Featured Post from University of Delaware

Researchers race to detect Alzheimer's sooner using $3.9M grant

Nov 15, 2024

3 min

Too often, people learn they have Alzheimer’s disease when it’s too late. The changes in the brain that lead to the disease manifesting with symptoms have already been occurring for decades.

Researchers at the University of Delaware will attempt to detect the disease sooner through a new study that examines changes in the arteries and brain tissue in midlife adults in their 50s and 60s. The findings of this work, funded by a nearly $4 million grant from the National Institute on Aging (NIA), could identify the earliest mechanisms linking vascular aging to the loss of brain tissue integrity, leading to new targets for interventions aimed at preventing age-related cognitive impairment.

“People who develop high blood pressure or stiffening of the aorta and carotid arteries in midlife are at a much higher risk for developing cognitive impairment or dementia in late life,” said Christopher Martens, the principal investigator of the study.

Martens, an associate professor of kinesiology and applied physiology in UD's College of Health Sciences and director of the Delaware Center for Cognitive Aging (DECCAR), is working closely with Curtis Johnson, an associate professor of biomedical engineering in the College of Engineering and leader of the neuroimaging biomarker core within DECCAR, on research funded by a nearly $4 million grant from the National Institute on Aging (NIA), a division of the National Institutes of Health (NIH).

“A lot happens as we age, so we’re aiming to pinpoint the timing and exact mechanisms that cause these changes in midlife adults,” Martens said.

This latest grant extends DECCAR’s ongoing Delaware Longitudinal Study for Alzheimer’s Prevention (DeLSAP), which seeks to study how risk and protective factors for dementia are related and change over time. Those eligible for DeLSAP could also meet the criteria for participating in the new study.

In his Neurovascular Aging Laboratory, Martens studies mechanisms leading to the stiffening of arteries, while Johnson is specifically interested in measuring the stiffness of the brain.

“As a person ages, the brain gets softer and breaks down, and we’re looking to see whether changes in arterial stiffness and patterns of blood flow in the brain cause this decline,” Johnson said.

Changes in blood flow to the brain come from controllable factors. Smoking, cardiovascular health, diet and exercise all impact blood flow positively and negatively.

“A lot of aging research is done at the end of life,” Johnson said. “We want to look at midlife and try to predict what happens later in life so we can prevent it.”

While the brain gets softer with age, arteries get stiffer.

“We hypothesize that midlife increases in stiffness in blood vessels cause damaging pulsatile pressure to enter the brain,” Martens said. “We believe this is one of the reasons we start to develop cognitive issues at an older age because the brain is exposed to increased pressure; that pressure is likely inflicting damage on surrounding brain tissue.”

In Johnson’s Mechanical Neuroimaging Lab, researchers will use high-resolution magnetic resonance elastography (MRE) to determine where brain damage occurs and what specific brain structures may be affected.

“From an MRI perspective, most researchers look at AD and other neurodegenerative diseases like multiple sclerosis with an emphasis on detection in a hospital setting,” Johnson said. “Using highly specialized techniques we’ve developed, we focus on the earlier side and how these changes progress into disease from the neuroscience side, emphasizing prevention.”

Together, they’ll seek to learn whether arterial stiffness causes the kind of cognitive impairment seen in AD or whether the decline is associated with a loss in the integrity of brain tissue.

“If we can prove arterial stiffness is playing a causal role in cognitive aging, that would provide further support for focusing on blood vessel health as an intervention for delaying AD or other forms of dementia versus solely focusing on the brain,” Martens said.

Connect with:

Chris Martens

Associate Professor, Kinesiology & Applied Physiology

Prof. Martens's laboratory is interested in understanding mechanisms by which impaired vascular function contributes to cognitive declines.

Alzheimer's DiseaseAgingClinical TrialsCerebral Blood FlowVascular Aging

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Jun 23, 2026

3 min

Decoding epilepsy, one brainwave at a time

Epilepsy isn’t always easy to diagnose. Seizures often don't occur during routine brain-wave recordings, leaving doctors without the direct observation they need to make a clear diagnosis. In a proof-of-concept study in mice, University of Delaware researchers and collaborators showed that using artificial intelligence to detect early warning signs hidden in the brain's electrical rhythms can identify subtle EEG differences linked to a genetic form of epilepsy, even when no visible seizures occurred. The findings, published in the Journal of Neural Engineering, set the stage for the next phase of the research, which will test the method on EEGs from children being evaluated for epilepsy at Nemours Children's Health. A dictionary of brain waves Neurologists often use EEGs to help diagnose epilepsy, but routine recordings offer only about a 20-minute snapshot of brain activity. Without a seizure captured during that window, clinicians must look for far subtler clues that can be difficult to detect visually. That's where AI comes in. “Our machine-learning approach lets the algorithm learn the brain’s ‘language’ of waveforms, spotting subtle patterns humans might miss during manual review,” said Austin Brockmeier, assistant professor in electrical and computer engineering and computer and information sciences. Starting small with a mouse model When Brockmeier presented his computational neuroscience research at a seminar, he caught the attention of Amanda Hernan, an affiliated associate professor of psychological and brain sciences and biomedical engineering at UD and senior research scientist at Nemours Children’s Health. Hernan studies how variations in brain activity affect thinking and learning in children with epilepsy. The two decided to put machine learning to the test using EEGs from mice with epilepsy-causing variations in the TSC1 gene. The researchers used a panel of more than 40 mice, including animals with and without the gene variation, across three different genetic backgrounds, or strains. They extracted EEG segments from five days of recordings from each mouse for analysis. Because the EEG segments contained no seizure activity, the algorithm had to detect differences in the brain's baseline activity alone. It was able to distinguish between the mouse strains and to detect the TSC1 gene variation with high accuracy in two of the three strains. “These results show that EEG patterns contain measurable signals of neurological differences, even without visible seizures,” Hernan said. Taking it to the clinic Now, Brockmeier and Hernan will next apply their approach to EEG recordings from children being evaluated for epilepsy at Nemours Children's Health. Pediatric EEGs are shorter than the multi-day recordings used in the mouse study, and children present with many different types of epilepsy. But the researchers are optimistic. “The goal is to identify biomarkers that flag underlying changes in the brain’s electrical activity before seizures occur,” Hernan said. Earlier detection could lead to earlier treatment and less uncertainty for families. That uncertainty, Hernan said, takes a toll. “Seizures follow natural cycles, but without a way to know where you are in that cycle, the anticipation can be incredibly anxiety-provoking,” she explained. Better pattern recognition could also improve treatment decisions. For example, if a new medication is introduced during a natural lull in seizure activity, its benefits could be overestimated. Looking further ahead, the researchers envision a future where wearable EEG devices allow continuous, real-time monitoring for those with high risk of seizures. Similar approaches could eventually be applied to other neurological conditions, including autism and ADHD. "This is a step toward precision medicine," Brockmeier said. "Brain-wave typing could help identify which interventions will work best for a given patient." For families navigating the daily uncertainty of epilepsy, that kind of precision could make a huge difference. To speak with Brockmeier and Hernan, please reach out to mediarelations@udel.edu.

Jun 18, 2026

1 min

UD’s happiness expert appears on NPR's Hidden Brain to explain importance of a helping hand in a stressed-out America

Happiness isn’t just about chasing big, exciting moments. A lot of the science points to the smaller, everyday things that help people feel connected, calm and grounded. Simple habits like helping others when we see them struggling create a bigger impact than we often expect. University of Delaware's resident "happiness expert" Amit Kumar, a psychologist and assistant professor of marketing in UD's Lerner College of Business & Economics, appeared on NPR's Hidden Brain to discuss that very topic. Kumar discusses why sometimes it feels like we can't help others and how we can surmount those fears to build strong connections and also feel a greater sense of happiness. To speak with Kumar about this topic, click his profile.

Jun 11, 2026

1 min

Concussions in soccer featured

University of Delaware professor Tom Kaminski leads FIFA’s research on header safety and avoiding concussions. NBC10 Delaware Bureau reporter Tim Furlong tells us more about his findings.