Cognitive decline is a major and growing public health issue. We’re researching how a working memory for a particular sensory input or object — like the shape of a car, or its location in a parking lot — is encoded and represented in the brain. We want to better understand how shape and space are characterized in different brain regions, and how attention, memory and task demands influence those representations. This is key not only to describing and diagnosing attention deficits in human disorders, but also to developing more effective interventions.
In 2019, the Center for Disease Control and Prevention (CDC) reported that 1 in 9 U.S. adults older than 45 said they are experiencing cognitive decline (attention or memory loss). The report notes that cognitive impairment is one of the earliest noticeable symptoms of Alzheimer’s disease and related dementias. Alzheimer’s is the most expensive disease in the U.S., with estimated costs exceeding $277 billion in 2018. In that year, 20 percent of Medicare dollars were spent on the care of people with Alzheimer’s, and that figure is projected to rise to 33 percent by 2050.
Cognitive deficits also are present, and disabling, in many other human disorders. These include developmental disorders, such as attention deficit and autism spectrum conditions; neurological diseases or disorders like Parkinson’s disease and traumatic brain injury; and psychiatric ailments, including anxiety disorders and depression.
There are many kinds of memory. For example, some are long-term memories (such as remembering the name of your first-grade teacher), whereas others are shorter-term working memories that are retained only for as long as you need them (like remembering that the stove is on). Different regions of the brain seem to be important for specific kinds of memory.
In the past, most physiological research focused on examining responses at a single-cell level. Advancing beyond that point, our lab has developed and popularized a “population-based” analytic approach — looking at groups of neurons, and comparing these populations across brain regions. This novel method does not label each neuron with specific external world stimuli and task demands, as is common, but instead, charts only the relative neural activities of the neuronal populations.
This analytic approach enables us to make explicit the geometrical relationships among different stimulus responses within a cell population’s representation space. Such a data-driven approach allows us to better understand and characterize the representations of shape and space, as well as to illuminate how attention and memory influence or change these representations in different parts of the brain. For the first time, we have shown striking differences in the encoding of shape, space, and attention and memory across the brain’s dorsal and ventral cortical regions.
The same data-driven analytic technique can be used with functional magnetic resonance imaging (fMRI) data, substituting voxels (graphical units) for neurons to allow for the use of more complex and elaborate stimuli and task conditions. Understanding how attention and memory modulate representations in different parts of the brain is a crucial next step toward identifying and distinguishing early attentional and mnemonic deficits in disorders.
Our lab’s overarching goal is to better understand attention and memory and to link them with the underlying physiological mechanisms in order to improve the diagnosis and treatment of cognitive deficit disorders. Our memory physiology work aims to unlock the relationship between neuronal cellular properties and behavior, and to devise better interventions for cognitive issues.
Cognitive decline is not only a mounting societal concern but also a vital personal issue. Research suggests that Americans are twice as fearful of losing their mental capacity as they are of having diminished physical ability, and that 60 percent of American adults are worried about memory loss.
Many have described the understanding of the brain — an organ weighing just slightly more than 1,000 grams — and its daunting counterparts, the mind and thought, as the last frontier. The desire to revolutionize our understanding of the brain to accelerate the development and application of innovative technologies to treat, cure or even prevent human diseases is every neuroscientist’s dream. It also is the core ambition behind the 2013 White House announcement of the Brain Research through Advancing Innovative Neurotechnologies® (BRAIN) Initiative.
By developing data-driven population decoding approaches, we have clarified how shape, space and cognition are differently represented across brain regions, which can help in better differentiating attention and memory disorders. Further, using computational approaches, we have identified which single-cell characteristics are important for accurate representations — information that could aid in the placement and activation of neural interfaces. For example, we have identified areas best suited for accurate and stable reaches of the hand. Future work in our Purdue lab aims to apply these novel approaches to frontal brain regions, which are critical for managing these higher-level cognitive functions.
Anne Sereno, PhD
Professor, Weldon School of Biomedical Engineering, and Member, Purdue Engineering Initiative in Engineering-Medicine, College of Engineering
Professor, Mathematical & Computational, Neuroscience and Behavior, and Cognitive Psychology, Department of Psychological Sciences, College of Health and Human Sciences