Dermoid cysts are developmental abnormal arrangement of tissues and are often evident soon after birth. Its occurrence in the orbit is relatively rare. We report a case of orbital floor dermoid in an 18-year-old female patient who presented with progressive, painless swelling in the lower eyelid associated with mild proptosis of three months duration. The lesion was excised completely, and histopathology confirmed the diagnosis of dermoid cyst.

We examine the utility of implicit user behavioral signals captured using low-cost, o -the-shelf devices for anonymous gender and emotion recognition. A user study designed to examine male and female sensitivity to facial emotions con rms that females recognize (especially negative) emotions quicker and more accurately than men, mirroring prior ndings. Implicit viewer responses in the form of EEG brain signals and eye movements are then examined for existence of (a) emotion and gender-speci c pa erns from event-related potentials (ERPs) and xation distributions and (b) emotion and gender discriminability. Experiments reveal that (i) Gender and emotion-speci c di erences are observable from ERPs, (ii) multiple similarities exist between explicit responses gathered from users and their implicit behavioral signals, and (iii) Signicantly above-chance (≈70%) gender recognition is achievable on comparing emotion-speci c EEG responses-gender di erences are encoded best for anger and disgust. Also, fairly modest valence (positive vs negative emotion) recognition is achieved with EEG and eye-based features.

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Neural correlates corresponding to a specific cognitive tasks has been made possible with techniques like functional magnetic resonance imaging. The increasing number of neuroimaging studies has made meta-analysis methods popular for useful inferencing across multiple studies. The easy availability of neuroinformatic tools has also resulted in increasing the number of meta-analysis studies. We compare different meta-analysis approaches using hand-curated database (Brain map) and automated database (neurosynth) using the case study of reward-related studies. We combine meta-analysis with atlas-based approaches to quantitatively compare different meta analysis approaches. Based on our results, we propose further integration of different meta-analytic approaches with automated data mining methods for neuroimaging.

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