10 research outputs found
Pre-stimulus alpha activity modulates face and object processing in the intra-parietal sulcus, a MEG study
Face perception is crucial in all social animals. Recent studies have shown that pre-stimulus oscillations of brain activity modulate the perceptual performance of face vs. non-face stimuli, specifically under challenging conditions. However, it is unclear if this effect also occurs during simple tasks, and if so in which brain regions. Here we used magnetoencephalography (MEG) and a 1-back task in which participants decided if the two sequentially presented stimuli were the same or not in each trial. The aim of the study was to explore the effect of pre-stimulus alpha oscillation on the perception of face (human and monkey) and non-face stimuli. Our results showed that pre-stimulus activity in the left occipital face area (OFA) modulated responses in the intra-parietal sulcus (IPS) at around 170 ms after the presentation of human face stimuli. This effect was also found after participants were shown images of motorcycles. In this case, the IPS was modulated by pre-stimulus activity in the right OFA and the right fusiform face area (FFA). We conclude that pre-stimulus modulation of post-stimulus response also occurs during simple tasks and is therefore independent of behavioral responses
Embodying Time in the Brain: A Multi-Dimensional Neuroimaging Meta-Analysis of 95 Duration Processing Studies
Time is an omnipresent aspect of almost everything we experience internally or in the external world. The experience of time occurs through such an extensive set of contextual factors that, after decades of research, a unified understanding of its neural substrates is still elusive. In this study, following the recent best-practice guidelines, we conducted a coordinate-based meta-analysis of 95 carefully-selected neuroimaging papers of duration processing. We categorized the included papers into 14 classes of temporal features according to six categorical dimensions. Then, using the activation likelihood estimation (ALE) technique we investigated the convergent activation patterns of each class with a cluster-level family-wise error correction at p < 0.05. The regions most consistently activated across the various timing contexts were the pre-SMA and bilateral insula, consistent with an embodied theory of timing in which abstract representations of duration are rooted in sensorimotor and interoceptive experience, respectively. Moreover, class-specific patterns of activation could be roughly divided according to whether participants were timing auditory sequential stimuli, which additionally activated the dorsal striatum and SMA-proper, or visual single interval stimuli, which additionally activated the right middle frontal and inferior parietal cortices. We conclude that temporal cognition is so entangled with our everyday experience that timing stereotypically common combinations of stimulus characteristics reactivates the sensorimotor systems with which they were first experienced
A new family of generative adversarial nets using heterogeneous noise to model complex distributions
© Springer Nature Switzerland AG 2018. Generative adversarial nets (GANs) are effective framework for constructing data models and enjoys desirable theoretical justification. On the other hand, realizing GANs for practical complex data distribution often requires careful configuration of the generator, discriminator, objective function and training method and can involve much non-trivial effort. We propose an novel family of generative adversarial nets (GANs), where we employ both continuous noise and random binary codes in the generating process. The binary codes in the new GAN model (named BGANs) play the role of categorical latent variables helps improve the model capability and training stability when dealing with complex data distributions. BGAN has been evaluated and compared with existing GANs trained with the state-of-the-art method on both synthetic and practical data. The empirical evaluation shows effectiveness of BGAN