About

Marcelo Febo completed his PhD at the University of Puerto Rico Medical School and conducted postdoctoral studies at the University of Massachusetts Medical Center. His work focuses on measuring in vivo functional and structural changes in the rat brain following chronic drug exposure. Over the past decade, he has utilized high field functional magnetic resonance imaging (fMRI) in awake rats and mice to study neural activity. His research has been funded by the National Institute on Drug Abuse to examine the relationship between cocaine sensitization and alterations in maternal brain activity. He is currently the Program Director of Translational Research Imaging at the University of Florida Brain Institute and is a faculty member of the Department of Psychiatry. His research emphasizes using neuroimaging to study the neural correlates of addiction in rodent models. His work leverages the non-invasive nature of fMRI to conduct longitudinal studies on brain activation in response to cognitive, emotional, and drug stimuli, contributing to understanding conditions such as addiction and depression. His investigations include the long-term impact of chronic cocaine exposure on the dopaminergic system, the role of brain oxytocin and vasopressin systems in processing social stimuli, and the specific roles of the medial prefrontal cortex in motivation and emotion.

Research topics

• Medicine
• Internal medicine
• Chemistry
• Biology
• Psychology
• Computer Science
• Developmental psychology
• Psychiatry
• Artificial Intelligence
• Endocrinology
• Neuroscience
• Machine Learning
• Physiology
• Materials science
• Cell biology
• Pathology
• Nanotechnology
• Optoelectronics
• Biochemistry
• Biophysics

Selected publications

• Cannabidiol reduces oxycodone self-administration while preserving its analgesic efficacy in a rat model of neuropathic pain

  Scientific Reports · 2026-01-11 · 1 citations

  articleOpen access

  Prescription opioid misuse is a significant public health concern among individuals with chronic pain. Treating severe pain often requires high doses of opioids, increasing the risk of developing an opioid use disorder. Cannabidiol (CBD) is a non-intoxicating component of cannabis that has shown therapeutic potential without abuse liability. This study investigated the effects of CBD on oxycodone self-administration and hyperalgesia in an animal model of chronic neuropathic pain. Adult male rats were trained to self-administer intravenous oxycodone (0.06 mg/kg/infusion). Subsequently, they underwent chronic constriction injury (CCI) of the sciatic nerve or received sham surgery. Paw withdrawal latency was measured using the Hargreaves test as an indicator of thermal pain sensitivity. CBD (0, 1, 3, and 10 mg/kg, IP) was administered before the self-administration sessions, and pain testing was conducted afterward. The rats acquired oxycodone self-administration, as indicated by more active than inactive lever presses. CCI surgery decreased the paw withdrawal latency, confirming the induction of neuropathic pain. CCI alone did not affect oxycodone self-administration, suggesting that neuropathic pain does not substantially influence opioid intake at the dose tested. Treatment with CBD reduced oxycodone self-administration in both the sham and CCI rats. Oxycodone self-administration in the CCI rats reversed the CCI-induced decrease in paw withdrawal latency. However, CBD did not affect the antinociceptive effect of oxycodone in CCI rats. Taken together, these findings demonstrate that CBD reduces oxycodone self-administration without affecting the antinociceptive effects of oxycodone in neuropathic pain. This study supports the potential of CBD to reduce opioid use and misuse, regardless of pain status.

  PublisherOA PDFDOI

• Meth inflames and stimulates your brain through similar pathways – new research offers potential avenue to treat meth addiction

  2026-01-09

  articleOpen accessSenior author
  PublisherDOI

• Enhancing Data Sharing for Preclinical Traumatic Brain Injury Research with Common Data Elements

  Zenodo (CERN European Organization for Nuclear Research) · 2026-02-12

  preprintOpen access

  Preclinical traumatic brain injury (TBI) research is critical for elucidating pathobiology, identifying biomarkers, and developing potential therapies that would not be possible through clinical research alone. However, successful translation of preclinical results to the clinic has been problematic due to multiple factors, including a failure to consistently replicate preclinical data between multiple laboratories. In part, the replicability problem is due to insufficient rigor and transparency and lack of standardized, common data reporting formats. The PRE-Clinical Interagency reSearch resourcE-TBI (PRECISE-TBI), is a multi-agency funded project established in 2021 to develop cross-cutting resources, including instituting a usable common data element (CDE) framework to help tackle this problem. Development of a central preclinical CDE resource will parallel clinical efforts and define a minimal list of variables that have been designated as both common and important for replication by domain experts across the neurotrauma research community. Using a common, structured data format that unifies the reporting of common methods and outcome variables will increase transparency and rigor across the field and enhance data sharing for reuse. We provide an update on these efforts, with reference to a minimum set of common variables for injury models, behavioral tasks, biomarkers, and magnetic resonance imaging and spectroscopy data acquisition. We highlight CDE use using a series of case studies that exemplify how data can be mapped to CDEs both prospectively and retrospectively. These use cases inform both researchers and data scientists about real-world challenges and serve as the basis for iterative improvements as CDE use evolves.

  PublisherDOI

• Peripheral macrophages and T-cells accumulate in the degenerating optic tract after repetitive head impact

  Brain Behavior and Immunity · 2026-02-23

  articleOpen access

  • Repetitive head impacts induce optic tract –specific white matter pathology. • Blood Brain Barrier (BBB) disruption at the optic nerve facilitates peripheral immune cell entry. • Infiltrating peripheral F4/80 + macrophages, CD4 + and CD8 + T-cells also accumulate in the optic tract alongside activated microglia. • Elevated pro-inflammatory cytokines TNFα and IL-1β, together with complement C3 and chemoattractants Ccl2, Ccl5, Cxcl3, and Cxcl10, suggest synergistic interactions between innate and peripheral inflammatory cascades. • DTI and fMRI detect progressive structural and functional tract damage with clinical relevance. Chronic white matter inflammation is a feature of traumatic brain injury (TBI), persisting for years in humans and consistently observed in rodent models of repetitive mild TBI. Here, we use a high-frequency head impact (HFHI, 5 impacts per day, over 6 consecutive days) model to investigate neuroimmune responses in the optic tract, a white matter region particularly vulnerable to primary injury-induced degeneration. To capture a comprehensive view of pathology, we integrated immunohistochemistry, digital spatial proteomics, transcriptomic profiling, and BBB assessments with non-invasive imaging modalities, including diffusion tensor imaging (DTI) and functional MRI (fMRI). HFHI elicited a robust and sustained inflammatory response specifically within the optic tract, marked by elevated IBA1 + and CD68 + expression detectable from the acute phase and persisting for at least 3 m post-injury. Characterization of these IBA1 + cells revealed a strong F4/80 + phenotype, indicative of infiltrating peripheral macrophages. Concurrent with this, a transient blood brain barrier (BBB) disruption was observed at the optic nerve, potentially facilitating acute peripheral immune cell entry. We identified the recruitment of CD4 + and CD8 + T cells to the optic tract, with digital spatial proteomic signatures revealing Granzyme B and CTLA4 expression, indicative of both regulatory and cytotoxic immune activity. Transcriptomic analyses further suggest polarization toward CD4 + Th1 and CD8 + Tc1 subsets, as evidenced by increased expression of T-bet and IFNγ. Chronic elevations of pro-inflammatory cytokines TNFα and IL-1β, complement component C3, and the chemoattractants Ccl2, Ccl5, Cxcl3, and Cxcl10 further suggest that synergistic interactions between innate and peripheral inflammatory cascades contribute to white matter degeneration after repetitive head impact. Diffusion tensor imaging and fMRI reveal reductions in fractional anisotropy and disrupted optic tract–visual cortex connectivity, indicating functional consequences of this tract-specific immune activation. Importantly, DTI and fMRI provide sensitive, translational readouts of this neuroimmune pathology, with potential relevance to traumatic optic neuropathy and visual dysfunction in clinical populations. These findings support the potential of targeted immune modulation within the optic tract as a therapeutic approach to target this white matter specific injury.

  PublisherDOI

• Enhancing Data Sharing for Preclinical Traumatic Brain Injury Research with Common Data Elements

  Open MIND · 2026-02-12

  preprint

  Preclinical traumatic brain injury (TBI) research is critical for elucidating pathobiology, identifying biomarkers, and developing potential therapies that would not be possible through clinical research alone. However, successful translation of preclinical results to the clinic has been problematic due to multiple factors, including a failure to consistently replicate preclinical data between multiple laboratories. In part, the replicability problem is due to insufficient rigor and transparency and lack of standardized, common data reporting formats. The PRE-Clinical Interagency reSearch resourcE-TBI (PRECISE-TBI), is a multi-agency funded project established in 2021 to develop cross-cutting resources, including instituting a usable common data element (CDE) framework to help tackle this problem. Development of a central preclinical CDE resource will parallel clinical efforts and define a minimal list of variables that have been designated as both common and important for replication by domain experts across the neurotrauma research community. Using a common, structured data format that unifies the reporting of common methods and outcome variables will increase transparency and rigor across the field and enhance data sharing for reuse. We provide an update on these efforts, with reference to a minimum set of common variables for injury models, behavioral tasks, biomarkers, and magnetic resonance imaging and spectroscopy data acquisition. We highlight CDE use using a series of case studies that exemplify how data can be mapped to CDEs both prospectively and retrospectively. These use cases inform both researchers and data scientists about real-world challenges and serve as the basis for iterative improvements as CDE use evolves.

  DOI

• Dissociable, species-specific impact of Aβ on static and dynamic functional connectomes

  bioRxiv (Cold Spring Harbor Laboratory) · 2026-04-29

  articleOpen accessSenior author

  Temporal dynamics in functional connectomes provide a physiologically grounded signature of 'hidden' pathologies during preclinical stages of Alzheimer's disease (AD). We evaluated the effect of beta-amyloid (Aβ) on dynamic functional connectomes in transgenic mice and human subjects. Functional magnetic resonance images (fMRI) were collected in two strains of Aβ mice. fMRI-derived connectomes were segmented into discrete states using a hidden Markov model, and network strength, efficiency, and transitivity were analyzed per state. Human fMRI-derived connectome measures were analyzed across 3 states. Static network measures were significantly different between Aβ mice and controls, the former having high values for strength, efficiency and clustering coefficient in anterior cingulate, hippocampus, and retrosplenium. Dynamic network measures were stable within-states in Aβ mice. Similarly, human subjects with high Aβ had high node strength in precuneus and temporoparietal areas compared to low Aβ. Conversely, high Aβ was associated with high switch rates, high fractional occupancy, and state dwell times. Also, global strength, efficiency, and transitivity were less stable within states in the high Aβ group. Our results indicate that static, but not dynamic, connectome strength, efficiency, and network integration are increased in Aβ mice, while dynamic network states appear less stable in human functional connectomes. This data supports a dissociable, species-specific impact of Aβ, with dynamic network alterations present in humans but not in Aβ mouse models, suggesting additional non-Aβ-driven influences on dynamic functional connectivity in preclinical AD.

  PublisherOA PDFDOI

• Multi-site, in vivo MRI dataset of brain diffusivity measures before and after harmonization, and atrophy measures following controlled cortical impact in male and female adult rats

  Zenodo (CERN European Organization for Nuclear Research) · 2025-12-15

  datasetOpen access

  Traumatic brain injury (TBI) research faces persistent challenges in data comparability and reproducibility, particularly in multi-center preclinical studies. Structured, interoperable datasets are essential to identify robust imaging biomarkers and validate cross-site findings. This dataset comprises 343 diffusion-weighted MRI scans from 186 male and female Sprague Dawley rats subjected to controlled cortical impact (CCI) or sham procedures at four independent research sites. Imaging was performed at 3 and 30 days post-injury using harmonized acquisition protocols and field strengths ranging from 7T to 11.7T. A standardized processing pipeline generated scalar diffusion maps (FA, MD, AD, and RD), anatomical templates, and voxel-wise z-score–based indices of injury. Both unharmonized and harmonized versions of the dataset are provided. Harmonization was performed using NeuroCombat for scalar volumes and multi-site template registration for voxel-level alignment. The dataset supports investigations into sex, post-injury timepoint, and injury effects in experimental TBI and provides a foundation for testing image harmonization methods, developing quantification tools for automated assessment of injury, and training machine learning models. The dataset is published in the FAIR² framework, with machine-actionable metadata, responsible AI indicators, and structured documentation to support ethical, reproducible, and AI-ready reuse.

  PublisherDOI

• Corrigendum to “Functional connectivity within sensorimotor cortical and striatal regions is regulated by sepsis in a sex-dependent manner” [NeuroImage 305 (2025) 120995]

  NeuroImage · 2025-01-19

  erratumOpen accessSenior authorCorresponding
  PublisherDOI

• Improved Injury Detection Through Harmonizing Multi-Site Neuroimaging Data after Experimental TBI: A Translational Outcomes Project in NeuroTrauma (TOP-NT) Consortium Study

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-04-20 · 1 citations

  preprintOpen access

  Abstract Multi-site neuroimaging studies have become increasingly common in order to generate larger samples of reproducible data to answer questions associated with smaller effect sizes. The data harmonization model NeuroCombat has been shown to remove site effects introduced by differences in site-related technical variance while maintaining group differences, yet its effect on improving statistical power in pre-clinical models of CNS disease is unclear. The present study examined fractional anisotropy data computed from diffusion weighted imaging data at 3 and 30 days post-controlled cortical impact injury from 184 adult rats across four sites as part of the Translational-Outcome-Project-in-Neurotrauma (TOP-NT) Consortium. Findings confirmed prior clinical reports that NeuroCombat fails to remove site effects in data containing a high proportion-of-outliers (>5%) and skewness, which introduced significant variation in non-outlier sites. After removal of one outlier site and harmonization using a global sham population, harmonization displayed an increase in effect size in data that displayed group level effects (p<0.01) in both univariate and voxel-level volumes of pathology. This was characterized by movement toward similar distributions in voxel measurements (Kolmogorov-Smirnov p<<0.001 to >0.01) and statistical power increases within the ipsilateral cortex. Harmonization improved statistical power and frequency of significant differences in areas with existing group differences, thus improving the ability to detect regions affected by injury rather than by other confounds. These findings indicate the utility of NeuroCombat in reproducible data collection, where biological differences can be accurately revealed to allow for greater reliability in multi-site neuroimaging studies. Significance Statement This project demonstrates the utility of NeuroCombat in reducing site effects in multi-site rodent imaging. We also demonstrate that harmonization improves the ability to distinguish between sham and injured rats at the voxel level and increase statistical power and effect size in areas of injury. Multi-center studies are becoming more common to allow for increased efficiency in data collection, and with conservative approaches and analysis into the datasets, NeuroCombat can be utilized to improve study reliability and reproducibility.

  PublisherOA PDFDOI

• Translational Outcomes Project in Neurotrauma (TOP-NT) Pre-Clinical Consortium Study: A Synopsis

  Journal of Neurotrauma · 2025-01-22 · 7 citations

  articleOpen access

  Traumatic brain injury (TBI) has long been a leading cause of death and disability, yet research has failed to successfully translate findings from the pre-clinical, animal setting into the clinic. One factor that contributes significantly to this struggle is the heterogeneity observed in the clinical setting where patients present with injuries of varying types, severities, and comorbidities. Modeling this highly varied population in the laboratory remains challenging. Given feasibility constraints, individual laboratories often focus on single injury types and are limited to an abridged set of outcome measures. Furthermore, laboratories tend to use different injury or outcome methodologies from one another, making it difficult to compare studies and identify which pre-clinical findings may be best suited for clinical translation. The NINDS-funded Translational Outcomes Project in Neurotrauma (TOP-NT) is a multi-site consortium designed to address the reproducibility, rigor, and transparency of pre-clinical development and validation of clinically relevant biomarkers for TBI. The current overview article provides a detailed description of the infrastructure and strategic approach undertaken by the consortium. We outline the TOP-NT strategy to address three goals: (1) selection and cross-center validation of biomarker tools, (2) development and population of a data infrastructure to allow for the sharing and reuse of pre-clinical, animal research following findable, accessible, interoperable, and reusable data guidelines, and (3) demonstration of feasibility, reproducibility, and transparency in conducting a multi-center, pre-clinical research trial for TBI biomarker development. The synthesized scientific analysis and results of the TOP-NT efforts will be the topic of future articles.

  PublisherOA PDFDOI

Recent grants

• NIH Grant R01DA019946

  NIH · $1.6M · 2013

• NIH Grant R21DA038009

  NIH · $411k · 2018

• NIH Grant P50AG047266

  NIH · $14.5M · 2021

• Imaging Networks of Affective Behaviors and Dopamine in Alzheimer's Disease

  NIH · $406k · 2020–2024

Frequent coauthors

• Kenneth Blum

  Wright State University

  208 shared

• Luis M. Colon‐Perez

  University of North Texas

  72 shared

• Rajendra D. Badgaiyan

  University School

  58 shared

• Mark S. Gold

  57 shared

• Pablo D. Pérez

  43 shared

• Marjory Pompilus

  University of Florida

  38 shared

• Jasenka Zubcevic

  University of Toledo

  34 shared

• Adriaan W. Bruijnzeel

  University of Florida

  32 shared

Education

• Ph.D.

  University of Puerto Rico Medical School

• Other

  University of Massachusetts Medical Center

Awards & honors

• UF College of Medicine Term Professor (2018-2019)
• University of Florida, College of Medicine Exemplary Teacher…
• Elected Research Scientist Member, National Hispanic Science…
• Faculty Award, National Hispanic Science Network (2009)
• Suzannah Bliss Tieman Award for Research, Northeast Undergra…