Introduction:

The majority of autoimmune disorders like cancers are progressive and fatal. The exceptions seem to be only autoimmune demyelinating disorders and its most common type, Multiple Sclerosis (MS) that in majority of cases have a relapsing-remitting course and a better prognosis. Although MS at the onset could manifest as a clinically isolated syndrome, it soon takes the form of either relapsing-remitting or progressive (primary). Later on in the course of illness a minority of the relapsing-remitting MS (RRMS) may change its course to progressive and poor prognosis and this group is classified secondary progressive MS (SPMS) against the primary progressive MS (PPMS) that has a progressive course from the onset (1)

 Unfortunately it has not yet been sufficiently questioned and studied why MS and other similar autoimmune demyelinating disorders possess could have a relapsing-remitting course and a better prognosis, while the nature of autoimmune disorders are generally progressive with morbidity and mortality. Autoimmune disorders that like cancers as detailed in other articles on this site are the results of microbial invasions, and no microbes such as bacteria or viruses invade our beings to fool around, remit and relapse. So then why if autoimmune demyelinating disorders such as MS are also the byproducts of microbial invasions such as EBV (Epstein Barr Virus), have a remission and relapse course while the invasion targets our most precious organ, the brain. In fact the answer when probe to it well lies in our brain, not the invaders. It’s the brain that protects itself and fights back against the invasion and strives to undo the damage. This interesting fact that so far seems to happen only in the brain and at least to the myelin sheaths of the brain is a very new discovery in the very recent years. But this has not yet been applied in the explanation of the relapsing-remitting course of autoimmune demyelinating disorders such as MS, and this article could be the first.

The Brain fights back:

While the great majority of brain cells are essentially stable throughout life, oligodendrocyte precursor cells (OPCs) that generate new oligodendrocytes hence new myelin sheaths have been observed widespread in the brain even in adult life (2). The myelin or myelin sheaths that cover the nerve cell axons act as the nervous system wires for the conduction of information from one neuron to the other, or one area of the brain to the other. The white matters or the highways of the brain are basically made of the myelin and myelin sheaths that are the targets of microbial invasions in the autoimmune demyelinating disorders such as MS. Generally the process of myelination or the generation of myelin and myelin sheaths that start early in the third trimester, continues throughout adolescence and early adult life that contribute and correspond to the continuation of the general brain development until mid-20s (3). The reason or need for the long development of the brain through ongoing myelination is building its widespread communication infrastructures for learning, skills developments and other higher cortical functions that create cognitive and skills maturity.  

Our brain that is the only organ of the body that its growth or development continues until mid-20s would remain stable or stationary from then on generally if no efforts in further learning or skill developments happen on the part of the individual or demands from his or her environment. In fact it has been shown that while the human white matter oligodendrocytes show very little turnover during life, the gray matter oligodendrocytes, that link more with higher cognitive functions, continue to be added until the fourth decade. In other word the brain like the rest of the body organs would stop in its development or regeneration without any stimulation or trigger. Learning new subjects, skills, or use of the brain actively in problem solving, inventions and creations triggers the new brain development locally corresponding to the specific area of the brain that has been stimulated (4-10)

 In the case of invasion or damage of the brain, it has been known for long in TBI (Traumatic Brain Injury) and stroke that the intact parts of the brain over time take over the tasks of the damaged parts by neuro-regeneration and re-myelination. Myelin degeneration that is the pathognomonic of autoimmune demyelinating disorders such as MS and leads to reduction in the existing mature or adult oligodendrocyte and the number of internodes on the myelin sheath in animal studies have been shown to be associated with debris accumulation in microglia that trigger new myelin regeneration or re-myelination through the birth of new oligodendrocyts from oligodendrocyte precursor cells (OPCs) in live imaging studies. The new oligodendrocyts and internodes that soon become stable and integrate with the existing cells and nodes have been shown to enhance by neural activity and young brain age. That is why at the extreme old age or inactive brain, degeneration and engulfment of myelin by microglia occur with no new regeneration, hence cognitive and other high cortical functions decline (11-14).

The role of cortical re-myelination in disease, specially autoimmune demyelinating disorders such as MS seems to contribute to the relapsing-remitting course of these illnesses, specifically when noticing that the new individual oligodendrocytes form their internodes within a few hours. This well explains the autoimmune demyelinating disorders and MS’ fluctuating symptoms and overall their better prognosis compared to any other autoimmune disorders. The cortical more than the spinal cord’s myelin is correlated with the synaptic and structural plasticity of the brain so more stimulated for regeneration by neural or cortical activities. Therefore it could be plausible in the autoimmune demyelinating disorders such as MS, other than immune fostering treatments, any brain cortical activities that could prompt re-myelination could enhance remission (7,8,10,15).  

 The onset of progressive MS may be more relevant to the patient’s age than the duration of a pre-progression relapsing disease course. About one third of RRMS patients may never develop a progressive disease course. Age-of-progression-onset is similar between BOPMS and PPMS. Switching from relapses to progression in MS is an age-dependent process independent of pre-progression disease course or disease duration. Almost all patients with MS develop progressive disease course before age 75 (or by 35 years post-MS onset). Recent imaging studies suggest that myelination of the compact white matter ends by the 4^th decade followed by a slow degeneration in the white matter tracts in the following decades. Continued white matter tract repair (myelin and axons) may compensate for degeneration in previously damaged areas of the CNS until the end of 4^th decade. An advancing degenerative phenotype afterwards is possibly reflected by the clinical progression surfacing in the 5^th decade. PPMS patients with visual or brainstem/cerebellar onset had a significantly younger age at progression. SPMS patients with motor onset have a significantly higher age at progression and longer time to progression. Time to progression is significantly shorter in SPMS patients with higher age at disease onset. In summary the progression in MS is an age dependent process independent of relapses (11-15).

Of importance in any brain autoimmune or degenerative disorders, such as MS and Alzheimer’s Disease is also the role of microglia that rise to defense as the resident macrophages of the brain for the lack of any antibodies in the brain. Recent studies have revealed an expanding array of functions for microglia during brain development and in the adult brain for maintenance of the homeostasis after neurodegeneration resulting from infection and brain injury. Studies have shown that the cellular activities of microglia extend beyond their well-established role as immune sentinels and effectors to include synaptic organization, control of neuronal excitability, phagocytic debris removal and trophic support for brain protection and repair (16-19).

Unlike other organs and tissues of the body, aging affects the brain differently and by the brain regions differentially. First of all as discussed earlier, the brain growth or development mostly in the form of arborization and myelination continues until mid-20s and in some parts of the brain until the fourth decade. More importantly the different regions of the brain are not affected equally but differentially by aging and degenerative disorders. Moreover there are compelling evidences that microglia have phenotypic diversity in the healthy adult brain and also aging and degenerative diseases have a region-dependent impact on the brain. For example the microglia in the cerebellum hold a higher immune vigilant state and lower density so requiring each cell to survey a larger volume of tissue. In contrast the cortical and striatal microglia are similar to each other, while hippocampal microglia has an intermediate profile. Similarly the white matter microglia exist in a relatively less quiescent basal state than their grey matter counterparts, which could contribute to the more vigilant profile of microglia in the white matter-enriched cerebellum (20-21)

 Another factor is the genomic integration of endogenous retroviruses (ERVs) and other retrotransposons that although normally inactive, deficiencies in innate immunity could predispose to their reactivation. The cerebellum and hippocampus are more susceptible to the retrotransposition in the human brain and thus more immune vigilant and having higher expression of anti-viral interferon networks. Therefore more caudal regions of the CNS such as the cerebellum may be more vulnerable to age- or disease-related inflammatory degeneration if this heightened alertness is poorly controlled. However, the extra-alert phenotype may confer protective functions through increased vigilance and efficiency in removing potentially harmful agents, such as in the case of lower susceptibility of the cerebellum to amyloid deposition during ageing. Similar but to a lesser degree susceptibility to aging and degeneration has been shown in the hippocampal microglia. The cerebellum also along with caudate and putamen suffer from earlier atrophy in relapse-remitting than in primary-progressive MS. Also the demyelination is five times more in the cerebellar grey matter than the white matter (22-27).

 

Natural Interception in the course of MS:

It has been shown that myelin formation depends not alone on genetic programing, but environmental influence, experience, learning and exercise, plus other multiple intracellular and extracellular factors that all make myelination in the central nervous system a dynamic than a static process. Myelination has also been shown to depend on the sleep-wake cycle and up-regulation of myelin-related genes during sleep. Therefore poor and disturbed sleep-wake cycle and chronic insomnia could affect myelination and its regeneration substantially. It has been shown that the sleep loss could affect the node of Ranvier length, hence the nerve conduction in the brain. Therefore sleep is vital in promoting the white matter integrity. In recent years, a growing body of evidence has shown that myelin and the cells that form it, from OPCs to mature myelinating oligodendrocytes, are remarkably dynamic and responsive to the neurons they ensheathe. Artificially induced neuronal activity using selective optogenetic stimulation in premotor cortex can generate a rapid and robust proliferation of OPCs followed by increased myelination in the deep cortex and subcortical white matter within the stimulated circuit (28-36).

 Myelination and re-myelination especially in response to the environmental stimulus is time or period-dependent along the line of brain development, so the younger the brain the more impact. As discussed earlier all parts and structures of the brain including the white matter and myelination are task and stimulus-dependent, e.g. exercise, learning and training, such as piano playing, learning to read, mastering juggling^, and many others. To date, studies have demonstrated the dynamic influence of exogenous environmental stimuli on multiple regions of the brain. This environmental influence positively and negatively impacts programs governing myelination, and acts on myelinating oligodendrocyte (OL) cells across the entire human lifespan. Therefore the acquisition of new skills so to maintain a more active and dynamic brain would ensue in more plasticity including more myelination and re-myelination of the brain. The white matter of the brain which occupies almost half the volume of the human brain with its myelination not only genetically correspond to developmental behavioral and functional milestones, but later on in life to the environmental stimulus (37-45).

Similarly while brain injuries or insults to the brain, such as microbial invasions in the case of autoimmune disorders, e.g. MS causing damage to the plasticity of the brain including its myelination, any positive stimulus could help in its cellular regeneration and recovery. The pioneer work of the OPC proliferation reduction as a result of the blockade of action potential propagation in the optic nerve showed well how myelin is regulated by functional neuronal inputs, and can therefore participate in activity-dependent CNS plasticity (46). Over the lifespan, DTI (Diffusion Tensor Imaging) that identifies the conduction velocity and health of myelination or the white matter increases during normal brain development, but conversely decreases during typical age-related demyelination. DTI during learning a complex motor skill, such as juggling, has been shown to improve WM architecture when practiced regularly. Study of a second language in adults also influences WM plasticity as identified with DTI. These changes reflect learning-related increases in myelination (47-50).

Social environment also influences early myelin plasticity. Juvenile mouse studies of the prefrontal cortex have demonstrated that two weeks of social isolation could lead to alterations in Oligodendrocytes morphology, reduction in the myelin thickness, and deficits in working memory and sociability. Interestingly isolation in the adult mice had little effect on the myelin content, defining an important critical period in which juvenile social experience readily impacts regional brain development. Human studies on institutionally reared children have also demonstrated that severe neglect in early life compromises WM microstructure throughout the brain. However, early removal from adverse conditions and subsequent placement into high-quality foster care could promote more normative WM development, and therefore may support long-term motor, cognitive, and sensory remediation (51-58).

One of the oldest and most widely used experimental approaches to study the influence of experience on the brain is exposure to an enriched environment (59-61). Environmental enrichment (EE) refers to a complex and stimulating domain that challenges an organism to continuously adapt to its surroundings in a social, physical, and experiential manner. Early EE studies demonstrated widespread effects on numerous CNS cell types and under varied physiological conditions in both small and large mammals. Differential rearing in infant rhesus monkey shows that animals raised in larger groups demonstrate expansion of the CC (Corpus Callosum) and sustained improvement in cognitive performance versus age-matched, individually raised controls. In a model of Parkinson’s disease, young adult mice demonstrated an increase in new Oligodendrocyts(OLs) in the substantia nigra after a month of enriched housing. Similarly, EE increases OPC proliferation, and influences OPC number and cell fate in the amygdala of adult mice. EE also improves spatial learning in the aged rats by increasing the volume and length of myelinated fibers, volume of myelin sheaths, and total CC volume. Further, EE promotes progenitors derived from an endogenous pool of neural stem cells to generate OLs in a murine model of MS, with consequent enhanced re-myelination of lesions and reduced functional impairment (62-64).

Music is a multisensory form of EE that imparts cognitive (learning), auditory (listening), and motor (playing) stimulation, whereby simultaneous collaboration between multiple areas of the brain coordinate an organized response. Musical performance alters WM architecture and it has been shown that professional pianists who began playing during adolescence demonstrate improved WM integrity and WM plasticity, as shown in DTI. These studies have also revealed that these WM changes are relative to the amount of time spent practicing, and that specific WM regions are uniquely sensitive to piano playing during childhood, adolescence, and adulthood. This suggests age-specific regional plasticity in myelinating tracts, and functional adaptation within a critical period of development in WM undergoing maturation. Further, despite less overall training hours than adults, the larger number of involved brain regions correlated with practice during childhood, is a strong evidence the influence of early experience on WM plasticity. Pragmatically, these WM changes serve as a foundation to build upon with future experience. This adaptive response to music also occurs in the WM tracts of the adult, and in disease, emphasizing how life experiences – in this case learning could alter myelination and are influenced by the environment (65-68).

 Interacting with and adapting to our environment forms the basis for learning. Dynamic and influential learning involving WM occurs throughout life, but is especially critical during development, as organisms establish the infrastructure and patterns of circuitry in the brain. At the same level, any mental exercise or brain fitness such as cognitive training and stimulation that improves mental function, shapes and preserves WM integrity in the aging individuals that could be applied as treatment modalities in degenerating diseases such as Alzheimer’s disease and MS. Like music, meditation could improve myelination and WM efficiency in the areas of the brain such as the anterior cingulate cortex as it has been shown in DTI studies.

Physical activity not only improves the brain function and cognition, but also protects the brain from the detriments of aging. Voluntary exercise in mice enhances differentiation of OPCs into mature OLs, and increases oligodendrogenesis in the intact thoracic spinal cord after only a week of activity. Recent studies also confirm an impact of cardiorespiratory fitness on WM in older humans. DTI studies have shown positive relationship between fitness and spatial working memory that is mediated by WM microstructure. On the contrary, sedentary behavior in adults reduces WM integrity, but exercise is beneficial for WM health, and memory-related brain networks (69-79).

The nutritional environment impacts brain structure and function, and gross deviations in nutritional status are implicated in many neurological disorders. OLs, especially OPCs, have tremendous energy requirements. Synthesis and maintenance of myelin by OLs is a metabolically taxing process, and thus adequate dietary intake of a number of key elements is crucial to successful myelination. Iron deficiency is the most common nutritional health problem in the world, and has been linked to persistent hypo-myelination. This has important clinical implications during development, as the neurological sequelae (behavioral disorders, decreased cognitive ability, poor school performance) are long-lasting. Developmental disturbances in myelin synthesis and composition are not corrected with iron repletion. In the models of MS, MRI and histological iron distribution reveal that iron maintains myelin integrity and plays an important role in re-myelination and repair. Interestingly, age-related iron accumulation in the striatum is linked to demyelination and a reduction in declarative memory (80-84).

Essential fatty acids (EFAs) also play a key role in the structural integrity of myelin. Because the body cannot synthesize EFAs, they must be obtained from dietary intake. EFAs help build the myelin sheath, and their deficiency during infancy can delay brain development as well as accelerate the deterioration of cognitive processing in the adult (86).

Additionally, obesity is associated with reduced myelin. BMI is negatively correlated to WM integrity in multiple regions of the brain, including the CC, and has been implicated in the reduction of OL and OPC numbers in the murine spinal cord. Encouragingly, 7 weeks of exercise training reversed these reductions in the OL population. Obesity-related loss of WM integrity is prevalent in the limbic system and tracts connecting the frontal and temporal lobes, and could compound the effects of age-related cognitive decline. The reciprocal relationship between diet, exercise, and myelinogenesis highlights that adequate nutrition is required for normal brain development and plays a central role in myelin homeostasis (86-88).

Socialization tremendously impacts neurological development. Environmental resources like healthcare, education, and housing have a cause and effect relationship on the brain throughout life, and individual differences in cognition, emotion, and psychological wellbeing can be attributed to deviations in these social parameters. Early environmental adversity studies have demonstrated that rhesus monkeys raised in isolation and are detached from their environment, could be hostile and could not form adequate social attachments. Similarly, recent studies investigating social influence on WM plasticity have found that monkeys exposed to early life stress, particularly a disrupted infant-mother bond, demonstrate reductions in myelin and WM integrity, and elevations in plasma cortisol levels after maltreatment. These WM alterations are especially evident in regions of the brain associated with motor integration and emotional regulation (89-91).

 Murine studies also implicate neglect as a cause of reduced myelination in the prefrontal cortex. Two weeks of social impoverishment reduced myelin thickness and simplified OL morphology, and importantly, social reintegration in young adult mice did not lead to recovery. Further, DTI of language and limbic pathways reveals microstructural WM abnormalities in orphanage-reared children. Importantly, these changes correlate with the period of deprivation and time spent in the orphanage, i.e. in a deprived environment, and could misshape the trajectory of cognitive and behavioral neurodevelopment (92-93).

Conclusion:

It has been and it is still an enigma about the remission and relapse of autoimmune disorders (or any disorders) that’s the most common in the case of autoimmune demyelinating disorders, popularly Multiple Sclerosis (MS). Since at least two thirds of MS have a relapsing-remission course with an unknown reasons or sufficient explanations, this illness is a gold guiding marker to understand the relapsing-remitting illnesses if any more and above all understanding the defense of the brain against invasions. Since the question of pathogenesis of relapse and more importantly the remission has not been answered clearly or even worse has not been sought in the research arena, to find the answer if any, one needs to read between the lines and mostly in the basic neuroscience research as there are not many of such in the MS research field.

Therefore in this paper, I have surfed the neuroscience research that include mostly animal counterpart subjects to discern the answer to the remission and relapse of autoimmune demyelinating disorders such as MS. Although it has been hypothesized that remission in MS is driven by a small heat shock protein, αB crystalline that decreases the production of T_H1- and T_H17-type cytokines from auto-reactive T cells (94), it seems that the nature and the infrastructure of the brain holds a significant role as discussed above in the remission phases of MS.

 Oligodendrocyte precursor cells (OPCs) throughout the life generate new oligodendrocytes hence new myelin sheaths, particularly when triggered by an injury to the white matter of the brain, or in normal brain by stimulation from neural activities. Therefore in any demyelinating disease such as MS, the POCs are called into action the brain repairs itself, hence causes remissions. In fact the remission in MS starts first after the initial lesion of MS and the first isolated symptom, then the microbe e.g. EBV attacks back and causes relapse. This remission and relapse cycle will continue until one, the brain or microbe wins the battle.

The current available treatments of MS that involve monoclonal antibodies and fostering the immune system that are relatively effective, might not yield to a full recovery. Therefore it seems to be prudent to stimulate the brain and in this case the oligodendrocytes and their precursors to regenerate the damaged myelin and the myelin sheaths and lead to longer remission and hopefully full recovery. This importance could be accomplished either with neural stimulations e.g. DBS (Deep Brain Stimulation) (95-96) or simply by increasing the patient’s physical and mental activities to stimulate the brain and the POCs to repair itself, promote remission and lead to recovery (47, 49, 54, 56, 58). Also the correction of any trace element such as iron, B12 and essential fatty acids that are vital for the nutrition and wellbeing of the brain could enhance remission (80-85).

More important than any treatment, we need to move towards strategies for the prevention or lowering the prevalence of demyelinating diseases such as MS. To achieve so, first of all the body and mind need to be active, so there would be less chance of degenerations to demand treatments as detailed earlier. Secondly the provision of an enriched environment of rearing from early childhood or even farther before during conception for the fetus and lack of any stressful and adversarial life events on the developing brain could ensure a healthier brain, hence less damage and diseases, such as MS (59-64).

Dr.Mostafa Showraki, MD, FRCPC                                                                Lecturer, School of Medicine, University of Toronto                               Author: ADHD: Revisited Book, Amazon Kindle Books                   www.adhdrevisited.com/www.medicinerevisited.com

References:

1. Lublin FD, et al. (2014) Defining the clinical course of multiple sclerosis. Neurology. 83 (3): 278–286.
2. Swire M, Ffrench-Constant C. (2018). Seeing Is Believing: Myelin Dynamics in the Adult CNS. Neuron. 98(4):684-686.
3. Stadelmann, C, Timmler S, Barrantes-Freer A, Simons M. (2019)Myelin in the Central Nervous System:Structure, Function and Pathology. Physiological Reviews. 99 (3): 1381–1431.

1. Auer F, Vagionitis S, Czopka T. (2018) Evidence for myelin sheath remodeling in the CNS revealed by in vivo imaging. Curr. Biol. 28: 549-559.
2. Czopka T, Ffrench-Constant C, Lyons D.A. (2013) Individual oligodendrocytes have only a few hours in which to generate new myelin sheaths in vivo. Dev. Cell. 25: 599-609.
3. Hill R.A, Li A.M, Grutzendler J. (2018) Lifelong cortical myelin plasticity and age-related degeneration in the live mammalian brain.Nat. Neurosci. 21: 683-695.
4. Hughes E.G, Orthmann-Murphy J.L, Langseth A.J, Bergles D.E. (2018) Myelin remodeling through experience-dependent oligodendrogenesis in the adult somatosensory cortex. Nat. Neurosci. 21: 696-706.
5. McKenzie I.A, Ohayon D, Li H, de Faria J.P, Emery B, Tohyama K, Richardson W.D. (2014) Motor skill learning requires active central myelination. Science. 346: 318-322.
6. Sampaio-Baptista C, Johansen-Berg H. (2017) White matter plasticity in the adult brain.Neuron. 96: 1239-1251.

10. Bengtsson SL, Nagy Z, Skare S, Forsman L, Forssberg H, Ullén F.(2005) Extensive piano practicing has regionally specific effects on white matter development. Nat Neurosci. 8(9):1148-50.
11. Tutuncu M, Tang J, Zeid NA, et al. (2013) Onset of progressive phase is an age-dependent clinical milestone in multiple sclerosis. Mult Scler. 19(2):188–198.

1. Confavreux C, Vukusic S. (2006) Natural history of multiple sclerosis: a unifying concept. Brain. 129(Pt 3):606–16.
2. Tremlett H, Zhao Y, Devonshire V. (2009) Natural history comparisons of primary and secondary progressive multiple sclerosis reveals differences and similarities. J Neurol. 256(3):374–81.
3. Koch M, Mostert J, Heersema D, De Keyser J. (2007) Progression in multiple sclerosis: further evidence of an age dependent process. J Neurol Sci. 255(1-2):35–41.
4. Westlye LT, Walhovd KB, Dale AM, et al. (2010) Life-span changes of the human brain white matter: diffusion tensor imaging (DTI) and volumetry. Cereb Cortex. 20(9):2055–68.
5. Grabert K, Michoel T, Karavolos MH, et al.(2016) Microglial brain region-dependent diversity and selective regional sensitivities to aging. Nat Neurosci. 19(3):504–516.

17. Paolicelli RC, et al. (2011) Synaptic pruning by microglia is necessary for normal brain development. Science. 333(6048):1456-8.
18. Schafer DP, et al. (2012) Microglia sculpt postnatal neural circuits in an activity and complement-dependent manner.

Neuron. 74(4):691-705.

19. Neumann H, Kotter MR, Franklin RJ. (2009) Debris clearance by microglia: an essential link between degeneration and regeneration. Brain. 132(Pt 2):288-95.

21. Gehrmann J, Matsumoto Y, Kreutzberg GW.(1995) “Microglia: intrinsic immuneffector cell of the brain”. Brain Research. Brain Research Reviews. 20 (3): 269–87.
22. Hart AD, Wyttenbach A, Perry VH, Teeling JL. (2012) Age related changes in microglial phenotype vary between CNS regions: grey versus white matter differences. Brain Behav Immun. 26(5):754-65.
23. Lee KH, Horiuchi M, Itoh T, Greenhalgh DG, Cho K. (2011) Cerebellum-specific and age-dependent expression of an endogenous retrovirus with intact coding potential. Retrovirology. 8:82.
24. Baillie JK, et al. (2011) Somatic retrotransposition alters the genetic landscape of the human brain. Nature. 479(7374):534-7.
25. Damani MR, et al. (2011) Age-related alterations in the dynamic behavior of microglia. Aging Cell. 10(2):263-76.
26. Goh JO. (2011) Functional Dedifferentiation and Altered Connectivity in Older Adults: Neural Accounts of Cognitive Aging. Aging Dis. 2(1):30-48.
27. Eshaghi A, Marinescu RV, Young AL, et al. (2018) Progression of regional grey matter atrophy in multiple sclerosis. Brain. 141(6):1665–1677.
28. Gilmore CP, Donaldson I, Bö L, Owens T, Lowe J, Evangelou N.(2009) Regional variations in the extent and pattern of grey matter demyelination in multiple sclerosis: a comparison between the cerebral cortex, cerebellar cortex, deep grey matter nuclei and the spinal cord. J Neurol Neurosurg Psychiatry. 80(2):182-7.
29. Szulc-Lerch KU, et al. (2018) Repairing the brain with physical exercise: Cortical thickness and brain volume increases in long-term pediatric brain tumor survivors in response to a structured exercise intervention. Neuroimage Clin. 18:972–985.
30. Adkins DL. (2015) Cortical Stimulation-Induced Structural Plasticity and Functional Recovery after Brain Damage. Brain Neurotrauma: Molecular, Neuropsychological, and Rehabilitation Aspects.
31. Chen YH, et al. (2018) Exercise Ameliorates Motor Deficits and Improves Dopaminergic Functions in the Rat Hemi-Parkinson’s Model. Sci Rep. 8(1):3973.
32. Toritsuka M, Makinodan M, Kishimoto T. (2015) Social Experience-Dependent Myelination: An Implication for Psychiatric Disorders. Neural Plast. 2015:465345. doi:10.1155/2015/465345
33. de Vivo L, Bellesi M.(2019) The role of sleep and wakefulness in myelin plasticity. Glia. 67(11):2142–2152.
34. Fields R. D. (2015). A new mechanism of nervous system plasticity: Activity dependent myelination. Nature Reviews. Neuroscience, 16, 756–767.
35. Fields RD. (2008)White matter in learning, cognition and psychiatric disorders. Trends Neurosci. 31(7):361-70.
36. Forbes T. A., & Gallo V. (2017). All wrapped up: Environmental effects on myelination. Trends in Neurosciences, 40, 572–587.
37. Gibson E. M., et al. (2014) Neuronal activity promotes oligodendrogenesis and adaptive myelination in the mammalian brain. Science, 344, 1252304.
38. McKenzie I. A., et al. (2014) Motor skill learning requires active central myelination. Science, 346, 318–322.
39. Xiao L., et al. (2016) Rapid production of new oligodendrocytes is required in the earliest stages of motor skill learning. Nature Neuroscience, 19, 1210–1217.
40. Scholz J., et al. (2009) Training induces changes in white matter architecture. Nature Neuroscience, 12, 1370–1371.
41. Zatorre RJ, Fields RD, Johansen-Berg H. (2012) Plasticity in gray and white: neuroimaging changes in brain structure during learning. Nat Neurosci. 15(4):528-36.
42. Scholz J, Klein MC, Behrens TE, Johansen-Berg H. (2009) Training induces changes in white-matter architecture. Nat Neurosci. 12(11):1370-1.
43. Engel A, et al. (2014) Inter-individual differences in audio-motor learning of piano melodies and white matter fiber tract architecture. Hum Brain Mapp. 35(5):2483-97.
44. Zatorre RJ, Fields RD, Johansen-Berg H. (2012)Plasticity in gray and white: neuroimaging changes in brain structure during learning. Nature Neurosci. 15:528–536.
45. Mitew S, Hay CM, Peckham H, Xiao J, Koenning M, Emery B. (2014)Mechanisms regulating the development of oligodendrocytes and central nervous system myelin. 276:29–47.
46. Emery B, Lu QR. (2015)Transcriptional and epigenetic regulation of oligodendrocyte development and myelination in the central nervous system. Cold Spring Harb Perspect Biol. 7(9):a020461.
47. Barres BA, Raff MC. (1993)Proliferation of oligodendrocyte precursor cells depends on electrical activity in axons. 361(6409):258–260.
48. Mangin JM, Li P, Scafidi J, Gallo V. (2012)Experience-dependent regulation of NG2 progenitors in the developing barrel cortex. Nature Neurosci. 15(9):1192–1194.
49. Lebel C, Gee M, Camicioli R, Wieler M, Martin W, Beaulieu C.(2012) Diffusion tensor imaging of white matter tract evolution over the lifespan. 60:340–352.
50. Scholz J, Klein M, Behrens T, Johansen-Berg H. (2009)Training induces changes in white matter architecture. Nature Neurosci. 12(11):1367–1368.
51. Hosoda C, Tanaka K, Nariai T, Honda M, Hanakawa T.(2013) Dynamic neural network reorganization associated with second language vocabulary acquisition: a multimodal imaging study. J Neurosci. 33(34):13663-72.
52. Makinodan M, Rosen KM, Ito S, Corfas G. (2012)A Critical Period for Social Experience-Dependent Oligodendrocyte Maturation and Myelination. 337:1357–1360.
53. Bick J, Zhu T, Stamoulis C, Fox NA, Zeanah C, Nelson CA. (2015)Effect of early institutionalization and foster care on long-term white matter development: a randomized clinical trial. JAMA Pediatr. 169(3):211–219.
54. Young K, Psachoulia K, Tripathi R, Dunn S-J, Cossell L, Attwell D. (2013) Oligodendrocyte dynamics in the healthy adult CNS: evidence for myelin remodeling. 77:873–885.
55. McKenzie IA, et al. (2014) Motor skill learning requires active central myelination. Science. 2014 Oct 17; 346(6207):318-22.
56. de Lange AG, et al. (2016) White matter integrity as a marker for cognitive plasticity in aging. Neurobiol Aging. 47():74-82.
57. Dietz K, Polanco J, Pol S, Sim F. (2016) Targeting human oligodendrocyte progenitors for myelin repair. Exper Neurol. 283(B):489–500.
58. Hughes E, Kang S, Fukaya M, Bergles D. (2013) Oligodendrocyte progenitors balance growth with self-repulsion to achieve homeostasis in the adult brain. Nature Neurosci. 16(6):668–676.
59. Ontaneda D, Thompson A, Fox R, Cohen J. (2017) Progressive multiple sclerosis: prospects for disease therapy, repair, and restoration of function. 389:1357–1366.
60. Diamond MC, et al. (1964) The effects of an enriched environment on the histology of the rat cerebral cortex. J Comp Neurol. 123():111-20.
61. Kempermann G, Kuhn HG, Gage FH. (1997) More hippocampal neurons in adult mice living in an enriched environment. Nature. 386(6624):493-5.
62. Sánchez MM, Hearn EF, Do D, Rilling JK, Herndon JG. (1998) Differential rearing affects corpus callosum size and cognitive function of rhesus monkeys. Brain Res. 812(1-2):38-49.
63. Okuda H, et al. (2009) Environmental enrichment stimulates progenitor cell proliferation in the amygdala. J Neurosci Res. 87(16):3546-53.
64. Zhao YY, et al. (2012) Enriched environment increases the myelinated nerve fibers of aged rat corpus callosum. Anat Rec (Hoboken). 295(6):999-1005.
65. Magalon K, Cantarella C, Monti G, Cayre M, Durbec P.(2007) Enriched environment promotes adult neural progenitor cell mobilization in mouse demyelination models. Eur J Neurosci. 25(3):761-71.
66. Zatorre RJ, Chen JL, Penhune VB. (2007) When the brain plays music: auditory-motor interactions in music perception and production. Nat Rev Neurosci. 8(7):547-58.
67. Han Y, et al. (2009) Gray matter density and white matter integrity in pianists’ brain: a combined structural and diffusion tensor MRI study. Neurosci Lett. 459(1):3-6.
68. Imfeld A, Oechslin MS, Meyer M, Loenneker T, Jancke L. (2009) White matter plasticity in the corticospinal tract of musicians: a diffusion tensor imaging study. Neuroimage. 46(3):600-7.
69. Steele CJ, Bailey JA, Zatorre RJ, Penhune VB. (2013) Early musical training and white-matter plasticity in the corpus callosum: evidence for a sensitive period. J Neurosci. 33(3):1282-90.
70. Metzler-Baddeley C, et al. (2014) Improved Executive Function and Callosal White Matter Microstructure after Rhythm Exercise in Huntington’s Disease. J Huntingtons Dis. 3(3):273-83.
71. Sampaio-Baptista C., et al. (2013) Motor skill learning induces changes in white matter microstructure and myelination. J Neurosci. 33(50):19499-503.
72. Xiao L, et al. (2016) Rapid production of new oligodendrocytes is required in the earliest stages of motor-skill learning. Nat Neurosci. 19(9):1210-1217.
73. Engvig A, et al. (2012) Memory training impacts short-term changes in aging white matter: a longitudinal diffusion tensor imaging study. Hum Brain Mapp. 33(10):2390-406.
74. Tang YY, Hölzel BK, Posner MI.(2015) The neuroscience of mindfulness meditation. Nat Rev Neurosci. 16(4):213-25.
75. Posner MI, Tang YY, Lynch G. (2014) Mechanisms of white matter change induced by meditation training. Front Psychol. 5:1220.
76. Tang YY, Lu Q, Fan M, Yang Y, Posner MI. (2012) Mechanisms of white matter changes induced by meditation. Proc Natl Acad Sci U S A. 109(26):10570-4.
77. Kang DH, et al. (2013) The effect of meditation on brain structure: cortical thickness mapping and diffusion tensor imaging. Soc Cogn Affect Neurosci. 8(1):27-33.
78. Oberlin LE, et al. (2016) White matter microstructure mediates the relationship between cardiorespiratory fitness and spatial working memory in older adults. Neuroimage. 131():91-101.
79. Burzynska AZ , et al. (2014) Physical activity and cardiorespiratory fitness are beneficial for white matter in low-fit older adults. PLoS. 9(9):e107413.
80. Tian Q, et al. (2014) Physical activity predicts microstructural integrity in memory-related networks in very old adults. J Gerontol A Biol Sci Med Sci. 69(10):1284-90.
81. Connor JR, Menzies SL. (1996) Relationship of iron to oligodendrocytes and myelination. Glia. 17(2):83-93.
82. Todorich B, Pasquini JM, Garcia CI, Paez PM, Connor JR. (2009) Oligodendrocytes and myelination: the role of iron. Glia. 57(5):467-78.
83. Algarin C, et al. (2017) Differences on Brain Connectivity in Adulthood Are Present in Subjects with Iron Deficiency Anemia in Infancy. Front Aging Neurosci. 9:54.
84. Stephenson E, Nathoo N, Mahjoub Y, Dunn JF, Yong VW. (2014) Iron in multiple sclerosis: roles in neurodegeneration and repair. Nat Rev Neurol. 10(8):459-68.
85. Steiger TK, Weiskopf N, Bunzeck N.(2016) Iron Level and Myelin Content in the Ventral Striatum Predict Memory Performance in the Aging Brain. J Neurosci. 36(12):3552-8.
86. Yehuda S, Rabinovitz S, Mostofsky DI. (2005) Essential fatty acids and the brain: from infancy to aging. Neurobiol Aging. 26 Suppl 1():98-102.
87. Xu J, Li Y, Lin H, Sinha R, Potenza MN.(2013) Body mass index correlates negatively with white matter integrity in the fornix and corpus callosum; a diffusion tensor imaging study. Hum Brain Mapp. 34(5):1044–1052.
88. Yoon H, et al. (2016) Interplay between exercise and dietary fat modulates myelinogenesis in the central nervous system. Biochimica et Biophysica Acta. 1862(4):545–555.
89. Kullmann S, Schweizer F, Veit R, Fritsche A, Preissl H. (2015) Compromised white matter integrity in obesity. Obes Rev. 16(4):273-81.
90. Piccolo LR, Merz EC, He X, Sowell ER, Noble KG. (2016) Pediatric Imaging, Neurocognition, Genetics Study. Age-Related Differences in Cortical Thickness Vary by Socioeconomic Status. PLoS One. 11(9):e0162511.
91. Howell BR, et al. (2013) Brain white matter microstructure alterations in adolescent rhesus monkeys exposed to early life stress: associations with high cortisol during infancy. Biol Mood Anxiety Disord. 3(1):21.
92. Liu J, et al. (2012) Impaired adult myelination in the prefrontal cortex of socially isolated mice. Nat Neurosci. 15(12):1621-3
93. Makinodan M, Rosen KM, Ito S, Corfas G. (2012) A critical period for social experience-dependent oligodendrocyte maturation and myelination. Science. 337(6100):1357-60.
94. Champagne DL, et al. (2008) Maternal care and hippocampal plasticity: evidence for experience-dependent structural plasticity, altered synaptic functioning, and differential responsiveness to glucocorticoids and stress. J Neurosci. 28(23):6037-45.
95. Steinman, L. (2009) A molecular trio in relapse and remission in multiple sclerosis. Nat Rev Immunol9, 440–447.
96. Brandmeir NJ, Murray A, Cheyuo C, Ferari C, Rezai AR. (2019) Deep Brain Stimulation for Multiple Sclerosis Tremor: A Meta-Analysis. Neuromodulation. 2019 Nov 22. doi: 10.1111/ner.13063. [Epub ahead of print]
97. Abboud H, Hill E, Siddiqui J, Serra A, Walter B. (2017) Neuromodulation in multiple sclerosis. Mult Scler. 23(13):1663-1676.