of the Human Brain
Aims: The human brain is highly complex and is composed of many interconnected regions. The interconnected nature poses great challenges for studying brain function. In essence, the activation of a brain region in a cognitive task is driven by all regions that this region connects with, and it is difficult to tell which ones of these regions, or all of them, are responsible for this cognitive task. Thus, looking at brain activity alone is not enough for understanding brain function. We take a different approach, looking at what enables different brain regions to have different functions at first place - their structural differences. We study how different brain regions differ structurally and how their structural differences underpin their functional differences.
Progress: Our research reveals a systematic structural difference between sensory cortices and prefrontal cortex. We found that sensory cortices have topographically ordered wiring, high information capacity, but low flexibility; by contrast, frontal cortex has random wiring, low information capacity, but high flexibility. These structural differences match their functional differences: the high information capacity of sensory cortices is well suited for uni-sensory processing and multisensory integration, whereas the high flexibility of prefrontal cortex is well suited for executive control. Our research also reveals a reverse correlation between the sizes of sensory cortices and prefrontal cortex. We found that individuals with larger sensory cortices have smaller prefrontal cortex, and vice versa. This structural trade-off challenges the traditional view that the sizes of different brain regions simply scale with the overall brain size, and hints towards a functional trade-off between low-level sensory domains and high-level cognitive domains.
Aims: Mirroring the brain complexity, human behavior and consciousness are highly complex. The complexity is present not only in high-level cognitive domains such as introspection, planning, reasoning, but also in low-level sensory domains. For example, our perception of an image is rarely a truthful reflection of the physical features of the image, but is instead biased by the contexts of the image and by our experience or expectation. How does behavioral complexity arise from brain complexity? Research on brain-behavior relations often focuses on the similarity across individuals in brain and behavior. We instead take the opposite approach, studying how different individuals differ in their brain structure and how the inter-individual differences in brain structure give rise to the inter-individual differences in behavior and consciousness.
Progress: Our research reveals that a behaviorally advantageous visual cortex has the structure of a large surface area but a small thickness. We found that individuals with a larger visual cortical surface area can discriminate finer visual details and experience weaker visual illusions; by contrast, a thicker visual cortex is associated with poorer vision. Importantly, the impacts of brain structure on visual perception are mirrored in neural function. We found that neurons in visual cortex with a larger surface area have higher selectivity and more precise coding, whereas the opposite holds for neurons at thicker parts of the visual cortex. Our findings challenge the traditional view that a larger brain volume, whether coming from a larger cortical surface area or a larger cortical thickness, is functionally advantageous. To explain our findings, we built a computational model of visual cortex. The model suggests that enlarging the cortical surface area would increase the number of cortical units, whereas shortening the cortical thickness would decrease the processing delays within cortical units; either way, the structure would support higher functionality. The model predicts inter-individual correlations between visual perception and intrinsic connectivity, oscillation frequency, neurotransmitter level of visual cortex, which we all tested and confirmed.
From Brain Complexity
to Behavioral Complexity
Brain and Behavioral
Learning and Sleep
Aims: A remarkable feature of human brain and behavior is their adaptability and plasticity, or as Darwin put it, "survival of the fittest". The environmental inputs we receive while awake can induce changes in brain structure and function, via which we learn and adapt. Even when we are asleep and disconnected from the environment, the brain is still highly active, and the sleeping brain activity can induce brain structural changes. Research on brain plasticity often focuses on the net changes across the sleep-wake cycle. We instead study if different mechanisms of brain plasticity may be at play during wake versus sleep, and if the contrast between wake and sleep in brain plasticity may hold key to our behavioral plasticity and our ability to constantly learn.
Progress: We are currently testing how the brain structure and function change across the sleep-wake cycle, and whether these brain changes can account for the declines in behavioral performances with the time awake and the improvements in behavioral performances after sleep. While awake, the brain is driven by environmental inputs, which often induce activities incongruent with the brain's own wiring diagram. By contrast, during sleep, the brain is driven by itself, and its activity is congruent with its wiring diagram. We hypothesize that the environmental-driven nature of brain activity while awake may add noise to the brain's wiring and impair its efficiency, whereas the self-driven nature of brain activity while asleep may help to reinstate the wiring efficiency. We are also testing how learning and sleep interact to change brain structure and function. We hypothesize that, if the learning improves the brain’s wiring efficiency, it is ecologically beneficial and will get consolidated after sleep, and if not, it will be weakened by sleep.