What Is the Neural Architecture of Intelligence?

The human brain is home to around 100 billion neurons. That’s roughly the number of stars the Milky Way harbors. Compared to most stars that like to drift through the galaxy by their lonesome selves, our neurons are champion extroverts. They like to make connections; 10^15 of them. Thanks to the miraculous chemical and electrical choreography that our networking neurons stage on any ordinary day, we are able to write love letters, calculate gratuities, and cure diseases.

What is the neural architecture of intelligence?

What is it about the human brain that enables us to perceive information from the world around us, commit it to our memory banks as knowledge, and use it adaptively within various contexts? While scientists and philosophers have rummaged the brain’s all four corners for answers (perhaps it's about brain volume, structure, or different regions), recently the focus has shifted to the way neurons connect and distribute themselves across networks.

Psychologist Aron Barbey studies the neurobiology of intelligence. Using methods from network neuroscience, he explores the brain’s information-processing mechanisms that allow us to represent problems, devise different approaches to solve them, evaluate the consequences of our choices, adapt our strategies, and finally, select the best solutions. After all, as Barbey notes, at the heart of intelligence lies one of the hallmarks of the human mind: our ability to solve problems.

Here is a discussion with Barbey on some of the insights neuroscience research has uncovered about the mysteries of human intelligence.

How does the brain help us find solutions to the diverse problems we encounter in life?

Source: 17959117/Pixabay/CC0

Intuitively, we often think of human intelligence with respect to specific cognitive skills and abilities. Logical reasoning or mathematical problem solving often come to mind. In the scientific study of intelligence, we refer to a specific concept developed in the early 1900s by Charles Spearman called general intelligence. General intelligence is essentially our problem-solving aptitude—our capacity to find solutions to the diverse problems we encounter in life. Rather than referring to a specific type of problem or approach to problem-solving, general intelligence captures our ability to find adaptive solutions to all types of problems. And this is why general intelligence is so powerful and important as an area of scientific inquiry. Understanding the nature and mechanisms of general intelligence would prepare us to apply this solution to solve many more challenging life problems—through the design of smarter AI, better educational programs, more effective treatments for neurological disease, psychiatric illness, and so on. The stakes are high and the impact is far-reaching.

Is brain plasticity central to general intelligence?

The capacity for flexible, intelligent behavior is made possible by the brain’s remarkable capacity to reconfigure itself—to continually update prior knowledge on the basis of new information and to actively generate internal predictions that guide adaptive behavior and decision making. Contemporary research conceives of the brain as a dynamic and active inference generator that anticipates incoming sensory inputs, forming hypotheses about that world that can be tested against sensory signals that arrive in the brain. Plasticity is therefore critical for the emergence of human intelligence; it provides a powerful mechanism for updating prior beliefs, generating dynamic predictions about the world, and adapting in response to ongoing changes in the environment.

Tell us about core facets of problem-solving, crystallized and fluid intelligence.

Crystallized intelligence is the capacity to solve problems that depend on our prior knowledge and experience. We apply crystallized intelligence when we encounter familiar problems and when we engage brain networks that automatically recognize and are configured to solve these problems.

In contrast, fluid intelligence refers to adaptive reasoning and problem-solving skills. We apply fluid intelligence to solve novel problems that we haven’t encountered before, that is when we can’t rely directly on our prior knowledge and experience. Thus, fluid intelligence requires that brain networks find adaptive solutions through flexible and dynamic information processing.

Both crystallized and fluid intelligence, and their origins in the network architecture of the human brain, contribute to general intelligence.

What is the network neuroscience theory of intelligence?

We have developed a Network Neuroscience Theory of general intelligence that is based on these ideas. According to the theory, general intelligence reflects individual differences in the efficiency and flexibility of brain networks. The human brain is designed for efficiency, to minimize the cost of information processing while maximizing the capacity for growth and adaptation. Accumulating evidence indicates that general intelligence is associated with global efficiency, the capacity to integrate information across the brain as a whole.

Flexibility is afforded by brain plasticity. Network flexibility is shaped by the structural and functional organization of the brain, which may facilitate or constrain the transition of a network from one state to another. For example, transitioning to an easy-to-reach state requires a short, direct path, whereas transitioning to a difficult-to-reach state requires a long, winding path.

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Neuron anatomy

Source: geralt/Pixabay/CC0

The network neuroscience theory proposes that crystallized intelligence engages highly accessible representations of prior knowledge and experience and relies on easy-to-reach network states. In contrast, fluid intelligence reflects the capacity to solve novel problems and to demonstrate adaptive, flexible behavior. Fluid intelligence, therefore, engages networks that can transition to difficult-to-reach, highly flexible states. Thus, rather than attribute intelligence to a fixed set of brain regions or networks, this perspective is based on the dynamic reorganization of brain networks and proposes that intelligence is grounded in brain plasticity.

Our goal is to advance research and theory on the neurobiology of human intelligence by incorporating evidence from network neuroscience on the global topology and dynamics of the human brain.

Does intelligence reside in one particular region or network of the brain?

Historically, neuroscientists have focused on understanding the functional role of specific brain regions, proposing that general intelligence originates from a particular region, such as the dorsolateral prefrontal cortex, or, in more recent work, engages a primary brain network, such as the frontoparietal network.

But what we are increasingly realizing is that general intelligence cannot be localized to a specific brain region or network. Instead, the brain appears to enable general intelligence through large-scale network interactions and system-wide mechanisms for efficient and flexible information processing. Thus, by focusing on specific brain regions or networks, we may have missed the forest for the trees, failing to see the higher-order structure and large-scale network topology from which general intelligence emerges.

Is general intelligence trainable?

While this is an area of active research and debate, it doesn’t appear that it’s possible to significantly enhance general intelligence. However, it’s certainly possible to improve specific cognitive abilities through practice and to hone our problem-solving skills through education. In principle, if we could teach people not only how to solve specific problems in particular contexts, but to productively apply that knowledge to new situations, then this could facilitate the transfer of training and perhaps engender improvements in broader facets of intelligence. By understanding how specific skills are related to broader abilities and by studying global, system-wide brain network function, modern research promises new advances in the continued effort to achieve a deeper understanding of human intelligence and to one day improve it.

Many thanks to Aron Barbey for his time and insights. Dr. Barbey is a Professor of Psychology, Neuroscience, and Bioengineering at the University of Illinois at Urbana-Champaign. He is chair of the Intelligent Systems Major Research Theme, leader of the Intelligence, Learning, and Plasticity Initiative, and director of the Decision Neuroscience Laboratory at the Beckman Institute for Advanced Science and Technology.