Transcranial Magnetic Stimulation As A Diagnostic And Therapeutic Tool in Various Types Of DementiaⅢ

7. Parkinson’s Disease with Dementia 

In PD, basal ganglia degeneration may lead to cognitive decline resulting in PDD, which mainly involves deficits in executive functions with relatively preserved memory, learning, and higher-level language abilities. As documented with neuropathological and neuroimaging data, PDD depends on the disruption of the frontostriatal dopamine networks and cholinergic deficiency extending to frontal areas [117,118]. By these findings, Celebi et al. [119] demonstrated a significant decrease in SAI in PDD patients in comparison to healthy controls and PD patients without dementia. The degree of SAI impairment seems to be comparable to that in AD and shows a similar correlation with cognitive dysfunction. Cholinergic impairment in PDD was also reflected in the recording of CSP, which was prolonged in comparison to healthy controls [86], whereas in nondemented PD patients, it was shortened [22]. 

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Interestingly, in another study with non-demented PD patients, the reduction of SAI showed an association with visual hallucinations as it did in DLB [120] and with other non-motor PD symptoms such as REM sleep behavior disorder, dysphagia, and olfactory impairment. This finding led to the hypothesis that these symptoms might herald the onset of PDD [121]. A recent, randomized clinical trial assessed the effects of rTMS on cognitive impairment in PDD [122]. Real high-frequency or sham rTMS was applied over the hand area of each motor for 10 days, followed by 5 booster sessions every month for 3 months. The results showed only a minor effect on cognitive functions and a significant improvement in motor function in the active group.

8. Mild Cognitive Impairment 

MCI is a neurocognitive disorder that includes a decline of mental processes halfway between normal aging and dementia. According to the accepted definition, a decline in cognition must be present in at least one domain, but it is not sufficient to diagnose dementia and is not significant enough to impact the instrumental activities of daily living [123]. People suffering from MCI are at risk of developing various types of dementia [124], and the characteristics of their cognitive deficits as well as radiologic and laboratory biomarkers can indicate the most probable direction of imminent conversion [125–127]. Changes in TMS parameters resemble those found in particular dementia types, although they are less pronounced. As cited above, the meta-analysis of Mimura et al. [71] showed that MT, SAI, LICI, and SICI were different in AD and healthy controls. In the same work, respective calculations for MCI revealed that only MT was lower than in healthy controls. SAI showed only a tendency toward reduction. 

LICI and SICI seemed to be similar to normal; however, data from only two studies were available. The study of Benussi et al. [17] differentiated recruited patients into MCI-Alzheimer’s disease (MCI-AD), MCI-frontotemporal dementia (MCI-FTD), and MCI-dementia with Lewy bodies (MCI-DLB). SICI and ICF were reduced in MCI-FTD and MCI-DLB concerning healthy controls. SAI was reduced in MCI-AD and MCI-DLB and LICI was impaired in FTD, although not significantly. The authors employed the machine learning model to diagnose the MCI subtypes based on TMS measurements, similar to what they did with patients with overt dementias [65]. The prediction of particular diagnoses showed high accuracy (0.72–0.86) and high precision (0.72–0.90), which was only slightly lower than in overt dementias [65]. 

Overall, according to the results of the study of Benussi et al. [17], TMS could reliably diagnose MCI, which was not in full agreement with the meta-analysis of Mimura et al. [71]. It could be supposed that the methodological discrepancies between studies included in the meta-analysis and the need for more restrictive statistical comparisons might account for these discrepancies. Padovani et al. [64] observed impairment of SAI with unimpaired SICI and ICF among AD MCI patients in comparison to non-AD MCI. These findings suggested the existence of disturbed cholinergic pathways among the former. For differential diagnosis of AD MCI and non-AD MCI, they proposed SAI and the SICI-ICF/SAI ratio as electrocortical biomarkers with high specificity and sensitivity. This approach showed similar diagnostic accuracy in MCI patients as surrogate neuropathological hallmarks. Moreover, the addition of TMS measurements enhanced the diagnostic confidence for MCI stages of AD, FTD, and DLB in comparison to clinical work-up alone and comparison to clinical work-up and amyloid biomarkers [128]. 

rTMS has been recently investigated concerning its procognitive effect in MCI. In most studies, the prefrontal cortex has been targeted with high-frequency stimulation. A meta-analysis containing nine studies demonstrated that rTMS could yield a significant, beneficial effect on cognitive functions and memory [129]. Another meta-analysis, which included 13 studies, albeit on both MCI and AD patients, resulted in a similar conclusion. The bigger sample allowed, however, subgroup analysis, which indicated that low-frequency rTMS over the right DLPFC might improve memory, and rTMS over the inferior frontal gyrus might enhance executive performance [130]. The development of non-ferromagnetic electrodes and appropriate amplifiers made it possible to record the responses of electroencephalography (EEG) to TMS pulses. Moreover, the introduction of high-resolution systems containing up to 256 recording electrodes increased the spatial resolution of EEG. These advances allowed, recently, to measure excitability and connectivity beyond the motor cortex. 

The TMS pulse evokes the EEG response, which starts several milliseconds after the pulse and lasts up to several hundred milliseconds. Depending on the stimulus strength, the stimulation site, and brain plasticity as well as connectivity this response may be recorded under various electrodes with various latencies and amplitudes. Up to now, the main findings have concerned the P30 component, which can be usually well-delineated [131]. In general, this component, recorded from most EEG electrodes, is reduced in AD, reflecting the impaired connections between cortical areas [132]. Such impairment was also documented by functional neuroimaging, which led to coining the term “disconnection syndrome” as a description of one of the key pathological features of AD [133]. Over this background, several exceptions have been documented. One is the motor cortex, where responses seem to be stronger [134]. 

This finding may be attributed to the compensatory mechanism, which increases regional excitability, aiming to preserve the functional performance of the motor system. An increase in P30 amplitude was observed also in the prefrontal areas and was correlated inversely with cognitive decline in AD [135], suggesting increased, maladaptive connectivity between the prefrontal areas and other regions as another compensatory mechanism in the course of the overall decline of brain connectivity. On the other hand, some regions such as the temporoparietal area, ipsilateral to the stimulated motor cortex or the contralateral centro-frontal cortex, may exhibit more pronounced suppression of connectivity than the others, which may result from specific patterns of neurodegeneration [136]. 

TMS-evoked EEG responses also showed usefulness in the monitoring of therapeutic effects: In the study of Assogna et al. [115], FTD patients were treated with palmitoylethanolamide combined with luteolin, which led to improvement in NPI and FAB scores. The improvement seen in the tests was paralleled by the normalization of LICI and also by the enhancement of TMS-evoked EEG responses in the frontal lobes. The findings cited above come from small groups of patients. They still need replication and systematization, but they open a new perspective to investigate the functional aspects of neurodegenerative processes. One can also hope that such sensitive, neurophysiologic monitoring will contribute significantly to the optimization and individualization of current and future therapies.

9. Conclusions 

TMS offers new diagnostic and therapeutic possibilities for dementias. It is relatively cheap, non-invasive, and safe and is continuously enriched with new modalities and paradigms of stimulation. TMS is a unique method to test cortical excitability and functionality of brain connections. For this reason, it may be regarded as a valuable adjuvant tool to other methods with confirmed efficacy in dementia such as amyloid positron emission tomography (amyloid-PET) [137] or assessment of levels of amyloid-beta1-42 and tau protein in cerebrospinal fluid [138]. TMS seems to be a good candidate for a primary diagnostic tool, especially for early screening for the presence of neurodegenerative processes, as it is in the case of MCI. 

The methods currently used in clinical settings, including the above-mentioned ones, may not be well-suited for such tasks. Amyloid-PET is expensive, and lumbar puncture is invasive and usually requires admission to the hospital. TMS may, therefore, help identify target patients in a timely way for new, experimental therapies, which usually require the inclusion of patients with relatively preserved cognitive functions. To date, the results of TMS research point out that the diagnostic approach, which includes all paradigms of cortical excitability, may be helpful to detect the signs of the neurodegenerative process and to differentiate between particular dementia types. 

Diagnostic specificity and sensitivity may be increased by implementing machine learning or by the recording of TMS-evoked potentials with electroencephalography. However, additional research is required to confirm these initial, promising findings. In the face of the absence of established disease-modifying therapies or pharmacological treatments with proven efficacy, rTMS may be one of the possible options for enhancing cognition. Multisite stimulation combined with training seems to enhance cognitive performance with particularly high efficacy, but systematic studies in dementias other than AD are still lacking. It seems that future research will focus on the development of multimodal diagnostic approaches including clinical, imaging, and neurophysiological biomarkers, which will serve as a key to identifying high-risk individuals for early therapeutic interventions.

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