Topic: functional connectivity

Functional connectivity has been the focus of many research groups aiming to study the interaction between cells and brain regions. A standard method for analyzing connectivity is to statistically compare pairwise interactions between cells or brain regions across behavioral states or conditions. This methodology ignores the intrinsic properties of functional connectivity as a multivariate and dynamic signal, expressing the correlational configuration of the network. In this talk, I will present a geometric approach, combining Graph Theory and Riemannian Geometry to build "a graph of graphs" a

While anatomical connectivity changes slowly through synaptic learning, the functional connectivity of neurons changes rapidly with ongoing activity of neurons and their functional interactions. Functional networks of neurons and neural populations reflect how their interactions change with behaviors, stimulus types, and internal states. Therefore, the information propagation across a network can be analyzed through the varying topological properties of the functional networks. Our study investigates the functional networks of the visual cortex at both the single-cell and population levels. Ou

Electroencephalography (EEG) has been thoroughly studied for decades in psychiatry research. Yet its integration into clinical practice as a diagnostic/prognostic tool remains unachieved. We hypothesize that a key reason is the underlying patient's heterogeneity, overlooked in psychiatric EEG research relying on a case-control approach. We combine HD-EEG with normative modeling to quantify this heterogeneity using two well-established and extensively investigated EEG characteristics -spectral power and functional connectivity- across a cohort of 1674 patients with attention-deficit/hyperacti

Sex hormones are powerful neuromodulators of learning and memory. In rodents and nonhuman primates estrogen and progesterone influence the central nervous system across a range of spatiotemporal scales. Yet, their influence on the structural and functional architecture of the human brain is largely unknown. Here, I highlight findings from a series of dense-sampling neuroimaging studies from my laboratory designed to probe the dynamic interplay between the nervous and endocrine systems. Individuals underwent brain imaging and venipuncture every 12-24 hours for 30 consecutive days. These procedu

Hemispheric asymmetry in functional connectivity of the orbitofrontal cortex (OFC) has been recently demonstrated in reward-related cognitive tasks like gambling. In this work, which was part of our Neuromatch Academy 2022 project, we used resting state and task-dependent fMRI data from 339 human subjects from the Human Connectome Project (HCP 2020) to quantify the asymmetry of functional connectivity between left and right OFC, and posterior OFC (pOFC) regions during rest and task blocks. We then aimed to relate this asymmetry index (AI) to reward-driven impulsivity traits, quantified by subj

The understanding of the stroke lesions’ consequences is limited, and it relies mostly on behavioral reports and mere descriptive correlational information from neuroimaging techniques. Using functional magnetic resonance imaging, it has been shown that the functional synchronization between distinct regions of the brain, referred to as functional connectivity, is disrupted by stroke. Nevertheless, this kind of data is usually large and high-dimensional. Extracting useful information from the vast amount of information afforded by brain networks remains a great challenge so, in order to make s

Which genes contribute to making the human brain capable of language? We analyzed resting state fMRI and genetic single nucleotide polymorphism data of 30,660 people in the UK biobank and found 15 regions in the human DNA that relate to the brain language network. We link two genomic regions on chromosome 3 (EPHA3 and TBC1D5) to left-right differences in that network. All implicated genes tend to be more expressed during prenatal development. Therefore some genetic influences likely affect language network functional connectivity in the embryo and the fetus.

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

INTRODUCTION Graph theory is a state of the art approach to assess functional connectivity (FC) disruption in neurological disorders. However, this methodology does not allow distinction between positive and negative FC correlations; negative correlations, or anticorrelations, are usually either discardes or taken as positive values, and therefore its influence is rarely studied. RESEARCH QUESTION In the present study, we used magnetoencephalography (MEG) to construct cross-frequency networks, and studied the positive and negative correlations independently and jointly, to evaluate the contri

Resting-state functional magnetic resonance imaging (MRI) has yielded seemingly disparate insights into large-scale organization of the human brain. The brain’s large-scale organization can be divided into two broad categories: zero-lag representations of functional connectivity structure and time-lag representations of traveling wave or propagation structure. In this study, we sought to unify observed phenomena across these two categories in the form of three low-frequency spatiotemporal patterns composed of a mixture of standing and traveling wave dynamics. We showed that a range of empirica

The ability to effectively regulate emotions is a fundamental skill related to physical and psychological health. In this talk, I will present behavioral and fMRI data from several different studies that examined cognitive reappraisal, acceptance, and suppression emotion regulation strategies in healthy controls participants and in the context of randomized trials of cognitive behavioral therapy, mindfulness- based stress reduction, and aerobic exercise as interventions for adults with anxiety disorders. We will also examine the implementation of different types of functional connectivity anal

This talk will focus on the generative modelling of resting state time series or endogenous neuronal activity. I will survey developments in modelling distributed neuronal fluctuations – spectral dynamic causal modelling (DCM) for functional MRI – and how this modelling rests upon functional connectivity. The dynamics of brain connectivity has recently attracted a lot of attention among brain mappers. I will also show a novel method to identify dynamic effective connectivity using spectral DCM. Further, I will summarise the development of the next generation of DCMs towards large-scale, whole-

A major challenge of cognitive neuroscience is to understand how the brain as a network gives rise to our cognition. Simultaneous [18F]-fluorodeoxyglucose positron emission tomography functional magnetic resonance imaging (FDG-PET/fMRI) provides the opportunity to investigate brain connectivity not only via spatially distant, synchronous cerebrovascular hemodynamic responses (functional connectivity), but also glucose metabolism (metabolic connectivity). However, how these two modalities of brain connectivity differ in their relation to cognition is unknown. In this webinar, Dr Katharina Voi

While time-averaged dynamics of brain functional connectivity are known to reflect the underlying structural connections, the exact relationship between large-scale function and structure remains an unsolved issue in network neuroscience. Large-scale networks are traditionally observed by correlation of fMRI timecourses, and connectivity of source-reconstructed electrophysiological measures are less prominent. Accessing the brain by using multimodal recordings combining EEG, fMRI and diffusion MRI (dMRI) can help to refine the understanding of the spatio-temporal organization of both static an

Cross-sectional and longitudinal multimodal brain imaging studies using positron emission tomography (PET) and magnetic resonance imaging (MRI) have provided detailed insight into the pathophysiological progression of Alzheimer’s disease. It starts at an asymptomatic stage with widespread gradual accumulation of beta-amyloid and spread of pathological tau deposits. Subsequently changes of functional connectivity and glucose metabolism associated with mild cognitive impairment and brain atrophy may develop. However, the rate of progression to a symptomatic stage and ultimately dementia varies c

During histogenesis of the cerebral cortex, a proper laminar placement of defined numbers of specific cellular types is necessary to ensure proper functional connectivity patterns. There is a wide range of cortical malformations causing epilepsy and intellectual disability in humans, characterized with various degrees of neuronal misplacement, aberrant circuit organization or abnormal folding patterns. Although progress in human neurogenetics and brain imaging techniques have considerably advanced the identification of their causative genes, the pathophysiological mechanisms associated with de

Neuronal cultures and human stem-cell-derived organoids are fundamental building blocks of neuroscientific research and future personalized medicine. However, in-vitro networks show considerably more synchronous bursting activity than networks in-vivo [1]. One leading theory proposes that under a lack of external input, maladapted network’s plasticity leads to a pathological collective activity pattern: long periods of quiescence are interspersed with bursts of strong, synchronous activity [2, 3]. In theoretical simulations, weak external input can reduce this bursting behavior. However, expe

All-optical techniques play a pivotal role in the direct interrogation of biological neural networks and the investigation of their computational properties. Such techniques combine spatiotemporally precise optogenetic stimulation at cellular resolution to manipulate neuronal states in the network with optical imaging of fluorescent genetically-encoded indicators for simultaneous readout of neuronal activity [1, 2]. The biophysical models of various optogenetic tools have been studied computationally in single neurons, accurately fitting experimental data [3, 4]. However, the effects of optoge

Driving is a complex task that requires effective neural processing and coordination, which typically degrade with age. Previous studies suggest that age-related differences in cognitive and motor functions might influence driving performance. Herein, we investigated age-related differences in neural responses to reactive and proactive driving conditions using blink-related potentials [1]-[3] and source-level functional connectivity analyses based on amplitude envelope correlation [4]. Seventy-six subjects participated in the two separate driving experiments including reactive (19 young, 28 ol

Brain activity lies on a very complex network. This complexity is multiple but a prominent one is the non-linear and multi-factorial interaction between its nodes. In the specific case of Parkinson's disease (PD), the brain loses dopaminergic neurons in the substantia nigra compacta (SNc). Highly involved in the basal ganglia-cortex-thalamus-cerebellum (BG-Ctx-T-Cb) network, the main role of dopamine (DA) is in learning, decision-making and motor control, as manifested in the PD symptoms such as rigidity, slowness of movements, tremor and poor behavioural flexibility. Following DA loss, the un

Chronic pain is a serious clinical and scientific problem, affecting 1 in 5 people worldwide, yet its mechanisms and ways to treat it remain poorly understood. Pain is modulated by endogenous pain modulatory pathways that connect the brain to the spinal cord, up- and down-regulating the transmission of nociceptive information. The most important region when such modulation occurs is the Rostral Ventromedial Medulla (Fields et al., 1983; Chen and Heinricher, 2022). Despite extensive work characterising the responses of RVM cells during pharmacological interventions, little is currently known ab

Investigations of transcriptomic and neuroimaging data imply that the spatial patterning of the brain transcriptome follows broad spatial trends in the brain network architecture, which can be used to study the molecular mechanisms of functional connectivity. However, the sophisticated pre-processing and data fusion workflows involved in heteromodal data analysis often require the expertise of computer scientists. There is a need for tools that facilitate this process to enable research without the need for extensive programming knowledge. To address this problem, we present an extension to ou

The coordinated recruitment of neural ensembles is thought to underlie behaviourally relevant information processing in the brain. These ensembles are temporally dynamic with individual neurons flexibly recruited into functional groups. In premotor cortex, intermingled neurons are activated during movement planning and execution but also in response to contextual cues, and reward. However, probing the behavioural role of these ensembles and understanding the circuit mechanisms underlying dynamic ensemble formation has been challenging due to the difficulty of flexibly manipulating individual c