Biology subjects

Figueiredo, P.

Publications and source records attributed to Figueiredo, P..

12 recordsLinked to original sources

bioRxiv2026

Opportunities and pitfalls in preclinical cerebral blood flow mapping using arterial spin labelling MRI: insights from multicentre data

Cerebral blood flow (CBF) is a quantitative metric for mapping perfusion. While the prototypical MRI approach arterial spin labelling (ASL) is well-validated in humans, the reproducibility of rodent ASL mapping remains poor, limiting translational impact. To address this gap, we used both newly acquired and analysis of previously published data to illustrate biological and physical sources of variation in CBF measured with ASL. Via a meta-analysis, we quantified the variation in CBF reported from the cortex of healthy rodents. A total of 23 mouse studies (343 data points) and 5 rat studies (41 data points) met the inclusion criteria. We demonstrate that reported CBF values exhibit a broad variability (50-400 ml/100g/min) driven primarily by experimental confounds rather than physiological differences. Our meta-analysis explores which factors cause variance in perfusion rates measured. Our experimental data highlight biological factors, particularly the choice of anaesthesia (e.g., isoflurane vs. medetomidine) and strain variations, that alter baseline CBF. Our work, reflecting both state-of-the-art and conventional practice in preclinical imaging, highlights the need to account for multiple sources of variability. Establishing community guidelines for rigorous ASL calibration and physiological monitoring will support improved study design and accelerate translational alignment between rodent and human perfusion measurements. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=172 SRC="FIGDIR/small/733736v1_ufig1.gif" ALT="Figure 1"> View larger version (47K): org.highwire.dtl.DTLVardef@1e94d5org.highwire.dtl.DTLVardef@1bd5718org.highwire.dtl.DTLVardef@1a0fafcorg.highwire.dtl.DTLVardef@1bde97d_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2026

Test-retest reliability of resting-state fMRI functional connectivity: impact of scan length and number of participants

Resting-state functional MRI has been widely used to study brain connectivity, yet the test-retest reliability of commonly used metrics remains a concern. To improve reliability, extended scan lengths and larger subject cohorts are often recommended. However, these solutions can be impractical and pose challenges, particularly in studies of clinical populations. Here, we systematically assess the reliability of two main types of functional connectivity measures: node-based connectome metrics (edge-level intraclass correlation coefficient [ICC], connectome-level ICC, fingerprinting, and discriminability); and voxel-based resting-state networks (RSNs) (spatial similarity of independent component analysis [ICA] derived RSN maps quantified using the Dice coefficient). Using data from the Human Connectome Project, we evaluated the effects of scan length (3.6, 7.2, 10.8, and 14.4 minutes) and number of participants (10, 20, 50, and 100), on both within-session and between-session reliability. We found that multivariate connectome metrics demonstrated greater reliability than edge-level measures, and that scan length had stronger influence on test-retest reliability than the number of participants. For connectome metrics, 14 minutes of scanning and a cohort of approximately 10 participants were sufficient to achieve reliable estimates. In contrast, RSN measures benefited from larger cohort sizes. Our findings provide practical guidelines for designing resting-state fMRI studies in terms of scan length and number of participants, balancing reliability and feasibility. Ultimately, protocol choices should be guided by the specific study objectives and the functional connectivity metric of interest. KEY POINTSO_LIThis work systematically evaluates the within- and between-session test-retest reliability of node-based and voxel-based resting-state fMRI functional connectivity metrics as a function of scan length and number of participants. C_LIO_LILonger scan length ([~]11-14 minutes) improved the reliability of connectivity metrics, with specific requirements depending on the metric. C_LIO_LIThe number of participants had minimal effect on node-based metrics, but voxel-based metrics benefited from larger samples. C_LI

bioengineering↗

bioRxiv2025

Higher inter-trial latency variability contributes to reduced visual EEG responses in schizophrenia

Patients with schizophrenia show strong impairments in visual backward masking, which are associated with reduced EEG N1 responses. However, it is currently unclear whether reduced N1 amplitudes in patients reflect attenuated neural responses or increased inter-trial latency variability, as both can lead to reduced trial-averaged responses. Previous studies using trial-averaged data cannot distinguish between these two possibilities. Here, we estimated inter-trial latency variability of the visual N1 component and found significantly increased variability in patients compared to controls. Inter-trial latency-variability was a strong predictor of the N1 amplitude in both groups. Importantly, after accounting for the effect of latency variability in the group comparison, patients continued to exhibit significantly reduced N1 amplitudes, although the effect size diminished from large to medium. These findings indicate that both higher latency variability and attenuated neural responses contribute to visual processing deficits in schizophrenia.

neuroscience↗

bioRxiv2025

Disrupted salience network dynamics during the imagery of migraine attacks

Moderate to severe head pain is a hallmark of recurring migraine attacks. However, it is challenging to study patients during spontaneous attacks and most research on the brain mechanisms of pain in migraine patients has been limited to the processing of painful stimuli between attacks. Here, we hypothesize that the experience of a migraine attack extends beyond the response to painful stimuli and is associated with specific impairments of the salience network (SN), which integrates sensory, emotional and cognitive information in relation to salient stimuli. To test this hypothesis, we analysed the SN dynamics of a group of patients with episodic migraine in three distinct conditions: at rest during a spontaneous migraine attack (ictal phase); while performing an imagery task aiming to elicit the experience of a previous attack, during the interictal phase; and at rest, during the interictal phase. For comparison, we also studied a group of healthy controls in three matching conditions, including rest as well as an imagery task of a (non-migraine) head pain experience. We collected functional magnetic resonance imaging (fMRI) data and used a dynamic functional connectivity (dFC) analysis to examine the temporal features of the SN from a total of 78 samples. Compared to healthy controls, the SN had a significantly shorter lifetime in patients during the pain imagery task, but not during a migraine attack or interictal resting state. Our results support the disruption of the SN in migraine, and indicate that pain imagery may be a useful paradigm for isolating the emotional and cognitive aspects of pain and investigating SN dynamics.

neuroscience↗

bioRxiv2024

Disrupted activation of pain networks during attack imagery in patients with episodic migraine

Migraine is a prevalent and disabling brain disorder characterized by recurrent headache attacks alternating with pain-free periods. Patients with migraine exhibit altered brain activation in response to experimental nociceptive stimuli compared to healthy controls, suggesting impaired pain inhibition mechanisms. However, the relevance of these alterations to the underlying pathophysiology of migraine attacks remains unclear. To explore this relationship, we propose a novel pain imagery paradigm aimed to induce brain activation patterns associated with migraine attacks specifically during pain-free. The task required patients to alternate between imagining a severe migraine attack and being headache free, while healthy controls imagined severe physical head pain (e.g., toothache) and pain relief. We collected fMRI data from 14 episodic migraine without aura patients in the interictal phase and 15 healthy controls performing this task. Both patients and controls activated pain-related brain areas during imagery of pain relative to pain relief. Moreover, controls also activated the medial pain system associated with pain inhibition and attentional modulation of pain via top-down pathways. In contrast, patients significantly deactivated these areas, namely the anterior cingulate cortex and dorsolateral prefrontal cortex. Collectively, our findings indicate altered functioning of pain networks in migraine patients, suggesting a disease-related dysregulation of pain inhibition. Eventually, the proposed attack imagery paradigm may provide a promising alternative to studies of pain mechanisms in migraine research.

neuroscience↗

bioRxiv2024

Consistency of resting-state correlations between fMRI networks and EEG band-power

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 and to understand how factors such as the hemodynamic response delay and the use of different EEG data spaces (source/scalp) influence them. Using three distinct EEG-fMRI datasets, acquired independently on 1.5T, 3T and 7T MRI scanners (comprising 42 subjects in total), we evaluate the generalizability of our findings across different acquisition conditions. We found consistent correlations between fMRI RSN and EEG band-power time-series across subjects in the three datasets studied, with systematic variations with RSN, EEG frequency-band, and HRF delay, but not with EEG space. Qualitatively, the majority of these correlations were similar across the three datasets, despite important differences in field strength, number of subjects and resting-state conditions. Our findings support consistent correlations across specific fMRI RSNs and EEG bands and highlight the importance of methodological considerations in interpreting them that may explain conflicting reports in existing literature.

neuroscience↗

bioRxiv2024

Multilevel clinical fingerprinting: uncovering longitudinal changes in the functional connectome of the brain along the migraine cycle

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 of the migraine cycle are scarce. Here, we leverage the identifiability of individual functional connectomes (FC) to investigate changes along the migraine cycle. For this purpose, we employ a case-control longitudinal design to study a group of 10 patients with episodic menstrual or menstrual-related migraine without aura, in the 4 phases of their spontaneous migraine cycle (preictal, ictal, postictal, interictal), and a group of 14 healthy controls in corresponding phases of the menstrual cycle, using resting-state fMRI. We propose a novel multilevel clinical fingerprinting approach to analyse the differential FC identifiability within-subject, as well as within-session and within-group. The individual FC matrices are then reconstructed with 19 principal components maximizing identifiability at all levels, and analyzed with Network-Based Statistic to identify significant changes in FC strength. We observe decreased FC identifiability for patients in the preictal phase relative to controls, which increases with the progression of the attack and becomes comparable to controls in the interictal phase. Regarding the FC strength, is increased in the ictal and postictal phases relative to controls across several networks. Our novel multilevel clinical fingerprinting approach captures FC variations along the migraine cycle in a case-control longitudinal study, bringing new insights into the cyclic nature of the disorder.

bioengineering↗

bioRxiv2024

Structural connectome changes in episodic migraine: the role of the cerebellum

BackgroundThe 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 connectivity studies of migraine. Our objective is to investigate the structural connectivity of the entire brain, including the cerebellum, in individuals diagnosed with episodic migraine without aura during the interictal phase, compared with healthy controls. MethodsTo that end, 14 migraine patients and 15 healthy controls were recruited (all female), and diffusion-weighted and T1-weighted MRI data were acquired. The structural connectome was estimated for each participant based on two different whole-brain parcellations, including cortical and subcortical regions as well as the cerebellum. The structural connectivity patterns, as well as global and local graph theory metrics, were compared between patients and controls, for each of the two parcellations, using network-based statistics and a generalized linear model (GLM), respectively. We also compared the number of connectome streamlines within specific white matter tracts using a GLM. ResultsWe found increased structural connectivity in migraine patients relative to healthy controls with a distinct involvement of cerebellar regions, using both parcellations. Specifically, the node degree of the posterior lobe of the cerebellum was greater in patients than in controls and patients presented a higher number of streamlines within the anterior limb of the internal capsule. Moreover, the connectomes of patients exhibited greater global efficiency and shorter characteristic path length, which correlated with the age onset of migraine. ConclusionsA distinctive pattern of heightened structural connectivity and enhanced global efficiency in migraine patients compared to controls was identified, which distinctively involves the cerebellum. These findings provide evidence for increased integration within structural brain networks in migraine and underscore the significance of the cerebellum in migraine pathophysiology.

bioengineering↗

bioRxiv2024

Cerebrovascular reactivity mapping using breath-hold BOLD-fMRI: comparison of signal models combined with voxelwise lag optimization

Cerebrovascular reactivity (CVR) can be mapped noninvasively using blood oxygenation level dependent (BOLD) fMRI during a breath-hold (BH) task. Previous studies showed that the BH BOLD response is best modeled as the convolution of the partial pressure of end-tidal CO2 (PetCO2) with a canonical hemodynamic response function (HRF). However, previous model comparisons employed a global bulk time lag, which is now well accepted to provide only a rough approximation of the heterogeneous distribution of response latencies across the brain. Here, we investigate the best modeling approach for mapping CVR based on BH BOLD-fMRI data, when using a lagged general linear model approach combined with voxelwise lag optimization. In a group of fourteen healthy participants, we compared models considering: two types of regressors (PetCO2 and Block), three convolution models (no convolution; convolution with a single gamma HRF; and convolution with a double gamma HRF), and a variable HRF delay (3-11s). We found no significant improvements in model fit with other delays, and hence selected the canonical delay of 6s. Although the two regressor types yielded similar model fits, PetCO2 produced significantly greater CVR values than Block models. Interestingly, a single gamma HRF yielded the greatest CVR values in PetCO2 models, while block models benefited from convolution with a double gamma HRF. In conclusion, when modeling BH BOLD-fMRI signals with voxelwise lag optimization, PetCO2 regressors convolved with a single gamma HRF should be preferentially used. In case good quality PetCO2 recordings are unavailable, a block-based model convolved with the canonical HRF may be a good alternative. In conclusion, our manuscript reports the first systematic signal model comparison, providing evidence to support the use of specific modeling approaches for CVR mapping based on BH BOLD-fMRI.

bioengineering↗

bioRxiv2024

High-resolution perfusion imaging in rodents using pCASL at 9.4 T

Adequate perfusion is critical for maintaining normal brain function and aberrations thereof are hallmarks of many diseases. Pseudo-Continuous Arterial Spin Labeling (pCASL) MRI enables noninvasive perfusion mapping without contrast agent injection and with higher signal-to-noise ratio (SNR) than alternative methods. Despite its great potential, pCASL remains challenging, unstable, and relatively low-resolution in rodents - especially in mice - thereby limiting the investigation of perfusion properties in many transgenic or other relevant rodent models of disease. Here, we address this gap by developing a novel experimental setup for high-resolution pCASL imaging in mice and combining it with the enhanced SNR of cryogenic probes. We show that our new experimental setup allows for optimal positioning of the carotids within the cryogenic coil, rendering labelling reproducible. With the proposed methodology, we managed to increase the spatial resolution of pCASL perfusion images by a factor of 15 in mice; a factor of 6 in rats is gained compared to the state of the art just by virtue of the cryogenic coil. We also show that the improved pCASL perfusion imaging allows much better delineation of specific brain areas, both in healthy animals as well as in rat and mouse models of stroke. Our results bode well for future high-definition pCASL perfusion imaging in rodents. Data availabilityData will be freely made available upon request.

neuroscience↗

bioRxiv2022

Brain activation by a VR-based motor imagery andobservation task: An fMRI study

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-muscular channel. These can be further augmented through embodied feedback delivered through virtual reality (VR). Here, we used functional magnetic resonance imaging (fMRI) to map brain activation elicited by a VR-based MI-MO BCI task called NeuRow and compared with a conventional non-VR, and MI-only, task based on the Graz BCI paradigm. We found that, in healthy adults, NeuRow elicits stronger brain activation when compared to the Graz task, as well as to an overt motor execution task, recruiting large portions of the parietal and occipital cortices in addition to the motor and premotor cortices. In particular, NeuRow activates the mirror neuron system (MNS), associated with action observation, as well as visual areas related with visual attention and motion processing. We studied a cohort of healthy adults including younger and older subgroups, and found no significant age-related effects in the measured brain activity. Overall, our findings suggest that the virtual representation of the arms in a bimanual MI-MO task engage the brain beyond conventional MI tasks, even in older adults, which we propose could be explored for effective neurorehabilitation protocols.

neuroscience↗

bioRxiv2019

Intra-individual variability of sleep and nocturnal cardiac autonomic activity in elite female soccer players during an international tournament

PurposeThis study provides insights into the individual sleep patterns and nocturnal cardiac autonomic activity responses of elite female soccer players during an international tournament.\n\nMaterials and methodsTwenty elite female soccer players (aged 25.2{+/-}3.1 years) wore wrist actigraph units and heart rate (HR) monitors during night-sleep throughout 9 consecutive days (6 day-time training sessions [DT], 2 day-time matches [DM], and 1 evening-time match [EM]) of an international tournament. Training and match loads were monitored using the session-rating of perceived exertion (s-RPE) and wearable 18-Hz GPS (total distance covered [TD], training and match exposure time, and high-speed running [HSR]) to characterize training and match loads.\n\nResultsIndividually, s-RPE, TD, exposure time, and HSR during training sessions ranged from 20 to 680 arbitrary units (AU), 892 to 5176 m, 20 to 76 min, and 80 to 1140 m, respectively. During matches, s-RPE, TD, exposure time, and HSR ranged from 149 to 876 AU, 2236 to 11210 m, 20 to 98 min, and 629 to 3213 m, respectively. Individually, players slept less than recommended (<7 hours) on several days of the tournament, especially after EM (n=8; TST ranging between 6:00-6:54 h). Total sleep time coefficient of variation (CV) ranged between 3.1 and 18.7%. However, all players presented good sleep quality (i.e., sleep efficiency [≥]75%; individual range between: 75-98%) on each day of the tournament. Most of the players presented small fluctuations in nocturnal cardiac autonomic activity (individual nocturnal heart rate variability [HRV] ranged from 3.91-5.37 ms and HRV CV ranged from 2.8-9.0%), while two players presented higher HRV CV (11.5 and 11.7%; respectively).\n\nConclusionOverall, elite female soccer players seemed to be highly resilient to training and match schedules and loads during a 9 day international tournament.

physiology↗