Multi-physics simulations for investigating the effect of electrode conditions on transscleral ocular iontophoresis for particulate drug delivery into ocular tissues.

Purpose: Transscleral ocular iontophoresis has been proposed to deliver charged particulate drugs to ocular tissues effectively by transmitting a weak electrical current through the sclera. The electric fields formed are influenced by the electrode conditions, thus affecting the amount of particulate drugs delivered to the ocular tissues via iontophoresis. Computational simulation is widely used to simulate drug concentrations in the eye; therefore, reflecting the characteristics of the drugs in living tissues to the simulations is important for a more precise estimation of drug concentration. In this study, we investigated the effect of electrode conditions (location and size) on the efficacy of transscleral iontophoresis. Methods: We first determined the simulation parameters based on the comparison of the amount of drug in the sclera in the simulation and in vivo experimental results. The injection of the negatively charged nanoparticles into the cul-de-sac of the lower eyelid was simulated. The active electrode (cathode) was attached to the skin immediately above the injection site, while the return electrode (anode) was placed over the eyebrow. The drug concentration distribution in the eye, based on either the location or size of each electrode, was evaluated using the finite element method with the estimated simulation parameters. Results: Our results indicate that drug permeability varies depending on the location and the size of the electrodes. Conclusion: Our findings demonstrate that the determination of optimal electrode conditions is necessary to enhance the effectiveness of transscleral iontophoresis. Supplementary Information: The online version contains supplementary material available at 10.1007/s13534-024-00359-2.

Paradigm shift required for translational research on the brain.

Biomedical research on the brain has led to many discoveries and developments, such as understanding human consciousness and the mind and overcoming brain diseases. However, historical biomedical research on the brain has unique characteristics that differ from those of conventional biomedical research. For example, there are different scientific interpretations due to the high complexity of the brain and insufficient intercommunication between researchers of different disciplines owing to the limited conceptual and technical overlap of distinct backgrounds. Therefore, the development of biomedical research on the brain has been slower than that in other areas. Brain biomedical research has recently undergone a paradigm shift, and conducting patient-centered, large-scale brain biomedical research has become possible using emerging high-throughput analysis tools. Neuroimaging, multiomics, and artificial intelligence technology are the main drivers of this new approach, foreshadowing dramatic advances in translational research. In addition, emerging interdisciplinary cooperative studies provide insights into how unresolved questions in biomedicine can be addressed. This review presents the in-depth aspects of conventional biomedical research and discusses the future of biomedical research on the brain.

Multi-proteomic analyses of 5xFAD mice reveal new molecular signatures of early-stage Alzheimer's disease.

An early diagnosis of Alzheimer's disease is crucial as treatment efficacy is limited to the early stages. However, the current diagnostic methods are limited to mid or later stages of disease development owing to the limitations of clinical examinations and amyloid plaque imaging. Therefore, this study aimed to identify molecular signatures including blood plasma extracellular vesicle biomarker proteins associated with Alzheimer's disease to aid early-stage diagnosis. The hippocampus, cortex, and blood plasma extracellular vesicles of 3- and 6-month-old 5xFAD mice were analyzed using quantitative proteomics. Subsequent bioinformatics and biochemical analyses were performed to compare the molecular signatures between wild type and 5xFAD mice across different brain regions and age groups to elucidate disease pathology. There was a unique signature of significantly altered proteins in the hippocampal and cortical proteomes of 3- and 6-month-old mice. The plasma extracellular vesicle proteomes exhibited distinct informatic features compared with the other proteomes. Furthermore, the regulation of several canonical pathways (including phosphatidylinositol 3-kinase/protein kinase B signaling) differed between the hippocampus and cortex. Twelve potential biomarkers for the detection of early-stage Alzheimer's disease were identified and validated using plasma extracellular vesicles from stage-divided patients. Finally, integrin α-IIb, creatine kinase M-type, filamin C, glutamine γ-glutamyltransferase 2, and lysosomal α-mannosidase were selected as distinguishing biomarkers for healthy individuals and early-stage Alzheimer's disease patients using machine learning modeling with approximately 79% accuracy. Our study identified novel early-stage molecular signatures associated with the progression of Alzheimer's disease, thereby providing novel insights into its pathogenesis.

Transcranial alternating current stimulation over multiple brain areas with non-zero phase delays other than 180 degrees modulates visuospatial working memory performance.

While zero-phase lag synchronization between multiple brain regions has been widely observed, relatively recent reports indicate that systematic phase delays between cortical regions reflect the direction of communications between cortical regions. For example, it has been suggested that a non-zero phase delay of electroencephalography (EEG) signals at the gamma frequency band between the bilateral parietal areas may reflect the direction of communication between these areas. We hypothesized that the direction of communication between distant brain areas might be modulated by multi-site transcranial alternating current stimulation (tACS) with specific phase delays other than 0° and 180°. In this study, a new noninvasive brain stimulation (NIBS) method called multi-site multi-phase tACS (msmp-tACS) was proposed. The efficacy of the proposed method was tested in a case study using a visuospatial working memory (VWM) paradigm in which the optimal stimulation conditions including amplitudes and phases of multiple scalp electrodes were determined using finite element analysis adopting phasor representation. msmp-tACS was applied over the bilateral intraparietal sulci (IPS) and showed that 80 Hz tACS with the phase for the right IPS leading that for the left IPS by 90° (= 3.125 ms) partialized VWM performance toward the right visual hemifield. The three stimulation conditions were synchronized, RL, and LR, which refers to stimulation condition with no phase lag, stimulation phase of right IPS (rIPS) leading left IPS (lIPS) by 90° and the stimulation of lIPS leading rIPS by 90°, respectively. The lateralization of VWM significantly shifted towards right visual hemifield under the RL condition compared to the synchronized and LR conditions. The shift in VWM was the result of the stimulation affecting both left and right visual hemifield trials to certain degrees, rather than significantly increasing or decreasing VWM capacity of a specific visual hemifield. Altered brain dynamics caused by msmp-tACS partialized VWM performance, likely due to modulation of effective connectivity between the rIPS and lIPS. Our results suggest that msmp-tACS is a promising NBS method that can effectively modulate cortical networks that cannot be readily modulated with conventional multi-site stimulation methods.

Machine learning-based classification using electroencephalographic multi-paradigms between drug-naïve patients with depression and healthy controls.

BACKGROUND: Electroencephalography (EEG) is a supplementary diagnostic tool in psychiatry but lacks practical usage. EEG has demonstrated inconsistent diagnostic ability because major depressive disorder (MDD) is a heterogeneous psychiatric disorder with complex pathologies. In clinical psychiatry, it is essential to detect these complexities using multiple EEG paradigms. Though the application of machine learning to EEG signals in psychiatry has increased, an improvement in its classification performance is still required clinically. We tested the classification performance of multiple EEG paradigms in drug-naïve patients with MDD and healthy controls (HCs). METHODS: Thirty-one drug-naïve patients with MDD and 31 HCs were recruited in this study. Resting-state EEG (REEG), the loudness dependence of auditory evoked potentials (LDAEP), and P300 were recorded for all participants. Linear discriminant analysis (LDA) and support vector machine (SVM) classifiers with t-test-based feature selection were used to classify patients and HCs. RESULTS: The highest accuracy was 94.52 % when 14 selected features, including 12 P300 amplitudes (P300A) and two LDAEP features, were layered. The accuracy was 90.32 % when a SVM classifier for 30 selected features (14 P300A, 14 LDAEP, and 2 REEG) was layered in comparison to each REEG, P300A, and LDAEP, the best accuracies of which were 71.57 % (2-layered with LDA), 87.12 % (1-layered with LDA), and 83.87 % (6-layered with SVM), respectively. LIMITATIONS: The present study was limited by small sample size and difference in formal education year. CONCLUSIONS: Multiple EEG paradigms are more beneficial than a single EEG paradigm for classifying drug-naïve patients with MDD and HCs.

Low-dose curcumin enhances hippocampal neurogenesis and memory retention in young mice.

Adult neurogenesis generates new functional neurons from adult neural stem cells in various regions, including the subventricular zone (SVZ) of the lateral ventricles and subgranular zone (SGZ) of hippocampal dentate gyrus (DG). Available evidence shows hippocampal neurogenesis can be negatively or positively regulated by dietary components. In a previous study, we reported that curcumin (diferuloylmethane; a polyphenolic found in curry spice) stimulates the proliferation of embryonic neural stem cells (NSCs) by activating adaptive cellular stress responses. Here, we investigated whether subchronic administration of curcumin (once daily at 0.4, 2, or 10 mg/kg for 14 days) promotes hippocampal neurogenesis and neurocognitive function in young (5-week-old) mice. Oral administration of low-dose curcumin (0.4 mg/kg) increased the proliferation and survival of newly generated cells in hippocampus, but surprisingly, high-dose curcumin (10 mg/kg) did not effectively upregulate the proliferation or survival of newborn cells. Furthermore, hippocampal BDNF levels and phosphorylated CREB activity were elevated in only low-dose curcumin-treated mice. Passive avoidance testing revealed that low-dose curcumin increased cross-over latency times, indicating enhanced memory retention, and an in vitro study showed that low-concentration curcumin increased the proliferative activity of neural progenitor cells (NPCs) by upregulating NF1X levels. Collectively, our findings suggest that low-dose curcumin has neurogenic effects and that it may prevent age and neurodegenerative disease-related cognitive deficits.

A computational study on the optimization of transcranial temporal interfering stimulation with high-definition electrodes using unsupervised neural networks.

Transcranial temporal interfering stimulation (tTIS) can focally stimulate deep parts of the brain related to specific functions using beats at two high frequencies that do not individually affect the human brain. However, the complexity and nonlinearity of the simulation limit it in terms of calculation time and optimization precision. We propose a method to quickly optimize the interfering current value of high-definition electrodes, which can finely stimulate the deep part of the brain, using an unsupervised neural network (USNN) for tTIS. We linked a network that generates the values of electrode currents to another network, which is constructed to compute the interference exposure, for optimization by comparing the generated stimulus with the target stimulus. Further, a computational study was conducted using 16 realistic head models. We also compared tTIS with transcranial alternating current stimulation (tACS), in terms of performance and characteristics. The proposed method generated the strongest stimulation at the target, even when targeting deep areas or performing multi-target stimulation. The high-definition tTISl was less affected than tACS by target depth, and mis-stimulation was reduced compared with the case of using two-pair inferential stimulation in deep region. The optimization of the electrode currents for the target stimulus could be performed in 3 min. Using the proposed USNN for tTIS, we demonstrated that the electrode currents of tTIS can be optimized quickly and accurately. Moreover, we confirmed the possibility of precisely stimulating the deep parts of the brain via transcranial electrical stimulation.

80 Hz but not 40 Hz, transcranial alternating current stimulation of 80 Hz over right intraparietal sulcus increases visuospatial working memory capacity.

Working memory (WM) is a complex cognitive function involved in the temporary storage and manipulation of information, which has been one of the target cognitive functions to be restored in neurorehabilitation. WM capacity is known to be proportional to the number of gamma cycles nested in a single theta cycle. Therefore, gamma-band transcranial alternating current stimulation (tACS) should be dependent of the stimulation frequency; however, the results of previous studies that employed 40 Hz tACS have not been consistent. The optimal locations and injection currents of multiple scalp electrodes were determined based on numerical simulations of electric field. Experiments were conducted with 20 healthy participants. The order of three stimulation conditions (40 Hz tACS, 80 Hz tACS, and sham stimulation) were randomized but counterbalanced. Visual hemifield-specific visual WM capacity was assessed using a delayed visual match to the sample task. High gamma tACS significantly increased WM capacity, while low gamma tACS had no significant effect. Notably, 80 Hz tACS increased WM capacity on both the left and right visual hemifields, while previous tACS studies only reported the effects of tACS on contralateral hemifields. This is the first study to investigate the frequency-dependent effect of gamma-band tACS on WM capacity. Our findings also suggest that high gamma tACS might influence not only WM capacity but also communication between interhemispheric cortical regions. It is expected that high gamma tACS could be a promising neurorehabilitation method to enhance higher-order cognitive functions with similar mechanisms.

Association between the loudness dependence of auditory evoked potentials and age in patients with schizophrenia and depression.

OBJECTIVE: Although serotonergic dysfunction is significantly associated with major depressive disorder (MDD) and schizophrenia (SCZ), comparison of serotonergic dysfunction in both diseases has received little attention. Serotonin hypotheses have suggested diminished and elevated serotonin activity in MDD and SCZ, respectively. However, the foundations underlying these hypotheses are unclear regarding changes in serotonin neurotransmission in the aging brain. The loudness dependence of auditory evoked potentials (LDAEP) reflects serotonin neurotransmission. The present study compared the LDAEP between patients with SCZ or MDD and healthy controls (HCs). We further examined whether age was correlated with the LDAEP and clinical symptoms. METHODS: This prospective clinical study included 105 patients with SCZ (n = 54) or MDD (n = 51). Additionally, 35 HCs were recruited for this study. The LDAEP was measured on the midline channels via 62 electroencephalography channels. RESULTS: Patients with SCZ or MDD showed a significantly smaller mean LDAEP than those in HCs. The LDAEP was positively correlated with age in patients with SCZ or MDD. CONCLUSIONS: Changes in central serotonergic activity could be indicated by evaluating the LDAEP in patients with SCZ or MDD. Age-related reductions in serotonergic activity may be screened using the LDAEP in patients with SCZ or MDD.

Multipair transcranial temporal interference stimulation for improved focalized stimulation of deep brain regions: A simulation study.

Temporal interference stimulation (TIS) has been proved to be effective in stimulating deep brain regions while avoiding the stimulation of neocortical regions in animal experiments. In the traditional TIS, two alternating currents are injected with different frequencies via two electrode pairs attached to the scalp. In the human brain, however, it is difficult to achieve a focal stimulation of deep brain structures due to the high complexity of human brain structures. In this study, we hypothesized that the use of multiple electrode pairs may contribute to the more focalized delivery of temporal interference (TI) currents to the target site in the deep area of the brain. Based on this hypothesis, we proposed a novel multipair TIS method that employs more than two electrode pairs for improved focalized stimulation of the deep brain region (in this study, the head of the right hippocampus). Three realistic finite element models were used to validate the feasibility of the proposed multipair TIS. Additional electrode pairs were sequentially added to the conventional two-electrode pairs with the aim of maximizing the delivery of TI currents to the target while minimizing TI currents in the neocortical regions. The results confirmed that the multipair TIS provides better focalized stimulation than the conventional two-pair TIS for all three head models. It is expected that the proposed multipair TIS can be used to enhance the effectiveness of noninvasive deep brain stimulation.

In-vivo estimation of tissue electrical conductivities of a rabbit eye for precise simulation of electric field distributions during ocular iontophoresis.

Precise estimation of electrical conductivity of the eyes is important for the accurate analysis of electric field distributions in the eyes during ocular iontophoresis. In this study, we estimated the tissue electrical conductivities of a rabbit eye, which has been widely employed for neuro-ophthalmological experiments, through an in vivo experiment for the first time. Electrical potentials were measured at multiple locations on the skin, while weak currents were transmitted into the skin via two surface electrodes attached to the skin around the eye. A finite element model was constructed to calculate the electric potentials at the measurement locations. The conductivity values of different tissues were then estimated using an optimization procedure to minimize the difference between the measured and calculated electric potentials. The accuracy of the estimated tissue conductivity values of the rabbit eye was validated by comparing the measured and calculated electric potential values for different electrode montages. Further multi-physical analyses of iontophoretic drug delivery to the rabbit eye showed a significant influence of the conductivity profile on the resultant particle distribution. Overall, our results provide an important reference for the tissue electrical conductivity values of the rabbit eye, which could be further utilized for designing new medical devices for delivering electric fields to the eyes, such as transorbital and transscleral electrical stimulations.

Machine Learning-Based Electroencephalographic Phenotypes of Schizophrenia and Major Depressive Disorder.

Background: Psychiatric diagnosis is formulated by symptomatic classification; disease-specific neurophysiological phenotyping could help with its fundamental treatment. Here, we investigated brain phenotyping in patients with schizophrenia (SZ) and major depressive disorder (MDD) by using electroencephalography (EEG) and conducted machine-learning-based classification of the two diseases by using EEG components. Materials and Methods: We enrolled healthy controls (HCs) (n = 30) and patients with SZ (n = 34) and MDD (n = 33). An auditory P300 (AP300) task was performed, and the N1 and P3 components were extracted. Two-group classification was conducted using linear discriminant analysis (LDA) and support vector machine (SVM) classifiers. Positive and negative symptoms and depression and/or anxiety symptoms were evaluated. Results: Considering both the results of statistical comparisons and machine learning-based classifications, patients and HCs showed significant differences in AP300, with SZ and MDD showing lower N1 and P3 than HCs. In the sum of amplitudes and cortical sources, the findings for LDA with classification accuracy (SZ vs. HCs: 71.31%, MDD vs. HCs: 74.55%), sensitivity (SZ vs. HCs: 77.67%, MDD vs. HCs: 79.00%), and specificity (SZ vs. HCs: 64.00%, MDD vs. HCs: 69.67%) supported these results. The SVM classifier showed reasonable scores between SZ and HCs and/or MDD and HCs. The comparison between SZ and MDD showed low classification accuracy (59.71%), sensitivity (65.08%), and specificity (54.83%). Conclusions: Patients with SZ and MDD showed deficiencies in N1 and P3 components in the sum of amplitudes and cortical sources, indicating attentional dysfunction in both early and late sensory/cognitive gating input. The LDA and SVM classifiers in the AP300 are useful to distinguish patients with SZ and HCs and/or MDD and HCs.

Comparison of frontal alpha asymmetry among schizophrenia patients, major depressive disorder patients, and healthy controls.

BACKGROUND: Electroencephalography (EEG) frontal alpha asymmetry (FAA) has been observed in several psychiatric disorders. Dominance in left or right frontal alpha activity remains inconsistent in patients with major depressive disorder (MDD), patients with schizophrenia, and healthy controls. This study compared FAA among patients with MDD and schizophrenia, and healthy controls. METHODS: We recruited 20 patients with MDD, 18 patients with schizophrenia, and 16 healthy individuals. The EEG alpha frequency ranged from 8 Hz to 12 Hz. FAA was expressed as the difference between absolute power values of right and left hemisphere electrodes in the alpha frequency range (common-log-transformed frontal right- and left-hemisphere electrodes: F4-F3, F8-F7, FP2-FP1, AF4-AF3, F6-F5, and F2-F1). Hamilton depression and anxiety rating scales were evaluated in patients with MDD. Positive and negative syndrome scales were evaluated in patients with schizophrenia. RESULTS: Patients with schizophrenia showed significantly lower left FAA than healthy controls (F4-F3, schizophrenia vs. healthy controls: - 0.10 ± 0.04 vs. -0.05 ± 0.05). There were no significant differences in FAA between patients with schizophrenia and MDD as well as between patients with MDD and healthy controls. CONCLUSIONS: The present study suggests that FAA indicates a relatively lower activation of left frontal electrodes in schizophrenia. The left-lateralized FAA could be a neuropathological attribute in patients with schizophrenia, but a lack of sample size and information such as medication and duration of illness might obscure the interpretation and generalization of our findings. Thus, further studies to verify the findings would be warranted.

Individually customized transcranial temporal interference stimulation for focused modulation of deep brain structures: a simulation study with different head models.

Temporal interference (TI) stimulation was recently proposed that allows for the stimulation of deep brain structures with neocortical regions being minimally stimulated. For human brain modulation, TI current patterns are known to be considerably affected by the complex structures of the human head, and thus, it is hard to deliver TI current to a specific deep brain region. In this study, we optimized scalp electrode configurations and injection currents that can deliver maximum TI stimulation currents to a specific deep brain region, the head of the right hippocampus in this study, considering the real anatomical head structures of each individual. Three realistic finite element (FE) head models were employed for the optimization of TI stimulation. To generate TI current patterns, two pairs of scalp electrodes were selected, which carry two sinusoidally alternating currents with a small frequency difference. For every possible combination of electrode pairs, optimal injection currents delivering the maximal TI currents to the head of the right hippocampus were determined. The distribution of the optimized TI currents was then compared with that of the unoptimized TI currents and the conventional single frequency alternating current stimulation. Optimization of TI stimulation parameters allows for the delivery of the desired amount of TI current to the target region while effectively reducing the TI currents delivered to cortical regions compared to the other stimulation approaches. Inconsistency of the optimal stimulation conditions suggest that customized stimulation, considering the individual anatomical differences, is necessary for more effective transcranial TI stimulation. Customized transcranial TI stimulation based on the numerical field analysis is expected to enhance the overall effectiveness of noninvasive stimulation of the human deep brain structures.

Can Anodal Transcranial Direct Current Stimulation Increase Steady-State Visual Evoked Potential Responses?

BACKGROUND: It has been frequently reported that non-negligible numbers of individuals have steady-state visual evoked potential (SSVEP) responses of low signal-to-noise-ratio (SNR) to specific stimulation frequencies, which makes detection of the SSVEP difficult especially in brain-computer interface applications. We investigated whether SSVEP can be modulated by anodal transcranial direct-current stimulation (tDCS) of the visual cortex. METHODS: Each participant participated in two 20-min experiments-an actual tDCS experiment and a sham tDCS experiment-that were conducted on different days. Two representative electroencephalogram (EEG) features used for the SSVEP detection, SNR and amplitude, were tested for pre- and post-tDCS conditions to observe the effect of the anodal tDCS. RESULTS: The EEG features were significantly enhanced by the anodal tDCS for the electrodes with low pre-tDCS SNR values, whereas the effect was not significant for electrodes with relatively higher SNR values. CONCLUSION: Anodal tDCS of the visual cortex may be effective in enhancing the SNR and amplitude of the SSVEP response especially for individuals with low-SNR SSVEP.

Comparison of magnetic field distributions generated by various permanent magnets for transcranial static magnetic stimulation: A simulation study.

Recent experimental studies have shown that static magnetic field can be effective in modulating human brain functions. Following this discovery, a new noninvasive brain stimulation technique was developed: the transcranial static magnetic stimulation (tSMS). Various types of permanent magnets have been used in previous experimental studies, with the aim of validating the effectiveness of tSMS; nevertheless, the spatial distributions of magnetic field generated by these permanent magnets have not been fully investigated. In this study, we compared the distributions of magnetic field on the human cortical surface generated by five different cylindrical magnets (of various dimensions), using the finite element method. Our simulation results demonstrated that the magnitude of magnetic flux density induced in the cortical grey matter of the human brain is proportional to the volume of permanent magnets used, while the magnetic field gradient is not necessarily proportional to the volume of the magnets. Additionally, we showed that the use of magnets with internal holes might not be advantageous. The differences in magnetic field properties induced by various types of permanent magnets suggested that their careful selection, based on magnetic field simulations, might be necessary to increase the effectiveness of tSMS.

New Strategy for Finite Element Mesh Generation for Accurate Solutions of Electroencephalography Forward Problems.

The finite element method (FEM) is a numerical method that is often used for solving electroencephalography (EEG) forward problems involving realistic head models. In this study, FEM solutions obtained using three different mesh structures, namely coarse, densely refined, and adaptively refined meshes, are compared. The simulation results showed that the accuracy of FEM solutions could be significantly enhanced by adding a small number of elements around regions with large estimated errors. Moreover, it was demonstrated that the adaptively refined regions were always near the current dipole sources, suggesting that selectively generating additional elements around the cortical surface might be a new promising strategy for more efficient FEM-based EEG forward analysis.

Anodal frontal tDCS for chronic cluster headache treatment: a proof-of-concept trial targeting the anterior cingulate cortex and searching for nociceptive correlates.

BACKGROUND: Percutaneous occipital nerve stimulation (ONS) is effective in refractory chronic cluster headache (rCCH) patients. Responders to ONS differ from non-responders by greater glucose metabolism in subgenual anterior cingulate cortex (sgACC). We reasoned that transcranial direct current stimulation (tDCS), a non-invasive approach, might be able to activate this area and thus improve rCCH patients. Our objective was to explore in a pilot trial the therapeutic potential of tDCS (anode at Fz, cathode over C7) and its possible effects on pain perception, frontal executive functions and mood in rCCH patients. METHODS: Thirty-one patients were asked to apply daily 20-min sessions of 2 mA tDCS for 4 or 8 weeks after a 1-month baseline. CH attacks were monitored with paper diaries. The primary outcome measure was change in weekly attacks between baseline and the last week of tDCS. Twenty-three patients were available for a modified ITT analysis, 21 for per-protocol analysis. We also explored treatment-related changes in thermal pain thresholds and nociceptive blink reflexes (nBR), frontal lobe function and mood scales. RESULTS: In the per-protocol analysis there was a mean 35% decrease of attack frequency (p = 0.0001) with 41% of patients having a ≥ 50% decrease. Attack duration and intensity were also significantly reduced. After 8 weeks (n = 10), the 50% responder rate was 45%, but at follow-up 2 weeks after tDCS (n = 16) mean attack frequency had returned to baseline levels. The treatment effect was significant in patients with high baseline thermal pain thresholds in the forehead (n = 12), but not in those with low thresholds (n = 9). The Frontal Assessment Battery score increased after tDCS (p = 0.01), while there was no change in depression scores or nBR. CONCLUSION: tDCS with a Fz-C7 montage may have a preventive effect in rCCH patients, especially those with low pain sensitivity, suggesting that a sham-controlled trial in cluster headache is worthwhile. Whether the therapeutic effect is due to activation of the sgACC that can in theory be reached by the electrical field, or of other prefrontal cortical areas remains to be determined.

Altered Network Characteristics of Spike-Wave Discharges in Juvenile Myoclonic Epilepsy.

Epilepsy is a disease marked by hypersynchronous bursts of neuronal activity; therefore, identifying the network characteristics of the epileptic brain is important. Juvenile myoclonic epilepsy (JME) represents a common, idiopathic generalized epileptic syndrome, characterized by spike-and-wave discharge (SWD) electroencephalographic (EEG) waveforms. We compare herein the network properties of periods of SWD and baseline activity using graph theory. EEG data were obtained from 11 patients with JME. Functional cortical networks during SWD and baseline periods were estimated by calculating the coherence between all possible electrode pairs in the delta, theta, alpha, beta and gamma bands. Graph theoretical measures, including nodal degree, characteristic path length, clustering coefficient, and small-world index were then used to evaluate the characteristics of epileptic networks in JME. We also assessed short- and long-range connections between SWD and baseline networks. Compared to baseline, increased coherence was observed during SWD in all frequency bands. The nodal degree of the SWD network, particularly in the frontal region, was significantly higher compared to the baseline network. The clustering coefficient and small-world index were significantly lower in the theta and beta bands of the SWD versus baseline network, but the characteristic path length did not differ among networks. Long-range connections were increased during SWD, particularly between frontal and posterior brain regions. Our study suggests that SWD in JME is associated with increased local (particularly in frontal region) connectivity. Furthermore, the SWD network was associated with increased long-range connections, and reduced small-worldness, which may impair information processing during SWD.