Biology subjects

Branco, P.

Publications and source records attributed to Branco, P..

3 recordsLinked to original sources

bioRxiv2025

Revisiting Amplitude of Low-Frequency Fluctuations (ALFF) in Resting-state fMRI: Clarifications and Improvements

The amplitude of low-frequency fluctuations (ALFF) and its related measure, fractional ALFF (fALFF), are widely used resting-state fMRI techniques for quantifying spontaneous neural activity within specific frequency bands. However, inconsistencies in the definition and implementation of ALFF have led to confusion in the field. In this study, we provide a mathematical clarification of ALFF and fALFF by introducing two variants: the arithmetic mean-defined ALFF/fALFF (amALFF/amfALFF) and the quadratic mean-defined ALFF/fALFF (qmALFF/qmfALFF). We examine the relationships between mean BOLD intensity (MBI), amALFF, and qmALFF across both subjects and voxels using two independent datasets mapped onto different brain templates. Additionally, we investigate the impact of z-scoring the original BOLD signal on ALFF and fALFF metrics. Our key findings include: (1) MBI is positively correlated with both amALFF and qmALFF, highlighting the need for normalization to subject-level means; (2) normalized qmALFF and qmfALFF are highly correlated with normalized amALFF and amfALFF, respectively, at both the subject and voxel levels; (3) z-scoring the BOLD signal does not affect amfALFF or qmfALFF, but it substantially alters amALFF and qmALFF. Based on these findings, we present a comprehensive flowchart of the (f)ALFF algorithm implemented in the temporal domain. The full procedure is implemented in R, and the corresponding script is available at: https://github.com/lejianhuang/ALFF.

neuroscience↗

bioRxiv2022

Widespread, perception-related information in the human brain scales with levels of consciousness

How does the human brain generate coherent, subjective perceptions--transforming yellow and oblong visual sensory information into the perception of an edible banana 1? This is a hard problem. The standard viewpoint posits that anatomical and functional networks integrate local, specialized processing across the brain to somehow construct unique percepts. Here, we provide evidence for a novel organizational concept by uncovering task-specific information distributed across the human brain. First, we show that functional magnetic resonance imaging (fMRI) can uncover task-specific information throughout the neocortex, even across voxels traditionally discarded as "noise" (t-statistics {approx} 0), challenging the sensitivity of traditional linear, univariate analytical approaches. Remarkably, task-specific signals could also be uncovered from across-subject variances and were ubiquitous even in the subcortex and cerebellum. Finally, we show that the widespread signal in regions remote from a tasks primary and secondary sensory cortices depends on the level of sedation, suggesting it is related to perception{dagger} rather than sensory stimulus encoding. We hypothesize that these widespread, task-specific, and consciousness level-dependent signals may be the basis for coherent, subjective perceptions.

neuroscience↗

bioRxiv2021

Structural brain connectivity predicts acute pain after mild traumatic brain injury

Mild traumatic brain injury, mTBI, is a leading cause of disability worldwide, with acute pain manifesting as one of its most debilitating symptoms. Understanding acute post-injury pain is important since it is a strong predictor of long-term outcomes. In this study, we imaged the brains of 172 patients with mTBI, following a motorized vehicle collision and used a machine learning approach to extract white matter structural and resting state fMRI functional connectivity measures to predict acute pain. Stronger white matter tracts within the sensorimotor, thalamic-cortical, and default-mode systems predicted 20% of the variance in pain severity within 72 hours of the injury. This result generalized in two independent groups: 39 mTBI patients and 13 mTBI patients without whiplash symptoms. White matter measures collected at 6-months after the collision still predicted mTBI pain at that timepoint (n = 36). These white-matter connections were associated with two nociceptive psychophysical outcomes tested at a remote body site - namely conditioned pain modulation and magnitude of suprathreshold pain-, and with pain sensitivity questionnaire scores. Our validated findings demonstrate a stable white-matter network, the properties of which determine a significant amount of pain experienced after acute injury, pinpointing a circuitry engaged in the transformation and amplification of nociceptive inputs to pain perception.

neuroscience↗