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Cognitive impairments are one of the most prevalent and debilitating results of traumatic brain injury (TBI), and they can have a substantial impact on a persons social and professional prospects. Thus, disruption to white-matter pathways induced by diffuse axonal injury (DAI) causes a wide variety of cognitive problems (Galetto & Sacco, 2017). As a result of DAI, a vast network of regions serving various cognitive tasks may be affected, resulting in continuous impairments in the realms of executive functioning, attention, and memory. Although there is a period of transient remodelling in the early post-injury phase owing to the resolution of severe neurological events, many abnormalities remain in the chronic stage of injury. Several studies have shown the significance of cognitive rehabilitation in reducing the cognitive and behavioural repercussions of TBI, hence enhancing patients quality of life and autonomy.
Cognitive rehabilitation is described as a structured, functionally focused program of treatments based on assessing the patients brain and behavioural deficiencies. It is not restricted to restorative procedures that directly address cognitive problems produced by brain injury, but it may include the utilization of compensatory mechanisms by developing alternate trends of cognitive activity. Furthermore, it generates new sequences using external support devices, such as adaptive aids or prostheses, to enhance the patients general level of performance and quality of life (Pedrotty et al., 2021). The brain is capable of restructuring and relearning the operations that were compromised after a traumatic brain injury by facilitating the reversal of maladaptive neuroplasticity and resulting in a more effective neural growth state, which is a common aspect of various rehabilitation treatments.
The neuronal plasticity mechanism is modified by the behavioural encounter: the brain may be transformed by a wide range of experiences and stimuli throughout its existence. Even though several studies show the efficiency of rehabilitation in fostering brain repair, only a small percentage of them concentrate on the neural changes generated by cognitive therapy (Galetto & Sacco, 2017). As a result, these cognitive and behavioural measures alone may not give a thorough picture of the causal linkages between lesions, their location, and the functional abnormalities observed by people in their everyday lives.
Currently, new basic characteristics of connectivity maps associated with neural plasticity have been uncovered. Based on data from the motor system, it is commonly acknowledged that, after brain structural injury, both connectivity maps as well as behavioural abilities, may partially be recovered with intensive practice and therapy (Pedrotty et al., 2021). These findings support the notion that motor maps represent a level of neuronal connectivity within the brain essential for skill execution. Concerning biological level, this hypothesis was supported by trials on mice in which cholinergic connections to the motor cortex were blocked before skill training, inhibiting learning-dependent motor cortical map rearrangement and, as a result, impairing motor learning (Li & Hollis, 2021). Based on these considerations, skill training may generate plastic modifications in synaptic effectiveness in the motor cortex, resulting in alterations in map topography.
Behaviourally, the most significant characteristic of task-oriented learning to generate neural plasticity is the severity of training, which is described as the number of repetitions performed for specified tasks over a certain period. It is necessary to accomplish a particular level of training to achieve efficient brain reorganization after an injury. The term experience-dependent neuroplasticity is used to describe this phenomenon. It has been predicted that 1,000 to 10,000 tests of the same activity are required in an animal before a lasting change at the synapse level may be noticed (Li & Hollis, 2021). It has been discovered in animal tests that behavioural motor learning is controlled by the enhancement of long-term potentiation (LTP) and the suppression of long-term depression (LTD). Passive repetition without training results in none of these two systems. The quantity of synapses and networks rises during the early phases of training, and this process may be controlled in experimental contexts by injecting protein synthesis blockers into the cortex, therefore increasing or inhibiting skill growth (Trott et al., 2019). Training without learning, on the other hand, may have negative consequences like a reduction in the number of synapses, decreased postsynaptic responses, and deficits in behavioural skills.
Both animal and human models were studied to describe how actual healing differs from compensation. A specific study looked at the processes of rehabilitation-induced brain neural plasticity in rat species (Turolla et al., 2018). The study looked at whether delivering growth hormone (GH) accompanied by therapy after a severe lesion to the motor cortex may have a favourable long or short-term impact on the healing of the injured upper limb. The results showed that combining GH with motor therapy had a good impact whether used either shortly after or long following the injury (Turolla et al., 2018). GH treatment alone, on the other hand, resulted in better actin and nesting re-expression but no significant changes in behaviour. Another study looked at the application of anodal transcranial direct current stimulation (tDCS) to increase motor and somatosensory function restoration following recurrent traumatic brain injury (TBI). The amplitude and duration of both motor-evoked potentials (MEP) and somatosensory-evoked potentials (SEP) were greater in the tDCS category but lower in the sham-tDCS category (Turolla et al., 2018). These findings imply that anodal tDCS may be a beneficial strategy for enhancing transitory motor recovery by boosting cortical firing synchronization.
Neuroimaging and neurophysiological approaches may enable more accurate evaluation and diagnosis, as well as a better understanding of the brain processes behind cognitive advances. The findings of neuroimaging research have revealed that cognitive rehabilitation can considerably alter brain activity. Cognitive rehabilitation appears to lead to a reset of the dysfunctional mechanisms engaged in the healing process in general. In addition, after acquired brain damage, several self-reinforcing and malfunctioning processes are engaged, according to Gulyaevas (2017) negative plasticity theory. This is most likely due to a conjunction of lowered activity schedules, decreased sensory processing quality, and impaired neuromodulatory regulation. When these elements are combined, they increase dependence on simpler cognitive processes, which leads to negative learning. As a result, when doing increasingly complicated tasks, maladaptive brain alterations arise, resulting in lower cognitive task performance.
A notable illustration of this mechanism is the hyperactivity that is commonly observed following a TBI event, where regions of overactivity are hypothesized to reflect the failed attempts of a vicarial neural system to heal the damage detected in other places. As a consequence, the client needs greater energy to do the activity less spontaneously. Numerous studies have shown that persons with TBI may require to mobilize more wide and dispersed brain resources, particularly in response to difficult settings, to equal the behavioural function of control subjects (Kaur et al., 2020). The reasons for this complicated phenomenon are unknown and vary greatly across individuals: it has been described as brain reconfiguration, neural repair, degeneracy, or inadequate control of neural resources. Some research in the literature perceived this hyperactivation as a sort of reparation that aids task completion, such that in the dearth of compensatory neuronal recruitment, failure to execute or poor task completion would happen (Kaur et al., 2020). Alternatively, it is viewed as a sort of inadequate source control, resulting in the irregular or randomized participation of diverse regions during task execution.
Distinguishing between all of these alternative theories might greatly increase knowledge of how brain activity changes in performance and rehabilitation after TBI. More research on the relationship between neuroimaging and behavioural outcomes is needed. As a result, cognitive restructuring during rehabilitation happens when a patient employs a unique set of cognitive mechanisms to complete the same activity because the person has acquired a new cognitive technique. Thus, this is evident in a shift in a task-specific neuronal structure that occurs during learning or relearning operations in the injured brain, eliminating faulty connections (Owen & Guta, 2019). In several of the studies included in this review, complete functional recovery was followed by decreased patterns of activation, which may be viewed as the consequence of reweighting of interconnections within an established network (Galetto & Sacco, 2017). Even though neither of the research included in this analysis particularly addressed this issue, it is now well accepted that impaired connection can dramatically impair cognitive function in brain-damaged subjects.
In the context of TBI, however, it is fairly restrictive to explain functional recovery after cognitive therapy as the sole outcome of a reduction in malfunctioning hyperactivations. Instead, it is more appropriate to refer to it as a transfer of the neural circuit in which, in addition to a reduction in the zones hyperactivated during the activity, there may be enhanced participation of other neuronal circuits, which are normally engaged in healthy patients. To that aim, Montana et al. (2019) reported an increase in metabolic activity in the right parahippocampal and left hippocampus cortex throughout a verbal task following a computerized spatial memory exercise. Furthermore, there was an upsurge in signalling in the right anterior cingulate cortex, left posterior cingulate cortex, and posterior insula in conjunction with reduced activity in the dorsolateral prefrontal and supplementary motor areas (Montana et al., 2019). Increased activation of comparable circuits, which are regarded as elements of the default mode system, indicates that cognitive rehabilitation can modify this network, resulting in alterations in functional connectivity.
Non-invasive brain stimulation (NIBS) has assumed an important role in cognitive rehabilitation. Since non-invasive and pain-free NIBS methods, which are mostly associated with few side effects, may alter cortical excitation focally, they are increasingly being employed in therapeutic settings (Cripe et al., 2021). Both types of research included in this review demonstrated the usefulness of NIBS approaches in improving cognitive rehabilitation results, even in the context of more complicated cognitive and neurological sequelae (Cripe et al., 2021). Another research found that transcranial magnetic stimulation (TMS) was more effective in improving higher-order cognitive impairments in severely brain-injured patients. According to the findings of previous researchers, only integration of cognitive training and transcranial direct current stimulation (tDCS) was able to elicit substantial improvements in divided concentration in TBI patients (Galetto & Sacco, 2017). On the contrary, cognitive therapy alone was insufficient to enhance control performance. These findings are consistent with previous research, emphasizing the critical significance of NIBS instruments in enhancing neural plasticity and functional performance following brain damage.
Electroencephalography (EEG) and functional or structural magnetic resonance imaging (MRI) are two of the principal methods used to explore the brain alterations caused by TBI (MRI and fMRI, respectively). Researchers can use MRI and fMRI to evaluate brain alterations following therapy treatments in a non-invasive and efficient manner (Galetto & Sacco, 2017). Similarly, ERPs and oscillatory action from the human EEG provide useful details about the seriousness of the injury and its effect on neuronal pathways, such as their effectiveness in directing messages from the peripheral to the central nervous system (CNS), the capacity of CNS systems to sequence sensory information, and the capacity of specific sensory processes to interpret and integrate stimuli.
Several studies have shown the significance of cognitive rehabilitation in reducing the behavioural and cognitive repercussions of TBI, hence boosting patients independence and quality of life. Cognitive rehabilitation aims to intervene in cognitive problems produced by brain injury, as well as grasp the use of corrective mechanisms through the establishment of alternate sequences of cognitive activity. The feature that various rehabilitation treatments have in common is brain plasticity. By facilitating the repair of dysfunctional plasticity and resulting in a more functional neural development state, neural plasticity includes the brain rebuilding and relearning those skills that were lost following acquired brain damage.
References
Cripe, C. T., Cooper, R., Mikulecky, P., Huang, J. H., & Hack, D. C. (2021). Improved Mild Closed Head Traumatic Brain Injury Outcomes With a Brain-Computer Interface Amplified Cognitive Remediation Training. Cureus, 13(5).
Galetto, V., & Sacco, K. (2017). Neuroplastic changes induced by cognitive rehabilitation in traumatic brain injury: A review. Neurorehabilitation and Neural Repair, 31(9), 800-813.
Gulyaeva, N. V. (2017). Molecular mechanisms of neuroplasticity: An expanding universe. Biochemistry (Moscow), 82(3), 237-242.
Kaur, Y., Ouyang, G., Sommer, W., Weiss, S., Zhou, C., & Hildebrandt, A. (2020). What does temporal brain signal complexity reveal about verbal creativity?. Frontiers in Behavioral Neuroscience, 14, 146.
Li, Y., & Hollis, E. (2021). Basal forebrain cholinergic neurons selectively drive coordinated motor learning in mice. Journal of Neuroscience, 41(49), 10148-10160.
Montana, J. I., Tuena, C., Serino, S., Cipresso, P., & Riva, G. (2019). Neurorehabilitation of spatial memory using virtual environments: A systematic review. Journal of Clinical Medicine, 8(10), 1516.
Owen, M., & Guta, M. P. (2019). Physically sufficient neural mechanisms of consciousness. Frontiers in Systems Neuroscience, 13, 24.
Pedrotty, M., Wong, T. S., Wilde, E. A., Bigler, E. D., & Laatsch, L. K. (2021). Application of neuropsychology and imaging to brain injury and use of the integrative cognitive rehabilitation psychotherapy model. NeuroRehabilitation, (Preprint), 1-21.
Trott, R. E., Kleinig, T. J., Hillier, S. L., Hobbs, D. A., & Reynolds, K. J. (2019, June). A Modular Hybrid Exoskeletal-Soft Glove for High Degree of Freedom Monitoring Capability. In 2019 IEEE 16th International Conference on Rehabilitation Robotics (ICORR) (pp. 577-582). IEEE.
Turolla, A., Venneri, A., Farina, D., Cagnin, A., & Cheung, V. C. (2018). Rehabilitation induced neural plasticity after acquired brain injury. Neural plasticity, 2018.
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