Associative white matter connecting the dorsal and ventral posterior human cortex

Midlife dynamics of white matter architecture in lexical production

We aimed to examine the white matter changes associated with lexical production difficulties, beginning in midlife with increased naming latencies. To delay lexical production decline, middle-aged adults may rely on domain-general and language-specific compensatory mechanisms proposed by the LARA model (Lexical Access and Retrieval in Aging). However, the white matter changes supporting these mechanisms remains largely unknown. Using data from the CAMCAN cohort, we employed an unsupervised and data-driven methodology to examine the relationships between diffusion-weighted imaging and lexical production. Our findings indicate that midlife is marked by alterations in brain structure within distributed dorsal, ventral, and anterior cortico-subcortical networks, marking the onset of lexical production decline around ages 53-54. Middle-aged adults may initially adopt a "semantic strategy" to compensate for lexical production challenges, but this strategy seems compromised later (ages 55-60) as semantic control declines. These insights underscore the interplay between domain-general and language-specific processes in the trajectory of lexical production performance in healthy aging and hint at potential biomarkers for language-related neurodegenerative pathologies.

Processing demands modulate the activities and functional connectivity patterns of the posterior (VWFA-1) and anterior (VWFA-2) VWFA

Previous studies have shown that the visual word form area (VWFA) has structural and intrinsic functional connectivity with both language and attention networks. Nevertheless, it is still unclear how the functional connectivity pattern of the VWFA is regulated by processing demands induced by experimental tasks, and whether processing demands differentially regulate the posterior (VWFA-1) and anterior (VWFA-2) subregions of the VWFA. To address these questions, the present study adopted two tasks varying in processing demands (i.e., verbal and non-verbal tasks), and used generalized psychophysiological interaction (gPPI) and dynamic causal modeling (DCM) analyses to explore the task-dependent functional connectivity patterns of the two subregions of the VWFA. Activation analysis revealed that the VWFA-2 showed higher activation for the verbal task than the non-verbal task, while there were no activation differences in the VWFA-1 after controlling for the stimulus driven effects. Functional and effective connectivity analyses revealed that, for both VWFA-1 and VWFA-2, the verbal task enhanced connections from VWFAs to the ventral language regions (e.g., the left orbital frontal cortex), while the non-verbal task enhanced connections from VWFAs to the dorsal visuospatial regions (e.g., the left intraparietal sulcus). Results of the present study indicate that processing demands induced by tasks modulate both the local activity and functional connectivity patterns of the VWFA, providing new insights for understanding its domain-general function.

What Is a Visual Stream?

The dual stream model of the human and non-human primate visual systems remains Leslie Ungerleider's (1946-2020) most indelible contribution to visual neuroscience. In this model, a dorsal "where" stream specialized for visuospatial representation extends through occipitoparietal cortex, whereas a ventral "what" stream specialized for representing object qualities extends through occipitotemporal cortex. Over time, this model underwent a number of revisions and expansions. In one of her last scientific contributions, Leslie proposed a third visual stream specialized for representing dynamic signals related to social perception. This alteration invites the question: What is a visual stream, and how are different visual streams individuated? In this article, we first consider and reject a simple answer to this question based on a common idealizing visualization of the model, which conflicts with the complexities of the visual system that the model was intended to capture. Next, we propose a taxonomic answer that takes inspiration from the philosophy of science and Leslie's body of work, which distinguishes between neural mechanisms, pathways, and streams. In this taxonomy, visual streams are superordinate to pathways and mechanisms and provide individuation conditions for determining whether collections of cortical connections delineate different visual streams. Given this characterization, we suggest that the proposed third visual stream does not yet meet these conditions, although the tripartite model still suggests important revisions to how we think about the organization of the human and non-human primate visual systems.

Symptomatology after damage to the angular gyrus through the lenses of modern lesion-symptom mapping

Brain-behavior relationships are complex. For instance, one might know a brain region's function(s) but still be unable to accurately predict deficit type or severity after damage to that region. Here, I discuss the case of damage to the angular gyrus (AG) that can cause left-right confusion, finger agnosia, attention deficit, and lexical agraphia, as well as impairment in sentence processing, episodic memory, number processing, and gesture imitation. Some of these symptoms are grouped under AG syndrome or Gerstmann's syndrome, though its exact underlying neuronal systems remain elusive. This review applies recent frameworks of brain-behavior modes and principles from modern lesion-symptom mapping to explain symptomatology after AG damage. It highlights four major issues for future studies: (1) functionally heterogeneous symptoms after AG damage need to be considered in terms of the degree of damage to (i) different subdivisions of the AG, (ii) different AG connectivity profiles that disconnect AG from distant regions, and (iii) lesion extent into neighboring regions damaged by the same infarct. (2) To explain why similar symptoms can also be observed after damage to other regions, AG damage needs to be studied in terms of the networks of regions that AG functions with, and other independent networks that might subsume the same functions. (3) To explain inter-patient variability on AG symptomatology, the degree of recovery-related brain reorganisation needs to account for time post-stroke, demographics, therapy input, and pre-stroke differences in functional anatomy. (4) A better integration of the results from lesion and functional neuroimaging investigations of AG function is required, with only the latter so far considering AG function in terms of a hub within the default mode network. Overall, this review discusses why it is so difficult to fully characterize the AG syndrome from lesion data, and how this might be addressed with modern lesion-symptom mapping.

Diffusion tensor analysis of white matter tracts is prognostic of persisting post-concussion symptoms in collegiate athletes

BACKGROUND AND OBJECTIVES

After a concussion diagnosis, the most important issue for patients and loved ones is how long it will take them to recover. The main objective of this study is to develop a prognostic model of concussion recovery. This model would benefit many patients worldwide, allowing for early treatment intervention.

METHODS

The Concussion Assessment, Research and Education (CARE) consortium study enrolled collegiate athletes from 30 sites (NCAA athletic departments and US Department of Defense service academies), 4 of which participated in the Advanced Research Core, which included diffusion-weighted MRI (dMRI) data collection. We analyzed the dMRI data of 51 injuries of concussed athletes scanned within 48 h of injury. All athletes were cleared to return-to-play by the local medical staff following a standardized, graduated protocol. The primary outcome measure is days to clearance of unrestricted return-to-play. Injuries were divided into early (return-to-play < 28 days) and late (return-to-play >= 28 days) recovery based on the return-to-play clinical records. The late recovery group meets the standard definition of Persisting Post-Concussion Symptoms (PPCS). Data were processed using automated, state-of-the-art, rigorous methods for reproducible data processing using brainlife.io. All processed data derivatives are made available at https://brainlife.io/project/63b2ecb0daffe2c2407ee3c5/dataset. The microstructural properties of 47 major white matter tracts, 5 callosal, 15 subcortical, and 148 cortical structures were mapped. Fractional Anisotropy (FA) and Mean Diffusivity (MD) were estimated for each tract and structure. Correlation analysis and Receiver Operator Characteristic (ROC) analysis were then performed to assess the association between the microstructural properties and return-to-play. Finally, a Logistic Regression binary classifier (LR-BC) was used to classify the injuries between the two recovery groups.

RESULTS

The mean FA across all white matter volume was negatively correlated with return-to-play (r = -0.38, p = 0.00001). No significant association between mean MD and return-to-play was found, neither for FA nor MD for any other structure. The mean FA of 47 white matter tracts was negatively correlated with return-to-play (rμ = -0.27; rσ = 0.08; rmin = -0.1; rmax = -0.43). Across all tracts, a large mean ROC Area Under the Curve (AUCFA) of 0.71 ± 0.09 SD was found. The top classification performance of the LR-BC was AUC = 0.90 obtained using the 16 statistically significant white matter tracts.

DISCUSSION

Utilizing a free, open-source, and automated cloud-based neuroimaging pipeline and app (https://brainlife.io/docs/tutorial/using-clairvoy/), a prognostic model has been developed, which predicts athletes at risk for slow recovery (PPCS) with an AUC=0.90, balanced accuracy = 0.89, sensitivity = 1.0, and specificity = 0.79. The small number of participants in this study (51 injuries) is a significant limitation and supports the need for future large concussion dMRI studies and focused on recovery.

Associative white matter tracts selectively predict sensorimotor learning

Human learning varies greatly among individuals and is related to the microstructure of major white matter tracts in several learning domains, yet the impact of the existing microstructure of white matter tracts on future learning outcomes remains unclear. We employed a machine-learning model selection framework to evaluate whether existing microstructure might predict individual differences in learning a sensorimotor task, and further, if the mapping between tract microstructure and learning was selective for learning outcomes. We used diffusion tractography to measure the mean fractional anisotropy (FA) of white matter tracts in 60 adult participants who then practiced drawing a set of 40 unfamiliar symbols repeatedly using a digital writing tablet. We measured drawing learning as the slope of draw duration over the practice session and measured visual recognition learning for the symbols using an old/new 2-AFC task. Results demonstrated that tract microstructure selectively predicted learning outcomes, with left hemisphere pArc and SLF3 tracts predicting drawing learning and the left hemisphere MDLFspl predicting visual recognition learning. These results were replicated using repeat, held-out data and supported with complementary analyses. Results suggest that individual differences in the microstructure of human white matter tracts may be selectively related to future learning outcomes.

Reciprocal interactions among parietal and occipito-temporal representations support everyday object-directed actions

Everyday interactions with common manipulable objects require the integration of conceptual knowledge about objects and actions with real-time sensory information about the position, orientation and volumetric structure of the grasp target. The ability to successfully interact with everyday objects involves analysis of visual form and shape, surface texture, material properties, conceptual attributes such as identity, function and typical context, and visuomotor processing supporting hand transport, grasp form, and object manipulation. Functionally separable brain regions across the dorsal and ventral visual pathways support the processing of these different object properties and, in cohort, are necessary for functional object use. Object-directed grasps display end-state-comfort: they anticipate in form and force the shape and material properties of the grasp target, and how the object will be manipulated after it is grasped. End-state-comfort is the default for everyday interactions with manipulable objects and implies integration of information across the ventral and dorsal visual pathways. We propose a model of how visuomotor and action representations in parietal cortex interact with object representations in ventral and lateral occipito-temporal cortex. One pathway, from the supramarginal gyrus to the middle and inferior temporal gyrus, supports the integration of action-related information, including hand and limb position (supramarginal gyrus) with conceptual attributes and an appreciation of the action goal (middle temporal gyrus). A second pathway, from posterior IPS to the fusiform gyrus and collateral sulcus supports the integration of grasp parameters (IPS) with the surface texture and material properties (e.g., weight distribution) of the grasp target. Reciprocal interactions among these regions are part of a broader network of regions that support everyday functional object interactions.

brainlife.io: a decentralized and open-source cloud platform to support neuroscience research

Neuroscience is advancing standardization and tool development to support rigor and transparency. Consequently, data pipeline complexity has increased, hindering FAIR (findable, accessible, interoperable and reusable) access. brainlife.io was developed to democratize neuroimaging research. The platform provides data standardization, management, visualization and processing and automatically tracks the provenance history of thousands of data objects. Here, brainlife.io is described and evaluated for validity, reliability, reproducibility, replicability and scientific utility using four data modalities and 3,200 participants.

A systematic review of automated methods to perform white matter tract segmentation

White matter tract segmentation is a pivotal research area that leverages diffusion-weighted magnetic resonance imaging (dMRI) for the identification and mapping of individual white matter tracts and their trajectories. This study aims to provide a comprehensive systematic literature review on automated methods for white matter tract segmentation in brain dMRI scans. Articles on PubMed, ScienceDirect [NeuroImage, NeuroImage (Clinical), Medical Image Analysis], Scopus and IEEEXplore databases and Conference proceedings of Medical Imaging Computing and Computer Assisted Intervention Society (MICCAI) and International Symposium on Biomedical Imaging (ISBI), were searched in the range from January 2013 until September 2023. This systematic search and review identified 619 articles. Adhering to the specified search criteria using the query, "white matter tract segmentation OR fiber tract identification OR fiber bundle segmentation OR tractography dissection OR white matter parcellation OR tract segmentation," 59 published studies were selected. Among these, 27% employed direct voxel-based methods, 25% applied streamline-based clustering methods, 20% used streamline-based classification methods, 14% implemented atlas-based methods, and 14% utilized hybrid approaches. The paper delves into the research gaps and challenges associated with each of these categories. Additionally, this review paper illuminates the most frequently utilized public datasets for tract segmentation along with their specific characteristics. Furthermore, it presents evaluation strategies and their key attributes. The review concludes with a detailed discussion of the challenges and future directions in this field.

Parcellating the vertical associative fiber network of the temporoparietal area: Evidence from focused anatomic fiber dissections

Introduction

The connectivity of the temporoparietal (TP) region has been the subject of multiple anatomical and functional studies. Its role in high cognitive functions has been primarily correlated with long association fiber connections. As a major sensory integration hub, coactivation of areas within the TP requires a stream of short association fibers running between its subregions. The latter have been the subject of a small number of recent in vivo and cadaveric studies. This has resulted in limited understanding of this network and, in certain occasions, terminology ambiguity.

Research question

To systematically study the vertical parietal and temporoparietal short association fibers.

Material and methods

Thirteen normal, adult cadaveric hemispheres, were treated with the Klinger's freeze-thaw process and their subcortical anatomy was studied using the microdissection technique.

Results

Two separate fiber layers were identified. Superficially, directly beneath the cortical u-fibers, the Stratum proprium intraparietalis (SP) was seen connecting Superior Parietal lobule and Precuneal cortical areas to inferior cortical regions of the Parietal lobe, running deep to the Intraparietal sulcus. At the same dissection level, the IPL-TP fibers were identified as a bundle connecting the Inferior Parietal lobule with posterior Temporal cortical areas. At a deeper level, parallel to the Arcuate fasciculus fibers, the SPL-TP fibers were seen connecting the Superior Parietal lobule to posterior Temporal cortical areas.

Discussion and conclusion

To our knowledge this is the first cadaveric dissection study to comprehensively study and describe of the vertical association fibers of the temporoparietal region while proposing a universal terminology.

The effects of object size on spatial orientation: an eye movement study

Introduction

The processing of visual information in the human brain is divided into two streams, namely, the dorsal and ventral streams, object identification is related to the ventral stream and motion processing is related to the dorsal stream. Object identification is interconnected with motion processing, object size was found to affect the information processing of motion characteristics in uniform linear motion. However, whether the object size affects the spatial orientation is still unknown.

Methods

Thirty-eight college students were recruited to participate in an experiment based on the spatial visualization dynamic test. Eyelink 1,000 Plus was used to collect eye movement data. The final direction difference (the difference between the final moving direction of the target and the final direction of the moving target pointing to the destination point), rotation angle (the rotation angle of the knob from the start of the target movement to the moment of key pressing) and eye movement indices under conditions of different object sizes and motion velocities were compared.

Results

The final direction difference and rotation angle under the condition of a 2.29°-diameter moving target and a 0.76°-diameter destination point were significantly smaller than those under the other conditions (a 0.76°-diameter moving target and a 0.76°-diameter destination point; a 0.76°-diameter moving target and a 2.29°-diameter destination point). The average pupil size under the condition of a 2.29°-diameter moving target and a 0.76°-diameter destination point was significantly larger than the average pupil size under other conditions (a 0.76°-diameter moving target and a 0.76°-diameter destination point; a 0.76°-diameter moving target and a 2.29°-diameter destination point).

Discussion

A relatively large moving target can resist the landmark attraction effect in spatial orientation, and the influence of object size on spatial orientation may originate from differences in cognitive resource consumption. The present study enriches the interaction theory of the processing of object characteristics and motion characteristics and provides new ideas for the application of eye movement technology in the examination of spatial orientation ability.

Associative white matter tracts selectively predict sensorimotor learning

Human learning is a complex phenomenon that varies greatly among individuals and is related to the microstructure of major white matter tracts in several learning domains, yet the impact of the existing myelination of white matter tracts on future learning outcomes remains unclear. We employed a machine-learning model selection framework to evaluate whether existing microstructure might predict individual differences in the potential for learning a sensorimotor task, and further, if the mapping between the microstructure of major white matter tracts and learning was selective for learning outcomes. We used diffusion tractography to measure the mean fractional anisotropy (FA) of white matter tracts in 60 adult participants who then underwent training and subsequent testing to evaluate learning. During training, participants practiced drawing a set of 40 novel symbols repeatedly using a digital writing tablet. We measured drawing learning as the slope of draw duration over the practice session and visual recognition learning as the performance accuracy in an old/new 2-AFC recognition task. Results demonstrated that the microstructure of major white matter tracts selectively predicted learning outcomes, with left hemisphere pArc and SLF 3 tracts predicting drawing learning and the left hemisphere MDLFspl predicting visual recognition learning. These results were replicated in a repeat, held-out data set and supported with complementary analyses. Overall, results suggest that individual differences in the microstructure of human white matter tracts may be selectively related to future learning outcomes and open avenues of inquiry concerning the impact of existing tract myelination in the potential for learning.

Significance statement

A selective mapping between tract microstructure and future learning has been demonstrated in the murine model and, to our knowledge, has not yet been demonstrated in humans. We employed a data-driven approach that identified only two tracts, the two most posterior segments of the arcuate fasciculus in the left hemisphere, to predict learning a sensorimotor task (drawing symbols) and this prediction model did not transfer to other learning outcomes (visual symbol recognition). Results suggest that individual differences in learning may be selectively related to the tissue properties of major white matter tracts in the human brain.

A narrative review of the anatomy and function of the white matter tracts in language production and comprehension

Much is known about the role of cortical areas in language processing. The shift towards network approaches in recent years has highlighted the importance of uncovering the role of white matter in connecting these areas. However, despite a large body of research, many of these tracts' functions are not well-understood. We present a comprehensive review of the empirical evidence on the role of eight major tracts that are hypothesized to be involved in language processing (inferior longitudinal fasciculus, inferior fronto-occipital fasciculus, uncinate fasciculus, extreme capsule, middle longitudinal fasciculus, superior longitudinal fasciculus, arcuate fasciculus, and frontal aslant tract). For each tract, we hypothesize its role based on the function of the cortical regions it connects. We then evaluate these hypotheses with data from three sources: studies in neurotypical individuals, neuropsychological data, and intraoperative stimulation studies. Finally, we summarize the conclusions supported by the data and highlight the areas needing further investigation.

Multiple functions of the angular gyrus at high temporal resolution

Here, the functions of the angular gyrus (AG) are evaluated in the light of current evidence from transcranial magnetic/electric stimulation (TMS/TES) and EEG/MEG studies. 65 TMS/TES and 52 EEG/MEG studies were examined in this review. TMS/TES literature points to a causal role in semantic processing, word and number processing, attention and visual search, self-guided movement, memory, and self-processing. EEG/MEG studies reported AG effects at latencies varying between 32 and 800 ms in a wide range of domains, with a high probability to detect an effect at 300-350 ms post-stimulus onset. A three-phase unifying model revolving around the process of sensemaking is then suggested: (1) early AG involvement in defining the current context, within the first 200 ms, with a bias toward the right hemisphere; (2) attention re-orientation and retrieval of relevant information within 200-500 ms; and (3) cross-modal integration at late latencies with a bias toward the left hemisphere. This sensemaking process can favour accuracy (e.g. for word and number processing) or plausibility (e.g. for comprehension and social cognition). Such functions of the AG depend on the status of other connected regions. The much-debated semantic role is also discussed as follows: (1) there is a strong TMS/TES evidence for a causal semantic role, (2) current EEG/MEG evidence is however weak, but (3) the existing arguments against a semantic role for the AG are not strong. Some outstanding questions for future research are proposed. This review recognizes that cracking the role(s) of the AG in cognition is possible only when its exact contributions within the default mode network are teased apart.

The structural connectivity of the human angular gyrus as revealed by microdissection and diffusion tractography

The angular gyrus (AG) has been described in numerous studies to be consistently activated in various functional tasks. The angular gyrus is a critical connector epicenter linking multiple functional networks due to its location in the posterior part of the inferior parietal cortex, namely at the junction between the parietal, temporal, and occipital lobes. It is thus crucial to identify the different pathways that anatomically connect this high-order association region to the rest of the brain. Our study revisits the three-dimensional architecture of the structural AG connectivity by combining state-of-the-art postmortem blunt microdissection with advanced in vivo diffusion tractography to comprehensively describe the association, projection, and commissural fibers that connect the human angular gyrus. AG appears as a posterior "angular stone" of associative connections belonging to mid- and long-range dorsal and ventral fibers of the superior and inferior longitudinal systems, respectively, to short-range parietal, occipital, and temporal fibers, including U-shaped fibers in the posterior transverse system. Thus, AG is at a pivotal dorso-ventral position reflecting its critical role in the different functional networks, particularly in language elaboration and spatial attention and awareness in the left and right hemispheres, respectively. We also reveal striatal, thalamic, and brainstem connections and a typical inter-hemispheric homotopic callosal connectivity supporting the suggested AG role in the integration of sensory input for modulating motor control and planning. The present description of AG's highly distributed wiring diagram may drastically improve intraoperative subcortical testing and post-operative neurologic outcomes related to surgery in and around the angular gyrus.

A comparison of diffusion tensor imaging tractography and constrained spherical deconvolution with automatic segmentation in traumatic brain injury

Detection of microstructural white matter injury in traumatic brain injury (TBI) requires specialised imaging methods, of which diffusion tensor imaging (DTI) has been extensively studied. Newer fibre alignment estimation methods, such as constrained spherical deconvolution (CSD), are better than DTI in resolving crossing fibres that are ubiquitous in the brain and may improve the ability to detect microstructural injuries. Furthermore, automatic tract segmentation has the potential to improve tractography reliability and accelerate workflow compared to the manual segmentation commonly used. In this study, we compared the results of deterministic DTI based tractography and manual tract segmentation with CSD based probabilistic tractography and automatic tract segmentation using TractSeg. 37 participants with a history of TBI (with Glasgow Coma Scale 13-15) and persistent symptoms, and 41 healthy controls underwent deterministic DTI-based tractography with manual tract segmentation and probabilistic CSD-based tractography with TractSeg automatic segmentation.Fractional anisotropy (FA) and mean diffusivity of corpus callosum and three bilateral association tracts were measured. FA and MD values derived from both tractography methods were generally moderately to strongly correlated. CSD with TractSeg differentiated the groups based on FA, while DTI did not. CSD and TractSeg-based tractography may be more sensitive in detecting microstructural changes associated with TBI than deterministic DTI tractography. Additionally, CSD with TractSeg was found to be applicable at lower b-value and number of diffusion-encoding gradients data than previously reported.

A taxonomy of the brain's white matter: twenty-one major tracts for the 21st century

The functional and computational properties of brain areas are determined, in large part, by their connectivity profiles. Advances in neuroimaging and network neuroscience allow us to characterize the human brain noninvasively, but a comprehensive understanding of the human brain demands an account of the anatomy of brain connections. Long-range anatomical connections are instantiated by white matter, which itself is organized into tracts. These tracts are often disrupted by central nervous system disorders, and they can be targeted by neuromodulatory interventions, such as deep brain stimulation. Here, we characterized the connections, morphology, traversal, and functions of the major white matter tracts in the brain. There are major discrepancies across different accounts of white matter tract anatomy, hindering our attempts to accurately map the connectivity of the human brain. However, we are often able to clarify the source(s) of these discrepancies through careful consideration of both histological tract-tracing and diffusion-weighted tractography studies. In combination, the advantages and disadvantages of each method permit novel insights into brain connectivity. Ultimately, our synthesis provides an essential reference for neuroscientists and clinicians interested in brain connectivity and anatomy, allowing for the study of the association of white matter's properties with behavior, development, and disorders.

Leveraging manifold learning techniques to explore white matter anomalies: An application of the TractLearn pipeline in epilepsy

An accurate description of brain white matter anatomy in vivo remains a challenge. However, technical progress allows us to analyze structural variations in an increasingly sophisticated way. Current methods of processing diffusion MRI data now make it possible to correct some limiting biases. In addition, the development of statistical learning algorithms offers the opportunity to analyze the data from a new perspective. We applied newly developed tractography models to extract quantitative white matter parameters in a group of patients with chronic temporal lobe epilepsy. Furthermore, we implemented a statistical learning workflow optimized for the MRI diffusion data - the TractLearn pipeline - to model inter-individual variability and predict structural changes in patients. Finally, we interpreted white matter abnormalities in the context of several other parameters reflecting clinical status, as well as neuronal and cognitive functioning for these patients. Overall, we show the relevance of such a diffusion data processing pipeline for the evaluation of clinical populations. The "global to fine scale" funnel statistical approach proposed in this study also contributes to the understanding of neuroplasticity mechanisms involved in refractory epilepsy, thus enriching previous findings.

Denoising diffusion weighted imaging data using convolutional neural networks

Diffusion weighted imaging (DWI) with multiple, high b-values is critical for extracting tissue microstructure measurements; however, high b-value DWI images contain high noise levels that can overwhelm the signal of interest and bias microstructural measurements. Here, we propose a simple denoising method that can be applied to any dataset, provided a low-noise, single-subject dataset is acquired using the same DWI sequence. The denoising method uses a one-dimensional convolutional neural network (1D-CNN) and deep learning to learn from a low-noise dataset, voxel-by-voxel. The trained model can then be applied to high-noise datasets from other subjects. We validated the 1D-CNN denoising method by first demonstrating that 1D-CNN denoising resulted in DWI images that were more similar to the noise-free ground truth than comparable denoising methods, e.g., MP-PCA, using simulated DWI data. Using the same DWI acquisition but reconstructed with two common reconstruction methods, i.e. SENSE1 and sum-of-square, to generate a pair of low-noise and high-noise datasets, we then demonstrated that 1D-CNN denoising of high-noise DWI data collected from human subjects showed promising results in three domains: DWI images, diffusion metrics, and tractography. In particular, the denoised images were very similar to a low-noise reference image of that subject, more than the similarity between repeated low-noise images (i.e. computational reproducibility). Finally, we demonstrated the use of the 1D-CNN method in two practical examples to reduce noise from parallel imaging and simultaneous multi-slice acquisition. We conclude that the 1D-CNN denoising method is a simple, effective denoising method for DWI images that overcomes some of the limitations of current state-of-the-art denoising methods, such as the need for a large number of training subjects and the need to account for the rectified noise floor.

Gyral and sulcal connectivity in the human cerebral cortex

The rapid evolution of image acquisition and data analytic methods has established in vivo whole-brain tractography as a routine technology over the last 20 years. Imaging-based methods provide an additional approach to classic neuroanatomical studies focusing on biomechanical principles of anatomical organization and can in turn overcome the complexity of inter-individual variability associated with histological and tractography studies. In this work we propose a novel, reliable framework for determining brain tracts resolving the anatomical variance of brain regions. We distinguished 4 region types based on anatomical considerations: (i) gyral regions at borders between cortical communities; (ii) gyral regions within communities; (iii) sulcal regions at invariant locations across subjects; and (iv) other sulcal regions. Region types showed strikingly different anatomical and connection properties. Results allowed complementing the current understanding of the brain’s communication structure with a model of its anatomical underpinnings.

Development of white matter tracts between and within the dorsal and ventral streams

The degree of interaction between the ventral and dorsal visual streams has been discussed in multiple scientific domains for decades. Recently, several white matter tracts that directly connect cortical regions associated with the dorsal and ventral streams have become possible to study due to advancements in automated and reproducible methods. The developmental trajectory of this set of tracts, here referred to as the posterior vertical pathway (PVP), has yet to be described. We propose an input-driven model of white matter development and provide evidence for the model by focusing on the development of the PVP. We used reproducible, cloud-computing methods and diffusion imaging from adults and children (ages 5-8 years) to compare PVP development to that of tracts within the ventral and dorsal pathways. PVP microstructure was more adult-like than dorsal stream microstructure, but less adult-like than ventral stream microstructure. Additionally, PVP microstructure was more similar to the microstructure of the ventral than the dorsal stream and was predicted by performance on a perceptual task in children. Overall, results suggest a potential role for the PVP in the development of the dorsal visual stream that may be related to its ability to facilitate interactions between ventral and dorsal streams during learning. Our results are consistent with the proposed model, suggesting that the microstructural development of major white matter pathways is related, at least in part, to the propagation of sensory information within the visual system.

The vertical superior longitudinal fascicle and the vertical occipital fascicle

Association fibers of the human brain have long been considered to exclusively follow an anterior-posterior direction. Using magnetic resonance imaging techniques that allow in-vivo fiber dissection, vertically oriented association fibers have been rediscovered or newly described. Aside from the frontal aslant tract (FAT) in the frontal lobe, the vertical occipital fascicle (VOF) and the vertical portion of the superior longitudinal fascicle system (vSLF) have been studied in recent years. The aim of this review was to give an overview on the current knowledge regarding these two fiber tracts. A review of the available literature in the Medline database was conducted to gather all available publications dealing with either the VOF or the vSLF. One thousand two hundred seventy-three articles were obtained from the literature search of which a total of 71 articles met the final inclusion criteria of this review. We describe the history of the discovery of the respective fiber tract, its anatomical course and its boundaries integrating blunt fiber dissection studies and functional MRI/tractography studies. We discuss the functional properties of the respective fiber tract and its relevance in neurosurgery. The VOF is a fiber tract that has been discovered in the late XIX century and long been forgotten before being rediscovered in the 1970's. It lies lateral to the fibers of the sagittal stratum and mainly connects the superior and inferior occipital lobe. It plays a major role in reading and visual word and language comprehension and is said to be the main link between dorsal and ventral visual streams. The vSLF has many synonyms and is part of the superior longitudinal fascicle system. Recent studies were able to provide more insight into this set of fiber tracts showing distinct connections running from the superior and inferior parietal lobule to the posterior part of the temporal lobe. Its functional role is still not completely cleared. It is said to play a role in visual and auditory semantic language comprehension. It lies directly lateral to the arcuate fascicle. The VOF and the vSLF are vertically oriented fiber tracts connecting the temporo-parieto-occipital region and play a major role in the communication of dorsal and ventral visual streams (VOF), reading (VOF, vSLF) and visual and auditory semantic language comprehension (vSLF). They can consistently be identified using ex vivo blunt dissection techniques and in-vivo fiber tractography. Because of their localization and orientation these two fiber tracts can be combined to a fiber bundle system called posterior transverse system (PTS).

Missing links: The functional unification of language and memory (L∪M)

The field of neurocognition is currently undergoing a significant change of perspective. Traditional neurocognitive models evolved into an integrative and dynamic vision of cognitive functioning. Dynamic integration assumes an interaction between cognitive domains traditionally considered to be distinct. Language and declarative memory are regarded as separate functions supported by different neural systems. However, they also share anatomical structures (notably, the inferior frontal gyrus, the supplementary motor area, the superior and middle temporal gyrus, and the hippocampal complex) and cognitive processes (such as semantic and working memory) that merge to endorse our quintessential daily lives. We propose a new model, "L∪M" (i.e., Language/union/Memory), that considers these two functions interactively. We fractionated language and declarative memory into three fundamental dimensions or systems ("Receiver-Transmitter", "Controller-Manager" and "Transformer-Associative" Systems), that communicate reciprocally. We formalized their interactions at the brain level with a connectivity-based approach. This new taxonomy overcomes the modular view of cognitive functioning and reconciles functional specialization with plasticity in neurological disorders.

White matter variability, cognition, and disorders: a systematic review

Inter-individual differences can inform treatment procedures and—if accounted for—have the potential to significantly improve patient outcomes. However, when studying brain anatomy, these inter-individual variations are commonly unaccounted for, despite reports of differences in gross anatomical features, cross-sectional, and connectional anatomy. Brain connections are essential to facilitate functional organization and, when severed, cause impairments or complete loss of function. Hence, the study of cerebral white matter may be an ideal compromise to capture inter-individual variability in structure and function. We reviewed the wealth of studies that associate cognitive functions and clinical symptoms with individual tracts using diffusion tractography. Our systematic review indicates that tractography has proven to be a sensitive method in neurology, psychiatry, and healthy populations to identify variability and its functional correlates. However, the literature may be biased, as the most commonly studied tracts are not necessarily those with the highest sensitivity to cognitive functions and pathologies. Additionally, the hemisphere of the studied tract is often unreported, thus neglecting functional laterality and asymmetries. Finally, we demonstrate that tracts, as we define them, are not correlated with one, but multiple cognitive domains or pathologies. While our systematic review identified some methodological caveats, it also suggests that tract–function correlations might still be a promising tool in identifying biomarkers for precision medicine. They can characterize variations in brain anatomy, differences in functional organization, and predicts resilience and recovery in patients.

Alterations in white matter integrity and asymmetry in patients with benign childhood epilepsy with centrotemporal spikes and childhood absence epilepsy: An automated fiber quantification tractography study

PURPOSE

To investigate whether patients with benign childhood epilepsy with centrotemporal spikes (BECTS) and childhood absence epilepsy (CAE) show distinct patterns of white matter (WM) alterations and structural asymmetry compared with healthy controls and the relationship between WM alterations and epilepsy-related clinical variables.

METHODS

We used automated fiber quantification to create tract profiles of fractional anisotropy (FA) and mean diffusivity (MD) in twenty-six patients with BECTS, twenty-nine patients with CAE, and twenty-four healthy controls. Group differences in FA and MD were quantified at 100 equidistant nodes along the fiber tract and these alterations and epilepsy-related clinical variables were correlated. A lateralization index (LI) representing the structural asymmetry of the fiber tract was computed and compared between both patient groups and controls.

RESULTS

Compared with healthy controls, the BECTS group showed widespread FA reduction in 43.75% (7/16) and MD elevation in 50% (8/16) of identified fiber tracts, and the CAE group showed regional FA reduction in 31.25% (5/16) and MD elevation in 25% (4/16) of identified fiber tracts. In the BECTS group, FA and MD in the right anterior thalamic radiation positively and negatively correlated with the number of antiepileptic drugs, respectively, and MD in the right arcuate fasciculus (AF) positively correlated with seizure frequency. In the CAE group, the LI values were significantly lower in the inferior fronto-occipital fasciculus and the AF.

CONCLUSION

The two childhood epilepsy syndromes display different patterns of WM alterations and structural asymmetry, suggesting that neuroanatomical differences may underlie the different profiles of BECTS and CAE.

Visual Information Routes in the Posterior Dorsal and Ventral Face Network Studied with Intracranial Neurophysiology and White Matter Tract Endpoints

Occipitotemporal regions within the face network process perceptual and socioemotional information, but the dynamics and information flow between different nodes of this network are still debated. Here, we analyzed intracerebral EEG from 11 epileptic patients viewing a stimulus sequence beginning with a neutral face with direct gaze. The gaze could avert or remain direct, while the emotion changed to fearful or happy. N200 field potential peak latencies indicated that face processing begins in inferior occipital cortex and proceeds anteroventrally to fusiform and inferior temporal cortices, in parallel. The superior temporal sulcus responded preferentially to gaze changes with augmented field potential amplitudes for averted versus direct gaze, and large effect sizes relative to other network regions. An overlap analysis of posterior white matter tractography endpoints (from 1066 healthy brains) relative to active intracerebral electrodes in the 11 patients showed likely involvement of both dorsal and ventral posterior white matter pathways. Overall, our data provide new insight into the timing of face and social cue processing in the occipitotemporal brain and anchor the superior temporal cortex in dynamic gaze processing.

The Radically Embodied Conscious Cybernetic Bayesian Brain: From Free Energy to Free Will and Back Again

Drawing from both enactivist and cognitivist perspectives on mind, I propose that explaining teleological phenomena may require reappraising both "Cartesian theaters" and mental homunculi in terms of embodied self-models (ESMs), understood as body maps with agentic properties, functioning as predictive-memory systems and cybernetic controllers. Quasi-homuncular ESMs are suggested to constitute a major organizing principle for neural architectures due to their initial and ongoing significance for solutions to inference problems in cognitive (and affective) development. Embodied experiences provide foundational lessons in learning curriculums in which agents explore increasingly challenging problem spaces, so answering an unresolved question in Bayesian cognitive science: what are biologically plausible mechanisms for equipping learners with sufficiently powerful inductive biases to adequately constrain inference spaces? Drawing on models from neurophysiology, psychology, and developmental robotics, I describe how embodiment provides fundamental sources of empirical priors (as reliably learnable posterior expectations). If ESMs play this kind of foundational role in cognitive development, then bidirectional linkages will be found between all sensory modalities and frontal-parietal control hierarchies, so infusing all senses with somatic-motoric properties, thereby structuring all perception by relevant affordances, so solving frame problems for embodied agents. Drawing upon the Free Energy Principle and Active Inference framework, I describe a particular mechanism for intentional action selection via consciously imagined (and explicitly represented) goal realization, where contrasts between desired and present states influence ongoing policy selection via predictive coding mechanisms and backward-chained imaginings (as self-realizing predictions). This embodied developmental legacy suggests a mechanism by which imaginings can be intentionally shaped by (internalized) partially-expressed motor acts, so providing means of agentic control for attention, working memory, imagination, and behavior. I further describe the nature(s) of mental causation and self-control, and also provide an account of readiness potentials in Libet paradigms wherein conscious intentions shape causal streams leading to enaction. Finally, I provide neurophenomenological handlings of prototypical qualia including pleasure, pain, and desire in terms of self-annihilating free energy gradients via quasi-synesthetic interoceptive active inference. In brief, this manuscript is intended to illustrate how radically embodied minds may create foundations for intelligence (as capacity for learning and inference), consciousness (as somatically-grounded self-world modeling), and will (as deployment of predictive models for enacting valued goals).

Filtering in tractography using autoencoders (FINTA)

Current brain white matter fiber tracking techniques show a number of problems, including: generating large proportions of streamlines that do not accurately describe the underlying anatomy; extracting streamlines that are not supported by the underlying diffusion signal; and under-representing some fiber populations, among others. In this paper, we describe a novel autoencoder-based learning method to filter streamlines from diffusion MRI tractography, and hence, to obtain more reliable tractograms. Our method, dubbed FINTA (Filtering in Tractography using Autoencoders) uses raw, unlabeled tractograms to train the autoencoder, and to learn a robust representation of brain streamlines. Such an embedding is then used to filter undesired streamline samples using a nearest neighbor algorithm. Our experiments on both synthetic and in vivo human brain diffusion MRI tractography data obtain accuracy scores exceeding the 90% threshold on the test set. Results reveal that FINTA has a superior filtering performance compared to conventional, anatomy-based methods, and the RecoBundles state-of-the-art method. Additionally, we demonstrate that FINTA can be applied to partial tractograms without requiring changes to the framework. We also show that the proposed method generalizes well across different tracking methods and datasets, and shortens significantly the computation time for large (>1 M streamlines) tractograms. Together, this work brings forward a new deep learning framework in tractography based on autoencoders, which offers a flexible and powerful method for white matter filtering and bundling that could enhance tractometry and connectivity analyses.

The inferior fronto-occipital fascicle: a century of controversies from anatomy theaters to operative neurosurgery

INTRODUCTION

Since its first description in the early 19th century, the inferior frontooccipital fascicle (IFOF) and its anatomo-functional features were neglected in the neuroscientific literature for the last century. In the last decade, the rapid development of in vivo imaging for the reconstruction of white matter (WM) connectivity (i.e., tractography) and the consequent interest in more traditional ex vivo methods (postmortem dissection) have allowed a renewed debate about course, termination territories, anatomical relationships, and functional roles of this fascicle.

EVIDENCE ACQUISITION

We reviewed the main current knowledge concerning the structural and functional anatomy of the IFOF and possible implications in neurosurgical practice.

EVIDENCE SYNTHESIS

The IFOF connects the occipital cortex, the temporo-basal areas, the superior parietal lobule, and the pre-cuneus to the frontal lobe, passing through the ventral third of subinsular WM of the external capsule. This wide distribution of cortical terminations provides multimodal integration between several functional networks, including language, non-verbal semantic processing, object identification, visuo-spatial processing and planning, reading, facial expression recognition, memory and conceptualization, emotional and neuropsychological behavior. This anatomo-functional organization has important implication also in neurosurgical practice, especially when approaching the frontal, insular, temporo-parieto-occipital regions and the ventricular system.

CONCLUSIONS

The IFOF is the most extensive associative bundle of the human connectome. Its multi-layer organization reflects important implications in many aspects of brain functional processing. Accurate awareness of IFOF functional anatomy and integration between multimodal datasets coming from different sources has crucial implications for both neuroscientific knowledge and quality of neurosurgical treatments.

Occipital Intralobar fasciculi: a description, through tractography, of three forgotten tracts

Diffusion MRI paired with tractography has facilitated a non-invasive exploration of many association, projection, and commissural fiber tracts. However, there is still a scarcity of research studies related to intralobar association fibers. The Dejerines' (two of the most notable neurologists of 19th century France) gave an in-depth description of the intralobar fibers of the occipital lobe. Unfortunately, their exquisite work has since been sparsely cited in the modern literature. This work gives a modern description of many of the occipital intralobar lobe fibers described by the Dejerines. We perform a virtual dissection and reconstruct the tracts using diffusion MRI tractography. The dissection is guided by the Dejerines' treatise, Anatomie des Centres Nerveux. As an accompaniment to this article, we provided a French-to-English translation of the treatise portion concerning five intra-occipital tracts, namely: the stratum calcarinum, the stratum proprium cunei, the vertical occipital fasciculus of Wernicke, the transverse fasciculus of the cuneus and the transverse fasciculus of the lingual lobule of Vialet. It was possible to reconstruct all but one of these tracts. For completeness, the recently described sledge runner fasciculus, although not one of the Dejerines' tracts, was identified and successfully reconstructed.

White matter alterations in glaucoma and monocular blindness differ outside the visual system

The degree to which glaucoma has effects in the brain beyond the eye and the visual pathways is unclear. To clarify this, we investigated white matter microstructure (WMM) in 37 tracts of patients with glaucoma, monocular blindness, and controls. We used brainlife.io for reproducibility. White matter tracts were subdivided into seven categories ranging from those primarily involved in vision (the visual white matter) to those primarily involved in cognition and motor control. In the vision tracts, WMM was decreased as measured by fractional anisotropy in both glaucoma and monocular blind subjects compared to controls, suggesting neurodegeneration due to reduced sensory inputs. A test-retest approach was used to validate these results. The pattern of results was different in monocular blind subjects, where WMM properties increased outside the visual white matter as compared to controls. This pattern of results suggests that whereas in the monocular blind loss of visual input might promote white matter reorganization outside of the early visual system, such reorganization might be reduced or absent in glaucoma. The results provide indirect evidence that in glaucoma unknown factors might limit the reorganization as seen in other patient groups following visual loss.

Collegiate athlete brain data for white matter mapping and network neuroscience

We describe a dataset of processed data with associated reproducible preprocessing pipeline collected from two collegiate athlete groups and one non-athlete group. The dataset shares minimally processed diffusion-weighted magnetic resonance imaging (dMRI) data, three models of the diffusion signal in the voxel, full-brain tractograms, segmentation of the major white matter tracts as well as structural connectivity matrices. There is currently a paucity of similar datasets openly shared. Furthermore, major challenges are associated with collecting this type of data. The data and derivatives shared here can be used as a reference to study the effects of long-term exposure to collegiate athletics, such as the effects of repetitive head impacts. We use advanced anatomical and dMRI data processing methods publicly available as reproducible web services at brainlife.io.

Multitasking Compensatory Saccadic Training Program for Hemianopia Patients: A New Approach With 3-Dimensional Real-World Objects

Purpose

To examine whether a noncomputerized multitasking compensatory saccadic training program (MCSTP) for patients with hemianopia, based on a reading regimen and eight exercises that recreate everyday visuomotor activities using three-dimensional (3D) real-world objects, improves the visual ability/function, quality of life (QL), and functional independence (FI).

Methods

The 3D-MCSTP included four in-office visits and two customized home-based daily training sessions over 12 weeks. A quasiexperimental, pretest/posttest study design was carried out with an intervention group (IG) (n = 20) and a no-training group (NTG) (n = 20) matched for age, hemianopia type, and brain injury duration.

Results

The groups were comparable for the main baseline variables and all participants (n = 40) completed the study. The IG mainly showed significant improvements in visual-processing speed (57.34% ± 19.28%; P < 0.0001) and visual attention/retention ability (26.67% ± 19.21%; P < 0.0001), which also were significantly greater (P < 0.05) than in the NTG. Moreover, the IG showed large effect sizes (Cohen's d) in 75% of the total QL and FI dimensions analyzed; in contrast to the NTG that showed negligible mean effect sizes in 96% of these dimensions.

Conclusions

The customized 3D-MCSTP was associated with a satisfactory response in the IG for improving complex visual processing, QL, and FI.

Translational Relevance

Neurovisual rehabilitation of patients with hemianopia seems more efficient when programs combine in-office visits and customized home-based training sessions based on real objects and simulating real-life conditions, than no treatment or previously reported computer-screen approaches, probably because of better stimulation of patients´ motivation and visual-processing speed brain mechanisms.

The human endogenous attentional control network includes a ventro-temporal cortical node

Endogenous attention is the cognitive function that selects the relevant pieces of sensory information to achieve goals and it is known to be controlled by dorsal fronto-parietal brain areas. Here we expand this notion by identifying a control attention area located in the temporal lobe. By combining a demanding behavioral paradigm with functional neuroimaging and diffusion tractography, we show that like fronto-parietal attentional areas, the human posterior inferotemporal cortex exhibits significant attentional modulatory activity. This area is functionally distinct from surrounding cortical areas, and is directly connected to parietal and frontal attentional regions. These results show that attentional control spans three cortical lobes and overarches large distances through fiber pathways that run orthogonally to the dominant anterior-posterior axes of sensory processing, thus suggesting a different organizing principle for cognitive control.

Intraoperative Direct Stimulation Identification and Preservation of Critical White Matter Tracts During Brain Surgery

The study of brain connectomics has led to a rapid evolution in the understanding of human brain function. Traditional localizationist theories are being replaced by more accurate network, or hodologic, approaches that model brain function as widespread processes dependent on cortical and subcortical structures, as well as the white matter tracts (WMTs) that link these areas. Recent surgical literature suggests that WMTs may be more critical to preserve than cortical structures because of the comparably lower capacity of recovery of the former when damaged. Given the relevance of eloquent WMTs to neurologic function and thus quality of life, neurosurgical interventions must be tailored to maximize their preservation. Direct electric stimulation remains a vital tool for identification and avoidance of these critical tracts. Neurosurgeons therefore require proper understanding of the anatomy and function of WMTs, as well as the reported contemporary tasks used during intraoperative stimulation. We review the relevant tracts involved in language, visuospatial, and motor networks and the updated direct electric stimulation-based mapping tasks that aid in their preservation. The dominant-hemisphere language WMTs have been mapped using picture naming, semantic association, word repetition, reading, and writing tasks. For monitoring of vision and spatial functions, the modified picture naming and line bisection tasks, as well as the recording of visual evoked potentials, have been used. Repetitive movements and monitoring of motor evoked potentials and involuntary movements have been applied for preservation of the motor networks.

Proposal for human visual pathway in the extrastriate cortex by fiber tracking method using diffusion-weighted MRI

The extrastriate cortex in the human visual cortex is divided into two distinct clusters: the "what-information" processing area and the "where-information" processing area. It is widely accepted that the "what-information" cluster is processed through the ventral stream to the temporal cortex, and the "where-information" cluster through the dorsal stream to the parietal cortex. In human neuroanatomy, fiber bundles for the ventral stream (such as the inferior longitudinal fasciculus) are well defined, whereas fibers for the dorsal stream are poorly understood. In this study, we attempted to trace the dorsal stream fibers using a fiber tracking method using 7.0T diffusion-weighted MRI. We used data from a healthy male subject as well as from an unbiasedly selected nine-subject dataset in the Human Connectome Project. The surface of the visual area, including V1, V2, V3, V4, MT, was determined from the Brainnetome atlas (Fan et al., 2016), which is the connectivity-based parcellation framework of the human brain. The resulting visual pathway indicated that the putative pathway for the classical dorsal stream is unlikely to exist. Instead, we demonstrated that fiber connections exist between the angular gyrus with MT in the visual cortex, and between the angular gyrus and IT in the temporal cortex. Through that, we composed a two-pathway model for where-information processing that passes through the angular gyrus. Finally, we proposed a modified human visual pathway model based on our fiber tracking results in this report. The modified where-information pathway will provide a new aspect for the study of human visual processing.

Classifyber, a robust streamline-based linear classifier for white matter bundle segmentation

Virtual delineation of white matter bundles in the human brain is of paramount importance for multiple applications, such as pre-surgical planning and connectomics. A substantial body of literature is related to methods that automatically segment bundles from diffusion Magnetic Resonance Imaging (dMRI) data indirectly, by exploiting either the idea of connectivity between regions or the geometry of fiber paths obtained with tractography techniques, or, directly, through the information in volumetric data. Despite the remarkable improvement in automatic segmentation methods over the years, their segmentation quality is not yet satisfactory, especially when dealing with datasets with very diverse characteristics, such as different tracking methods, bundle sizes or data quality. In this work, we propose a novel, supervised streamline-based segmentation method, called Classifyber, which combines information from atlases, connectivity patterns, and the geometry of fiber paths into a simple linear model. With a wide range of experiments on multiple datasets that span from research to clinical domains, we show that Classifyber substantially improves the quality of segmentation as compared to other state-of-the-art methods and, more importantly, that it is robust across very diverse settings. We provide an implementation of the proposed method as open source code, as well as web service.

Identification of a distinct association fiber tract "IPS-FG" to connect the intraparietal sulcus areas and fusiform gyrus by white matter dissection and tractography

The intraparietal sulcus (IPS) in the posterior parietal cortex (PPC) is well-known as an interface for sensorimotor integration in visually guided actions. However, our understanding of the human neural network between the IPS and the cortical visual areas has been devoid of anatomical specificity. We here identified a distinctive association fiber tract “IPS-FG” to connect the IPS areas and the fusiform gyrus (FG), a high-level visual region, by white matter dissection and tractography. The major fiber bundles of this tract appeared to arise from the medial bank of IPS, in the superior parietal lobule (SPL), and project to the FG on the ventral temporal cortex (VTC) in post-mortem brains. This tract courses vertically at the temporo-parieto-occipital (TPO) junction where several fiber tracts intersect to connect the dorsal-to-ventral cortical regions, including the vertical occipital fasciculus (VOF). We then analyzed the structural connectivity of this tract with diffusion-MRI (magnetic resonance imaging) tractography. The quantitative tractography analysis revealed the major streamlines of IPS-FG interconnect the posterior IPS areas (e.g., IP1, IPS1) with FG (e.g., TF, FFC, VVC, PHA2, PIT) on the Human Connectome Project multimodal parcellation atlas (HCP MMP 1.0). Since the fronto-parietal network, including the posterior IPS areas, is recruited by multiple cognitive demands, the IPS-FG could play a role in the visuomotor integration as well as the top-down modulation of various cognitive functions reciprocally.

Anatomy of nerve fiber bundles at micrometer-resolution in the vervet monkey visual system

Although the primate visual system has been extensively studied, detailed spatial organization of white matter fiber tracts carrying visual information between areas has not been fully established. This is mainly due to the large gap between tracer studies and diffusion-weighted MRI studies, which focus on specific axonal connections and macroscale organization of fiber tracts, respectively. Here we used 3D polarization light imaging (3D-PLI), which enables direct visualization of fiber tracts at micrometer resolution, to identify and visualize fiber tracts of the visual system, such as stratum sagittale, inferior longitudinal fascicle, vertical occipital fascicle, tapetum and dorsal occipital bundle in vervet monkey brains. Moreover, 3D-PLI data provide detailed information on cortical projections of these tracts, distinction between neighboring tracts, and novel short-range pathways. This work provides essential information for interpretation of functional and diffusion-weighted MRI data, as well as revision of wiring diagrams based upon observations in the vervet visual system.

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.

Spatial organization of occipital white matter tracts in the common marmoset

The primate brain contains a large number of interconnected visual areas, whose spatial organization and intracortical projections show a high level of conservation across species. One fiber pathway of recent interest is the vertical occipital fasciculus (VOF), which is thought to support communication between dorsal and ventral visual areas in the occipital lobe. A recent comparative diffusion MRI (dMRI) study reported that the VOF in the macaque brain bears a similar topology to that of the human, running superficial and roughly perpendicular to the optic radiation. The present study reports a comparative investigation of the VOF in the common marmoset, a small New World monkey whose lissencephalic brain is approximately tenfold smaller than the macaque and 150-fold smaller than the human. High-resolution ex vivo dMRI of two marmoset brains revealed an occipital white matter structure that closely resembles that of the larger primate species, with one notable difference. Namely, unlike in the macaque and the human, the VOF in the marmoset is spatially fused with other, more anterior vertical tracts, extending anteriorly between the parietal and temporal cortices. We compare several aspects of this continuous structure, which we term the VOF complex (VOF +), and neighboring fasciculi to those of macaques and humans. We hypothesize that the essential topology of the VOF+ is a conserved feature of the posterior cortex in anthropoid primates, with a clearer fragmentation into multiple named fasciculi in larger, more gyrified brains.

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.

The visual word form area (VWFA) is part of both language and attention circuitry

While predominant models of visual word form area (VWFA) function argue for its specific role in decoding written language, other accounts propose a more general role of VWFA in complex visual processing. However, a comprehensive examination of structural and functional VWFA circuits and their relationship to behavior has been missing. Here, using high-resolution multimodal imaging data from a large Human Connectome Project cohort (N = 313), we demonstrate robust patterns of VWFA connectivity with both canonical language and attentional networks. Brain-behavior relationships revealed a striking pattern of double dissociation: structural connectivity of VWFA with lateral temporal language network predicted language, but not visuo-spatial attention abilities, while VWFA connectivity with dorsal fronto-parietal attention network predicted visuo-spatial attention, but not language abilities. Our findings support a multiplex model of VWFA function characterized by distinct circuits for integrating language and attention, and point to connectivity-constrained cognition as a key principle of human brain organization.

Mapping the human middle longitudinal fasciculus through a focused anatomo-imaging study: shifting the paradigm of its segmentation and connectivity pattern

Τhe middle longitudinal fasciculus (MdLF) was initially identified in humans as a discrete subcortical pathway connecting the superior temporal gyrus (STG) to the angular gyrus (AG). Further anatomo-imaging studies, however, proposed more sophisticated but conflicting connectivity patterns and have created a vague perception on its functional anatomy. Our aim was, therefore, to investigate the ambiguous structural architecture of this tract through focused cadaveric dissections augmented by a tailored DTI protocol in healthy participants from the Human Connectome dataset. Three segments and connectivity patterns were consistently recorded: the MdLF-I, connecting the dorsolateral Temporal Pole (TP) and STG to the Superior Parietal Lobule/Precuneus, through the Heschl's gyrus; the MdLF-II, connecting the dorsolateral TP and the STG with the Parieto-occipital area through the posterior transverse gyri and the MdLF-III connecting the most anterior part of the TP to the posterior border of the occipital lobe through the AG. The lack of an established termination pattern to the AG and the fact that no significant leftward asymmetry is disclosed tend to shift the paradigm away from language function. Conversely, the theory of "where" and "what" auditory pathways, the essential relationship of the MdLF with the auditory cortex and the functional role of the cortical areas implicated in its connectivity tend to shift the paradigm towards auditory function. Allegedly, the MdLF-I and MdLF-II segments could underpin the perception of auditory representations; whereas, the MdLF-III could potentially subserve the integration of auditory and visual information.