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Studying electroencephalography (EEG) in response to transcranial magnetic stimulation (TMS) is gaining popularity for investigating the dynamics of complex neural architecture in the brain. For example, the primary motor cortex (M1) executes voluntary movements by complex connections with other associated subnetworks. To understand these connections better, we analyzed EEG signal response to TMS at left M1 from schizophrenia patients and healthy controls and in contrast with resting state EEG recording. After removing artifacts from EEG, we conducted 2D to 3D sLORETA conversion, a well-established source localization method, for estimating signal strength of 68 source dipoles or cortical regions inside the brain. Next, we studied dynamic connectivity by computing time-evolving spatial coherence of 2278 (=68*(68-1)/2) pairs of cortical regions, with sliding window technique of 200ms window size and 20ms shift over 1sec long data. Pairs with consistent coherence (coherence>0.8 during 200+ sliding windows of patients and controls combined) were chosen for identifying stable networks. For example, we found that during the resting state, precuneus was steadily coherent with middle and superior temporal gyrus in the left hemisphere in both patient and controls. Their connectivity pattern over the sliding windows significantly differed between patients and controls (pvalue<0.05). Whereas for M1, the same was true for two other coherent pairs namely, superamarginal gyrus with lateral occipital gyrus in right hemisphere and medial orbitofrontal gyrus with fusiform in left hemisphere. The TMS-EEG dynamic connectivity results can help to differentiate patient and normal subjects and also help to better understand the brain architecture and mechanisms. 

In recent years, there is an increasing interest in noninvasive treatments for neurological disorders like Alzheimer and Depression. Transcranial magnetic stimulation (TMS) is one of the most effective methods used for this purpose. The performance of TMS highly depends on the coils used for the generation of magnetic field and induced electric field particularly their designs affecting depth and focality tradeoff characteristics. Among a variety of proposed and used TMS coil designs, circular coils are commonly used both in research and medical and clinical applications. In current study, we focus on changing the outer and inner sizes (diameter) and winding turns of ring coils and try to reach deeper brain regions without significant field strength decay. The induced electric field and the decay rate of the generated field with depth were studied with finite element method calculations. The results of the performed simulations indicate that larger diameter coils have a larger equivalent field emission aperture and produce larger footprint of induced electric field initially. However, their emission solid angles are smaller and, as a result, the field divergence or the decay rates of the generated field with depth are smaller as well, which give them a good potential to perform better for deep brain stimulation compared with that of smaller coil. 

Electroencephalogram (EEG) recording is a widely used method to measure electrical activity in the brain. Rodent EEG brain recording not only is noninvasive but also has the advantages to accomplish full brain monitoring, compared with that of the invasive techniques like micro-electrode-arrays. In comparison to other noninvasive recording techniques, EEG is the only technique that can achieve sub-ms scale time resolution, which is essential to obtain causal relationship. In this work, we demonstrated a simple microfabrication process for developing a high-density polyimide-based rodent EEG recording cap. A 34-channel rodent electrode array with a total size of 11mmx8mm, individual electrode diameter 240μm and interconnect wire linewidth 35μm was designed and fabricated. For the fabrication process, we first deposit 350nm SiO2 on a silicon substrate. We then fabricate 6-7μm thick first layer polyimide caps with fingers and contact holes. Gold deposition and then lithography etching of 34 channel contact-electrodes and their interconnects were fabricated in the second step. The third step was to cover metal interconnects with a 10μm thick second layer polyimide, which was fabricated with photolithography before the final film released by HF undercutting etching of SiO2 layer. Then the fabricated EEG cap is interfaced with a commercial 34-channel female connector, which is soldered with 34-line wires. These wires are then connected to an ADC to record the EEG data in computer for post-processing. With polyimide, the EEG cap is biocompatible, and flexible which makes it suitable for good contact with rodent skulls. 

Transcranial magnetic stimulation (TMS) is gaining increasing attention for therapeutic treatment of mental illnesses. However, a clear understanding of its impact to the underlying brain mechanisms is critical for its effective application. For this, we analyze electroencephalography (EEG) response to TMS subthreshold pulse at the left motor cortex from 6 healthy controls and 6 schizophrenia patients. We use principal component analysis (PCA) along sparse nonnegative matrix factorization (NMF), an unsupervised machine learning technique, on brain connectivity data established by sliding window coherence of EEG based source localized data. The source localization was achieved by using the sLORETA algorithm on our EEG data after artifact removal. This, hence, provides high temporal and spatial resolution in the connectivity analysis results, giving advantage over other neuroimaging modalities. PCA aids in establishing the number of common underlying connected subnetworks (say k) across subjects whereas NMF is employed to derive these k spatial and temporal signature subnetwork response to the stimulus. Within these signatures, we studied motor cortical connectivity and found that schizophrenia patients exhibited sensory gating deficits as compared to controls. These findings can act as potential biomarkers to monitor TMS for clinical therapeutic techniques in the future. 

Cerebellar-prefrontal connectivity has been recognized as important for behaviors ranging from motor coordination to cognition. Many of these behaviors are known to involve excitatory or inhibitory modulations from the prefrontal cortex. We used cerebellar transcranial magnetic stimulation (TMS) with simultaneous electroencephalography (EEG) to probe cerebellar-evoked electrical activity in prefrontal cortical areas and used magnetic resonance spectroscopy (MRS) measures of prefrontal GABA and glutamate levels to determine if they are correlated with those potentials. Cerebellar-evoked bilateral prefrontal synchrony in the theta to gamma frequency range showed patterns that reflect strong GABAergic inhibitory function (r = − 0.66, p = 0.002). Stimulation of prefrontal areas evoked bilateral prefrontal synchrony in the theta to low beta frequency range that reflected, conversely, glutamatergic excitatory function (r = 0.66, p = 0.002) and GABAergic inhibitory function (r = − 0.65, p = 0.002). Cerebellar-evoked prefrontal synchronization had opposite associationswith cognition and motor coordination: it was positively associated with workingmemory performance (r =0.57, p = 0.008) but negatively associated with coordinated motor function as measured by rapid finger tapping (r = − 0.59, p = 0.006). The results suggest a relationship between regional GABA levels and interregional effects on synchrony. Stronger cerebellar-evoked prefrontal synchrony was associated with better working memory but surprisingly worse motor coordination, which suggests competing effects for motor activity and cognition. The data supports the use of a TMS-EEG-MRS approach to study the neurochemical basis of large-scale oscillations modulated by the cerebellar-prefrontal connectivity.