Characterization of antiseizure medications effects on the EEG neurodynamic by fractal dimension.

Objectives: An important challenge in epilepsy is to define biomarkers of response to treatment. Many electroencephalography (EEG) methods and indices have been developed mainly using linear methods, e.g., spectral power and individual alpha frequency peak (IAF). However, brain activity is complex and non-linear, hence there is a need to explore EEG neurodynamics using nonlinear approaches. Here, we use the Fractal Dimension (FD), a measure of whole brain signal complexity, to measure the response to anti-seizure therapy in patients with Focal Epilepsy (FE) and compare it with linear methods. Materials: Twenty-five drug-responder (DR) patients with focal epilepsy were studied before (t1, named DR-t1) and after (t2, named DR-t2) the introduction of the anti-seizure medications (ASMs). DR-t1 and DR-t2 EEG results were compared against 40 age-matched healthy controls (HC). Methods: EEG data were investigated from two different angles: frequency domain-spectral properties in δ, θ, α, ß, and γ bands and the IAF peak, and time-domain-FD as a signature of the nonlinear complexity of the EEG signals. Those features were compared among the three groups. Results: The δ power differed between DR patients pre and post-ASM and HC (DR-t1 vs. HC, p < 0.01 and DR-t2 vs. HC, p < 0.01). The θ power differed between DR-t1 and DR-t2 (p = 0.015) and between DR-t1 and HC (p = 0.01). The α power, similar to the δ, differed between DR patients pre and post-ASM and HC (DR-t1 vs. HC, p < 0.01 and DR-t2 vs. HC, p < 0.01). The IAF value was lower for DR-t1 than DR-t2 (p = 0.048) and HC (p = 0.042). The FD value was lower in DR-t1 than in DR-t2 (p = 0.015) and HC (p = 0.011). Finally, Bayes Factor analysis showed that FD was 195 times more likely to separate DR-t1 from DR-t2 than IAF and 231 times than θ. Discussion: FD measured in baseline EEG signals is a non-linear brain measure of complexity more sensitive than EEG power or IAF in detecting a response to ASMs. This likely reflects the non-oscillatory nature of neural activity, which FD better describes. Conclusion: Our work suggests that FD is a promising measure to monitor the response to ASMs in FE.

Contribution of TMS and TMS-EEG to the Understanding of Mechanisms Underlying Physiological Brain Aging.

In the human brain, aging is characterized by progressive neuronal loss, leading to disruption of synapses and to a degree of failure in neurotransmission. However, there is increasing evidence to support the notion that the aged brain has a remarkable ability to reorganize itself, with the aim of preserving its physiological activity. It is important to develop objective markers able to characterize the biological processes underlying brain aging in the intact human, and to distinguish them from brain degeneration associated with many neurological diseases. Transcranial magnetic stimulation (TMS), coupled with electromyography or electroencephalography (EEG), is particularly suited to this aim, due to the functional nature of the information provided, and thanks to the ease with which it can be integrated with behavioral manipulation. In this review, we aimed to provide up to date information about the role of TMS and TMS-EEG in the investigation of brain aging. In particular, we focused on data about cortical excitability, connectivity and plasticity, obtained by using readouts such as motor evoked potentials and transcranial evoked potentials. Overall, findings in the literature support an important potential contribution of TMS to the understanding of the mechanisms underlying normal brain aging. Further studies are needed to expand the current body of information and to assess the applicability of TMS findings in the clinical setting.

Microsurgical Clipping of Intracranial Aneurysms Assisted by Neurophysiological Monitoring, Microvascular Flow Probe, and ICG-VA: Outcomes and Intraoperative Data on a Multimodal Strategy.

OBJECTIVE: The aim of this study is to report data on a multimodal monitoring strategy based on the intraoperative use of neurophysiological monitoring, flowmetry by microflow probe, and intraoperative indocyanine green video angiography (ICG-VA) during microsurgical clipping of intracranial aneurysms. METHODS: This retrospective analysis was performed on 85 consecutive patients undergoing clipping of 96 intracranial aneurysms with the present monitoring strategy. Patient outcomes were evaluated by assessing rate of aneurysm exclusion and postoperative occurrence of ischemic injury. Intraoperative data for the strategy in addition to changes in each monitoring technique depending on aneurysm features were reported. RESULTS: Complete aneurysm exclusion was achieved in 98.9% of cases. Postoperative symptomatic ischemic injury was recorded in 2.08% aneurysms. Clip repositioning occurred in 40.6% of cases: because of motor evoked potential (MEP) decrease in 9.3%, flowmetry in 22.91%, and ICG-VA in 8.3% of treated aneurysms (1.05% after ICG injection, 7.4% after the squeezing maneuver). The role of each technique differed according to aneurysm features; flowmetry alterations occurred more frequently in distal than in proximal aneurysms (P = 0.0001) and in atherosclerotic aneurysms (P = 0.0001). MEP impairment occurred more often in proximal aneurysms (P < 0.05). ICG-VA disclosed remnant aneurysms mainly in atherosclerotic aneurysms (P < 0.05); only one false negative remnant neck was recorded with a negative predictive value of 98.8%. CONCLUSIONS: Microsurgical clipping assisted by a multimodal monitoring strategy achieved a high rate of aneurysm exclusion with low morbidity in our series. Our data show that the 3 techniques used in our strategy were complementary and that a monitoring strategy can be tailored to aneurysm features.

Functional mapping of left parietal areas involved in simple addition and multiplication. A single-case study of qualitative analysis of errors.

All electrostimulation studies on arithmetic have so far solely reported general errors. Nonetheless, a classification of the errors during stimulation can inform us about underlying arithmetic processes. The present electrostimulation study was performed in a case of left parietal glioma. The patient's erroneous responses suggested that calculation was mainly applied for addition and a combination of retrieval and calculation was mainly applied for multiplication. The findings of the present single-case study encourage follow up with further data collection with the same paradigm.