Biology subjects

Aquino, K.

Publications and source records attributed to Aquino, K..

5 recordsLinked to original sources

bioRxiv2024

Extracting interpretable signatures of whole-brain dynamics through systematic comparison

The brains complex distributed dynamics are typically quantified using a limited set of manually selected statistical properties, leaving the possibility that alternative dynamical properties may outperform those reported for a given application. Here, we address this limitation by systematically comparing diverse, interpretable features of both intra-regional activity and inter-regional functional coupling from resting-state functional magnetic resonance imaging (rs-fMRI) data, demonstrating our method using case-control comparisons of four neuropsychiatric disorders. Our findings generally support the use of linear time-series analysis techniques for rs-fMRI case-control analyses, while also identifying new ways to quantify informative dynamical fMRI structures. While simple statistical representations of fMRI dynamics performed surprisingly well (e.g., properties within a single brain region), combining intra-regional properties with inter-regional coupling generally improved performance, underscoring the distributed, multifaceted changes to fMRI dynamics in neuropsychiatric disorders. The comprehensive, data-driven method introduced here enables systematic identification and interpretation of quantitative dynamical signatures of multivariate time-series data, with applicability beyond neuroimaging to diverse scientific problems involving complex time-varying systems.

neuroscience↗

bioRxiv2022

Using in silico perturbational approach to identify critical areas in schizophrenia

Schizophrenia is a debilitating neuropsychiatric disorder whose underlying correlates remain unclear despite decades of neuroimaging investigation. One contentious topic concerns the role of global signal fluctuations and how they affect more focal functional changes. Moreover, it has been difficult to pinpoint causal mechanisms of circuit disruption. Here we analysed resting-state fMRI data from 47 schizophrenia patients and 118 age-matched healthy controls and used dynamical analyses to investigate how global fluctuations and other functional metastable states are affected by this disorder. We then used in-silico perturbation of a whole-brain model to identify critical areas involved in the disease. We found that brain dynamics in the schizophrenic group were characterised by an increased probability of globally coherent states and reduced recurrence of a substate dominated by coupled activity in the default mode and limbic networks. Perturbing a set of temporoparietal sensory and associative areas in a model of the healthy brain reproduced global pathological dynamics. Healthy brain dynamics were instead restored by perturbing a set of medial fronto-temporal and cingulate regions in the model of pathology. These results highlight the relevance of global signal alterations in schizophrenia and identify a set of vulnerable areas involved in determining a shift in brain state.

neuroscience↗

bioRxiv2021

Extracting dynamical understanding from neural-mass models of mouse cortex

New brain atlases with high spatial resolution and whole-brain coverage have rapidly advanced our knowledge of the brains neural architecture, including the systematic variation of excitatory and inhibitory cell densities across the mammalian cortex. But understanding how the brains microscale physiology shapes brain dynamics at the macroscale has remained a challenge. While physiologically based mathematical models of brain dynamics are well placed to bridge this explanatory gap, their complexity can form a barrier to providing clear mechanistic interpretation of the dynamics they generate. In this work we develop a neural-mass model of the mouse cortex and show how bifurcation diagrams, which capture local dynamical responses to inputs and their variation across brain regions, can be used to understand the resulting whole-brain dynamics. We show that strong fits to resting-state functional magnetic resonance imaging (fMRI) data can be found in surprisingly simple dynamical regimes--including where all brain regions are confined to a stable fixed point--in which regions are able to respond strongly to variations in their inputs, consistent with direct structural connections providing a strong constraint on functional connectivity in the anesthetized mouse. We also use bifurcation diagrams to show how perturbations to local excitatory and inhibitory coupling strengths across the cortex, constrained by cell-density data, provide spatially dependent constraints on resulting cortical activity, and support a greater diversity of coincident dynamical regimes. Our work illustrates methods for visualizing and interpreting model performance in terms of underlying dynamical mechanisms, an approach that is crucial for building explanatory and physiologically grounded models of the dynamical principles that underpin large-scale brain activity.

neuroscience↗

bioRxiv2018

Transdiagnostic variations in impulsivity and compulsivity in obsessive-compulsive disorder and gambling disorder correlate with effective connectivity in cortical-striatal-thalamic-cortical circuits.

BackgroundIndividual differences in impulsivity and compulsivity is thought to underlie vulnerability to a broad range of disorders and are closely tied to cortical-striatal-thalamic-cortical (CSTC) function. However, whether impulsivity and compulsivity in clinical disorders is continuous with the healthy population and explains CSTC dysfunction across different disorders remains unclear.\n\nMethodsWe characterized the relationship between CSTC effective connectivity, estimated using dynamic causal modelling of functional magnetic resonance imaging data, and dimensional phenotypes of impulsivity and compulsivity in two symptomatically distinct but phenotypically related disorders, obsessive-compulsive disorder (OCD) and gambling disorder (GD). 487 online participants provided data for modelling of dimensional phenotypes. These data were combined with 34 OCD patients, 22 GD patients, and 39 healthy controls, who underwent functional magnetic resonance imaging.\n\nResultsThree core dimensions were identified: disinhibition, impulsivity, and compulsivity. Patients scores on these dimensions were continuously distributed with the healthy participants, supporting a continuum model of psychopathology. Across all participants, higher disinhibition correlated with lower bottom-up connectivity in the dorsal circuit and increased bottom-up connectivity in the ventral circuit, and higher compulsivity correlated with reduced bottom-up connectivity in the dorsal circuit. Similar changes in effective connectivity were observed with increasing clinical severity that were not accounted for by phenotypic variation, demonstrating convergence towards behaviourally and clinically relevant changes in brain dynamics. Effective connectivity did not differ as a function of traditional diagnostic labels.\n\nConclusionsCSTC dysfunction across OCD and GD is better characterized by dimensional phenotypes than diagnostic comparisons, supporting investigation of quantitative liability phenotypes.

neuroscience↗

bioRxiv2018

Two spatially distinct posterior alpha sources fulfill different functional roles in attention

Directing attention helps to extract relevant information and suppress distracters. Alpha brain oscillations (8-12Hz) play a fundamental role in this process, with a power decrease facilitating processing of important information and power increase inhibiting brain regions processing irrelevant information. Evidence for this phenomenon arises from visual attention studies (Worden et al., 2000), however, the effect also exists in other modalities, including the somatosensory system (Haegens et al., 2011) and inter-sensory attention tasks (Foxe and Snyder, 2011). We investigated what happens when attention is divided between two modalities using both a multi- and unimodal attention paradigm while recording EEG over 128 scalp electrodes in two separate experiments. In Experiment 1 participants divided their attention between the visual and somatosensory modality to determine the temporal or spatial frequency of a target stimulus (vibrotactile stimulus or Gabor grating). In Experiment 2, participants divided attention between two visual hemifields to identify the orientation of a target Gabor grating. In both experiments, pre-stimulus alpha power in visual areas decreased linearly with increasing attention to visual stimuli. In contrast, alpha power in parietal areas showed lower pre-stimulus alpha power when attention was divided between modalities, compared to unimodal attention. These results suggest that there are two different alpha sources, where one reflects the visual spotlight of attention and the other reflects attentional effort. To our knowledge, this is the first study to show that attention recruits two spatially distinct alpha sources in occipital and parietal brain regions, which act simultaneously but serve different functions in attention.\n\nSIGNIFICANCE STATEMENTAttention to one spatial location/sensory modality leads to power changes of alpha oscillations (~10Hz) with decreased power over regions processing relevant information and power increases to actively inhibit areas processing to-be-ignored information. Here, we used detailed source modelling to investigate EEG data recorded during separate uni-modal (visual) and multi- (visual and somatosensory) attention tasks. Participants either focused their attention on one modality/spatial location or directed it to both. We show for the first time two distinct alpha sources are active simultaneously but play different roles. A sensory (visual) alpha source was linearly modulated by attention representing the visual spotlight of attention. In contrast, a parietal alpha source was modulated by attentional effort, showing lowest alpha power when attention was divided.

neuroscience↗