No abstract

Generative adversarial nets (GANs) and variational auto-encoders have significantly improved our distribution modeling capabilities, showing promise for dataset augmentation, image-to-image translation and feature learning. However, to model high-dimensional distributions, sequential training and stacked architectures are common, increasing the number of tunable hyper-parameters as well as the training time. Nonetheless, the sample complexity of the distance metrics remains one of the factors affecting GAN training. We first show that the recently proposed sliced Wasserstein distance has compelling sample complexity properties when compared to the Wasserstein distance. To further improve the sliced Wasserstein distance we then analyze its 'projection complexity' and develop the max-sliced Wasserstein distance which enjoys compelling sample complexity while reducing projection complexity, albeit necessitating a max estimation. We finally illustrate that the proposed distance trains GANs on high-dimensional images up to a resolution of 256x256 easily.

In understanding the brain's response to extensive practice and development of high-level, expert skill, a key question is whether the same brain structures remain involved throughout the different stages of learning and a form of adaptation occurs, or a new functional circuit is formed with some structures dropping off and others joining. After training subjects on a set of complex motor tasks (tying knots), we utilized fMRI to observe that in subjects who learned the task well new regional activity emerged in posterior medial structures, i.e. the posterior cingulate gyrus. Activation associated with weak learning of the knots involved areas that mediate visual spatial computations. Brain activity associated with no substantive learning indicated involvement of areas dedicated to the declarative aspects learning such as the anterior cingulate and prefrontal cortex. The new activation for the pattern of strong learning has alternate interpretations involving either retrieval during episodic memory or a shift toward non-executive cognitive control of the task. While these interpretations are not resolved, the study makes clear that single time-point images of motor skill can be misleading because the brain structures that implement action can change following practice.

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This study investigates the effect of arousal on visual selection processes. Arousal is predicted to narrow the window of attention surrounding a point of focus. BOLD response to a letter discrimination task was measured under aroused (aversive noise) and non-aroused conditions (n = 8). Results revealed spatially distinct responses for trials invoking a narrow versus wide attentional focus. Under arousal a wide focus showed posterior thalamic activation similar to that associated with the narrowed attentional focus. This reflects altered stimulus filtering and supported the hypothesis. Relevant neuroanatomy involving the locus coeruleus and a triangular circuit of selective attention is discussed. The data demonstrates the intersection of arousal and visual stimulus selection systems, identifies a cognitive consequence of arousal, and provides the first fMRI evidence for brain stem autonomic arousal.