bioRxiv Subject Collection: Neuroscience's Journal
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Saturday, April 27th, 2024
| Time |
Event |
| 5:36a |
Neural networks representing temporal expectation in mice
The ability to attend to specific moments in time is crucial for survival across species facilitating perception and motor performance by leveraging prior temporal knowledge for predictive processing. Despite its importance, the neural mechanisms underlying the utilization of macro-scale and meso-scale neural resources during temporal processing and their relationship to behavioural strategies and motor responses remain largely unexplored. To investigate the capacity for predictive temporal structure of multisensory stimuli to optimize motor behaviour, we established a behavioural paradigm, in which mice were trained to an auditory-cue and visual-target presented at expected or unexpected temporal delays. Using a combination of stimulus-evoked and resting-state functional magnetic resonance imaging, we examined task-related evoked activity in brain-wide networks and found that that the formation of temporal expectations relying on accumulated sensory information and combined multisensory input involves plasticity across large macro-scale cortical networks comprised of primary sensory systems, sensory association areas including posterior parietal cortex, retrosplenial cortex, prefrontal top-down executive control centres of the brain, as well as hippocampal networks. Additionally, employing in vivo two-photon calcium imaging, we explored local single-cell dynamics within the posterior parietal cortex during this task and found that temporal expectation could be decoded directly from neuronal activity within this brain region. Overall, our study provides insights into the neural correlates underlying the formation of multisensory temporal expectations in the mouse brain and highlights the recruitment of neural resources across temporally-driven statistical learning processes. | | 5:36a |
Menopause status and sex affect memory for spatial context information and white matter microstructure at midlife
Decline in spatial context memory emerges in midlife, the time when most females transition from pre- to post-menopause. Recent evidence suggests that, among post-menopausal females, advanced age is associated with functional brain alterations and lower spatial context memory. However, it is unknown whether similar effects are evident for white matter (WM) and, moreover, whether such effects contribute to sex differences at midlife. To address this, we conducted a study on 96 cognitively unimpaired middle-aged adults (30 males, 32 pre-menopausal females, 34 post-menopausal females). Spatial context memory was assessed using a face-location memory paradigm, while WM microstructure was assessed using diffusion tensor imaging. Behaviorally, advanced age was associated with lower spatial context memory in post- menopausal females but not pre-menopausal females or males. Additionally, advanced age was associated with microstructural variability in predominantly frontal WM (e.g., anterior corona radiata, genu of corpus callosum), which was related to lower spatial context memory among post-menopausal females. Our findings suggest that post-menopausal status enhances vulnerability to age effects on the brain's WM and episodic memory. | | 5:36a |
Mind captioning: Evolving descriptive text of mental content from human brain activity
A central challenge in neuroscience is decoding brain activity to uncover the mental content comprising multiple components and their interactions. Despite progress in decoding language-related information from human brain activity, generating comprehensive descriptions of intricate and structured mental content linked to visual semantics remains elusive. Here, we present a method that progressively generates descriptive text mirroring brain representations via semantic features computed by a deep language model. We constructed linear decoding models to decode brain activity, measured by functional magnetic resonance imaging (fMRI) while subjects viewed videos, into semantic features of corresponding video captions. We then iteratively optimized candidate descriptions by aligning their semantic features with the brain-decoded features through word replacement and interpolation. This process resulted in the evolution of increasingly well-structured descriptions that faithfully captured the viewed content. Remarkably, comprehensible descriptions were generated even when excluding the fronto-temporal language areas from the analysis, highlighting explicit representations of structured semantic information outside the typical language network. Additionally, our method generalized to generate descriptions of imagined content, providing a means to interpret intricate mental content by translating brain signals into linguistic descriptions. These findings pave the way for non-verbal thought-based brain-to-text communication, potentially aiding individuals facing difficulties in language expression. | | 5:36a |
Microglial MyD88-dependent pathways are regulated in a sex specific manner in the context of HMGB1-induced anxiety
Chronic stress is a major risk factor for development and recurrence of anxiety disorders. Chronic stress has been shown to impact the immune system, causing microglial activation in the medial prefrontal cortex (mPFC), a brain region involved in the pathogenesis of anxiety. HMGB1 is both an established modulator of neuronal firing and a potent pro-inflammatory stimulus that is released from neuronal and non-neuronal cells following stress. HMGB1 in the context of stress acts as a danger associated molecular pattern (DAMP) instigating robust proinflammatory responses throughout the brain; so much so, that localized drug delivery of HMGB1 alters behavior in the absence of any other forms of stress i.e. social isolation, or behavioral stress models. Few studies have investigated the molecular mechanisms which underlie HMGB1 associated behavioral effects in a cell-specific manner. The aim of this study is to investigate cellular and molecular mechanisms underlying HMGB1 induced behavioral dysfunction with regards to cell-type specificity and potential sex differences. Here, we report that both male and female mice exhibited anxiety-like behavior following increased HMGB1 in the mPFC as well as changes in microglial morphology. However, only female mice showed microglial activation characterized by increased phagocytic capacity and decreased Tmem119 expression. Moreover, when measuring RNA from isolated microglia and non-microglial cells from the frontal cortex we found that female HMGB1 treated mice displayed a robust increase of RAGE and MyD88. Given these findings, to further investigate the underlying molecular mechanisms associated with HMGB1 induced anxiety-like behavior and microglia activation in mice, we used cKO (conditional knockout) mice with conditional deletion of MyD88 in microglia and repeated the paradigm. For males, we saw that the genetic manipulation did not prevent behavioral deficits in response to HMGB1 treatment. However, female cKO mice were protected from HMGB1- induced behavioral deficits. This study supports the hypothesis that the MyD88 signaling in microglia may be a crucial mediator of stress response in adult female mice. | | 10:51a |
Structure, dynamics, coding and optimal biophysical parameters of efficient excitatory-inhibitory spiking networks
The principle of efficient coding posits that sensory cortical networks are designed to encode maximal sensory information with minimal metabolic cost. Despite the major influence of efficient coding in neuroscience, it has remained unclear whether fundamental empirical properties of neural network activity can be explained solely based on this normative principle. Here, we rigorously derive the structural, coding, biophysical and dynamical properties of excitatory-inhibitory recurrent networks of spiking neurons that emerge directly from imposing that the network minimizes an instantaneous loss function and a time-averaged performance measure enacting efficient coding. The optimal network has biologically-plausible biophysical features, including realistic integrate-and-fire spiking dynamics, spike-triggered adaptation, and a non-stimulus-specific excitatory external input regulating metabolic cost. The efficient network has excitatory-inhibitory recurrent connectivity between neurons with similar stimulus tuning implementing feature-specific competition, similar to that recently found in visual cortex. Networks with unstructured connectivity cannot reach comparable levels of coding efficiency. The optimal biophysical parameters include 4 to 1 ratio of excitatory vs inhibitory neurons and 3 to 1 ratio of mean inhibitory-to-inhibitory vs. excitatory-to-inhibitory connectivity that closely match those of cortical sensory networks. The efficient network has biologically-plausible spiking dynamics, with a tight instantaneous E-I balance that makes them capable to achieve efficient coding of external stimuli varying over multiple time scales. Together, these results explain how efficient coding may be implemented in cortical networks and suggests that key properties of biological neural networks may be accounted for by efficient coding. | | 10:51a |
A detailed spatio-temporal atlas of the white matter tracts for the fetal brain
This study presents the construction of a comprehensive spatiotemporal atlas detailing the development of white matter tracts in the fetal brain using diffusion magnetic resonance imaging (dMRI). Our research leverages data collected from fetal MRI scans conducted between 22 and 37 weeks of gestation, capturing the dynamic changes in the brain's microstructure during this critical period. The atlas includes 60 distinct white matter tracts, including commissural, projection, and association fibers. We employed advanced fetal dMRI processing techniques and tractography to map and characterize the developmental trajectories of these tracts. Our findings reveal that the development of these tracts is characterized by complex patterns of fractional anisotropy (FA) and mean diffusivity (MD), reflecting key neurodevelopmental processes such as axonal growth, involution of the radial-glial scaffolding, and synaptic pruning. This atlas can serve as a useful resource for neuroscience research and clinical practice, improving our understanding of the fetal brain and potentially aiding in the early diagnosis of neurodevelopmental disorders. By detailing the normal progression of white matter tract development, the atlas can be used as a benchmark for identifying deviations that may indicate neurological anomalies or predispositions to disorders. | | 4:31p |
Neural activity for complex sounds in the marmoset medial prefrontal cortex
Vocalizations play an important role in the daily life of nonhuman primates and are likely precursors of human language. Recent functional imaging studies in the highly vocal common marmoset (Callithrix jacchus) have suggested that medial prefrontal cortex area 32 may be a part of a vocalization-processing network but the response properties of area 32 neurons to auditory stimuli remain unknown. Here, we performed electrophysiological recordings in area 32 with high-density Neuropixels probes and characterized neuronal responses to a variety of sounds including conspecific vocalizations. More than half of the neurons in area 32 responded to conspecific vocalizations and other complex auditory stimuli. These responses exhibited dynamics consisting of an initially non-selective reduction in neural activity, followed by an increase in activity that immediately conveyed sound selectivity. Our findings demonstrate that primate mPFC area 32 plays a critical role in processing species-specific and biologically relevant sounds. | | 5:46p |
Hearing function moderates age-related changes in brain morphometry in the HCP Aging cohort
Introduction: There are well-established relationships between aging and neurodegenerative changes, and between aging and hearing loss. The goal of this study was to determine how structural brain aging is influenced by hearing loss. Methods: Human Connectome Project Aging (HCP-A) data were analyzed, including T1-weighted MRI and Words in Noise (WIN) thresholds (n=623). Freesurfer extracted gray and white matter volume, and cortical thickness, area, and curvature. Linear regression models targeted (1) interactions between age and WIN threshold and (2) correlations with WIN threshold adjusted for age, both corrected for false discovery rate (pFDR<0.05). Results: WIN threshold moderated age-related increase in volume in bilateral inferior lateral ventricles, with higher threshold associated with increased age-related ventricle expansion. Age-related deterioration in occipital cortex was also increased with higher WIN thresholds. When controlling for age, high WIN threshold was correlated with reduced cortical thickness in Heschl's gyrus, calcarine sulcus, and other sensory regions, and reduced temporal lobe white matter. Older volunteers with poorer hearing and cognitive scores had the lowest volume in left parahippocampal white matter. Conclusions: Preserved hearing abilities in aging associated with a reduction of age-related changes to medial temporal lobe, and preserved hearing at any age associated with preserved cortical tissue in auditory and other sensory regions. Future longitudinal studies are needed to assess the causal nature of these relationships, but these results indicate interventions which preserve hearing function may combat some neurodegenerative changes in aging. | | 6:21p |
Single-nucleus and spatial transcriptomic profiling of human temporal cortex and white matter reveals novel associations with AD pathology
Alzheimer's disease (AD) is a neurodegenerative disorder with complex pathological manifestations and is the leading cause of cognitive decline and dementia in elderly individuals. A major goal in AD research is to identify new therapeutic pathways by studying the molecular and cellular changes in the disease, either downstream or upstream of the pathological hallmarks. In this study, we present a comprehensive investigation of cellular heterogeneity from the temporal cortex region of 40 individuals, comprising healthy donors and individuals with differing tau and amyloid burden. Using single-nucleus transcriptome analysis of 430,271 nuclei from both gray and white matter of these individuals, we identified cell type-specific subclusters in both neuronal and glial cell types with varying degrees of association with AD pathology. In particular, these associations are present in layer specific glutamatergic (excitatory) neuronal types, along with GABAergic (inhibitory) neurons and glial subtypes. These associations were observed in early as well as late pathological progression. We extended this analysis by performing multiplexed in situ hybridization using the CARTANA platform, capturing 155 genes in 13 individuals with varying levels of tau pathology. By modeling the spatial distribution of these genes and their associations with the pathology, we not only replicated key findings from our snRNA data analysis, but also identified a set of cell type-specific genes that show selective enrichment or depletion near pathological inclusions. Together, our findings allow us to prioritize specific cell types and pathways for targeted interventions at various stages of pathological progression in AD. | | 6:21p |
Pharmaco-resistant temporal lobe epilepsy gradually perturbs the cortex-wide excitation-inhibition balance
Excitation-inhibition (E/I) imbalance is theorized as a key mechanism in the pathophysiology of epilepsy, with a mounting body of previous research focusing on elucidating its cellular manifestations. However, there are limited studies into E/I imbalance at macroscale and its microcircuit-level mechanisms and clinical associations. In our current work, we computed the Hurst exponent--a previously validated index of the E/I ratio--from resting-state fMRI time series, and simulated microcircuit parameters using biophysical computational models. We found a broad reduction in the Hurst exponent in pharmaco-resistant temporal lobe epilepsy (TLE), indicative of a shift towards more excitable network dynamics. Connectome decoders pointed to temporolimbic and frontocentral areas as plausible network epicenters of E/I imbalance. Computational simulations further revealed that enhancing cortical excitability in patients likely reflected atypical increases in recurrent connection strength of local neuronal ensembles. Moreover, mixed cross-sectional and longitudinal analyses revealed heightened E/I elevation in patients with longer disease duration, more frequent electroclinical seizures and inter-ictal epileptic spikes, and worse cognitive functioning. Replicated in an independent dataset, our work provides compelling in-vivo evidence of a macroscale shift in E/I balance in TLE patients that undergoes progressive changes and underpins cognitive impairments, potentially informing treatment strategies targeting E/I mechanisms. |
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