Brain dynamics

This four-day workshop combines whole-brain modelling, machine learning and high-order interaction analysis to study human neuroimaging data beyond pairwise descriptions. Through reproducible Python workflows, participants combine theory-driven simulations with multivariate descriptors of collective brain dynamics to capture individual variability, explore brain health and support more mechanistic analyses of M/EEG and fMRI data. Opening lectures by Rodrigo Cofré on whole-brain models and high-order interactions, Kaichao Wu on modelling brain criticality in health and disease, Yonatan Sanz Per

…Study distributed brain dynamics and adaptive behaviour using recordings from thousands of neurons across multiple regions.

…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 Conscious

The spatio-temporal structure of brain dynamics at the macroscopic level has been hypothesized to reflect neuronal communication for cognitive processes. In particular, recent studies have focused on time-irreversibility and its relationship with consciousness [1,2]. Beyond this example of high-level cognitive function, this raises the question of the role of different ingredients that shape the structure-function relationship in whole-brain dynamics, which can be formalized using the Ornstein-Uhlenbeck (OU) process that combines input “noise” and effective connectivity as key ingredients. Her

White matter (WM) tracts shape the brain’s dynamical activity, and their damage (e.g., disconnections) results in functional alterations and cognitive symptoms [1]. Here, we use neural mass modeling to test the in-vivo effects of WM disconnections [2]. We create models of local versus global, and edge versus nodal effects of WM disconnections in a large fMRI dataset comprising individuals affected by varying degrees of white matter hyperintensities (WMH), in order to estimate the impact of WMH on brain dynamics in a data-driven manner. We use a virtual-lesioning (disconnectome [3]) approach in

…analysis to find alterations in brain dynamics related to prodromal dementia with Lewy bodies (MCI-LB).We used resting state fMRI data (TR=0.98s, 580 scans) of 30 participants with MCI-LB (age 68.5 ± 6.0, 16 women) and 55 healthy controls (HC; age 67.7 ± 6.4, 33 women). The participants underwent neuropsychological examination and MRI measurement at Masaryk University in Brno (CZ). Inclusion in MCI-LB group was based on MCI-LB diagnostic criteria. Preprocessed fMRI data were analysed with Coactivation patten analysis. We anal

…from the much richer repertoire of brain activity [1].In order to address this limitation, we studied the capacity to break the isotropy in connectivity and enrich dynamics by modulating the spatial arrangement of neurons in the substrate they grow. Specifically, we cultured neurons on polydimethylsiloxa

How the brain responds to non-invasive brain stimulation, such as transcranial magnetic stimulation (TMS), depends on the physiological state. In recent years, we have come to understand what happens at the stimulation site, but the whole-brain response remains unclear. Here, we consider the brain as an autonomous control system and stimuli as control inputs, and use the framework of control theory to describe the whole-brain response to brain stimuli. Our method, based on the so-called controllability gramian, can reveal not only the average controllability, i.e. how easily the brain dynamics

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 r

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 bel

Psychotic disorders are characterized by heterogeneity in etiopathology, clinical presentation and individual trajectory, complicating diagnosis and treatment. Despite the increasing amount of studies investigating significant alterations, the mechanisms underlying the emergence and progression of these disorders remains unclear. It is therefore fundamental to improve our ability to differentiate between clinical subgroups and to move towards a more personalised approach. Here, we aim to highlight critical neural correlates in early stages of psychosis, and to identify relevant biomarkers corr

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

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

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.