US researchers discover neurons that “light up” when humans see images of food
26 Aug 2022 --- When consumers look at specific foods, a specialized part of the visual cortex lights up, according to a recent study by the Massachusetts Institute of Technology (MIT) neuroscientists. This newly discovered population of food-responsive neurons is located in the ventral visual stream, alongside populations that respond specifically to faces, bodies, places and words.
MIT postdoc Meenakshi Khosla is the paper’s lead author, and MIT research scientist N. Apurva Ratan Murty. The study appears in the journal Current Biology.
According to the researchers, these findings may reflect the special significance of food in human culture.
“Food is central to human social interactions and cultural practices. It’s not just sustenance,” says Nancy Kanwisher, Walter A. Rosenblith Professor of Cognitive Neuroscience and a member of MIT’s McGovern Institute for Brain Research and Center for Brains, Minds, and Machines.
“Food is core to so many elements of our cultural identity, religious practice, social interactions, and many other things humans do.”
Tapping into visual categories
While studying the ventral visual stream, the part of the brain that recognizes objects dating more than two decades ago, Kanwisher discovered cortical regions that respond selectively to faces.
According to the researchers, these findings may reflect the special significance of food in human culture.Later, she and her team discovered other regions that respond selectively to places, bodies, or words. Most of those areas were found when researchers expressly set out to look for them. “However, that hypothesis-driven approach can limit what you end up finding,” Kanwisher says.
To uncover the fundamental structure of the ventral visual stream, Kanwisher and Khosla decided to analyze a large, publicly available dataset of full-brain functional magnetic resonance imaging (fMRI) responses from eight human subjects as they viewed thousands of images.
The researchers wanted to see when we apply a data-driven, hypothesis-free strategy, what kinds of selectivities pop up, and whether those are consistent with what had been discovered before. “A second goal was to see if we could discover novel selectivities that either haven’t been hypothesized before or that have remained hidden due to the lower spatial resolution of fMRI data,” Khosla details.
To do that, the researchers applied a mathematical method to discover neural populations that can’t be identified from traditional fMRI data.
An fMRI image comprises many voxels – three-dimensional units representing a cube of brain tissue. Each voxel contains hundreds of thousands of neurons. If some of those neurons belong to smaller populations that respond to one type of visual input, their responses may be drowned out by other populations within the same voxel.
New study methods
The new analytical method can tease neural populations’ responses within each fMRI data voxel. Using this approach, the researchers found four populations corresponding to previously identified clusters that respond to faces, places, bodies and words.
“That tells us that this method works and that the things that we found before are not just obscure properties of that pathway, but major, dominant properties,” Kanwisher explains.
Interestingly, a fifth population also emerged, and this one appeared to be selective for images of food.
“We were quite puzzled by this because food is not a visually homogeneous category,” Khosla underscores. “Things like apples and corn and pasta all look so unlike each other, yet we found a single population that responds similarly to all these diverse food items.”
The food-specific population, which the researchers call the ventral food component (VFC), appears to be spread across two clusters of neurons on either side of the FFA. The fact that the food-specific populations are spread out between other category-specific populations may help explain why they have not been seen before, the researchers state.
“Food selectivity had been harder to characterize before because the populations that are selective for food are intermingled with nearby populations that have distinct responses to other stimulus attributes. The low spatial resolution of fMRI prevents us from seeing this selectivity because the responses of different neural populations get mixed in a voxel,” Khosla further explains.
Experimenting with food and non-food items
In one experiment, the researchers used items that looked very similar – for example, a banana and a yellow crescent moon.
In one experiment, they fed the model-matched images of food and non-food items that looked very similar – for example, a banana and a yellow crescent moon.
“Those matched stimuli have very similar visual properties, but the main attribute in which they differ is edible versus inedible,” Khosla continues. “We could feed those arbitrary stimuli through the predictive model and see whether it would still respond more to food than non-food, without collecting the fMRI data.”
They could also use the computational model to analyze much larger datasets consisting of millions of images. Those simulations helped confirm that the VFC is highly selective for food images.
From their analysis of the human fMRI data, the researchers found that in some subjects, the VFC responded slightly more to processed foods such as pizza than unprocessed foods like apples. In the future, they hope to explore how factors such as familiarity and like or dislike of a particular food might affect individuals’ responses to that food.
Additional questions raised?
Based on an analysis of an extensive public database of human brain responses to a set of 10,000 images, the findings raise many additional questions about how and why this neural population develops.
In future studies, the researchers hope to explore how people’s responses to certain foods might differ depending on their likes and dislikes or their familiarity with certain types of food.
They also hope to study when and how this region becomes specialized during early childhood and what other parts of the brain it communicates with.
Another question is whether this food-selective population will be seen in other animals, such as monkeys, who do not attach the cultural significance to food that humans do.
Edited by Elizabeth Green
