bioRxiv Subject Collection: Neuroscience's Journal
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Tuesday, February 20th, 2024
| Time |
Event |
| 5:39a |
Stability from subspace rotations and traveling waves
Cortical activity shows stability, including the ability to recover from disruptions. We analyzed spiking from the prefrontal cortex (PFC) of monkeys performing working memory tasks with mid-memory-delay distractions. Perturbation of cortex by events (distraction by a gaze shift or visual distractor, or other sensory inputs) caused rotational dynamics in a subspace that often returned spiking to patterns similar to pre-disruption patterns. The rotations were predictive of behavioral performance. Further, we found direct correspondence between state-space rotations and traveling waves rotating across the surface of the PFC. This suggests a role for subspace rotations in cortical stability and a correspondence between subspace trajectories and traveling waves. | | 12:46p |
Intrinsic structural covariation links cerebellum subregions to the cerebral cortex
The human cerebellum is increasingly recognized to be involved in non-motor and higher-order cognitive functions. Yet, its ties with the entire cerebral cortex have not been holistically studied in a whole-brain exploration with a unified analytical framework. Here, we characterized dissociable cortical-cerebellar structural covariation patterns across the brain in n=38,527 UK Biobank participants. Our results invigorate previous observations in that important shares of cortical-cerebellar structural covariation are described as i) a dissociation between the higher-level cognitive system and lower-level sensorimotor system, as well as ii) an anticorrelation between the visual-attention system and advanced associative networks within the cerebellum. We also discovered a novel pattern of ipsilateral, rather than contralateral, cerebral-cerebellar associations. Furthermore, phenome-wide association assays revealed key phenotypes, including cognitive phenotypes, lifestyle, physical properties, and blood assays, associated with each decomposed covariation pattern, helping to understand their real-world implications. This systems neuroscience view paves the way for future studies to explore the implications of these structural covariations, potentially illuminating new pathways in our understanding of neurological and cognitive disorders. | | 12:46p |
Personalized circuit modeling captures variation in cortical functional connectivity
Functional magnetic resonance imaging (fMRI) of the human cortex reveals patterns of correlated neural dynamics that are individual-specific and associated with phenotypic variation. However, circuit mechanisms underlying individual variation in functional connectivity (FC) are not well understood. Here, we fit individual-level FC patterns with a biophysically-based circuit model of large-scale cortical dynamics. This model is fit with a small number of neurophysiologically interpretable parameters, and incorporates a hierarchical gradient in local synaptic strengths across cortex parameterized via the structural MRI-derived T1w/T2w map. We applied our modeling framework to resting-state fMRI FC from a large cohort of subjects (N=842) from the Human Connectome Project. We found that the model captures a substantial portion of individual variation in FC, especially with personalized degrees of local synaptic specialization along the hierarchical gradient. Furthermore, the model can capture to the within-subject variation in FC across scans. Empirically, we found that principal modes of individual variation in FC follow interpretable topographic patterns. We developed a framework to assess model expressivity via how these empirical modes of FC variation align with variations in simulated FC induced by parameter perturbations. This framework reveals a straightforward mapping between key parameters and the leading modes of variation across subjects and provides a principled approach to extending computational models. Collectively, our modeling results establish a foundation for personalized computational modeling of functional dynamics in large-scale brain circuits. | | 12:46p |
Phase delays between mouse globus pallidus neurons entrained by common oscillatory drive arise from their intrinsic properties, not their coupling
A hallmark of Parkinson's disease is the appearance of correlated oscillatory discharge throughout the cortico-basal ganglia (BG) circuits. In the primate globus pallidus (GP), where the discharge of GP neurons is normally uncorrelated, pairs of GP neurons exhibit oscillatory spike correlations with a broad distribution of pairwise phase delays in experimental parkinsonism. The transition to oscillatory correlations is considered an indication of the collapse of the normally segregated information channels traversing the BG, and the large phase delays are thought to reflect pathological changes in synaptic connectivity in the BG. Here we study the structure and phase delays of correlations measured from independent neurons in the mouse external GP (GPe) subjected to an identical 1-100 Hz sinusoidal drive. We find that spectral modes of a GPe neurons empirical instantaneous phase response curve (iPRC), elucidate at what phases of the oscillatory drive the GPe neuron locks when it is entrained, and the distribution of phases at which it fires when it is not. We show, mathematically, that the spike cross-intensity function (CIF) is the cross-correlation function of the spike phase distributions of a neuronal pair. Moreover, the distribution of GPe CIF phase delays arises from the diversity of iPRCs, and is broadened when the neurons become entrained. Modeling GPe networks with realistic intranuclear connectivity demonstrates that the connectivity decorrelates GPe neurons without affecting CIF phase delays. Thus, common oscillatory drive gives rise to GPe correlations whose diverse structure and pairwise phase delays reflect their intrinsic properties as captured by their iPRCs. | | 4:18p |
Differential transcriptional profiles of vagal sensory neurons in female and male mice.
The differences in metabolic homeostasis, diabetes, and obesity between males and females are evident in rodents and humans. Vagal sensory neurons in the vagus nerve ganglia innervate a variety of visceral organs and use specialized nerve endings to sense interoceptive signals. This visceral organ-brain axis plays a role in relaying interoceptive signals to higher brain centers as well as in regulating the vago-vagal reflex. I hypothesized that molecularly distinct populations of vagal sensory neurons would result in differences in metabolic homeostasis between the sexes. Single-nucleus RNA sequencing analysis of vagal sensory neurons from females and males reveals differences in the transcriptional profiles of cells in the vagus nerve ganglia. These differences are linked to the expression of sex-specific genes such as Xist, Tsix, and Ddx3y. Among the 13 neuronal clusters, one-fourth of the neurons in male mice are located in the Ddx3y-enriched VN1 and VN8 clusters, which display a higher enrichment of Trpv1, Piezo2, Htr3a, and Vip genes. In contrast, 70% of the neurons in females are found in Xist-enriched clusters VN4, 6, 7, 10, 11, and 13, which show enriched genes such as Fgfr1, Lpar1, Cpe, Esr1, Nrg1, Egfr, and Oprm1. Two clusters of satellite cells are identified, one of which in males contains some oligodendrocyte precursor cells. A small population of cells express Ucp1 and Plin1, indicating that they are epineural adipocytes. Understanding the physiological consequences of differences in these transcriptomic profiles on energy balance and metabolic homeostasis would help develop sex-specific treatments for obesity and metabolic dysregulation. | | 5:30p |
A Neural Network Approach to Identify Left-Right Orientation of Anatomical Brain MRI
Left-right orientation misidentification in brain MRIs presents significant challenges due to several factors, including metadata loss or ambiguity, which often occurs during the de-identification of medical images for research, conversion between image formats, software operations that strip or overwrite metadata, and the use of older imaging systems that stored orientation differently. This study presents a novel application of deep-learning to enhance the accuracy of left-right orientation identification in anatomical brain MRI scans. A three-dimensional Convolutional Neural Network model was trained using 350 MRIs and evaluated on eight distinct brain MRI databases, totaling 3,384 MRIs, to assess its performance across various conditions, including neurodegenerative diseases. The proposed deep-learning framework demonstrated a 99.6% accuracy in identifying the left-right orientation, thus addressing challenges associated with the loss of orientation metadata. GradCAM was used to visualize areas of the brain where the model focused, demonstrating the importance of the right planum temporale and surrounding areas in judging left-right orientation. The planum temporale is known to exhibit notable left-right asymmetry related to language functions, underscoring the biological validity of the model. More than half of the ten left-right misidentified MRIs involved notable brain feature variations, such as severe temporal lobe atrophy, arachnoidal cysts adjacent to the temporal lobe, or unusual cerebral torque, indicating areas for further investigation. This approach offers a potential solution to the persistent issue of left-right misorientation in brain MRIs and supports the reliability of neuroscientific research by ensuring accurate data interpretation. | | 5:30p |
Neurovascular mitochondrial susceptibility impacts blood-brain barrier function and behavior
Maintenance of blood-brain barrier (BBB) integrity is critical to optimal brain function, and its impairment has been linked to multiple neurological disorders. A notable feature of the BBB is its elevated mitochondrial content compared to peripheral endothelial cells, although the functional implications of this phenomenon remain unknown. Here we studied BBB mitochondrial function in the context of the 22q11.2 deletion syndrome (22qDS), a condition associated with a highly increased risk for neuropsychiatric disease. As the 22q11.2 deletion includes 6 mitochondrial genes, and because we have previously identified BBB impairment in 22qDS, we addressed the hypothesis that mitochondrial deficits contribute to BBB dysfunction and impact behavior in this condition. We report mitochondrial impairment in human induced pluripotent stem cell (iPSC)-derived BBB endothelial cells from 22qDS patients, and in BBB endothelial cells from a mouse model of 22qDS. Remarkably, treatment to improve mitochondrial function attenuates mitochondrial deficits and enhances BBB function in both the iPSC and mouse 22qDS models. This treatment also corrected social memory in the mouse model, a deficit previously associated with BBB dysfunction. As BBB integrity correlated with social memory performance, together our findings suggest that mitochondrial dysfunction in the BBB influences barrier integrity and behavior in 22qDS. | | 5:30p |
Delayed cerebrovascular dysfunction and social deficits after traumatic brain injury
Traumatic brain injury (TBI) survivors face debilitating long-term psychosocial consequences, including social isolation and depression. Acute TBI modifies neurovascular physiology and behavior but a gap in our understanding are the chronic physiological implications of altered brain perfusion on behavioral activities, particularly social interactions. We investigated longitudinal functional vascular networks across the brain for 2-months post-TBI and its impact on social behavior. Adult C57/BL6 male mice received a moderate cortical TBI. Behavior (foot-fault, open-field, 3-chamber social preference) was assessed at baseline, 3-, 7-, 14-, 30-, and 60-days post injury (dpi) followed by magnetic resonance imaging (MRI, 9.4T). Anatomical MRI (T2-weighted), dynamic susceptibility contrast (DSC) perfusion weighted MRI (PWI) were acquired at each temporal epoch. After the final 60dpi MRI, animals underwent transcardial perfusion fixation to map angioarchitecture. MRI data were analyzed using standardized protocols followed by cross-correlations between social behavior, cerebral perfusion, and vascular metrics. Social behavior deficits at 60dpi emerged as reduced interaction with a familiar cage-mate (partner). We observed multiphasic decrements in cerebral blood flow (CBF) encompassing lesion and perilesional cortex where acute reductions at 3-14dpi partially recovered by 30dpi, followed by significant reductions in perfusion at 60dpi. The CBF perturbations extended antero-posteriorly from the ipsilateral TBI impact site but also adulterated contralateral brain regions. CBF reductions impacted regions known to regulate social behavior including hippocampus, hypothalamus, and rhinal cortex. Alongside perfusion deficits at 60dpi, social isolation in TBI-mice emerged with a significant decline in preference to spend time with a cage mate. Cortical vascular density was also reduced corroborating the decline in brain perfusion and social interaction. Thus, the novel temporal neurovascular loss, and subsequent recovery followed by chronic decrements are broadly reflected by social interaction perturbations. Our correlations strongly implicate a linkage between vascular density, cerebral perfusion, and social interactions, where early evaluation can potentially predict long-term outcomes. Thus, our study provides a clinically relevant timeline of alterations in functional vascular recovery that can guide research for future therapeutics. | | 6:47p |
Healthy dietary choices involve prefrontal mechanisms associated with long-term reward maximization but not cognitive control
Taste and health are critical factors to be considered when choosing foods. Prioritizing healthiness over tastiness requires self-control. It has also been suggested that self-control is guided by cognitive control. We then hypothesized that neural mechanisms underlying healthy food choice are associated with both self-control and cognitive control. Human participants performed a food choice task and a working memory (WM) task during functional MRI scanning. Their degree of self-control was assessed behaviorally by the value discount of delayed monetary rewards in intertemporal choice. Prioritizing healthiness in food choice was associated with greater activity in the superior, dorsolateral, and medial prefrontal cortices. Importantly, the prefrontal activity was greater in individuals with smaller delay discounting (i.e., high self-control) who preferred a delayed larger reward to an immediate smaller reward in intertemporal choice. On the other hand, WM activity did not show a correlation with delay discounting or food choice activity, which was further supported by supplementary results that analyzed data from the Human Connectome Project. Our results suggest that the prefrontal cortex plays a critical role in healthy food choice, which requires self-control, but not cognitive control, for maximization of reward attainments in a remote future. | | 6:47p |
Multimodal classification of neurons in the lateral septum
The lateral septum (LS) is a nucleus in the ventral forebrain that modulates complex social and affective behaviors. Several distinct neuronal types have been described in the LS; however, the full extent of this cellular and molecular diversity remains unclear. We address this gap by profiling the transcriptional identity of mature LS neurons originating from two progenitor lineages defined by their anatomical location and expression of the transcription factor Nkx2.1. We describe 12 molecularly distinct subtypes of LS neurons that fall into two main groups: those with a history of Nkx2.1 expression and those without. We discovered that LS neurons from the Nkx2.1 lineage share an enrichment of select cell adhesion and communication molecules. Despite this, we found that LS neurons that have distinct developmental origins can exhibit significant transcriptional similarities. We then examined the spatial relationships among neurons in the LS, revealing that each subtype occupies a discrete anatomical domain. These anatomical domains are defined by graded patterns of gene expression that correlate with the molecular taxonomy of LS neuron subtypes and encode proteins involved in synaptic signaling. Lastly, we genetically labeled non-overlapping subgroups of LS neurons, and detailed their connective, morphological, and electrophysiological properties. Our findings offer a deeper understanding of neuronal heterogeneity in the LS, paving the way for future studies into how these neuronal types contribute to regulating emotional and motivated behaviors. | | 6:47p |
Generalizable Neural Models of Emotional Engagement and Disengagement
Emotional reactivity to negative content profoundly impacts our mental well-being and is a hallmark of disorders characterized by emotion dysregulation. Traditional approaches have examined emotional responses and regulation in isolation, neglecting their temporal dynamics. Movie designs can capture both, in their natural progression throughout time, yet they pose complexity due to the mix of relevant and irrelevant information. To address these challenges and uncover general neural mechanisms of affect, we used dynamic predictive modeling across different narratives, emotional contexts, and participant groups. We analyzed two independent data sets containing different narratives of highly emotionally negative content and one neutral narrative during functional magnetic resonance imaging (fMRI). Following fMRI scanning, individuals provided continuous subjective annotations of emotional intensity throughout these movie clips. Patterns of functional connectivity predicting group response of emotional disengagement in negative movies generalized to diverse narratives and participants, demonstrating specificity to negative content. This prediction involved widespread between-network connections increases. Conversely, emotional engagement generalized across narratives and participants, including neutral contexts, with a less intense emotional intensity induction. Prediction for engagement was marked by widespread between-network connections decreases. Activation analyses distinguished brain regions for disengagement in the default network and engagement in the dorsal attention and visual network. These patterns remained consistent across studies and emotional contexts, revealing generic engagement and disengagement responses even in less emotional movie contexts. These findings demonstrate that movies elicit behavioral and neural responses that contribute to understanding the ecological generalizability of emotional cinematic experiences. Together this work helps to better understand cognitive and neural mechanisms underpinning engagement in and disengagement from emotionally evocative narratives. | | 6:47p |
Theta-burst direct electrical stimulation remodels human brain networks
Patterned brain stimulation is a powerful therapeutic approach for treating a wide range of brain disorders. In particular, theta-burst stimulation (TBS), characterized by rhythmic bursts of 3-8 Hz mirroring endogenous brain rhythms, is delivered by transcranial magnetic stimulation to improve cognitive functions and relieve symptoms of depression. However, the mechanism by which TBS alters underlying neural activity remains poorly understood. In 10 pre-surgical epilepsy participants undergoing intracranial monitoring, we investigated the neural effects of TBS. Employing intracranial EEG (iEEG) during direct electrical stimulation across 29 stimulation cortical locations, we observed that individual bursts of electrical TBS consistently evoked strong neural responses spanning broad cortical regions. These responses exhibited dynamic changes over the course of stimulation presentations including either increasing or decreasing voltage responses, suggestive of short-term plasticity in the amplitude of the local field potential voltage response. Notably, stronger stimulation augmented the mean amplitude and distribution of TBS responses , leading to greater proportion of recording sites demonstrating short-term plasticity. TBS responses were stimulation site-specific and propagated according to the underlying functional brain architecture, as stronger responses were observed in regions with strong baseline effective (cortico-cortical evoked potentials) and functional (low frequency phase locking) connectivity. Further, our findings enabled the predictions of locations where both TBS responses and change in these responses (e.g. short-term plasticity) were observed. Future work may focus on using pre-treatment connectivity alongside other biophysical factors to personalize stimulation parameters, thereby optimizing induction of neuroplasticity within disease-relevant brain networks. | | 8:02p |
A multidimensional investigation of sleep and biopsychosocial profiles with associated neural signatures
Sleep is essential for optimal functioning and health. Interconnected to multiple biological, psychological and socio-environmental factors (i.e., biopsychosocial factors), the multidimensional nature of sleep is rarely capitalized on in research. Here, we deployed a data-driven approach to identify sleep-biopsychosocial profiles that linked self-reported sleep patterns to inter-individual variability in health, cognition, and lifestyle factors in 770 healthy young adults. We uncovered five profiles, including two profiles reflecting general psychopathology associated with either reports of general poor sleep or an absence of sleep complaints (i.e., sleep resilience) respectively. The three other profiles were driven by sedative-hypnotics-use and social satisfaction, sleep duration and cognitive performance, and sleep disturbance linked to cognition and mental health. Furthermore, identified sleep-biopsychosocial profiles displayed unique patterns of brain network organization. In particular, somatomotor network connectivity alterations were involved in the relationships between sleep and biopsychosocial factors. These profiles can potentially untangle the interplay between individuals' variability in sleep, health, cognition and lifestyle - equipping research and clinical settings to better support individual's well-being. |
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