Effects of alternating current stimulation on the healthy and diseased brain

Cognitive and neurological dysfunctions can severely impact a patient's daily activities. In addition to medical treatment, non-invasive transcranial alternating current stimulation (tACS) has been proposed as a therapeutic technique to improve the functional state of the brain. Although during the last years tACS was applied in numerous studies to improve motor, somatosensory, visual and higher order cognitive functions, our knowledge is still limited regarding the mechanisms as to which type of ACS can affect cortical functions and altered neuronal oscillations seem to be the key mechanism. Because alternating current send pulses to the brain at predetermined frequencies, the online- and after-effects of ACS strongly depend on the stimulation parameters so that “optimal” ACS paradigms could be achieved. This is of interest not only for neuroscience research but also for clinical practice. In this study, we summarize recent findings on ACS-effects under both normal conditions and in brain diseases

A Rapid Sound-Action Association Effect in Human Insular Cortex

BACKGROUND: Learning to play a musical piece is a prime example of complex sensorimotor learning in humans. Recent studies using electroencephalography (EEG) and transcranial magnetic stimulation (TMS) indicate that passive listening to melodies previously rehearsed by subjects on a musical instrument evokes differential brain activation as compared with unrehearsed melodies. These changes were already evident after 20–30 minutes of training. The exact brain regions involved in these differential brain responses have not yet been delineated. METHODOLOGY/PRINCIPAL FINDING: Using functional MRI (fMRI), we investigated subjects who passively listened to simple piano melodies from two conditions: In the ‘actively learned melodies’ condition subjects learned to play a piece on the piano during a short training session of a maximum of 30 minutes before the fMRI experiment, and in the ‘passively learned melodies’ condition subjects listened passively to and were thus familiarized with the piece. We found increased fMRI responses to actively compared with passively learned melodies in the left anterior insula, extending to the left fronto-opercular cortex. The area of significant activation overlapped the insular sensorimotor hand area as determined by our meta-analysis of previous functional imaging studies. CONCLUSIONS/SIGNIFICANCE: Our results provide evidence for differential brain responses to action-related sounds after short periods of learning in the human insular cortex. As the hand sensorimotor area of the insular cortex appears to be involved in these responses, re-activation of movement representations stored in the insular sensorimotor cortex may have contributed to the observed effect. The insular cortex may therefore play a role in the initial learning phase of action-perception associations

Time Scales of Auditory Habituation in the Amygdala and Cerebral Cortex

Habituation is a fundamental form of learning manifested by a decrement of neuronal responses to repeated sensory stimulation. In addition, habituation is also known to occur on the behavioral level, manifested by reduced emotional reactions to repeatedly presented affective stimuli. It is, however, not clear which brain areas show a decline in activity during repeated sensory stimulation on the same time scale as reduced valence and arousal experience and whether these areas can be delineated from other brain areas with habituation effects on faster or slower time scales. These questions were addressed using functional magnetic resonance imaging acquired during repeated stimulation with piano melodies. The magnitude of functional responses in the laterobasal amygdala and in related cortical areas and that of valence and arousal ratings, given after each music presentation, declined in parallel over the experiment. In contrast to this long-term habituation (43 min), short-term decreases occurring within seconds were found in the primary auditory cortex. Sustained responses that remained throughout the whole investigated time period were detected in the ventrolateral prefrontal cortex extending to the dorsal part of the anterior insular cortex. These findings identify an amygdalocortical network that forms the potential basis of affective habituation in human

Fat navigators and Moiré phase tracking comparison for motion estimation and retrospective correction

Purpose: To compare motion tracking by two modern methods (fat navigators - FatNavs and Moiré phase tracking - MPT) as well as their performance for retrospective correction of very high resolution acquisitions. Methods: A direct comparison of FatNavs and MPT motion parameters was performed for several deliberate motion patterns to estimate the agreement between methods. In addition, two different navigator resolution were applied. 0.5 mm isotropic MP2RAGE images with simultaneous MPT and FatNavs tracking were acquired in nine cooperative subjects with no intentional motion. Retrospective motion corrections based on both tracking modalities were compared qualitatively and quantitatively. The FatNavs impact on quantitative T1 maps was also investigated. Results: Both methods showed good agreement within a 0.3 mm/° margin in subjects that moved very little. Higher resolution FatNavs (2mm) showed overall better agreement with MPT than 4mm resolution ones, except for fast and large motion. The retrospective motion corrections based on MPT or FatNavs were at par in 33 cases out of 36, and visibly improved image quality compared to the uncorrected images. In separate fringe cases, both methods suffered from their respective potential shortcomings: unreliable marker attachment for MPT and poor temporal resolution for FatNavs. The magnetization transfer induced by the navigator RF pulses had a visible impact on the T1 values distribution, with a shift of the gray and white matter peaks of 12 ms at most. Conclusion: This work confirms both FatNavs and MPT as excellent retrospective motion correction methods for very high resolution imaging of cooperative subjects

Exploration of Interpretability Techniques for Deep COVID-19 Classification using Chest X-ray Images

The outbreak of COVID-19 has shocked the entire world with its fairly rapid spread and has challenged different sectors. One of the most effective ways to limit its spread is the early and accurate diagnosis of infected patients. Medical imaging such as X-ray and Computed Tomography (CT) combined with the potential of Artificial Intelligence (AI) plays an essential role in supporting the medical staff in the diagnosis process. Thereby, the use of five different deep learning models (ResNet18, ResNet34, InceptionV3, InceptionResNetV2, and DenseNet161) and their Ensemble have been used in this paper, to classify COVID-19, pneumoni{\ae} and healthy subjects using Chest X-Ray. Multi-label classification was performed to predict multiple pathologies for each patient, if present. Foremost, the interpretability of each of the networks was thoroughly studied using techniques like occlusion, saliency, input X gradient, guided backpropagation, integrated gradients, and DeepLIFT. The mean Micro-F1 score of the models for COVID-19 classifications ranges from 0.66 to 0.875, and is 0.89 for the Ensemble of the network models. The qualitative results depicted the ResNets to be the most interpretable model