Reconstructing visual experiences from human brain activity offers a unique way to
understand how the brain represents the world, and to interpret the connection between …

Several deep neural networks have recently been shown to generate activations similar to
those of the brain in response to the same input. These algorithms, however, remain largely …

Models that predict brain responses to stimuli provide one measure of understanding of a
sensory system and have many potential applications in science and engineering. Deep …

The integration of deep learning and neuroscience has been advancing rapidly, which has
led to improvements in the analysis of brain activity and the understanding of deep learning …

Our ability to comprehend speech remains, to date, unrivaled by deep learning models. This
feat could result from the brain's ability to fine-tune generic sound representations for speech …

Research in hearing sciences has provided extensive knowledge about how the human
auditory system processes speech and assists communication. In contrast, little is known …

Mathematical operations have long been regarded as a sparse, symbolic process in
neuroimaging studies. In contrast, advances in artificial neural networks (ANN) have …

Comparing artificial neural networks with outputs of neuroimaging techniques has recently
seen substantial advances in (computer) vision and text-based language models. Here, we …

Amplitude modulation, a recently focused mode of modulation in fast–slow dynamics, plays
a crucial role in governing the behaviors of relaxation oscillations. This modulation mode …

Natural sounds contain rich patterns of amplitude modulation (AM), which is one of the
essential sound dimensions for auditory perception. The sensitivity of human hearing to AM …