Part 1: Definition and Discovery of Neuroplasticity, Examples of Neuroplasticity, Observations and Causes of Neuroplasticity and Positive/Negative Plasticity

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Definition and Discovery of Neuroplasticity

Neuroplasticity is an umbrella term used to refer to the ability of our brain to reorganise itself, both physically and functionally, throughout our lives due to our environment, behaviour, thinking, and emotions (Hampton, 2015).

Also known as brain plasticity and neural plasticity, it is the ability of the brain to change throughout an individual’s life, e.g. brain activity associated with a given function can be transferred to a different location, the proportion of grey matter can change, and synapses may strengthen or weaken over time.

We used to think that the adult brain was pretty much a physiologically static and fixed organ, or hard wired after critical developmental periods in childhood (Hampton, 2015).

Have you ever heard the phrase “you can’t teach an old dog new tricks”? Basically, it means that once we pass the childhood stage and a certain age, we’re stuck with whatever we have learned – our ways, habits, personality, character…

So, we went on believing this to be true for centuries, and although the concept of neuroplasticity is not new and mentions of a “malleable brain” go way back to the 1800s, it was only with the relatively recent capability to visually “see” into the brain, using functional magnetic resonance imaging (fMRI), that science has confirmed this incredible changing ability of the brain beyond a doubt (Hampton, 2016).

Research beginning in the latter half of the 20th century showed that many aspects of the brain can be altered (or are “plastic”), even through adulthood (Bennett et al., 1964; Livingston, 1966; Rakic, 2002; Sasmita et al., 2018).

However, the developing brain exhibits a higher degree of plasticity than the adult brain (Hensch and Bilimoria, 2012; Ryugo and Limb, 2000).

Michael Merzenich, one of the most significant researchers in the neuroplasticity discovery, was conducting experiments back in the early 1970s to prove that the brain was specialised, compartmentalised and fixed. He was attempting to show that if there was damage to one part of the brain, because it had a fixed function, that skill could not be relearned.

But ironically, he proved the exact opposite, with the research revealing that the brain is one big learning tissue, and that the skills previously learned by damaged tissue can be relearned in other parts of the brain. There is much evidence where this is visible (DrDonna, 2013).

Examples of Neuroplasticity

A study in 2006 by Maguire, Woollett and Spiers showed that London taxi drivers have a larger hippocampus (in the temporal lobe) than London bus drivers (Maguire, Woollett and Spiers, 2006). This is explained by the fact that the hippocampus is key in efficient navigation, through its role in the formation and access of complex memories, including spatial ones. The hippocampus of taxi drivers is stimulated more than that of bus drivers and gets to change over time, given the way in which taxi drivers have to navigate around London as opposed to following the limited set of routes that bus drivers do.

Plasticity has been observed in the brains of bilingual people, where the left inferior parietal cortex is larger than in monolingual brains, suggesting that learning a second language is associated with structural changes in the brain (Mechelli et al., 2004).

Plastic changes also occur in the brains of musicians compared to non-musicians.

In 2003, Gaser and Schlaug compared professional musicians (who practice at least one hour per day) to amateur musicians and non-musicians, and they found that in several brain areas involved in playing music (motor regions, anterior superior parietal areas and inferior temporal areas), the volume of cortex was:

  • Highest in professional musicians
  • Intermediate in amateur musicians
  • Lowest in non-musicians

(Gaser and Schlaug, 2003)

In another study in 2006, Draganski and his colleagues imaged the brains of German medical students 3 months before their medical exam and right after the exam.

They then compared the brains of these students to the brains of students who were not studying for exams at this time and discovered that the medical student’s brains showed changes in regions of brain known to be involved in memory and learning (Draganski et al, 2006).

This shows one more time that we don’t need to become an expert to exhibit signs of neuroplasticity, and that changes in the brain will occur following any experience of learning.

And just in case you are in any doubt whatsoever, as to how powerful and capable your mind is, the following experiment should excite you:

The experiment took place in Harvard Medical School, by neuroscientist Alvaro Pascual-Leone, whereby volunteers were asked into the lab to learn and practice a little five-finger piano exercise.

Another group of volunteers were asked to come in and merely think about practicing the piano exercise, by playing the simple piece of music in their head, holding their hands still while imagining how they would move their fingers. They were all instructed to play as fluidly as they could, trying to keep to the metronome’s 60 beats per minute (a device used by musicians that marks time at a selected rate by giving a regular tick) (Begley, 2007).

For five consecutive days, the volunteers practiced for two hours and then took a test.

At the end of each day’s practice session, they sat beneath a coil of wire that sent a brief magnetic pulse into the motor cortex of their brain, located in a strip running from the crown of the head toward each ear.

The so-called transcranial magnetic stimulation (TMS) test allows scientists to infer the function of neurons just beneath the coil (Begley, 2007).

In the piano players, the TMS mapped how much of the motor cortex controlled the finger movements needed for the piano exercise.

The scientists compared the TMS data on the two groups after a week of practice, and found that it showed the same expansion in the region of motor cortex that controls the piano-playing fingers, in those who actually physically played the piano and those who only imagined doing so (Begley, 2007)!

Observations and Causes of Neuroplasticity

Neuroplasticity can be observed at multiple scales, from microscopic changes in individual neurons to larger-scale changes such as cortical remapping in response to injury (Pascual-Leone et al., 2011).

Behaviour, environmental stimuli, thoughts, and emotions may also cause neuroplastic change through activity-dependent plasticity, which has significant implications for healthy development, learning, memory, and recovery from brain damage (Pascual-Leone et al., 2011; Ganguly and Poo, 2013; Keller and Just, 2016).

At the single cell level, synaptic plasticity refers to changes in the connections between neurons, whereas non-synaptic plasticity refers to changes in their intrinsic excitability.

One of the fundamental principles underlying neuroplasticity is based on the idea that individual synaptic connections are constantly being removed or recreated, largely dependent upon the activity of the neurons that bear them.

The activity-dependence of synaptic plasticity is captured in the aphorism which is often used to summarise Hebbian theory:

  • “neurons that fire together, wire together”
  • “neurons that fire out of sync, fail to link”

If two nearby neurons often produce an impulse in close temporal proximity, their functional properties may converge.

Conversely, neurons that are not regularly activated simultaneously may be less likely to functionally converge.

In the late 1970s and early 1980s several groups began exploring the impact of interfering with sensory inputs on cortical map reorganisation.

Researchers in the field included Michael Merzenich, Jon Kaas and Doug Rasmusson.

They found that if the cortical map is deprived of its input, it activates at a later time in response to other, usually adjacent inputs.

Many research groups have since corroborated and extended these findings.

Merzenich’s 1984 study involved the mapping of owl monkey hands before and after amputation of the third digit.

Before amputation, the cortical map had five distinct areas, one each corresponding to each digit of the experimental hand.

Sixty two days following amputation of the third digit, the area in the cortical map formerly occupied by that digit had been invaded by the previously adjacent second and fourth digit zones.

The areas representing digit one and five are not located directly beside the area representing digit three, so these regions remained, for the most part, unchanged following amputation (Merzenich, 1984).

This study demonstrates that only those regions that border a certain area invade it to alter the cortical map (Anderson, 2012).

In the somatic sensory system, in which this phenomenon has been most thoroughly investigated, Wall, Xu and Wang have traced the mechanisms underlying this plasticity.

Reorganisation is not cortically emergent, but occurs at every level in the processing hierarchy; this produces the map changes observed in the cerebral cortex (Wall, Xu and Wang, 2002).

Merzenich, Recanzone and Jenkins (1990) initiated studies relating sensory experience, without pathological perturbation, to cortically observed plasticity in the primate somatosensory system, with the finding that sensory sites activated in an attended operant behaviour increase in their cortical representation (Jenkins, Merzenich and Recanzone, 1990).

Shortly thereafter, Ford Ebner and colleagues (1994) made similar efforts in the rodent whisker barrel cortex (also part of the somatosensory system) (Armstrong-James, Diamond and Ebner 1994).

These two groups largely diverged over the years.

The rodent whisker barrel efforts became a focus for Ebner, Matthew Diamond, Michael Armstrong James, Robert Sachdev and Kevin Fox.

Great inroads were made in identifying the locus of change as being at cortical synapses expressing NMDA receptors (important for controlling synaptic plasticity and memory function), and in implicating cholinergic inputs (which promote cortical activation during both wakefulness and rapid eye movement sleep) as necessary for normal expression.

The work of Ron Frostig, Daniel Polley and others (1999, 2004) identified behavioural manipulations causing a substantial impact on the cortical plasticity in that system (Polley, Chen-Bee and Frostig, 1999; Polley, Kvasnak and Frostig, 2004).

Merzenich and Blake (2002, 2005, 2006) went on to use cortical implants to study the evolution of plasticity in both the somatosensory and auditory systems. Both systems show similar changes with respect to behaviour (Blake et al., 2002; Blake et al., 2002; Blake et al., 2005; Blake et al., 2006).

When a stimulus becomes cognitively associated with reinforcement, its cortical representation is strengthened and enlarged.

In some cases, cortical representations can increase two to threefold in 1 to 2 days when a new sensory motor behaviour is first acquired, and changes are largely finalised within at most a few weeks.

Control studies show that these changes are not caused by sensory experience alone: they require learning about the sensory experience, they are strongest for the stimuli that are associated with reward, and they occur with equal ease in operant and in classical conditioning behaviours.

‘Positive/Negative Plasticity’

Norman Doidge, following the lead of Michael Merzenich, separates manifestations of neuroplasticity into adaptations that have positive or negative behavioural consequences.

For example, if an organism can recover after a stroke to normal levels of performance, that adaptiveness could be considered an example of “positive plasticity”.

Changes such as an excessive level of neuronal growth leading to spasticity or tonic paralysis, or excessive neurotransmitter release in response to injury that could result in nerve cell death are considered as an example of “negative” plasticity.

In addition, Dr. Doidge deems both drug addiction and obsessive-compulsive disorder as examples of “negative plasticity”, as the synaptic rewiring resulting in these behaviours is also highly maladaptive.

A 2005 study found that the effects of neuroplasticity occur even more rapidly than previously expected. Researchers imaged the brains of medical students during a period of their studying for exams. In a matter of months, the student’s gray matter increased significantly in the posterior and lateral parietal cortex (Draganski et al., 2006).

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