bioRxiv Subject Collection: Neuroscience's Journal
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Friday, February 9th, 2024
| Time |
Event |
| 12:16a |
Bayesian Modelling Approaches for Breath-Hold Induced Cerebrovascular Reactivity
Cerebrovascular reactivity (CVR) reflects the ability of blood vessels to dilate and constrict in response to a vasoactive stimulus and is an important indicator of cerebrovascular health. CVR can be mapped non-invasively with functional magnetic resonance imaging (fMRI) based on blood oxygen level-dependent (BOLD) contrast in combination with a breath-hold (BH) task. There are several ways to analyse this type of data and retrieve individual CVR amplitude and timing information. The most common approach involves employing a time-shifted general linear model with the measured end-tidal carbon dioxide signal as a regressor of interest. In this work, we introduce a novel method for CVR mapping based on a variational Bayesian approach. We analysed BOLD fMRI data from six participants that performed a BH task in ten different sessions each, and computed the corresponding CVR amplitude and delay maps for each session/subject. No statistically significant differences were observed between the modelling approaches in the CVR delay and amplitude maps in grey matter. Notably, the largest difference between methods was apparent in the case of low CVR amplitude, attributed to how each method addressed noisy voxels, particularly in white matter and cerebral spinal fluid. Both approaches showed highly reproducible CVR amplitude maps where between-subject variability was significantly larger than between-session variability. Furthermore, our results illustrated that the Bayesian approach is more computationally efficient, and future implementations could incorporate more complex noise models, non-linear fitting, and physiologically meaningful information into the model in the form of priors. This work demonstrates the utility of variational Bayesian modelling for CVR mapping and highlights its potential for characterising BOLD fMRI dynamics in the study of cerebrovascular health and its application to clinical settings. | | 12:48a |
Generation of surrogate brain maps preserving spatial autocorrelation through random rotation of geometric eigenmodes
The brain expresses activity in complex spatiotemporal patterns, reflected in the influence of spatially distributed cytoarchitectural, biochemical, and genetic properties. The correspondence between these multimodal "brain maps" may reflect underlying causal pathways and is hence a topic of substantial interest. However, these maps possess intrinsic smoothness (spatial autocorrelation, SA) which can inflate spurious cross-correlations, leading to false positive associations. Identifying true associations requires knowledge about the distribution of correlations that arise by chance in the presence of SA. This null distribution can be generated from an ensemble of surrogate brain maps that preserve internal SA but break correlations between maps. The present work introduces "eigenstrapping", using a spectral decomposition of cortical and subcortical surfaces in terms of geometric eigenmodes, and then randomly rotating these modes to produce SA-preserving surrogate brain maps. It is shown that these surrogates appropriately represent the null distribution of chance pairwise correlations, with similar or superior false positive control to current state-of-the-art procedures. Eigenstrapping is fast, eschews the need for parametric assumptions about the nature of the SA, and works with maps defined on smooth surfaces with or without a boundary. It generalizes to broader classes of null models than existing techniques, offering a unified approach for inference on cortical and subcortical maps, spatiotemporal processes, and complex patterns possessing higher-order correlations. | | 12:48a |
Spike Neural Network of Motor Cortex Model for Arm Reaching Controlling
Motor Cortex modeling is significant to understand movement planning and execution, and inter-connected recurrent neural network has successful described the dynamics of neurons. However, most of existing methods take continues signal based neural networks to simulate the MC activities, which do not reflect the biological spike neural signal. To address this limitation, we proposed a spike neural network based modeling approach to model the Motor Cortex activity in arm reaching task. Specifically, we built a model of motor cortex based on integrate-and-fire spiking neurons with conductance-based synapses. Second, we carefully design the interconnections of neurons with two different time scale and assigned them into two layers. Besides, prior knowledge based parameter initialization is also proposed to ensure the spikes communication and the training performance. Experiments show the effectiveness of proposed the method that high similar with real spike at single cell and population level. | | 2:02a |
Experience and behavior modulate piriform cortex odor representation in freely moving mice
In rodents, activity in the piriform cortex (PC) has been shown to reliably encode the identity of olfactory information within single sessions of odor delivery. However, recent evidence from chronic PC recordings found significant unreliability in this ensemble code over longer periods. The causes of this phenomenon, termed representational drift, are still being investigated across multiple sensory systems, but prior work has suggested a role for animal behavior in this observed unreliability of coding. To explore this possibility in PC, we recorded from the same populations of neurons in freely-moving, awake mice using micro-endoscopic calcium imaging as they gained passive experience with a panel of odorants over 5 consecutive days. As in prior studies, PC odor responses within a single session could be used to accurately decode odor identity. However, responses became less consistent across days of experience as odor-evoked response properties of the neurons shifted with experience. During these recordings, within and across sessions, decreases in olfactory investigative behavior correlated with decreased odor-evoked response from PC neurons. Similarly, decreases in odor investigation correlated with a decrease in representational consistency, and trials with greater odor investigation could be used to decode odor identity from PC neurons more accurately over time. Overall, this data supports recent evidence of long-term shifts in the ensembles of PC neurons encoding odor-identity (drift) but supports a role for behavioral modulation of overall PC activity and ensemble response consistency. | | 2:02a |
Neural basis of self-control
Humans are often tempted by small, but immediate rewards that seem more attractive than a larger, delayed reward, even when such choices are clearly against one's own best interest. Resisting this temptation and remaining committed to a long-term goal requires self-control, the ability to inhibit self-defeating behavior. Here, we report evidence that neurons in the Supplementary Eye Field encode self-control of oculomotor behavior. We designed a modified version of the intertemporal choice task that distinguishes states of high and low self-control. Supplementary Eye Field neurons encodes distinct levels of self-control during all stages of the trial, even before any choice targets or a later temptation were presented. Fluctuations in Supplementary Eye Field activity were predictive of the monkeys' behavioral response to temptation, suggesting Supplementary Eye Field is critical for self-control behaviors. A partially overlapping population predicted the initial choice, revealing a common neuronal mechanism underlying the ability to make prudent choices that are more beneficial in the long run, and the ability to adhere to those choices by exercising self-control and resisting temptation. Our findings suggest that Supplementary Eye Field is part of a neuronal circuit that underlies the capacity for self-control, which is crucial for maintaining and achieving long-term goals. | | 2:02a |
Insulin resistance alters the coupling between cerebral blood flow and glucose metabolism in younger and older adults: Implications for neurovascular coupling
Rising rates of insulin resistance and an ageing population are set to exact an increasing toll on individuals and society. Here we examine the contribution of insulin resistance and age to the coupling of cerebral blood flow and glucose metabolism; a critical process in the supply of energy for the brain. Thirty-four younger (20-42 years) and 41 older (66-86 years) healthy adults underwent a simultaneous resting state MR/PET scan, including arterial spin labelling. Rates of cerebral blood flow and glucose metabolism were derived using a functional atlas of 100 brain regions. Older adults had lower cerebral blood flow than younger adults in 95 regions, reducing to 36 regions after controlling for cortical atrophy and blood pressure. Younger and older insulin sensitive adults showed small, negative correlations between relatively high rates of regional cerebral blood flow and glucose metabolism. This pattern was inverted in insulin resistant older adults, who showed hypoperfusion and hypometabolism across the cortex, and a positive coupling. In insulin resistant younger adults, coupling showed inversion to positive correlations, although not to the extent seen in older adults. Our findings suggest that the normal course of ageing and insulin resistance alter the rates and coupling of cerebral blood flow and metabolism. They underscore the criticality of insulin sensitivity to brain health across the adult lifespan. | | 2:37a |
Backpropagation-Based Recollection of Memories: Biological Plausibility and Computational Efficiency
Since the advent of the neuron doctrine more than a century ago, information processing in the brain is widely believed to follow the forward pre to post-synaptic neurons direction. Challenging this view, we introduce the backpropagation-based recollection hypothesis as follows: Cue-based memory recollection occurs when backpropagated Action Potentials (APs), originating in sparse neurons that uniquely activate in response to a specific trace being recalled (e.g. image of a cat), travel backwards. The resulting transient backpropagating currents follow the available open backward and lateral pathways, guided by synaptic weights or couplings. In doing so, they stimulate the same neurons that fired during the very first perception and subsequent encoding, effectively allowing a ''replay'' of the experience (e.g., recalling the image of the cat). This process is pervasive, seen in tasks like cue-based attention, imagination, future episodic thinking, modality-specific language understanding, and naming. After detailing our hypothesis, we challenge it against a thorough literature review, finding compelling evidence supporting our claims. We further found that gap junctions could be a plausible medium for such currents, and that cholinergic modulation, which is known to favour backpropagated APs and is crucial for memory, is a reasonable candidate trigger for the entire process. We then leverage computer simulations to demonstrate the computational efficiency of the backpropagation-based recollection principle in (i) reconstructing an image, backwards, starting from its forward-pass sparse activations and (ii) successfully naming an object with a comparable high accuracy as a state of the art machine learning classifier. Given the converging evidence and the hypothesis's critical role in cognition, this paradigm shift warrants broader attention: it opens the way, among others, to novel interpretations of language acquisition and understanding, the interplay between memory encoding and retrieval, as well as reconciling the apparently opposed views between sparse coding and distributed representations, crucial for developing a theory of consciousness and the mind. | | 11:18a |
Microglia-astrocyte crosstalk regulates synapse remodeling via Wnt signaling
Astrocytes and microglia are emerging key regulators of activity-dependent synapse remodeling that engulf and remove synapses in response to changes in neural activity. Yet, the degree to which these cells communicate to coordinate this process remains an open question. Here, we use whisker removal in postnatal mice to induce activity-dependent synapse removal in the barrel cortex. We show that astrocytes do not engulf synapses in this paradigm. Instead, astrocytes reduce their contact with synapses prior to microglia-mediated synapse engulfment. We further show that reduced astrocyte-contact with synapses is dependent on microglial CX3CL1-CX3CR1 signaling and release of Wnts from microglia following whisker removal. These results demonstrate an activity-dependent mechanism by which microglia instruct astrocyte-synapse interactions, which then provides a permissive environment for microglia to remove synapses. We further show that this mechanism is critical to remodel synapses in a changing sensory environment and this signaling is upregulated in several disease contexts. | | 11:18a |
Label free, capillary-scale blood flow mapping in vivo reveals that low intensity focused ultrasound evokes persistent dilation in cortical microvasculature
Non-invasive, low intensity focused ultrasound (FUS) is an emerging neuromodulation technique that offers the potential for precision, personalized therapy. An increasing body of research has identified mechanosensitive ion channels that can be modulated by FUS and support acute electrical activity in neurons. However, neuromodulatory effects that persist from hours to days have also been reported. The brains ability to provide targeted blood flow to electrically active regions involve a multitude of non-neuronal cell types and signaling pathways in the cerebral vasculature; an open question is whether persistent effects can be attributed, at least partly, to vascular mechanisms. Using a novel in vivo optical approach, we found that microvascular responses, unlike larger vessels which prior investigations have explored, exhibit persistent dilation. This finding and approach offers a heretofore unseen aspect of the effects of FUS in vivo and indicate that concurrent changes in neurovascular function may partially underly persistent neuromodulatory effects. | | 11:18a |
Mapping Serotonergic Dynamics using Drug-Modulated Molecular Connectivity
Brain imaging plays a critical role in unraveling the complex functional architecture of animal and human brains. However, individual imaging modalities often face limitations confining them to narrow physiological perspectives. Our study introduces "Molecular connectivity" (MC), a novel concept in imaging that provides a detailed view of molecular interactions and their implications for brain functionality. This research bridges the gap between functional magnetic resonance imaging (fMRI) which tracks neurovascular dynamics, and positron emission tomography (PET), revealing molecular changes at the receptor level. The integration of these techniques can enhance our comprehension of brain-wide effects of drugs. In this study, we delve deeper into this integration by extracting molecular connectivity (MC) at the individual subject level using dynamic [11C]DASB PET scans, which map serotonin transporters (SERT). We particularly focus on assessing the ability of this method to track pharmacological alterations introduced by methylenedioxymethamphetamine (MDMA).
Our comprehensive analysis involves a comparison between MC and functional connectivity (FC), utilizing seed-based and independent component analysis (ICA) during resting states. We identified significant, physiologically pertinent independent components with the [11C]DASB data, thereby enhancing the interpretation of FC results. Remarkably, we observed pronounced changes in MC following a single MDMA administration with strong correlations between resting state MC and the spatial-temporal patterns of MDMAs effect on SERT occupancy.
This research marks a pioneering effort in investigating subject-level MC using PET imaging. Our findings suggests that these advanced imaging techniques can substantially refine our understanding of how drugs influence the overarching functional organization of the brain. | | 11:18a |
Learning within a sensory-motor circuit links action to expected outcome
The cortex integrates sound- and movement-related signals to predict the acoustic consequences of behavior and detect violations from expectations. Although expectation- and prediction-related activity has been observed in the auditory cortex of humans, monkeys, and mice during vocal and non-vocal acoustic behaviors, the specific cortical circuitry required for forming memories, recalling expectations, and making predictions remains unknown. By combining closed-loop behavior, electrophysiological recordings, longitudinal pharmacology, and targeted optogenetic circuit activation, we identify a cortical locus for the emergence of expectation and error signals. Movement-related expectation signals and sound-related error signals emerge in parallel in the auditory cortex and are concentrated in largely distinct neurons, consistent with a compartmentalization of different prediction-related computations. On a trial-by-trial basis, expectation and error signals are correlated in auditory cortex, consistent with a local circuit implementation of an internal model. Silencing the auditory cortex during motor-sensory learning prevents the emergence of expectation signals and error signals, revealing the auditory cortex as a necessary node for learning to make predictions. Prediction-like signals can be experimentally induced in the auditory cortex, even in the absence of behavioral experience, by pairing optogenetic motor cortical activation with sound playback, indicating that cortical circuits are sufficient for movement-like predictive processing. Finally, motor-sensory experience realigns the manifold dimensions in which auditory cortical populations encode movement and sound, consistent with predictive processing. These findings show that prediction-related signals reshape auditory cortex dynamics during behavior and reveal a cortical locus for the emergence of expectation and error. | | 12:34p |
Cocaine sensitization in male rats requires activation of estrogen receptors
Gonadal steroids play a modulatory role in cocaine use disorders, and are responsible for many sex differences observed in the behavioral response to cocaine. In females, it is well established that estradiol enhances the behavioral response to cocaine. In males, we have recently shown that testosterone enhances sensitization to cocaine but its mechanism of action remains to be elucidated. The current study investigated the contribution of DHT, a non-aromatizable androgen, and of estradiol, in regulating cocaine-induced sensitization in male rats. Gonadectomized (GDX) male rats treated with estradiol sensitized to repeated cocaine administration, while GDX rats treated with DHT did not, implicating estradiol in cocaine sensitization. Furthermore, intact male rats treated with the antiestrogen ICI 182,780 did not show sensitization to repeated cocaine. This study demonstrates the pivotal role of estradiol in cocaine-induced neuroplasticity and neuroadaptations in the rodent brain. | | 5:32p |
Sex Differences in Neural Networks Recruited by Frontloaded Binge Alcohol Drinking
Frontloading is an alcohol drinking pattern where intake is skewed toward the onset of access. The goal of the current study was to identify brain regions involved in frontloading. Whole brain imaging was performed in 63 C57Bl/6J (32 female and 31 male) mice that underwent 8 days of binge drinking using the drinking-in-the-dark (DID) model. On days 1-7, three hours into the dark cycle, mice received 20% (v/v) alcohol or water for two hours. Intake was measured in 1-minute bins using volumetric sippers, which facilitated analyses of drinking patterns. On day 8 mice were perfused 80 minutes into the DID session and brains were extracted. Brains were then processed to stain for Fos protein using iDISCO+. Following light sheet imaging, ClearMap2.1 was used to register brains to the Allen Brain Atlas and detect Fos+ cells. For brain network analyses, day 8 drinking patterns were used to characterize mice as frontloaders or non-frontloaders using a recently developed change-point analysis. Based on this analysis the groups were female frontloaders (n = 20), female non-frontloaders (n = 2), male frontloaders (n = 13) and male non-frontloaders (n = 8). There were no differences in total alcohol intake in animals that frontloaded versus those that did not. Only two female mice were characterized as non-frontloaders, thus preventing brain network analysis of this group. Functional correlation matrices were calculated for each group from log10 Fos values. Euclidean distances were calculated from these R values and hierarchical clustering was used to determine modules (highly connected groups of brain regions). In males, alcohol access decreased modularity (3 modules in both frontloaders and non-frontloaders) as compared to water drinkers (7 modules). In females, an opposite effect was observed. Alcohol access (9 modules for frontloaders) increased modularity as compared to water drinkers (5 modules). These results suggest sex differences in how alcohol consumption reorganizes the functional architecture of neural networks. Next, key brain regions in each network were identified. Connector hubs, which primarily facilitate communication between modules, and provincial hubs, which facilitate communication within modules, were of specific interest for their important and differing roles. In males, 4 connector hubs and 17 provincial hubs were uniquely identified in frontloaders (i.e., were brain regions that did not have this status in male non-frontloaders or water drinkers). These represented a group of hindbrain regions (e.g., locus coeruleus and the pontine gray) functionally connected to striatal/cortical regions (e.g., cortical amygdalar area) by the paraventricular nucleus of the thalamus. In females, 16 connector and 17 provincial hubs were uniquely identified which were distributed across 8 of the 9 modules in the female frontloader alcohol drinker network. Only one brain region (the nucleus raphe pontis) was a connector hub in both sexes, suggesting that frontloading in males and females may be driven by different brain regions. In conclusion, alcohol consumption led to fewer, but more densely connected, groups of brain regions in males but not females, and recruited different hub brain regions between the sexes. These results suggest that alcohol frontloading leads to a reduction in network efficiency in male mice. | | 6:49p |
Glial expression of Drosophila UBE3A causes spontaneous seizures modulated by 5-HT signaling
Misexpression of the E3 ubiquitin ligase UBE3Ais thought to contribute to a range of neurological disorders. In the context of Dup15q syndrome, excess genomic copies of UBE3A is thought to contribute to the autism, muscle tone and spontaneous seizures characteristic of the disorder. In a Drosophila model of Dup 15q syndrome, it was recently shown glial-driven expression of the UBE3A ortholog dube3a led to a "bang-sensitive" phenotype, where mechanical shock triggers convulsions, suggesting glial dube3a expression contributes to hyperexcitability in flies. Here we directly compare the consequences of glial- and neuronal-driven dube3a expression on motor coordination and neuronal excitability in Drosophila. We utilized IowaFLI tracker and developed a hidden Markov Model to classify seizure-related immobilization. Both glial and neuronal driven dube3a expression led to clear motor phenotypes. However, only glial-driven dube3a expression displayed spontaneous immobilization events, that were exacerbated at high-temperature (38 {degrees}C). Using a tethered fly preparation we monitored flight muscle activity, we found glial-driven dube3a flies display spontaneous spike discharges which were bilaterally synchronized indicative of seizure activity. Neither control flies, nor neuronal-dube3a overexpressing flies display such firing patterns. Prior drug screen indicated bang-sensitivity in glial-driven dube3a expressing flies could be suppressed by certain 5-HT modulators. Consistent with this report, we found glial-driven dube3a flies fed the serotonin reuptake inhibitor vortioxetine and the 5HT2A antagonist ketanserin displayed reduced immobilization and spike bursting. Together these findings highlight the potential for glial pathophysiology to drive Dup15q syndrome-related seizure activity. |
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