Langbahn Team – Weltmeisterschaft

Neuroplasticity

Neuroplasticity, also known as neural plasticity or just plasticity, is the ability of neural networks in the brain to change through growth and reorganization. Neuroplasticity refers to the brain's ability to reorganize and rewire its neural connections, enabling it to adapt and function in ways that differ from its prior state. This process can occur in response to learning new skills, experiencing environmental changes, recovering from injuries, or adapting to sensory or cognitive deficits. Such adaptability highlights the dynamic and ever-evolving nature of the brain, even into adulthood..[1] These changes range from individual neuron pathways making new connections, to systematic adjustments like cortical remapping or neural oscillation. Other forms of neuroplasticity include homologous area adaptation, cross modal reassignment, map expansion, and compensatory masquerade.[2] Examples of neuroplasticity include circuit and network changes that result from learning a new ability, information acquisition,[3] environmental influences,[4] pregnancy,[5] caloric intake,[6] practice/training,[7] and psychological stress.[8]

Neuroplasticity was once thought by neuroscientists to manifest only during childhood,[9][10] but research in the latter half of the 20th century showed that many aspects of the brain can be altered (or are "plastic") even through adulthood.[11] Furthermore, starting from the primary stimulus-response sequence in simple reflexes, the organisms' capacity to correctly detect alterations within themselves and their context depends on the concrete nervous system architecture, which evolves in a particular way already during gestation.[12][13][14] Adequate nervous system development forms us as human beings with all necessary cognitive functions. The physicochemical properties of the mother-fetus bio-system affect the neuroplasticity of the embryonic nervous system in their ecological context.[12][13][14] However, the developing brain exhibits a higher degree of plasticity than the adult brain.[15] Activity-dependent plasticity can have significant implications for healthy development, learning, memory, and recovery from brain damage.[16][17][18]

History

Origin

The term plasticity was first applied to behavior in 1890 by William James in The Principles of Psychology where the term was used to describe "a structure weak enough to yield to an influence, but strong enough not to yield all at once".[19][20] The first person to use the term neural plasticity appears to have been the Polish neuroscientist Jerzy Konorski.[11][21]

One of the first experiments providing evidence for neuroplasticity was conducted in 1793, by Italian anatomist Michele Vicenzo Malacarne, who described experiments in which he paired animals, trained one of the pair extensively for years, and then dissected both. Malacarne discovered that the cerebellums of the trained animals were substantially larger than the cerebellum of the untrained animals. However, while these findings were significant, they were eventually forgotten.[22] In 1890, the idea that the brain and its function are not fixed throughout adulthood was proposed by William James in The Principles of Psychology, though the idea was largely neglected.[20] Up until the 1970s, neuroscientists believed that the brain's structure and function was essentially fixed throughout adulthood.[23]

While the brain was commonly understood as a nonrenewable organ in the early 1900s, the pioneering neuroscientist Santiago Ramón y Cajal used the term neuronal plasticity to describe nonpathological changes in the structure of adult brains. Based on his renowned neuron doctrine, Cajal first described the neuron as the fundamental unit of the nervous system that later served as an essential foundation to develop the concept of neural plasticity.[24] Many neuroscientists used the term plasticity to explain the regenerative capacity of the peripheral nervous system only. Cajal, however, used the term plasticity to reference his findings of degeneration and regeneration in the adult brain (a part of the central nervous system). This was controversial, with some like Walther Spielmeyer and Max Bielschowsky arguing that the CNS cannot produce new cells.[25][26]

The term has since been broadly applied:

Given the central importance of neuroplasticity, an outsider would be forgiven for assuming that it was well defined and that a basic and universal framework served to direct current and future hypotheses and experimentation. Sadly, however, this is not the case. While many neuroscientists use the word neuroplasticity as an umbrella term it means different things to different researchers in different subfields ... In brief, a mutually agreed-upon framework does not appear to exist.[27]

Research and discovery

In 1923, Karl Lashley conducted experiments on rhesus monkeys that demonstrated changes in neuronal pathways, which he concluded were evidence of plasticity. Despite this, and other research that suggested plasticity, neuroscientists did not widely accept the idea of neuroplasticity.

Inspired by work from Nicolas Rashevsky,[28] in 1943, McCulloch and Pitts proposed the artificial neuron, with a learning rule, whereby new synapses are produced when neurons fire simultaneously.[29] This is then extensively discussed in The organization of behavior (Hebb, 1949) and is now known as Hebbian learning.

In 1945, Justo Gonzalo concluded from his research on brain dynamics, that, contrary to the activity of the projection areas, the "central" cortical mass (more or less equidistant from the visual, tactile and auditive projection areas), would be a "maneuvering mass", rather unspecific or multisensory, with capacity to increase neural excitability and re-organize the activity by means of plasticity properties.[30] He gives as a first example of adaptation, to see upright with reversing glasses in the Stratton experiment,[31] and specially, several first-hand brain injuries cases in which he observed dynamic and adaptive properties in their disorders, in particular in the inverted perception disorder [e.g., see pp 260–62 Vol. I (1945), p 696 Vol. II (1950)].[30] He stated that a sensory signal in a projection area would be only an inverted and constricted outline that would be magnified due to the increase in recruited cerebral mass, and re-inverted due to some effect of brain plasticity, in more central areas, following a spiral growth.[32]

Marian Diamond of the University of California, Berkeley, produced the first scientific evidence of anatomical brain plasticity, publishing her research in 1964.[33][34]

Other significant evidence was produced in the 1960s and after, notably from scientists including Paul Bach-y-Rita, Michael Merzenich along with Jon Kaas, as well as several others.[23][35]

In the 1960s, Paul Bach-y-Rita invented a device that was tested on a small number of people, and involved a person sitting in a chair, embedded in which were nubs that were made to vibrate in ways that translated images received in a camera, allowing a form of vision via sensory substitution.[36][37]

Studies in people recovering from stroke also provided support for neuroplasticity, as regions of the brain that remained healthy could sometimes take over, at least in part, functions that had been destroyed; Shepherd Ivory Franz did work in this area.[38][39]

Eleanor Maguire documented changes in hippocampal structure associated with acquiring the knowledge of London's layout in local taxi drivers.[40][41][42] A redistribution of grey matter was indicated in London Taxi Drivers compared to controls. This work on hippocampal plasticity not only interested scientists, but also engaged the public and media worldwide. 1. Neuroplasticity Mechanisms: Synaptic and Structural Changes Neuroplasticity involves synaptic plasticity, which is a change in the strength of synaptic connections, and structural plasticity, which is a change in the brain's physical structure. There are two major processes underlying synaptic plasticity: long-term potentiation and long-term depression. Long-term potentiation strengthens the synapses between neurons when they are repeatedly activated together, making communication between them more efficient. Conversely, LTD weakens synapses when activation patterns are less frequent and helps the brain to "prune" unnecessary connections. These processes are generally thought to be the underpinning mechanisms of learning and memory, as well as the recovery ability of the brain after in

Michael Merzenich is a neuroscientist who has been one of the pioneers of neuroplasticity for over three decades. He has made some of "the most ambitious claims for the field – that brain exercises may be as useful as drugs to treat diseases as severe as schizophrenia – that plasticity exists from cradle to the grave, and that radical improvements in cognitive functioning – how we learn, think, perceive, and remember are possible even in the elderly."[36] Merzenich's work was affected by a crucial discovery made by David Hubel and Torsten Wiesel in their work with kittens. The experiment involved sewing one eye shut and recording the cortical brain maps. Hubel and Wiesel saw that the portion of the kitten's brain associated with the shut eye was not idle, as expected. Instead, it processed visual information from the open eye. It was "…as though the brain didn't want to waste any 'cortical real estate' and had found a way to rewire itself."[36]

This implied neuroplasticity during the critical period. However, Merzenich argued that neuroplasticity could occur beyond the critical period. His first encounter with adult plasticity came when he was engaged in a postdoctoral study with Clinton Woosley. The experiment was based on observation of what occurred in the brain when one peripheral nerve was cut and subsequently regenerated. The two scientists micromapped the hand maps of monkey brains before and after cutting a peripheral nerve and sewing the ends together. Afterwards, the hand map in the brain that they expected to be jumbled was nearly normal. This was a substantial breakthrough. Merzenich asserted that, "If the brain map could normalize its structure in response to abnormal input, the prevailing view that we are born with a hardwired system had to be wrong. The brain had to be plastic."[36] Merzenich received the 2016 Kavli Prize in Neuroscience "for the discovery of mechanisms that allow experience and neural activity to remodel brain function."[43]

Neurobiology

There are different ideas and theories on what biological processes allow for neuroplasticity to occur. The core of this phenomenon is based upon synapses and how connections between them change based on neuron functioning. It is widely agreed upon that neuroplasticity takes on many forms, as it is a result of a variety of pathways. These pathways, mainly signaling cascades, allow for gene expression alterations that lead to neuronal changes, and thus neuroplasticity.

There are a number of other factors that are thought to play a role in the biological processes underlying the changing of neural networks in the brain. Some of these factors include synapse regulation via phosphorylation, the role of inflammation and inflammatory cytokines, proteins such as Bcl-2 proteins and neutrophorins, and energy production via mitochondria.[44]

JT Wall and J Xu have traced the mechanisms underlying neuroplasticity. Re-organization is not cortically emergent, but occurs at every level in the processing hierarchy; this produces the map changes observed in the cerebral cortex.[45]

Types

Christopher Shaw and Jill McEachern (eds) in "Toward a theory of Neuroplasticity", state that there is no all-inclusive theory that overarches different frameworks and systems in the study of neuroplasticity. However, researchers often describe neuroplasticity as "the ability to make adaptive changes related to the structure and function of the nervous system."[46] Correspondingly, two types of neuroplasticity are often discussed: structural neuroplasticity and functional neuroplasticity.

Structural neuroplasticity

Structural plasticity is often understood as the brain's ability to change its neuronal connections. New neurons are constantly produced and integrated into the central nervous system throughout the life span based on this type of neuroplasticity.[47] Researchers nowadays use multiple cross-sectional imaging methods (i.e. magnetic resonance imaging (MRI), computerized tomography (CT)) to study the structural alterations of the human brains.[48] This type of neuroplasticity often studies the effect of various internal or external stimuli on the brain's anatomical reorganization. The changes of grey matter proportion or the synaptic strength in the brain are considered as examples of structural neuroplasticity. Structural neuroplasticity is currently investigated more within the field of neuroscience in current academia.[24]

Functional neuroplasticity

Functional plasticity refers to the brain's ability to alter and adapt the functional properties of network of neurons. It can occur in four known ways namely:

  1. homologous area adaptation
  2. map expansion
  3. cross-model reassignment
  4. compensatory masquerade.[2]

Homologous area adaptation

Homologous area adaptation is the assumption of a particular cognitive process by a homologous region in the opposite hemisphere.[49] For instance, through homologous area adaptation a cognitive task is shifted from a damaged part of the brain to its homologous area in opposite side of the brain. Homologous area adaptation is a type of functional neuroplasticity that occur usually in children rather than adults.

Map expansion

In map expansion, cortical maps related to particular cognitive tasks expand due to frequent exposure to stimuli. Map expansion has been proven through experiments performed in relation to the study: experiment on effect of frequent stimulus on functional connectivity of the brain was observed in individuals learning spatial routes.[50]

Cross-model reassignment

Cross-model reassignment involves reception of novel input signals to a brain region which has been stripped off its default input.

Compensatory masquerade

Functional plasticity through compensatory masquerade occurs using different cognitive processes for an already established cognitive task.

Changes in the brain associated with functional neuroplasticity can occur in response to two different types of events:

In the latter case the functions from one part of the brain transfer to another part of the brain based on the demand to produce recovery of behavioral or physiological processes.[51] Regarding physiological forms of activity-dependent plasticity, those involving synapses are referred to as synaptic plasticity. The strengthening or weakening of synapses that results in an increase or decrease of firing rate of the neurons are called long-term potentiation (LTP) and long-term depression (LTD), respectively, and they are considered as examples of synaptic plasticity that are associated with memory.[52] The cerebellum is a typical structure with combinations of LTP/LTD and redundancy within the circuitry, allowing plasticity at several sites.[53] More recently it has become clearer that synaptic plasticity can be complemented by another form of activity-dependent plasticity involving the intrinsic excitability of neurons, which is referred to as intrinsic plasticity.[54][55][56] This, as opposed to homeostatic plasticity does not necessarily maintain the overall activity of a neuron within a network but contributes to encoding memories.[57] Also, many studies have indicated functional neuroplasticity in the level of brain networks, where training alters the strength of functional connections.[58][59] Although a recent study discusses that these observed changes should not directly relate to neuroplasticity, since they may root in the systematic requirement of the brain network for reorganization.[60]

Applications and examples

The adult brain is not entirely "hard-wired" with fixed neuronal circuits. There are many instances of cortical and subcortical rewiring of neuronal circuits in response to training as well as in response to injury.

There is ample evidence[61] for the active, experience-dependent re-organization of the synaptic networks of the brain involving multiple inter-related structures including the cerebral cortex.[62] The specific details of how this process occurs at the molecular and ultrastructural levels are topics of active neuroscience research. The way experience can influence the synaptic organization of the brain is also the basis for a number of theories of brain function including the general theory of mind and neural Darwinism. The concept of neuroplasticity is also central to theories of memory and learning that are associated with experience-driven alteration of synaptic structure and function in studies of classical conditioning in invertebrate animal models such as Aplysia.

There is evidence that neurogenesis (birth of brain cells) occurs in the adult, rodent brain—and such changes can persist well into old age.[63] The evidence for neurogenesis is mainly restricted to the hippocampus and olfactory bulb, but research has revealed that other parts of the brain, including the cerebellum, may be involved as well.[64] However, the degree of rewiring induced by the integration of new neurons in the established circuits is not known, and such rewiring may well be functionally redundant.[65]

Treatment of brain damage

A surprising consequence of neuroplasticity is that the brain activity associated with a given function can be transferred to a different location; this can result from normal experience and also occurs in the process of recovery from brain injury. Neuroplasticity is the fundamental issue that supports the scientific basis for treatment of acquired brain injury with goal-directed experiential therapeutic programs in the context of rehabilitation approaches to the functional consequences of the injury.

Neuroplasticity is gaining popularity as a theory that, at least in part, explains improvements in functional outcomes with physical therapy post-stroke. Rehabilitation techniques that are supported by evidence which suggest cortical reorganization as the mechanism of change include constraint-induced movement therapy, functional electrical stimulation, treadmill training with body-weight support, and virtual reality therapy. Robot assisted therapy is an emerging technique, which is also hypothesized to work by way of neuroplasticity, though there is currently insufficient evidence to determine the exact mechanisms of change when using this method.[66]

One group has developed a treatment that includes increased levels of progesterone injections in brain-injured patients. "Administration of progesterone after traumatic brain injury[67] (TBI) and stroke reduces edema, inflammation, and neuronal cell death, and enhances spatial reference memory and sensory-motor recovery."[68] In a clinical trial, a group of severely injured patients had a 60% reduction in mortality after three days of progesterone injections.[69] However, a study published in the New England Journal of Medicine in 2014 detailing the results of a multi-center NIH-funded phase III clinical trial of 882 patients found that treatment of acute traumatic brain injury with the hormone progesterone provides no significant benefit to patients when compared with placebo.[70]

Binocular vision

For decades, researchers assumed that humans had to acquire binocular vision, in particular stereopsis, in early childhood or they would never gain it. In recent years, however, successful improvements in persons with amblyopia, convergence insufficiency or other stereo vision anomalies have become prime examples of neuroplasticity; binocular vision improvements and stereopsis recovery are now active areas of scientific and clinical research.[71][72][73]

Phantom limbs

A diagrammatic explanation of the mirror box. The patient places the intact limb into one side of the box (in this case the right hand) and the amputated limb into the other side. Due to the mirror, the patient sees a reflection of the intact hand where the missing limb would be (indicated in lower contrast). The patient thus receives artificial visual feedback that the "resurrected" limb is now moving when they move the good hand.

In the phenomenon of phantom limb sensation, a person continues to feel pain or sensation within a part of their body that has been amputated. This is strangely common, occurring in 60–80% of amputees.[74] An explanation for this is based on the concept of neuroplasticity, as the cortical maps of the removed limbs are believed to have become engaged with the area around them in the postcentral gyrus. This results in activity within the surrounding area of the cortex being misinterpreted by the area of the cortex formerly responsible for the amputated limb.

The relationship between phantom limb sensation and neuroplasticity is a complex one. In the early 1990s V.S. Ramachandran theorized that phantom limbs were the result of cortical remapping. However, in 1995 Herta Flor and her colleagues demonstrated that cortical remapping occurs only in patients who have phantom pain.[75] Her research showed that phantom limb pain (rather than referred sensations) was the perceptual correlate of cortical reorganization.[76] This phenomenon is sometimes referred to as maladaptive plasticity.

In 2009, Lorimer Moseley and Peter Brugger carried out an experiment in which they encouraged arm amputee subjects to use visual imagery to contort their phantom limbs into impossible[clarification needed] configurations. Four of the seven subjects succeeded in performing impossible movements of the phantom limb. This experiment suggests that the subjects had modified the neural representation of their phantom limbs and generated the motor commands needed to execute impossible movements in the absence of feedback from the body.[77]

Chronic pain

Individuals who have chronic pain experience prolonged pain at sites that may have been previously injured, yet are otherwise currently healthy. This phenomenon is related to neuroplasticity due to a maladaptive reorganization of the nervous system, both peripherally and centrally. During the period of tissue damage, noxious stimuli and inflammation cause an elevation of nociceptive input from the periphery to the central nervous system. Prolonged nociception from the periphery then elicits a neuroplastic response at the cortical level to change its somatotopic organization for the painful site, inducing central sensitization.[78] For instance, individuals experiencing complex regional pain syndrome demonstrate a diminished cortical somatotopic representation of the hand contralaterally as well as a decreased spacing between the hand and the mouth.[79] Additionally, chronic pain has been reported to significantly reduce the volume of grey matter in the brain globally, and more specifically at the prefrontal cortex and right thalamus.[80] However, following treatment, these abnormalities in cortical reorganization and grey matter volume are resolved, as well as their symptoms. Similar results have been reported for phantom limb pain,[81] chronic low back pain[82] and carpal tunnel syndrome.[83]

Meditation

A number of studies have linked meditation practice to differences in cortical thickness or density of gray matter.[84][85][86][87] One of the most well-known studies to demonstrate this was led by Sara Lazar, from Harvard University, in 2000.[88] Richard Davidson, a neuroscientist at the University of Wisconsin, has led experiments in collaboration with the Dalai Lama on effects of meditation on the brain. His results suggest that meditation may lead to change in the physical structure of brain regions associated with attention, anxiety, depression, fear, anger, and compassion as well as the ability of the body to heal itself.[89][90]

Artistic engagement and art therapy

There is substantial evidence that artistic engagement in a therapeutic environment can create changes in neural network connections as well as increase cognitive flexibility.[91][92] In one 2013 study, researchers found evidence that long-term, habitual artistic training (e.g. musical instrument practice, purposeful painting, etc.) can "macroscopically imprint a neural network system of spontaneous activity in which the related brain regions become functionally and topologically modularized in both domain-general and domain-specific manners".[93] In simple terms, brains repeatedly exposed to artistic training over long periods develop adaptations to make such activity both easier and more likely to spontaneously occur.

Some researchers and academics have suggested that artistic engagement has substantially altered the human brain throughout our evolutionary history. D.W Zaidel, adjunct professor of behavioral neuroscience and contributor at VAGA, has written that "evolutionary theory links the symbolic nature of art to critical pivotal brain changes in Homo sapiens supporting increased development of language and hierarchical social grouping".[94]

Music therapy

There is evidence that engaging in music-supported therapy can improve neuroplasticity in patients who are recovering from brain injuries. Music-supported therapy can be used for patients that are undergoing stroke rehabilitation where a one month study of stroke patients participating in music-supported therapy showed a significant improvement in motor control in their affected hand.[95] Another finding was the examination of grey matter volume of adults developing brain atrophy and cognitive decline where playing a musical instrument, such as the piano, or listening to music can increase grey matter volume in areas such as the caudate nucleus, Rolandic operculum, and cerebellum.[96] Evidence also suggests that music-supported therapy can improve cognitive performance, well-being, and social behavior in patients who are recovering from damage to the orbitofrontal cortex (OFC) and recovering from mild traumatic brain injury. Neuroimaging post music-supportrd therapy revealed functional changes in OFC networks, with improvements observed in both task-based and resting-state fMRI analyses.[97]

Fitness and exercise

Aerobic exercise increases the production of neurotrophic factors (compounds that promote growth or survival of neurons), such as brain-derived neurotrophic factor (BDNF), insulin-like growth factor 1 (IGF-1), and vascular endothelial growth factor (VEGF).[98][99][100] Exercise-induced effects on the hippocampus are associated with measurable improvements in spatial memory.[101][102][103][104] Consistent aerobic exercise over a period of several months induces marked clinically significant improvements in executive function (i.e., the "cognitive control" of behavior) and increased gray matter volume in multiple brain regions, particularly those that give rise to cognitive control.[100][101][105][106] The brain structures that show the greatest improvements in gray matter volume in response to aerobic exercise are the prefrontal cortex and hippocampus;[100][101][102] moderate improvements are seen in the anterior cingulate cortex, parietal cortex, cerebellum, caudate nucleus, and nucleus accumbens.[100][101][102] Higher physical fitness scores (measured by VO2 max) are associated with better executive function, faster processing speed, and greater volume of the hippocampus, caudate nucleus, and nucleus accumbens.[101]

Deafness and loss of hearing

Due to hearing loss, the auditory cortex and other association areas of the brain in deaf and/or hard of hearing people undergo compensatory plasticity.[107][108][109] The auditory cortex usually reserved for processing auditory information in hearing people now is redirected to serve other functions, especially for vision and somatosensation.

Deaf individuals have enhanced peripheral visual attention,[110] better motion change but not color change detection ability in visual tasks,[108][109][111] more effective visual search,[112] and faster response time for visual targets[113][114] compared to hearing individuals. Altered visual processing in deaf people is often found to be associated with the repurposing of other brain areas including primary auditory cortex, posterior parietal association cortex (PPAC), and anterior cingulate cortex (ACC).[115] A review by Bavelier et al. (2006) summarizes many aspects on the topic of visual ability comparison between deaf and hearing individuals.[116]

Brain areas that serve a function in auditory processing repurpose to process somatosensory information in congenitally deaf people. They have higher sensitivity in detecting frequency change in vibration above threshold[117] and higher and more widespread activation in auditory cortex under somatosensory stimulation.[118][107] However, speeded response for somatosensory stimuli is not found in deaf adults.[113]

Cochlear implant

Neuroplasticity is involved in the development of sensory function. The brain is born immature and then adapts to sensory inputs after birth. In the auditory system, congenital hearing loss, a rather frequent inborn condition affecting 1 of 1000 newborns, has been shown to affect auditory development, and implantation of a sensory prostheses activating the auditory system has prevented the deficits and induced functional maturation of the auditory system.[119] Due to a sensitive period for plasticity, there is also a sensitive period for such intervention within the first 2–4 years of life. Consequently, in prelingually deaf children, early cochlear implantation, as a rule, allows the children to learn the mother language and acquire acoustic communication.[120]

Blindness

Due to vision loss, the visual cortex in blind people may undergo cross-modal plasticity, and therefore other senses may have enhanced abilities. Or the opposite could occur, with the lack of visual input weakening the development of other sensory systems. One study suggests that the right posterior middle temporal gyrus and superior occipital gyrus reveal more activation in the blind than in the sighted people during a sound-moving detection task.[121] Several studies support the latter idea and found weakened ability in audio distance evaluation, proprioceptive reproduction, threshold for visual bisection, and judging minimum audible angle.[122][123]

Human echolocation

Human echolocation is a learned ability for humans to sense their environment from echoes. This ability is used by some blind people to navigate their environment and sense their surroundings in detail. Studies in 2010[124] and 2011[125] using functional magnetic resonance imaging techniques have shown that parts of the brain associated with visual processing are adapted for the new skill of echolocation. Studies with blind patients, for example, suggest that the click-echoes heard by these patients were processed by brain regions devoted to vision rather than audition.[125]

Attention deficit hyperactivity disorder

Reviews of MRI and electroencephalography (EEG) studies on individuals with ADHD suggest that the long-term treatment of ADHD with stimulants, such as amphetamine or methylphenidate, decreases abnormalities in brain structure and function found in subjects with ADHD, and improves function in several parts of the brain, such as the right caudate nucleus of the basal ganglia,[126][127][128] left ventrolateral prefrontal cortex (VLPFC), and superior temporal gyrus.[129]

In early child development

Neuroplasticity is most active in childhood as a part of normal human development, and can also be seen as an especially important mechanism for children in terms of risk and resiliency.[130] Trauma is considered a great risk as it negatively affects many areas of the brain and puts a strain on the sympathetic nervous system from constant activation. Trauma thus alters the brain's connections such that children who have experienced trauma may be hyper vigilant or overly aroused.[131] However, a child's brain can cope with these adverse effects through the actions of neuroplasticity.[132]

Neuroplasticity is shown in four different categories in children and covering a wide variety of neuronal functioning. These four types include impaired, excessive, adaptive, and plasticity.[133]

There are many examples of neuroplasticity in human development. For example, Justine Ker and Stephen Nelson looked at the effects of musical training on neuroplasticity, and found that musical training can contribute to experience dependent structural plasticity. This is when changes in the brain occur based on experiences that are unique to an individual. Examples of this are learning multiple languages, playing a sport, doing theatre, etc. A study done by Hyde in 2009, showed that changes in the brain of children could be seen in as little as 15 months of musical training.[134] Ker and Nelson suggest this degree of plasticity in the brains of children can "help provide a form of intervention for children... with developmental disorders and neurological diseases."[135]

In animals

In a single lifespan, individuals of an animal species may encounter various changes in brain morphology. Many of these differences are caused by the release of hormones in the brain; others are the product of evolutionary factors or developmental stages.[136][137][138][139] Some changes occur seasonally in species to enhance or generate response behaviors.

Seasonal brain changes

Changing brain behavior and morphology to suit other seasonal behaviors is relatively common in animals.[140] These changes can improve the chances of mating during breeding season.[136][137][138][140][141][142] Examples of seasonal brain morphology change can be found within many classes and species.

Within the class Aves, black-capped chickadees experience an increase in the volume of their hippocampus and strength of neural connections to the hippocampus during fall months.[143][144] These morphological changes within the hippocampus which are related to spatial memory are not limited to birds, as they can also be observed in rodents and amphibians.[140] In songbirds, many song control nuclei in the brain increase in size during mating season.[140] Among birds, changes in brain morphology to influence song patterns, frequency, and volume are common.[145] Gonadotropin-releasing hormone (GnRH) immunoreactivity, or the reception of the hormone, is lowered in European starlings exposed to longer periods of light during the day.[136][137]

The California sea hare, a gastropod, has more successful inhibition of egg-laying hormones outside of mating season due to increased effectiveness of inhibitors in the brain.[138] Changes to the inhibitory nature of regions of the brain can also be found in humans and other mammals.[139] In the amphibian Bufo japonicus, part of the amygdala is larger before breeding and during hibernation than it is after breeding.[141]

Seasonal brain variation occurs within many mammals. Part of the hypothalamus of the common ewe is more receptive to GnRH during breeding season than at other times of the year.[142] Humans experience a change in the "size of the hypothalamic suprachiasmatic nucleus and vasopressin-immunoreactive neurons within it"[139] during the fall, when these parts are larger. In the spring, both reduce in size.[146]

Traumatic brain injury research

A group of scientists found that if a small stroke (an infarction) is induced by obstruction of blood flow to a portion of a monkey's motor cortex, the part of the body that responds by movement moves when areas adjacent to the damaged brain area are stimulated. In one study, intracortical microstimulation (ICMS) mapping techniques were used in nine normal monkeys. Some underwent ischemic-infarction procedures and the others, ICMS procedures. The monkeys with ischemic infarctions retained more finger flexion during food retrieval and after several months this deficit returned to preoperative levels.[147] With respect to the distal forelimb representation, "postinfarction mapping procedures revealed that movement representations underwent reorganization throughout the adjacent, undamaged cortex."[147] Understanding of interaction between the damaged and undamaged areas provides a basis for better treatment plans in stroke patients. Current research includes the tracking of changes that occur in the motor areas of the cerebral cortex as a result of a stroke. Thus, events that occur in the reorganization process of the brain can be ascertained. The treatment plans that may enhance recovery from strokes, such as physiotherapy, pharmacotherapy, and electrical-stimulation therapy, are also being studied.

Jon Kaas, a professor at Vanderbilt University, has been able to show "how somatosensory area 3b and ventroposterior (VP) nucleus of the thalamus are affected by longstanding unilateral dorsal-column lesions at cervical levels in macaque monkeys."[148] Adult brains have the ability to change as a result of injury but the extent of the reorganization depends on the extent of the injury. His recent research focuses on the somatosensory system, which involves a sense of the body and its movements using many senses. Usually, damage of the somatosensory cortex results in impairment of the body perception. Kaas' research project is focused on how these systems (somatosensory, cognitive, motor systems) respond with plastic changes resulting from injury.[148]

One recent study of neuroplasticity involves work done by a team of doctors and researchers at Emory University, specifically Donald Stein[149] and David Wright. This is the first treatment in 40 years that has significant results in treating traumatic brain injuries while also incurring no known side effects and being cheap to administer.[69] Stein noticed that female mice seemed to recover from brain injuries better than male mice, and that at certain points in the estrus cycle, females recovered even better. This difference may be attributed to different levels of progesterone, with higher levels of progesterone leading to the faster recovery from brain injury in mice. However, clinical trials showed progesterone offers no significant benefit for traumatic brain injury in human patients.[150]

Aging

Transcriptional profiling of the frontal cortex of persons ranging from 26 to 106 years of age defined a set of genes with reduced expression after age 40, and especially after age 70.[151] Genes that play central roles in synaptic plasticity were the most significantly affected by age, generally showing reduced expression over time. There was also a marked increase in cortical DNA damage, likely oxidative DNA damage, in gene promoters with aging.[151]

Reactive oxygen species appear to have a significant role in the regulation of synaptic plasticity and cognitive function.[152] However age-related increases in reactive oxygen species may also lead to impairments in these functions.

Multilingualism

There is a beneficial effect of multilingualism on people's behavior and cognition. Numerous studies have shown that people who study more than one language have better cognitive functions and flexibilities than people who only speak one language. Bilinguals are found to have longer attention spans, stronger organization and analyzation skills, and a better theory of mind than monolinguals. Researchers have found that the effect of multilingualism on better cognition is due to neuroplasticity.

In one prominent study, neurolinguists used a voxel-based morphometry (VBM) method to visualize the structural plasticity of brains in healthy monolinguals and bilinguals. They first investigated the differences in density of grey and white matter between two groups and found the relationship between brain structure and age of language acquisition. The results showed that grey-matter density in the inferior parietal cortex for multilinguals were significantly greater than monolinguals. The researchers also found that early bilinguals had a greater density of grey matter relative to late bilinguals in the same region. The inferior parietal cortex is a brain region highly associated with the language learning, which corresponds to the VBM result of the study.[153]

Recent studies have also found that learning multiple languages not only re-structures the brain but also boosts brain's capacity for plasticity. A recent study found that multilingualism not only affects the grey matter but also white matter of the brain. White matter is made up of myelinated axons that is greatly associated with learning and communication. Neurolinguists used a diffusion tensor imaging (DTI) scanning method to determine the white matter intensity between monolinguals and bilinguals. Increased myelinations in white matter tracts were found in bilingual individuals who actively used both languages in everyday life. The demand of handling more than one language requires more efficient connectivity within the brain, which resulted in greater white matter density for multilinguals.[154]

While it is still debated whether these changes in brain are result of genetic disposition or environmental demands, many evidences suggest that environmental, social experience in early multilinguals affect the structural and functional reorganization in the brain.[155][156]

Novel treatments of depression

Historically, the monoamine imbalance hypothesis of depression played a dominant role in psychiatry and drug development.[157] However, while traditional antidepressants cause a quick increase in noradrenaline, serotonin, or dopamine, there is a significant delay in their clinical effect and often an inadequate treatment response.[158] As neuroscientists pursued this avenue of research, clinical and preclinical data across multiple modalities began to converge on pathways involved in neuroplasticity.[159] They found a strong inverse relationship between the number of synapses and severity of depression symptoms[160] and discovered that in addition to their neurotransmitter effect, traditional antidepressants improved neuroplasticity but over a significantly protracted time course of weeks or months.[161] The search for faster acting antidepressants found success in the pursuit of ketamine, a well-known anesthetic agent, that was found to have potent anti-depressant effects after a single infusion due to its capacity to rapidly increase the number of dendritic spines and to restore aspects of functional connectivity.[162] Additional neuroplasticity promoting compounds with therapeutic effects that were both rapid and enduring have been identified through classes of compounds including serotonergic psychedelics, cholinergic scopolamine, and other novel compounds. To differentiate between traditional antidepressants focused on monoamine modulation and this new category of fast acting antidepressants that achieve therapeutic effects through neuroplasticity, the term psychoplastogen was introduced.[163]

See also

References

  1. ^ Costandi, Moheb (19 August 2016). Neuroplasticity. MIT Press. ISBN 978-0-262-52933-4. OCLC 987683015.
  2. ^ a b Grafman J (1 July 2000). "Conceptualizing functional neuroplasticity". Journal of Communication Disorders. 33 (4): 345–356. doi:10.1016/S0021-9924(00)00030-7. PMID 11001161.
  3. ^ Fuchs E, Flügge G (2014). "Adult neuroplasticity: more than 40 years of research". Neural Plasticity. 2014: 541870. doi:10.1155/2014/541870. PMC 4026979. PMID 24883212.
  4. ^ Davidson RJ, McEwen BS (April 2012). "Social influences on neuroplasticity: stress and interventions to promote well-being". Nature Neuroscience. 15 (5): 689–695. doi:10.1038/nn.3093. PMC 3491815. PMID 22534579.
  5. ^ Paternina-Die M, Martínez-García M, Martín de Blas D, Noguero I, Servin-Barthet C, Pretus C, et al. (February 2024). "Women's neuroplasticity during gestation, childbirth and postpartum". Nature Neuroscience. 27 (2): 319–327. doi:10.1038/s41593-023-01513-2. ISSN 1546-1726. PMC 10849958. PMID 38182834.
  6. ^ Shaffer J (26 July 2016). "Neuroplasticity and Clinical Practice: Building Brain Power for Health". Frontiers in Psychology. 7: 1118. doi:10.3389/fpsyg.2016.01118. PMC 4960264. PMID 27507957.
  7. ^ Park DC, Huang CM (July 2010). "Culture Wires the Brain: A Cognitive Neuroscience Perspective". Perspectives on Psychological Science. 5 (4): 391–400. doi:10.1177/1745691610374591. PMC 3409833. PMID 22866061.
  8. ^ McEwen BS (April 2018). "Redefining neuroendocrinology: Epigenetics of brain-body communication over the life course". Frontiers in Neuroendocrinology. 49: 8–30. doi:10.1016/j.yfrne.2017.11.001. PMID 29132949. S2CID 1681145.
  9. ^ Leuner B, Gould E (January 2010). "Structural plasticity and hippocampal function". Annual Review of Psychology. 61 (1): 111–140. doi:10.1146/annurev.psych.093008.100359. PMC 3012424. PMID 19575621.
  10. ^ Kusiak AN, Selzer ME (2013). "Neuroplasticity in the spinal cord". In Barnes MP, Good DC (eds.). Neurological Rehabilitation (3rd ed.). China: Elsevier Inc. Chapters. ISBN 978-0-12-807792-4. Archived from the original on 13 July 2020. Retrieved 3 June 2020.
  11. ^ a b Livingston RB (1966). "Brain mechanisms in conditioning and learning" (PDF). Neurosciences Research Program Bulletin. 4 (3): 349–354.
  12. ^ a b Val Danilov I (2023). "Shared Intentionality Before Birth: Emulating a Model of Mother-Fetus Communication for Developing Human-Machine Systems." In: Arai, K. (eds) Intelligent Systems and Applications. IntelliSys 2023. Lecture Notes in Networks and Systems, vol 824. Springer, Cham. https://doi.org/10.1007/978-3-031-47715-7_5
  13. ^ a b Val Danilov I (2024). "The Origin of Natural Neurostimulation: A Narrative Review of Noninvasive Brain Stimulation Techniques." OBM Neurobiology 2024; 8(4): 260; https://doi:10.21926/obm.neurobiol.2404260.
  14. ^ a b Val Danilov I (2024). "Child Cognitive Development with the Maternal Heartbeat: A Mother-Fetus Neurocognitive Model and Architecture for Bioengineering Systems." In International Conference on Digital Age & Technological Advances for Sustainable Development (pp. 216-223). Springer, Cham. https://doi.org/10.1007/978-3-031-75329-9_24
  15. ^ Hensch TK, Bilimoria PM (July 2012). "Re-opening Windows: Manipulating Critical Periods for Brain Development". Cerebrum. 2012: 11. PMC 3574806. PMID 23447797.
  16. ^ Pascual-Leone A, Freitas C, Oberman L, Horvath JC, Halko M, Eldaief M, et al. (October 2011). "Characterizing brain cortical plasticity and network dynamics across the age-span in health and disease with TMS-EEG and TMS-fMRI". Brain Topography. 24 (3–4): 302–315. doi:10.1007/s10548-011-0196-8. PMC 3374641. PMID 21842407.
  17. ^ Ganguly K, Poo MM (October 2013). "Activity-dependent neural plasticity from bench to bedside". Neuron. 80 (3): 729–741. doi:10.1016/j.neuron.2013.10.028. PMID 24183023.
  18. ^ Carey L, Walsh A, Adikari A, Goodin P, Alahakoon D, De Silva D, et al. (2 May 2019). "Finding the Intersection of Neuroplasticity, Stroke Recovery, and Learning: Scope and Contributions to Stroke Rehabilitation". Neural Plasticity. 2019: 5232374. doi:10.1155/2019/5232374. PMC 6525913. PMID 31191637.
  19. ^ Warraich Z, Kleim JA (1 December 2010). "Neural Plasticity: The Biological Substrate For Neurorehabilitation". PM&R. 2 (12 Suppl 2): S208–S219. doi:10.1016/j.pmrj.2010.10.016. PMID 21172683. S2CID 36928880.
  20. ^ a b James W (1890). "Chapter IV: Habits". The Principles of Psychology. Archived from the original on 18 July 2017.
  21. ^ LeDoux JE (2002). Synaptic self: how our brains become who we are. New York, United States: Viking. p. 137. ISBN 978-0-670-03028-6.
  22. ^ Rosenzweig MR (1996). "Aspects of the search for neural mechanisms of memory". Annual Review of Psychology. 47: 1–32. doi:10.1146/annurev.psych.47.1.1. PMID 8624134.
  23. ^ a b O'Rourke M (25 April 2007). "Train Your Brain". Slate. Archived from the original on 18 August 2011.
  24. ^ a b Mateos-Aparicio P, Rodríguez-Moreno A (2019). "The Impact of Studying Brain Plasticity". Frontiers in Cellular Neuroscience. 13 (66): 66. doi:10.3389/fncel.2019.00066. PMC 6400842. PMID 30873009.
  25. ^ Fuchs E, Flügge G (2014). "Adult neuroplasticity: more than 40 years of research". Neural Plasticity. 2014 (5): 541870. doi:10.1155/2014/541870. PMC 4026979. PMID 24883212.
  26. ^ Frank W S, Nitsch R (November 2002). "Santiago Ramón y Cajal's concept of neuronal plasticity: the ambiguity lives on". Trends in Neurosciences. 25 (11): 589–591. doi:10.1016/s0166-2236(02)02251-8. ISSN 0166-2236. PMID 12392934.
  27. ^ Shaw C, McEachern J, eds. (2001). Toward a theory of neuroplasticity. London, England: Psychology Press. ISBN 978-1-84169-021-6.
  28. ^ Abraham TH (December 2002). "(Physio)logical circuits: The intellectual origins of the McCulloch–Pitts neural networks". Journal of the History of the Behavioral Sciences. 38 (1): 3–25. doi:10.1002/jhbs.1094. ISSN 0022-5061. PMID 11835218.
  29. ^ McCulloch WS, Pitts W (1 December 1943). "A logical calculus of the ideas immanent in nervous activity". The Bulletin of Mathematical Biophysics. 5 (4): 115–133. doi:10.1007/BF02478259. ISSN 1522-9602.
  30. ^ a b Gonzalo Rodríguez-Leal J, Gonzalo Fonrodona I, Gonzalo Rodríguez-Leal J, Gonzalo Fonrodona I (11 February 2021). "Brain Dynamics: The brain activity according to the dynamic conditions of nervous excitability. Volume 1". eprints.ucm.es. Retrieved 28 January 2023.
  31. ^ Stratton GM (1896). "Some preliminary experiments on vision without inversion of the retinal image". Psychological Review. 3 (6): 611–7. doi:10.1037/h0072918. S2CID 13147419.
  32. ^ Gonzalo J (1952). "Dinámica cerebral". Trabajos del Instituto Cajal de Investigaciones Biológicas. 44: 95–157. hdl:10347/4341. Retrieved 12 April 2012.
  33. ^ Diamond MC, Krech D, Rosenzweig MR (August 1964). "The effects of an enriched environment on the histology of the rat cerebral cortex". The Journal of Comparative Neurology. 123: 111–120. doi:10.1002/cne.901230110. PMID 14199261. S2CID 30997263.
  34. ^ Bennett EL, Diamond MC, Krech D, Rosenzweig MR (October 1964). "Chemical and Anatomical Plasticity of Brain". Science. 146 (3644): 610–619. Bibcode:1964Sci...146..610B. doi:10.1126/science.146.3644.610. PMID 14191699.
  35. ^ Brain Science Podcast Episode #10, "Neuroplasticity"
  36. ^ a b c d Doidge N (2007). The Brain That Changes Itself: Stories of Personal Triumph from the frontiers of brain science. New York: Viking. ISBN 978-0-670-03830-5.
  37. ^ "Wired Science . Video: Mixed Feelings". PBS. Archived from the original on 22 December 2007. Retrieved 12 June 2010.
  38. ^ "Shepherd Ivory Franz". Rkthomas.myweb.uga.edu. Archived from the original on 3 February 2012. Retrieved 12 June 2010.
  39. ^ Colotla VA, Bach-y-Rita P (June 2002). "Shepherd Ivory Franz: his contributions to neuropsychology and rehabilitation" (PDF). Cognitive, Affective & Behavioral Neuroscience. 2 (2): 141–148. doi:10.3758/CABN.2.2.141. PMID 12455681. S2CID 45175011. Archived from the original on 1 March 2012.{{cite journal}}: CS1 maint: unfit URL (link)
  40. ^ Maguire EA, Frackowiak RS, Frith CD (September 1997). "Recalling routes around london: activation of the right hippocampus in taxi drivers". The Journal of Neuroscience. 17 (18): 7103–7110. doi:10.1523/JNEUROSCI.17-18-07103.1997. PMC 6573257. PMID 9278544.
  41. ^ Woollett K, Maguire EA (December 2011). "Acquiring "the Knowledge" of London's layout drives structural brain changes". Current Biology. 21 (24): 2109–2114. Bibcode:2011CBio...21.2109W. doi:10.1016/j.cub.2011.11.018. PMC 3268356. PMID 22169537.
  42. ^ Maguire EA, Gadian DG, Johnsrude IS, Good CD, Ashburner J, Frackowiak RS, et al. (April 2000). "Navigation-related structural change in the hippocampi of taxi drivers". Proceedings of the National Academy of Sciences of the United States of America. 97 (8): 4398–4403. Bibcode:2000PNAS...97.4398M. doi:10.1073/pnas.070039597. PMC 18253. PMID 10716738.
  43. ^ "2016 Kavli Prize in Neuroscience". 2 June 2016. Archived from the original on 5 June 2016. Retrieved 2 June 2016.
  44. ^ Gulyaeva NV (March 2017). "Molecular mechanisms of neuroplasticity: An expanding universe". Biochemistry (Moscow). 82 (3): 237–242. doi:10.1134/S0006297917030014. ISSN 0006-2979. PMID 28320264. S2CID 6539117.
  45. ^ Wall JT, Xu J, Wang X (September 2002). "Human brain plasticity: an emerging view of the multiple substrates and mechanisms that cause cortical changes and related sensory dysfunctions after injuries of sensory inputs from the body". Brain Research. Brain Research Reviews. 39 (2–3): 181–215. doi:10.1016/S0165-0173(02)00192-3. PMID 12423766. S2CID 26966615.
  46. ^ Zilles K (October 1992). "Neuronal plasticity as an adaptive property of the central nervous system". Annals of Anatomy - Anatomischer Anzeiger. 174 (5): 383–391. doi:10.1016/s0940-9602(11)80255-4. PMID 1333175.
  47. ^ Puderbaugh M, Emmady PD (2023). "Neuroplasticity". StatPearls. StatPearls Publishing. PMID 32491743. Retrieved 10 October 2023.
  48. ^ Chang Y (2014). "Reorganization and plastic changes of the human brain associated with skill learning and expertise". Frontiers in Human Neuroscience. 8 (55): 35. doi:10.3389/fnhum.2014.00035. PMC 3912552. PMID 24550812.
  49. ^ Grafman J (2000). "Conceptualizing functional neuroplasticity". Journal of Communication Disorders. 33 (4): 345–356. doi:10.1016/S0021-9924(00)00030-7. ISSN 0021-9924. PMID 11001161.
  50. ^ Keller TA, Just MA (15 January 2016). "Structural and functional neuroplasticity in human learning of spatial routes". NeuroImage. 125: 256–266. doi:10.1016/j.neuroimage.2015.10.015. ISSN 1053-8119. PMID 26477660. S2CID 2784354.
  51. ^ Freed WJ, de Medinaceli L, Wyatt RJ (March 1985). "Promoting functional plasticity in the damaged nervous system". Science. 227 (4694): 1544–1552. Bibcode:1985Sci...227.1544F. doi:10.1126/science.3975624. PMID 3975624.
  52. ^ Patten AR, Yau SY, Fontaine CJ, Meconi A, Wortman RC, Christie BR (October 2015). "The Benefits of Exercise on Structural and Functional Plasticity in the Rodent Hippocampus of Different Disease Models". Brain Plasticity. 1 (1): 97–127. doi:10.3233/BPL-150016. PMC 5928528. PMID 29765836.
  53. ^ Mitoma H, Kakei S, Yamaguchi K, Manto M (April 2021). "Physiology of Cerebellar Reserve: Redundancy and Plasticity of a Modular Machine". International Journal of Molecular Sciences. 22 (9): 4777. doi:10.3390/ijms22094777. PMC 8124536. PMID 33946358.
  54. ^ Zhang W, Linden DJ (November 2003). "The other side of the engram: experience-driven changes in neuronal intrinsic excitability". Nature Reviews. Neuroscience. 4 (11): 885–900. doi:10.1038/nrn1248. PMID 14595400. S2CID 17397545.
  55. ^ Debanne D, Inglebert Y, Russier M (February 2019). "Plasticity of intrinsic neuronal excitability" (PDF). Current Opinion in Neurobiology. 54: 73–82. doi:10.1016/j.conb.2018.09.001. PMID 30243042. S2CID 52812190. Archived (PDF) from the original on 3 February 2020. Retrieved 29 February 2020.
  56. ^ Scheler, Gabriele (2013). "Learning intrinsic excitability in medium spiny neurons". F1000Research. 2: 88. doi:10.12688/f1000research.2-88.v2. PMC 4264637. PMID 25520776.
  57. ^ Grasselli G, Boele HJ, Titley HK, Bradford N, van Beers L, Jay L, et al. (January 2020). "SK2 channels in cerebellar Purkinje cells contribute to excitability modulation in motor-learning-specific memory traces". PLOS Biology. 18 (1): e3000596. doi:10.1371/journal.pbio.3000596. PMC 6964916. PMID 31905212.
  58. ^ Duru AD, Balcioglu TH (2018). "Functional and Structural Plasticity of Brain in Elite Karate Athletes". Journal of Healthcare Engineering. 2018: 8310975. doi:10.1155/2018/8310975. PMC 6218732. PMID 30425820.
  59. ^ Kelly C, Castellanos FX (March 2014). "Strengthening connections: functional connectivity and brain plasticity". Neuropsychology Review. 24 (1): 63–76. doi:10.1007/s11065-014-9252-y. PMC 4059077. PMID 24496903.
  60. ^ Saberi M, Khosrowabadi R, Khatibi A, Misic B, Jafari G (2021). "Requirement to change of functional brain network across the lifespan". PLOS ONE. 16 (11): e0260091. Bibcode:2021PLoSO..1660091S. doi:10.1371/journal.pone.0260091. PMC 8601519. PMID 34793536.
  61. ^ Yu F, Jiang Qj, Sun Xy, Zhang Rw (22 August 2014). "A new case of complete primary cerebellar agenesis: clinical and imaging findings in a living patient". Brain. 138 (6): e353. doi:10.1093/brain/awu239. ISSN 0006-8950. PMC 4614135. PMID 25149410.
  62. ^ Scheler G (January 2023). "Sketch of a novel approach to a neural model". arXiv:2209.06865. {{cite journal}}: Cite journal requires |journal= (help)
  63. ^ Duque A, Arellano JI, Rakic P (January 2022). "An assessment of the existence of adult neurogenesis in humans and value of its rodent models for neuropsychiatric diseases". Molecular Psychiatry. 27 (1): 377–382. doi:10.1038/s41380-021-01314-8. ISSN 1476-5578. PMC 8967762. PMID 34667259.
  64. ^ Ponti G, Peretto P, Bonfanti L (June 2008). Reh TA (ed.). "Genesis of neuronal and glial progenitors in the cerebellar cortex of peripuberal and adult rabbits". PLOS ONE. 3 (6): e2366. Bibcode:2008PLoSO...3.2366P. doi:10.1371/journal.pone.0002366. PMC 2396292. PMID 18523645.
  65. ^ França TF (November 2018). "Plasticity and redundancy in the integration of adult born neurons in the hippocampus". Neurobiology of Learning and Memory. 155: 136–142. doi:10.1016/j.nlm.2018.07.007. PMID 30031119. S2CID 51710989.
  66. ^ Young JA, Tolentino M (January 2011). "Neuroplasticity and its applications for rehabilitation". American Journal of Therapeutics. 18 (1): 70–80. doi:10.1097/MJT.0b013e3181e0f1a4. PMID 21192249.
  67. ^ Traumatic Brain Injury (a story of TBI and the results of ProTECT using progesterone treatments) Emory University News Archives
  68. ^ Cutler SM, Pettus EH, Hoffman SW, Stein DG (October 2005). "Tapered progesterone withdrawal enhances behavioral and molecular recovery after traumatic brain injury". Experimental Neurology. 195 (2): 423–429. doi:10.1016/j.expneurol.2005.06.003. PMID 16039652. S2CID 6305569.
  69. ^ a b Stein, Donald. "Plasticity." Personal interview. Alyssa Walz. 19 November 2008.
  70. ^ "Progesterone offers no significant benefit in traumatic brain injury clinical trial". Atlanta, GA: Emory University. Archived from the original on 27 March 2015.
  71. ^ Maino DM (January 2009). "Neuroplasticity: Teaching an old brain new tricks". Review of Optometry. 39: 46. Archived from the original on 19 August 2014.
  72. ^ Vedamurthy I, Huang SJ, Levi DM, Bavelier D, Knill DC (27 December 2012). "Recovery of stereopsis in adults through training in a virtual reality task". Journal of Vision. 12 (14): 53. doi:10.1167/12.14.53.
  73. ^ Hess RF, Thompson B (February 2013). "New insights into amblyopia: binocular therapy and noninvasive brain stimulation". Journal of AAPOS. 17 (1): 89–93. doi:10.1016/j.jaapos.2012.10.018. PMID 23352385.
  74. ^ Beaumont G, Mercier C, Michon PE, Malouin F, Jackson PL (February 2011). "Decreasing phantom limb pain through observation of action and imagery: a case series". Pain Medicine. 12 (2): 289–299. doi:10.1111/j.1526-4637.2010.01048.x. PMID 21276185.
  75. ^ Flor H, Elbert T, Knecht S, Wienbruch C, Pantev C, Birbaumer N, et al. (June 1995). "Phantom-limb pain as a perceptual correlate of cortical reorganization following arm amputation". Nature. 375 (6531): 482–484. Bibcode:1995Natur.375..482F. doi:10.1038/375482a0. PMID 7777055. S2CID 205025856. Archived from the original on 20 November 2020. Retrieved 21 December 2018.
  76. ^ Flor H (May 2003). "Cortical reorganisation and chronic pain: implications for rehabilitation". Journal of Rehabilitation Medicine. 35 (41 Suppl): 66–72. doi:10.1080/16501960310010179. PMID 12817660.
  77. ^ Moseley GL, Brugger P (November 2009). "Interdependence of movement and anatomy persists when amputees learn a physiologically impossible movement of their phantom limb". Proceedings of the National Academy of Sciences of the United States of America. 106 (44): 18798–18802. Bibcode:2009PNAS..10618798M. doi:10.1073/pnas.0907151106. PMC 2774040. PMID 19858475.
  78. ^ Seifert F, Maihöfner C (October 2011). "Functional and structural imaging of pain-induced neuroplasticity". Current Opinion in Anesthesiology. 24 (5): 515–523. doi:10.1097/aco.0b013e32834a1079. PMID 21822136. S2CID 6680116.
  79. ^ Maihöfner C, Handwerker HO, Neundörfer B, Birklein F (December 2003). "Patterns of cortical reorganization in complex regional pain syndrome". Neurology. 61 (12): 1707–1715. doi:10.1212/01.wnl.0000098939.02752.8e. PMID 14694034. S2CID 23080189.
  80. ^ Apkarian AV, Sosa Y, Sonty S, Levy RM, Harden RN, Parrish TB, et al. (November 2004). "Chronic back pain is associated with decreased prefrontal and thalamic gray matter density". The Journal of Neuroscience. 24 (46): 10410–10415. doi:10.1523/JNEUROSCI.2541-04.2004. PMC 6730296. PMID 15548656. Archived from the original on 22 June 2020. Retrieved 8 September 2019.
  81. ^ Karl A, Birbaumer N, Lutzenberger W, Cohen LG, Flor H (May 2001). "Reorganization of motor and somatosensory cortex in upper extremity amputees with phantom limb pain". The Journal of Neuroscience. 21 (10): 3609–3618. doi:10.1523/JNEUROSCI.21-10-03609.2001. PMC 6762494. PMID 11331390.
  82. ^ Flor H, Braun C, Elbert T, Birbaumer N (March 1997). "Extensive reorganization of primary somatosensory cortex in chronic back pain patients". Neuroscience Letters. 224 (1): 5–8. doi:10.1016/s0304-3940(97)13441-3. PMID 9132689. S2CID 18151663. Archived from the original on 20 November 2020. Retrieved 21 December 2018.
  83. ^ Napadow V, Kettner N, Ryan A, Kwong KK, Audette J, Hui KK (June 2006). "Somatosensory cortical plasticity in carpal tunnel syndrome--a cross-sectional fMRI evaluation". NeuroImage. 31 (2): 520–530. doi:10.1016/j.neuroimage.2005.12.017. PMID 16460960. S2CID 7367285.
  84. ^ Sasmita AO, Kuruvilla J, Ling AP (November 2018). "Harnessing neuroplasticity: modern approaches and clinical future". The International Journal of Neuroscience. 128 (11): 1061–1077. doi:10.1080/00207454.2018.1466781. PMID 29667473. S2CID 4957270.
  85. ^ Pagnoni G, Cekic M (October 2007). "Age effects on gray matter volume and attentional performance in Zen meditation". Neurobiology of Aging. 28 (10): 1623–1627. doi:10.1016/j.neurobiolaging.2007.06.008. hdl:11380/609140. PMID 17655980. S2CID 16755503.
  86. ^ Vestergaard-Poulsen P, van Beek M, Skewes J, Bjarkam CR, Stubberup M, Bertelsen J, et al. (January 2009). "Long-term meditation is associated with increased gray matter density in the brain stem". NeuroReport. 20 (2): 170–174. doi:10.1097/WNR.0b013e328320012a. PMID 19104459. S2CID 14263267.
  87. ^ Luders E, Toga AW, Lepore N, Gaser C (April 2009). "The underlying anatomical correlates of long-term meditation: larger hippocampal and frontal volumes of gray matter". NeuroImage. 45 (3): 672–678. doi:10.1016/j.neuroimage.2008.12.061. PMC 3184843. PMID 19280691.
  88. ^ Lazar SW, Kerr CE, Wasserman RH, Gray JR, Greve DN, Treadway MT, et al. (November 2005). "Meditation experience is associated with increased cortical thickness". NeuroReport. 16 (17): 1893–1897. doi:10.1097/01.wnr.0000186598.66243.19. PMC 1361002. PMID 16272874.
  89. ^ Lutz A, Greischar LL, Rawlings NB, Ricard M, Davidson RJ (November 2004). "Long-term meditators self-induce high-amplitude gamma synchrony during mental practice". Proceedings of the National Academy of Sciences of the United States of America. 101 (46): 16369–16373. Bibcode:2004PNAS..10116369L. doi:10.1073/pnas.0407401101. PMC 526201. PMID 15534199.
  90. ^ Davidson RJ, Lutz A (January 2008). "Buddha's Brain: Neuroplasticity and Meditation" (PDF). IEEE Signal Processing Magazine. 25 (1): 176–174. Bibcode:2008ISPM...25..176D. doi:10.1109/MSP.2008.4431873. PMC 2944261. PMID 20871742. Archived (PDF) from the original on 12 January 2012. Retrieved 19 April 2018.
  91. ^ Lin CS, Liu Y, Huang WY, Lu CF, Teng S, Ju TC, et al. (2013). "Sculpting the Intrinsic Modular Organization of Spontaneous Brain Activity by Art". PLOS ONE. 8 (6): e66761. Bibcode:2013PLoSO...866761L. doi:10.1371/journal.pone.0066761. ISSN 1932-6203. PMC 3694132. PMID 23840527.
  92. ^ Patel AD (July 2003). "Language, music, syntax and the brain". Nature Neuroscience. 6 (7): 674–681. doi:10.1038/nn1082. ISSN 1546-1726. PMID 12830158. S2CID 15689983.
  93. ^ Lin CS, Liu Y, Huang WY, Lu CF, Teng S, Ju TC, et al. (26 June 2013). "Sculpting the Intrinsic Modular Organization of Spontaneous Brain Activity by Art". PLOS ONE. 8 (6): e66761. Bibcode:2013PLoSO...866761L. doi:10.1371/journal.pone.0066761. ISSN 1932-6203. PMC 3694132. PMID 23840527.
  94. ^ Zaidel DW (February 2010). "Art and brain: insights from neuropsychology, biology and evolution". Journal of Anatomy. 216 (2): 177–183. doi:10.1111/j.1469-7580.2009.01099.x. ISSN 0021-8782. PMC 2815940. PMID 19490399.
  95. ^ Grau-Sánchez J, Amengual JL, Rojo N, Veciana de las Heras M, Montero J, Rubio F, et al. (2013). "Plasticity in the sensorimotor cortex induced by Music-supported therapy in stroke patients: a TMS study". Frontiers in Human Neuroscience. 7: 494. doi:10.3389/fnhum.2013.00494. ISSN 1662-5161. PMC 3759754. PMID 24027507.
  96. ^ Marie D, Müller CA, Altenmüller E, Van De Ville D, Jünemann K, Scholz DS, et al. (June 2023). "Music interventions in 132 healthy older adults enhance cerebellar grey matter and auditory working memory, despite general brain atrophy". Neuroimage: Reports. 3 (2): 100166. doi:10.1016/j.ynirp.2023.100166.
  97. ^ Vik BM, Skeie GO, Specht K (25 June 2019). "Neuroplastic Effects in Patients With Traumatic Brain Injury After Music-Supported Therapy". Frontiers in Human Neuroscience. 13: 177. doi:10.3389/fnhum.2019.00177. ISSN 1662-5161. PMC 6604902. PMID 31293405.
  98. ^ Tarumi T, Zhang R (January 2014). "Cerebral hemodynamics of the aging brain: risk of Alzheimer disease and benefit of aerobic exercise". Frontiers in Physiology. 5: 6. doi:10.3389/fphys.2014.00006. PMC 3896879. PMID 24478719. Exercise-related improvements in brain function and structure may be conferred by the concurrent adaptations in vascular function and structure. Aerobic exercise increases the peripheral levels of growth factors (e.g., BDNF, IFG-1, and VEGF) that cross the blood-brain barrier (BBB) and stimulate neurogenesis and angiogenesis (Trejo et al., 2001; Lee et al., 2002; Fabel et al., 2003; Lopez-Lopez et al., 2004).
  99. ^ Szuhany KL, Bugatti M, Otto MW (January 2015). "A meta-analytic review of the effects of exercise on brain-derived neurotrophic factor". Journal of Psychiatric Research. 60: 56–64. doi:10.1016/j.jpsychires.2014.10.003. PMC 4314337. PMID 25455510. Consistent evidence indicates that exercise improves cognition and mood, with preliminary evidence suggesting that brain-derived neurotrophic factor (BDNF) may mediate these effects. The aim of the current meta-analysis was to provide an estimate of the strength of the association between exercise and increased BDNF levels in humans across multiple exercise paradigms. We conducted a meta-analysis of 29 studies (N = 1111 participants) examining the effect of exercise on BDNF levels in three exercise paradigms: (1) a single session of exercise, (2) a session of exercise following a program of regular exercise, and (3) resting BDNF levels following a program of regular exercise. Moderators of this effect were also examined. Results demonstrated a moderate effect size for increases in BDNF following a single session of exercise (Hedges' g = 0.46, p < 0.001). Further, regular exercise intensified the effect of a session of exercise on BDNF levels (Hedges' g = 0.59, p = 0.02). Finally, results indicated a small effect of regular exercise on resting BDNF levels (Hedges' g = 0.27, p = 0.005). ... Effect size analysis supports the role of exercise as a strategy for enhancing BDNF activity in humans
  100. ^ a b c d Gomez-Pinilla F, Hillman C (2013). "The Influence of Exercise on Cognitive Abilities". Comprehensive Physiology. Vol. 3. pp. 403–28. doi:10.1002/cphy.c110063. ISBN 978-0-470-65071-4. PMC 3951958. PMID 23720292.
  101. ^ a b c d e Erickson KI, Leckie RL, Weinstein AM (September 2014). "Physical activity, fitness, and gray matter volume". Neurobiology of Aging. 35 (Suppl 2): S20–S28. doi:10.1016/j.neurobiolaging.2014.03.034. PMC 4094356. PMID 24952993.
  102. ^ a b c Erickson KI, Miller DL, Roecklein KA (February 2012). "The aging hippocampus: interactions between exercise, depression, and BDNF". The Neuroscientist. 18 (1): 82–97. doi:10.1177/1073858410397054. PMC 3575139. PMID 21531985.
  103. ^ Lees C, Hopkins J (October 2013). "Effect of aerobic exercise on cognition, academic achievement, and psychosocial function in children: a systematic review of randomized control trials". Preventing Chronic Disease. 10: E174. doi:10.5888/pcd10.130010. PMC 3809922. PMID 24157077.
  104. ^ Carvalho A, Rea IM, Parimon T, Cusack BJ (2014). "Physical activity and cognitive function in individuals over 60 years of age: a systematic review". Clinical Interventions in Aging. 9: 661–682. doi:10.2147/CIA.S55520. PMC 3990369. PMID 24748784.
  105. ^ Guiney H, Machado L (February 2013). "Benefits of regular aerobic exercise for executive functioning in healthy populations". Psychonomic Bulletin & Review. 20 (1): 73–86. doi:10.3758/s13423-012-0345-4. PMID 23229442.
  106. ^ Buckley J, Cohen JD, Kramer AF, McAuley E, Mullen SP (2014). "Cognitive control in the self-regulation of physical activity and sedentary behavior". Frontiers in Human Neuroscience. 8: 747. doi:10.3389/fnhum.2014.00747. PMC 4179677. PMID 25324754.
  107. ^ a b Karns CM, Dow MW, Neville HJ (July 2012). "Altered cross-modal processing in the primary auditory cortex of congenitally deaf adults: a visual-somatosensory fMRI study with a double-flash illusion". The Journal of Neuroscience. 32 (28): 9626–9638. doi:10.1523/JNEUROSCI.6488-11.2012. PMC 3752073. PMID 22787048. Archived from the original on 17 March 2020.
  108. ^ a b Bottari D, Heimler B, Caclin A, Dalmolin A, Giard MH, Pavani F (July 2014). "Visual change detection recruits auditory cortices in early deafness". NeuroImage. 94: 172–184. doi:10.1016/j.neuroimage.2014.02.031. PMID 24636881. S2CID 207189746. Archived from the original on 20 November 2020. Retrieved 11 November 2020.
  109. ^ a b Bavelier D, Brozinsky C, Tomann A, Mitchell T, Neville H, Liu G (November 2001). "Impact of early deafness and early exposure to sign language on the cerebral organization for motion processing". The Journal of Neuroscience. 21 (22): 8931–8942. doi:10.1523/JNEUROSCI.21-22-08931.2001. PMC 6762265. PMID 11698604. Archived from the original on 4 June 2020.
  110. ^ Neville HJ, Lawson D (March 1987). "Attention to central and peripheral visual space in a movement detection task: an event-related potential and behavioral study. II. Congenitally deaf adults". Brain Research. 405 (2): 268–283. doi:10.1016/0006-8993(87)90296-4. PMID 3567605. S2CID 41719446.
  111. ^ Armstrong BA, Neville HJ, Hillyard SA, Mitchell TV (November 2002). "Auditory deprivation affects processing of motion, but not color". Brain Research. Cognitive Brain Research. 14 (3): 422–434. doi:10.1016/S0926-6410(02)00211-2. PMID 12421665.
  112. ^ Stivalet P, Moreno Y, Richard J, Barraud PA, Raphel C (January 1998). "Differences in visual search tasks between congenitally deaf and normally hearing adults". Brain Research. Cognitive Brain Research. 6 (3): 227–232. doi:10.1016/S0926-6410(97)00026-8. PMID 9479074.
  113. ^ a b Heimler B, Pavani F (April 2014). "Response speed advantage for vision does not extend to touch in early deaf adults". Experimental Brain Research. 232 (4): 1335–1341. doi:10.1007/s00221-014-3852-x. hdl:11572/67241. PMID 24477765. S2CID 18995518. Archived from the original on 4 June 2018. Retrieved 11 November 2020.
  114. ^ Hauthal N, Debener S, Rach S, Sandmann P, Thorne JD (2015). "Visuo-tactile interactions in the congenitally deaf: a behavioral and event-related potential study". Frontiers in Integrative Neuroscience. 8: 98. doi:10.3389/fnint.2014.00098. PMC 4300915. PMID 25653602.
  115. ^ Scott GD, Karns CM, Dow MW, Stevens C, Neville HJ (2014). "Enhanced peripheral visual processing in congenitally deaf humans is supported by multiple brain regions, including primary auditory cortex". Frontiers in Human Neuroscience. 8: 177. doi:10.3389/fnhum.2014.00177. PMC 3972453. PMID 24723877.
  116. ^ Bavelier D, Dye MW, Hauser PC (November 2006). "Do deaf individuals see better?". Trends in Cognitive Sciences. 10 (11): 512–518. doi:10.1016/j.tics.2006.09.006. PMC 2885708. PMID 17015029.
  117. ^ Levänen S, Hamdorf D (March 2001). "Feeling vibrations: enhanced tactile sensitivity in congenitally deaf humans". Neuroscience Letters. 301 (1): 75–77. doi:10.1016/S0304-3940(01)01597-X. PMID 11239720. S2CID 1650771. Archived from the original on 20 November 2020. Retrieved 11 November 2020.
  118. ^ Auer ET, Bernstein LE, Sungkarat W, Singh M (May 2007). "Vibrotactile activation of the auditory cortices in deaf versus hearing adults". NeuroReport. 18 (7): 645–648. doi:10.1097/WNR.0b013e3280d943b9. PMC 1934619. PMID 17426591. Archived from the original on 20 November 2020.
  119. ^ Kral A, Sharma A (February 2012). "Developmental neuroplasticity after cochlear implantation". Trends in Neurosciences. 35 (2): 111–122. doi:10.1016/j.tins.2011.09.004. PMC 3561718. PMID 22104561.
  120. ^ Kral A, O'Donoghue GM (October 2010). "Profound deafness in childhood". The New England Journal of Medicine. 363 (15): 1438–1450. doi:10.1056/nejmra0911225. PMID 20925546. S2CID 13639137.
  121. ^ Dormal G, Rezk M, Yakobov E, Lepore F, Collignon O (July 2016). "Auditory motion in the sighted and blind: Early visual deprivation triggers a large-scale imbalance between auditory and "visual" brain regions". NeuroImage. 134: 630–644. doi:10.1016/j.neuroimage.2016.04.027. PMID 27107468. S2CID 25832602. Archived from the original on 20 November 2020. Retrieved 11 November 2020.
  122. ^ Cappagli G, Cocchi E, Gori M (May 2017). "Auditory and proprioceptive spatial impairments in blind children and adults". Developmental Science. 20 (3): e12374. doi:10.1111/desc.12374. PMID 26613827. Archived from the original on 20 November 2020. Retrieved 11 November 2020.
  123. ^ Vercillo T, Burr D, Gori M (June 2016). "Early visual deprivation severely compromises the auditory sense of space in congenitally blind children". Developmental Psychology. 52 (6): 847–853. doi:10.1037/dev0000103. PMC 5053362. PMID 27228448.
  124. ^ Thaler L, Arnott SR, Goodale MA (13 August 2010). "Human Echolocation I". Journal of Vision. 10 (7): 1050. doi:10.1167/10.7.1050.
  125. ^ a b Thaler L, Arnott SR, Goodale MA (2011). "Neural correlates of natural human echolocation in early and late blind echolocation experts". PLOS ONE. 6 (5): e20162. Bibcode:2011PLoSO...620162T. doi:10.1371/journal.pone.0020162. PMC 3102086. PMID 21633496.
  126. ^ Hart H, Radua J, Nakao T, Mataix-Cols D, Rubia K (February 2013). "Meta-analysis of functional magnetic resonance imaging studies of inhibition and attention in attention-deficit/hyperactivity disorder: exploring task-specific, stimulant medication, and age effects". JAMA Psychiatry. 70 (2): 185–198. doi:10.1001/jamapsychiatry.2013.277. PMID 23247506.
  127. ^ Spencer TJ, Brown A, Seidman LJ, Valera EM, Makris N, Lomedico A, et al. (September 2013). "Effect of psychostimulants on brain structure and function in ADHD: a qualitative literature review of magnetic resonance imaging-based neuroimaging studies". The Journal of Clinical Psychiatry. 74 (9): 902–917. doi:10.4088/JCP.12r08287. PMC 3801446. PMID 24107764.
  128. ^ Frodl T, Skokauskas N (February 2012). "Meta-analysis of structural MRI studies in children and adults with attention deficit hyperactivity disorder indicates treatment effects". Acta Psychiatrica Scandinavica. 125 (2): 114–126. doi:10.1111/j.1600-0447.2011.01786.x. PMID 22118249. S2CID 25954331. Basal ganglia regions like the right globus pallidus, the right putamen, and the nucleus caudatus are structurally affected in children with ADHD. These changes and alterations in limbic regions like ACC and amygdala are more pronounced in non-treated populations and seem to diminish over time from child to adulthood. Treatment seems to have positive effects on brain structure.
  129. ^ Kowalczyk OS, Cubillo AI, Smith A, Barrett N, Giampietro V, Brammer M, et al. (October 2019). "Methylphenidate and atomoxetine normalise fronto-parietal underactivation during sustained attention in ADHD adolescents". European Neuropsychopharmacology. 29 (10): 1102–1116. doi:10.1016/j.euroneuro.2019.07.139. PMID 31358436. S2CID 198983414. Archived from the original on 20 November 2020. Retrieved 11 November 2020.
  130. ^ Masten AS (May 2011). "Resilience in children threatened by extreme adversity: frameworks for research, practice, and translational synergy". Development and Psychopathology. 23 (2): 493–506. doi:10.1017/S0954579411000198. PMID 23786691. S2CID 12068256.
  131. ^ Schore AN (2001). "The effects of early relational trauma on right brain development, affect regulation, and infant mental health". Infant Mental Health Journal. 1 (2): 201–269. doi:10.1002/1097-0355(200101/04)22:1<201::AID-IMHJ8>3.0.CO;2-9. S2CID 9711339.
  132. ^ Cioni G, D'Acunto G, Guzzetta A (2011). "Perinatal brain damage in children". Gene Expression to Neurobiology and Behavior: Human Brain Development and Developmental Disorders. Progress in Brain Research. Vol. 189. pp. 139–154. doi:10.1016/B978-0-444-53884-0.00022-1. ISBN 978-0-444-53884-0. PMID 21489387.
  133. ^ Mundkur N (October 2005). "Neuroplasticity in children". Indian Journal of Pediatrics. 72 (10): 855–857. doi:10.1007/BF02731115. PMID 16272658. S2CID 32108524.
  134. ^ Hyde KL, Lerch J, Norton A, Forgeard M, Winner E, Evans AC, et al. (March 2009). "Musical training shapes structural brain development". The Journal of Neuroscience. 29 (10): 3019–3025. doi:10.1523/JNEUROSCI.5118-08.2009. PMC 2996392. PMID 19279238.
  135. ^ Ker J, Nelson S (June 2019). "The effects of musical training on brain plasticity and cognitive processes" (PDF). Jr Neuro Psych and Brain Res: JNPBR. Archived from the original (PDF) on 29 June 2019.
  136. ^ a b c Parry DM, Goldsmith AR, Millar RP, Glennie LM (March 1997). "Immunocytochemical localization of GnRH precursor in the hypothalamus of European starlings during sexual maturation and photorefractoriness". Journal of Neuroendocrinology. 9 (3): 235–243. doi:10.1046/j.1365-2826.1997.00575.x. PMID 9089475. S2CID 23737670.
  137. ^ a b c Parry DM, Goldsmith AR (August 1993). "Ultrastructural evidence for changes in synaptic input to the hypothalamic luteinizing hormone-releasing hormone neurons in photosensitive and photorefractory starlings". Journal of Neuroendocrinology. 5 (4): 387–95. doi:10.1111/j.1365-2826.1993.tb00499.x. PMID 8401562. S2CID 32142178.
  138. ^ a b c Wayne NL, Kim YJ, Yong-Montenegro RJ (March 1998). "Seasonal fluctuations in the secretory response of neuroendocrine cells of Aplysia californica to inhibitors of protein kinase A and protein kinase C". General and Comparative Endocrinology. 109 (3): 356–365. doi:10.1006/gcen.1997.7040. PMID 9480743.
  139. ^ a b c Hofman MA, Swaab DF (May 1992). "Seasonal changes in the suprachiasmatic nucleus of man". Neuroscience Letters. 139 (2): 257–260. doi:10.1016/0304-3940(92)90566-p. hdl:20.500.11755/44b0a214-7ffe-4a5d-b8e5-290354dd93f5. PMID 1608556. S2CID 22326141. Archived from the original on 20 November 2020. Retrieved 22 October 2020.
  140. ^ a b c d Nottebohm F (December 1981). "A brain for all seasons: cyclical anatomical changes in song control nuclei of the canary brain". Science. 214 (4527): 1368–1370. Bibcode:1981Sci...214.1368N. doi:10.1126/science.7313697. PMID 7313697.
  141. ^ a b Takami S, Urano A (February 1984). "The volume of the toad medial amygdala-anterior preoptic complex is sexually dimorphic and seasonally variable". Neuroscience Letters. 44 (3): 253–258. doi:10.1016/0304-3940(84)90031-4. PMID 6728295. S2CID 42303950.
  142. ^ a b Xiong JJ, Karsch FJ, Lehman MN (March 1997). "Evidence for seasonal plasticity in the gonadotropin-releasing hormone (GnRH) system of the ewe: changes in synaptic inputs onto GnRH neurons". Endocrinology. 138 (3): 1240–1250. doi:10.1210/endo.138.3.5000. PMID 9048632.
  143. ^ Barnea A, Nottebohm F (November 1994). "Seasonal recruitment of hippocampal neurons in adult free-ranging black-capped chickadees". Proceedings of the National Academy of Sciences of the United States of America. 91 (23): 11217–11221. Bibcode:1994PNAS...9111217B. doi:10.1073/pnas.91.23.11217. PMC 45198. PMID 7972037.
  144. ^ Smulders TV, Sasson AD, DeVoogd TJ (May 1995). "Seasonal variation in hippocampal volume in a food-storing bird, the black-capped chickadee". Journal of Neurobiology. 27 (1): 15–25. doi:10.1002/neu.480270103. PMID 7643072.
  145. ^ Smith GT (September 1996). "Seasonal plasticity in the song nuclei of wild rufous-sided towhees". Brain Research. 734 (1–2): 79–85. doi:10.1016/0006-8993(96)00613-0. PMID 8896811. S2CID 37336866.
  146. ^ Tramontin AD, Brenowitz EA (June 2000). "Seasonal plasticity in the adult brain". Trends in Neurosciences. 23 (6): 251–8. doi:10.1016/s0166-2236(00)01558-7. PMID 10838594. S2CID 16888328.
  147. ^ a b Frost SB, Barbay S, Friel KM, Plautz EJ, Nudo RJ (June 2003). "Reorganization of remote cortical regions after ischemic brain injury: a potential substrate for stroke recovery". Journal of Neurophysiology. 89 (6): 3205–3214. doi:10.1152/jn.01143.2002. PMID 12783955. S2CID 14103000.
  148. ^ a b Jain N, Qi HX, Collins CE, Kaas JH (October 2008). "Large-scale reorganization in the somatosensory cortex and thalamus after sensory loss in macaque monkeys". The Journal of Neuroscience. 28 (43): 11042–11060. doi:10.1523/JNEUROSCI.2334-08.2008. PMC 2613515. PMID 18945912.
  149. ^ "Coulter Department of Biomedical Engineering: BME Faculty". Bme.gatech.edu. Archived from the original on 24 June 2008. Retrieved 12 June 2010.
  150. ^ "Progesterone offers no significant benefit in traumatic brain injury clinical trial". news.emory.edu. 10 December 2014. Archived from the original on 27 March 2015. Retrieved 29 December 2016.
  151. ^ a b Lu T, Pan Y, Kao SY, Li C, Kohane I, Chan J, et al. (June 2004). "Gene regulation and DNA damage in the ageing human brain". Nature. 429 (6994): 883–891. Bibcode:2004Natur.429..883L. doi:10.1038/nature02661. PMID 15190254. S2CID 1867993.
  152. ^ Massaad CA, Klann E (May 2011). "Reactive oxygen species in the regulation of synaptic plasticity and memory". Antioxidants & Redox Signaling. 14 (10): 2013–2054. doi:10.1089/ars.2010.3208. PMC 3078504. PMID 20649473.
  153. ^ Mechelli A, Crinion JT, Noppeney U, O'Doherty J, Ashburner J, Frackowiak RS, et al. (October 2004). "Neurolinguistics: structural plasticity in the bilingual brain". Nature. 431 (7010): 757. Bibcode:2004Natur.431..757M. doi:10.1038/431757a. hdl:11858/00-001M-0000-0013-D79B-1. PMID 15483594. S2CID 4338340.
  154. ^ Pliatsikas C, Moschopoulou E, Saddy JD (February 2015). "The effects of bilingualism on the white matter structure of the brain". Proceedings of the National Academy of Sciences of the United States of America. 112 (5): 1334–1337. doi:10.1073/pnas.1414183112. PMC 4321232. PMID 25583505.
  155. ^ Draganski B, Gaser C, Busch V, Schuierer G, Bogdahn U, May A (January 2004). "Neuroplasticity: changes in grey matter induced by training" (PDF). Nature. 427 (6972): 311–312. Bibcode:2004Natur.427..311D. doi:10.1038/427311a. PMID 14737157. S2CID 4421248. Archived (PDF) from the original on 26 June 2022.
  156. ^ Golestani N, Paus T, Zatorre RJ (August 2002). "Anatomical correlates of learning novel speech sounds". Neuron. 35 (5): 997–1010. doi:10.1016/S0896-6273(02)00862-0. PMID 12372292. S2CID 16089380.
  157. ^ Lee, S., Jeong, J., Kwak, Y., Park, S.K. (2010). "Depression research: where are we now?". Molecular Brain. 3: 8. doi:10.1186/1756-6606-3-8. PMC 2848031. PMID 20219105.
  158. ^ Rodrigo Machado-Vieira, Jacqueline Baumann, Cristina Wheeler-Castillo, David Latov, Ioline D. Henter, Giacomo Salvadore, et al. (2010). "The Timing of Antidepressant Effects: A Comparison of Diverse Pharmacological and Somatic Treatments". Pharmaceuticals (Basel, Switzerland). 3 (1): 19–41. doi:10.3390/ph3010019. PMC 3991019. PMID 27713241.
  159. ^ Christopher Pittenger, Ronald S Duman (2008). "Stress, Depression, and Neuroplasticity: A Convergence of Mechanisms". Neuropsychopharmacology. 33 (1): 88–109. doi:10.1038/sj.npp.1301574. PMID 17851537. S2CID 646328.
  160. ^ Sophie E. Holmes, Dustin Scheinost, Sjoerd J. Finnema, Mika Naganawa, Margaret T. Davis, Nicole DellaGioia, et al. (2019). "Lower synaptic density is associated with depression severity and network alterations". Nature Communications. 10 (1): 1529. Bibcode:2019NatCo..10.1529H. doi:10.1038/s41467-019-09562-7. PMC 6449365. PMID 30948709.
  161. ^ Ioana Rădulescu, Ana Miruna, Drăgoi Simona, Corina Trifu, Mihai Bogdan Cristea (5 August 2021). "Neuroplasticity and depression: Rewiring the brain's networks through pharmacological therapy". Experimental and Therapeutic Medicine. 22 (4): 1131. doi:10.3892/etm.2021.10565. PMC 8383338. PMID 34504581.
  162. ^ Catharine H. Duman, Ronald S. Duman (2015). "Spine synapse remodeling in the pathophysiology and treatment of depression". Neuroscience Letters. 601: 20–29. doi:10.1016/j.neulet.2015.01.022. PMC 4497940. PMID 25582786.
  163. ^ Calvin Ly, Alexandra C. Greb, Lindsay P. Cameron, Jonathan M. Wong, Eden V. Barragan, Paige C. Wilson, et al. (2018). "Psychedelics Promote Structural and Functional Neural Plasticity". Cell Reports. 23 (11): 3170–3182. doi:10.1016/j.celrep.2018.05.022. PMC 6082376. PMID 29898390.

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