Extensive sampling of neural activity during rich cognitive phenomena is critical for robust
understanding of brain function. Here we present the Natural Scenes Dataset (NSD), in …

The mental contents of perception and imagery are thought to be encoded in hierarchical
representations in the brain, but previous attempts to visualize perceptual contents have …

Decoding visual stimuli from neural responses recorded by functional Magnetic Resonance
Imaging (fMRI) presents an intriguing intersection between cognitive neuroscience and …

Understanding how the brain encodes external stimuli and how these stimuli can be
decoded from the measured brain activities are long-standing and challenging questions in …

Vision science, particularly machine vision, has been revolutionized by introducing large-
scale image datasets and statistical learning approaches. Yet, human neuroimaging studies …

The application of deep learning (DL) models to neuroimaging data poses several
challenges, due to the high dimensionality, low sample size, and complex temporo-spatial …

Abstract Machine learning is a field of computer science that builds algorithms that learn. In
many cases, machine learning algorithms are used to recreate a human ability like adding a …

Precision Neuroscience: Dense Sampling of Individual Brains: Neuron Skip to Main Content
Advertisement Neuron This journal offers authors two options (open access or subscription) to …

Reconstructing human vision from brain activities has been an appealing task that helps to
understand our cognitive process. Even though recent research has seen great success in …

With the advent of brain imaging techniques and machine learning tools, much effort has
been devoted to building computational models to capture the encoding of visual …