Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Video

Updated: Mar 14, 2026

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

16.4K

Mapping face encoding using functional MRI in multiple sclerosis across disease phenotypes.

Maria A Rocca1,2, Laura Vacchi1, Mariaemma Rodegher2

  • 1Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Via Olgettina, 60, 20132, Milan, Italy.

Brain Imaging and Behavior
|October 8, 2016
PubMed
Summary

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

CT Quantification of Intraventricular Hemorrhage Volume in Poor-Grade Aneurysmal Subarachnoid Hemorrhage: Impact on Mortality and Long-Term Disability.

Neurocritical care·2026
Same author

Anti-CD20 Therapies in Pediatric Acquired Demyelinating Syndromes: Evidence Across MS, AQP4-IgG-Positive NMOSD and MOGAD.

CNS drugs·2026
Same author

An update on the differential diagnosis of migraine in adults: when and how neuroimaging makes the difference.

Expert review of neurotherapeutics·2026
Same author

Affective and cognitive theory of mind and associated brain functional alterations in frontotemporal dementia.

Brain communications·2026
Same author

Distinct age-related pattern of mitochondrial somatic mutations across multiple sclerosis phenotypes.

Journal of neurology·2026
Same author

Early deterioration in isolated pontine stroke: predictors and outcomes.

Journal of neurology·2026
Same journal

Normalization method for relative cerebral blood flow influences sex and cognitive status effects in nondemented older adults.

Brain imaging and behavior·2026
Same journal

Lack of association of the 5-HTTLPR polymorphism and brain serotonin transporter or receptor in healthy individuals: bayesian and frequentist meta-analyses.

Brain imaging and behavior·2026
Same journal

Prediction modeling in transdiagnostic risk: results from the PROCAN study.

Brain imaging and behavior·2026
Same journal

Impact of modifiable lifestyle factors on dementia subtypes and brain structural changes across KDIGO risk categories in the UK biobank.

Brain imaging and behavior·2026
Same journal

Disrupted white matter functional connectivity in post-stroke cognitive impairment: Insights from resting-state fMRI.

Brain imaging and behavior·2026
Same journal

Neural correlates of acceptance and commitment therapy in major depressive disorder: a task-based fMRI study.

Brain imaging and behavior·2026
See all related articles
This summary is machine-generated.

Multiple sclerosis (MS) patients show altered brain activity during face encoding (FE). Early MS stages involve increased visual area recruitment, while later stages show frontal lobe involvement, correlating with disease severity.

Area of Science:

  • Neuroimaging
  • Neurology
  • Cognitive Neuroscience

Background:

  • Multiple sclerosis (MS) is a demyelinating disease affecting the central nervous system.
  • Understanding the neural underpinnings of cognitive deficits in MS is crucial for patient management.
  • Face encoding (FE) performance and its neural correlates may be altered in MS.

Purpose of the Study:

  • To investigate the behavioral and functional magnetic resonance imaging (fMRI) correlates of face encoding (FE) in multiple sclerosis (MS) patients.
  • To examine how FE-related brain activity varies across different MS clinical phenotypes (clinically isolated syndromes - CIS, relapsing-remitting MS - RRMS, and secondary progressive MS - SPMS).
  • To correlate fMRI findings with clinical, cognitive-executive performance, and structural MRI measures of disease-related damage.
Keywords:
Attentive-executive domainClinical phenotypesFace encodingMultiple sclerosisfMRI

More Related Videos

Functional Mapping with Simultaneous MEG and EEG
06:04

Functional Mapping with Simultaneous MEG and EEG

Published on: June 14, 2010

18.5K
Magnetic Resonance Imaging of Multiple Sclerosis at 7.0 Tesla
08:51

Magnetic Resonance Imaging of Multiple Sclerosis at 7.0 Tesla

Published on: February 19, 2021

10.0K

Related Experiment Videos

Last Updated: Mar 14, 2026

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

16.4K
Functional Mapping with Simultaneous MEG and EEG
06:04

Functional Mapping with Simultaneous MEG and EEG

Published on: June 14, 2010

18.5K
Magnetic Resonance Imaging of Multiple Sclerosis at 7.0 Tesla
08:51

Magnetic Resonance Imaging of Multiple Sclerosis at 7.0 Tesla

Published on: February 19, 2021

10.0K

Main Methods:

  • fMRI during a face encoding (FE) task was administered to 75 MS patients (CIS, RRMS, SPMS) and 22 healthy controls (HC).
  • Analysis correlated fMRI activity during FE with behavioral, clinical, neuropsychological, and structural MRI data.
  • Brain activation and deactivation patterns were compared across patient groups and HC.

Main Results:

  • All participants activated face perception/encoding networks and deactivated default-mode network areas.
  • MS patients exhibited abnormal patterns of increased/decreased activation and deactivation compared to HC.
  • CIS patients showed increased recruitment of posterior-visual areas; RRMS patients showed greater activation in thalami, para-hippocampal gyri, and anterior cingulum compared to CIS/SPMS; SPMS patients demonstrated increased frontal lobe recruitment.
  • Abnormal activation patterns correlated significantly with clinical, cognitive, and structural MRI measures.

Conclusions:

  • Face encoding network abnormalities are present in MS and differ across clinical phenotypes.
  • Early MS stages (CIS) are characterized by compensatory hyperactivation in visual processing areas.
  • Later MS stages (SPMS) show aberrant functional recruitment in frontal regions, potentially contributing to clinical symptom severity.