ABSTRACT
Neural plasticity is a major factor driving cortical reorganization after stroke. We here tested whether repetitively enhancing motor cortex plasticity by means of intermittent theta-burst stimulation (iTBS) prior to physiotherapy might promote recovery of function early after stroke. Functional magnetic resonance imaging (fMRI) was used to elucidate underlying neural mechanisms. Twenty-six hospitalized, first-ever stroke patients (time since stroke: 1-16 days) with hand motor deficits were enrolled in a sham-controlled design and pseudo-randomized into 2 groups. iTBS was administered prior to physiotherapy on 5 consecutive days either over ipsilesional primary motor cortex (M1-stimulation group) or parieto-occipital vertex (control-stimulation group). Hand motor function, cortical excitability, and resting-state fMRI were assessed 1 day prior to the first stimulation and 1 day after the last stimulation. Recovery of grip strength was significantly stronger in the M1-stimulation compared to the control-stimulation group. Higher levels of motor network connectivity were associated with better motor outcome. Consistently, control-stimulated patients featured a decrease in intra- and interhemispheric connectivity of the motor network, which was absent in the M1-stimulation group. Hence, adding iTBS to prime physiotherapy in recovering stroke patients seems to interfere with motor network degradation, possibly reflecting alleviation of post-stroke diaschisis.
Subject(s)
Motor Cortex/physiopathology , Neuronal Plasticity/physiology , Stroke/physiopathology , Stroke/therapy , Transcranial Magnetic Stimulation/methods , Aged , Aged, 80 and over , Arm/physiopathology , Female , Hand Strength/physiology , Humans , Inpatients , Magnetic Resonance Imaging , Male , Motor Cortex/diagnostic imaging , Movement Disorders/diagnostic imaging , Movement Disorders/etiology , Movement Disorders/physiopathology , Movement Disorders/therapy , Neural Pathways/diagnostic imaging , Neural Pathways/physiopathology , Physical Therapy Modalities , Recovery of Function/physiology , Rest , Single-Blind Method , Stroke/complications , Stroke/diagnostic imaging , Treatment OutcomeABSTRACT
Conventional mass-univariate analyses have been previously used to test for group differences in neural signals. However, machine learning algorithms represent a multivariate decoding approach that may help to identify neuroimaging patterns associated with functional impairment in "individual" patients. We investigated whether fMRI allows classification of individual motor impairment after stroke using support vector machines (SVMs). Forty acute stroke patients and 20 control subjects underwent resting-state fMRI. Half of the patients showed significant impairment in hand motor function. Resting-state connectivity was computed by means of whole-brain correlations of seed time-courses in ipsilesional primary motor cortex (M1). Lesion location was identified using diffusion-weighted images. These features were used for linear SVM classification of unseen patients with respect to motor impairment. SVM results were compared with conventional mass-univariate analyses. Resting-state connectivity classified patients with hand motor deficits compared with controls and nonimpaired patients with 82.6-87.6% accuracy. Classification was driven by reduced interhemispheric M1 connectivity and enhanced connectivity between ipsilesional M1 and premotor areas. In contrast, lesion location provided only 50% sensitivity to classify impaired patients. Hence, resting-state fMRI reflects behavioral deficits more accurately than structural MRI. In conclusion, multivariate fMRI analyses offer the potential to serve as markers for endophenotypes of functional impairment.
Subject(s)
Brain Mapping , Brain/pathology , Machine Learning , Movement Disorders/etiology , Movement Disorders/pathology , Stroke/complications , Aged , Aged, 80 and over , Brain/blood supply , Disability Evaluation , Female , Humans , Image Processing, Computer-Assisted , Male , Middle Aged , Neural Pathways/blood supply , Neural Pathways/pathology , Neuroimaging , Rest , Severity of Illness IndexABSTRACT
BACKGROUND: Animal models of anxiety disorders emphasize the crucial role of locus ceruleus-noradrenergic (norepinephrine, NE) signaling, the basolateral amygdala (BLA) and their interactions in the expression of anxiety-like behavioral responses to stress. Despite clinical evidence for the efficacy of a ß-noradrenergic receptor blockade with propranolol in the alleviation of anxiety symptoms and the secondary prevention of post traumatic stress disorder, preclinical evidence for a ß-noradrenergic modulation of BLA activity in humans is missing. METHOD: We combined functional magnetic resonance imaging in healthy volunteers with probabilistic mapping of intra-amygdalar responses to fearful, neutral and happy facial expressions to test the hypothesis that a ß-noradrenergic receptor blockade with propranolol would inactivate the BLA. RESULTS: Consistent with our a priori hypothesis, propranolol diminished BLA responses to facial expressions, independent of their emotional valence. The absence of activity changes in probabilistically defined visual control regions underscores the specific action of propranolol in the BLA. CONCLUSIONS: Our findings provide the missing link between the anxiolytic potential of propranolol and the biological basis of ß-noradrenergic activation in the human BLA as a key target for the pharmacological inhibition of anxiety neurocircuitry. Moreover, our findings add to emerging evidence that NE modulates both the reactivity (sensitivity) and the operating characteristics (specificity) of the BLA via ß-noradrenergic receptors.
