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4.4 What Are the Limits to This Cortical Plasticity?
It is important to clarify that evidence of cortical reorganization exists in both congenital and late blind individuals. However, the neuroplastic changes associated with partial blindness remain less understood [19, 22, 27, 58]. For example, Baker et al. [8] found evidence of cortical reorganization in individuals with partial visual field loss due to age-related macular degeneration (AMD). Dilks et al. [27] reported converging behavioral and neuroimaging evidence from a stroke patient consistent with reorganization after deafferentation of human visual cortex, but other studies have been unable to demonstrate the same results [58, 86]. It is also worth noting, if not at least anecdotally, that some blind or severely visually deprived subjects do not adapt well to the loss of sight. In these subjects, preliminary studies suggest that the occipital cortex is not or at most, only partially reorganized [20, 33, 34, 61, 62, 77]. For these individuals, a neuroprosthetic approach might be a functionally desirable solution but it is important to understand their capacity for processing visual information.
The variability in both the behavioral and neurophysiological adaptations could be related not only to the profoundness of the visual loss but also the amount of time spent visually deprived. Thus, the time course associated with neuroplastic changes and whether or not cortical areas can still process visual information after longstanding visual deprivation are important questions to be considered. In this context, we have recently reported the case of a late blind patient (at the time of study, he had no light perception in either eye for at least 12 years), who suddenly experienced elementary and complex visual hallucinations located in his right visual field [2]. Neuro-radiological examination revealed that the patient had an arteriovenous malformation located in his left striate cortex. Although the underlying pathophysiology of visual hallucinations in this patient is uncertain, the presence of visual hallucinations could represent an increased level of excitability, possibly related to cortical “release” [23, 57] or from an “irritative” phenomenon reflecting the pathological activation of neural ensembles in the regions where the occipital lesion is located [6]. Nonetheless, these findings provide evidence that the occipital cortex of some blind subjects can still generate visual perceptions and strengthen the notion that long-term deafferented occipital cortex can remain functionally active and be potentially recruited to process visual information despite the complete absence of visual input. Of course, it will be very useful to know in advance the feasibility of generating visual perceptions in blind subjects before the implantation of any visual neuroprosthetic device. In this context it has been proposed that image-guided transcranial magnetic stimulation (TMS), can be used as a noninvasive method to systematically map the visual sensations induced by focal stimulation of the human occipital cortex and there are already clinical protocols which allow to relate the localization of the real site of stimulation to characteristic positions in the visual field [32]. This procedure has the potential to improve our understanding of physiologic organization and plastic changes in the human visual system and to establish the degree and extent of remaining functional visual cortex in blind subjects (Fig. 4.3).
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Fig. 4.3 Frameless interface to aid in the positioning of the transcranial magnetic stimulator coil over a subject’s brain. This technique enables use of anatomical information as an interactive navigational guide for stimulator coil position and allows recording of the position and orientation of the coil at the instant of stimulation for later correlation with the response data. (a) An example of the live display. (b) Interface to identify the position of the TMS coil over the subject’s MRI data at several customized locations (modified from [32]). (c) Customized interface to facilitate the recording of phosphene data
Evidence of cortical reorganization within a time frame as short as months has been observed in animal studies [47, 48]. However human research on this matter remains equivocal [8, 27] and more conclusive data and measures of these functional changes need to be obtained. Furthermore, although rapid reorganization seems possible, it may be dependent on the interaction of several factors (i.e. age, time since onset of blindness, disease severity, etc.). At the same time, the cerebral organization between two given blind persons may be substantially different depending on the pathology, the age of blindness, personal experience, etc. Clearly, much more evidence is needed about the extent of cortical reorganization in the adult human visual system and the conditions under which reorganization occurs [26].
4.5 Possible Mechanisms Behind Brain Plasticity
As stated previously, brain plasticity refers to the neurophysiological changes that occur in relation to the organization of the brain and in response to alterations of neural activity and sensory experience. These changes are especially evident during development and after neurologic injury and can be best conceptualized with encompassing multiple levels of operation from molecular to cellular levels on to neural systems and ultimately, on to behavior.
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As it was first suggested by Santiago Ramón y Cajal in his Textura del Sistema Nervioso del Hombre y los Vertebrados [18], plasticity can be regarded as a type of “structural modification that implies the formation of new neural pathways through ramification and progressive growth of the dendritic terminals”. In general, these changes can involve rapid reinforcement of pre-established synaptic pathways and even the formation of new neuronal pathways [16, 24, 37, 55, 72, 73]. Consequently, and as a result of experience neurotransmitters are modulated, synapses change their morphology, dendrites and spines grow and contract, axons change their trajectory and cortical representational maps are altered.
Although several mechanisms are likely to be involved in all these processes, the current working model emphasizes the selective strengthening of synapses following classical Hebbian learning rules that have guided much of the work in both the field of cortical synaptic plasticity and cortical representational reorganization [41]. At the cellular level, it has been suggested that functional reorganization may rely on mechanisms involving modifications in the excitatory/inhibitory neurotransmission [30, 45, 95] and/or a increased synthesis of neurotrophic factors [46, 49]. In this way, functional reorganization correlates in time with dendritic sprouting and with changes in the excitatory/inhibitory neurotransmission.
There also is evidence that the mechanisms involved in synaptic plasticity can vary between cortical regions [84, 85] and involve glial cells [13]. Thus, the last few years have provided extraordinary evidence regarding the molecular mechanisms underlying neuroplastic changes. The exciting future in this context involves the possibility of developing new approaches such as specific rehabilitation strategies and pharmacological interventions to modulate these processes and ultimately optimize rehabilitative outcomes.
4.6 Modulation of Brain Plasticity: Recent Developments
Enhancement of function-enabling plasticity and prevention of function-disabling plasticity can be accomplished through several approaches such as specific rehabilitation procedures, pharmacological interventions and/or exogenous electrical/ magnetic stimulation. For example, a number of studies have demonstrated that cortical maps can be contracted or expanded by loss of peripheral inputs or by enhanced use [3, 9, 21, 29, 37, 55, 56, 72, 78, 96]. Furthermore, as demonstrated by mapping studies after micro-infarcts, it is clear that behavior is one of the most powerful modulators of post-injury recovery and therefore, behavioral intervention to enhance recovery is becoming increasingly popular [3, 70, 72, 75]. These rehabilitation therapies have significantly improved the quality of life of many of patients after brain damage and suggest that this ability of the brain to reorganize itself by experience-dependent neural plasticity could be also used to develop new training strategies to accelerate learning and maximize the adaptation to prosthetic vision devices. Learning electrically stimulated visual patterns can be a new and difficult experience. Although the continued use of the visual implant
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may, by itself, restore some visual perception, carefully guided visual rehabilitation may be necessary to maximize the adaptation and get the most from these devices.
There are other possible methods to modulate plasticity that are currently being evaluated and could potentially act as adjuvant therapy. Pharmacological approaches [43], for example, the coupling of D-amphetamine (D-AMPH) and rehabilitative training seems to be useful in promoting behavioral function as well as neurotrophic and neuroplastic responses in animal studies [10, 88] and these effects have also been established during language learning in the human [15]. However, clinical studies on the use of D-AMPH as a pharmacological adjunct to post-stroke rehabilitation have yielded mixed results probably because of type, dosage and timing of drug delivery [87, 94]. Nonetheless, it seems that practice-dependent changes of cortical plasticity can be facilitated by pharmacological strategies that rely on adrenergic and cholinergic mechanisms and show a trend towards decrease of antagonists to these neurotransmitter systems [43]. These findings provide preliminary evidence that the pharmacological approach combined with appropriate rehabilitation strategies may be beneficial to promote post-injury recovery facilitating the “re-learning” processes and could potentially extend to the case of visual rehabilitation.
Another possibility to enhance training effects is the use of intracortical microstimulation techniques [1, 68, 69, 71, 75]. This procedure appears to induce dendritic growth in a frequency specific manner, however direct cortical microstimulation requires extensive neurosurgical procedures (e.g. a craniotomy) thus questioning its overall feasibility within the clinical setting. Alternative approaches that could induce similar effects and that are being currently tested include noninvasive brain stimulation techniques such as transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS). TMS is a non-invasive and painfree technique for cortical stimulation in humans [11] that consists of a magnetic field emanating from a wire coil held outside the head. tDCS consists of applying a weak electrical current (1–2 mA) to modulate the activity of neurons. Both techniques are able to induce electrical currents in nearby regions of the brain that can influence brain plasticity and reorganization [25, 44, 89]. These techniques have recently been tested in studies with stroke patients with very promising results [3, 66] and show potential for future application in the rehabilitation of persons with a visual neuroprosthesis. For example, high frequency repetitive transcranial magnetic stimulation (rTMS) over the occipital cortex could be used prior to the training sessions with any visual prosthetic device to enhance excitability and facilitate the interpretation of the visual percepts. Such as strategy may be especially appropriate during early stages of training and learning.
4.7 Neuroplasticity and Other Neuroprostheses Efforts
In terms of restoring lost sensory function, cochlear implant research has arguably been the most successful and has translated into a viable therapeutic option for over 110,000 deaf adults and children worldwide [14, 31, 53, 59, 74]. After some time,
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Fig. 4.4 The neural plasticity of the visual cortex can contribute to ever-improving correlation between the physical world and evoked phosphenes. Immediately after implantation the evoked phosphenes are likely to induce a poor perception of an object (the letter “E” in this example). However, appropriate learning and rehabilitation strategies will contribute to provide concordant perceptions (modified from [67])
and with adequate and intensive training, deaf individuals can learn to comprehend and in some cases, even acquire speech. By analogy, after the surgical implantation of any visual prosthesis, the right learning and rehabilitation strategies could potentially help to modulate the plasticity of the brain and contribute to ever-improving performance and more concordant perceptions [67] (Fig. 4.4).
It is remarkable that studies investigating neuroplasticity in the deaf and following cochlear implantation bear striking parallels with those seen in visual neuropros theses development. For example, similar to activation of the occipital cortex by auditory stimuli in the blind, the auditory cortex (Brodmann’s areas 41, 42 and 22) is activated in deaf subjects in response to visual stimuli [36]. Thus, like in the case of the blind, the removal of one sensory modality leads to neural reorganization of the remaining ones. Visual–auditory plasticity in the deaf has also been found in patients with cochlear implants [31, 50, 64, 65]. Neuroimaging studies indicate that after implantation of a cochlear device, primary auditory cortex is activated by the sound of spoken words in deaf patients who had lost hearing before the development of language. Interestingly, it appears that if metabolism in the auditory cortex is restored by cross-modal plasticity changes before implantation, the auditory cortex can no longer respond to signals from a cochlear implant installed afterwards and patients do not show improvement in language capabilities [52]. It is important to note that many changes are invariably linked to chronic electrical stimulation that in turn, complicate the interpretation of the neuroplastic changes that ensue. Again, drawing from cochlear research experience, chronic stimulation can lead to a significant reduction in spiral ganglion neurons; de-myelination of residual ganglion neurons; shrinkage of the perikaryon of neurons throughout the auditory pathway and reduced spontaneous activity throughout the auditory