bioRxiv Subject Collection: Neuroscience's Journal
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Sunday, February 25th, 2024
| Time |
Event |
| 3:30a |
Expectations about presence enhance the influence of content-specific expectations on low-level orientation judgements
Will something appear and if so, what will it be? Perceptual expectations can concern both the presence and content of a stimulus. However, it is unclear how these different types of expectations interact with each other in biasing perception. Here, we tested how expectations about stimulus presence and content differently affect perceptual inference. Across separate online discovery (N=110) and replication samples (N=218), participants were asked to judge both the presence and content (orientation) of noisy grating stimuli. Crucially, preceding compound cues simultaneously and orthogonally predicted both whether a grating was likely to appear as well as what its orientation would be. We found that expectations of presence interacted with expectations of content, such that the latters effect on discrimination was larger when a stimulus was expected to appear than when it was not. This interaction was observed both when a grating was truly presented and when participants falsely perceived one. Confidence in having seen a grating on the other hand was independently affected by presence and content expectations. Further, modelling revealed higher sensitivity in distinguishing between grating presence and absence following absence cues than presence cues, demonstrating an asymmetry between gathering evidence in favour of stimulus presence and absence. Finally, evidence for overweighted predictions being associated with hallucination-like perception was inconclusive. In sum, our results provide nuance to popular predictive processing accounts of perception by showing that expectations of presence and content have distinct but interacting roles in shaping conscious perception. | | 5:00a |
Graphene microelectrode arrays, 4D structured illumination microscopy, and a machine learning-based spike sorting algorithm permit the analysis of ultrastructural neuronal changes during neuronal signalling in a model of Niemann-Pick disease type C
Simultaneously recording network activity and ultrastructural changes of the synapse is essential for advancing our understanding of the basis of neuronal functions. However, the rapid millisecond-scale fluctuations in neuronal activity and the subtle sub-diffraction resolution changes of synaptic morphology pose significant challenges to this endeavour. Here, we use graphene microelectrode arrays (G-MEAs) to address these challenges, as they are compatible with high spatial resolution imaging across various scales as well as high temporal resolution electrophysiological recordings. Furthermore, alongside G-MEAs, we deploy an easy-to-implement machine learning-based algorithm to efficiently process the large datasets collected from MEA recordings. We demonstrate that the combined use of G-MEAs, machine learning (ML)-based spike analysis, and four-dimensional (4D) structured illumination microscopy (SIM) enables the monitoring of the impact of disease progression on hippocampal neurons which have been treated with an intracellular cholesterol transport inhibitor mimicking Niemann-Pick disease type C (NPC) and show that synaptic boutons, compared to untreated controls, significantly increase in size, which leads to a loss in neuronal signalling capacity. | | 5:00a |
Miniature linear and split-belt treadmills reveal mechanisms of adaptive motor control in walking Drosophila
To navigate complex environments, walking animals must detect and overcome unexpected perturbations. One technical challenge when investigating adaptive locomotion is measuring behavioral responses to precise perturbations during naturalistic walking; another is that manipulating neural activity in sensorimotor circuits often reduces spontaneous locomotion. To overcome these obstacles, we introduce miniature treadmill systems for coercing locomotion and tracking 3D kinematics of walking Drosophila. By systematically comparing walking in three experimental setups, we show that flies compelled to walk on the linear treadmill have similar stepping kinematics to freely walking flies, while kinematics of tethered walking flies are subtly different. Genetically silencing mechanosensory neurons alters step kinematics of flies walking on the linear treadmill across all speeds, while inter-leg coordination remains intact. We also found that flies can maintain a forward heading on a split-belt treadmill by adapting the step distance of their middle legs. Overall, these insights demonstrate the utility of miniature treadmills for studying insect locomotion. | | 5:00a |
Deep Learning Behavioral Phenotyping System in the Diagnosis of Parkinson's Disease with Drosophila melanogaster
Drosophila Melanogaster is widely used as animal models for Parkinsons disease (PD) research. Because of the complexity of MoCap and quantitative assessment among Drosophila Melanogaster, however, there is a technical issue that identify PD symptoms within drosophila based on objective spontaneous behavioral characteristics. Here, we developed a deep learning framework generated from kinematic features of body posture and motion between wildtype and SNCAE46K mutant drosophila genetically modeled {square}-Syn, supporting clustering and classification of PD individuals. We record locomotor activity in a 3D-printed trap, and utilize the pre-analysis pose estimation software DeepLabCut (DLC) to calculate and generate numerical data representing the motion speed, tremor frequency, and limb motion of Drosophila Melanogaster. By plugging these data as the input, the diagnosis result (1/0) representing PD or WT as the output. Our result provides a toolbox which would be valuable in the investigation of PD progressing and pharmacotherapeutic drug development. | | 5:00a |
Synaptic vesicle characterization of iPSC-derived dopaminergic neurons provides insight into distinct secretory vesicle pools
The impairment of dopaminergic (DA) neurons plays a central role in the development of Parkinson's disease. Evidence for distinct populations of synaptic vesicles (SVs) differing in neurotransmitter content (glutamate versus dopamine) has been attributed to differences in trafficking pathways and their exocytosis kinetics. However, the molecular and ultrastructural organization of the two types of vesicles remains poorly understood. Here we examined the development of axonal varicosities in human iPSC-derived DA neurons and glutamatergic neurons (i3Neurons). While i3Neurons are comprised of 40-50 nm small clear SVs, DA neurons are predominantly comprised of large pleomorphic vesicles including empty and dense core vesicles, in addition to the classical SVs. The large vesicles were positive for VMAT2, the monoamine vesicular transporter responsible for loading dopamine, and are distinctly larger in size and spatially segregated from the VGLUT1/2-positive vesicles when expressed in an ectopic SV-like organelle reconstitution system. Moreover, these VMAT2-positive vesicles were also colocalized to known SV markers such as Rab3, SCAMP5, VAMP2, SV2C and can be clustered by the matrix protein synapsin. Our results show that DA neurons display inherent differences in their populations of neurotransmitter-containing secretory vesicles, and iPSC-derived neurons are powerful models for the study of presynaptic structures. | | 5:00a |
Code Multiplexed Nanocapacitor Arrays for Scalable Neural Recordings
Large scale neural recordings are redefining our understanding of the brain. However, simultaneously recording potentials from thousands of microelectrodes remains challenging. We overcome this limitation by measuring activity-induced changes in mutual capacitance. Code division multiplexing enabled simultaneous recordings of neural activity from 1,024 nanocapacitor electrodes at a density of 10k electrodes/mm.2 Features of neural activity i.e., action potentials, bursts, and local field potentials were measured in recordings, benchmarking our device against the state-of-the-art.
SummaryCapacitive sensing of neural activity improves the scalability, fabrication, and miniaturization of microelectrode arrays. | | 5:00a |
Molecular, Cellular, and Developmental Organization of the Mouse Vomeronasal Organ at Single Cell Resolution
We have generated single cell transcriptomic atlases of vomeronasal organs (VNO) from juvenile and adult mice. Combined with spatial molecular imaging, we uncover a distinct, previously unidentified class of cells that express the vomeronasal receptors and a population of canonical olfactory sensory neurons in the VNO. High resolution trajectory and cluster analyses reveal the lineage relationship, spatial distribution of cell types, and a putative cascade of molecular events that specify the V1r, V2r, and OR lineages from a common stem cell population. The expression of vomeronasal and olfactory receptors follow power law distributions, but there is high variability in average expression levels between individual receptor and cell types. Substantial co-expression is found between receptors across clades, from different classes, and between olfactory and vomeronasal receptors, with nearly half from pairs located on the same chromosome. Interestingly, the expression of V2r, but not V1r, genes is associated with various transcription factors, suggesting distinct mechanisms of receptor choice associated with the two cell types. We identify association between transcription factors, surface axon guidance molecules, and individual VRs, thereby uncovering a molecular code that guides the specification of the vomeronasal circuitry. Our study provides a wealth of data on the development and organization of the accessory olfactory system at both cellular and molecular levels to enable a deeper understanding of vomeronasal system function. | | 5:44a |
Hypoxia disrupts circadian rhythms in astrocytes and causes synapse engulfment defects
Astrocytes are emerging as key regulators of neuronal synaptic network maturation and function, through control of synaptic pruning. This is important, because individuals with ASD have excess glutamatergic synapses in the cortex, but the biological mechanisms underlying this phenotype remain unclear.
Here, we used human cortical organoids (hCO) derived from induced pluripotent stem cells (hiPSCs), to examine the effect of hypoxia on synapse engulfment in human astrocytes at postnatal-equivalent stages of development. We identified that hypoxia significantly inhibits the synaptosome phagocytosis, and that this phenotype is mediated through disruptions in the astrocytic circadian rhythm molecular pathway and subsequent decreased expression of MEGF10. Lastly, we demonstrated that circadian clock disruptions are sufficient to induce these observed phenotypes even in the absence of hypoxia, both in hCOs and within the mouse hippocampus in vivo.
Our study uncovers a novel mechanistic link between hypoxia, circadian rhythms disruptions, and synapse pruning by astrocytes, and provides insight into the pathophysiology of ASD, and other neuropsychiatric diseases. Separately, the demonstration of the presence of circadian rhythms in hCOs opens an unprecedented opportunity to dissect the role of circadian clocks in normal brain development and how it contributes to specific diseases of environmental or genetic origin. | | 2:19p |
Cortical tracking of speech is reduced in adults who stutter when listening for speaking
This study explores cortical tracking of speech (CTS) in adults who stutter (AWS) compared to typically fluent adults (TFA) while listening to sentences. We manipulated the upcoming involvement of the speech-motor system during listening: participants either had to simply listen to the sentences (listening only) or complete unfinished sentences by naming a picture (listening-for-speaking). AWS, known for atypical neural structure and functionaing in the speech-motor network, exhibited reduced CTS in the theta band in temporal sensors during the listening-for-speaking task, reflected at the source level in the left temporo-parietal junction and the right pre-motor and supplementary motor regions. Additionally, connectivity analyses reveal that TFA had stronger inter- and intra-hemispheric information transfer in the theta range than AWS in both tasks, involving frontal, temporo-parietal, (pre-)motor, and superior temporal regions, with different patterns according to the task. Notably, increased connectivity from the right superior temporal cortex to the left sensorimotor cortex correlated with faster naming times in the listening-for-speaking task. These findings suggest that atypical speech-motor functioning in stuttering impact also speech perception, especially in situations requiring articulatory alertness, and highlight the involvement of frontal and (pre-) motor regions in normal conditions in CTS.
Significance StatementThis study shows for the first time that individuals with a speech-motor impairment, namely persistent developmental stuttering, also show impaired cortical tracking of speech, especially when upcoming speech production is required. The effects emerge in the theta range, corresponding to the syllabic rhythm, suggested to be an optimal interface between the human biomechanic constraints for producing sounds and the human brains perceptual capabilities for speech. Our study highlights the relevance of speech-motor regions in cortical tracking of speech and suggests that spoken language perception in individuals with speech-motor deficits is an important ground for research, especially in real-life conversational settings where smooth transitioning between listening and speaking is required. | | 5:00p |
Discovery of novel compounds and target mechanisms using a high throughput, multiparametric phenotypic screen in a human neuronal model of Tuberous Sclerosis
Tuberous sclerosis complex (TSC) is a rare genetic disorder caused by mutations in the mTOR pathway genes TSC1 or TSC2. TSC can affect multiple organs including the brain, and most patients (75-90%) present with seizures during early childhood and intractable epilepsy throughout life. mTOR inhibitors, part of the current standard of care, lack the optimal characteristics to fully address patient phenotypes. Here, we report on the application of our all-optical electrophysiology platform for phenotypic screening in a human neuronal model of TSC. We used CRISPR/Cas9-isogenic TSC2-/- iPS cell lines to identify disease-associated changes to neuronal morphology, transcript expression and neuronal excitability. We established a robust multiparametric electrophysiological phenotype which we then validated in TSC patient-derived neurons. We used this phenotype to conduct a screen of [~]30,000 small molecule compounds in human iPS cell-derived neurons and identified chemical scaffolds that rescued the functional TSC disease parameters. Confirmed hits may act via different mechanisms than direct mTOR pathway inhibition. This strategy provides molecular starting points for therapeutic development in TSC and a framework for phenotype discovery and drug screening in other neurological disorders. | | 6:19p |
Mitochondrial origins of the pressure to sleep
The neural control of sleep requires that sleep need is sensed during waking and discharged during sleep. To obtain a comprehensive, unbiased view of molecular changes in the brain that may underpin these processes, we have characterized the transcriptomes of single cells isolated from rested and sleep-deprived flies. Transcripts upregulated after sleep deprivation, in sleep-control neurons projecting to the dorsal fan-shaped body (dFBNs) but not ubiquitously in the brain, encode almost exclusively proteins with roles in mitochondrial respiration and ATP synthesis. These gene expression changes are accompanied by mitochondrial fragmentation, enhanced mitophagy, and an increase in the number of contacts between mitochondria and the endoplasmic reticulum, creating conduits for the replenishment of peroxidized lipids. The morphological changes are reversible after recovery sleep and blunted by the installation of an electron overflow in the respiratory chain. Inducing or preventing mitochondrial fission or fusion in dFBNs alters sleep and the electrical properties of sleep-control cells in opposite directions: hyperfused mitochondria increase, whereas fragmented mitochondria decrease, neuronal excitability and sleep. ATP levels in dFBNs rise after enforced waking because of diminished ATP consumption during the arousal-mediated inhibition of these neurons, which predisposes them to heightened oxidative stress. Consistent with this view, uncoupling electron flux from ATP synthesis relieves the pressure to sleep, while exacerbating mismatches between electron supply and ATP demand (by powering ATP synthesis with a light-driven proton pump) promotes sleep. Sleep, like ageing, may be an inescapable consequence of aerobic metabolism. | | 6:19p |
Pathologic α-Synuclein-NOD2 Interaction and RIPK2 Activation Drives Microglia-Induced Neuroinflammation in Parkinson's Disease
Pathological aggregation of -Synuclein (-Syn) and neuroinflammation are closely linked to Parkinsons disease (PD). However, the specific regulators of the neuroinflammation caused by pathological -syn remain obscure. In this study, we show that NOD2/RIPK2 signaling is a crucial regulator of neuroinflammation in PD. Pathological -syn binds to NOD2, causing self-oligomerization and complex formation with RIPK2, leading to RIPK2 ubiquitination and activation of MAPK and NF-kB. Notably, this NOD2/RIPK2 signaling is particularly active in microglia of human PD brains and the -Syn preformed fibril (-Syn PFF) mouse model. Depleting NOD2 or RIPK2 reduces neuroinflammation and protects against dopamine neuron degeneration in a pathologic -Syn mouse model by blocking the formation of neurotoxic reactive astrocytes caused by microglia activation. The discovery of NOD2/RIPK2 signaling as a key regulator of neuroinflammation in PD provides a new understanding of -Syn-driven neuroinflammation and neurodegeneration in PD and a potential new therapeutic strategy.
Graphical Abstract
O_FIG O_LINKSMALLFIG WIDTH=198 HEIGHT=200 SRC="FIGDIR/small/580982v1_ufig1.gif" ALT="Figure 1">
View larger version (72K):
org.highwire.dtl.DTLVardef@3bc55org.highwire.dtl.DTLVardef@1417ed1org.highwire.dtl.DTLVardef@ece8b4org.highwire.dtl.DTLVardef@1a1c078_HPS_FORMAT_FIGEXP M_FIG C_FIG In briefPathological -Synuclein (-Syn) binds to the microglial NOD2 protein, which in turn triggers NOD2/RIPK2 complex and RIPK2 phosphorylation/ubiquitination. This process activates the NF-kB/MAPK pathways, ultimately leading to neurotoxic reactive astrocyte-induced dopaminergic neurodegeneration. Depletion of RIPK2 (RIPK2 KO) or NOD2 (NOD2) protects dopamine neurons in a mouse model of Parkinsons disease (PD). These findings provide insights into -Syn-driven neuroinflammation and offer potential therapeutic strategies for PD.
HighlightsNOD2/RIPK2 signaling is identified as a crucial regulator of neuroinflammation in PD.
NOD2/RIPK2 signaling is highly active in microglia in human PD brains and -Syn PFF mouse models.
Pathological -Syn binds to NOD2, triggering self-oligomerization and RIPK2 complex formation, leading to MAPK and NF-kB activation
Genetic depletion of NOD2 or RIPK2 reduces neuroinflammation and protects dopamine neurons by blocking the formation of neurotoxic reactive astrocytes. |
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