Learning and memory go hand-in-hand. When a baby learns how to crawl, she understands that she can get somewhere faster. When she learns that applesauce tastes good, she is recalling something she learned from the memory of its pleasant taste. For psychology and biology Professor Kari Hoffman, a researcher in York’s Centre for Vision Research and in the Faculty of Health, the neuroscience behind how a baby learns that crawling is a faster way to get to the applesauce, is a source of never-ending fascination.
Left: Kari Hoffman with a computer graphic showing parallel recordings of a host of neurons
The simple yet perplexing question of how we learn is at the heart of Hoffman’s research. From a baby to an adult, learning is a lifelong challenge and process for our brains, says Hoffman. She is investigating not only how we learn, but also how neurons actually work when we learn.
Plumbing the depths of how our brains learn has taken Hoffman to many different areas. "What kinds of things do we learn about? That question has led me into areas of social psychology and looking at how we process faces and the social cues generated in our behaviours," she says. "It turns out that our brain is very interested in processing this kind of signal and it is also something that we are very good at and that fact is true across a number of species.
"Another area that this question pulls me toward is the plasticity in our brain and neuroscience," says Hoffman. "When you take neurons and their connections to each other, how are they modified over time so that later on, after you’ve had an experience [applesauce tastes good], you might remember how to do something better because you’ve had that experience [crawling is a faster way to get to applesauce]."
Her quest has also taken her into the realm of sleep research. She is interested in what happens to our memories when we sleep. Many of us regard sleep as a time when our brains shut down, when we rest and recharge. Hoffman says that the opposite is true. For decades, researchers have shown there is no blank or down period for our brains and that in fact neurons in our brain have a particular pattern of firing during sleep and replaying what we’ve learned during the day. "Research shows that our memories improve and become more robust to interference during sleep. It’s more difficult to forget a memory if there has been this consolidation period," says Hoffman.
The real world implications of her research are many, says Hoffman. While researchers know so much about learning, there are gaps in our understanding of what neurons are doing while learning is underway. Neurons in our brain never turn off, says Hoffman. They are always changing and their patterns of activity cluster in response to stimuli. "They come and go, and ebb and flow," she says. Past research has taken a static approach, where something is either evident or it is not. However, says Hoffman, one of the clear things neuroscientists are coming to understand is that the dynamic activity exhibited by neurons may be key to our success or failure at doing certain things.
Understanding how the brain synchronizes information and stimuli has already shown great inroads into figuring out how epilepsy takes place, says Hoffman. “Epilepsy is a pretty clear example of where the dynamics of brain synchronization are important. There are also other disorders out there where it appears that the timing of responses – again involving the dynamics of the brain – can be implicated; from autistic children who have difficulty integrating things in time, to attention deficit hyperactivity disorder and even at subclinical levels in our daily lives.
“Why is it that we fatigue when we do from a cram session? We can all recall thinking ‘I have to take a break’ when we engage in long bouts of learning something new. We have an intuitive sense that we need to do such things as taking a break and researchers can directly quantify the memory improvements when we take those breaks," says Hoffman. "But what is actually going on with the neurons to enable us to learn more – and better – by taking breaks, in conjunction with focused learning periods?"
Mapping brain activity
To determine how this process takes place, Hoffman is mapping episodic memories (the memories of unique personal experiences such as events, times, places and the associated emotions). Working out of a state-of-the-art laboratory at York University, Hoffman and a team of seven graduate and undergraduate students work to map neuron activity in the brain during episodic memories. Humans, like many other animals, are very tuned into memories that involve other people or agents and that makes episodic memory favourable for the kind of work Hoffman and her team are pursuing. Most of our recollections involve social situations, says Hoffman. Starting with understanding what behaviours are relevant and looking across species, Hoffman is mapping the electrical activity of neurons during these situations. "You can listen to multiple neurons simultaneously and that ends up being key to understanding how the brain activity is changing in time," she says.
Imagine trying to identify a tune played by an orchestra, but only listening to one instrument. "If it is a solo then you would be lucky, however, if it is one instrument playing one section, it becomes more difficult and you have to listen again and again to different sections to reconstruct the tune. This works if the tune is the same every time you listen, however it falls short if the tune, tempo or song changes." The key to Hoffman’s unique approach is listening to multiple neurons at one time, a technique known as parallel recording. It is through this technique that she can identify when there is a change and by listening to neurons together, she can gain a better picture of the tune or memory being played.
Another aspect of the dynamics that Hoffman is examining is the scale of the neuronal ensemble involved in memory formation. She uses an analogy of a stadium, where if you were outside the stadium, you could make out that a goal had been scored, but wouldn’t hear any particular conversation, so you would miss the details about the game being played. Inside the stadium however, you would only be able to make out the immediate conversations around you and that might not always include the details about the game. As a result, what you would learn would be limited to what you hear in that specific conversation.
"What we see going on in the brain is that there are small and large groups of neurons that form conversations, break apart and re-form new conversations. To understand what the brain is doing, the trick is to examine as many neurons, or audience members, as possible, so that you get a handle on the game being played – not just the goals and not the irrelevant conversations. Determining which conversations are important, you’ll want to get the "group vote", akin to holding a microphone a section and do that for multiple sections. This gives us a microscopic, meso- and macroscopic scale of what is going on in the brain."
By using multiple scales, "we have a much better ability to determine which neurons are involved in forming a particular memory and how the neural conversations change to reflect that learning – whether the change happens across the brain, region by region, or even at the level of specific neurons."
Through these multiple scales, Hoffman says she can then reverse engineer to find out how signals at the smaller scale contribute to the larger scale signal. This reconstruction process is important for improving the performance of medical imaging devices such as EEG and MEG, as well as for reading out neural signals in paralyzed or locked-in individuals using brain-computer interfaces.
Capturing the attention of the research community
Hoffman’s approach has captured the imagination of the research community. Earlier this year, she received a prestigious Sloan Research Fellowship in the field of neuroscience from the Alfred P. Sloan Foundation in the United States. The fellowships are awarded to early-career scientists and scholars of outstanding promise for a period of two years and for Hoffman, in recognition of the potential for her research to make a substantial contribution to the field of neuroscience.
Hoffman was also one of four York researchers to have collectively received $1.24 million in research funding through four grants from the Ontario Research Fund. The grants, which were announced in September, match $1.24 million previously allocated to the research projects through the Canada Foundation for Innovation. She is also the recipient of $100,000 through the Ontario government’s Early Researcher Award program. She has federal support through the Canada Foundation for Innovation and the Natural Sciences & Engineering Research Council of Canada.
Hoffman has a PhD in neuroscience from the University of Arizona. She completed a post-doctoral fellowship at the Max Planck Institute for Biological Cybernetics in Germany. She is currently a member of the Centre for Vision Research and a faculty member in York’s Graduate Diploma in Neuroscience program.
By Jenny Pitt-Clark, YFile editor