According to Dr. Joe Tsien, a neuroscientist at the Medical College of Georgia at Augusta University, the brain’s basic computational algorithm is organized by power-of-two-based logic.
According to Dr. Tsien, our brains have a basic algorithm that enables intelligence. Image credit: Geralt / Kun Xie et al / Sci-News.com.
Dr. Tsien is talking about the Theory of Connectivity, a fundamental principle for how our billions of neurons assemble and align not just to acquire knowledge, but to generalize and draw conclusions from it.
“Intelligence is really about dealing with uncertainty and infinite possibilities,” he said.
“It appears to be enabled when a group of similar neurons form a variety of cliques to handle each basic like recognizing food, shelter, friends and foes.”
“Groups of cliques then cluster into functional connectivity motifs (FCMs) to handle every possibility in each of these basics. The more complex the thought, the more cliques join in.”
Dr. Tsien first published his theory in a paper in the Nov. 2015 issue of the journal Trends in Neuroscience.
Now he and his colleagues from Augusta University and the University of Georgia in the United States, and the Yunnan Academy of Science and Technology, Northwestern Polytechnical University and Tsinghua University in China, have documented the algorithm at work in seven different brain regions involved with those basics like food and fear in mice and hamsters.
“In the present study, we systematically tested six predictions made by the Theory of Connectivity. We show that this power-of-two-based permutation logic operated in seven different brain regions and in two animal species during processing appetitive, emotional and social experiences,” the researchers said.
“For it to be a universal principle, it needs to be operating in many neural circuits, so we selected seven different brain regions and, surprisingly, we indeed saw this principle operating in all these regions,” Dr. Tsien explained.
“Intricate organization seems plausible, even essential, in a human brain, which has about 86 billion neurons and where each neuron can have tens of thousands of synapses, putting potential connections and communications between neurons into the trillions.”
“On top of the seemingly endless connections is the reality of the infinite things each of us can presumably experience and learn.”
Researchers have long been curious about how the brain is able to not only hold specific information, like a computer, but — unlike even the most sophisticated technology — to also categorize and generalize the information into abstract knowledge and concepts.
“Many people have long speculated that there has to be a basic design principle from which intelligence originates and the brain evolves, like how the double helix of DNA and genetic codes are universal for every organism,” Dr. Tsien said.
“We present evidence that the brain may operate on an amazingly simple mathematical logic.”
“In my view, he proposes an interesting idea that proposes a simple organizational principle of the brain, and that is supported by intriguing and suggestive evidence,” said Dr. Thomas C. Südhof, Avram Goldstein Professor in the Stanford University School of Medicine, neuroscientist studying synapse formation and function and a winner of the 2013 Nobel Prize in Physiology or Medicine.
“This idea is very much worth testing further,” he added.
At the heart of the Theory of Connectivity is the algorithm, N=2i–1, which defines how many cliques are needed for an FCM and which enabled the authors to predict the number of cliques needed to recognize food options, for example, in their testing of the theory.
“N is the number of neural cliques connected in different possible ways; 2 means the neurons in those cliques are receiving the input or not; i is the information they are receiving; and -1 is just part of the math that enables you to account for all possibilities,” Dr. Tsien said.
To test the theory, the researchers placed electrodes in the areas of the brain so they could ‘listen’ to the response of neurons, or their action potential, and examine the unique waveforms resulting from each.
They gave the animals, for example, different combinations of four different foods, such as usual rodent biscuits as well as sugar pellets, rice and milk, and as the Theory of Connectivity would predict, the scientists could identify all 15 different cliques, or groupings of neurons, that responded to the potential variety of food combinations.
The neuronal cliques appear prewired during brain development because they showed up immediately when the food choices did.
The fundamental mathematical rule even remained largely intact when the NMDA receptor, a master switch for learning and memory, was disabled after the brain matured.
“We also learned that size does mostly matter, because while the human and animal brain both have a six-layered cerebral cortex — the lumpy outer layer of the brain that plays a key role in higher brain functions like learning and memory — the extra longitudinal length of the human cortex provides more room for cliques and FCMs,” Dr. Tsien said.
“And while the overall girth of the elephant brain is definitely larger than the human brain, for example, most of its neurons reside in the cerebellum with far less in their super-sized cerebral cortex.”
“The cerebellum is more involved in muscle coordination, which may help explain the agility of the huge mammal, particularly its trunk.”
The team’s findings were published online Nov. 15 in the journal Frontiers in Systems Neuroscience.
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Kun Xie et al. Brain Computation is Organized via Power-of-Two-Based Permutation Logic. Front. Syst. Neurosci, published online November 15, 2016; doi: 10.3389/fnsys.2016.00095
