Investigating microstructural variation in the human hippocampus using non-negative matrix factorization

In this work we use non-negative matrix factorization to identify patterns of microstructural variance in the human hippocampus. We utilize high-resolution structural and diffusion magnetic resonance imaging data from the Human Connectome Project to query hippocampus microstructure on a multivariate, voxelwise basis. Application of non-negative matrix factorization identifies spatial components (clusters of voxels sharing similar covariance patterns), as well as subject weightings (individual variance across hippocampus microstructure). By assessing the stability of spatial components as well as the accuracy of factorization, we identified 4 distinct microstructural components. Furthermore, we quantified the benefit of using multiple microstructural metrics by demonstrating that using three microstructural metrics (T1-weighted/T2-weighted signal, mean diffusivity and fractional anisotropy) produced more stable spatial components than when assessing metrics individually. Finally, we related individual subject weightings to demographic and behavioural measures using a partial least squares analysis. Through this approach we identified interpretable relationships between hippocampus microstructure and demographic and behavioural measures. Taken together, our work suggests non-negative matrix factorization as a spatially specific analytical approach for neuroimaging studies and advocates for the use of multiple metrics for data-driven component analyses

Placebo stimulates neuroplasticity in depression: implications for clinical practice and research

Neither psychological nor neuroscientific investigations have been able to fully explain the paradox that placebo is designed to be inert in randomized controlled trials (RCTs), yet appears to be effective in evaluations of clinical interventions in all fields of medicine and alternative medicine. This article develops the Neuroplasticity Placebo Theory, which posits that neuroplasticity in fronto-limbic areas is the unifying factor in placebo response (seen in RCTs) and placebo effect (seen in clinical interventions) where it is not intended to be inert. Depression is the disorder that has the highest placebo response of any medical condition and has the greatest potential for understanding how placebos work: recent developments in understanding of the pathophysiology of depression suggest that fronto-limbic areas are sensitized in depression which is associated with a particularly strong placebo phenomenon. An innovative linkage is made between diverse areas of the psychology and the translational psychiatry literature to provide supportive evidence for the Neuroplasticity Placebo Theory. This is underpinned by neuro-radiological evidence of fronto-limbic change in the placebo arm of antidepressant trials. If placebo stimulates neuroplasticity in fronto-limbic areas in conditions other than depression - and results in a partially active treatment in other areas of medicine - there are far reaching consequences for the day-to-day use of placebo in clinical practice, the future design of RCTs in all clinical conditions, and existing unwarranted assertions about the efficacy of antidepressant medications. If fronto-limbic neuroplasticity is the common denominator in designating placebo as a partially active treatment, the terms placebo effect and placebo response should be replaced by the single term “placebo treatment.

Observing plasticity of the auditory system: Volumetric decreases along with increased functional connectivity in aspiring professional musicians

Playing music relies on several sensory systems and the motor system, and poses strong demands on control processes, hence, offering an excellent model to study how experience can mold brain structure and function. Although most studies on neural correlates of music expertise rely on cross-sectional comparisons, here we compared within-person changes over time in aspiring professionals intensely preparing for an entrance exam at a University of the Arts to skilled amateur musicians not preparing for a music exam. In the group of aspiring professionals, we observed gray-matter volume decrements in left planum polare, posterior insula, and left inferior frontal orbital gyrus over a period of about 6 months that were absent among the amateur musicians. At the same time, the left planum polare, the largest cluster of structural change, showed increasing functional connectivity with left and right auditory cortex, left precentral gyrus, left supplementary motor cortex, left and right postcentral gyrus, and left cingulate cortex, all regions previously identified to relate to music expertise. In line with the expansion–renormalization pattern of brain plasticity (Wenger et al., 2017a. Expansion and renormalization of human brain structure during skill acquisition. Trends Cogn Sci. 21:930–939.), the aspiring professionals might have been in the selection and refinement period of plastic change

Studying neuroanatomy using MRI

The study of neuroanatomy using imaging enables key insights into how our brains function, are shaped by genes and environment, and change with development, aging, and disease. Developments in MRI acquisition, image processing, and data modelling have been key to these advances. However, MRI provides an indirect measurement of the biological signals we aim to investigate. Thus, artifacts and key questions of correct interpretation can confound the readouts provided by anatomical MRI. In this review we provide an overview of the methods for measuring macro- and mesoscopic structure and inferring microstructural properties; we also describe key artefacts and confounds that can lead to incorrect conclusions. Ultimately, we believe that, though methods need to improve and caution is required in its interpretation, structural MRI continues to have great promise in furthering our understanding of how the brain works

Inter- and intra-individual variation in brain structural-cognition relationships in aging

The sources of inter- and intra-individual variability in age-related cognitive decline remain poorly understood. We examined the association between 20-year trajectories of cognitive decline and multimodal brain structure and morphology in older age. We used the Whitehall II Study, an extensively characterised cohort with 3T brain magnetic resonance images acquired at older age (mean age = 69.52 ± 4.9) and 5 repeated cognitive performance assessments between mid-life (mean age = 53.2 ±4.9 years) and late-life (mean age = 67.7 ± 4.9). Using non-negative matrix factorization, we identified 10 brain components integrating cortical thickness, surface area, fractional anisotropy, and mean and radial diffusivities. We observed two latent variables describing distinct brain-cognition associations. The first describes variations in 5 structural components associated with low mid-life performance across multiple cognitive domains, decline in reasoning, but maintenance of fluency abilities. The second describes variations in 6 structural components associated with low mid-life performance in fluency and memory, but retention of multiple abilities. Expression of latent variables predicts future cognition 3.2 years later (mean age = 70.87 ± 4.9). This data-driven approach highlights brain-cognition relationships wherein individuals degrees of cognitive decline and maintenance across diverse cognitive functions are both positively and negatively associated with markers of cortical structure

Studying neuroanatomy using MRI

The study of neuroanatomy using imaging enables key insights into how our brains function, are shaped by genes and environment, and change with development, aging, and disease. Developments in MRI acquisition, image processing, and data modelling have been key to these advances. However, MRI provides an indirect measurement of the biological signals we aim to investigate. Thus, artifacts and key questions of correct interpretation can confound the readouts provided by anatomical MRI. In this review we provide an overview of the methods for measuring macro- and mesoscopic structure and inferring microstructural properties; we also describe key artefacts and confounds that can lead to incorrect conclusions. Ultimately, we believe that, though methods need to improve and caution is required in its interpretation, structural MRI continues to have great promise in furthering our understanding of how the brain works

Investigating metabolic, vascular and structural neuroplasticity in healthy and diseased brain using advanced neuroimaging techniques

The brain’s lifelong capacity for reorganization is termed ‘plasticity’. It relies on molecular signalling translated into long lasting modifications. MRI has been widely used to assess neuroplasticity in vivo, showing brain’s ability to undergo functional and structural reorganization. However, there is a lack of understanding of the physiological events supporting neuroplasticity and advanced MRI techniques could help in the investigation of the biological meaning of these events and their alterations during neuroinflammation. This thesis has two main aims. Neuroscientifically, it aims to better understand mechanisms supporting neuroplasticity in the healthy and diseased brain. Methodologically, it aims to explore new MRI approaches to the study of neuroplasticity. The early experiments investigate the mechanisms underlying long-term neuroplasticity in MS. The studies then aim to elucidate the changes in brain energetics underlying adaptation in healthy and MS brain using calibrated fMRI. I explored new approaches to analyse the relative oxygen consumption during task adaptation in the same population. A new task to study short-term neuroplasticity was validated and used to demonstrate changes in resting blood flow after task execution. The same task was used to investigate the relationship between GM myelination and functional activity during task execution. Overall, we show the feasibility of using quantitative methods to study neuroplasticity, encouraging their application to improve biological interpretation in imaging studies. Our results highlight the importance of studying the brain as a network and the advantages of integrating different MRI modalities. We also show that our methods are applicable to MS populations, despite the observed metabolic impairment with neuroinflammation. Our methods may, in future, contribute to the study of disease progression and to the development of targeted interventions to limit the damage of inflammation