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Objective There is a long interest in using EEG measurements to inform transcranial Electrical Stimulation (tES) but adoption is lacking. The conventional approach is to use anatomical head-models for both source localization (the EEG inverse problem) and current flow modeling (the tES forward model), but this approach is computationally demanding, requires an anatomical MRI, and strict assumptions about the target brain regions. We evaluate techniques whereby tES dose is derived from EEG without the need for an anatomical head model or assumptions. Approach The approaches are verified using a Finite Element Method (FEM) simulation of the EEG generated by a dipole, oriented either tangential or radial to the surface, and then simulating brain current flow produced by various model-free techniques including: (1) Voltage-to-voltage, (2) Voltage-to-Current; (3) Laplacian; and two Ad-Hoc techniques (4) Dipole sink-to-sink; and (5) Sink to Concentric Ring. These model-free approaches are compared to a numerically optimized dose that assumes perfect understanding of the dipole location and head anatomy. We vary the number of electrodes from a few to over three hundred, with focality or intensity as optimization criterion. Main results Our results demonstrate how simple Ad-Hoc approaches can achieve reasonable targeting for the case of a cortical dipole with 2–8 electrodes and no need for a model of the head. Significance For its simplicity and linearity, model-free EEG guided lends itself to broad adoption and can be applied to a static (tDCS), time-variant (e.g. tACS, tRNS, tPCS), or closed-loop tES. Figure options Download full-size image Download high-quality image (1118 K) Download as PowerPoint slide Figure options Download full-size image Download high-quality image (1499 K) Download as PowerPoint slide

Purpose One-third of epilepsy patients develop drug resistance epilepsy (DRE), and half of them can benefit from the surgical removal of epileptic focus (EF). Neuromodulation represents the only hope to ameliorate the quality of life of the remaining patients. Cathodal transcranial direct current stimulation (ctDCS) is a techniques able to non-invasively inhibit cortical excitability, which is abnormally increased in epilepsy, but its efficacy in reducing seizures and in modulating epileptic network is still under debate. We evaluated the efficacy of 20-min 1 mA ctDCS vs sham-tDCS in reducing seizure frequency and in modulating the functional connectivity (FC) between EF and the other cortical areas, in temporal DRE patients. Methods After 7 days of seizure diary, patients were randomized to either first-ctDCS or first-sham-ctDCS treatment. On day 8, patients underwent the assigned stimulation. On day 38, patients underwent the single-session opposite stimulation. 7 days after the second session, the study was concluded. The ctDCS cathode was placed over the EF and the anode over the contralateral homologous region. Immediately before and after stimulations, a one-hour resting state closed-eyes 19-electrodes video-EEG recording was acquired. We enrolled ten patients affected by temporal lobe DRE (4 males; 42 ± 15.7 years old; 4 symptomatic and 6 cryptogenic;5 right EF). Results ctDCS reduced the percent weekly SF more than sham stimulation (−71 ± 33% ctDCS vs 25 ± 125% sham; Z = −2.201, p = 0.028). EA changes did not differ between ctDCS respect to sham-ctDCS ( p > 0.200 consistently). No patients reported worsening of SF or of seizure intensity. FC changed after real stimulation in all patients and involved the focus in 71% of the new connections. No FC change was found after sham. Conclusions we demonstrated that an individualized ctDCS reduced seizure frequency in temporal DRE without any safety concern. FC changes may help to explain ctDCS effects on DRE patients.

Objective The increase of elderly population prompted growing research for the understanding of cerebral phenomena sustaining learning abilities, with inclusion of long-term potentiation (LTP)-like plasticity phenomena. Aim of the present study was to characterize LTP-like plasticity dependence on age and gender. Methods A LTP-like primary motor cortex plasticity inducing a potentiation of the motor evoked potential (MEP) to focal transcranial magnetic stimulation as a consequence of a paired associative stimulation (PAS) was induced in a 50 healthy subject cohort, equally distributed for gender and age groups (25 young subjects, mean age ± SD = 29.8 ± 4.5 years; elderly 61.1 ± 4.1 years). Results Resting motor thresholds’ excitability level increased in the elderly group, the basal MEP did not depend on gender or age. The PAS-induced primary motor cortex (M1) plastic excitability modulation was similar in young females and males, while it decreased with age in females only. Conclusions A reduction of the PAS-induced M1 plasticity in females after menopause was documented, possibly due to an impairment of intracortical excitatory network activity. Significance A LTP-like plasticity dependence on age was found in female only, suggesting caution in interpreting behavioural studies on learning abilities in dependence on age.

Brodmann’s pioneering work resulted in the classification of the cortical areas based on their cyto-architecture and topology. Here, we aim at documenting that cortical areas can be also classified by neuronal activities specific to well identifiable structures and to the latter’s networking within the whole brain. We investigated this notion in the primary somatosensory area (S1) and in the primary motor area (M1) in both hemispheres. Our results show that S1 and M1 are topologically differentiated by their respective neuronal activities, which are specific, independent of hemisphere and of subject’s state (i.e., at rest, performing movements or receiving external stimulations). S1 displays higher power than M1 (p = .001) in the beta frequency band, while the opposite occurs in the gamma2 band (p = .034). We also show that the fractal dimensions (FD) emerged from our study as a strong index capable of differentiating the two brain areas in all subject’s states, with S1’s FD smaller than M1’s (p .00001). The present work intends to be a first step toward the identification and classification of brain cortical areas via the dynamics of their neuronal activity, which we believe will advance our knowledge of the brain’s intimate structural–functional unity.