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Background: The salience network (SN) is a transitory mediator between active and passive states of mind. Multiple cortical areas, including the opercular, insular, and cingulate cortices have been linked in this processing, though knowledge of network connectivity has been devoid of structural specificity. Objective: The current study sought to create an anatomically specific connectivity model of the neural substrates involved in the salience network. Methods: A literature search of PubMed and BrainMap Sleuth was conducted for resting‐state and task‐based fMRI studies relevant to the salience network according to PRISMA guidelines. Publicly available meta‐analytic software was utilized to extract relevant fMRI data for the creation of an activation likelihood estimation (ALE) map and relevant parcellations from the human connectome project overlapping with the ALE data were identified for inclusion in our SN model. DSI‐based fiber tractography was then performed on publicaly available data from healthy subjects to determine the structural connections between cortical parcellations comprising the network. Results: Nine cortical regions were found to comprise the salience network: areas AVI (anterior ventral insula), MI (middle insula), FOP4 (frontal operculum 4), FOP5 (frontal operculum 5), a24pr (anterior 24 prime), a32pr (anterior 32 prime), p32pr (posterior 32 prime), and SCEF (supplementary and cingulate eye field), and 46. The frontal aslant tract was found to connect the opercular‐insular cluster to the middle cingulate clusters of the network, while mostly short U‐fibers connected adjacent nodes of the network. Conclusion: Here we provide an anatomically specific connectivity model of the neural substrates involved in the salience network. These results may serve as an empiric basis for clinical translation in this region and for future study which seeks to expand our understanding of how specific neural substrates are involved in salience processing and guide subsequent human behavior. [ABSTRACT FROM AUTHOR]

Introduction. The ventral premotor area (VPM) plays a crucial role in executing various aspects of motor control. These include hand reaching, joint coordination, and direction of movement in space. While many studies discuss the VPM and its relationship to the rest of the motor network, there is minimal literature examining the connectivity of the VPM outside of the motor network. Using region-based fMRI studies, we built a neuroanatomical model to account for these extra-motor connections. Methods. Thirty region-based fMRI studies were used to generate an activation likelihood estimation (ALE) using BrainMap software. Cortical parcellations overlapping the ALE were used to construct a preliminary model of the VPM connections outside the motor network. Diffusion spectrum imaging (DSI)-based fiber tractography was performed to determine the connectivity between cortical parcellations in both hemispheres, and a laterality index (LI) was calculated with resultant tract volumes. The resulting connections were described using the cortical parcellation scheme developed by the Human Connectome Project (HCP). Results. Four cortical regions were found to comprise the VPM. These four regions included 6v, 4, 3b, and 3a. Across mapped brains, these areas showed consistent interconnections between each other. Additionally, ipsilateral connections to the primary motor cortex, supplementary motor area, and dorsal premotor cortex were demonstrated. Inter-hemispheric asymmetries were identified, especially with areas 1, 55b, and MI connecting to the ipsilateral VPM regions. Conclusion. We describe a preliminary cortical model for the underlying connectivity of the ventral premotor area. Future studies should further characterize the neuroanatomic underpinnings of this network for neurosurgical applications. [ABSTRACT FROM AUTHOR]

Purpose: White matter tracts link different regions of the brain, and the known functions of those interconnected regions may offer clues about the roles that white matter tracts play in information relay. The authors of this report discuss the structure and function of the lateral occipital lobe and how the lateral occipital lobe communicates with other regions via white matter tracts. Methods: The authors used generalized q-sampling imaging and cadaveric brain dissections to uncover the subcortical white matter connections of the lateral occipital lobe. The authors created GQI of ten healthy controls and dissected ten cadaveric brains. Results: The middle longitudinal fasciculus, vertical occipital fasciculus, inferior fronto-occipital fasciculus, inferior longitudinal fasciculus, optic radiations, and a diverse array of U-shaped fibers connect the lateral occipital lobe to itself, parts of the temporal, parietal, and medial occipital cortices. The complex functional processes attributed to the lateral occipital lobe, including object recognition, facial recognition, and motion perception are likely related to the subcortical white matter tracts described within this study. Conclusions: There was good concordance between the white matter tracts generated using GQI and the white matter tracts that were found after dissection of the cadaveric brains. This article presents the anatomic connections of the lateral occipital lobe and discusses the associated functions. [ABSTRACT FROM AUTHOR]

Simple Summary: Connectomics enables us to map whole brain networks that can be applied to operative neurosurgery to improve neuro-oncological outcomes. Damage to the superior frontal gyrus during frontal lobe surgery is thought to induce supplementary motor area (SMA) syndrome in patients. However, network-based modeling may provide a more accurate cortical model of SMA syndrome, including the Frontal Aslant Tract (FAT). The aim of our study was to retrospectively assess if surgical tractography with diffusion tensor imaging (DTI) decreases the likelihood of SMA syndrome. Compared to patients who underwent surgery preserving the SFG (n = 23), patients who had their FAT and SMA networks mapped through DTI and subsequently preserved were less likely to experience transient SMA syndrome. Preserving the FAT and SMA improves functional outcomes in patients following medial frontal glioma surgery and demonstrates how network-based approaches can improve surgical outcomes. Connectomics is the use of big data to map the brain's neural infrastructure; employing such technology to improve surgical planning may improve neuro-oncological outcomes. Supplementary motor area (SMA) syndrome is a well-known complication of medial frontal lobe surgery. The 'localizationist' view posits that damage to the posteromedial bank of the superior frontal gyrus (SFG) is the basis of SMA syndrome. However, surgical experience within the frontal lobe suggests that this is not entirely true. In a study on n = 45 patients undergoing frontal lobe glioma surgery, we sought to determine if a 'connectomic' or network-based approach can decrease the likelihood of SMA syndrome. The control group (n = 23) underwent surgery avoiding the posterior bank of the SFG while the treatment group (n = 22) underwent mapping of the SMA network and Frontal Aslant Tract (FAT) using network analysis and DTI tractography. Patient outcomes were assessed post operatively and in subsequent follow-ups. Fewer patients (8.3%) in the treatment group experienced transient SMA syndrome compared to the control group (47%) (p = 0.003). There was no statistically significant difference found between the occurrence of permanent SMA syndrome between control and treatment groups. We demonstrate how utilizing tractography and a network-based approach decreases the likelihood of transient SMA syndrome during medial frontal glioma surgery. We found that not transecting the FAT and the SMA system improved outcomes which may be important for functional outcomes and patient quality of life. [ABSTRACT FROM AUTHOR]

The supplementary motor area (SMA) plays an important role in the initiation and coordination of internally and externally cued movements. Such movements include reaching, grasping, speaking, and bilateral hand coordination. While many studies discuss the SMA and its relationship to other parts of the motor network, there is minimal literature examining the connectivity of the SMA outside of the motor network. Using region-based fMRI studies, we built a neuroanatomical model to account for these extra-motor connections. Thirty region-based fMRI studies were used to generate an activation likelihood estimation (ALE) using BrainMap software. Cortical parcellations overlapping the ALE were used to construct a preliminary model of the SMA connections outside the motor network. DSI-based fiber tractography was performed to determine the connectivity between cortical parcellations. The resulting connections were described using the cortical parcellation scheme developed by the Human Connectome Project (HCP). Four left hemisphere regions were found to comprise the SMA. These included areas SFL, SCEF, 6ma, and 6mp. Across mapped brains, these areas showed consistent interconnections between each other. Additionally, ipsilateral connections to the primary motor cortex, left inferior and middle frontal gyri, the anterior cingulate gyrus, and insula were demonstrated. Connections to the contralateral SMA, anterior cingulate, lateral premotor, and inferior frontal cortices were also identified. We describe a preliminary cortical model for the underlying structural connectivity of the supplementary motor area outside the motor network. Future studies should further characterize the neuroanatomic underpinnings of this network for the purposes of medical application. • We built a neuroanatomical model to account for extra-motor connections of the SMA. • Thirty region-based fMRI studies were used to generate an ALE. • HCP parcellations overlapping the ALE constructed the preliminary model of the SMA. • Four regions, areas SFL, SCEF, 6ma, and 6mp were found to comprise the SMA. [ABSTRACT FROM AUTHOR]

The dorsal premotor area (DPM) plays an important role in hand coordination and muscle recruitment for lifting activities. Lesions in the area have demonstrated that the DPM is critical in the integration of movements that require combinations of reaching, grasping, and lifting. While many have looked at its functional connectivity, few studies have shown the full anatomical connectivity of DPM including its connections beyond the motor network. Using region-based fMRI studies, we built a neuroanatomical model to account for these extra-motor connections. In this study, we performed meta-analysis and tractography with the goal of creating a map of the dorsal premotor network using the Human Connectome Project parcellation scheme nomenclature (i.e. the Glasser Atlas). While there are other possible ways to map this, we feel that it is critical that neuroimaging begin to move towards all of its data expressed in a single nomenclature which can be compared across studies, and a potential framework that we can build upon in future studies. Thirty region-based fMRI studies were used to generate an activation likelihood estimation (ALE) using BrainMap software (Research Imaging Institute of Texas Health Science Center San Antonio). Cortical parcellations overlapping the ALE were used to construct a preliminary model of the Dorsal Premotor Area. Diffusion spectrum imaging (DSI) based tractography was performed to determine the connectivity between cortical parcellations and connections throughout cortex. The resulting connectivities were described using the cortical parcellation scheme developed by the Human Connectome Project (HCP). Three left hemisphere regions were found to comprise the Dorsal Premotor Area. These included areas 6a, 6d. and 6v, Across mapped brains, these areas showed consistent interconnections between each other. Additionally, ipsilateral connections to the premotor cortex, sensorimotor cortex, superior and inferior parietal lobule, middle and inferior frontal gyrus, and insula were demonstrated. Connections to the contralateral supplementary motor area and premotor cortex were also identified. We describe a preliminary cortical model for the underlying structural connectivity of the Dorsal Premotor Area. Future studies should further characterize the neuroanatomic underpinnings of this network. • Thirty region-based fMRI studies were analysed to create a map of the dorsal premotor network using the HCP nomenclature. • Three left hemisphere regions were found to comprise the Dorsal Premotor Area. These included areas 6a, 6d. and 6v. • We describe a preliminary cortical model for the underlying structural connectivity of the Dorsal Premotor Area. [ABSTRACT FROM AUTHOR]

The ventral attention network (VAN) is an important mediator of stimulus-driven attention. Multiple cortical areas, such as the middle and inferior frontal gyri, anterior insula, inferior parietal lobule, and temporo-parietal junction have been linked in this processing. However, knowledge of network connectivity has been devoid of structural specificity. Using relevant task-based fMRI studies, an activation likelihood estimation (ALE) of the VAN was generated Regions of interest corresponding to the HCP cortical parcellation scheme were co-registered onto this ALE in MNI coordinate space and visually assessed for inclusion in the network. DSI-based fiber tractography was performed to determine the structural connections between cortical areas comprising the VAN. Fourteen regions within the right cerebral hemisphere were found to overlap the ALE of the VAN: 6a, 6r, 7AM, 7PM, 8C, AVI, FOP4, MIP, p9-46v, PCV, PFm, PGi, TPOJ1, and TPOJ2. Regions demonstrated consistent U-shaped interconnections between adjacent parcellations, and the SLF was found to connect frontal and parietal areas of the network. We present a tractographic model of the VAN. This model comprises parcellations within the frontal and parietal cortices that are linked via the SLF. Future studies may refine this model with the ultimate goal of clinical application. • The ventral attention network consists of 14 cortical parcellations. • These parcellations localize to the frontal and parietal lobes. • These parcellations are interconnected via U−fibers and the SLF. • Future studies will refine this network model for clinical application. [ABSTRACT FROM AUTHOR]

Graph theory is a promising mathematical tool to study the connectome. However, little research has been undertaken to correlate graph metrics to functional properties of the brain. In this study, we report a unique association between the strength of cortical regions and their function. Eight structural graphs were constructed within DSI Studio using publicly available imaging data derived from the Human Connectome Project. Whole-brain fiber tractography was performed to quantify the strength of each cortical region comprising our atlas. Rank-order analysis revealed 27 distinct areas with high average strength, several of which are associated with eloquent cortical functions. Area 4 localizes to the primary motor cortex and is important for fine motor control. Areas 2, 3a and 3b localize to the primary sensory cortex and are involved in primary sensory processing. Areas V1-V4 in the occipital pole are involved in primary visual processing. Several language areas, including area 44, were also found to have high average strength. Regions of average high strength tend to localize to eloquent areas of the brain, such as the primary sensorimotor cortex, primary visual cortex, and Broca's area. Future studies will examine the dynamic effects of neurologic disease on this metric. • Strength is a graph metric that quantifies the number of connections to a part of cortex. • Eight structural graphs were constructed in DSI Studio to measure regional strength. • Regions of high average strength appear to correlate with eloquent functions in the brain. [ABSTRACT FROM AUTHOR]

Introduction: The dorsal attention network (DAN) is an important mediator of goal‐directed attentional processing. Multiple cortical areas, such as the frontal eye fields, intraparietal sulcus, superior parietal lobule, and visual cortex, have been linked in this processing. However, knowledge of network connectivity has been devoid of structural specificity. Methods: Using attention‐related task‐based fMRI studies, an anatomic likelihood estimation (ALE) of the DAN was generated. Regions of interest corresponding to the cortical parcellation scheme previously published under the Human Connectome Project were co‐registered onto the ALE in MNI coordinate space and visually assessed for inclusion in the network. DSI‐based fiber tractography was performed to determine the structural connections between relevant cortical areas comprising the network. Results: Twelve cortical regions were found to be part of the DAN: 6a, 7AM, 7PC, AIP, FEF, LIPd, LIPv, MST, MT, PH, V4t, VIP. All regions demonstrated consistent u‐shaped interconnections between adjacent parcellations. The superior longitudinal fasciculus connects the frontal, parietal, and occipital areas of the network. Conclusions: We present a tractographic model of the DAN. This model comprises parcellations within the frontal, parietal, and occipital cortices principally linked through the superior longitudinal fasciculus. Future studies may refine this model with the ultimate goal of clinical application. [ABSTRACT FROM AUTHOR]

Objective: There is a body of evidence that supports the idea of a coordinated interplay between three large-scale cerebral networks, the default mode network (DMN), the control network (CTRL), and the salience network (SN). Interactions between these networks have been linked with the process of transitioning from internal to external mental states. Methods: Using meta-analytic software provided by BrainMap, we generated anatomic likelihood estimates (ALEs) of the DMN, SN, and CTRL networks. ALEs were displayed using Mango. Pre-constructed Region of Interests(ROIs) corresponding to the 180 cerebral parcellations published under the Human Connectome Project were used to identify the parcellations comprising each network. DSI-based fiber tracking was performed to establish the connectivity between parcellations of each network. Results: The DMN includes parcellations that localize to the posterior and anterior cingulate cortex and inferior parietal lobule. The CTRL network localizes to the dorsolateral prefrontal cortex and lateral parietal lobe. The SN localizes to the middle cingulate cortex and anterior insula. The SN also connects to SCEF, a parcellation in the supplementary motor area. Conclusion: The DMN is a well-known resting-state network that is anti-correlated with the CTRL network. The SN has been described as the switch between these two networks. The SN's connection to SCEF may explain how the brain prepares for proposed activity during such transfers. We propose models of three critical brain networks that play a role in the transition from internal to external mental states. Future studies will refine these models of the command-and-control axis for clinical application. [ABSTRACT FROM AUTHOR]

Objective: The Inferior Longitudinal Fasciculus (ILF) is one of the major white matter tract bundles connecting key cortical areas of the cerebrum. The location, functional connectivity, and structural connectivity of the cortical regions giving rise to the ILF have previously been described. Using these data we demonstrate the extent and anatomical boundaries of the ILF. Methods: We built an anatomic model of the ILF based on the parcellation scheme previously published under the Human Connectome Project. Through Diffusion Spectrum Imaging, we demonstrate the tractography of this fasciculus arising from its relevant cortical regions, and show a tract map summarizing those regions with white matter connections specific to the ILF. Results: The ILF extends from the ventral and lateral temporal cortices to parts of the occipital lobe. Seven parcellations of the temporal lobe and one from the posterior parietal lobe demonstrate structural connectivity in the distribution of the ILF. Most demonstrate fiber tracts via the ILF to early visual areas, V1-V4. Conclusion: The literature describes several critical functions to the ILF including visual processing, object recognition, reading disturbance, emotional processing, facial recognition, ventral semantic processing, visual hallucinations, and arithmetic. Precisely what cortical information is integrated and transferred from the occipital lobe to areas of the temporal and parietal lobes remains poorly understood. Our connection model of the ILF is one step forward towards elucidating these processes. We show the anatomic connections of the ILF and define the cortical regions from which the ILF arises. Future studies will refine this model for clinical application. [ABSTRACT FROM AUTHOR]

Abstract: Introduction: Supplementary motor area (SMA) syndrome is a constellation of temporary symptoms that may occur following tumors of the frontal lobe. Affected patients develop akinesia and mutism but often recover within weeks to months. With our own case examples and with correlations to fiber tracking validated by gross anatomical dissection as ground truth, we describe a white matter pathway through which recovery may occur. Methods: Diffusion spectrum imaging from the Human Connectome Project was used for tractography analysis. SMA outflow tracts were mapped in both hemispheres using a predefined seeding region. Postmortem dissections of 10 cadaveric brains were performed using a modified Klingler technique to verify the tractography results. Results: Two cases were identified in our clinical records in which patients sustained permanent SMA syndrome after complete disconnection of the SMA and corpus callosum (CC). After investigating the postoperative anatomy of these resections, we identified a pattern of nonhomologous connections through the CC connecting the premotor area to the contralateral premotor and SMAs. The transcallosal fibers have projections from the previously described frontal aslant tract (FAT) and thus, we have termed this path the “crossed FAT.” Conclusions: We hypothesize that this newly described tract may facilitate recovery from SMA syndrome by maintaining interhemispheric connectivity through the supplementary motor and premotor areas. [ABSTRACT FROM AUTHOR]

Background and Purpose: Mapping the topology of the visual system is critical for understanding how complex cognitive processes like reading can occur. We aim to describe the connectivity of the visual system to understand how the cerebrum accesses visual information in the lateral occipital lobe. Methods: Using meta‐analytic software focused on task‐based functional MRI studies, an activation likelihood estimation (ALE) of the visual network was created. Regions of interest corresponding to the cortical parcellation scheme previously published under the Human Connectome Project were co‐registered onto the ALE to identify the hub‐like regions of the visual network. Diffusion Spectrum Imaging‐based fiber tractography was performed to determine the structural connectivity of these regions with extraoccipital cortices. Results: The fundus of the superior temporal sulcus (FST) and parietal area H (PH) were identified as hub‐like regions for the visual network. FST and PH demonstrated several areas of coactivation beyond the occipital lobe and visual network. Furthermore, these parcellations were highly interconnected with other cortical regions throughout extraoccipital cortices related to their nonvisual functional roles. A cortical model demonstrating connections to these hub‐like areas was created. Conclusions: FST and PH are two hub‐like areas that demonstrate extensive functional coactivation and structural connections to nonvisual cerebrum. Their structural interconnectedness with language cortices along with the abnormal activation of areas commonly located in the temporo‐occipital region in dyslexic individuals suggests possible important roles of FST and PH in the integration of information related to language and reading. Future studies should refine our model by examining the functional roles of these hub areas and their clinical significance. [ABSTRACT FROM AUTHOR]

The medial occipital lobe, composed of the lingual gyrus and cuneus, is necessary for both basic and higher level visual processing. It is also known to facilitate cross-modal, nonvisual functions, such as linguistic processing and verbal memory, after the loss of the visual senses. A detailed cortical model elucidating the white matter connectivity associated with this area could improve our understanding of the interacting brain networks that underlie complex human processes and postoperative outcomes related to vision and language. Generalized q-sampling imaging tractography, validated by gross anatomic dissection for qualitative visual agreement, was performed on 10 healthy adult controls obtained from the Human Connectome Project. Major white matter connections were identified by tractography and validated by gross dissection, which connected the medial occipital lobe with itself and the adjacent cortices, especially the temporal lobe. The short- and long-range connections identified consisted mainly of U-shaped association fibers, intracuneal fibers, and inferior fronto-occipital fasciculus, inferior longitudinal fasciculus, middle longitudinal fasciculus, and lingual–fusiform connections. The medial occipital lobe is an extremely interconnected system, supporting its ability to perform coordinated basic visual processing, but also serves as a center for many long-range association fibers, supporting its importance in nonvisual functions, such as language and memory. The presented data represent clinically actionable anatomic information that can be used in multimodal navigation of white matter lesions in the medial occipital lobe to prevent neurologic deficits and improve patients' quality of life after cerebral surgery. [ABSTRACT FROM AUTHOR]

The parahippocampal gyrus is understood to have a role in high cognitive functions including memory encoding and retrieval and visuospatial processing. A detailed understanding of the exact location and nature of associated white tracts could significantly improve postoperative morbidity related to declining capacity. Through diffusion tensor imaging−based fiber tracking validated by gross anatomic dissection as ground truth, we have characterized these connections based on relationships to other well-known structures. Diffusion imaging from the Human Connectome Project for 10 healthy adult controls was used for tractography analysis. We evaluated the parahippocampal gyrus as a whole based on connectivity with other regions. All parahippocampal gyrus tracts were mapped in both hemispheres, and a lateralization index was calculated with resultant tract volumes. We identified 2 connections of the parahippocampal gyrus: inferior longitudinal fasciculus and cingulum. Lateralization of the cingulum was detected (P < 0.05). The parahippocampal gyrus is an important center for memory processing. Subtle differences in executive functioning following surgery for limbic tumors may be better understood in the context of the fiber-bundle anatomy highlighted by this study. [ABSTRACT FROM AUTHOR]

Introduction: The semantic network is an important mediator of language, enabling both speech production and the comprehension of multimodal stimuli. A major challenge in the field of neurosurgery is preventing semantic deficits. Multiple cortical areas have been linked to semantic processing, though knowledge of network connectivity has lacked anatomic specificity. Using attentional task‐based fMRI studies, we built a neuroanatomical model of this network. Methods: One hundred and fifty‐five task‐based fMRI studies related to categorization of visual words and objects, and auditory words and stories were used to generate an activation likelihood estimation (ALE). Cortical parcellations overlapping the ALE were used to construct a preliminary model of the semantic network based on the cortical parcellation scheme previously published under the Human Connectome Project. Deterministic fiber tractography was performed on 25 randomly chosen subjects from the Human Connectome Project, to determine the connectivity of the cortical parcellations comprising the network. Results: The ALE analysis demonstrated fourteen left hemisphere cortical regions to be a part of the semantic network: 44, 45, 55b, IFJa, 8C, p32pr, SFL, SCEF, 8BM, STSdp, STSvp, TE1p, PHT, and PBelt. These regions showed consistent interconnections between parcellations. Notably, the anterior temporal pole, a region often implicated in semantic function, was absent from our model. Conclusions: We describe a preliminary cortical model for the underlying structural connectivity of the semantic network. Future studies will further characterize the neurotractographic details of the semantic network in the context of medical application. [ABSTRACT FROM AUTHOR]

Background: The default mode network (DMN) is an important mediator of passive states of mind. Multiple cortical areas, such as the anterior cingulate cortex, posterior cingulate cortex, and lateral parietal lobe, have been linked in this processing, though knowledge of network connectivity had limited tractographic specificity. Methods: Using resting‐state fMRI studies related to the DMN, we generated an activation likelihood estimation (ALE). We built a tractographical model of this network based on the cortical parcellation scheme previously published under the Human Connectome Project. DSI‐based fiber tractography was performed to determine the structural connections between cortical parcellations comprising the network. Results: Seventeen cortical regions were found to be part of the DMN: 10r, 31a, 31pd, 31pv, a24, d23ab, IP1, p32, POS1, POS2, RSC, PFm, PGi, PGs, s32, TPOJ3, and v23ab. These regions showed consistent interconnections between adjacent parcellations, and the cingulum was found to connect the anterior and posterior cingulate clusters within the network. Conclusions: We present a preliminary anatomic model of the default mode network. Further studies may refine this model with the ultimate goal of clinical application. [ABSTRACT FROM AUTHOR]

The inferior temporal gyrus (ITG) is known to be involved in high-cognitive functions, including visual and language comprehensions and emotion regulation. A detailed understanding of the nature of association fibers could significantly improve postoperative morbidity related to declining capacity. Through diffusion spectrum imaging−based fiber tracking, we have characterized these connections on the basis of their relationships to other cortical areas. Diffusion spectrum images from 10 healthy adults of the Human Connectome Project were randomly selected and used for tractography analysis. We evaluated the ITG as a whole based on connectivity with other regions. All ITG tracts were mapped in both hemispheres, and a lateralization index was calculated with resultant tract volumes. We identified 5 major connections of the ITG: U-fiber, inferior longitudinal fasciculus, vertical occipital fasciculus, arcuate fasciculus, and uncinate fasciculus. There was no fiber lateralization detected. This study highlights the principal white-matter pathways of the ITG and demonstrates key underlying connections. We present a summary of the relevant clinical anatomy for this region of the cerebrum as part of a larger effort to understand it in its entirety. [ABSTRACT FROM AUTHOR]

Introduction Interest in the function of the inferior parietal lobule (IPL) has resulted in increased understanding of its involvement in visuospatial and cognitive functioning, and its role in semantic networks. A basic understanding of the nuanced white-matter anatomy in this region may be useful in improving outcomes when operating in this region of the brain. We sought to derive the surgical relationship between the IPL and underlying major white-matter bundles by characterizing macroscopic connectivity. Methods Data of 10 healthy adult controls from the Human Connectome Project were used for tractography analysis. All IPL connections were mapped in both hemispheres, and distances were recorded between cortical landmarks and major tracts. Ten postmortem dissections were then performed using a modified Klingler technique to serve as ground truth. Results We identified three major types of connections of the IPL. (1) Short association fibers connect the supramarginal and angular gyri, and connect both of these gyri to the superior parietal lobule. (2) Fiber bundles from the IPL connect to the frontal lobe by joining the superior longitudinal fasciculus near the termination of the Sylvian fissure. (3) Fiber bundles from the IPL connect to the temporal lobe by joining the middle longitudinal fasciculus just inferior to the margin of the superior temporal sulcus. Conclusions We present a summary of the relevant anatomy of the IPL as part of a larger effort to understand the anatomic connections of related networks. This study highlights the principle white-matter pathways and highlights key underlying connections. [ABSTRACT FROM AUTHOR]

• An auditory network model was created based on the Human Connectome Project scheme. • A meta-analysis of task-based functional MRI studies were used to create the model. • Structural connections were identified by diffusion spectrum MRI-based tractography. • Fifteen cortical regions were found to form a part of the auditory network model. • These regions showed consistent interconnections between adjacent parcellations. The auditory network plays an important role in interaction with the environment. Multiple cortical areas, such as the inferior frontal gyrus, superior temporal gyrus and adjacent insula have been implicated in this processing. However, understanding of this network's connectivity has been devoid of tractography specificity. Using attention task-based functional magnetic resonance imaging (MRI) studies, an activation likelihood estimation (ALE) of the auditory network was generated. Regions of interest corresponding to the cortical parcellation scheme previously published under the Human Connectome Project were co-registered onto the ALE in the Montreal Neurological Institute coordinate space, and visually assessed for inclusion in the network. Diffusion spectrum MRI-based fiber tractography was performed to determine the structural connections between cortical parcellations comprising the network. Fifteen cortical regions were found to be part of the auditory network: areas 44 and 8C, auditory area 1, 4, and 5, frontal operculum area 4, the lateral belt, medial belt and parabelt, parietal area F centromedian, perisylvian language area, retroinsular cortex, supplementary and cingulate eye field and the temporoparietal junction area 1. These regions showed consistent interconnections between adjacent parcellations. The frontal aslant tract was found to connect areas within the frontal lobe, while the arcuate fasciculus was found to connect the frontal and temporal lobe, and subcortical U-fibers were found to connect parcellations within the temporal area. Further studies may refine this model with the ultimate goal of clinical application. [ABSTRACT FROM AUTHOR]