Anatomical Connectivity Patterns Research Articles

Diverse and asymmetric patterns of single-neuron projectome in regulating interhemispheric connectivity

The corpus callosum, historically considered primarily for homotopic connections, supports many heterotopic connections, indicating complex interhemispheric connectivity. Understanding this complexity is crucial yet challenging due to diverse cell-specific wiring patterns. Here, we utilized public AAV bulk tracing and single-neuron tracing data to delineate the anatomical connection patterns of mouse brains and conducted wide-field calcium imaging to assess functional connectivity across various brain states in male mice. The single-neuron data uncovered complex and dense interconnected patterns, particularly for interhemispheric-heterotopic connections. We proposed a metric “heterogeneity” to quantify the complexity of the connection patterns. Computational modeling of these patterns suggested that the heterogeneity of upstream projections impacted downstream homotopic functional connectivity. Furthermore, higher heterogeneity observed in interhemispheric-heterotopic projections would cause lower strength but higher stability in functional connectivity than their intrahemispheric counterparts. These findings were corroborated by our wide-field functional imaging data, underscoring the important role of heterotopic-projection heterogeneity in interhemispheric communication.

The human mediodorsal thalamus: Organization, connectivity, and function

The human mediodorsal thalamic nucleus (MD) is crucial for higher cognitive functions, while the fine anatomical organization of the MD and the function of each subregion remain elusive. In this study, using high-resolution data provided by the Human Connectome Project, an anatomical connectivity-based method was adopted to unveil the topographic organization of the MD. Four fine-grained subregions were identified in each hemisphere, including the medial (MDm), central (MDc), dorsal (MDd), and lateral (MDl), which recapitulated previous cytoarchitectonic boundaries from histological studies. The subsequent connectivity analysis of the subregions also demonstrated distinct anatomical and functional connectivity patterns, especially with the prefrontal cortex. To further evaluate the function of MD subregions, partial least squares analysis was performed to examine the relationship between different prefrontal-subregion connectivity and behavioral measures in 1012 subjects. The results showed subregion-specific involvement in a range of cognitive functions. Specifically, the MDm predominantly subserved emotional-cognition domains, while the MDl was involved in multiple cognitive functions especially cognitive flexibility and inhibition. The MDc and MDd were correlated with fluid intelligence, processing speed, and emotional cognition. In conclusion, our work provides new insights into the anatomical and functional organization of the MD and highlights the various roles of the prefrontal-thalamic circuitry in human cognition.

Anatomical and functional coupling between the dorsal and ventral attention networks

Studies have indicated that the dorsal attention network (DAN) and the ventral attention network (VAN) functionally interact via several fronto-parietal connector hubs. However, the anatomical connectivity profiles of these connector hubs, and the coupling between the anatomical and functional connectivities of them, are still unknown. In the present study, we found that functional connector hubs anatomically bridged the DAN and VAN based on multimodal magnetic resonance imaging data from the Human Connectome Project (HCP) Consortium and an independent Chinese cohort. The three hubs had unique anatomical connectivity patterns with the attention sub-networks. For each connector hub, the pattern of anatomical connectivity resembled the functional one. Finally, the strength of the anatomical connectivity of these connector hubs was positively associated with the functional connectivity at the group- and individual-levels. Our findings help to better understand the anatomical mechanisms underlying the functional interactions between the DAN and the VAN.

Organization of Afferents along the Anterior–posterior and Medial–lateral Axes of the Rat Orbitofrontal Cortex

The orbitofrontal cortex (OFC) has been anatomically divided into a number of subregions along its medial–lateral axis, which behavioral research suggests have distinct functions. Recently, evidence has emerged suggesting functional diversity is also present along the anterior–posterior axis of the rodent OFC. However, the patterns of anatomical connections that underlie these differences have not been well characterized. Here, we use the retrograde tracer cholera toxin subunit B (CTB) to simultaneously label the projections into the anterior lateral (ALO), posterior lateral (PLO), and posterior ventral (PVO) portions of the rat OFC. Our methodological approach allowed us to simultaneously compare the density and input patterns into these OFC subdivisions. We observed distinct and topographically organized projection patterns into ALO, PLO, and PVO from the mediodorsal and the submedius nuclei of the thalamus. We also observed different levels of connectivity strength into these OFC subdivisions from the amygdala, motor cortex, sensory cortices and medial prefrontal cortical structures, including medial OFC, infralimbic and prelimbic cortices. Interestingly, while labelling in some of these input regions revealed only a gradient in connectivity strength, other regions seem to project almost exclusively to specific OFC subdivisions. Moreover, differences in input patterns between ALO and PLO were as pronounced as those between PLO and PVO. Together, our results support the existence of distinct anatomical circuits within lateral OFC along its anterior–posterior axis.

New Insights Into the Anatomy, Connectivity and Clinical Implications of the Middle Longitudinal Fasciculus.

The middle longitudinal fascicle (MdLF) is a long, associative white matter tract connecting the superior temporal gyrus (STG) with the parietal and occipital lobe. Previous studies show different cortical terminations, and a possible segmentation pattern of the tract. In this study, we performed a post-mortem white matter dissection of 12 human hemispheres and an in vivo deterministic fiber tracking of 24 subjects acquired from the Human Connectome Project to establish whether a constant organization of fibers exists among the MdLF subcomponents and to acquire anatomical information on each subcomponent. Moreover, two clinical cases of brain tumors impinged on MdLF territories are reported to further discuss the anatomical results in light of previously published data on the functional involvement of this bundle. The main finding is that the MdLF is consistently organized into two layers: an antero-ventral segment (aMdLF) connecting the anterior STG (including temporal pole and planum polare) and the extrastriate lateral occipital cortex, and a posterior-dorsal segment (pMdLF) connecting the posterior STG, anterior transverse temporal gyrus and planum temporale with the superior parietal lobule and lateral occipital cortex. The anatomical connectivity pattern and quantitative differences between the MdLF subcomponents along with the clinical cases reported in this paper support the role of MdLF in high-order functions related to acoustic information. We suggest that pMdLF may contribute to the learning process associated with verbal-auditory stimuli, especially on left side, while aMdLF may play a role in processing/retrieving auditory information already consolidated within the temporal lobe.

Temporal-thalamic and cingulo-opercular connectivity in people with schizophrenia

A growing body of research has suggested that people with schizophrenia (SZ) exhibit altered patterns of functional and anatomical brain connectivity. For example, many previous resting state functional connectivity (rsFC) studies have shown that, compared to healthy controls (HC), people with SZ demonstrate hyperconnectivity between subregions of the thalamus and sensory cortices, as well as hypoconnectivity between subregions of the thalamus and prefrontal cortex. In addition to thalamic findings, hypoconnectivity between cingulo-opercular brain regions thought to be involved in salience detection has also been commonly reported in people with SZ. However, previous studies have largely relied on seed-based analyses. Seed-based approaches require researchers to define a single a priori brain region, which is then used to create a rsFC map across the entire brain. While useful for testing specific hypotheses, these analyses are limited in that only a subset of connections across the brain are explored. In the current manuscript, we leverage novel network statistical techniques in order to detect latent functional connectivity networks with organized topology that successfully differentiate people with SZ from HCs. Importantly, these techniques do not require a priori seed selection and allow for whole brain investigation, representing a comprehensive, data-driven approach to determining differential connectivity between diagnostic groups. Across two samples, (Sample 1: 35 SZ, 44 HC; Sample 2: 65 SZ, 79 HC), we found evidence for differential rsFC within a network including temporal and thalamic regions. Connectivity in this network was greater for people with SZ compared to HCs. In the second sample, we also found evidence for hypoconnectivity within a cingulo-opercular network of brain regions in people with SZ compared to HCs. In summary, our results replicate and extend previous studies suggesting hyperconnectivity between the thalamus and sensory cortices and hypoconnectivity between cingulo-opercular regions in people with SZ using data-driven statistical and graph theoretical techniques.

Randomly connected networks generate emergent selectivity and predict decoding properties of large populations of neurons.

Modern recording methods enable sampling of thousands of neurons during the performance of behavioral tasks, raising the question of how recorded activity relates to theoretical models. In the context of decision making, functional connectivity between choice-selective cortical neurons was recently reported. The straightforward interpretation of these data suggests the existence of selective pools of inhibitory and excitatory neurons. Computationally investigating an alternative mechanism for these experimental observations, we find that a randomly connected network of excitatory and inhibitory neurons generates single-cell selectivity, patterns of pairwise correlations, and the same ability of excitatory and inhibitory populations to predict choice, as in experimental observations. Further, we predict that, for this task, there are no anatomically defined subpopulations of neurons representing choice, and that choice preference of a particular neuron changes with the details of the task. We suggest that distributed stimulus selectivity and functional organization in population codes could be emergent properties of randomly connected networks.

Mapping mesoscale cortical connectivity in monkey sensorimotor cortex with optical imaging and microstimulation.

To map in vivo cortical circuitry at the mesoscale, we applied a novel approach to map interareal functional connectivity. Electrical intracortical microstimulation (ICMS) in conjunction with optical imaging of intrinsic signals (OIS) was used map functional connections in somatosensory cortical areas in anesthetized squirrel monkeys. ICMS produced activations that were focal and that displayed responses which were stimulation intensity dependent. ICMS in supragranular layers of Brodmann Areas 3b, 1, 2, 3a, and M1 evoked interareal activation patterns that were topographically appropriate and appeared consistent with known anatomical connectivity. Specifically, ICMS revealed Area 3b connections with Area 1; Area 1 connections with Areas 2 and 3a; Area 2 connections with Areas 1, 3a, and M1; Area 3a connections with Areas M1, 1, and 2; and M1 connections with Areas 3a, 1, and 2. These somatosensory connectivity patterns were reminiscent of feedforward patterns observed anatomically, although feedback contributions are also likely present. Further consistent with anatomical connectivity, intra-areal and intra-areal patterns of activation were patchy with patch sizes of 200-300 μm. In summary, ICMS with OIS is a novel approach for mapping interareal and intra-areal connections in vivo. Comparisons with feedforward and feedback anatomical connectivity are discussed.

Individualized Cortical Parcellation Based on Diffusion MRI Tractography.

The spatial topological properties of cortical regions vary across individuals. Connectivity-based functional and anatomical cortical mapping in individuals will facilitate research on structure-function relationships. However, individual-specific cortical topographic properties derived from anatomical connectivity are less explored than those based on functional connectivity. We aimed to develop a novel individualized anatomical connectivity-based parcellation framework and investigate individual differences in spatial topographic features of cortical regions using diffusion magnetic resonance imaging (dMRI) tractography. Using a high-quality, repeated-session dMRI dataset (42 subjects, 2 sessions per subject), cortical parcels were derived through in vivo anatomical connectivity-based parcellation. These individual-specific parcels demonstrated good within-individual reproducibility and reflected interindividual differences in anatomical brain organization. Connectivity in these individual-specific parcels was significantly more homogeneous than that based on the group atlas. We found that the position, size, and topography of these anatomical parcels were highly variable across individuals and demonstrated nonredundant information about individual differences. Finally, we found that intersubject variability in anatomical connectivity was correlated with the diversity of anatomical connectivity patterns. Overall, we identified cortical parcels that show homogeneous anatomical connectivity patterns. These parcels displayed marked intersubject spatial variability, which may be used in future functional studies to reveal structure-function relationships in the human brain.

The Connectivity Fingerprint of the Fusiform Gyrus Captures the Risk of Developing Autism in Infants with Tuberous Sclerosis Complex.

Tuberous sclerosis complex (TSC) is a rare genetic disorder characterized by benign tumors throughout the body; it is generally diagnosed early in life and has a high prevalence of autism spectrum disorder (ASD), making it uniquely valuable in studying the early development of autism, before neuropsychiatric symptoms become apparent. One well-documented deficit in ASD is an impairment in face processing. In this work, we assessed whether anatomical connectivity patterns of the fusiform gyrus, a central structure in face processing, capture the risk of developing autism early in life. We longitudinally imaged TSC patients at 1, 2, and 3 years of age with diffusion compartment imaging. We evaluated whether the anatomical connectivity fingerprint of the fusiform gyrus was associated with the risk of developing autism measured by the Autism Observation Scale for Infants (AOSI). Our findings suggest that the fusiform gyrus connectivity captures the risk of developing autism as early as 1year of age and provides evidence that abnormal fusiform gyrus connectivity increases with age. Moreover, the identified connections that best capture the risk of developing autism involved the fusiform gyrus and limbic and paralimbic regions that were consistent with the ASD phenotype, involving an increased number of left-lateralized structures with increasing age.

Delineating functional segregations of the human middle temporal gyrus with resting-state functional connectivity and coactivation patterns.

Although the middle temporal gyrus (MTG) has been parcellated into subregions with distinguished anatomical connectivity patterns, whether the structural topography of MTG can inform functional segregations of this area remains largely unknown. Accumulating evidence suggests that the brain's underlying organization and function can be directly and effectively delineated with resting‐state functional connectivity (RSFC) by identifying putative functional boundaries between cortical areas. Here, RSFC profiles were used to explore functional segregations of the MTG and defined four subregions from anterior to posterior in two independent datasets, which showed a similar pattern with MTG parcellation scheme obtained using anatomical connectivity. The functional segregations of MTG were further supported by whole brain RSFC, coactivation, and specific RFSC, and coactivation mapping. Furthermore, the fingerprint with predefined 10 networks and functional characterizations of each subregion using meta‐analysis also identified functional distinction between subregions. The specific connectivity analysis and functional characterization indicated that the bilateral most anterior subregions mainly participated in social cognition and semantic processing; the ventral middle subregions were involved in social cognition in left hemisphere and auditory processing in right hemisphere; the bilateral ventro‐posterior subregions participated in action observation, whereas the left subregion was also involved in semantic processing; both of the dorsal subregions in superior temporal sulcus were involved in language, social cognition, and auditory processing. Taken together, our findings demonstrated MTG sharing similar structural and functional topographies and provide more detailed information about the functional organization of the MTG, which may facilitate future clinical and cognitive research on this area.

Connectomics of neurodegeneration.

Misfolded protein aggregates are a classical hallmark of many neurodegenerative diseases. By combining a mouse model of misfolded protein injection and a brain network model of misfolded protein diffusion, a study now finds a strong link between the stereotypical spreading patterns of neurodegeneration, protein expression and anatomical connectivity.

Corresponding anatomical and coactivation architecture of the human precuneus showing similar connectivity patterns with macaques

The precuneus (PCun) is one of the most expanded areas of the association cortex and plays an important role in integrating information from different modalities. However, whether the functional architecture of PCun is shared by humans and macaques is an open question. We used both anatomical connectivity and task-dependent coactivation patterns to parcellate the human PCun and consistently identified three subregions in the human PCun using two independent datasets. Two subregions were located in the dorsal PCun and one subregion was located in the ventral PCun. This parcellation scheme for the PCun was supported by identifying the subregion-specific networks and by functional characterization. Then, the absolute and relative gray matter volume of precuneus in human and macaque was calculated and significantly smaller absolute and relative gray matter volume in macaque was identified. Next, three macaque PCun subregions were defined based on our tractographic atlas. Finally, the whole brain anatomical connectivity patterns and connectivity fingerprints with 17 predefined homologous target brain areas were mapped for each PCun subregion and revealed that the PCun shares similar anatomical connectivity patterns in humans and macaques. The similar anatomical connectivity patterns of PCun were validated by an independent in-house dataset. Our findings demonstrated that anatomical connectivity patterns can reflect the functional architecture of the PCun in humans and that the functional architecture of the PCun is similar in humans and macaques.

Dysregulation of resting-state functional connectivity in patients with Cushing's disease.

To explore the anatomical distance-dependent functional connectivity patterns in patients with active phase of Cushing's disease (CD) and to evaluate the associations between hypercortisol exposure and regional normalized functional connectivity strengths (nFCSs). Based on the fMRI data in 32 CD patients and 32 healthy controls (HCs), we computed the nFCSs for each voxel in the brain and further divided them into long-range and short-range nFCSs. General linear models was used to investigate between-group differences in these nFCS metrics and the correlations between the nFCSs and clinical variables. Compared with HC, CD patients showed dysregulation of the nFCSs mainly in the default mode network. They showed an overall higher nFCS in bilateral parahippocampal cortex mainly owing to the disruption of long-range nFCS and a relatively lower nFCS in bilateral posterior cingulate cortex (PCC), bilateral lateral parietal cortex (LP), and right prefrontal cortex (PFC). In addition, their long-range nFCS was lower in the bilateral anterior cingulate cortex, PCC, and LP; short-range nFCS was lower in the bilateral PFC. Notably, the positive correlation between the nFCSs in their right parahippocampal cortex and serum cortisol levels at 08:00 remained significant after taking the anatomical distance into consideration. The discrepant functional connectivity patterns found in our study indicated a hypercortisol-associated, distance-dependent disruption of resting-state functional connectivity in patients with active CD. We provide novel insights into the impacts of hypercortisol exposure and the pathophysiologic mechanisms of CD, which may facilitate advances in CD intervention ultimately.

Exploiting Gene Expression Profiles for the Automated Prediction of Connectivity between Brain Regions.

The brain comprises a complex system of neurons interconnected by an intricate network of anatomical links. While recent studies demonstrated the correlation between anatomical connectivity patterns and gene expression of neurons, using transcriptomic information to automatically predict such patterns is still an open challenge. In this work, we present a completely data-driven approach relying on machine learning (i.e., neural networks) to learn the anatomical connection directly from a training set of gene expression data. To do so, we combined gene expression and connectivity data from the Allen Mouse Brain Atlas to generate thousands of gene expression profile pairs from different brain regions. To each pair, we assigned a label describing the physical connection between the corresponding brain regions. Then, we exploited these data to train neural networks, designed to predict brain area connectivity. We assessed our solution on two prediction problems (with three and two connectivity class categories) involving cortical and cerebellum regions. As demonstrated by our results, we distinguish between connected and unconnected regions with 85% prediction accuracy and good balance of precision and recall. In our future work we may extend the analysis to more complex brain structures and consider RNA-Seq data as additional input to our model.

Mixed Spatial and Movement Representations in the Primate Posterior Parietal Cortex.

The posterior parietal cortex (PPC) of humans and non-human primates plays a key role in the sensory and motor transformations required to guide motor actions to objects of interest in the environment. Despite decades of research, the anatomical and functional organization of this region is still a matter of contention. It is generally accepted that specialized parietal subregions and their functional counterparts in the frontal cortex participate in distinct segregated networks related to eye, arm and hand movements. However, experimental evidence obtained primarily from single neuron recording studies in non-human primates has demonstrated a rich mixing of signals processed by parietal neurons, calling into question ideas for a strict functional specialization. Here, we present a brief account of this line of research together with the basic trends in the anatomical connectivity patterns of the parietal subregions. We review, the evidence related to the functional communication between subregions of the PPC and describe progress towards using parietal neuron activity in neuroprosthetic applications. Recent literature suggests a role for the PPC not as a constellation of specialized functional subdomains, but as a dynamic network of sensorimotor loci that combine multiple signals and work in concert to guide motor behavior.

Distinct Anatomical Connectivity Patterns Differentiate Subdivisions of the Nonlemniscal Auditory Thalamus in Mice.

Systematic examination of the inputs and outputs of the nonlemniscal auditory thalamus will facilitate the functional elucidation of this complex structure in the central auditory system. In mice, comprehensive tracing studies that reveal the long-range connectivity of the nonlemniscal auditory thalamus are lacking. To this end, we used Cre-inducible anterograde and monosynaptic retrograde viruses in Calbindin-2A-dgCre-D and Calretinin-IRES-Cre mice, focusing on the differences across subdivisions of the nonlemniscal auditory thalamus. We found that, 1) the dorsal and medial parts of the auditory thalamus were predominantly connected to sensory processing centers, whereas the posterior intralaminar (PIN) and peripeduncular nucleus (PP) were additionally connected to emotion and motivation modulation centers; 2) ventral auditory cortical areas were the major source of cortical inputs for all subdivisions, and the PIN/PP received more inputs from cortical layer 5 than other subdivisions did; 3) deep layers of the superior colliculus and rostral part of the nonlemniscal inferior colliculus preferentially projected to the PIN/PP; and 4) compared with the dorsal auditory thalamus, the PIN/PP mainly innervated association cortices. In addition, new brain areas connected to the nonlemniscal auditory thalamus, mostly the PIN/PP, were identified. Our results suggested subdivision-specific function of the nonlemniscal auditory thalamus in sound processing.

Function-specific and Enhanced Brain Structural Connectivity Mapping via Joint Modeling of Diffusion and Functional MRI

A joint structural-functional brain network model is presented, which enables the discovery of function-specific brain circuits, and recovers structural connections that are under-estimated by diffusion MRI (dMRI). Incorporating information from functional MRI (fMRI) into diffusion MRI to estimate brain circuits is a challenging task. Usually, seed regions for tractography are selected from fMRI activation maps to extract the white matter pathways of interest. The proposed method jointly analyzes whole brain dMRI and fMRI data, allowing the estimation of complete function-specific structural networks instead of interactively investigating the connectivity of individual cortical/sub-cortical areas. Additionally, tractography techniques are prone to limitations, which can result in erroneous pathways. The proposed framework explicitly models the interactions between structural and functional connectivity measures thereby improving anatomical circuit estimation. Results on Human Connectome Project (HCP) data demonstrate the benefits of the approach by successfully identifying function-specific anatomical circuits, such as the language and resting-state networks. In contrast to correlation-based or independent component analysis (ICA) functional connectivity mapping, detailed anatomical connectivity patterns are revealed for each functional module. Results on a phantom (Fibercup) also indicate improvements in structural connectivity mapping by rejecting false-positive connections with insufficient support from fMRI, and enhancing under-estimated connectivity with strong functional correlation.

Diffusion Tensor Tractography Reveals Disrupted Structural Connectivity during Brain Aging

Brain aging is one of the most crucial biological processes that entail many physical, biological, chemical, and psychological changes, and also a major risk factor for most common neurodegenerative diseases. To improve the quality of life for the elderly, it is important to understand how the brain is changed during the normal aging process. We compared diffusion tensor imaging (DTI)-based brain networks in a cohort of 75 healthy old subjects by using graph theory metrics to describe the anatomical networks and connectivity patterns, and network-based statistic (NBS) analysis was used to identify pairs of regions with altered structural connectivity. The NBS analysis revealed a significant network comprising nine distinct fiber bundles linking 10 different brain regions showed altered white matter structures in young-old group compare with middle-aged group (p < .05, family-wise error-corrected). Our results might guide future studies and help to gain a better understanding of brain aging.

Cortical and thalamic connectivity to the second auditory cortex of the cat is resilient to the onset of deafness.

It has been well established that following sensory loss, cortical areas that would normally be involved in perceiving stimuli in the absent modality are recruited to subserve the remaining senses. Despite this compensatory functional reorganization, there is little evidence to date for any substantial change in the patterns of anatomical connectivity between sensory cortices. However, while many auditory areas are contracted in the deaf, the second auditory cortex (A2) of the cat undergoes a volumetric expansion following hearing loss, suggesting this cortical area may demonstrate a region-specific pattern of structural reorganization. To address this hypothesis, and to complement existing literature on connectivity within auditory cortex, we injected a retrograde neuronal tracer across the breadth and cortical thickness of A2 to provide the first comprehensive quantification of projections from cortical and thalamic auditory and non-auditory regions to the second auditory cortex, and to determine how these patterns are affected by the onset of deafness. Neural projections arising from auditory, visual, somatomotor, and limbic cortices, as well as thalamic nuclei, were compared across normal hearing, early-deaf, and late-deaf animals. The results demonstrate that, despite previously identified changes in A2 volume, the pattern of projections into this cortical region are unaffected by the onset of hearing loss. These results fail to support the idea that crossmodal plasticity reflects changes in the pattern of projections between cortical regions and provides evidence that the pattern of connectivity that supports normal hearing is retained in the deaf brain.