NeuroImage. Clinical
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NeuroImage. Clinical · Jan 2019
ReviewAddressing heterogeneity (and homogeneity) in treatment mechanisms in depression and the potential to develop diagnostic and predictive biomarkers.
It has been 10 years since machine learning was first applied to neuroimaging data in psychiatric disorders to identify diagnostic and prognostic markers at the level of the individual. Proof of concept findings in major depression have since been extended in international samples and are beginning to include hundreds of samples from multisite data. Neuroimaging provides the unique capability to detect an acute depressive state in major depression, while we would not expect perfect classification with current diagnostic criteria which are based solely on clinical features. ⋯ Irrespective of the mechanism, the capacity for response will moderate the outcome, which includes inherent models of interpersonal relationships that could be associated with genetic risk load and represented by patterns of functional and structural neural correlates as a predictive biomarker. We propose that methods which directly address heterogeneity are essential and that a synergistic combination could bring together data-driven inductive and symptom-based deductive approaches. Through this iterative process, major depression can develop from being syndrome characterized by a collection of symptoms to a disease with an identifiable pathophysiology.
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NeuroImage. Clinical · Jan 2019
Randomized Controlled TrialEffects of high- and low-frequency repetitive transcranial magnetic stimulation on motor recovery in early stroke patients: Evidence from a randomized controlled trial with clinical, neurophysiological and functional imaging assessments.
Repetitive transcranial magnetic stimulation (rTMS) can modulate cortical excitability, and may be beneficial for motor recovery after stroke. However, the neuroplasticity effects of rTMS have not been thoroughly investigated in the early stage after stroke. ⋯ HF- and LF-rTMS can both improve motor function by modulating motor cortical activation in the early phase of stroke.
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NeuroImage. Clinical · Jan 2019
Brainstem pathology in amyotrophic lateral sclerosis and primary lateral sclerosis: A longitudinal neuroimaging study.
Brainstem pathology is a hallmark feature of ALS, yet most imaging studies focus on cortical grey matter alterations and internal capsule white matter pathology. Brainstem imaging in ALS provides a unique opportunity to appraise descending motor tract degeneration and bulbar lower motor neuron involvement. ⋯ ALS and PLS patients exhibit considerable brainstem atrophy compared to both disease- and healthy controls. Volume reductions in ALS and PLS are dominated by medulla oblongata pathology, but pontine atrophy can also be detected. In ALS, vertex analyses confirm the flattening of the medullary pyramids bilaterally in comparison to healthy controls and widespread pontine shape deformations in contrast to PLS. The ALS cohort exhibit bilateral density reductions in the mesencephalic crura in contrast to healthy controls, central pontine atrophy compared to disease controls, peri-aqueduct mesencephalic and posterior pontine changes in comparison to PLS patients. CONCLUS: ions: Computational brainstem imaging captures the degeneration of both white and grey matter components in ALS. Our longitudinal data indicate progressive brainstem atrophy over time, underlining the biomarker potential of quantitative brainstem measures in ALS. At a time when a multitude of clinical trials are underway worldwide, there is an unprecedented need for accurate biomarkers to monitor disease progression and detect response to therapy. Brainstem imaging is a promising addition to candidate biomarkers of ALS and PLS.
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NeuroImage. Clinical · Jan 2019
Examining resting-state functional connectivity in first-episode schizophrenia with 7T fMRI and MEG.
Schizophrenia is often characterized by dysconnections in the brain, which can be estimated via functional connectivity analyses. Commonly measured using resting-state functional magnetic resonance imaging (fMRI) in order to characterize the intrinsic or baseline function of the brain, fMRI functional connectivity has significantly contributed to the understanding of schizophrenia. However, these measures may not capture the full extent of functional connectivity abnormalities in schizophrenia as fMRI is temporally limited by the hemodynamic response. ⋯ In fMRI, patients demonstrated hyperconnectivity between subcortical and auditory networks, as well as hypoconnectivity between interhemispheric homotopic sensorimotor network components. In MEG, patients demonstrated hypoconnectivity between sensorimotor and task positive networks in the delta frequency band. Results not only support the dysconnectivity hypothesis of schizophrenia, but also suggest the importance of jointly examining multimodal neuroimaging data as critical disorder-related information may not be detectable in a single modality alone.
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NeuroImage. Clinical · Jan 2019
Differential medial temporal lobe and default-mode network functional connectivity and morphometric changes in Alzheimer's disease.
We report group level differential detection of medial temporal lobe resting-state functional connectivity disruption and morphometric changes in the transition from cognitively normal to early mild cognitive impairment in an age-, education- and gender-matched 105 subjects Alzheimer's Disease Neuroimaging Initiative dataset. In mild Alzheimer's Disease, but not early mild cognitive impairment, characteristic brain atrophy was detected in FreeSurfer estimates of subcortical and hippocampal subfield volumes and cortical thinning. ⋯ Key findings include: a) focal, bilaterally symmetric spatial organization of affected medial temporal lobe regions; b) mutual hyperconnectivity involving ventral medial temporal lobe structures (temporal pole, uncus); c) dorsal medial temporal lobe hypoconnectivity with anterior and posterior midline default-mode network nodes; and d) a complex pattern of transient and persistent changes in hypo- and hyper-connectivity across Alzheimer's Disease stages. These findings position medial temporal lobe resting state functional connectivity as a candidate biomarker of an Alzheimer's Disease pathophysiological cascade, potentially in advance of clinical biomarkers, and coincident with biomarkers of the earliest stages of Alzheimer's neuropathology.