Patrícia Figueiredo

Patrícia Figueiredo
University of Lisbon | UL

DPhil

About

145
Publications
20,152
Reads
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2,859
Citations
Introduction
Patrícia Figueiredo currently works at the Institute for Systems and Robotics (ISR), Institute Superior Técnico (IST), Universidade de Lisboa. Patrícia does research in Biomedical Engineering, Medical Physics, Neuroimaging, MRI and Neuroscience. Her main current projects are "Imaging cerebrovascular physiology by functional MRI" and "Imaging dynamic brain networks by EEG and fMRI".
Additional affiliations
January 2015 - June 2015
École Polytechnique Fédérale de Lausanne
Position
  • Invited researcher
January 2012 - December 2015
University College London
Position
  • Honorary Senior Lecturer
January 2011 - present
Institute for Systems and Robotics
Position
  • Senior Researcher
Education
January 1998 - August 2003
University of Oxford
Field of study
  • Neuroimaging
September 1996 - December 1997
University of Lisbon
Field of study
  • Biophysics and Biomedical Engineering
September 1991 - August 1996
Technical University of Lisbon
Field of study
  • Physics and Engineering

Publications

Publications (145)
Article
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Objective To analyze cognitive performance and brain activation during a working memory task in patients with migraine during various phases of the migraine cycle and compare to healthy participants. Background Cognitive difficulties reported during migraine attacks remain poorly understood, despite evidence that the lateral frontoparietal network...
Article
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Background The pathophysiology of migraine remains poorly understood, yet a growing number of studies have shown structural connectivity disruptions across large-scale brain networks. Although both structural and functional changes have been found in the cerebellum of migraine patients, the cerebellum has barely been assessed in previous structural...
Preprint
Several simultaneous EEG-fMRI studies have aimed to identify the relationship between EEG band power and fMRI resting state networks (RSNs) to elucidate their neurobiological significance. Although common patterns have emerged, inconsistent results have also been reported. This study examines the consistency of these correlations across subjects an...
Preprint
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Migraine is a common neurological disorder characterized by recurrent headache episodes alternating with symptom-free periods, which has been associated with alterations across large-scale functional brain networks albeit with variable findings. Critically, despite the cyclic nature of the disorder, longitudinal studies spanning the various phases...
Preprint
Full-text available
BACKGROUND: Migraine's pathophysiology remains poorly understood, yet a growing number of studies have shown structural connectivity disruptions across large-scale brain networks. Both macro- and micro-structural changes have been found in the cerebellum of migraine patients; however, the cerebellum has not been considered in previous structural co...
Preprint
Full-text available
Objective To analyze cognition and brain activation during an executive task in migraine patients studied in the different phases of the migraine cycle, compared with healthy participants. Background Cognitive difficulties reported during migraine attacks remain poorly understood, despite evidence that the lateral frontoparietal network undergoes...
Article
Full-text available
Purpose Arterial spin labeling (ASL) is a widely used contrast‐free MRI method for assessing cerebral blood flow (CBF). Despite the generally adopted ASL acquisition guidelines, there is still wide variability in ASL analysis. We explored this variability through the ISMRM‐OSIPI ASL‐MRI Challenge, aiming to establish best practices for more reprodu...
Article
Full-text available
Diffusional kurtosis imaging (DKI) extends diffusion tensor imaging (DTI), characterizing non-Gaussian diffusion effects but requires longer acquisition times. To ensure the robustness of DKI parameters, data acquisition ordering should be optimized allowing for scan interruptions or shortening. Three methodologies were used to examine how reduced...
Preprint
Full-text available
Background: Migraine is a neurological disorder exhibiting a cyclic pattern of clinical manifestations. Although both structural and functional brain changes have been reported in comparison with healthy controls, it is not clear to what extent these vary across the migraine cycle. Here, we present a longitudinal study of menstrual migraine using d...
Article
Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are two commonly used non-invasive techniques for measuring brain activity in neuroscience and brain- computer interfaces (BCI). While EEG has high temporal resolution and low spatial resolution, fMRI has high spatial resolution and low temporal resolution. In this review...
Article
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To investigate the neural correlates of working memory during a spontaneous migraine attack compared to the interictal phase, using functional magnetic resonance imaging (fMRI). Cognitive disturbances are commonly observed during migraine attacks, particularly in the headache phase. However, the neural basis of these changes remains unknown. In a f...
Article
Full-text available
Training motor imagery (MI) and motor observation (MO) tasks is being intensively exploited to promote brain plasticity in the context of post-stroke rehabilitation strategies. This may benefit from the use of closed-loop neurofeedback, embedded in brain-computer interfaces (BCI’s) to provide an alternative non-muscular channel, which may be furthe...
Article
Background: Previous functional magnetic resonance imaging studies have identified brain-connectivity alterations across multiple regions in people with migraine when compared to healthy controls. Few studies have focused on such changes throughout the different phases of the migraine cycle. We aimed to investigate functional connectivity during s...
Article
Full-text available
Purpose Arterial spin labeling (ASL) acquisitions at multiple post‐labeling delays may provide more accurate quantification of cerebral blood flow (CBF), by fitting appropriate kinetic models and simultaneously estimating relevant parameters such as the arterial transit time (ATT) and arterial cerebral blood volume (aCBV). We evaluate the effects o...
Article
Purpose: The consensus for the clinical implementation of arterial spin labeling (ASL) perfusion imaging recommends a segmented 3D Gradient and Spin-Echo (GRASE) readout for optimal signal-to-noise-ratio(SNR). The correction of the associated susceptibility-induced geometric distortions has been shown to improve diagnostic precision, but its impac...
Chapter
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The brain’s functional networks can be assessed using imaging techniques like functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). Recent studies have suggested a link between the dynamic functional connectivity (dFC) captured by these two modalities, but the exact relationship between their spatiotemporal organization is...
Article
Effective use of conceptual knowledge engages semantic representation and control processes to access information in a goal-driven manner. Neuropsychological findings of patients presenting either degraded knowledge (e.g., semantic dementia) or disrupted control (e.g., semantic aphasia) converge with neuroimaging evidence from young adults, and del...
Article
Full-text available
Motor imagery (MI)-based brain-computer interfaces (BCI) have shown increased potential for the rehabilitation of stroke patients; nonetheless, their implementation in clinical practice has been restricted due to their low accuracy performance. To date, although a lot of research has been carried out in benchmarking and highlighting the most valuab...
Preprint
Full-text available
Training motor imagery (MI) and motor observation (MO) tasks is being intensively exploited to promote brain plasticity in the context of post-stroke rehabilitation strategies. The desired brain plasticity mechanisms may benefit from the use of closed-loop neurofeedback, embedded in brain-computer interfaces (BCIs) to provide an alternative non-mus...
Preprint
Motor imagery(MI)-based Brain-Computer Interfaces (BCI) have shown increased potential for the rehabilitation of stroke patients; nonetheless, their implementation in clinical practice has been restricted due to their low accuracy performance. To date, although a lot of research has been made in benchmarking and highlighting the most valuable class...
Conference Paper
Full-text available
Electroencephalography-based Brain-Computer Interfaces (BCI's) can provide an alternative non-muscular channel of control to stroke survivors, especially to those who lack volitional movement. This is achieved through motor-imagery (MI) practice, involving the activation of motor-related brain regions. MI is reinforced in a closed-loop BCI through...
Poster
Full-text available
The simultaneous acquisition of EEG and fMRI induces two severe artifacts on the EEG, the Gradient Artifact (GA) and the Pulse artifact (PA), which prevent its application to neurofeedback (NF) runs. Few methods have been proposed to reduce these artifacts in real-time, but they are either slow, publicly unavailable, hardware-dependent, or propriet...
Preprint
Full-text available
Background: Restorative Brain-Computer Interfaces (BCI's) can provide an alternative non-muscular channel for patients who lack volitional movement by reinforcing the modulation of sensorimotor rhythms through motor-imagery (MI). MI practice can be augmented through embodied feedback delivered by virtual reality (VR). Nonetheless, detailed informat...
Article
Full-text available
Research on schizophrenia typically focuses on one paradigm for which clear-cut differences between patients and controls are established. Great efforts are made to understand the underlying genetical, neurophysiological, and cognitive mechanisms, which eventually may explain the clinical outcome. One tacit assumption of these “deep rooting” approa...
Poster
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This poster aim to shed light on BCI illiteracy by measuring brain activation during a MI task typically used in BCIs, simultaneously using EEG and fMRI.
Conference Paper
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In the last few years, Brain-Computer Interfaces(BCI’s) have progressed as an emerging research area in the domain of neurotechnology. This is primarily due to the introduction of low-cost electroencephalographic (EEG) systems that render BCI technology accessible for non-medical research, but also due to the advancements of signal processing and m...
Article
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There are many factors outlined in the signal processing pipeline that impact brain–computer interface (BCI) performance, but some methodological factors do not depend on signal processing. Nevertheless, there is a lack of research assessing the effect of such factors. Here, we investigate the impact of VR, immersiveness, age, and spatial resolutio...
Article
Full-text available
Objective Summarize evidence for use of advanced MRI techniques as monitoring biomarkers in the clinic, and highlight the latest bench-to-bedside developments. Methods Experts in advanced MRI techniques applied to high-grade glioma treatment response assessment convened through a European framework. Current evidence regarding the potential for mon...
Article
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Objective To summarize evidence for use of advanced MRI techniques as monitoring biomarkers in the clinic, and to highlight the latest bench-to-bedside developments. Methods The current evidence regarding the potential for monitoring biomarkers was reviewed and individual modalities of metabolism and/or chemical composition imaging discussed. Perf...
Article
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Objective: Histogram-based metrics extracted from diffusion-tensor imaging (DTI) have been suggested as potential biomarkers for cerebral small vessel disease (SVD), but methods and results have varied across studies. This work aims to assess the impact of mask selection for extracting histogram-based metrics of fractional anisotropy (FA) and mean...
Article
Full-text available
Background and Objectives: The motor sequelae after a stroke are frequently persistent and cause a high degree of disability. Cortical ischemic or hemorrhagic strokes affecting the cortico-spinal pathways are known to cause a reduction of cortical excitability in the lesioned area not only for the local connectivity impairment but also due to a con...
Preprint
Full-text available
Purpose Histogram-based metrics extracted from diffusion-tensor imaging (DTI) have been suggested as potential biomarkers for cerebral small vessel disease (SVD), but methods and results have varied across studies. This work aims to assess the impact of mask selection for extracting histogram-based metrics of fractional anisotropy (FA) and mean dif...
Article
Full-text available
Successful use of conceptual knowledge entails the assembling of semantic representations and control processes to access the subsets of knowledge relevant in each situation. Research has suggested that representation and control mechanisms interact to support categorization. Notably, depleted representations in semantic dementia and disrupted cont...
Article
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Cerebrovascular reactivity (CVR) is defined as the ability of vessels to alter their caliber in response to vasoactive factors, by means of dilating or constricting, in order to increase or decrease regional cerebral blood flow (CBF). Importantly, CVR may provide a sensitive biomarker for pathologies where vasculature is compromised. Furthermore, t...
Article
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Pain is an under-reported but prevalent symptom in Parkinson’s Disease (PD), impacting patients’ quality of life. Both pain and PD conditions cause cortical excitability reduction and non-invasive brain stimulation. Mental representation techniques are thought to be able to counteract it, also resulting effectively in chronic pain conditions. We ai...
Chapter
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In recent years, increasing evidence of the positive impact of Virtual Reality (VR) on neurofeedback training has emerged. The immersive properties of VR training scenarios have been shown to facilitate neurofeedback learning while leading to cognitive enhancements such as increased working memory performance. However, in the design of an immersive...
Article
Full-text available
Brain functional connectivity measured by resting-state fMRI varies over multiple time scales, and recurrent dynamic functional connectivity (dFC) states have been identified. These have been found to be associated with different cognitive and pathological states, with potential as disease biomarkers, but their neuronal underpinnings remain a matte...
Preprint
Full-text available
In the last few years,Brain-Computer Interfaces (BCIs) have progressed as an emerging research area in the fields of human-computer interaction and interactive systems.This is primarily due to the introduction of low-cost electroencephalographic (EEG) systems that render BCI technology accessible for non-medical research but also due to the advance...
Preprint
Full-text available
Research on schizophrenia typically focuses on one paradigm, for which clear-cut abnormalities between patients and controls are established. Great care is taken to understand the underlying genetical, neurophysiological, and cognitive mechanisms, which eventually may explain the clinical outcome. This approach has led to many important hypotheses...
Article
Full-text available
Purpose There is an annual incidence of 50,000 glioma cases in Europe. The optimal treatment strategy is highly personalised, depending on tumour type, grade, spatial localization, and the degree of tissue infiltration. In research settings, advanced magnetic resonance imaging (MRI) has shown great promise as a tool to inform personalised treatment...
Poster
Full-text available
We have previously developed a novel VR-based motor imagery (MI) and motor observation (MO) task targeting the upper limbs for stroke rehabilitation-NeuRow; it consists of imagining the kinaesthetic experience of rowing using the left or right arm. Here, we evaluate brain activation elicited by NeuRow and compare it with an abstract MI task using t...
Poster
Full-text available
The correction of MR artifacts from EEG acquired simultaneously with fMRI comes with a trade-off between artifact removal and physiological signal preservation. A possible concern is the preservation of the commonly studied alpha band, which is essential for its correct interpretation1. Our goal was to investigate changes in the individual alpha ba...
Article
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Encephalopathy related to Status Epilepticus during slow Sleep (ESES) is an age-related, epileptic syndrome, which associates cognitive/behavioral disturbances with a peculiar pattern of spike activity. One promising line of research is the study of ESES in cases of early thalamic lesions. We studied 7 ESES patients with unilateral thalamic lesions...
Article
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Electroencephalogram microstates are recurrent scalp potential configurations that remain stable for around 90 ms. The dynamics of two of the four canonical classes of microstates, commonly labeled as C and D, have been suggested as a potential endophenotype for schizophrenia. For endophenotypes, unaffected relatives of patients must show abnormali...
Article
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Visual backward masking (VBM) deficits are candidate endophenotypes of schizophrenia indexing genetic liability of the disorder. In VBM, a target is followed by a mask that deteriorates target perception. Schizophrenia patients and, to a lesser extent, their unaffected relatives show strong and reproducible VBM deficits. In patients, VBM deficits a...
Article
Full-text available
Purpose To assess the impact of the different post‐processing options in the calibration of arterial spin labeling (ASL) data on perfusion quantification and its reproducibility. Theory and Methods Absolute quantification of perfusion measurements is one of the promises of ASL techniques. However, it is highly dependent on a calibration procedure...
Article
Depression and schizophrenia are two psychiatric diseases with high co-morbidity. For this reason, it is important to find sensitive endophenotypes, which may disentangle the two disorders. The Shine-Through paradigm, a visual backward masking task, is a potential endophenotype for schizophrenia. Masking is strongly deteriorated in schizophrenia pa...
Article
Full-text available
To maximize brain plasticity after stroke, a plethora of rehabilitation strategies have been explored. These include the use of intensive motor training, motor-imagery (MI), and action-observation (AO). Growing evidence of the positive impact of virtual reality (VR) techniques on recovery following stroke has been shown. However, most VR tools are...
Conference Paper
Full-text available
Electroencephalography (EEG) neurofeedback (NF) training has been shown to produce long-lasting effects on the improvement of cognitive function as well as the normalization of aberrant brain activity in disease. However, the impact of the sensory modality used as the NF reinforcement signal on training effectiveness has not been systematically inv...
Article
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Most fMRI studies of the brain’s intrinsic functional connectivity (FC) have assumed that this is static; however, it is now clear that it changes over time. This is particularly relevant in epilepsy, which is characterized by a continuous interchange between epileptic and normal brain states associated with the occurrence of epileptic activity. In...
Article
Visual backward masking is strongly impaired in patients with schizophrenia. Masking deficits have been proposed as potential endophenotypes of schizophrenia. Masking performance deficits manifest as strongly reduced amplitudes in the electroencephalogram (EEG). In order to fulfill the criteria of an endophenotype, masking deficits should not vary...
Article
Full-text available
Social dominance, the main organizing principle of social hierarchies, facilitates priority access to resources by dominant individuals. Throughout taxa, individuals are more likely to become dominant if they act first in social situations and acting fast may provide evolutionary advantage; yet whether fast decision-making is a behavioral predispos...
Article
Objective With the advent of high-density EEG and studies of large numbers of participants, yielding increasingly greater amounts of data, supervised methods for artifact rejection have become excessively time consuming. Here, we propose a novel automatic pipeline (APP) for pre-processing and artifact rejection of EEG data, which innovates relative...
Article
External stimuli and tasks often elicit negative BOLD responses in various brain regions, and growing experimental evidence supports that these phenomena are functionally meaningful. In this work, the high sensitivity available at 7T was explored to map and characterize both positive (PBRs) and negative BOLD responses (NBRs) to visual checkerboard...
Article
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The simultaneous acquisition of electroencephalography (EEG) with functional magnetic resonance imaging (fMRI) is a very promising non-invasive technique for the study of human brain function. Despite continuous improvements, it remains a challenging technique, and a standard methodology for data analysis is yet to be established. Here we review th...