Apr 5, 2019
EPNEC Seminar Room B, Medical Campus
Title: Approaches to Understanding the Function of Intrinsic Activity and its Relationship to Task-evoked Activity in the Human Brain
Traditionally neuroscience research has focused on characterizing the topography and patterns of brain activation evoked by specific cognitive or behavioral tasks to understand human brain functions. This activation-based paradigm treated underlying spontaneous brain activity, a.k.a. intrinsic activity, as noise hence irrelevant to cognitive or behavioral functions. This view, however, has been profoundly modified by the discovery that intrinsic activity is not random, but temporally correlated at rest in widely distributed spatiotemporal patterns, so called resting state networks (RSN). Studies of temporal correlation of spontaneous activity among brain regions, or functional connectivity (FC), have yielded important insights into the network organization of the human brain. However, the underlying fundamental relationship between intrinsic and task-evoked brain activity has remained unclear, becoming an increasingly important topic in neuroscience. An emerging view is that neural activity evoked by a task and the associated behavior is influenced and constrained by intrinsic activity.
Additionally, intrinsic activity may be shaped in the course of development or adult life by neural activity evoked by a task through a Hebbian learning process. This thesis aims to reveal correspondences between intrinsic activity and task-evoked activity to better understand the nature and function of intrinsic brain activity. We measured in human visual cortex the blood oxygen level dependent (BOLD) signal with fMRI to analyze the multivoxel activity patterns and FC structures of intrinsic activity, and compare them to those evoked by natural and synthetic visual stimuli.
In chapter 1, we review previous evidence of an association between intrinsic and task-evoked activity across studies using different experimental methods. Two experimental strategies from the literature were adapted to our own experiments. First, from anesthetized animal studies of intrinsic activity in visual cortex, we set out to measure of macro-scale multi-voxel patterns of spontaneous activity fluctuations as they relate to visually driven patterns of activity (Chapters 2 and 4). Second, from inter-subject correlation studies of visual activity driven by natural stimuli, we adapted studies in Chapter 5.
In Chapter 2 to 4, we establish a multivariate-pattern analysis (MVPA) approach to evaluate patterns of intrinsic and task-evoked activity. The main idea is that patterns of activity induced by behaviorally relevant stimuli over long periods of time would be represented in spontaneous activity patterns within the same areas. To test the idea, in Chapter 2, we compare the overall degree of pattern similarities among frame-wise resting-state activity patterns and visual-stimulus evoked activity patterns for natural and synthetic (phase and position scrambled) object images during low-level detection task. We found that the variability, not mean, of pattern similarity was significantly higher for natural than synthetic stimuli in visual occipital regions that preferred particular stimulus categories. Chapter 3 extends the static categorical pattern similarity measure of Chapter 2 into a temporal correlation measure. We built pattern-based FC matrices in regions that preferred particular stimulus categories. These pattern-based FCs resemble that of resting-state FC of the same regions indicating that resting state patterns are related to category-specific stimulus-evoked multivoxel activity patterns. In Chapter 4, we repeat the analysis used in Chapter 2 with language stimuli. Language stimuli (alphabetic letters and English words) are interesting as they are learned through intensive training as kids learn to read. Therefore, they represent a non-natural category of stimuli that is however highly trained in literate individuals.
The visual stimuli used in Chapter 2 to 4 are designed specifically for a laboratory environment that does not correspond to realistic ecological environments. In Chapter 5, to overcome this limitation, we use the more naturalistic visual experience of movie-watching and compare the whole-brain FC network structure of movie-watching and of resting-state. We show the whole-brain FC structure evoked by movie-watching is partly constrained by the resting network structure.
In conclusion, we demonstrate a link between intrinsic activity and task-evoked activity in terms of multi-vertex activity patterns and FC network structures, supporting the idea of a closed-cycle relationship between task-evoked activity and intrinsic activity in human brain.
Organizer / Host: Dr. Maurizio Corbetta