Consciousness at the edge of chaos
Over the last 20 years, neuroimaging and electrophysiology techniques have become central to understanding the mechanisms that accompany loss and recovery of consciousness. Much of this research is performed in the context of healthy individuals with neurotypical brain dynamics. Yet, a true understanding of how consciousness emerges from the joint action of neurons has to account for how severely pathological brains, often showing phenotypes typical of unconsciousness, can nonetheless generate a subjective viewpoint. In this presentation, I will start from the context of Disorders of Consciousness and will discuss recent work aimed at finding generalizable signatures of consciousness that are reliable across a spectrum of brain electrophysiological phenotypes focusing in particular on the notion of edge-of-chaos criticality.
Interacting spiral wave patterns underlie complex brain dynamics and are related to cognitive processing
The large-scale activity of the human brain exhibits rich and complex patterns, but the spatiotemporal dynamics of these patterns and their functional roles in cognition remain unclear. Here by characterizing moment-by-moment fluctuations of human cortical functional magnetic resonance imaging signals, we show that spiral-like, rotational wave patterns (brain spirals) are widespread during both resting and cognitive task states. These brain spirals propagate across the cortex while rotating around their phase singularity centres, giving rise to spatiotemporal activity dynamics with non-stationary features. The properties of these brain spirals, such as their rotational directions and locations, are task relevant and can be used to classify different cognitive tasks. We also demonstrate that multiple, interacting brain spirals are involved in coordinating the correlated activations and de-activations of distributed functional regions; this mechanism enables flexible reconfiguration of task-driven activity flow between bottom-up and top-down directions during cognitive processing. Our findings suggest that brain spirals organize complex spatiotemporal dynamics of the human brain and have functional correlates to cognitive processing.
Off the rails - how pathological patterns of whole brain activity emerge in epileptic seizures
In most brains across the animal kingdom, brain dynamics can enter pathological states that are recognisable as epileptic seizures. Yet usually, brain operate within certain constraints given through neuronal function and synaptic coupling, that will prevent epileptic seizure dynamics from emerging. In this talk, I will bring together different approaches to identifying how networks in the broadest sense shape brain dynamics. Using illustrative examples from intracranial EEG recordings, disorders characterised by molecular disruption of a single neurotransmitter receptor type, to single-cell recordings of whole-brain activity in the larval zebrafish, I will address three key questions - (1) how does the regionally specific composition of synaptic receptors shape ongoing physiological brain activity; (2) how can disruption of this regionally specific balance result in abnormal brain dynamics; and (3) which cellular patterns underly the transition into an epileptic seizure.
Hidden nature of seizures
How seizures emerge from the abnormal dynamics of neural networks within the epileptogenic tissue remains an enigma. Are seizures random events, or do detectable changes in brain dynamics precede them? Are mechanisms of seizure emergence identical at the onset and later stages of epilepsy? Is the risk of seizure occurrence stable, or does it change over time? A myriad of questions about seizure genesis remains to be answered to understand the core principles governing seizure genesis. The last decade has brought unprecedented insights into the complex nature of seizure emergence. It is now believed that seizure onset represents the product of the interactions between the process of a transition to seizure, long-term fluctuations in seizure susceptibility, epileptogenesis, and disease progression. During the lecture, we will review the latest observations about mechanisms of ictogenesis operating at multiple temporal scales. We will show how the latest observations contribute to the formation of a comprehensive theory of seizure genesis, and challenge the traditional perspectives on ictogenesis. Finally, we will discuss how combining conventional approaches with computational modeling, modern techniques of in vivo imaging, and genetic manipulation open prospects for exploration of yet hidden mechanisms of seizure genesis.
GED: A flexible family of versatile methods for hypothesis-driven multivariate decompositions
Does that title put you to sleep or pique your interest? The goal of my presentation is to introduce a powerful yet under-utilized mathematical equation that is surprisingly effective at uncovering spatiotemporal patterns that are embedded in data -- but that might be inaccessible in traditional analysis methods due to low SNR or sparse spatial distribution. If you flunked calculus, then don't worry: the math is really easy, and I'll spend most of the time discussing intuition, simulations, and applications in real data. I will also spend some time in the beginning of the talk providing a bird's-eye-view of the empirical research in my lab, which focuses on mesoscale brain dynamics associated with error monitoring and response competition.
Advances in Computational Psychiatry: Understanding (cognitive) control as a network process
The human brain is a complex organ characterized by heterogeneous patterns of interconnections. Non-invasive imaging techniques now allow for these patterns to be carefully and comprehensively mapped in individual humans, paving the way for a better understanding of how wiring supports cognitive processes. While a large body of work now focuses on descriptive statistics to characterize these wiring patterns, a critical open question lies in how the organization of these networks constrains the potential repertoire of brain dynamics. In this talk, I will describe an approach for understanding how perturbations to brain dynamics propagate through complex wiring patterns, driving the brain into new states of activity. Drawing on a range of disciplinary tools – from graph theory to network control theory and optimization – I will identify control points in brain networks and characterize trajectories of brain activity states following perturbation to those points. Finally, I will describe how these computational tools and approaches can be used to better understand the brain's intrinsic control mechanisms and their alterations in psychiatric conditions.
Brain dynamics underlying memory for continuous natural events
The world confronts our senses with a continuous stream of rapidly changing information. Yet, we experience life as a series of episodes or events, and in memory these pieces seem to become even further organized. How do we recall and give structure to this complex information? Recent studies have begun to examine these questions using naturalistic stimuli and behavior: subjects view audiovisual movies and then freely recount aloud their memories of the events. We find brain activity patterns that are unique to individual episodes, and which reappear during verbal recollection; robust generalization of these patterns across people; and memory effects driven by the structure of links between events in a narrative. These findings construct a picture of how we comprehend and recall real-world events that unfold continuously across time.
Dragons, Sleep, and the Claustrum
The mammalian claustrum, by virtue of its dense interconnectivity with cortex and other brain structures, has been hypothesized to mediate functions ranging from decision making to consciousness. I will be presenting experimental evidence for the existence of a claustrum in reptiles, its role in generating brain dynamics characteristic of sleep, and discuss our neuroetholgical approach towards understanding fundamental aspects of sleep and claustrum function.