Correspondences between retinotopic areas and myelin maps in human visual cortex

Distributed network flows generate localized category selectivity in human visual cortex

A central goal of neuroscience is to understand how function-relevant brain activations are generated. Here we test the hypothesis that function-relevant brain activations are generated primarily by distributed network flows. We focused on visual processing in human cortex, given the long-standing literature supporting the functional relevance of brain activations in visual cortex regions exhibiting visual category selectivity. We began by using fMRI data from N = 352 human participants to identify category-specific responses in visual cortex for images of faces, places, body parts, and tools. We then systematically tested the hypothesis that distributed network flows can generate these localized visual category selective responses. This was accomplished using a recently developed approach for simulating - in a highly empirically constrained manner - the generation of task-evoked brain activations by modeling activity flowing over intrinsic brain connections. We next tested refinements to our hypothesis, focusing on how stimulus-driven network interactions initialized in V1 generate downstream visual category selectivity. We found evidence that network flows directly from V1 were sufficient for generating visual category selectivity, but that additional, globally distributed (whole-cortex) network flows increased category selectivity further. Using null network architectures we also found that each region's unique intrinsic "connectivity fingerprint" was key to the generation of category selectivity. These results generalized across regions associated with all four visual categories tested (bodies, faces, places, and tools), and provide evidence that the human brain's intrinsic network organization plays a prominent role in the generation of functionally relevant, localized responses.

Functional localization of visual motion area FST in humans

The fundus of the superior temporal sulcus (FST) in macaques is implicated in the processing of complex motion signals, yet a human homolog remains elusive. Here we considered potential localizers and evaluated their effectiveness in delineating putative FST (pFST), from hMT and MST, two nearby motion-sensitive areas in humans. Nine healthy participants underwent scanning sessions with 2D and 3D motion localizers, as well as population receptive field (pRF) mapping. We observed consistent anterior and inferior activation relative to hMT and MST in response to stimuli that contained coherent 3D, but not 2D, motion. Motion opponency and myelination measures further validated the functional and structural distinction between pFST and hMT/MST. At the same time, standard pRF mapping techniques that reveal the visual field organization of hMT/MST proved suboptimal for delineating pFST. Our findings provide a robust framework for localizing pFST in humans, and underscore its distinct functional role in motion processing.

Principles of cortical areas and their implications for neuroimaging

Cortical organization should constrain the study of how the brain performs behavior and cognition. A fundamental concept in cortical organization is that of arealization: that the cortex is parceled into discrete areas. In part one of this report, we review how non-human animal studies have illuminated principles of cortical arealization by revealing: (1) what defines a cortical area, (2) how cortical areas are formed, (3) how cortical areas interact with one another, and (4) what "computations" or "functions" areas perform. In part two, we discuss how these principles apply to neuroimaging research. In doing so, we highlight several examples where the commonly accepted interpretation of neuroimaging observations requires assumptions that violate the principles of arealization, including nonstationary areas that move on short time scales, large-scale gradients as organizing features, and cortical areas with singular functionality that perfectly map psychological constructs. Our belief is that principles of neurobiology should strongly guide the nature of computational explanations.

Orienting role of the putative human posterior infero-temporal area in visual attention

The dorsal attention network (DAN) is a network of brain regions essential for attentional orienting, which includes the lateral intraparietal area (LIP) and frontal eye field (FEF). Recently, the putative human dorsal posterior infero-temporal area (phPITd) has been identified as a new node of the DAN. However, its functional relationship with other areas of the DAN and its specific role in visual attention remained unclear. In this study, we analyzed a large publicly available neuroimaging dataset to investigate the intrinsic functional connectivities (FCs) of the phPITd with other brain areas. The results showed that the intrinsic FCs of the phPITd with the areas of the visual network and the DAN were significantly stronger than those with the ventral attention network (VAN) areas and areas of other networks. We further conducted individual difference analyses with a sample size of 295 participants and a series of attentional tasks to investigate which attentional components each phPITd-based DAN edge predicts. Our findings revealed that the intrinsic FC of the left phPITd with the LIPv could predict individual ability in attentional orienting, but not in alerting, executive control, and distractor suppression. Our results not only provide direct evidence of the phPITd's functional relationship with the LIPv, but also offer a comprehensive understanding of its specific role in visual attention.

Homotopic local-global parcellation of the human cerebral cortex from resting-state functional connectivity

Resting-state fMRI is commonly used to derive brain parcellations, which are widely used for dimensionality reduction and interpreting human neuroscience studies. We previously developed a model that integrates local and global approaches for estimating areal-level cortical parcellations. The resulting local-global parcellations are often referred to as the Schaefer parcellations. However, the lack of homotopic correspondence between left and right Schaefer parcels has limited their use for brain lateralization studies. Here, we extend our previous model to derive homotopic areal-level parcellations. Using resting-fMRI and task-fMRI across diverse scanners, acquisition protocols, preprocessing and demographics, we show that the resulting homotopic parcellations are as homogeneous as the Schaefer parcellations, while being more homogeneous than five publicly available parcellations. Furthermore, weaker correlations between homotopic parcels are associated with greater lateralization in resting network organization, as well as lateralization in language and motor task activation. Finally, the homotopic parcellations agree with the boundaries of a number of cortical areas estimated from histology and visuotopic fMRI, while capturing sub-areal (e.g., somatotopic and visuotopic) features. Overall, these results suggest that the homotopic local-global parcellations represent neurobiologically meaningful subdivisions of the human cerebral cortex and will be a useful resource for future studies. Multi-resolution parcellations estimated from 1479 participants are publicly available (https://github.com/ThomasYeoLab/CBIG/tree/master/stable_projects/brain_parcellation/Yan2023_homotopic).

Accurate localization and coactivation profiles of the frontal eye field and inferior frontal junction: an ALE and MACM fMRI meta-analysis

The frontal eye field (FEF) and the inferior frontal junction (IFJ) are prefrontal structures involved in mediating multiple aspects of goal-driven behavior. Despite being recognized as prominent nodes of the networks underlying spatial attention and oculomotor control, and working memory and cognitive control, respectively, the limited quantitative evidence on their precise localization has considerably impeded the detailed understanding of their structure and connectivity. In this study, we performed an activation likelihood estimation (ALE) fMRI meta-analysis by selecting studies that employed standard paradigms to accurately infer the localization of these regions in stereotaxic space. For the FEF, we found the highest spatial convergence of activations for prosaccade and antisaccade paradigms at the junction of the precentral sulcus and superior frontal sulcus. For the IFJ, we found consistent activations across oddball/attention, working memory, task-switching and Stroop paradigms at the junction of the inferior precentral sulcus and inferior frontal sulcus. We related these clusters to previous meta-analyses, sulcal/gyral neuroanatomy, and a comprehensive brain parcellation, highlighting important differences compared to their results and taxonomy. Finally, we leveraged the ALE peak coordinates as seeds to perform a meta-analytic connectivity modeling (MACM) analysis, which revealed systematic coactivation patterns spanning the frontal, parietal, and temporal cortices. We decoded the behavioral domains associated with these coactivations, suggesting that these may allow FEF and IFJ to support their specialized roles in flexible behavior. Our study provides the meta-analytic groundwork for investigating the relationship between functional specialization and connectivity of two crucial control structures of the prefrontal cortex.

Information transmission velocity-based dynamic hierarchical brain networks

The brain functions as an accurate circuit that regulates information to be sequentially propagated and processed in a hierarchical manner. However, it is still unknown how the brain is hierarchically organized and how information is dynamically propagated during high-level cognition. In this study, we developed a new scheme for quantifying the information transmission velocity (ITV) by combining electroencephalogram (EEG) and diffusion tensor imaging (DTI), and then mapped the cortical ITV network (ITVN) to explore the information transmission mechanism of the human brain. The application in MRI-EEG data of P300 revealed bottom-up and top-down ITVN interactions subserving P300 generation, which was comprised of four hierarchical modules. Among these four modules, information exchange between visual- and attention-activated regions occurred at a high velocity, related cognitive processes could thus be efficiently accomplished due to the heavy myelination of these regions. Moreover, inter-individual variability in P300 was probed to be attributed to the difference in information transmission efficiency of the brain, which may provide new insight into the cognitive degenerations in clinical neurodegenerative disorders, such as Alzheimer's disease, from the transmission velocity perspective. Together, these findings confirm the capacity of ITV to effectively determine the efficiency of information propagation in the brain.

Seeing and extrapolating motion trajectories share common informative activation patterns in primary visual cortex

The natural environment is dynamic and moving objects become constantly occluded, engaging the brain in a challenging completion process to estimate where and when the object might reappear. Although motion extrapolation is critical in daily life-imagine crossing the street while an approaching car is occluded by a larger standing vehicle-its neural underpinnings are still not well understood. While the engagement of low-level visual cortex during dynamic occlusion has been postulated, most of the previous group-level fMRI-studies failed to find evidence for an involvement of low-level visual areas during occlusion. In this fMRI-study, we therefore used individually defined retinotopic maps and multivariate pattern analysis to characterize the neural basis of visible and occluded changes in motion direction in humans. To this end, participants learned velocity-direction change pairings (slow motion-upwards; fast motion-downwards or vice versa) during a training phase without occlusion and judged the change in stimulus direction, based on its velocity, during a following test phase with occlusion. We find that occluded motion direction can be predicted from the activity patterns during visible motion within low-level visual areas, supporting the notion of a mental representation of motion trajectory in these regions during occlusion.

Multitask representations in the human cortex transform along a sensory-to-motor hierarchy

Human cognition recruits distributed neural processes, yet the organizing computational and functional architectures remain unclear. Here, we characterized the geometry and topography of multitask representations across the human cortex using functional magnetic resonance imaging during 26 cognitive tasks in the same individuals. We measured the representational similarity across tasks within a region and the alignment of representations between regions. Representational alignment varied in a graded manner along the sensory-association-motor axis. Multitask dimensionality exhibited compression then expansion along this gradient. To investigate computational principles of multitask representations, we trained multilayer neural network models to transform empirical visual-to-motor representations. Compression-then-expansion organization in models emerged exclusively in a rich training regime, which is associated with learning optimized representations that are robust to noise. This regime produces hierarchically structured representations similar to empirical cortical patterns. Together, these results reveal computational principles that organize multitask representations across the human cortex to support multitask cognition.

A Large Video Set of Natural Human Actions for Visual and Cognitive Neuroscience Studies and Its Validation with fMRI

The investigation of the perception of others' actions and underlying neural mechanisms has been hampered by the lack of a comprehensive stimulus set covering the human behavioral repertoire. To fill this void, we present a video set showing 100 human actions recorded in natural settings, covering the human repertoire except for emotion-driven (e.g., sexual) actions and those involving implements (e.g., tools). We validated the set using fMRI and showed that observation of the 100 actions activated the well-established action observation network. We also quantified the videos' low-level visual features (luminance, optic flow, and edges). Thus, this comprehensive video set is a valuable resource for perceptual and neuronal studies.

What has vision science taught us about functional MRI?

In the domain of human neuroimaging, much attention has been paid to the question of whether and how the development of functional magnetic resonance imaging (fMRI) has advanced our scientific knowledge of the human brain. However, the opposite question is also important; how has our knowledge of the brain advanced our understanding of fMRI? Here, we discuss how and why scientific knowledge about the human and animal visual system has been used to answer fundamental questions about fMRI as a brain measurement tool and how these answers have contributed to scientific discoveries beyond vision science.

Parcellating the human brain using resting-state dynamic functional connectivity

Brain cartography has expanded substantially over the past decade. In this regard, resting-state functional connectivity (FC) plays a key role in identifying the locations of putative functional borders. However, scant attention has been paid to the dynamic nature of functional interactions in the human brain. Indeed, FC is typically assumed to be stationary across time, which may obscure potential or subtle functional boundaries, particularly in regions with high flexibility and adaptability. In this study, we developed a dynamic FC (dFC)-based parcellation framework, established a new functional human brain atlas termed D-BFA (DFC-based Brain Functional Atlas), and verified its neurophysiological plausibility by stereo-EEG data. As the first dFC-based whole-brain atlas, the proposed D-BFA delineates finer functional boundaries that cannot be captured by static FC, and is further supported by good correspondence with cytoarchitectonic areas and task activation maps. Moreover, the D-BFA reveals the spatial distribution of dynamic variability across the brain and generates more homogenous parcels compared with most alternative parcellations. Our results demonstrate the superiority and practicability of dFC in brain parcellation, providing a new template to exploit brain topographic organization from a dynamic perspective. The D-BFA will be publicly available for download at https://github.com/sliderplm/D-BFA-618.

Cortical visual area CSv as a cingulate motor area: a sensorimotor interface for the control of locomotion

The response properties, connectivity and function of the cingulate sulcus visual area (CSv) are reviewed. Cortical area CSv has been identified in both human and macaque brains. It has similar response properties and connectivity in the two species. It is situated bilaterally in the cingulate sulcus close to an established group of medial motor/premotor areas. It has strong connectivity with these areas, particularly the cingulate motor areas and the supplementary motor area, suggesting that it is involved in motor control. CSv is active during visual stimulation but only if that stimulation is indicative of self-motion. It is also active during vestibular stimulation and connectivity data suggest that it receives proprioceptive input. Connectivity with topographically organized somatosensory and motor regions strongly emphasizes the legs over the arms. Together these properties suggest that CSv provides a key interface between the sensory and motor systems in the control of locomotion. It is likely that its role involves online control and adjustment of ongoing locomotory movements, including obstacle avoidance and maintaining the intended trajectory. It is proposed that CSv is best seen as part of the cingulate motor complex. In the human case, a modification of the influential scheme of Picard and Strick (Picard and Strick, Cereb Cortex 6:342-353, 1996) is proposed to reflect this.

Predicting the retinotopic organization of human visual cortex from anatomy using geometric deep learning

Whether it be in a single neuron or a more complex biological system like the human brain, form and function are often directly related. The functional organization of human visual cortex, for instance, is tightly coupled with the underlying anatomy with cortical shape having been shown to be a useful predictor of the retinotopic organization in early visual cortex. Although the current state-of-the-art in predicting retinotopic maps is able to account for gross individual differences, such models are unable to account for any idiosyncratic differences in the structure-function relationship from anatomical information alone due to their initial assumption of a template. Here we developed a geometric deep learning model capable of exploiting the actual structure of the cortex to learn the complex relationship between brain function and anatomy in human visual cortex such that more realistic and idiosyncratic maps could be predicted. We show that our neural network was not only able to predict the functional organization throughout the visual cortical hierarchy, but that it was also able to predict nuanced variations across individuals. Although we demonstrate its utility for modeling the relationship between structure and function in human visual cortex, our approach is flexible and well-suited for a range of other applications involving data structured in non-Euclidean spaces.

Interspecies activation correlations reveal functional correspondences between marmoset and human brain areas

The common marmoset has enormous promise as a nonhuman primate model of human brain functions. While resting-state functional MRI (fMRI) has provided evidence for a similar organization of marmoset and human cortices, the technique cannot be used to map the functional correspondences of brain regions between species. This limitation can be overcome by movie-driven fMRI (md-fMRI), which has become a popular tool for noninvasively mapping the neural patterns generated by rich and naturalistic stimulation. Here, we used md-fMRI in marmosets and humans to identify whole-brain functional correspondences between the two primate species. In particular, we describe functional correlates for the well-known human face, body, and scene patches in marmosets. We find that these networks have a similar organization in both species, suggesting a largely conserved organization of higher-order visual areas between New World marmoset monkeys and humans. However, while face patches in humans and marmosets were activated by marmoset faces, only human face patches responded to the faces of other animals. Together, the results demonstrate that higher-order visual processing might be a conserved feature between humans and New World marmoset monkeys but that small, potentially important functional differences exist.

Structure, function and connectivity fingerprints of the frontal eye field versus the inferior frontal junction: A comprehensive comparison

The human prefrontal cortex contains two prominent areas, the frontal eye field and the inferior frontal junction, that are crucially involved in the orchestrating functions of attention, working memory and cognitive control. Motivated by comparative evidence in non-human primates, we review the human neuroimaging literature, suggesting that the functions of these regions can be clearly dissociated. We found remarkable differences in how these regions relate to sensory domains and visual topography, top-down and bottom-up spatial attention, spatial versus non-spatial (i.e., feature- and object-based) attention and working memory and, finally, the multiple-demand system. Functional magnetic resonance imaging (fMRI) studies using multivariate pattern analysis reveal the selectivity of the frontal eye field and inferior frontal junction to spatial and non-spatial information, respectively. The analysis of functional and effective connectivity provides evidence of the modulation of the activity in downstream visual areas from the frontal eye field and inferior frontal junction and sheds light on their reciprocal influences. We therefore suggest that future studies should aim at disentangling more explicitly the role of these regions in the control of spatial and non-spatial selection. We propose that the analysis of the structural and functional connectivity (i.e., the connectivity fingerprints) of the frontal eye field and inferior frontal junction may be used to further characterize their involvement in a spatial ('where') and a non-spatial ('what') network, respectively, highlighting segregated brain networks that allow biasing visual selection and working memory performance to support goal-driven behaviour.

The unique role of parietal cortex in action observation: Functional organization for communicative and manipulative actions

Action observation is supported by a network of regions in occipito-temporal, parietal, and premotor cortex in primates. Recent research suggests that the parietal node has regions dedicated to different action classes including manipulation, interpersonal interactions, skin displacement, locomotion, and climbing. The goals of the current study consist of: 1) extending this work with new classes of actions that are communicative and specific to humans, 2) investigating how parietal cortex differs from the occipito-temporal and premotor cortex in representing action classes. Human subjects underwent fMRI scanning while observing three action classes: indirect communication, direct communication, and manipulation, plus two types of control stimuli, static controls which were static frames from the video clips, and dynamic controls consisting of temporally-scrambled optic flow information. Using univariate analysis, MVPA, and representational similarity analysis, our study presents several novel findings. First, we provide further evidence for the anatomical segregation in parietal cortex of different action classes: We have found a new site that is specific for representing human-specific indirect communicative actions in cytoarchitectonic parietal area PFt. Second, we found that the discriminability between action classes was higher in parietal cortex than the other two levels suggesting the coding of action identity information at this level. Finally, our results advocate the use of the control stimuli not just for univariate analysis of complex action videos but also when using multivariate techniques.

Optic flow selectivity in the macaque parieto-occipital sulcus

In humans, several neuroimaging studies have demonstrated that passive viewing of optic flow stimuli activates higher-level motion areas, like V6 and the cingulate sulcus visual area (CSv). In macaque, there are few studies on the sensitivity of V6 and CSv to egomotion compatible optic flow. The only fMRI study on this issue revealed selectivity to egomotion compatible optic flow in macaque CSv but not in V6 (Cotterau et al. Cereb Cortex 27(1):330-343, 2017, but see Fan et al. J Neurosci. 35:16303-16314, 2015). Yet, it is unknown whether monkey visual motion areas MT + and V6 display any distinctive fMRI functional profile relative to the optic flow stimulation, as it is the case for the homologous human areas (Pitzalis et al., Cereb Cortex 20(2):411-424, 2010). Here, we described the sensitivity of the monkey brain to two motion stimuli (radial rings and flow fields) originally used in humans to functionally map the motion middle temporal area MT + (Tootell et al. J Neurosci 15: 3215-3230, 1995a; Nature 375:139-141, 1995b) and the motion medial parietal area V6 (Pitzalis et al. 2010), respectively. In both animals, we found regions responding only to optic flow or radial rings stimulation, and regions responding to both stimuli. A region in the parieto-occipital sulcus (likely including V6) was one of the most highly selective area for coherently moving fields of dots, further demonstrating the power of this type of stimulation to activate V6 in both humans and monkeys. We did not find any evidence that putative macaque CSv responds to Flow Fields.

The visual white matter connecting human area prostriata and the thalamus is retinotopically organized

The human visual system is capable of processing visual information from fovea to the far peripheral visual field. Recent fMRI studies have shown a full and detailed retinotopic map in area prostriata, located ventro-dorsally and anterior to the calcarine sulcus along the parieto-occipital sulcus with strong preference for peripheral and wide-field stimulation. Here, we report the anatomical pattern of white matter connections between area prostriata and the thalamus encompassing the lateral geniculate nucleus (LGN). To this end, we developed and utilized an automated pipeline comprising a series of Apps that run openly on the cloud computing platform brainlife.io to analyse 139 subjects of the Human Connectome Project (HCP). We observe a continuous and extended bundle of white matter fibers from which two subcomponents can be extracted: one passing ventrally parallel to the optic radiations (OR) and another passing dorsally circumventing the lateral ventricle. Interestingly, the loop travelling dorsally connects the thalamus with the central visual field representation of prostriata located anteriorly, while the other loop travelling more ventrally connects the LGN with the more peripheral visual field representation located posteriorly. We then analyse an additional cohort of 10 HCP subjects using a manual plane extraction method outside brainlife.io to study the relationship between the two extracted white matter subcomponents and eccentricity, myelin and cortical thickness gradients within prostriata. Our results are consistent with a retinotopic segregation recently demonstrated in the OR, connecting the LGN and V1 in humans and reveal for the first time a retinotopic segregation regarding the trajectory of a fiber bundle between the thalamus and an associative visual area.

Functional Segregation of the Middle Temporal Visual Motion Area Revealed With Coactivation-Based Parcellation

Traditionally, the visual motion area (MT) is considered as a brain region specialized for visual motion perception. However, accumulating evidence showed that MT is also related to various functions, suggesting that it is a complex functional area and different functional subregions might exist in this area. To delineate functional subregions of this area, left and right masks of MT were defined using meta-analysis in the BrainMap database, and coactivation-based parcellation was then performed on these two masks. Two dorsal subregions (Cl1 and Cl2) and one ventral subregion (Cl3) of left MT, as well as two dorsal-anterior subregions (Cl1 and Cl2), one ventral-anterior subregion (Cl3), and an additional posterior subregion (Cl4) of right MT were identified. In addition to vision motion, distinct and specific functions were identified in different subregions characterized by task-dependent functional connectivity mapping and forward/reverse inference on associated functions. These results not only were in accordance with the previous findings of a hemispheric asymmetry of MT, but also strongly confirmed the existence of subregions in this region with distinct and specific functions. Furthermore, our results extend the special role of visual motion perception on this area and might facilitate future cognitive study.

Cross-species cortical alignment identifies different types of anatomical reorganization in the primate temporal lobe

Evolutionary adaptations of temporo-parietal cortex are considered to be a critical specialization of the human brain. Cortical adaptations, however, can affect different aspects of brain architecture, including local expansion of the cortical sheet or changes in connectivity between cortical areas. We distinguish different types of changes in brain architecture using a computational neuroanatomy approach. We investigate the extent to which between-species alignment, based on cortical myelin, can predict changes in connectivity patterns across macaque, chimpanzee, and human. We show that expansion and relocation of brain areas can predict terminations of several white matter tracts in temporo-parietal cortex, including the middle and superior longitudinal fasciculus, but not the arcuate fasciculus. This demonstrates that the arcuate fasciculus underwent additional evolutionary modifications affecting the temporal lobe connectivity pattern. This approach can flexibly be extended to include other features of cortical organization and other species, allowing direct tests of comparative hypotheses of brain organization.

Antipsychotic agent-induced deterioration of the visual system in first-episode untreated patients with schizophrenia maybe self-limited: Findings from a secondary small sample follow-up study based on a pilot follow-up study

Define changes in the visual cortex and retina in first-episode schizophrenia patients with visual disturbance (FUSCHVD) accompanied by antipsychotic agent treatment is important for guiding treatment. We examined the visual system prior to and after 3 years of antipsychotic-agent treatment in 48 patients with FUSCHVD and 50 healthy controls, and after 3.5 years of antipsychotic-agent treatment in 12 patients with FUSCHVD and 12 healthy subjects who came from the cohort with 3 years of follow up. Reduction of the visual cortex gray matter volume (GMV) was observed in patients compared to healthy controls, and impairments deteriorated accompanied with 3 years' treatment with antipsychotic agents. Total retinal thickness was also reduced in patients but did not deteriorated with treatment with antipsychotic agents. However, in the 12 patients who performed the additional 6-month follow-up, GMV and total retinal thickness reductions did not demonstrate any further trend in deterioration. These findings indicate that the reductions of GMV and retinal thickness may be self-limited. Although these findings were consistent with previous reports, it was only observed in a small number of patients. Therefore, clinicians should remain pay greater attention to visual system impairment in FUSCHVD.

Genetic influence is linked to cortical morphology in category-selective areas of visual cortex

Human visual cortex contains discrete areas that respond selectively to specific object categories such as faces, bodies, and places. A long-standing question is whether these areas are shaped by genetic or environmental factors. To address this question, here we analyzed functional MRI data from an unprecedented number (n = 424) of monozygotic (MZ) and dizygotic (DZ) twins. Category-selective maps were more identical in MZ than DZ twins. Within each category-selective area, distinct subregions showed significant genetic influence. Structural MRI analysis revealed that the ‘genetic voxels’ were predominantly located in regions with higher cortical curvature (gyral crowns in face areas and sulcal fundi in place areas). Moreover, we found that cortex was thicker and more myelinated in genetic voxels of face areas, while it was thinner and less myelinated in genetic voxels of place areas. This double dissociation suggests a differential development of face and place areas in cerebral cortex.

It remains unclear whether the functional organization of the visual cortex is shaped by genetic or environmental factors. Using fMRI in twins (n = 424), these authors show that activation patterns in category-selective areas are heritable, and that the genetic effects in these areas are linked to structural properties of cortical tissue.

White matter dissection and structural connectivity of the human vertical occipital fasciculus to link vision-associated brain cortex

The vertical occipital fasciculus (VOF) is an association fiber tract coursing vertically at the posterolateral corner of the brain. It is re-evaluated as a major fiber tract to link the dorsal and ventral visual stream. Although previous tractography studies showed the VOF’s cortical projections fall in the dorsal and ventral visual areas, the post-mortem dissection study for the validation remains limited. First, to validate the previous tractography data, we here performed the white matter dissection in post-mortem brains and demonstrated the VOF’s fiber bundles coursing between the V3A/B areas and the posterior fusiform gyrus. Secondly, we analyzed the VOF’s structural connectivity with diffusion tractography to link vision-associated cortical areas of the HCP MMP1.0 atlas, an updated map of the human cerebral cortex. Based on the criteria the VOF courses laterally to the inferior longitudinal fasciculus (ILF) and craniocaudally at the posterolateral corner of the brain, we reconstructed the VOF’s fiber tracts and found the widespread projections to the visual cortex. These findings could suggest a crucial role of VOF in integrating visual information to link the broad visual cortex as well as in connecting the dual visual stream.

To Watch is to Work: a Review of NeuroImaging Data on Tool Use Observation Network

Since the discovery of mirror neurons in the 1990s, many neuroimaging studies have tackled the issue of action observation with the aim of unravelling a putative homolog human system. However, these studies do not distinguish between non-tool-use versus tool-use actions, implying that a common brain network is systematically involved in the observation of any action. Here we provide evidence for a brain network dedicated to tool-use action observation, called the tool-use observation network, mostly situated in the left hemisphere, and distinct from the non-tool-use action observation network. Areas specific for tool-use action observation are the left cytoarchitectonic area PF within the left inferior parietal lobe and the left inferior frontal gyrus. The neural correlates associated with the observation of tool-use reported here offer new insights into the neurocognitive bases of action observation and tool use, as well as addressing more fundamental issues on the origins of specifically human phenomena such as cumulative technological evolution.

Organization of extrastriate and temporal cortex in chimpanzees compared to humans and macaques

There is evidence for enlargement of association cortex in humans compared to other primate species. Expansion of temporal association cortex appears to have displaced extrastriate cortex posteriorly and inferiorly in humans compared to macaques. However, the details of the organization of these recently expanded areas are still being uncovered. Here, we used diffusion tractography to examine the organization of extrastriate and temporal association cortex in chimpanzees, humans, and macaques. Our goal was to characterize the organization of visual and auditory association areas with respect to their corresponding primary areas (primary visual cortex and auditory core) in humans and chimpanzees. We report three results: (1) Humans, chimpanzees, and macaques show expected retinotopic organization of primary visual cortex (V1) connectivity to V2 and to areas immediately anterior to V2; (2) In contrast to macaques, chimpanzee and human V1 shows apparent connectivity with lateral, inferior, and anterior temporal regions, beyond the retinotopically organized extrastriate areas; (3) Also in contrast to macaques, chimpanzee and human auditory core shows apparent connectivity with temporal association areas, with some important differences between humans and chimpanzees. Diffusion tractography reconstructs diffusion patterns that reflect white matter organization, but does not definitively represent direct anatomical connectivity. Therefore, it is important to recognize that our findings are suggestive of species differences in long-distance white matter organization rather than demonstrations of direct connections. Our data support the conclusion that expansion of temporal association cortex, and the resulting posterior displacement of extrastriate cortex, occurred in the human lineage after its separation from the chimpanzee lineage. It is possible, however, that some expansion of the temporal lobe occurred prior to the separation of humans and chimpanzees, reflected in the reorganization of long white matter tracts in the temporal lobe that connect occipital areas to the fusiform gyrus, middle temporal gyrus, and anterior temporal lobe.

Functional neuroanatomy of blindsight revealed by activation likelihood estimation meta-analysis

Blindsight, the residual abilities of patients with cortical blindness to respond proficiently to stimuli they do not consciously acknowledge, offers a unique opportunity to study the functional and anatomical mechanisms sustaining visual awareness. Over decades, the phenomenon has been documented in a wide number of different patients, across independent laboratories, and for a variety of tasks and stimulus properties. Nevertheless, the functional neuroanatomy of blindsight remains elusive and alternative proposals have been put forth. To tackle this issue from a novel perspective, we performed a quantitative Activation Likelihood Estimation (ALE) meta-analysis on the neuroimaging literature available on blindsight. Significant activity was reported in subcortical structures, such as the superior colliculus, pulvinar and amygdala, as well as in cortical extrastriate areas along the dorsal and ventral visual stream. This data-driven functional network collectively defines the extant neural fingerprint of blindsight. To further characterize the unique combination of segregation and integration in brain networks engaged in blindsight, we measured the relationship between active areas and experimental features in the original studies, their clustering and hierarchical organization. Results support a network-based organization in the functional neuroanatomy of blindsight, which likely reflects the intersection of different stimulus properties and behavioural tasks examined. We suggest that the conceptualization of blindsight as a constellation of multiple nonconscious visual abilities is better apt as a summary of present-day wisdom, thereby mirroring the variety of existing V1-independent pathway and their different functional roles.

The Human Connectome Project 7 Tesla retinotopy dataset: Description and population receptive field analysis

About a quarter of human cerebral cortex is dedicated mainly to visual processing. The large-scale spatial organization of visual cortex can be measured with functional magnetic resonance imaging (fMRI) while subjects view spatially modulated visual stimuli, also known as "retinotopic mapping." One of the datasets collected by the Human Connectome Project involved ultrahigh-field (7 Tesla) fMRI retinotopic mapping in 181 healthy young adults (1.6-mm resolution), yielding the largest freely available collection of retinotopy data. Here, we describe the experimental paradigm and the results of model-based analysis of the fMRI data. These results provide estimates of population receptive field position and size. Our analyses include both results from individual subjects as well as results obtained by averaging fMRI time series across subjects at each cortical and subcortical location and then fitting models. Both the group-average and individual-subject results reveal robust signals across much of the brain, including occipital, temporal, parietal, and frontal cortex as well as subcortical areas. The group-average results agree well with previously published parcellations of visual areas. In addition, split-half analyses show strong within-subject reliability, further demonstrating the high quality of the data. We make publicly available the analysis results for individual subjects and the group average, as well as associated stimuli and analysis code. These resources provide an opportunity for studying fine-scale individual variability in cortical and subcortical organization and the properties of high-resolution fMRI. In addition, they provide a set of observations that can be compared with other Human Connectome Project measures acquired in these same participants.

The role of putative human anterior intraparietal sulcus area in observed manipulative action discrimination

INTRODUCTION

Although it has become widely accepted that the action observation network (AON) includes three levels (occipito-temporal, parietal and premotor), little is known concerning the specific role of these levels within perceptual tasks probing action observation. Recent single cell studies suggest that the parietal level carries the information required to discriminate between two-alternative observed actions, but do not exclude possible contributions from the other two levels.

METHODS

Two functional magnetic resonance imaging experiments used a task-based attentional modulation paradigm in which subjects viewed videos of an actor performing a manipulative action on a coloured object, and discriminated between either two observed manipulative actions, two actors or two colours.

RESULTS

Both experiments demonstrated that relative to actor and colour discrimination, discrimination between observed manipulative actions involved the putative human anterior intraparietal sulcus (phAIP) area in parietal cortex. In one experiment, where the observed actions also differed with regard to effectors, premotor cortex was also specifically recruited.

CONCLUSIONS

Our results highlight the primary role of parietal cortex in discriminating between two-alternative observed manipulative actions, consistent with the view that this level plays a major role in representing the identity of an observed action.

Disparity level identification using the voxel-wise Gabor model of fMRI data

Perceiving disparities is the intuitive basis for our understanding of the physical world. Although many electrophysiology studies have revealed the disparity-tuning characteristics of the neurons in the visual areas of the macaque brain, neuron population responses to disparity processing have seldom been investigated. Many disparity studies using functional magnetic resonance imaging (fMRI) have revealed the disparity-selective visual areas in the human brain. However, it is unclear how to characterize neuron population disparity-tuning responses using fMRI technique. In the present study, we constructed three voxel-wise encoding Gabor models to predict the voxel responses to novel disparity levels and used a decoding method to identify the new disparity levels from population responses in the cortex. Among the three encoding models, the fine-coarse model (FCM) that used fine/coarse disparities to fit the voxel responses to disparities outperformed the single model and uncrossed-crossed model. Moreover, the FCM demonstrated high accuracy in predicting voxel responses in V3A complex and high accuracy in identifying novel disparities from responses in V3A complex. Our results suggest that the FCM can better characterize the voxel responses to disparities than the other two models and V3A complex is a critical visual area for representing disparity information.

Rapid and specific processing of person-related information in human anterior temporal lobe

The anterior temporal lobe (ATL), located at the tip of the human temporal lobes, has been heavily implicated in semantic processing by neuropsychological and functional imaging studies. These techniques have revealed a hemispheric specialization of ATL, but little about the time scale on which it operates. Here we show that ATL is specifically activated in intracerebral recordings when subjects discriminate the gender of an actor presented in a static frame followed by a video. ATL recording sites respond briefly (100 ms duration) to the visual static presentation of an actor in a task-, but not in a stimulus-duration-dependent way. Their response latencies correlate with subjects' reaction times, as do their activity levels, but oppositely in the two hemispheres operating in a push-pull fashion. Comparison of ATL time courses with those of more posterior, less specific regions emphasizes the role of inhibitory operations sculpting the fast ATL responses underlying semantic processing.

Neural Encoding and Decoding with Deep Learning for Dynamic Natural Vision

Convolutional neural network (CNN) driven by image recognition has been shown to be able to explain cortical responses to static pictures at ventral-stream areas. Here, we further showed that such CNN could reliably predict and decode functional magnetic resonance imaging data from humans watching natural movies, despite its lack of any mechanism to account for temporal dynamics or feedback processing. Using separate data, encoding and decoding models were developed and evaluated for describing the bi-directional relationships between the CNN and the brain. Through the encoding models, the CNN-predicted areas covered not only the ventral stream, but also the dorsal stream, albeit to a lesser degree; single-voxel response was visualized as the specific pixel pattern that drove the response, revealing the distinct representation of individual cortical location; cortical activation was synthesized from natural images with high-throughput to map category representation, contrast, and selectivity. Through the decoding models, fMRI signals were directly decoded to estimate the feature representations in both visual and semantic spaces, for direct visual reconstruction and semantic categorization, respectively. These results corroborate, generalize, and extend previous findings, and highlight the value of using deep learning, as an all-in-one model of the visual cortex, to understand and decode natural vision.

Human Scene-Selective Areas Represent 3D Configurations of Surfaces

It has been argued that scene-selective areas in the human brain represent both the 3D structure of the local visual environment and low-level 2D features (such as spatial frequency) that provide cues for 3D structure. To evaluate the degree to which each of these hypotheses explains variance in scene-selective areas, we develop an encoding model of 3D scene structure and test it against a model of low-level 2D features. We fit the models to fMRI data recorded while subjects viewed visual scenes. The fit models reveal that scene-selective areas represent the distance to and orientation of large surfaces, at least partly independent of low-level features. Principal component analysis of the model weights reveals that the most important dimensions of 3D structure are distance and openness. Finally, reconstructions of the stimuli based on the model weights demonstrate that our model captures unprecedented detail about the local visual environment from scene-selective areas.

Fiber length profiling: A novel approach to structural brain organization

There has been a recent increased interest in the structural connectivity of the cortex. However, an important feature of connectivity remains relatively unexplored; tract length. In this article, we develop an approach to characterize fiber length distributions across the human cerebral cortex. We used data from 76 participants of the Adult WU-Minn Human Connectome Project using probabilistic tractography. We found that connections of different lengths are not evenly distributed across the cortex. They form patterns where certain areas have a high density of fibers of a specific length while other areas have very low density. To assess the relevance of these new maps in relation to established characteristics, we compared them to structural indices such as cortical myelin content and cortical thickness. Additionally, we assessed their relation to resting state network organization. We noted that areas with very short fibers have relatively more myelin and lower cortical thickness while the pattern is inverted for longer fibers. Furthermore, the cortical fiber length distributions produce specific correlation patterns with functional resting state networks. Specifically, we find evidence that as resting state networks increase in complexity, their length profiles change. The functionally more complex networks correlate with maps of varying lengths while primary networks have more restricted correlations. We posit that these maps are a novel way of differentiating between 'local modules' that have restricted connections to 'neighboring' areas and 'functional integrators' that have more far reaching connectivity.

Local-Global Parcellation of the Human Cerebral Cortex from Intrinsic Functional Connectivity MRI

A central goal in systems neuroscience is the parcellation of the cerebral cortex into discrete neurobiological "atoms". Resting-state functional magnetic resonance imaging (rs-fMRI) offers the possibility of in vivo human cortical parcellation. Almost all previous parcellations relied on 1 of 2 approaches. The local gradient approach detects abrupt transitions in functional connectivity patterns. These transitions potentially reflect cortical areal boundaries defined by histology or visuotopic fMRI. By contrast, the global similarity approach clusters similar functional connectivity patterns regardless of spatial proximity, resulting in parcels with homogeneous (similar) rs-fMRI signals. Here, we propose a gradient-weighted Markov Random Field (gwMRF) model integrating local gradient and global similarity approaches. Using task-fMRI and rs-fMRI across diverse acquisition protocols, we found gwMRF parcellations to be more homogeneous than 4 previously published parcellations. Furthermore, gwMRF parcellations agreed with the boundaries of certain cortical areas defined using histology and visuotopic fMRI. Some parcels captured subareal (somatotopic and visuotopic) features that likely reflect distinct computational units within known cortical areas. These results suggest that gwMRF parcellations reveal neurobiologically meaningful features of brain organization and are potentially useful for future applications requiring dimensionality reduction of voxel-wise fMRI data. Multiresolution parcellations generated from 1489 participants are publicly available (https://github.com/ThomasYeoLab/CBIG/tree/master/stable_projects/brain_parcellation/Schaefer2018_LocalGlobal).

Parcellating Cerebral Cortex: How Invasive Animal Studies Inform Noninvasive Mapmaking in Humans

The cerebral cortex in mammals contains a mosaic of cortical areas that differ in function, architecture, connectivity, and/or topographic organization. A combination of local connectivity (within-area microcircuitry) and long-distance (between-area) connectivity enables each area to perform a unique set of computations. Some areas also have characteristic within-area mesoscale organization, reflecting specialized representations of distinct types of information. Cortical areas interact with one another to form functional networks that mediate behavior, and each area may be a part of multiple, partially overlapping networks. Given their importance to the understanding of brain organization, mapping cortical areas across species is a major objective of systems neuroscience and has been a century-long challenge. Here, we review recent progress in multi-modal mapping of mouse and nonhuman primate cortex, mainly using invasive experimental methods. These studies also provide a neuroanatomical foundation for mapping human cerebral cortex using noninvasive neuroimaging, including a new map of human cortical areas that we generated using a semiautomated analysis of high-quality, multimodal neuroimaging data. We contrast our semiautomated approach to human multimodal cortical mapping with various extant fully automated human brain parcellations that are based on only a single imaging modality and offer suggestions on how to best advance the noninvasive brain parcellation field. We discuss the limitations as well as the strengths of current noninvasive methods of mapping brain function, architecture, connectivity, and topography and of current approaches to mapping the brain's functional networks.

Construction of a neonatal cortical surface atlas using Multimodal Surface Matching in the Developing Human Connectome Project

We propose a method for constructing a spatio-temporal cortical surface atlas of neonatal brains aged between 36 and 44 weeks of post-menstrual age (PMA) at the time of scan. The data were acquired as part of the Developing Human Connectome Project (dHCP), and the constructed surface atlases are publicly available. The method is based on a spherical registration approach: Multimodal Surface Matching (MSM), using cortical folding for driving the alignment. Templates have been generated for the anatomical cortical surface and for the cortical feature maps: sulcal depth, curvature, thickness, T1w/T2w myelin maps and cortical regions. To achieve this, cortical surfaces from 270 infants were first projected onto the sphere. Templates were then generated in two stages: first, a reference space was initialised via affine alignment to a group average adult template. Following this, templates were iteratively refined through repeated alignment of individuals to the template space until the variability of the average feature sets converged. Finally, bias towards the adult reference was removed by applying the inverse of the average affine transformations on the template and de-drifting the template. We used temporal adaptive kernel regression to produce age-dependant atlases for 9 weeks (36-44 weeks PMA). The generated templates capture expected patterns of cortical development including an increase in gyrification as well as an increase in thickness and T1w/T2w myelination with increasing age.

A cross-validated cytoarchitectonic atlas of the human ventral visual stream

The human ventral visual stream consists of several areas that are considered processing stages essential for perception and recognition. A fundamental microanatomical feature differentiating areas is cytoarchitecture, which refers to the distribution, size, and density of cells across cortical layers. Because cytoarchitectonic structure is measured in 20-micron-thick histological slices of postmortem tissue, it is difficult to assess (a) how anatomically consistent these areas are across brains and (b) how they relate to brain parcellations obtained with prevalent neuroimaging methods, acquired at the millimeter and centimeter scale. Therefore, the goal of this study was to (a) generate a cross-validated cytoarchitectonic atlas of the human ventral visual stream on a whole brain template that is commonly used in neuroimaging studies and (b) to compare this atlas to a recently published retinotopic parcellation of visual cortex (Wang et al., 2014). To achieve this goal, we generated an atlas of eight cytoarchitectonic areas: four areas in the occipital lobe (hOc1-hOc4v) and four in the fusiform gyrus (FG1-FG4), then we tested how the different alignment techniques affect the accuracy of the resulting atlas. Results show that both cortex-based alignment (CBA) and nonlinear volumetric alignment (NVA) generate an atlas with better cross-validation performance than affine volumetric alignment (AVA). Additionally, CBA outperformed NVA in 6/8 of the cytoarchitectonic areas. Finally, the comparison of the cytoarchitectonic atlas to a retinotopic atlas shows a clear correspondence between cytoarchitectonic and retinotopic areas in the ventral visual stream. The successful performance of CBA suggests a coupling between cytoarchitectonic areas and macroanatomical landmarks in the human ventral visual stream, and furthermore, that this coupling can be utilized for generating an accurate group atlas. In addition, the coupling between cytoarchitecture and retinotopy highlights the potential use of this atlas in understanding how anatomical features contribute to brain function. We make this cytoarchitectonic atlas freely available in both BrainVoyager and FreeSurfer formats (http://vpnl.stanford.edu/vcAtlas). The availability of this atlas will enable future studies to link cytoarchitectonic organization to other parcellations of the human ventral visual stream with potential to advance the understanding of this pathway in typical and atypical populations.

Multiple time courses of somatosensory responses in human cortex

Here we show how anatomical and functional data recorded from patients undergoing stereo-EEG can be used to decompose the cortical processing following nerve stimulation in different stages characterized by specific topography and time course. Tibial, median and trigeminal nerves were stimulated in 96 patients, and the increase in gamma power was evaluated over 11878 cortical sites. All three nerve datasets exhibited similar clusters of time courses: phasic, delayed/prolonged and tonic, which differed in topography, temporal organization and degree of spatial overlap. Strong phasic responses of the three nerves followed the classical somatotopic organization of SI, with no overlap in either time or space. Delayed responses presented overlaps between pairs of body parts in both time and space, and were confined to the dorsal motor cortices. Finally, tonic responses occurred in the perisylvian region including posterior insular cortex and were evoked by the stimulation of all three nerves, lacking any spatial and temporal specificity. These data indicate that the somatosensory processing following nerve stimulation is a multi-stage hierarchical process common to all three nerves, with the different stages likely subserving different functions. While phasic responses represent the neural basis of tactile perception, multi-nerve tonic responses may represent the neural signature of processes sustaining the capacity to become aware of tactile stimuli.

Detailed T1-Weighted Profiles from the Human Cortex Measured in Vivo at 3 Tesla MRI

Studies into cortical thickness in psychiatric diseases based on T1-weighted MRI frequently report on aberrations in the cerebral cortex. Due to limitations in image resolution for studies conducted at conventional MRI field strengths (e.g. 3 Tesla (T)) this information cannot be used to establish which of the cortical layers may be implicated. Here we propose a new analysis method that computes one high-resolution average cortical profile per brain region extracting myeloarchitectural information from T1-weighted MRI scans that are routinely acquired at a conventional field strength. To assess this new method, we acquired standard T1-weighted scans at 3 T and compared them with state-of-the-art ultra-high resolution T1-weighted scans optimised for intracortical myelin contrast acquired at 7 T. Average cortical profiles were computed for seven different brain regions. Besides a qualitative comparison between the 3 T scans, 7 T scans, and results from literature, we tested if the results from dynamic time warping-based clustering are similar for the cortical profiles computed from 7 T and 3 T data. In addition, we quantitatively compared cortical profiles computed for V1, V2 and V7 for both 7 T and 3 T data using a priori information on their relative myelin concentration. Although qualitative comparisons show that at an individual level average profiles computed for 7 T have more pronounced features than 3 T profiles the results from the quantitative analyses suggest that average cortical profiles computed from T1-weighted scans acquired at 3 T indeed contain myeloarchitectural information similar to profiles computed from the scans acquired at 7 T. The proposed method therefore provides a step forward to study cortical myeloarchitecture in vivo at conventional magnetic field strength both in health and disease.

Changes in structural network are associated with cortical demyelination in early multiple sclerosis

The aim of this study was to investigate the interplay between structural connectivity and cortical demyelination in early multiple sclerosis. About 27 multiple sclerosis patients and 18 age-matched controls underwent two MRI scanning sessions. The first was done at 7T and involved acquiring quantitative T₁ and T₂ * high-resolution maps to estimate cortical myelination. The second was done on a Connectom scanner and consisted of acquiring high angular resolution diffusion-weighted images to compute white matter structural connectivity metrics: strength, clustering and local efficiency. To further investigate the interplay between structural connectivity and cortical demyelination, patients were divided into four groups according to disease-duration: 0-1 year, 1-2 years, 2-3 years, and >3 years. ANOVA and Spearman's correlations were used to highlight relations between metrics. ANOVA detected a significant effect between disease duration and both cortical myelin (p = 2 × 10^-8 ) and connectivity metrics (p < 10^-4 ). We observed significant cortical myelin loss in the shorter disease-duration cohorts (0-1 year, p = .0015), and an increase in connectivity in the longer disease-duration cohort (2-3 years, strength: p = .01, local efficiency: p = .002, clustering: p = .001). Moreover, significant covariations between myelin estimation and white matter connectivity metrics were observed: Spearman's Rho correlation coefficients of 0.52 (p = .0003), 0.55 (p = .0001), and 0.53 (p = .0001) for strength, local efficiency, and clustering, respectively. An association between cortical myelin loss and changes in white matter connectivity in early multiple sclerosis was detected. These changes in network organization might be the result of compensatory mechanisms in response to the ongoing cortical diffuse damage in the early stages of multiple sclerosis.

Two New Cytoarchitectonic Areas on the Human Mid-Fusiform Gyrus

Areas of the fusiform gyrus (FG) within human ventral temporal cortex (VTC) process high-level visual information associated with faces, limbs, words, and places. Since classical cytoarchitectonic maps do not adequately reflect the functional and structural heterogeneity of the VTC, we studied the cytoarchitectonic segregation in a region, which is rostral to the recently identified cytoarchitectonic areas FG1 and FG2. Using an observer-independent and statistically testable parcellation method, we identify 2 new areas, FG3 and FG4, in 10 human postmortem brains on the mid-FG. The mid-fusiform sulcus reliably identifies the cytoarchitectonic transition between FG3 and FG4. We registered these cytoarchitectonic areas to the common reference space of the single-subject Montreal Neurological Institute (MNI) template and generated probability maps, which reflect the intersubject variability of both areas. Future studies can relate in vivo neuroimaging data with these microscopically defined cortical areas to functional parcellations. We discuss these results in the context of both large-scale functional maps and fine-scale functional clusters that have been identified within the human VTC. We propose that our observer-independent cytoarchitectonic parcellation of the FG better explains the functional heterogeneity of the FG compared with the homogeneity of classic cytoarchitectonic maps.

Dynamic Network Communication in the Human Functional Connectome Predicts Perceptual Variability in Visual Illusion

Ubiquitous variability between individuals in visual perception is difficult to standardize and has thus essentially been ignored. Here we construct a quantitative psychophysical measure of illusory rotary motion based on the Pinna-Brelstaff figure (PBF) in 73 healthy volunteers and investigate the neural circuit mechanisms underlying perceptual variation using functional magnetic resonance imaging (fMRI). We acquired fMRI data from a subset of 42 subjects during spontaneous and 3 stimulus conditions: expanding PBF, expanding modified-PBF (illusion-free) and expanding modified-PBF with physical rotation. Brain-wide graph analysis of stimulus-evoked functional connectivity patterns yielded a functionally segregated architecture containing 3 discrete hierarchical networks, commonly shared between rest and stimulation conditions. Strikingly, communication efficiency and strength between 2 networks predominantly located in visual areas robustly predicted individual perceptual differences solely in the illusory stimulus condition. These unprecedented findings demonstrate that stimulus-dependent, not spontaneous, dynamic functional integration between distributed brain networks contributes to perceptual variability in humans.

Cortical representation of different taste modalities on the gustatory cortex: A pilot study

Background

Right insular cortex is involved in taste discrimination, but its functional organization is still poorly known. In general, sensory cortices represent the spatial prevalence of relevant features for each sensory modality (visual, auditory, somatosensory) in an ordered way across the cortical space. Following this analogy, we hypothesized that primary taste cortex is organized in similar ordered way in response to six tastes with known receptorial mechanisms (sweet, bitter, sour, salt, umami, CO₂)_.

Design

Ten normal subjects were enrolled in a pilot study. We used functional magnetic resonance imaging (fMRI), a high resolution cortical registration method, and specialized procedures of feature prevalence localization, to map fMRI responses within the right insular cortex, to water solutions of quinine hydrochloride (bitter), Acesulfamate K (sweet), sodium chloride (salt), mono potassium glutamate + inosine 5' mono phosphate (Umami), citric acid (sour) and carbonated water (CO₂). During an fMRI scan delivery of the solutions was applied in pseudo-random order interleaved with cleaning water.

Results

Two subjects were discarded due to excessive head movements. In the remaining subjects, statistically significant activations were detected in the fMRI responses to all tastes in the right insular cortex (p<0.05, family-wise corrected for multiple comparisons). Cortical representation of taste prevalence highlighted two spatially segregated clusters, processing two and three tastes coupled together (sweet-bitter and salt-umami-sour), with CO₂ in between.

Conclusions

Cortical representation of taste prevalence within the right primary taste cortex appears to follow the ecological purpose of enhancing the discrimination between safe nutrients and harmful substances.

Quantitative MRI provides markers of intra-, inter-regional, and age-related differences in young adult cortical microstructure

Measuring the structural composition of the cortex is critical to understanding typical development, yet few investigations in humans have charted markers in vivo that are sensitive to tissue microstructural attributes. Here, we used a well-validated quantitative MR protocol to measure four parameters (R₁, MT, R₂*, PD*) that differ in their sensitivity to facets of the tissue microstructural environment (R₁, MT: myelin, macromolecular content; R₂*: myelin, paramagnetic ions, i.e., iron; PD*: free water content). Mapping these parameters across cortical regions in a young adult cohort (18–39 years, N = 93) revealed expected patterns of increased macromolecular content as well as reduced tissue water content in primary and primary adjacent cortical regions. Mapping across cortical depth within regions showed decreased expression of myelin and related processes – but increased tissue water content – when progressing from the grey/white to the grey/pial boundary, in all regions. Charting developmental change in cortical microstructure cross-sectionally, we found that parameters with sensitivity to tissue myelin (R₁ & MT) showed linear increases with age across frontal and parietal cortex (change 0.5–1.0% per year). Overlap of robust age effects for both parameters emerged in left inferior frontal, right parietal and bilateral pre-central regions. Our findings afford an improved understanding of ontogeny in early adulthood and offer normative quantitative MR data for inter- and intra-cortical composition, which may be used as benchmarks in further studies.

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We mapped multi-parameter maps (MPMs) across and within cortical regions.

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We charted age effects (ages 18–39) on myelin and related processes.

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MPMs sensitive to myelin (R₁, MT) showed elevated values in primary areas over most cortical depths.

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R₂* map foci tended to overlap MPMs sensitive to myelin (R₁, MT).

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R₁ and MT increased with age (0.5–1.0% per year) at mid-depth in frontal and parietal cortex.

Multimodal surface matching with higher-order smoothness constraints

In brain imaging, accurate alignment of cortical surfaces is fundamental to the statistical sensitivity and spatial localisation of group studies, and cortical surface-based alignment has generally been accepted to be superior to volume-based approaches at aligning cortical areas. However, human subjects have considerable variation in cortical folding, and in the location of functional areas relative to these folds. This makes alignment of cortical areas a challenging problem. The Multimodal Surface Matching (MSM) tool is a flexible, spherical registration approach that enables accurate registration of surfaces based on a variety of different features. Using MSM, we have previously shown that driving cross-subject surface alignment, using areal features, such as resting state-networks and myelin maps, improves group task fMRI statistics and map sharpness. However, the initial implementation of MSM's regularisation function did not penalize all forms of surface distortion evenly. In some cases, this allowed peak distortions to exceed neurobiologically plausible limits, unless regularisation strength was increased to a level which prevented the algorithm from fully maximizing surface alignment. Here we propose and implement a new regularisation penalty, derived from physically relevant equations of strain (deformation) energy, and demonstrate that its use leads to improved and more robust alignment of multimodal imaging data. In addition, since spherical warps incorporate projection distortions that are unavoidable when mapping from a convoluted cortical surface to the sphere, we also propose constraints that enforce smooth deformation of cortical anatomies. We test the impact of this approach for longitudinal modelling of cortical development for neonates (born between 31 and 43 weeks of post-menstrual age) and demonstrate that the proposed method increases the biological interpretability of the distortion fields and improves the statistical significance of population-based analysis relative to other spherical methods.