By: Carolyn A. Scott, Ph.D.
Rainbow Rehabilitation Centers
Editor’s Note: While the last edition of RainbowVisions focused on our developing understanding of neuroplasticity, the neurobiology of neuroplasticity, and neuroplasticity after acquired brain injury, this article focuses more specifically on evidence for neuroplasticity in cognitive domains.
An individual who experiences a traumatic brain injury may also experience resulting deficits in cognition. To better understand how the brain works and recovers from injury, we must have an understanding of how the brain learns and adapts to experience. This understanding may also help us shape our treatments so they are most effective.
The first portion of this article will explore examples of neuroplasticity in cognition within a typical adult brain. The second portion will examine examples of cognitive neuroplasticity in adult individuals who sustained an acquired brain injury.
Neuroplasticity has been demonstrated in several cognitive domains. Evidence for plasticity of visuospatial (the identification of the location of objects) and visuoperceptual skills (the ability to identify attributes) and memory of visually presented information has been demonstrated.
The hippocampus and medial temporal lobes are used in making new memories (Scoville & Milner, 1957) and more specifically, episodic memory, which relates to autobiographical events (Burgess, Becker, King, O’Keefe, 2001; Burgess, Maguire, & O’Keefe, 2002; Vargha-Khadem, et al., 1997) and spatial memory which facilitates navigation (Burgess, Maguire, & O’Keefe, 2002; Vargha-Khadem et al., 1997).
Differences in the size of the hippocampus have been found among animals and humans. For example, in songbirds who store their food, hippocampal volume is greater relative to their brain and body size as compared to non-food storing birds (Lee et al., 2001). Additionally, hippocampal volume was found to be greater during food storing season (fall) as compared to spring (Smulders, Sasson, & DeVoogd, 1995) highlighting that brain volume changed with experience as the hippocampus was more or less utilized.
Maguire et al. (2000) examined the brains of healthy, licensed taxi drivers in London to evaluate whether their extensive navigation experience would result in structural brain changes as compared to healthy non-taxi driver control groups.
Taxi drivers in London acquire approximately three to four years of training to learn the city and then must pass a series of examinations prior to licensure. Maguire et al. (2000) found that the taxi drivers had significantly increased gray matter volume in the bilateral posterior hippocampus as compared to controls, and that controls had larger bilateral anterior hippocampi. No other significant group differences were found when comparing the taxi driver and control groups’ brains.
Additionally, the longer an individual had worked as a taxi driver, the greater their right posterior hippocampal volume (while controlling for age). The authors note that prior research has indicated that the posterior hippocampus is useful in recalling previously learned visuospatial information, and propose that the above differences in hippocampal volume were redistributions of “gray matter in the hippocampus” to accommodate increasingly detailed mental maps of London.
Taxi drivers are assumed to have more detailed maps than control groups and more experienced drivers are assumed to have more detailed maps than less experienced drivers. The hippocampus is proposed to be important in the storage of and use of mental maps of our surroundings (Maguire et al., 2000).
As follow up to these findings, Maguire et al. (2003) used imaging to investigate whether increased posterior hippocampal size was related to experience gained as a taxi driver or innate navigational expertise.
To do this, the authors had a sample of healthy non-taxi drivers navigate through a virtual-reality town and then later recreate the town from memory. The participants were also tested on their ability to recognize scenes from the town and on visual and verbal memory tasks
Based on their performance on the above tests, participants were grouped according to their apparently innate navigational ability. Maguire et al. (2003) did not find any association between gray-matter volume on imaging and performance on the navigational or memory tasks.
Maguire et al. (2003) suggests that this lack of a finding further supports their hypothesis that it is the experience (time spent by the taxi drivers acquiring and then updating mental maps of London) that caused an increase in posterior hippocampal volume.
Further research on navigational abilities and neuroplasticity indicated that driving flexible routes (taxi drivers vs. bus drivers; Maguire, Woollett, & Spiers, 2006) is related to greater right posterior hippocampal volume.
Similarly, individuals training to become taxi drivers had significant increases in their posterior hippocampal gray matter volume at the completion of training as compared to:
- before training
- individuals who failed to complete training
- control participants who were not undergoing training (Woollett and Maguire, 2011).
Rodent models support the finding that effortful learning takes place in the hippocampus and this learning is related to neurogenesis, the growth of new neurons (Gould, Beylin, Tanapat, Reeves, & Shorts, 1999).
Language is another domain where evidence for neuroplasticity has been found. Recovery of language abilities after injury will be discussed later in the article but plasticity has also been documented in healthy adults during second language learning.
Mechelli et al. (2004) used voxel-based morphometry, a neuroimaging analysis technique, to examine the differences in gray matter (which largely contains neuronal cell bodies) and white matter (which largely consists of myelinated axons) between English speaking monolinguals and bilinguals.
The bilinguals were split into two groups; those who learned a second European language before age 5 and used it regularly and those who learned a second European language between ages 10-15 and spoke the language for at least five years.
Gray-matter density in the left inferior parietal cortex was greater in bilingual individuals as compared to monolinguals (Mechelli et al., 2004). Those who learned the second language at an earlier age had greater volumes of gray matter in the inferior parietal cortex as compared to the bilingual group who had learned a second language at an older age (Mechelli et al., 2004).
Mechelli et al (2004) also examined English proficiency (reading, writing, comprehension, and production) among native Italian speakers who learned English between ages 2 and 34. There were no significant differences in gray or white matter, except that those with greater second language proficiency had significantly greater gray matter density in the same region of the left inferior parietal cortex as highlighted in the mono vs. bilingual study.
Furthermore, the individuals who learned English at a later age had less left inferior parietal region density as compared to those who learned at an earlier age (Mechelli et al., 2004).
The authors propose that experience alters the structure of the brain. Additional support for plasticity in second-language learning comes from Osterhout et al. (2008). They found evidence for structural change in the brain due to second-language learning.
In a small pilot study, the authors found that individuals learning a second language in an intensive but short-term setting had changes in their gray matter using voxel-based morphometry.
Musicians can also illustrate experience-dependent neuroplasticity. For example, conductors, who need to be able to locate sounds more often than other musicians or non-musicians, are better at separating adjacent sound sources in their peripheral auditory field (Munte, Altenmuller, & Jancke, 2002).
Munte et al. (2002) also reviewed evidence demonstrating that the auditory cortex can be shaped by years of practice as professional musicians can distinguish differences in a sequence of notes sooner than non-musicians.
Increased gray matter volumes in several brain regions can be found in musicians as compared to non-musicians (Gasser & Schlaug, 2003; Schlaug, Jancke, Huang, & Steimetz, 1995). Gaser and Schlaug (2003) used voxel-based morphometry to look at brain anatomy differences among professional musicians, amateur musicians, and nonmusicians. The authors found a positive correlation (professional musicians > amateur musicians > non-musicians) in the amount of gray matter in the following regions: primary motor and sensory, premotor, anterior superior parietal, and inferior temporal gyrus bilaterally.
While Gaser and Schlaug (2003) acknowledged that individuals with anatomy-supporting music skill may self-select to become musicians, they note that animal research and work with humans in multiple domains has found experience-driven plasticity.
They conclude that it is likely that the musicians’ extensive practice with their instrument (in this case, the keyboard) contributed to the greater amounts of gray matter in the above noted areas.
Neuroplasticity after brain injury
While evidence exists for experience-dependent changes in the brain within some of the cognitive domains, there is less research discussing cognitive plasticity and recovery following acquired brain injury (ABI), in particular, traumatic brain injury (TBI).
Stroke has provided a good research model for examining plasticity and rehabilitation as it typically involves a more discrete lesion than traumatic brain injury. The research from the stroke population can be extrapolated to the TBI population with some caution.
Neuroplasticity and aphasia
Experience-dependent changes in language skills have been found in healthy adults and individuals with stroke (Fridriksson, 2010; Vitali et al., 2007). Fridriksson (2010) looked at 26 individuals with chronic aphasia and had them complete 30 hours of training targeting anomia (difficulty in recall of words or names).
The individuals’ ability to produce the names of common objects during an fMRI scan prior to training and after training was then measured. Fridriksson (2010) found that participants who had a significant increase pre-training to post-training in left hemisphere activation (particularly the parietal lobe and premotor cortex) demonstrated improvement in naming ability. This was as compared to those who did not have a significant change in cortical activation (between onset and completion of training) or those who had damage in those areas in the left hemisphere.
Thus, changes in experience (in the form of training) resulted in cortical changes as measured by greater neural activation, highlighting an example of experience-dependent neuroplasticity in the cognitive domain. Additional methods for treating aphasia after stroke were designed to capitalize on this neuroplasticity.
Plasticity and treatment of aphasia
In our last issue of RainbowVisions Magazine, the potential negative of plasticity was discussed. Specifically, learned non-use was reviewed with the idea being that you must “use it or lose it.” If individuals with acquired brain injury did not use the tissue around the lesion location, that surviving tissue would map to another function or site.
An example of this is individuals who experienced residual upper extremity hemiplegia (one-sided paralysis) as a result of their stroke. These individuals fail to use their hemiparetic arm spontaneously, preferring to use their intact arm as a compensatory strategy. Without encouragement to use their weak side, the stronger upper extremity is used more often, reinforcing its use and reinforcing the learned non-use of the hemiparetic extremity.
Taub introduced a new method of treatment, dubbed Constraint-Induced Movement Therapy (CIMT) to help individuals with chronic hemiparesis. In CIMT, participants are required to use their more affected extremity for long, intensive, and repetitive therapy sessions. The positive progress made by individuals with chronic motoric deficits encouraged researchers to use a similar therapy design to treat chronic aphasia. The resulting treatment, Constraint-Induced Aphasia Therapy (CIAT), has been called Constraint-Induced Language Therapy and Intensive Language Action Therapy but the principles remain similar.
There are four main components to CIAT (Meinzer, Rodriguez, & Gonzalez Rothi, 2012). Therapy participants are trained in a setting so that the therapy is relevant to daily life and more likely to generalize. The therapist uses shaping which is a gradual increase in task difficulty as the participant achieves mastery through practice. Massed-practice (longer sessions over a few weeks or longer with material presented numerous times), is used in order to drive Hebbian learning (neurons that ‘fire together, wire together’).
And finally, to overcome learned nonuse, the use of gestures, writing, and communication devices is restricted or discouraged. Learned non-use in speech is often the result of repeated failure to satisfactorily verbalize one’s thoughts and the resulting reinforcement of alternative communication strategies (Pulvermuller et al. 2001).
Constraint-induced aphasia therapy has been found to be effective in treating chronic aphasia (Kurland, Pulvermuller, Silva, Burke, & Andrianopoulos, 2012; Pulvermuller et al., 2001; see Meinzer, Rodriguez, & Gonzalez Rothi, 2012 for a review) and research is beginning to explore whether CIAT can be effective in treating acute aphasia.
Kirmess and Maher (2010) adapted CIAT to accommodate a rehabilitation hospital setting (e.g., greater interruptions and participant fatigue) and found it to be an effective treatment, however, the study included only three individuals and would need replication.
Few studies have used imaging to demonstrate the plastic changes which appear to be occurring (see Meinzer, Rodriguez, & Gonzalez Rothi, 2012 for a review) during CIAT. In a study of 16 chronically aphasic individuals who underwent CIAT, Richter, Miltner, and Straub (2008) scanned participants in fMRI before and after treatment.
They found that increased right hemisphere activity during language tasks before therapy predicted a better response to treatment, while decreased activity in parts of the right-hemisphere after CIAT predicted language improvement. Richter, Miltner, and Straub (2008) did not find significant differences in the left hemisphere as a result of training.
Meinzer et al. (2008) used fMRI to demonstrate that increased activity in the perilesional area (areas close to the lesion) was correlated with language improvement for trained materials. Activity in other areas of the left or right hemisphere was not related to language improvement (Meinzer et al, 2008).
The authors suggested that the improvement demonstrated by participants was related to increased connectivity to the perilesional areas. Further research needs to be conducted to better clarify the biological basis for CIAT’s success.
Plasticity and neglect
Another cognitive deficit that may be found after an acquired brain injury is neglect. Visual neglect occurs subsequent to right hemisphere lesions and it has been argued to occur as a result of impairment in attention.
Thimm, Fink, Kust, Karbe, and Strum (2006) examined the impact of computerized alertness training on a group of individuals with chronic and stable spatial neglect. At the completion of the three-week training, participants were more alert and performed better on tests measuring neglect. They also demonstrated increased activation in areas of both hemispheres which have been associated with alertness and spatial attention.
However, when the participants were scanned again a month after completing training, their performance on behavioral tests had returned to baseline. In contrast, they continued to demonstrate increased activation in the bilateral frontal areas, right anterior cingulate cortex, right angular gyrus, and left tempoparietal cortex.
Thimm, Fink, Kust, Karbe, and Strum (2006) suggest that the poor sustainability in gains on behavioral neglect tests may have been related to the measures used to assess neglect but also suggests that there were no long-term effects of alertness training.
The authors also suggest that continued increased activation in the brain (as measured on fMRI) was indicative of neuroplasticity, the reactivation of attentional networks. However, Thimm, Fink, Kust, Karbe, and Strum (2006) note that the reactivation of these networks was not sufficient to elicit long-term improvement of neglect symptoms.
Much of the work on neuroplasticity in the cognitive domains suffers from the same weaknesses. The number of participants in the studies is too small or focuses on one population, making it hard to generalize the findings.
Furthermore, neuroimaging techniques can present their own challenges so that, at times, it can be difficult to determine whether findings are spurious or the result of true change (Terrazas & McNaughton, 2000).
Additionally, as the work with neglect pointed out, observed neuroplasticity on imaging may not translate to functional gains. Finally, it should also be noted that some would argue (Rose, 2013) that restricting the use of gestures may interfere with natural language cueing and that research on multimodality speech therapies has demonstrated that these treatments have similar outcomes to constraint-induced aphasia therapies.
What can be done?
The evidence for experience-dependent neuroplasticity within cognitive domains continues to build, and as treatment providers, the industry is in a unique position to help clients maximize their own plasticity.
Kleim and Jones’ (2008) principles of experience-dependent neural plasticity can help us shape therapy for our clients. Clients must “use it or lose it”, “use it and improve it”, and have an opportunity for repetitive, intense, and specific therapy that can transfer to other settings.
Ultimately, we want individuals who have experienced a traumatic brain injury to have the opportunity to maximize their recovery through experiences which encourage plasticity within their brains.
Carolyn A. Scott, Ph.D.
Dr. Scott earned her Ph.D. at Wayne State University in Clinical Psychology. After an internship at the John D. Dingell VA Medical Center, she completed specialized post-doctoral training in Neuropsychology and Rehabilitation Psychology at the Rehabilitation Institute of Michigan. While there, Dr. Scott worked with individuals who had experienced traumatic brain injuries, stroke, spinal cord injuries, and other neurological and orthopedic conditions on both an inpatient and outpatient basis. In addition to other responsibilities, Dr. Scott provides client and team consultation services and brief and expanded neuropsychological evaluations at Rainbow Rehabilitation Centers, Inc.
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