The Neuroimaging and Modulation Lab (NIMLAB), directed by Dr.
John E. Desmond, is part of the Cognitive
Neuroscience Division of the Department
of Neurology at the Johns Hopkins
University School of Medicine.
The laboratory investigates neural correlates of cognition and behavior using neuroimaging
methods such as functional magnetic
resonance imaging (fMRI) and neuromodulation techniques such as transcranial magnetic stimulation
• The contributions of the cerebellum, and
cerebro-cerebellar circuits, to cognition. The cerebellum has
traditionally been viewed as a structure involved in motor
coordination. However, neuroimaging and patient studies have revealed
unexpected cerebellar involvement in cognitive performance beyond motor
behavior. We are specifically interested in cerebellar contributions to
verbal working memory performance.
aging in humans affects neural systems that are important for
associative memory. These
investigations pay special attention to two systems particularly
important for classical conditioning, the medial temporal lobe and
The implications of this research are that simple eyeblink
conditioning procedures may provide reliable indications of the
integrity of cerebellar and medial temporal lobe structures.
Such indications could be particularly useful for assessing
brain dysfunction in disorders such as Alzheimer’s Disease.
• Integration of transcranial magnetic stimulation with
functional MRI. TMS and fMRI are complementary methods, because
fMRI can reveal which regions of the brain activate during a cognitive
task, whereas TMS can assess which of those activations are necessary
• Clinical applications of functional MRI, including
characterization of altered brain activation due to disease, surgical
planning, and diagnosis. An important aspect of fMRI for clinical
purposes is that it is powerful enough to assess brain activations at
the level of the individual patient as well as at the group level.
• Methodological aspects of functional MRI, such as
estimating statistical power for group analyses. Such information can
be used for designing neuroimaging studies with the appropriate sample
size for detecting significant differences between conditions, or
significant differences between populations of subjects.