Fast and functionally specific cortical thickness changes induced by visual stimulation

Structural characteristics of the human brain serve as important markers of brain development, aging, disease progression, and neural plasticity. They are considered stable properties, changing slowly over time. Multiple recent studies reported that structural brain changes measured with magnetic resonance imaging (MRI) may occur much faster than previously thought, within hours or even minutes. The mechanisms behind such fast changes remain unclear, with hemodynamics as one possible explanation. Here we investigated the functional specificity of cortical thickness changes induced by a flickering checkerboard and compared them to blood oxygenation level-dependent (BOLD) functional MRI activity. We found that checkerboard stimulation led to a significant thickness increase, which was driven by an expansion at the gray-white matter boundary, functionally specific to V1, confined to the retinotopic representation of the checkerboard stimulus, and amounted to 1.3% or 0.022 mm. Although functional specificity and the effect size of these changes were comparable to those of the BOLD signal in V1, thickness effects were substantially weaker in V3. Furthermore, a comparison of predicted and measured thickness changes for different stimulus timings suggested a slow increase of thickness over time, speaking against a hemodynamic explanation. Altogether, our findings suggest that visual stimulation can induce structural gray matter enlargement measurable with MRI.

Resting-state neural correlates of visual Gestalt experience

Subjective perceptual experience is influenced not only by bottom-up sensory information and experience-based top-down processes, but also by an individual's current brain state. Specifically, a previous study found increased prestimulus insula and intraparietal sulcus (IPS) activity before participants perceived an illusory Gestalt (global) compared with the non-illusory (local) interpretation of a bistable stimulus. That study provided only a snapshot of the brain state that favors the illusory interpretation. In the current study, we tested whether areas that differentiate between the illusory and non-illusory perception, immediately before stimulus onset, are also associated with an individual's general tendency to perceive it, which remains stable over time. We examined individual differences in task-free functional connectivity of insula and IPS and related them to differences in the individuals' duration of the two stimulus interpretations. We found stronger connectivity of the IPS with areas of the default mode and visual networks to be associated with shorter local perceptual phases, i.e. a faster switch to an illusory percept, and an opposite effect for insula connectivity with the early visual cortex. Our findings suggest an important role of IPS and insula interactions with nodes of key intrinsic networks in forming a perceptual tendency toward illusory Gestalt perception.

No common factor for illusory percepts, but a link between pareidolia and delusion tendency: A test of predictive coding theory

Predictive coding theory is an influential view of perception and cognition. It proposes that subjective experience of the sensory information results from a comparison between the sensory input and the top-down prediction about this input, the latter being critical for shaping the final perceptual outcome. The theory is able to explain a wide range of phenomena extending from sensory experiences such as visual illusions to complex pathological states such as hallucinations and psychosis. In the current study we aimed at testing the proposed connection between different phenomena explained by the predictive coding theory by measuring the manifestation of top-down predictions at progressing levels of complexity, starting from bistable visual illusions (alternating subjective experience of the same sensory input) and pareidolias (alternative meaningful interpretation of the sensory input) to self-reports of hallucinations and delusional ideations in everyday life. Examining the correlation structure of these measures in 82 adult healthy subjects revealed a positive association between pareidolia proneness and a tendency for delusional ideations, yet without any relationship to bistable illusions. These results show that only a subset of the phenomena that are explained by the predictive coding theory can be attributed to one common underlying factor. Our findings thus support the hierarchical view of predictive processing with independent top-down effects at the sensory and cognitive levels.

Increased insula activity precedes the formation of subjective illusory Gestalt

The constructive nature of human perception sometimes leads us to perceiving rather complex impressions from simple sensory input: for example, recognizing animal contours in cloud formations or seeing living creatures in shadows of objects. A special type of bistable stimuli gives us a rare opportunity to study the neural mechanisms behind this process. Such stimuli can be visually interpreted either as simple or as more complex illusory content on the basis of the same sensory input. Previous studies demonstrated increased activity in the superior parietal cortex during the perception of an illusory Gestalt impression compared to a simpler interpretation. Here, we examined the role of slow fluctuations of resting-state fMRI activity in shaping the subsequent illusory interpretation by investigating activity related to the illusory Gestalt not only during, but also prior to its perception. We presented 31 participants with a bistable motion stimulus, which can be perceived either as four moving dot pairs (local) or two moving illusory squares (global). fMRI was used to measure brain activity in a slow event-related design. We observed stronger IPS and putamen responses to the stimulus when participants perceived the global interpretation compared to the local, confirming the findings of previous studies. Most importantly, we also observed that the global stimulus interpretation was preceded by an increased activity of the bilateral dorsal insula, which is known to process saliency and gate information for conscious access. Our data suggest an important role of the dorsal insula in shaping complex illusory interpretations of the sensory input.

Improved cortical surface reconstruction using sub-millimeter resolution MPRAGE by image denoising

Automatic cerebral cortical surface reconstruction is a useful tool for cortical anatomy quantification, analysis and visualization. Recently, the Human Connectome Project and several studies have shown the advantages of using T₁-weighted magnetic resonance (MR) images with sub-millimeter isotropic spatial resolution instead of the standard 1-mm isotropic resolution for improved accuracy of cortical surface positioning and thickness estimation. Nonetheless, sub-millimeter resolution images are noisy by nature and require averaging multiple repetitions to increase the signal-to-noise ratio for precisely delineating the cortical boundary. The prolonged acquisition time and potential motion artifacts pose significant barriers to the wide adoption of cortical surface reconstruction at sub-millimeter resolution for a broad range of neuroscientific and clinical applications. We address this challenge by evaluating the cortical surface reconstruction resulting from denoised single-repetition sub-millimeter T₁-weighted images. We systematically characterized the effects of image denoising on empirical data acquired at 0.6 mm isotropic resolution using three classical denoising methods, including denoising convolutional neural network (DnCNN), block-matching and 4-dimensional filtering (BM4D) and adaptive optimized non-local means (AONLM). The denoised single-repetition images were found to be highly similar to 6-repetition averaged images, with a low whole-brain averaged mean absolute difference of ~0.016, high whole-brain averaged peak signal-to-noise ratio of ~33.5 dB and structural similarity index of ~0.92, and minimal gray matter–white matter contrast loss (2% to 9%). The whole-brain mean absolute discrepancies in gray matter–white matter surface placement, gray matter–cerebrospinal fluid surface placement and cortical thickness estimation were lower than 165 μm, 155 μm and 145 μm—sufficiently accurate for most applications. These discrepancies were approximately one third to half of those from 1-mm isotropic resolution data. The denoising performance was equivalent to averaging ~2.5 repetitions of the data in terms of image similarity, and 1.6–2.2 repetitions in terms of the cortical surface placement accuracy. The scan-rescan variability of the cortical surface positioning and thickness estimation was lower than 170 μm. Our unique dataset and systematic characterization support the use of denoising methods for improved cortical surface reconstruction at sub-millimeter resolution.

Improving in vivo human cerebral cortical surface reconstruction using data-driven super-resolution

Accurate and automated reconstruction of the in vivo human cerebral cortical surface from anatomical magnetic resonance (MR) images facilitates the quantitative analysis of cortical structure. Anatomical MR images with sub-millimeter isotropic spatial resolution improve the accuracy of cortical surface and thickness estimation compared to the standard 1-millimeter isotropic resolution. Nonetheless, sub-millimeter resolution acquisitions require averaging multiple repetitions to achieve sufficient signal-to-noise ratio and are therefore long and potentially vulnerable to subject motion. We address this challenge by synthesizing sub-millimeter resolution images from standard 1-millimeter isotropic resolution images using a data-driven supervised machine learning-based super-resolution approach achieved via a deep convolutional neural network. We systematically characterize our approach using a large-scale simulated dataset and demonstrate its efficacy in empirical data. The super-resolution data provide improved cortical surfaces similar to those obtained from native sub-millimeter resolution data. The whole-brain mean absolute discrepancy in cortical surface positioning and thickness estimation is below 100 μm at the single-subject level and below 50 μm at the group level for the simulated data, and below 200 μm at the single-subject level and below 100 μm at the group level for the empirical data, making the accuracy of cortical surfaces derived from super-resolution sufficient for most applications.

Analysis strategies for high-resolution UHF-fMRI data

Functional MRI (fMRI) benefits from both increased sensitivity and specificity with increasing magnetic field strength, making it a key application for Ultra-High Field (UHF) MRI scanners. Most UHF-fMRI studies utilize the dramatic increases in sensitivity and specificity to acquire high-resolution data reaching sub-millimeter scales, which enable new classes of experiments to probe the functional organization of the human brain. This review article surveys advanced data analysis strategies developed for high-resolution fMRI at UHF. These include strategies designed to mitigate distortion and artifacts associated with higher fields in ways that attempt to preserve spatial resolution of the fMRI data, as well as recently introduced analysis techniques that are enabled by these extremely high-resolution data. Particular focus is placed on anatomically-informed analyses, including cortical surface-based analysis, which are powerful techniques that can guide each step of the analysis from preprocessing to statistical analysis to interpretation and visualization. New intracortical analysis techniques for laminar and columnar fMRI are also reviewed and discussed. Prospects for single-subject individualized analyses are also presented and discussed. Altogether, there are both specific challenges and opportunities presented by UHF-fMRI, and the use of proper analysis strategies can help these valuable data reach their full potential.

Advantages of cortical surface reconstruction using submillimeter 7 T MEMPRAGE

Recent advances in MR technology have enabled increased spatial resolution for routine functional and anatomical imaging, which has created demand for software tools that are able to process these data. The availability of high-resolution data also raises the question of whether higher resolution leads to substantial gains in accuracy of quantitative morphometric neuroimaging procedures, in particular the cortical surface reconstruction and cortical thickness estimation. In this study we adapted the FreeSurfer cortical surface reconstruction pipeline to process structural data at native submillimeter resolution. We then quantified the differences in surface placement between meshes generated from (0.75 mm)³ isotropic resolution data acquired in 39 volunteers and the same data downsampled to the conventional 1 mm³ voxel size. We find that when processed at native resolution, cortex is estimated to be thinner in most areas, but thicker around the Cingulate and the Calcarine sulci as well as in the posterior bank of the Central sulcus. Thickness differences are driven by two kinds of effects. First, the gray-white surface is found closer to the white matter, especially in cortical areas with high myelin content, and thus low contrast, such as the Calcarine and the Central sulci, causing local increases in thickness estimates. Second, the gray-CSF surface is placed more interiorly, especially in the deep sulci, contributing to local decreases in thickness estimates. We suggest that both effects are due to reduced partial volume effects at higher spatial resolution. Submillimeter voxel sizes can therefore provide improved accuracy for measuring cortical thickness.

Disrupting parietal function prolongs dominance durations in binocular rivalry

Human brain imaging studies of bistable perceptual phenomena revealed that frontal and parietal areas are activated during perceptual switches between the two conflicting percepts. However, these studies do not provide information about causality, i.e., whether activity reports a consequence or a cause of the perceptual change. Here we used functional magnetic resonance imaging to individually localize four parietal regions involved in perceptual switches during binocular rivalry in 15 subjects and subsequently disturbed their neural processing and that of a control site using 2 Hz repetitive transcranial magnetic stimulation (TMS) during binocular rivalry. We found that TMS over one of the sites, the right intraparietal sulcus (IPS), prolonged the periods of stable percepts. Additionally, the more lateralized the blood oxygen level-dependent signal was in IPS, the more lateralized the TMS effects were. Lateralization varied considerably across subjects, with a right-hemispheric bias. Control replay experiments rule out nonspecific effects of TMS on task performance, reaction times, or eye blinks. Our results thus demonstrate a causal, destabilizing, and individually lateralized effect of normal IPS function on perceptual continuity in rivalry. This is in accord with a role of IPS in perceptual selection, relating its role in rivalrous perception to that in attention.