Relating neural oscillations to laminar fMRI connectivity in visual cortex

Decoding the rhythmic representation and communication of visual contents

Rhythmic neural activity is considered essential for adaptively modulating responses in the visual system. In this opinion article we posit that visual brain rhythms also serve a key function in the representation and communication of visual contents. Collating a set of recent studies that used multivariate decoding methods on rhythmic brain signals, we highlight such rhythmic content representations in visual perception, imagery, and prediction. We argue that characterizing representations across frequency bands allows researchers to elegantly disentangle content transfer in feedforward and feedback directions. We further propose that alpha dynamics are central to content-specific feedback propagation in the visual system. We conclude that considering rhythmic content codes is pivotal for understanding information coding in vision and beyond.

Sleep, learning, and memory in human research using noninvasive neuroimaging techniques

An accumulating body of evidence indicates that sleep is beneficial for learning and memory. Task performance improves significantly after a period that includes sleep, whereas a lack of sleep nullifies or impairs such improvements. Our current knowledge about sleep's role in learning and memory has been obtained based on studies that were conducted in both animal models and human subjects. Nevertheless, how sleep promotes learning and memory in humans is not fully understood. In this review, we overview our current understating of how sleep may contribute to learning and memory, covering different roles of non-rapid eye movement and rapid eye movement sleep. We then discuss cutting-edge advanced techniques that are currently available, including simultaneous functional magnetic resonance imaging (fMRI) and electroencephalogram (EEG) and simultaneous functional magnetic resonance spectroscopy (fMRS) and EEG measurements, and evaluate how these may contribute to advance the understanding of the role of sleep in human cognition. We also highlight the current limitations and challenges using these methods and discuss ways that may allow us to overcome these limitations.

Laminar functional magnetic resonance imaging in vision research

Magnetic resonance imaging (MRI) scanners at ultra-high magnetic fields have become available to use in humans, thus enabling researchers to investigate the human brain in detail. By increasing the spatial resolution, ultra-high field MR allows both structural and functional characterization of cortical layers. Techniques that can differentiate cortical layers, such as histological studies and electrode-based measurements have made critical contributions to the understanding of brain function, but these techniques are invasive and thus mainly available in animal models. There are likely to be differences in the organization of circuits between humans and even our closest evolutionary neighbors. Thus research on the human brain is essential. Ultra-high field MRI can observe differences between cortical layers, but is non-invasive and can be used in humans. Extensive previous literature has shown that neuronal connections between brain areas that transmit feedback and feedforward information terminate in different layers of the cortex. Layer-specific functional MRI (fMRI) allows the identification of layer-specific hemodynamic responses, distinguishing feedback and feedforward pathways. This capability has been particularly important for understanding visual processing, as it has allowed researchers to test hypotheses concerning feedback and feedforward information in visual cortical areas. In this review, we provide a general overview of successful ultra-high field MRI applications in vision research as examples of future research.