Trial, Aisen said.

“We need more studies looking at people before they have Alzheimer’s symptoms,” Aisen said. “The reason many promising drug treatments have failed to date is because they intervened at the end-stage of the disease when it’s too late. The time to intervene is when the brain is still functioning well — when people are asymptomatic.”

Although elevated amyloid is associated with subsequent cognitive decline, the study did not prove a causal relationship.

For years, researchers have acknowledged age is the biggest risk factor when it comes to Alzheimer’s. For more than 90 percent of people with Alzheimer’s, symptoms do not appear until after age 60, according to the Centers for Disease Control and Prevention.

In 2014, about 46 million adults living in the United States — 15 percent of the population — were 65 or older. By 2050, that number is expected to expand to 88 million or 22 percent of the population.

The tipping point

Researchers measured amyloid levels in 445 cognitively normal people in the United States and Canada via cerebrospinal fluid taps or positron emission tomography (PET) scans: 242 had normal amyloid levels and 202 had elevated amyloid levels. Cognitive tests were performed on the participants, who had an average age of 74.

Although the observation period lasted 10 years, each participant, on average, was observed for three years. The maximum follow-up was 10 years.

The elevated amyloid group was older and less educated. Additionally, a larger proportion of this group carried at least one copy of the ApoE4 gene, which increases the odds that someone will develop Alzheimer’s.

Based on global cognition scores, at the four-year mark, 32 percent of people with elevated amyloid had developed symptoms consistent with the early stage of Alzheimer’s disease. In comparison, only 15 percent of participants with normal amyloid showed a substantial decline in cognition.

Analyzing a smaller sample size at year 10, researchers noted that 88 percent of people with elevated amyloid were projected to show significant mental decline based on global cognitive tests. Comparatively, just 29 percent of people with normal amyloid showed cognitive decline.

Alzheimer’s disease research worldwide

Alzheimer’s was recently a disease that could be diagnosed only after death with an autopsy.

If Alzheimer’s prevalence estimates were to include this “preclinical stage” before symptoms arise, the number of those affected would more than double from the current estimate of 5.4 million Americans, the study stated. NeuroscienceNews.com image is for illustrative purposes only.

Aisen and the researchers at USC ATRI have developed ways to identify early signs of Alzheimer’s by creating a set of cognitive tests called the Preclinical Alzheimer Cognitive Composite. This battery of tests and variations of it are widely used to detect Alzheimer’s before dementia symptoms emerge, Aisen said.

“Our outcome measures are becoming the standard for early Alzheimer’s disease intervention studies,” Aisen said. “Drug companies will not invest in early intervention studies without a regulatory pathway forward. ATRI and USC are building a framework for drug development in Alzheimer’s disease.”

As a research institution devoted to promoting health across the life span, USC has more than 70 researchers dedicated to the prevention, treatment and potential cure of Alzheimer’s disease.

Reisa Sperling at Harvard Medical School, Ronald Petersen at the Mayo Clinic, Chung-Kai Sun at USC ATRI and Michael Weiner at the University of California, San Francisco also contributed to this study.

Funding: This work was supported by Biomarkers Across Neurodegenerative Disease, Alzheimer’s Association, Michael J. Fox Foundation, Weston Brain Institute, Alzheimer’s Disease Neuroimaging Initiative, National Institutes of Health.

Source: Zen Vuong – USC
Image Source: NeuroscienceNews.com image is in the public domain.

Original Research: Abstract for “Association Between Elevated Brain Amyloid and Subsequent Cognitive Decline Among Cognitively Normal Persons” by Michael C. Donohue, PhD; Reisa A. Sperling, MD, MMSc; Ronald Petersen, MD, PhD; Chung-Kai Sun, MS; Michael W. Weiner, MD; Paul S. Aisen, MD; for the Alzheimer’s Disease Neuroimaging Initiative in JAMA. Published online June 13 2017 doi:10.1001/jama.2017.6669

Abstract

Association Between Elevated Brain Amyloid and Subsequent Cognitive Decline Among Cognitively Normal Persons

Importance Among cognitively normal individuals, elevated brain amyloid (defined by cerebrospinal fluid assays or positron emission tomography regional summaries) can be related to risk for later Alzheimer-related cognitive decline.

Objective To characterize and quantify the risk for Alzheimer-related cognitive decline among cognitively normal individuals with elevated brain amyloid.

Design, Setting, and Participants Exploratory analyses were conducted with longitudinal cognitive and biomarker data from 445 cognitively normal individuals in the United States and Canada. Participants were observed from August 23, 2005, to June 7, 2016, for a median of 3.1 years (interquartile range, 2.0-4.2 years; maximum follow-up, 10.3 years) as part of the Alzheimer’s Disease Neuroimaging Initiative (ADNI).

Exposures Individuals were classified at baseline as having normal (n = 243) or elevated (n = 202) brain amyloid using positron emission tomography amyloid imaging or a cerebrospinal fluid assay of amyloid β.

Main Outcomes and Measures Outcomes included scores on the Preclinical Alzheimer Cognitive Composite (PACC; a sum of 4 baseline standardized z scores, which decreases with worse performance), Mini-Mental State Examination (MMSE; 0 [worst] to 30 [best] points), Clinical Dementia Rating Sum of Boxes (CDR–Sum of Boxes; 0 [best] to 18 [worst] points), and Logical Memory Delayed Recall (0 [worst] to 25 [best] story units).

Results Among the 445 participants (243 with normal amyloid, 202 with elevated amyloid), mean (SD) age was 74.0 (5.9) years, mean education was 16.4 (2.7) years, and 52% were women. The mean score for PACC at baseline was 0.00 (2.60); for MMSE, 29.0 (1.2); for CDR–Sum of Boxes, 0.04 (0.14); and for Logical Memory Delayed Recall, 13.1 (3.3). Compared with the group with normal amyloid, those with elevated amyloid had worse mean scores at 4 years on the PACC (mean difference, 1.51 points [95% CI, 0.94-2.10]; P < .001), MMSE (mean difference, 0.56 points [95% CI, 0.32-0.80]; P < .001), and CDR–Sum of Boxes (mean difference, 0.23 points [95% CI, 0.08-0.38]; P = .002). For Logical Memory Delayed Recall, between-group score was not statistically significant at 4 years (mean difference, 0.73 story units [95% CI, −0.02 to 1.48]; P = .056).

Conclusions and Relevance Exploratory analyses of a cognitively normal cohort followed up for a median of 3.1 years suggest that elevation in baseline brain amyloid level, compared with normal brain amyloid level, was associated with higher likelihood of cognitive decline, although the findings are of uncertain clinical significance. Further research is needed to assess the clinical importance of these differences and measure longer-term associations.

“Association Between Elevated Brain Amyloid and Subsequent Cognitive Decline Among Cognitively Normal Persons” by Michael C. Donohue, PhD; Reisa A. Sperling, MD, MMSc; Ronald Petersen, MD, PhD; Chung-Kai Sun, MS; Michael W. Weiner, MD; Paul S. Aisen, MD; for the Alzheimer’s Disease Neuroimaging Initiative in JAMA. Published online June 13 2017 doi:10.1001/jama.2017.6669