bioRxiv Subject Collection: Neuroscience's Journal
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Monday, October 14th, 2024
| Time |
Event |
| 5:38a |
Neural mechanisms of adaptive value coding in the amygdala
To address their needs, animals must optimize behavior by integrating external cues with internal state signals, such as hunger or thirst, environmental conditions, and past experiences. Accordingly, the perceived value of a reward varies depending on an animal's current needs. Updating the specific value of rewards predicted by external cues depends on the basolateral amygdala (BLA). However, neurophysiological investigations have centered around the assumption of stimulus-invariant value representations and have not been able to account for behavioral findings that support the BLA's ability to represent stimulus-specific value of distinct appetitive or aversive outcomes. To address how the BLA encodes and updates stimulus-specific value representations, we exposed head-fixed mice to distinct sets of gustatory rewards while tracking perceived value using lick microstructural analysis. Two-photon calcium imaging of BLA principal neurons revealed that the magnitude of the BLA population response scaled with perceived reward value and that the values of different rewards were encoded by distinct neuronal subpopulations. Moreover, reward representations rapidly re-scaled when mice were exposed to a reward that was larger than all previous rewards. Finally, value representations depended on an animal's internal state as thirst selectively increased the responses to water rewards whereas aversive experiences strongly attenuated responses to sucrose. Our findings demonstrate that value representations in the BLA are stimulus-specific and highly adaptive to account for changes in relative reward value and to reflect an animal's current affective and homeostatic state. This mechanism enables sensory-specific value updates necessary for state-adapted decision making and learning. | | 5:38a |
Amyloid-beta, alpha-synuclein and tau aggregated co-pathologies enhance neuropathology and neuroinflammation
Lewy pathology due to alpha-synuclein (-syn) inclusions is one of the major hallmarks of Parkinson Disease (PD). A{beta}-Amyloid (A{beta}) and phosphorylated tau, pathologies usually found in Alzheimers Disease (AD), have also been implicated in PD, with over 50% of patients exhibited the co-expression of these proteins (co-pathologies). In both AD and PD postmortem tissue, neuroinflammation, the activation of microglia and resident macrophages and the infiltration of immune cells from the periphery, including T cells and monocytes, are drivers of neurodegeneration. However, how the co-expression of these pathologies contribute to the inflammatory response and overall neurodegenerative disease phenotype remains unknown. To understand how the co-expression of pathologies drives neuropathology, we developed a novel co-pathology model by stereotaxically injecting -syn pre-formed fibrils (PFFs) into the striatum, and AAV-doublemut tau virus into the entorhinal cortex, of 3-month-old J20 transgenic mice with A{beta} pathology. We analyzed immune cell populations in the brain and periphery at 3 months post-induction (3MPI). At 6MPI, neuronal loss in the hippocampus and substantia nigra pars compacta were assessed along with pathological protein deposition. At 3MPI, the co-pathology mouse model begins to exhibit enhanced pathology load in the cortex and hippocampus. There was a robust neuroinflammatory response in interconnected brain regions, including increased microglial cell number, changes in microglial activation markers, and infiltration of T cells. This was synergistic in the co-pathology model, compared to the individual models, supporting the hypothesis that these collectively may drive the progression of disease. | | 5:38a |
Can we predict sleep health based on brain features? A large-scale machine learning study
Objectives: Normal sleep is crucial for brain health. Recent studies have reported robust associations between sleep disturbance and various brain structural and functional traits. However, the complex interplay between sleep health and macro-scale brain organization remains inconclusive. In this study, we aimed to uncover the links between brain imaging features and diverse sleep health-related characteristics by means of Machine Learning (ML). Methods: We used 28,088 participants from the UK Biobank to calculate 4677 structural and functional neuroimaging markers. Then, we employed them to predict self-reported insomnia symptoms, sleep duration, easiness getting up in the morning, chronotype, daily nap, daytime sleepiness, and snoring. We built seven different linear and nonlinear ML models for each sleep health-related characteristic to assess their predictability. Results: We performed an extensive ML analysis that involved more than 100,000 hours of computing. We observed relatively low performance in predicting all sleep health-related characteristics (e.g., balanced accuracy ranging between 0.50-0.59). Across all models, the best performance achieved was 0.59, using a Linear SVM to predict easiness getting up in the morning. Conclusions: The low capability of multimodal neuroimaging markers in predicting sleep health-related characteristics, even under extensive ML optimization in a large population sample suggests a complex relationship between sleep health and brain organization. | | 5:38a |
Tracking the Morphological Evolution of Neuronal Dendrites by First-Passage Analysis
A high degree of structural complexity arises in dynamic neuronal dendrites due to extensive branching patterns and diverse spine morphologies, which enable the nervous system to adjust function, construct complex input pathways and thereby enhance the computational power of the system. Owing to the determinant role of dendrite morphology in the functionality of the nervous system, recognition of pathological changes due to neurodegenerative disorders is of crucial importance. We show that the statistical analysis of a temporary signal generated by cargos that have diffusively passed through the complex dendritic structure yields vital information about dendrite morphology. As a feasible scenario, we propose engineering mRNA-carrying multilamellar liposomes to diffusively reach the soma and release mRNAs, which encodes a specific protein upon encountering ribosomes. The concentration of this protein over a large population of neurons can be externally measured, as a detectable temporary signal. By developing a stochastic coarse-grained approach for first-passage through dendrites, we connect the model parameters to the characteristics of the evolving signal and, on the other hand, map them to the key morphological properties affected by neurodegenerative diseases--- including the density and size of spines, the extent of the tree, and the segmental increase of dendrite diameter towards soma. Thus, we establish a direct link between the dendrite morphology and the statistical characteristics of the detectable signal. Our approach provides a fast noninvasive measurement technique to indirectly extract vital information about the morphological evolution of dendrites in the course of neurodegenerative disease progression. | | 5:38a |
A biophysically-detailed model of inter-areal interactions in cortical sensory processing
Mechanisms of top-down modulation in sensory perception and their relation to underlying connectivity are not completely understood. We present here a biophysically-detailed computational model of two interconnected cortical areas, representing the first steps in a cortical processing hierarchy, as a tool for potential discovery. The model integrates a large body of data from rodent primary somatosensory cortex and reproduces biological features across multiple scales: from a handful of ion channels defining a diversity of electrical types in hundreds of thousands of morphologically detailed neurons, to local and long-range networks mediated by hundreds of millions of synapses. Notably, long-range connectivity in the model incorporates target lamination patterns associated with feed-forward and feedback pathways. We use the model to study the impact of inter-areal interactions on sensory processing. First, we exhibit a cortico-cortical loop between the two model areas (X and Y), wherein sensory input to area X produces a response with two components in time, the first driven by the stimulus and the second by feedback from area Y. We perform a structural and functional characterization of this loop, finding a differential impact of layer-specific pathways in the feed-forward and feedback directions. Second, we explore stimulus discrimination by presenting four different spatially-segregate stimulus patterns. We observe well-defined temporal sequences of functional cell assembly activation, with stimulus specificity in early but not late assemblies in area X, i.e., in the stimulus-driven component of the response but not in the feedback-driven component. We also find the earliest assembly in area Y to be specific to pairs of patterns, consistent with the topography of connections. Finally, we examine the integration of bottom-up and top-down signals. When presenting a second stimulus coincident with the feedback-driven component, we observe an approximate linear superposition of responses. We find the implied lack of interaction consistent with the naive connectivity in the model and the absence of plasticity mechanisms that would underlie the learning of top-down influences. This work represents a first step in the study of inter-areal interactions with biophysically-detailed simulations. | | 5:38a |
X-ray Diffraction Reveals Periodicity in Murine Neocortex
Background: The perineuronal net (PNN) is a form of extracellular matrix which develops as a lattice like structure around neuronal somas, proximal dendrites and synapses. In homeostasis, it supports synaptic stability, protects neurons, and helps regulate inhibition/excitation. In pathology, it has been described as degraded or even absent. Sensory deprivation has been shown to alter PNN structures. New Methods: Here, we measured the X-ray diffraction patterns of mouse brain tissue to establish a novel method for examining nanoscale brain structures. Two groups of mice were examined, a control group, and one which underwent 30 days (P0-P30) of whisker-trimming - an established method of sensory deprivation, affecting the mouse barrel cortex (whisker sensory processing region of somatosensory cortex). Mice were perfused, and primary somatosensory cortices (barrel cortex) were isolated for x-ray diffraction imaging. Results: X-ray images were characterized using a specially developed machine-learning approach, and the clusters that correspond to the two groups are well separated in the space of the principal components. Conclusions: We hypothesize that such separation is related to the development of nanoscale structural components within PNNs of control mice and the absence of such structures in sensory deprived mice. | | 12:45p |
FiNNpy 2.0: Fast MEG source reconstruction
Herein, we present the 2.0 update of FiNNpy, which expands the toolkit's initial scope from the analysis of multi-site electrophysiological activity to track information propagation to include source reconstruction capability for MEG signals. Following the toolkit's design guidelines, the new functionality has been optimized towards minimal resource consumption, making source reconstruction much faster, especially when executed in a parallelized fashion. Furthermore, several quality-of-life aspects are introduced to support source reconstruction, such as grouping source-space activity into cortical areas, a cohesive documentation & in-code extensive literature references, and wrapping of previously terminal exclusive functions of FreeSurfer. | | 3:34p |
Suppression of Visceral Nociception by Selective C-Fiber Transmission Block Using Temporal Interference Sinusoidal Stimulation
Chronic visceral pain management remains challenging due to limitations in selective targeting of C-fiber nociceptors. This study investigates temporal interference stimulation (TIS) on dorsal root ganglia (DRG) as a novel approach for selective C-fiber transmission block. We employed (1) GCaMP6 recordings in mouse whole DRG using a flexible, transparent microelectrode array for visualizing L6 DRG neuron activation, (2) ex vivo single-fiber recordings to assess sinusoidal stimulation effects on peripheral nerve axons, (3) in vivo behavioral assessment measuring visceromotor responses (VMR) to colorectal distension in mice, including a TNBS-induced visceral hypersensitivity model, and (4) immunohistological analysis to evaluate immediate immune responses in DRG following TIS. We demonstrated that TIS (2000 Hz and 2020 Hz carrier frequencies) enabled tunable activation of L6 DRG neurons, with the focal region adjustable by altering stimulation amplitude ratios. Low-frequency (20-50 Hz) sinusoidal stimulation effectively blocked C-fiber and A{delta}-fiber transmission while sparing fast-conducting A-fibers, with 20 Hz showing highest efficacy. TIS of L6 DRG reversibly suppressed VMR to colorectal distension in both control and TNBS-induced visceral hypersensitive mice. The blocking effect was fine-tunable by adjusting interfering stimulus signal amplitude ratios. No apparent immediate immune responses were observed in DRG following hours-long TIS. In conclusion, TIS on lumbosacral DRG demonstrates promise as a selective, tunable approach for managing chronic visceral pain by effectively blocking C-fiber transmission. This technique addresses limitations of current neuromodulation methods and offers potential for more targeted relief in chronic visceral pain conditions. | | 5:35p |
Specific Bacterial Taxa and Their Metabolite, DHPS, Linked to Alzheimers Disease, Parkinsons Disease, and Amyotrophic Lateral Sclerosis.
Neurodegenerative diseases (NDDs) are multifactorial disorders frequently associated with gut dysbiosis, oxidative stress, and inflammation; however, the pathophysiological mechanisms remain poorly understood. We investigated bacterial and metabolic dyshomeostasis in the gut microbiome associated with early disease stages across three NDDs, amyotrophic lateral sclerosis (ALS), Alzheimers Disease (AD), Parkinsons Disease (PD), and healthy controls (HC) and discovered a previously unrecognized link between a microbial-derived metabolite with an unknown role in human physiology, 2,3-dihydroxypropane-1-sulfonate (DHPS), and NDDs. DHPS was downregulated in AD, ALS, and PD, while Eubacterium and Desulfovibrio, capable of metabolizing this metabolite,1-4 were increased in all disease cohorts. Additionally, select taxa within the Clostridia class had strong negative correlations to DHPS suggesting a potential role in DHPS metabolism. Hydrogen sulfide is a catabolic product of DHPS,1,5 and hydrogen sulfide promotes inflammation,6-8 oxidative stress,9 mitochondrial damage,10 and gut dysbiosis,2,11 known hallmarks of NDD. These findings suggest that cryptic sulfur metabolism via DHPS is a missing link in our current understanding of NDD onset and progression. To the best of our knowledge, we are the first to provide evidence of a conserved gut-brain axis linkage of specific bacterial taxa and their metabolism of DHPS shared by three neurodegenerative diseases. | | 6:46p |
Human brain changes after first psilocybin use
Psychedelics have robust effects on acute brain function and long-term behavior but whether they also cause enduring functional and anatomical brain changes is unknown. In a placebo-controlled, within-subjects, electroencephalography, and magnetic resonance imaging study in 28 healthy, entirely psychedelic-naive participants, anatomical and functional brain changes were detected from one-hour to one-month after a single high-dose (25 mg) of psilocybin. Increases in cognitive flexibility, psychological insight, and well-being were seen at one-month. Diffusion imaging done before and one-month after 25mg psilocybin revealed decreased axial diffusivity bilaterally in prefrontal-subcortical tracts that correlated with decreased brain network modularity over the same time period. Decreased modularity also correlated with improved well-being. Increased cortical signal entropy at 1- and 2-hours post-dosing predicted improved psychological well-being at one-month. Next-day psychological insight mediated the entropy to well-being relationship. All effects were exclusive to 25mg psilocybin; no effects occurred with a 1mg placebo dose. | | 6:46p |
IGF-1 IMPACTS NEOCORTICAL INTERNEURON CONNECTIVITY IN EPILEPTIC SPASM GENERATION AND RESOLUTION
Little is known about the mechanisms that generate epileptic spasms following perinatal brain injury. Recent studies have implicated reduced levels of Insulin-like Growth Factor 1 (IGF-1) in these patients brains. Other studies have reported low levels of the inhibitory neurotransmitter, GABA. In the TTX brain injury model of epileptic spasms, we undertook experiments to evaluate the impact of IGF-1 deficiencies on neocortical interneurons and their role in spasms. Quantitative immunohistochemical analyses revealed that neocortical interneurons that express glutamic acid decarboxylase, parvalbumin, or synaptotagmin 2 co-express IGF-1. In epileptic rats, expression of these three interneuron markers were reduced in the neocortex. IGF-1 expression was also reduced, but surprisingly this loss was confined to interneurons. Interneuron connectivity was reduced in tandem with IGF-1 deficiencies. Similar changes were observed in surgically resected neocortex from infantile epileptic spasms syndrome (IESS) patients. To evaluate the impact of IGF-1 deficiencies on interneuron development, IGF-1R levels were reduced in the neocortex of neonatal conditional IGF-1R knock out mice by viral injections. Four weeks later, this experimental maneuver resulted in similar reductions in interneuron connectivity. Treatment with the IGF-1 derived tripeptide, (1-3)IGF-1, abolished epileptic spasms in most animals, rescued interneuron connectivity, and restored neocortical levels of IGF-1. Our results implicate interneuron IGF-1 deficiencies, possibly impaired autocrine IGF-1 signaling and a resultant interneuron dysmaturation in epileptic spasm generation. By restoring IGF-1 levels, (1-3)IGF-1 likely suppresses spasms by rescuing interneuron connectivity. Results point to (1-3)IGF-1 and its analogues as potential novel disease-modifying therapies for this neurodevelopmental disorder. | | 6:46p |
Axon-specific microtubule regulation drives asymmetric regeneration of sensory neuron axons
Sensory dorsal root ganglion (DRG) neurons have a unique pseudo-unipolar morphology in which a stem axon bifurcates into a peripheral and a central axon, with different regenerative abilities. Whereas peripheral DRG axons regenerate, central axons are unable to regrow. Central axon regeneration can however be elicited by a prior conditioning lesion to the peripheral axon. How DRG axon asymmetry is established, remains unknown. Here we developed an in vitro system replicating DRG pseudo-unipolarization and asymmetric axon regeneration. Using this model, we observed that from early development, central DRG axons have a higher density of growing microtubules. This asymmetry was also present in vivo and was abolished by a conditioning lesion that decreased microtubule polymerization of central DRG axons. An axon-specific microtubule-associated protein (MAP) signature, including the severases spastin and katanin and the microtubule regulators CRMP5 and tau, was found and shown to adapt upon conditioning lesion. Supporting its significance, interfering with the DRG MAP signature either in vitro or in vivo, readily abolished central-peripheral asymmetries in microtubule dynamics and regenerative ability. In summary, our data unveil that axon-specific microtubule regulation drives asymmetric regeneration of sensory neuron axons. |
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