Network-Based Asymmetry of the Human Auditory System

Advanced progress of vestibular compensation in vestibular neural networks

Vestibular compensation is the natural process of recovery that occurs with acute peripheral vestibular lesion. Here, we summarize the current understanding of the mechanisms underlying vestibular compensation, focusing on the role of the medial vestibular nucleus (MVN), the central hub of the vestibular system, and its associated neural networks. The disruption of neural activity balance between the bilateral MVNs underlies the vestibular symptoms after unilateral vestibular damage, and this balance disruption can be partially reversed by the mutual inhibitory projections between the bilateral MVNs, and their top-down regulation by other brain regions via different neurotransmitters. However, the detailed mechanism of how MVN is involved in vestibular compensation and regulated remains largely unknown. A deeper understanding of the vestibular neural network and the neurotransmitter systems involved in vestibular compensation holds promise for improving treatment outcomes and developing more effective interventions for vestibular disorders.

Auditory hemispheric asymmetry for actions and objects

What is the function of auditory hemispheric asymmetry? We propose that the identification of sound sources relies on the asymmetric processing of two complementary and perceptually relevant acoustic invariants: actions and objects. In a large dataset of environmental sounds, we observed that temporal and spectral modulations display only weak covariation. We then synthesized auditory stimuli by simulating various actions (frictions) occurring on different objects (solid surfaces). Behaviorally, discrimination of actions relies on temporal modulations, while discrimination of objects relies on spectral modulations. Functional magnetic resonance imaging data showed that actions and objects are decoded in the left and right hemispheres, respectively, in bilateral superior temporal and left inferior frontal regions. This asymmetry reflects a generic differential processing-through differential neural sensitivity to temporal and spectral modulations present in environmental sounds-that supports the efficient categorization of actions and objects. These results support an ecologically valid framework of the functional role of auditory brain asymmetry.

Structural connectivity changes in unilateral hearing loss

Network connectivity, as mapped by the whole brain connectome, plays a crucial role in regulating auditory function. Auditory deprivation such as unilateral hearing loss might alter structural network connectivity; however, these potential alterations are poorly understood. Thirty-seven acoustic neuroma patients with unilateral hearing loss (19 left-sided and 18 right-sided) and 19 healthy controls underwent diffusion-weighted and T1-weighted imaging to assess edge strength, node strength, and global efficiency of the structural connectome. Edge strength was estimated by pair-wise normalized streamline density from tractography and connectomics. Node strength and global efficiency were calculated through graph theory analysis of the connectome. Pure-tone audiometry and word recognition scores were used to correlate the degree and duration of unilateral hearing loss with node strength and global efficiency. We demonstrate significantly stronger edge strength and node strength through the visual network, weaker edge strength and node strength in the somatomotor network, and stronger global efficiency in the unilateral hearing loss patients. No discernible correlations were observed between the degree and duration of unilateral hearing loss and the measures of node strength or global efficiency. These findings contribute to our understanding of the role of structural connectivity in hearing by facilitating visual network upregulation and somatomotor network downregulation after unilateral hearing loss.

How brain structure-function decoupling supports individual cognition and its molecular mechanism

Functional signals emerge from the structural network, supporting multiple cognitive processes through underlying molecular mechanism. The link between human brain structure and function is region-specific and hierarchical across the neocortex. However, the relationship between hierarchical structure-function decoupling and the manifestation of individual behavior and cognition, along with the significance of the functional systems involved, and the specific molecular mechanism underlying structure-function decoupling remain incompletely characterized. Here, we used the structural-decoupling index (SDI) to quantify the dependency of functional signals on the structural connectome using a significantly larger cohort of healthy subjects. Canonical correlation analysis (CCA) was utilized to assess the general multivariate correlation pattern between region-specific SDIs across the whole brain and multiple cognitive traits. Then, we predicted five composite cognitive scores resulting from multivariate analysis using SDIs in primary networks, association networks, and all networks, respectively. Finally, we explored the molecular mechanism related to SDI by investigating its genetic factors and relationship with neurotransmitter receptors/transporters. We demonstrated that structure-function decoupling is hierarchical across the neocortex, spanning from primary networks to association networks. We revealed better performance in cognition prediction is achieved by using high-level hierarchical SDIs, with varying significance of different brain regions in predicting cognitive processes. We found that the SDIs were associated with the gene expression level of several receptor-related terms, and we also found the spatial distributions of four receptors/transporters significantly correlated with SDIs, namely D2, NET, MOR, and mGluR5, which play an important role in the flexibility of neuronal function. Collectively, our findings corroborate the association between hierarchical macroscale structure-function decoupling and individual cognition and provide implications for comprehending the molecular mechanism of structure-function decoupling. PRACTITIONER POINTS: Structure-function decoupling is hierarchical across the neocortex, spanning from primary networks to association networks. High-level hierarchical structure-function decoupling contributes much more than low-level decoupling to individual cognition. Structure-function decoupling could be regulated by genes associated with pivotal receptors that are crucial for neuronal function flexibility.

The Auditory Agnosias: a Short Review of Neurofunctional Evidence

PURPOSE OF REVIEW

To investigate the neurofunctional correlates of pure auditory agnosia and its varieties (global, verbal, and nonverbal), based on 116 anatomoclinical reports published between 1893 and 2022, with emphasis on hemispheric lateralization, intrahemispheric lesion site, underlying cognitive impairments.

RECENT FINDINGS

Pure auditory agnosia is rare, and observations accumulate slowly. Recent patient reports and neuroimaging studies on neurotypical subjects offer insights into the putative mechanisms underlying auditory agnosia, while challenging traditional accounts. Global auditory agnosia frequently results from bilateral temporal damage. Verbal auditory agnosia strictly correlates with language-dominant hemisphere lesions. Damage involves the auditory pathways, but the critical lesion site is unclear. Both the auditory cortex and associative areas are reasonable candidates, but cases resulting from brainstem damage are on record. The hemispheric correlates of nonverbal auditory input disorders are less clear. They correlate with unilateral damage to either hemisphere, but evidence is scarce. Based on published cases, pure auditory agnosias are neurologically and functionally heterogeneous. Phenotypes are influenced by co-occurring cognitive impairments. Future studies should start from these facts and integrate patient data and studies in neurotypical individuals.

Lateralization and Time-Course of Cortical Phonological Representations during Syllable Production

Spoken language contains information at a broad range of timescales, from phonetic distinctions on the order of milliseconds to semantic contexts which shift over seconds to minutes. It is not well understood how the brain's speech production systems combine features at these timescales into a coherent vocal output. We investigated the spatial and temporal representations in cerebral cortex of three phonological units with different durations: consonants, vowels, and syllables. Electrocorticography (ECoG) recordings were obtained from five participants while speaking single syllables. We developed a novel clustering and Kalman filter-based trend analysis procedure to sort electrodes into temporal response profiles. A linear discriminant classifier was used to determine how strongly each electrode's response encoded phonological features. We found distinct time-courses of encoding phonological units depending on their duration: consonants were represented more during speech preparation, vowels were represented evenly throughout trials, and syllables during production. Locations of strongly speech-encoding electrodes (the top 30% of electrodes) likewise depended on phonological element duration, with consonant-encoding electrodes left-lateralized, vowel-encoding hemispherically balanced, and syllable-encoding right-lateralized. The lateralization of speech-encoding electrodes depended on onset time, with electrodes active before or after speech production favoring left hemisphere and those active during speech favoring the right. Single-electrode speech classification revealed cortical areas with preferential encoding of particular phonemic elements, including consonant encoding in the left precentral and postcentral gyri and syllable encoding in the right middle frontal gyrus. Our findings support neurolinguistic theories of left hemisphere specialization for processing short-timescale linguistic units and right hemisphere processing of longer-duration units.

Resolving inter-regional communication capacity in the human connectome

Applications of graph theory to the connectome have inspired several models of how neural signaling unfolds atop its structure. Analytic measures derived from these communication models have mainly been used to extract global characteristics of brain networks, obscuring potentially informative inter-regional relationships. Here we develop a simple standardization method to investigate polysynaptic communication pathways between pairs of cortical regions. This procedure allows us to determine which pairs of nodes are topologically closer and which are further than expected on the basis of their degree. We find that communication pathways delineate canonical functional systems. Relating nodal communication capacity to meta-analytic probabilistic patterns of functional specialization, we also show that areas that are most closely integrated within the network are associated with higher order cognitive functions. We find that these regions' proclivity towards functional integration could naturally arise from the brain's anatomical configuration through evenly distributed connections among multiple specialized communities. Throughout, we consider two increasingly constrained null models to disentangle the effects of the network's topology from those passively endowed by spatial embedding. Altogether, the present findings uncover relationships between polysynaptic communication pathways and the brain's functional organization across multiple topological levels of analysis and demonstrate that network integration facilitates cognitive integration.

Brain network communication: concepts, models and applications

Understanding communication and information processing in nervous systems is a central goal of neuroscience. Over the past two decades, advances in connectomics and network neuroscience have opened new avenues for investigating polysynaptic communication in complex brain networks. Recent work has brought into question the mainstay assumption that connectome signalling occurs exclusively via shortest paths, resulting in a sprawling constellation of alternative network communication models. This Review surveys the latest developments in models of brain network communication. We begin by drawing a conceptual link between the mathematics of graph theory and biological aspects of neural signalling such as transmission delays and metabolic cost. We organize key network communication models and measures into a taxonomy, aimed at helping researchers navigate the growing number of concepts and methods in the literature. The taxonomy highlights the pros, cons and interpretations of different conceptualizations of connectome signalling. We showcase the utility of network communication models as a flexible, interpretable and tractable framework to study brain function by reviewing prominent applications in basic, cognitive and clinical neurosciences. Finally, we provide recommendations to guide the future development, application and validation of network communication models.

Integrating multimodal and multiscale connectivity blueprints of the human cerebral cortex in health and disease

The brain is composed of disparate neural populations that communicate and interact with one another. Although fiber bundles, similarities in molecular architecture, and synchronized neural activity all reflect how brain regions potentially interact with one another, a comprehensive study of how all these interregional relationships jointly reflect brain structure and function remains missing. Here, we systematically integrate 7 multimodal, multiscale types of interregional similarity ("connectivity modes") derived from gene expression, neurotransmitter receptor density, cellular morphology, glucose metabolism, haemodynamic activity, and electrophysiology in humans. We first show that for all connectivity modes, feature similarity decreases with distance and increases when regions are structurally connected. Next, we show that connectivity modes exhibit unique and diverse connection patterns, hub profiles, spatial gradients, and modular organization. Throughout, we observe a consistent primacy of molecular connectivity modes-namely correlated gene expression and receptor similarity-that map onto multiple phenomena, including the rich club and patterns of abnormal cortical thickness across 13 neurological, psychiatric, and neurodevelopmental disorders. Finally, to construct a single multimodal wiring map of the human cortex, we fuse all 7 connectivity modes and show that the fused network maps onto major organizational features of the cortex including structural connectivity, intrinsic functional networks, and cytoarchitectonic classes. Altogether, this work contributes to the integrative study of interregional relationships in the human cerebral cortex.

Benchmarking functional connectivity by the structure and geometry of the human brain

The brain's structural connectivity supports the propagation of electrical impulses, manifesting as patterns of coactivation, termed functional connectivity. Functional connectivity emerges from the underlying sparse structural connections, particularly through polysynaptic communication. As a result, functional connections between brain regions without direct structural links are numerous, but their organization is not completely understood. Here we investigate the organization of functional connections without direct structural links. We develop a simple, data-driven method to benchmark functional connections with respect to their underlying structural and geometric embedding. We then use this method to reweigh and reexpress functional connectivity. We find evidence of unexpectedly strong functional connectivity among distal brain regions and within the default mode network. We also find unexpectedly strong functional connectivity at the apex of the unimodal-transmodal hierarchy. Our results suggest that both phenomena-functional modules and functional hierarchies-emerge from functional interactions that transcend the underlying structure and geometry. These findings also potentially explain recent reports that structural and functional connectivity gradually diverge in transmodal cortex. Collectively, we show how structural connectivity and geometry can be used as a natural frame of reference with which to study functional connectivity patterns in the brain.

A perturbative approach to study information communication in brain networks

How communication among neuronal ensembles shapes functional brain dynamics is a question of fundamental importance to neuroscience. Communication in the brain can be viewed as a product of the interaction of node activities with the structural network over which these activities flow. The study of these interactions is, however, restricted by the difficulties in describing the complex dynamics of the brain. There is thus a need to develop methods to study these network-dynamical interactions and how they impact information flow, without having to ascertain dynamics a priori or resort to restrictive analytical approaches. Here, we adapt a recently established network analysis method based on perturbations, it to a neuroscientific setting to study how information flow in the brain can raise from properties of underlying structure. For proof-of-concept, we apply the approach on in silico whole-brain models. We expound on the functional implications of the distributions of metrics that capture network-dynamical interactions, termed net influence and flow. We also study the network-dynamical interactions at the level of resting-state networks. An attractive feature of this method is its simplicity, which allows a direct translation to an experimental or clinical setting, such as for identifying targets for stimulation studies or therapeutic interventions.

Insights from auditory cortex for GABA+ magnetic resonance spectroscopy studies of aging

Changes in levels of the inhibitory neurotransmitter γ-aminobutyric acid (GABA) may underlie aging-related changes in brain function. GABA and co-edited macromolecules (GABA+) can be measured with MEGA-PRESS magnetic resonance spectroscopy (MRS). The current study investigated how changes in the aging brain impact the interpretation of GABA+ measures in bilateral auditory cortices of healthy young and older adults. Structural changes during aging appeared as decreasing proportion of grey matter in the MRS volume of interest and corresponding increase in cerebrospinal fluid. GABA+ referenced to H₂ O without tissue correction declined in aging. This decline persisted after correcting for tissue differences in MR-visible H₂ O and relaxation times but vanished after considering the different abundance of GABA+ in grey and white matter. However, GABA+ referenced to creatine and N-acetyl aspartate (NAA), which showed no dependence on tissue composition, decreased in aging. All GABA+ measures showed hemispheric asymmetry in young but not older adults. The study also considered aging-related effects on tissue segmentation and the impact of co-edited macromolecules. Tissue segmentation differed significantly between commonly used algorithms, but aging-related effects on tissue-corrected GABA+ were consistent across methods. Auditory cortex macromolecule concentration did not change with age, indicating that a decline in GABA caused the decrease in the compound GABA+ measure. Most likely, the macromolecule contribution to GABA+ leads to underestimating an aging-related decrease in GABA. Overall, considering multiple GABA+ measures using different reference signals strengthened the support for an aging-related decline in auditory cortex GABA levels.

Brain atrophy in prodromal synucleinopathy is shaped by structural connectivity and gene expression

Isolated REM sleep behaviour disorder (iRBD) is a synucleinopathy characterized by abnormal behaviours and vocalizations during REM sleep. Most iRBD patients develop dementia with Lewy bodies, Parkinson's disease, or multiple system atrophy over time. Patients with iRBD exhibit brain atrophy patterns that are reminiscent of those observed in overt synucleinopathies. However, the mechanisms linking brain atrophy to the underlying alpha-synuclein pathophysiology are poorly understood. Our objective was to investigate how the prion-like and regional vulnerability hypotheses of alpha-synuclein might explain brain atrophy in iRBD. Using a multicentric cohort of 182 polysomnography-confirmed iRBD patients who underwent T1-weighted MRI, we performed vertex-based cortical surface and deformation-based morphometry analyses to quantify brain atrophy in patients (67.8 years, 84% men) and 261 healthy controls (66.2 years, 75%) and investigated the morphological correlates of motor and cognitive functioning in iRBD. Next, we applied the agent-based Susceptible-Infected-Removed model (i.e., a computational model that simulates in silico the spread of pathologic alpha-synuclein based on structural connectivity and gene expression) and tested if it recreated atrophy in iRBD by statistically comparing simulated regional brain atrophy to the atrophy observed in patients. The impact of SNCA and GBA gene expression and brain connectivity was then evaluated by comparing the model fit to the one obtained in null models where either gene expression or connectivity was randomized. The results showed that iRBD patients present with cortical thinning and tissue deformation, which correlated with motor and cognitive functioning. Next, we found that the computational model recreated cortical thinning (r = 0.51, p = 0.0007) and tissue deformation (r = 0.52, p = 0.0005) in patients, and that the connectome's architecture along with SNCA and GBA gene expression contributed to shaping atrophy in iRBD. We further demonstrated that the full agent-based model performed better than network measures or gene expression alone in recreating the atrophy pattern in iRBD. In summary, atrophy in iRBD is extensive, correlates with motor and cognitive function, and can be recreated using the dynamics of agent-based modelling, structural connectivity, and gene expression. These findings support the concepts that both prion-like spread and regional susceptibility account for the atrophy observed in prodromal synucleinopathies. Therefore, the agent-based Susceptible-Infected-Removed model may be a useful tool for testing hypotheses underlying neurodegenerative diseases and new therapies aimed at slowing or stopping the spread of alpha-synuclein pathology.

Quantitative mapping of the brain's structural connectivity using diffusion MRI tractography: A review

Diffusion magnetic resonance imaging (dMRI) tractography is an advanced imaging technique that enables in vivo reconstruction of the brain's white matter connections at macro scale. It provides an important tool for quantitative mapping of the brain's structural connectivity using measures of connectivity or tissue microstructure. Over the last two decades, the study of brain connectivity using dMRI tractography has played a prominent role in the neuroimaging research landscape. In this paper, we provide a high-level overview of how tractography is used to enable quantitative analysis of the brain's structural connectivity in health and disease. We focus on two types of quantitative analyses of tractography, including: 1) tract-specific analysis that refers to research that is typically hypothesis-driven and studies particular anatomical fiber tracts, and 2) connectome-based analysis that refers to research that is more data-driven and generally studies the structural connectivity of the entire brain. We first provide a review of methodology involved in three main processing steps that are common across most approaches for quantitative analysis of tractography, including methods for tractography correction, segmentation and quantification. For each step, we aim to describe methodological choices, their popularity, and potential pros and cons. We then review studies that have used quantitative tractography approaches to study the brain's white matter, focusing on applications in neurodevelopment, aging, neurological disorders, mental disorders, and neurosurgery. We conclude that, while there have been considerable advancements in methodological technologies and breadth of applications, there nevertheless remains no consensus about the "best" methodology in quantitative analysis of tractography, and researchers should remain cautious when interpreting results in research and clinical applications.

Integrating Philosophy of Understanding With the Cognitive Sciences

We provide two programmatic frameworks for integrating philosophical research on understanding with complementary work in computer science, psychology, and neuroscience. First, philosophical theories of understanding have consequences about how agents should reason if they are to understand that can then be evaluated empirically by their concordance with findings in scientific studies of reasoning. Second, these studies use a multitude of explanations, and a philosophical theory of understanding is well suited to integrating these explanations in illuminating ways.

Network structure and transcriptomic vulnerability shape atrophy in frontotemporal dementia

Connections among brain regions allow pathological perturbations to spread from a single source region to multiple regions. Patterns of neurodegeneration in multiple diseases, including behavioural variant of frontotemporal dementia (bvFTD), resemble the large-scale functional systems, but how bvFTD-related atrophy patterns relate to structural network organization remains unknown. Here we investigate whether neurodegeneration patterns in sporadic and genetic bvFTD are conditioned by connectome architecture. Regional atrophy patterns were estimated in both genetic bvFTD (75 patients, 247 controls) and sporadic bvFTD (70 patients, 123 controls). First, we identified distributed atrophy patterns in bvFTD, mainly targeting areas associated with the limbic intrinsic network and insular cytoarchitectonic class. Regional atrophy was significantly correlated with atrophy of structurally- and functionally-connected neighbours, demonstrating that network structure shapes atrophy patterns. The anterior insula was identified as the predominant group epicentre of brain atrophy using data-driven and simulation-based methods, with some secondary regions in frontal ventromedial and antero-medial temporal areas. We found that FTD-related genes, namely C9orf72 and TARDBP, confer local transcriptomic vulnerability to the disease, modulating the propagation of pathology through the connectome. Collectively, our results demonstrate that atrophy patterns in sporadic and genetic bvFTD are jointly shaped by global connectome architecture and local transcriptomic vulnerability, providing an explanation as to how heterogenous pathological entities can lead to the same clinical syndrome.

Right-Lateralized Enhancement of the Auditory Cortical Network During Imagined Music Performance

Although the primary role of the auditory cortical areas is to process actual sounds, these areas are also activated by tasks that process imagined music, suggesting that the auditory cortical areas are involved in the processes underlying musical imagery. However, the mechanism by which these areas are involved in such processes is unknown. To elucidate this feature of the auditory cortical areas, we analyzed their functional networks during imagined music performance in comparison with those in the resting condition. While imagined music performance does not produce any musical sounds, the participants heard the same actual sounds from the MRI equipment in both experimental conditions. Therefore, if the functional connectivity between these conditions differs significantly, one can infer that the auditory cortical areas are actively involved in imagined music performance. Our functional connectivity analysis revealed a significant enhancement in the auditory network during imagined music performance relative to the resting condition. The reconfiguration profile of the auditory network showed a clear right-lateralized increase in the connectivity of the auditory cortical areas with brain regions associated with cognitive, memory, and emotional information processing. On the basis of these results, we hypothesize that auditory cortical areas and their networks are actively involved in imagined music performance through the integration of auditory imagery into mental imagery associated with music performance.

Cortical disorders of speech processing: Pure word deafness and auditory agnosia

Selective disorders of auditory speech processing due to brain lesions are reviewed. Over 120 years after the first anatomic report (Dejerine and Sérieux, 1898), fewer than 80 cumulative cases of generalized auditory agnosia and pure word deafness with documented brain lesions are on record. Most patients (approximately 70%) had vascular lesions. Damage is very frequently bilateral in generalized auditory agnosia, and more frequently unilateral in pure word deafness. In unilateral cases, anatomical disconnection is not a prerequisite, and disorders may be due to functional disconnection. Regardless of whether lesions are unilateral or bilateral, speech processing difficulties emerge in the presence of damage to the superior temporal regions of the language-dominant hemisphere, suggesting that speech input is processed asymmetrically at early stages already. Extant evidence does not allow establishing whether processing asymmetry originates in the primary auditory cortex or in higher associative cortices, nor whether auditory processing in the brainstem is entirely symmetric. Results are consistent with the view that the difficulty in processing auditory input characterized by quick spectral and/or temporal changes is one of the critical dimensions of the disorder. Forthcoming studies should focus on detailed audiologic, neurolinguistic, and neuroanatomic descriptions of each case.

Multiscale communication in cortico-cortical networks

Signaling in brain networks unfolds over multiple topological scales. Areas may exchange information over local circuits, encompassing direct neighbours and areas with similar functions, or over global circuits, encompassing distant neighbours with dissimilar functions. Here we study how the organization of cortico-cortical networks mediate localized and global communication by parametrically tuning the range at which signals are transmitted on the white matter connectome. We show that brain regions vary in their preferred communication scale. By investigating the propensity for brain areas to communicate with their neighbors across multiple scales, we naturally reveal their functional diversity: unimodal regions show preference for local communication and multimodal regions show preferences for global communication. We show that these preferences manifest as region- and scale-specific structure-function coupling. Namely, the functional connectivity of unimodal regions emerges from monosynaptic communication in small-scale circuits, while the functional connectivity of transmodal regions emerges from polysynaptic communication in large-scale circuits. Altogether, the present findings reveal that communication preferences are highly heterogeneous across the cortex, shaping regional differences in structure-function coupling.

Profiling Transcription Initiation in Peripheral Leukocytes Reveals Severity-Associated Cis-Regulatory Elements in Critical COVID-19

The contribution of transcription factors (TFs) and gene regulatory programs in the immune response to COVID-19 and their relationship to disease outcome is not fully understood. Analysis of genome-wide changes in transcription at both promoter-proximal and distal cis-regulatory DNA elements, collectively termed the 'active cistrome,' offers an unbiased assessment of TF activity identifying key pathways regulated in homeostasis or disease. Here, we profiled the active cistrome from peripheral leukocytes of critically ill COVID-19 patients to identify major regulatory programs and their dynamics during SARS-CoV-2 associated acute respiratory distress syndrome (ARDS). We identified TF motifs that track the severity of COVID- 19 lung injury, disease resolution, and outcome. We used unbiased clustering to reveal distinct cistrome subsets delineating the regulation of pathways, cell types, and the combinatorial activity of TFs. We found critical roles for regulatory networks driven by stimulus and lineage determining TFs, showing that STAT and E2F/MYB regulatory programs targeting myeloid cells are activated in patients with poor disease outcomes and associated with single nucleotide genetic variants implicated in COVID-19 susceptibility. Integration with single-cell RNA-seq found that STAT and E2F/MYB activation converged in specific neutrophils subset found in patients with severe disease. Collectively we demonstrate that cistrome analysis facilitates insight into disease mechanisms and provides an unbiased approach to evaluate global changes in transcription factor activity and stratify patient disease severity.

Neonatal Hearing Screening: Prevalence of Unilateral and Bilateral Hearing Loss and Associated Risk Factors

INTRODUCTION

Newborn hearing screening is essential for early identification of hearing loss to decrease the adverse effects of hearing loss. The objective of this study was to determine the prevalence of hearing loss and risk factors of congenital hearing loss in newborns.

METHODS

In this analytical case-control study, a hearing screening test was performed for all newborns aged 3-14 days.

RESULTS

Of 5,500 newborns evaluated, 24 newborns had hearing loss. The prevalence of hearing loss was 4.36 per 1,000. Of 24 hearing-impaired newborns, 15 had bilateral hearing loss (BHL) (62.5%) and nine had unilateral hearing loss (UHL) (37.5%). Among the neonates with hearing loss, the prevalence of hearing loss was higher (77.8%) in the right ear. The main risk factors identified in this study were low gestational age (P=0.001), hospitalization in the neonatal intensive care unit (NICU) (P=0.008), exposure to ototoxic drugs (P=0.001), gestational diabetes P=0.01), craniofacial anomalies (P=0.01), convulsion (P=0.03), consanguineous marriage of parents (P=0.001), low birth weight (P=0.01), and hyperbilirubinemia (P=0.001).

CONCLUSION

The prevalence of hearing loss was higher in the right ear than in the left ear. NICU stay, use of ototoxic drugs, low gestational age (<35 weeks), gestational diabetes, craniofacial anomalies, convulsion, consanguineous marriage of parents, low birth weight, and hyperbilirubinemia were significant risk factors for congenital hearing loss in studied newborns.

Topological Aberrance of Structural Brain Network Provides Quantitative Substrates of Post-Traumatic Brain Injury Attention Deficits in Children

Background: Traumatic brain injury (TBI)-induced attention deficits are among the most common long-term cognitive consequences in children. Most of the existing studies attempting to understand the neuropathological underpinnings of cognitive and behavioral impairments in TBI have utilized heterogeneous samples and resulted in inconsistent findings. The current research proposed to investigate topological properties of the structural brain network in children with TBI and their relationship with post-TBI attention problems in a more homogeneous subgroup of children who had severe post-TBI attention deficits (TBI-A). Materials and Methods: A total of 31 children with TBI-A and 35 group-matched controls were involved in the study. Diffusion tensor imaging-based probabilistic tractography and graph theoretical techniques were used to construct the structural brain network in each subject. Network topological properties were calculated in both global level and regional (nodal) level. Between-group comparisons among the topological network measures and analyses for searching brain-behavioral were all corrected for multiple comparisons using Bonferroni method. Results: Compared with controls, the TBI-A group showed significantly higher nodal local efficiency and nodal clustering coefficient in left inferior frontal gyrus and right transverse temporal gyrus, whereas significantly lower nodal clustering coefficient in left supramarginal gyrus and lower nodal local efficiency in left parahippocampal gyrus. The temporal lobe topological alterations were significantly associated with the post-TBI inattentive and hyperactive symptoms in the TBI-A group. Conclusion: The results suggest that TBI-related structural re-modularity in the white matter subnetworks associated with temporal lobe may play a critical role in the onset of severe post-TBI attention deficits in children. These findings provide valuable input for understanding the neurobiological substrates of post-TBI attention deficits, and have the potential to serve as quantitatively measurable criteria guiding the development of more timely and tailored strategies for diagnoses and treatments to the affected individuals. Impact statement This study provides a new insight into the neurobiological substrates associated with post-traumatic brain injury attention deficits (TBI-A) in children, by evaluating topological alterations of the structural brain network. The results demonstrated that relative to group-matched controls, the children with TBI-A had significantly altered nodal local efficiency and nodal clustering coefficient in temporal lobe, which strongly linked to elevated inattentive and hyperactive symptoms in the TBI-A group. These findings suggested that white matter structural re-modularity in subnetworks associated with temporal lobe may serve as quantitatively measurable biomarkers for early prediction and diagnosis of post-TBI attention deficits in children.

Inhibitory effect of tDCS on auditory evoked response: Simultaneous MEG-tDCS reveals causal role of right auditory cortex in pitch learning

A body of literature has demonstrated that the right auditory cortex (AC) plays a dominant role in fine pitch processing. However, our understanding is relatively limited about whether this asymmetry extends to perceptual learning of pitch. There is also a lack of causal evidence regarding the role of the right AC in pitch learning.  We addressed these points with anodal transcranial direct current stimulation (tDCS), adapting a previous behavioral study in which anodal tDCS over the right AC was shown to block improvement of a microtonal pitch pattern learning task over 3 days. To address the physiological changes associated with tDCS, we recorded MEG data simultaneously with tDCS on the first day, and measured behavioral thresholds on the following two consecutive days. We tested three groups of participants who received anodal tDCS over their right or left AC, or sham tDCS, and measured the N1m auditory evoked response before, during, and after tDCS. Our data show that anodal tDCS of the right AC disrupted pitch discrimination learning up to two days after its application, whereas learning was unaffected by left-AC or sham tDCS. Although tDCS reduced the amplitude of the N1m ipsilaterally to the stimulated hemisphere on both left and right, only right AC N1m amplitude reductions were associated with the degree to which pitch learning was disrupted. This brain-behavior relationship confirms a causal link between right AC physiological responses and fine pitch processing, and provides neurophysiological insight concerning the mechanisms of action of tDCS on the auditory system.

Topographic gradients of intrinsic dynamics across neocortex

The intrinsic dynamics of neuronal populations are shaped by both microscale attributes and macroscale connectome architecture. Here we comprehensively characterize the rich temporal patterns of neural activity throughout the human brain. Applying massive temporal feature extraction to regional haemodynamic activity, we systematically estimate over 6000 statistical properties of individual brain regions' time-series across the neocortex. We identify two robust spatial gradients of intrinsic dynamics, one spanning a ventromedial-dorsolateral axis and dominated by measures of signal autocorrelation, and the other spanning a unimodal-transmodal axis and dominated by measures of dynamic range. These gradients reflect spatial patterns of gene expression, intracortical myelin and cortical thickness, as well as structural and functional network embedding. Importantly, these gradients are correlated with patterns of meta-analytic functional activation, differentiating cognitive versus affective processing and sensory versus higher-order cognitive processing. Altogether, these findings demonstrate a link between microscale and macroscale architecture, intrinsic dynamics, and cognition.

Network communication models improve the behavioral and functional predictive utility of the human structural connectome

The connectome provides the structural substrate facilitating communication between brain regions. We aimed to establish whether accounting for polysynaptic communication in structural connectomes would improve prediction of interindividual variation in behavior as well as increase structure-function coupling strength. Connectomes were mapped for 889 healthy adults participating in the Human Connectome Project. To account for polysynaptic signaling, connectomes were transformed into communication matrices for each of 15 different network communication models. Communication matrices were (a) used to perform predictions of five data-driven behavioral dimensions and (b) correlated to resting-state functional connectivity (FC). While FC was the most accurate predictor of behavior, communication models, in particular communicability and navigation, improved the performance of structural connectomes. Communication also strengthened structure-function coupling, with the navigation and shortest paths models leading to 35-65% increases in association strength with FC. We combined behavioral and functional results into a single ranking that provides insight into which communication models may more faithfully recapitulate underlying neural signaling patterns. Comparing results across multiple connectome mapping pipelines suggested that modeling polysynaptic communication is particularly beneficial in sparse high-resolution connectomes. We conclude that network communication models can augment the functional and behavioral predictive utility of the human structural connectome.

Signal propagation via cortical hierarchies

The wiring of the brain is organized around a putative unimodal-transmodal hierarchy. Here we investigate how this intrinsic hierarchical organization of the brain shapes the transmission of information among regions. The hierarchical positioning of individual regions was quantified by applying diffusion map embedding to resting-state functional MRI networks. Structural networks were reconstructed from diffusion spectrum imaging and topological shortest paths among all brain regions were computed. Sequences of nodes encountered along a path were then labeled by their hierarchical position, tracing out path motifs. We find that the cortical hierarchy guides communication in the network. Specifically, nodes are more likely to forward signals to nodes closer in the hierarchy and cover a range of unimodal and transmodal regions, potentially enriching or diversifying signals en route. We also find evidence of systematic detours, particularly in attention networks, where communication is rerouted. Altogether, the present work highlights how the cortical hierarchy shapes signal exchange and imparts behaviorally relevant communication patterns in brain networks.

In the present report we asked how signals travel on brain networks and what types of nodes they potentially visit en route. We traced individual path motifs to investigate the propensity of communication paths to explore the putative unimodal-transmodal cortical hierarchy. We find that the architecture of the network promotes signaling via the hierarchy, suggesting a link between the structure and function of the network. Importantly, we also find instances where detours are promoted, particularly as paths traverse attention-related networks. Finally, information about hierarchical position aids navigation in some parts of the network, over and above spatial location. Altogether, the present results touch on several emerging themes in network neuroscience, including the nature of structure-function relationships, network communication and the role of cortical hierarchies.

Spatial Patterning of Tissue Volume Loss in Schizophrenia Reflects Brain Network Architecture

BACKGROUND

There is growing recognition that connectome architecture shapes cortical and subcortical gray matter atrophy across a spectrum of neurological and psychiatric diseases. Whether connectivity contributes to tissue volume loss in schizophrenia in the same manner remains unknown.

METHODS

Here, we relate tissue volume loss in patients with schizophrenia to patterns of structural and functional connectivity. Gray matter deformation was estimated in a sample of 133 individuals with chronic schizophrenia (48 women, mean age 34.7 ± 12.9 years) and 113 control subjects (64 women, mean age 23.5 ± 8.4 years). Deformation-based morphometry was used to estimate cortical and subcortical gray matter deformation from T1-weighted magnetic resonance images. Structural and functional connectivity patterns were derived from an independent sample of 70 healthy participants using diffusion spectrum imaging and resting-state functional magnetic resonance imaging.

RESULTS

We found that regional deformation is correlated with the deformation of structurally and functionally connected neighbors. Distributed deformation patterns are circumscribed by specific functional systems (the ventral attention network) and cytoarchitectonic classes (limbic class), with an epicenter in the anterior cingulate cortex.

CONCLUSIONS

Altogether, the present study demonstrates that brain tissue volume loss in schizophrenia is conditioned by structural and functional connectivity, accounting for 25% to 35% of regional variance in deformation.

General theory of topological explanations and explanatory asymmetry

In this paper, I present a general theory of topological explanations, and illustrate its fruitfulness by showing how it accounts for explanatory asymmetry. My argument is developed in three steps. In the first step, I show what it is for some topological property A to explain some physical or dynamical property B. Based on that, I derive three key criteria of successful topological explanations: a criterion concerning the facticity of topological explanations, i.e. what makes it true of a particular system; a criterion for describing counterfactual dependencies in two explanatory modes, i.e. the vertical and the horizontal and, finally, a third perspectival one that tells us when to use the vertical and when to use the horizontal mode. In the second step, I show how this general theory of topological explanations accounts for explanatory asymmetry in both the vertical and horizontal explanatory modes. Finally, in the third step, I argue that this theory is universally applicable across biological sciences, which helps in unifying essential concepts of biological networks. This article is part of the theme issue 'Unifying the essential concepts of biological networks: biological insights and philosophical foundations'.

Decreased inter-hemispheric interactions but increased intra-hemispheric integration during typical aging

Normal aging is known to be accompanied by decreased segregation across the whole-brain functional network, which is associated with cognitive decline. Although compelling evidence supports reduced segregation and increased integration in whole-brain functional connectivity with aging, the age effect on the reorganization of large-scale functional networks at the hemispheric level remains unclear. Here, we aimed to examine age-related differences in inter-hemispheric interactions and intra-hemispheric integration by using resting-state functional MRI data of a healthy adult lifespan sample. The results showed that age-related decreases in inter-hemispheric integration were found in entire functional networks in both hemispheres, except for the sensorimotor network (SMN) and posterior default mode network (DMN). Specifically, aging was accompanied by increasing inter-hemispheric segregation in the left frontoparietal network (FPN) and left ventral attention network (VAN), as well as right-brain networks located in the auditory network (AN), visual network (VN), and temporal parts of the DMN. Moreover, aging was associated with increasing intra-hemispheric integration within the bilateral VN and posterior DMN while decreasing intra-hemispheric integration within the right VAN. These remarkable changes with aging confirm that there are dynamic interactions between functional networks across the lifespan and provide a means of investigating the mechanisms of cognitive aging.

Local vulnerability and global connectivity jointly shape neurodegenerative disease propagation

It is becoming increasingly clear that brain network organization shapes the course and expression of neurodegenerative diseases. Parkinson disease (PD) is marked by progressive spread of atrophy from the midbrain to subcortical structures and, eventually, to the cerebral cortex. Recent discoveries suggest that the neurodegenerative process involves the misfolding and prion-like propagation of endogenous α-synuclein via axonal projections. However, the mechanisms that translate local "synucleinopathy" to large-scale network dysfunction and atrophy remain unknown. Here, we use an agent-based epidemic spreading model to integrate structural connectivity, functional connectivity, and gene expression and to predict sequential volume loss due to neurodegeneration. The dynamic model replicates the spatial and temporal patterning of empirical atrophy in PD and implicates the substantia nigra as the disease epicenter. We reveal a significant role for both connectome topology and geometry in shaping the distribution of atrophy. The model also demonstrates that SNCA and GBA transcription influence α-synuclein concentration and local regional vulnerability. Functional coactivation further amplifies the course set by connectome architecture and gene expression. Altogether, these results support the theory that the progression of PD is a multifactorial process that depends on both cell-to-cell spreading of misfolded proteins and regional vulnerability.

Gradients of structure-function tethering across neocortex

The white matter architecture of brain networks promotes synchrony among neuronal populations, giving rise to richly patterned functional networks. Relating structure and function is a fundamental question for systems neuroscience, but the nature of the relationship is unknown. Here we examine the possibility that structure–function relationships are not uniform in the brain. We find that structure and function are closely aligned in unimodal cortex (primary sensory and motor regions), but diverge in transmodal cortex (default mode and salience networks). The divergence between structure and function closely follows representational and cytoarchitectonic hierarchies, reflecting a macroscale gradient. Our findings suggest structure and function are not uniformly related, but gradually decouple in parallel to this macroscale gradient.

The white matter architecture of the brain imparts a distinct signature on neuronal coactivation patterns. Interregional projections promote synchrony among distant neuronal populations, giving rise to richly patterned functional networks. A variety of statistical, communication, and biophysical models have been proposed to study the relationship between brain structure and function, but the link is not yet known. In the present report we seek to relate the structural and functional connection profiles of individual brain areas. We apply a simple multilinear model that incorporates information about spatial proximity, routing, and diffusion between brain regions to predict their functional connectivity. We find that structure–function relationships vary markedly across the neocortex. Structure and function correspond closely in unimodal, primary sensory, and motor regions, but diverge in transmodal cortex, particularly the default mode and salience networks. The divergence between structure and function systematically follows functional and cytoarchitectonic hierarchies. Altogether, the present results demonstrate that structural and functional networks do not align uniformly across the brain, but gradually uncouple in higher-order polysensory areas.

Resting-state connectivity of the bed nucleus of the stria terminalis and the central nucleus of the amygdala in clinical anxiety

Background

The central nucleus of the amygdala and bed nucleus of the stria terminalis are involved primarily in phasic and sustained aversive states. Although both structures have been implicated in pathological anxiety, few studies with a clinical population have specifically focused on them, partly because of their small size. Previous work in our group used high-resolution imaging to map the restingstate functional connectivity of the bed nucleus of the stria terminalis and the central nucleus of the amygdala in healthy subjects at 7 T, confirming and extending structural findings in humans and animals, while providing additional insight into cortical connectivity that is potentially unique to humans.

Methods

In the current follow-up study, we contrasted resting-state functional connectivity in the bed nucleus of the stria terminalis and central nucleus of the amygdala at 7 T between healthy volunteers (n = 30) and patients with generalized and/or social anxiety disorder (n = 30).

Results

Results revealed significant voxel-level group differences. Compared with healthy volunteers, patients showed stronger resting-state functional connectivity between the central nucleus of the amygdala and the lateral orbitofrontal cortex and superior temporal sulcus. They also showed weaker resting-state functional connectivity between the bed nucleus of the stria terminalis and the dorsolateral prefrontal cortex and occipital cortex.

Limitations

These findings depart from a previous report of resting-state functional connectivity in the central nucleus of the amygdala and bed nucleus of the stria terminalis under sustained threat of shock in healthy volunteers.

Conclusion

This study provides functional MRI proxies of the functional dissociation of the bed nucleus of the stria terminalis and central nucleus of the amygdala, and suggests that resting-state functional connectivity of key structures in the processing of defensive responses do not recapitulate changes related to induced state anxiety. Future work needs to replicate and further probe the clinical significance of these findings.

A probabilistic atlas of the human inner ear's bony labyrinth enables reliable atlas-based segmentation of the total fluid space

Intravenous contrast agent-enhanced magnetic resonance imaging of the endolymphatic space (ELS) of the inner ear permits direct, in-vivo, non-invasive visualization of labyrinthine structures and thus verification of endolymphatic hydrops (ELH). However, current volumetric assessment approaches lack normalization. The aim of this study was to develop a probabilistic atlas of the inner ear's bony labyrinth as a first step towards an automated and reproducible volume-based quantification of the ELS. The study included three different datasets: a source dataset (D1) to build the probabilistic atlas and two testing sets (D2, D3). D1 included 24 right-handed patients (12 females; mean age 51.5 ± 3.9 years) and D2 5 patients (3 female; mean age 48.8 ± 5.01 years) with vestibular migraine without ELH or any measurable vestibular deficits. D3 consisted of five patients (one female; mean age 46 ± 5.2 years) suffering from unilateral Menière's disease and ELH. Data processing comprised three steps: preprocessing using an affine and deformable fusion registration pipeline, computation of an atlas for the left and right inner ear using a label-assisted approach, and validation of the atlas based on localizing and segmenting previously unseen ears. The three-dimensional probabilistic atlas of the inner ear's bony labyrinth consisted of the internal acoustic meatus and inner ears (including cochlea, otoliths, and semicircular canals) for both sides separately. The analyses showed a high level of agreement between the atlas-based segmentation and the manual gold standard with an overlap of 89% for the right ear and 86% for the left ear (measured by dice scores). This probabilistic in vivo atlas of the human inner ear's bony labyrinth and thus of the inner ear's total fluid space for both ears represents a necessary step towards a normalized, easily reproducible and reliable volumetric quantification of the perilymphatic and endolymphatic space in view of MR volumetric assessment of ELH. The proposed atlas lays the groundwork for state-of-the-art approaches (e.g., deep learning) and will be provided to the scientific community.

Reduced brain microstructural asymmetry in patients with childhood leukemia treated with chemotherapy compared with healthy controls

Microstructural asymmetry of the brain can provide more direct causal explanations of functional lateralization than can macrostructural asymmetry. We performed a cross-sectional diffusion imaging study of 314 patients treated for childhood acute lymphoblastic leukemia (ALL) at a single institution and 92 healthy controls. An asymmetry index based on diffusion metrics was computed to quantify brain microstructural asymmetry. The effects of age and the asymmetry metrics of the two cohorts were examined with t-tests and linear models. We discovered two new types of microstructural asymmetry. Myelin-related asymmetry in controls was prominent in the back brain (89% right), whereas axon-related asymmetry occurred in the front brain (67% left) and back brain (88% right). These asymmetries indicate that white matter is more mature and more myelinated in the left back brain, potentially explaining the leftward lateralization of language and visual functions. The asymmetries increase throughout childhood and adolescence (P = 0.04) but were significantly less in patients treated for ALL (P<0.01), especially in younger patients. Our results indicate that atypical brain development may appear long before patients treated with chemotherapy become symptomatic.

Reduced Structural Connectivity Between Left Auditory Thalamus and the Motion-Sensitive Planum Temporale in Developmental Dyslexia

Developmental dyslexia is characterized by the inability to acquire typical reading and writing skills. Dyslexia has been frequently linked to cerebral cortex alterations; however, recent evidence also points toward sensory thalamus dysfunctions: dyslexics showed reduced responses in the left auditory thalamus (medial geniculate body, MGB) during speech processing in contrast to neurotypical readers. In addition, in the visual modality, dyslexics have reduced structural connectivity between the left visual thalamus (lateral geniculate nucleus, LGN) and V5/MT, a cerebral cortex region involved in visual movement processing. Higher LGN-V5/MT connectivity in dyslexics was associated with the faster rapid naming of letters and numbers (RANln), a measure that is highly correlated with reading proficiency. Here, we tested two hypotheses that were directly derived from these previous findings. First, we tested the hypothesis that dyslexics have reduced structural connectivity between the left MGB and the auditory-motion-sensitive part of the left planum temporale (mPT). Second, we hypothesized that the amount of left mPT-MGB connectivity correlates with dyslexics RANln scores. Using diffusion tensor imaging-based probabilistic tracking, we show that male adults with developmental dyslexia have reduced structural connectivity between the left MGB and the left mPT, confirming the first hypothesis. Stronger left mPT-MGB connectivity was not associated with faster RANln scores in dyslexics, but was in neurotypical readers. Our findings provide the first evidence that reduced cortico-thalamic connectivity in the auditory modality is a feature of developmental dyslexia and it may also affect reading-related cognitive abilities in neurotypical readers.SIGNIFICANCE STATEMENT Developmental dyslexia is one of the most widespread learning disabilities. Although previous neuroimaging research mainly focused on pathomechanisms of dyslexia at the cerebral cortex level, several lines of evidence suggest an atypical functioning of subcortical sensory structures. By means of diffusion tensor imaging, we here show that dyslexic male adults have reduced white matter connectivity in a cortico-thalamic auditory pathway between the left auditory motion-sensitive planum temporale and the left medial geniculate body. Connectivity strength of this pathway was associated with measures of reading fluency in neurotypical readers. This is novel evidence on the neurocognitive correlates of reading proficiency, highlighting the importance of cortico-subcortical interactions between regions involved in the processing of spectrotemporally complex sound.

Insights Into Auditory Cortex Dynamics From Non-invasive Brain Stimulation

Non-invasive brain stimulation (NIBS) has been widely used as a research tool to modulate cortical excitability of motor as well as non-motor areas, including auditory or language-related areas. NIBS, especially transcranial magnetic stimulation (TMS) and transcranial direct current stimulation, have also been used in clinical settings, with however variable therapeutic outcome, highlighting the need to better understand the mechanisms underlying NIBS techniques. TMS was initially used to address causality between specific brain areas and related behavior, such as language production, providing non-invasive alternatives to lesion studies. Recent literature however suggests that the relationship is not as straightforward as originally thought, and that TMS can show both linear and non-linear modulation of brain responses, highlighting complex network dynamics. In particular, in the last decade, NIBS studies have enabled further advances in our understanding of auditory processing and its underlying functional organization. For instance, NIBS studies showed that even when only one auditory cortex is stimulated unilaterally, bilateral modulation may result, thereby highlighting the influence of functional connectivity between auditory cortices. Additional neuromodulation techniques such as transcranial alternating current stimulation or transcranial random noise stimulation have been used to target frequency-specific neural oscillations of the auditory cortex, thereby providing further insight into modulation of auditory functions. All these NIBS techniques offer different perspectives into the function and organization of auditory cortex. However, further research should be carried out to assess the mode of action and long-term effects of NIBS to optimize their use in clinical settings.