Scientists at the École Polytechnique Fédérale de Lausanne (EPFL) and collaborators compared human brain communication networks with those of macaques and mice and found that only the human brains transmitted information via multiple parallel pathways.
The researchers said their study “Evidence for increased parallel information transmission in human brain networks compared to macaques and male mice,” published in Nature Communications, not only provided new insights into mammalian evolution but also could potentially play a role in neurorehabilitation after brain injury, or in the prevention of cognitive decline in pathologies of advanced age.
“Some people age healthily, while others experience cognitive decline, so we’d like to see if there is a relationship between this difference and the presence of parallel information streams, and whether they could be trained to compensate neurodegenerative processes,” said Alessandra Griffa, PhD, senior postdoctoral researcher.
When describing brain communication networks, Griffa likes to use travel metaphors. Brain signals are sent from a source to a target, establishing a polysynaptic pathway that intersects multiple brain regions “like a road with many stops along the way.”
She explains that structural brain connectivity pathways have already been observed based on networks (“roads”) of neuronal fibers. But as a scientist in the medical image processing lab (MIP:Lab) in EPFL’s school of engineering, and a research coordinator at Lausanne University Hospital’s (CHUV) Leenaards Memory Centre, Griffa wanted to follow patterns of information transmission to see how messages are sent and received. She and her colleagues created “brain traffic maps” that could be compared between humans and other mammals.
Reconstructing the brain road maps
To achieve this, the researchers used open-source diffusion (DWI) and functional magnetic resonance imaging (fMRI) data from humans, macaques, and mice, which was gathered while subjects were awake and at rest. The DWI scans allowed the scientists to reconstruct the brain “road maps,” and the fMRI scans allowed them to see different brain regions light up along each “road,” which indicated that these pathways were relaying neural information.
They analyzed the multimodal MRI data using information and graph theory, and Griffa says that it is this novel combination of methods that yielded fresh insights.
“By applying a graph- and information-theory approach to assess information-related pathways in male mouse, macaque, and human brains, we show a brain communication gap between selective information transmission in non-human mammals, where brain regions share information through single polysynaptic pathways, and parallel information transmission in humans, where regions share information through multiple parallel pathways,” wrote the investigators.
“In humans, parallel transmission acts as a major connector between unimodal and transmodal systems. The layout of information-related pathways is unique to individuals across different mammalian species, pointing at the individual-level specificity of information routing architecture. Our work provides evidence that different communication patterns are tied to the evolution of mammalian brain networks.”
“What’s new in our study is the use of multimodal data in a single model combining two branches of mathematics: graph theory, which describes the polysynaptic ‘roadmaps,’ and information theory, which maps information transmission (or ‘traffic’) via the roads,” explained Griffa. The basic principle is that messages passed from a source to a target remain unchanged or are further degraded at each stop along the road, like the telephone game we played as children.”
The researchers’ approach revealed that in the non-human brains, information was sent along a single “road,” while in humans, there were multiple parallel pathways between the same source and target. Furthermore, these parallel pathways were as unique as fingerprints, and could be used to identify individuals.
“Such parallel processing in human brains has been hypothesized, but never observed before at a whole-brain level,” added Griffa.
Griffa explained that the beauty of the model is its simplicity, and its generating new perspectives and research avenues in evolution and computational neuroscience. For example, the findings can be linked to the expansion of human brain volume over time, which has given rise to more complex connectivity patterns.
“We could hypothesize that these parallel information streams allow for multiple representations of reality, and the ability to perform abstract functions specific to humans,” she pointed out.
Although this hypothesis is only speculative, as the study involved no testing of subjects’ computational or cognitive ability, these are questions that Griffa would like to explore in the future.