Faculty Bibliography

Brain activity observed at many spatiotemporal scales exhibits a 1/f-like power spectrum, including neuronal membrane potentials, neural field potentials, noninvasive electroencephalography (EEG), magnetoencephalography (MEG), and functional magnetic resonance imaging (fMRI) signals. A 1/f-like power spectrum is indicative of arrhythmic brain activity that does not contain a predominant temporal scale (hence, 'scale-free'). This characteristic of scale-free brain activity distinguishes it from brain oscillations. Although scale-free brain activity and brain oscillations coexist, our understanding of the former remains limited. Recent research has shed light on the spatiotemporal organization, functional significance, and potential generative mechanisms of scale-free brain activity, as well as its developmental and clinical relevance. A deeper understanding of this prevalent brain signal should provide new insights into, and analytical tools for, cognitive neuroscience.

Studies employing functional connectivity-type analyses have established that spontaneous fluctuations in functional magnetic resonance imaging (fMRI) signals are organized within large-scale brain networks. Meanwhile, fMRI signals have been shown to exhibit 1/f-type power spectra - a hallmark of scale-free dynamics. We studied the interplay between functional connectivity and scale-free dynamics in fMRI signals, utilizing the fractal connectivity framework - a multivariate extension of the univariate fractional Gaussian noise model, which relies on a wavelet formulation for robust parameter estimation. We applied this framework to fMRI data acquired from healthy young adults at rest and while performing a visual detection task. First, we found that scale-invariance existed beyond univariate dynamics, being present also in bivariate cross-temporal dynamics. Second, we observed that frequencies within the scale-free range do not contribute evenly to inter-regional connectivity, with a systematically stronger contribution of the lowest frequencies, both at rest and during task. Third, in addition to a decrease of the Hurst exponent and inter-regional correlations, task performance modified cross-temporal dynamics, inducing a larger contribution of the highest frequencies within the scale-free range to global correlation. Lastly, we found that across individuals, a weaker task modulation of the frequency contribution to inter-regional connectivity was associated with better task performance manifesting as shorter and less variable reaction times. These findings bring together two related fields that have hitherto been studied separately - resting-state networks and scale-free dynamics, and show that scale-free dynamics of human brain activity manifest in cross-regional interactions as well.

Despite intense recent research, the neural correlates of conscious visual perception remain elusive. The most established paradigm for studying brain mechanisms underlying conscious perception is to keep the physical sensory inputs constant and identify brain activities that correlate with the changing content of conscious awareness. However, such a contrast based on conscious content alone would not only reveal brain activities directly contributing to conscious perception, but also include brain activities that precede or follow it. To address this issue, we devised a paradigm whereby we collected, trial-by-trial, measures of objective performance, subjective awareness, and the confidence level of subjective awareness. Using magnetoencephalography recordings in healthy human volunteers, we dissociated brain activities underlying these different cognitive phenomena. Our results provide strong evidence that widely distributed slow cortical potentials (SCPs) correlate with subjective awareness, even after the effects of objective performance and confidence were both removed. The SCP correlate of conscious perception manifests strongly in its waveform, phase, and power. In contrast, objective performance and confidence were both contributed by relatively transient brain activity. These results shed new light on the brain mechanisms of conscious, unconscious, and metacognitive processing.

What neural mechanisms underlie the seamless flow of our waking consciousness? A necessary albeit insufficient condition for such neural mechanisms is that they should be consistently modulated across time were a segment of the conscious stream to be repeated twice. In this study, we experimentally manipulated the content of a story followed by subjects during functional magnetic resonance imaging (fMRI) independently from the modality of sensory input (as visual text or auditory speech) as well as attentional focus. We then extracted brain activity patterns consistently modulated across subjects by the evolving content of the story regardless of whether it was presented visually or auditorily. Specifically, in one experiment we presented the same story to different subjects via either auditory or visual modality. In a second experiment, we presented two different stories simultaneously, one auditorily, one visually, and manipulated the subjects' attentional focus. This experimental design allowed us to dissociate brain activities underlying modality-specific sensory processing from modality-independent story processing. We uncovered a network of brain regions consistently modulated by the evolving content of a story regardless of the sensory modality used for stimulus input, including the superior temporal sulcus/gyrus (STS/STG), the inferior frontal gyrus (IFG), the posterior cingulate cortex (PCC), the medial frontal cortex (MFC), the temporal pole (TP), and the temporoparietal junction (TPJ). Many of these regions have previously been implicated in semantic processing. Interestingly, different stories elicited similar brain activity patterns, but with subtle differences potentially attributable to varying degrees of emotional valence and self-relevance.

When faced with ambiguous sensory inputs, subjective perception alternates between the different interpretations in a stochastic manner. Such multistable perception phenomena have intrigued scientists and laymen alike for over a century. Despite rigorous investigations, the underlying mechanisms of multistable perception remain elusive. Recent studies using multivariate pattern analysis revealed that activity patterns in posterior visual areas correlate with fluctuating percepts. However, increasing evidence suggests that vision--and perception at large--is an active inferential process involving hierarchical brain systems. We applied searchlight multivariate pattern analysis to functional magnetic resonance imaging signals across the human brain to decode perceptual content during bistable perception and simple unambiguous perception. Although perceptually reflective activity patterns during simple perception localized predominantly to posterior visual regions, bistable perception involved additionally many higher-order frontoparietal and temporal regions. Moreover, compared with simple perception, both top-down and bottom-up influences were dramatically enhanced during bistable perception. We further studied the intermittent presentation of ambiguous images--a condition that is known to elicit perceptual memory. Compared with continuous presentation, intermittent presentation recruited even more higher-order regions and was accompanied by further strengthened top-down influences but relatively weakened bottom-up influences. Taken together, these results strongly support an active top-down inferential process in perception.

A widely held assumption is that spontaneous and task-evoked brain activity sum linearly, such that the recorded brain response in each single trial is the algebraic sum of the constantly changing ongoing activity and the stereotypical evoked activity. Using functional magnetic resonance imaging signals acquired from normal humans, we show that this assumption is invalid. Across widespread cortices, evoked activity interacts negatively with ongoing activity, such that higher prestimulus baseline results in less activation or more deactivation. As a consequence of this negative interaction, trial-to-trial variability of cortical activity decreases following stimulus onset. We further show that variability reduction follows overlapping but distinct spatial pattern from that of task-activation/deactivation and it contains behaviorally relevant information. These results favor an alternative perspective to the traditional dichotomous framework of ongoing and evoked activity. That is, to view the brain as a nonlinear dynamical system whose trajectory is tighter when performing a task. Further, incoming sensory stimuli modulate the brain's activity in a manner that depends on its initial state. We propose that across-trial variability may provide a new approach to brain mapping in the context of cognitive experiments.