Integrated technology for evaluation of brain function and neural plasticity

Department of Clinical Neuroscience, Hospital Fatebenefratelli, Isola Tiberina 39, 00186-Rome, Italy.
Physical Medicine and Rehabilitation Clinics of North America (Impact Factor: 1.09). 03/2004; 15(1):263-306. DOI: 10.1016/S1047-9651(03)00124-4
Source: PubMed

ABSTRACT The study of neural plasticity has expanded rapidly in the past decades and has shown the remarkable ability of the developing, adult, and aging brain to be shaped by environmental inputs in health and after a lesion. Robust experimental evidence supports the hypothesis that neuronal aggregates adjacent to a lesion in the sensorimotor brain areas can take over progressively the function previously played by the damaged neurons. It definitely is accepted that such a reorganization modifies sensibly the interhemispheric differences in somatotopic organization of the sensorimotor cortices. This reorganization largely subtends clinical recovery of motor performances and sensorimotor integration after a stroke. Brain functional imaging studies show that recovery from hemiplegic strokes is associated with a marked reorganization of the activation patterns of specific brain structures. To regain hand motor control, the recovery process tends over time to bring the bilateral motor network activation toward a more normal intensity/extent, while overrecruiting simultaneously new areas, perhaps to sustain this process. Considerable intersubject variability exists in activation/hyperactivation pattern changes over time. Some patients display late-appearing dorsolateral prefrontal cortex activation, suggesting the development of "executive" strategies to compensate for the lost function. The AH in stroke often undergoes a significant "remodeling" of sensory and motor hand somatotopy outside the "normal" areas, or enlargement of the hand representation. The UH also undergoes reorganization, although to a lesser degree. Although absolute values of the investigated parameters fluctuate across subjects, secondary to individual anatomic variability, variation is minimal with regards to interhemispheric differences, due to the fact that individual morphometric characters are mirrored in the two hemispheres. Excessive interhemispheric asymmetry of the sensorimotor hand areas seems to be the parameter with highest sensitivity in describing brain reorganization after a monohemispheric lesion, and mapping motor and somatosensory cortical areas through focal TMS, fMRI, PET, EEG, and MEG is useful in studying hand representation and interhemispheric asymmetries in normal and pathologic conditions. TMS and MEG allow the detection of sensorimotor areas reshaping, as a result of either neuronal reorganization or recovery of the previously damaged neural network. These techniques have the advantage of high temporal resolution but also have limitations. TMS provides only bidimensional scalp maps, whereas MEG, even if giving three-dimensional mapping of generator sources, does so by means of inverse procedures that rely on the choice of a mathematical model of the head and the sources. These techniques do not test movement execution and sensorimotor integration as used in everyday life. fMRI and PET may provide the ideal means to integrate the findings obtained with the other two techniques. This multitechnology combined approach is at present the best way to test the presence and amount of plasticity phenomena underlying partial or total recovery of several functions, sensorimotor above all. Dynamic patterns of recovery are emerging progressively from the relevant literature. Enhanced recruitment of the affected cortex, be it spared perilesional tissue, as in the case of cortical stroke, or intact but deafferented cortex, as in subcortical strokes, seems to be the rule, a mechanism especially important in early postinsult stages. The transfer over time of preferential activation toward contralesional cortices, as observed in some cases, seems, however, to reflect a less efficient type of plastic reorganization, with some aspects of maladaptive plasticity. Reinforcing the use of the affected side can cause activation to increase again in the affected side with a corresponding enhancement of clinical function. Activation of the UH MI may represent recruitment of direct (uncrossed) corticospinal tracts and relate more to mirror movements, but it more likely reflects activity redistribution within preexisting bilateral, large-scale motor networks. Finally, activation of areas not normally engaged in the dysfunctional tasks, such as the dorsolateral prefrontal cortex or the superior parietal cortex in motor paralysis, might reflect the implication of compensatory cognitive strategies. An integrated approach with technologies able to investigate functional brain imaging is of considerable value in providing information on the excitability, extension, localization, and functional hierarchy of cortical brain areas. Deepening knowledge of the mechanisms regulating the long-term recovery (even if partial), observed for most neurologic sequelae after neural damage, might prompt newer and more efficacious therapeutic and rehabilitative strategies for neurologic diseases.

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    • "Standard EEG techniques are characterized by low spatial resolution (several centimeters) when compared to structural MRI and PET techniques producing relatively non-invasive views of " in vivo " brain anatomy (millimeters to a few centimeters). However, structural MRI does not provide functional information about the brain, and PET scan of brain glucose metabolism/rCBF is limited in its temporal resolution (i.e., seconds to minutes for PET) compared to EEG (i.e., milliseconds; Rossini and Dal Forno, 2004). It should be noted that high temporal resolution of EEG is crucial for the study of an emerging property of brain activity, namely the spontaneous and event-related oscillatory gross electromagnetic activity at different frequency ranges, categorized as 1–4 Hz (delta), 4–8 Hz (theta), 8–13 Hz (alpha), 13–30 Hz (beta), and N30 Hz (gamma). "
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    ABSTRACT: Alzheimer's disease (AD) is the most frequent neurodegenerative disorder and cause of dementia along aging. It is characterized by a pathological extracellular accumulation of amyloid-beta peptides that affects excitatory and inhibitory synaptic transmission. It also triggers aberrant patterns of neuronal circuit activity at the network level. Growing evidence shows that AD targets cortical neuronal networks related to cognitive functions including episodic memory and visuospatial attention. This is partially reflected by the abnormal mechanisms of cortical neural synchronization and coupling that generate resting state electroencephalographic (EEG) rhythms. The cortical neural synchronization is typically indexed by EEG power density. The EEG coupling between electrode pairs probes functional (inter-relatedness of EEG signals) and effective (casual effect from one over the other electrode) connectivity. The former is typically indexed by EEG spectral coherence (linear) or synchronization likelihood (linear-nonlinear), the latter by granger causality or information theory indexes. Here we revised resting state EEG studies in mild cognitive impairment (MCI) and AD subjects as a window on abnormalities of the cortical neural synchronization and functional and effective connectivity. Results showed abnormalities of the EEG power density at specific frequency bands (<12Hz) in the MCI and AD populations, associated to an altered functional and effective EEG connectivity among long range cortical networks (i.e. fronto-parietal and fronto-temporal). These results suggest that resting state EEG rhythms reflect the abnormal cortical neural synchronization and coupling in the brain of prodromal and overt AD subjects, possibly reflecting dysfunctional neuroplasticity of the neural transmission in long range cortical networks. Copyright © 2015. Published by Elsevier B.V.
    International journal of psychophysiology: official journal of the International Organization of Psychophysiology 02/2015; DOI:10.1016/j.ijpsycho.2015.02.008 · 2.65 Impact Factor
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    • "There is increasing interest in using robotic devices to assist individuals who suffered neurologic injuries such as stroke and spinal cord injury (Marchal-Crespo and Reinkensmeyer 2009). Neurologic patients' active participation is thought to be essential for provoking motor plasticity (Lotze et al 2003, Perez et al 2004), and by assisting the movement that participants cannot achieve by themselves, active assist exercise provides novel somatosensory stimulation that can help induce brain plasticity (Rossini and Dal Forno 2004). Triggered assistance allows the participant to attempt a movement without any robotic assistance, only initiating the assistance when some performance variable (e.g. "
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    ABSTRACT: Triggered assistance has been shown to be a successful robotic strategy for provoking motor plasticity, probably because it requires neurologic patients' active participation to initiate a movement involving their impaired limb. Triggered assistance, however, requires sufficient residual motor control to activate the trigger and, thus, is not applicable to individuals with severe neurologic injuries. In these situations, brain and body-computer interfaces have emerged as promising solutions to control robotic devices. In this paper, we investigate the feasibility of a body-machine interface to detect motion execution only monitoring the autonomic nervous system (ANS) response. Four physiological signals were measured (blood pressure, breathing rate, skin conductance response and heart rate) during an isometric pinching task and used to train a classifier based on hidden Markov models. We performed an experiment with six healthy subjects to test the effectiveness of the classifier to detect rest and active pinching periods. The results showed that the movement execution can be accurately classified based only on peripheral autonomic signals, with an accuracy level of 84.5%, sensitivity of 83.8% and specificity of 85.2%. These results are encouraging to perform further research on the use of the ANS response in body-machine interfaces.
    Physiological Measurement 12/2012; 34(1):35-51. DOI:10.1088/0967-3334/34/1/35 · 1.62 Impact Factor
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    • "However, these functional brain imaging methods, despite their high spatial resolution for anatomical details, are relatively limited in their temporal resolution when measuring functional brain activation (seconds to minutes). Thus, these more recent neuroimaging techniques cannot discriminate the activation of different relays within a distributed network either in International Journal of Alzheimer's Disease series or in parallel [3]. Over the years, several improvements have been introduced to EEG measures in part, because neuroelectric signals can track information processing with millisecond precision. "
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    05/2011; 2011:927573. DOI:10.4061/2011/927573
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