Metastable States of Multiscale Brain Networks Are Keys to Crack the Timing Problem

The dynamics of the environment where we live in and the interaction with it, predicting events, provided strong evolutionary pressures for the brain functioning to process temporal information and generate timed responses. As a result, the human brain is able to process temporal information and generate temporal patterns. Despite the clear importance of temporal processing to cognition, learning, communication and sensory, motor and emotional processing, the basal mechanisms of how animals differentiate simple intervals or provide timed responses are still under debate. The lesson we learned from the last decade of research in neuroscience is that functional and structural brain connectivity matter. Specifically, it has been accepted that the organization of the brain in interacting segregated networks enables its function. In this paper we delineate the route to a promising approach for investigating timing mechanisms. We illustrate how novel insight into timing mechanisms can come by investigating brain functioning as a multi-layer dynamical network whose clustered dynamics is bound to report the presence of metastable states. We anticipate that metastable dynamics underlie the real-time coordination necessary for the brain's dynamic functioning associated to time perception. This new point of view will help further clarifying mechanisms of neuropsychiatric disorders

The unbalanced reorganization of weaker functional connections induces the altered brain network topology in schizophrenia

Abstract Network neuroscience shed some light on the functional and structural modifications occurring to the brain associated with the phenomenology of schizophrenia. In particular, resting-state functional networks have helped our understanding of the illness by highlighting the global and local alterations within the cerebral organization. We investigated the robustness of the brain functional architecture in 44 medicated schizophrenic patients and 40 healthy comparators through an advanced network analysis of resting-state functional magnetic resonance imaging data. The networks in patients showed more resistance to disconnection than in healthy controls, with an evident discrepancy between the two groups in the node degree distribution computed along a percolation process. Despite a substantial similarity of the basal functional organization between the two groups, the expected hierarchy of healthy brains' modular organization is crumbled in schizophrenia, showing a peculiar arrangement of the functional connections, characterized by several topologically equivalent backbones. Thus, the manifold nature of the functional organization’s basal scheme, together with its altered hierarchical modularity, may be crucial in the pathogenesis of schizophrenia. This result fits the disconnection hypothesis that describes schizophrenia as a brain disorder characterized by an abnormal functional integration among brain regions

Time discrimination and change detection could share a common brain network: findings of a task-based fMRI study

IntroductionOver the past few years, several studies have described the brain activation pattern related to both time discrimination (TD) and change detection processes. We hypothesize that both processes share a common brain network which may play a significant role in more complex cognitive processes. The main goal of this proof-of-concept study is to describe the pattern of brain activity involved in TD and oddball detection (OD) paradigms, and in processes requiring higher cognitive effort.MethodsWe designed an experimental task, including an auditory test tool to assess TD and OD paradigms, which was conducted under functional magnetic resonance imaging (fMRI) in 14 healthy participants. We added a cognitive control component into both paradigms in our test tool. We used the general linear model (GLM) to analyze the individual fMRI data images and the random effects model for group inference.ResultsWe defined the areas of brain activation related to TD and OD paradigms. We performed a conjunction analysis of contrast TD (task > control) and OD (task > control) patterns, finding both similarities and significant differences between them.DiscussionWe conclude that change detection and other cognitive processes requiring an increase in cognitive effort require participation of overlapping functional and neuroanatomical components, suggesting the presence of a common time and change detection network. This is of particular relevance for future research on normal cognitive functioning in the healthy population, as well as for the study of cognitive impairment and clinical manifestations associated with various neuropsychiatric conditions such as schizophrenia

On the phase synchronization and metastability of neural networks

Orientador: Prof. Dr. Sergio Roberto LopesDissertação (mestrado) - Universidade Federal do Paraná, Setor de Ciências Exatas, Programa de Pós-Graduação em Física. Defesa : Curitiba, 24/02/2021Inclui referências: p.93-104Resumo: Regioes cerebrais e neuronios precisam se comunicar eficientemente e coordenar as suas respectivas atividades. Para conseguir isso, dois fenomenos importantes sao a sincronizacao de fase, relevante para comunicacao neural, e a metastabilidade, relevante para atividade neural. Nessa dissertacao, estudamos ambas em uma rede de neuronios bursting acoplados quimicamente sob uma topologia aleatoria. A temperatura desses neuronios influencia seu modo de disparo, que pode ser bursting ou caotico ou periodico. O bursting caotico leva a uma transicao naomonotonica comum, enquanto o periodico leva a transicoes nao-monotonicas mais incomuns. Em todos os casos, observamos que as diferencas de fase entre neuronios mudam intermitentemente ao longo do tempo, mesmo em redes fortemente sincronizadas em fase. Chamamos esse fenomeno promiscuidade, e o medimos diretamente calculando como os tempos de burst dos neuronios flutuam entre si ao longo do tempo. Entao, agrupando neuronios de acordo com suas fases, exploramos como a promiscuidade afeta a composicao desses clusters, e obtemos detalhes aprofundados sobre a sincronizacao de fase dessa rede. Tambem calculamos duas variabilidades neurais, medindo como os tempos de disparo se dispersam ao longo do tempo ou da rede, e encontramos que os dois possuem valores similares e estao fortemente correlacionados com o grau de sincronizacao de fase da rede para acoplamento fraco. Em seguida, expandimos nosso foco para metastabilidade como vista em neurociencia, considerando promiscuidade um tipo de comportamento metastavel. Nos fazemos uma mini-revisao das diferentes definicoes do termo, e discutimos elas. Com isso, categorizamos brevemente os mecanismos dinamicos levando a metastabilidade. Finalmente, usando o conhecimento obtido no estudo de promiscuidade, investigamos novamente a rede promiscua para discutir como metastabilidade pode diferir dependendo das multiplas escalas do sistema. Palavras-chave: Metastabilidade. Sincronizacao de Fase. Redes Neurais.Abstract: Brain regions and neurons need to communicate effectively and coordinate their respective activities. To manage this, two important phenomena are phase synchronization, relevant for neural communication, and metastability, relevant for neural activity. In this dissertation, we aim to study both in a network of chemically coupled Hodgkin-Huxley-type bursting neurons under a random topology. The temperature of these neurons influences their firing mode, which can be either chaotic or periodic bursting. The firing mode in turn influences the transitions from desynchronization to phase synchronization when neurons are coupled in networks. Chaotic bursting leads to a common monotonic transition, while periodic bursting leads to rarer nonmonotonic transitions. In all these cases, we observe that phase differences between neurons change intermittently throughout time, even in strongly phase-synchronized networks. We call this promiscuity, and measure it directly by calculating how neuron's burst times drift from each other across time. Then, grouping neurons according to their phases, we explore how promiscuity affects the composition of these clusters, and obtain detailed knowledge of the network's phase synchronization. We also calculate two neuronal variabilities, measuring how the neuronal firing times disperse over time or over the network, and find that the two have very similar values and are strongly correlated to the network's degree of PS for weak coupling. Next, we expand our focus to metastability as viewed in neuroscience, regarding promiscuity as a type of metastable behavior. We provide a mini-review of the different definitions of metastability, and discuss them. With this, we categorize briefly the dynamical mechanisms leading to metastability. Finally, using the insights gained from studying promiscuity, we investigate the promiscuous network again to discuss how metastability can differ depending on the multiple scales of a system. Keywords: Metastability. Phase synchronization. Neural networks

Tracing back the source of contamination

From the time a contaminant is detected in an observation well, the question of where and when the contaminant was introduced in the aquifer needs an answer. Many techniques have been proposed to answer this question, but virtually all of them assume that the aquifer and its dynamics are perfectly known. This work discusses a new approach for the simultaneous identification of the contaminant source location and the spatial variability of hydraulic conductivity in an aquifer which has been validated on synthetic and laboratory experiments and which is in the process of being validated on a real aquifer