Tinnitus and chronic pain are sensory-perceptual disorders associated with negative affect and high impact on well-being and behavior. It is now becoming increasingly clear that higher cognitive and affective brain systems are critically involved in the pathology of both disorders. Here, we propose that the ventromedial prefrontal cortex and the nucleus accumbens are part of a central “gatekeeping” system in both sensory modalities, which evaluates the relevance and affective value of sensory stimuli and controls information flow via descending pathways. If this frontostriatal system is compromised, long-lasting disturbances are the result. Parallels in both systems are striking and mutually informative, and progress in understanding central gating mechanisms might provide a new impetus to the therapy of tinnitus and chronic pain.

The underlying functional neuroanatomy of tinnitus remains poorly understood. Few studies have focused on functional cerebral connectivity changes in tinnitus patients. The aim of this study was to test if functional MRI “resting-state” connectivity patterns in auditory network differ between tinnitus patients and normal controls. Thirteen chronic tinnitus subjects and fifteen age-matched healthy controls were studied on a 3 tesla MRI. Connectivity was investigated using independent component analysis and an automated component selection approach taking into account the spatial and temporal properties of each component. Connectivity in extra-auditory regions such as brainstem, basal ganglia/NAc, cerebellum, parahippocampal, right prefrontal, parietal, and sensorimotor areas was found to be increased in tinnitus subjects. The right primary auditory cortex, left prefrontal, left fusiform gyrus, and bilateral occipital regions showed a decreased connectivity in tinnitus. These results show that there is a modification of cortical and subcortical functional connectivity in tinnitus encompassing attentional, mnemonic, and emotional networks. Our data corroborate the hypothesized implication of non-auditory regions in tinnitus physiopathology and suggest that various regions of the brain seem involved in the persistent awareness of the phenomenon as well as in the development of the associated distress leading to disabling chronic tinnitus.

Thirteen chronic tinnitus patients and fifteen age-matched healthy controls were studied on a 3 T magnetic resonance imaging (MRI) scanner during resting condition (i.e. eyes closed, no task performance). The auditory resting-state component was selected using an automatic component selection approach. Functional connectivity (correlations/anticorrelations) in the extracted network was portrayed by integrating the independent component analysis (ICA) approach with a graph theory method. Tinnitus and control groups showed different graph connectivity patterns. In the control group, the connectivity graph was divided into two distinct anti-correlated networks. The first one encompassed the auditory cortices and the insula. The second one encompassed frontoparietal and anterior cingulate cortices, brainstem, amygdala, basal ganglia/nucleus accumbens and parahippocampal regions. In the tinnitus group, only one of the two previously described networks was observed, encompassing the auditory cortices and the insula. Direct group comparison showed, in the tinnitus group, an increased functional connectivity between auditory cortices and the left parahippocampal region surviving multiple comparisons. We

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Abstract:The term 'locked-in' syndrome (LIS) describes a medical condition in which persons concerned are severely paralyzed and at the same time fully conscious and awake. The resulting anarthria makes it impossible for these patients to naturally communicate, which results in diagnostic as well as serious practical and ethical problems. Therefore, developing alternative, muscle-independent communication means is of prime importance. Such communication means can be realized via brain-computer interfaces (BCIs) circumventing the muscular system by using brain signals associated with preserved cognitive, sensory, and emotional brain functions. Primarily, BCIs based on electrophysiological measures have been developed and applied with remarkable success. Recently, also blood flow-based neuroimaging methods, such as functional magnetic resonance imaging (fMRI) and functional near-infrared spectroscopy (fNIRS), have been explored in this context.After reviewing recent literature on the development of especially hemodynamically based BCIs, we introduce a highly reliable and easy-to-apply communication procedure that enables untrained participants to motor-independently and relatively effortlessly answer multiple-choice questions based on intentionally generated single-trial fMRI signals that can be decoded online. Our technique takes advantage of the participants' capability to voluntarily influence certain spatio-temporal aspects of the blood oxygenation level-dependent (BOLD) signal: source location (by using different mental tasks), signal onset and offset. We show that healthy participants are capable of hemodynamically encoding at least four distinct information units on a single-trial level without extensive pretraining and with little effort. Moreover, realtime data analysis based on simple multi-filter correlations allows for automated answer decoding with a high accuracy (94.9%) demonstrating the robustness of the presented method. Following our 'proof of concept', the next step will involve clinical trials with LIS patients, undertaken in close collaboration with their relatives and caretakers in order to elaborate individually tailored communication protocols.� Corresponding author. As our procedure can be easily transferred to MRI-equipped clinical sites, it may constitute a simple and effective possibility for online detection of residual consciousness and for LIS patients to communicate basic thoughts and needs in case no other alternative communication means are available (yet) -especially in the acute phase of the LIS. Future research may focus on further increasing the efficiency and accuracy of fMRI-based BCIs by implementing sophisticated data analysis methods (e.g., multivariate and independent component analysis) and neurofeedback training techniques. Finally, the presented BCI approach could be transferred to portable fNIRS systems as only this would enable hemodynamically based communication in daily life situations.