bioRxiv Subject Collection: Neuroscience's Journal
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Monday, December 30th, 2024
| Time |
Event |
| 7:47a |
Primary sensory neuron dysfunction underlying mechanical itch hypersensitivity in a Shank3 mouse model of autism
Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder marked by social deficits, repetitive behaviors, and atypical sensory perception. The link between ASD and skin abnormalities, inducing itchiness, has never been investigated in depth. This study explores mechanical itch sensitivity in the Shank3{Delta}C/{Delta}C mouse model. Key observations include heightened scratching in response to skin deformation and hypersensitivity to mechanical itch (i.e. alloknesis) in Shank3{Delta}C/{Delta}C mice. In Shank3{Delta}C/{Delta}C mice, ex vivo electrophysiological experiments revealed that C-fiber low-threshold mechanoreceptors (C-LTMRs) were hyporesponsive, and transcriptomic analysis showed a downregulation of TAFA4, a protein secreted by C-LMTRs. Interestingly, pharmacologically inhibiting A{beta}-LTMR, important in mechanical itch initiation, abolished the itch hypersensitivity. Also, TAFA4 injections reduced the spontaneous scratching response to skin deformation but failed to restore itch sensitivity. Our data suggest that somatosensory deficits in Shank3{Delta}C/{Delta}C mice lead to hypersensitivity to itchiness and indicate that two pathways might regulate mechanical itchiness, dependent on TAFA4. | | 7:47a |
Loss of SynDIG4/PRRT1 alters distribution of AMPA receptors in Rab4- and Rab11-positive endosomes and impairs basal AMPA receptor recycling.
The transmembrane protein Synapse Differentiation Induced Gene 4 (SynDIG4) functions as an auxiliary factor of AMPA receptors (AMPARs) and plays a critical role in excitatory synapse plasticity as well as hippocampal-dependent learning and memory. Mice lacking SynDIG4 have reduced surface expression of GluA1 and GluA2 and are impaired in single tetanus-induced long-term potentiation and NMDA receptor (NMDAR)-dependent long-term depression. These findings suggest that SynDIG4 may play an important role in regulating AMPAR distribution through intracellular trafficking mechanisms; however, the precise roles by which SynDIG4 governs AMPAR distribution remain unclear. In this study, we characterized the endocytosis and recycling of GluA1-containing AMPARs under basal conditions. We did not observe any change in baseline endocytosis; however, we did observe a significant decrease in recycling of GluA1-containing AMPARs in cultured hippocampal neurons from mice lacking SynDIG4. This resulted in a significant increase in the levels of internal GluA1 and GluA2, along with greater colocalization of these subunits with Rab4-positive recycling endosomes in hippocampal neurons lacking SynDIG4. Notably, the overlap between Rab4- and Rab11-positive vesicles was elevated in hippocampal neurons lacking SynDIG4, suggesting an impairment in the trafficking between Rab4 and Rab11 compartments. Furthermore, our findings revealed a reduction in surface GluA1 within synaptic regions of hippocampal neurons lacking SynDIG4. Collectively, these results indicate that SynDIG4 regulates the distribution of GluA1-containing AMPARs via the Rab4-dependent endosomal recycling pathway, thereby maintaining AMPAR levels at synaptic regions under baseline conditions. This regulatory function of SynDIG4 may contribute to the deficits in GluA1-dependent synaptic plasticity and impairment of hippocampal-dependent learning and memory behaviors observed in SynDIG4 deficient mice. | | 2:15p |
A 3D-printed cradle for mouse preclinical MRI with an integrated water heating system
Functional Magnetic Resonance Imaging (fMRI) of small animals is mainly performed under sedation or anesthesia to avoid movement, which is detrimental to image quality. Heating systems to warm the animals usually rely on airflow or heating blankets or pads with circulating water to comply with MR compatibility requirements. However, these solutions are often suboptimal for small animals like mice scanned at ultra-high magnetic fields with long-bore MR scanners. We designed and built an MR cradle with an integrated water chamber, maximizing the contact surface with the mouse's body. This large contact surface helps maintain body temperature without overheating the animal, thus reducing the risk of burns and hyperthermia. Our cradle keeps the mouse's body temperature stable within the physiological range during an MRI session and fits the bore of a Bruker 17.2T scanner. We share the 3D drawings and all the information needed to replicate the cradle. Our design can be adapted to work on preclinical scanners with similar bore sizes and customized to add stimulation devices. | | 2:50p |
Impaired axon regeneration and heightened synaptic dynamics in the injured aged mammalian cortex
How aging affects axon regeneration and synaptic repair in the brain is poorly understood. To study age-related changes in neural circuits, we developed a model of axonal injury in the aged (> 2 years) mouse somatosensory cortex. By directly tracking fluorescently labelled injured axons by multiphoton imaging, we find that while axon degeneration in the aged brain is comparable to the young adult brain, axon regeneration is impaired. We further examine changes in the most common type of cortical synapses, En Passant Boutons (EPBs), and observe a transient and significant increase in the number and size of boutons 6 hours post-lesion. Using a computational model of a recurrent neural network, we examined the functional consequences of these synaptic increases on memory, comparing results to models of the young adult brain. The results suggest that increased synaptic dynamics might enable partial recovery from injury via synaptic re-wiring in the aged brain. | | 3:21p |
NeuroTorch: A Python library for neuroscience-oriented machine learning
Machine learning (ML) has become a powerful tool for data analysis, leading to significant advances in neuroscience research. While ML algorithms are proficient in general-purpose tasks, their highly technical nature often hinders their compatibility with the observed biological principles and constraints in the brain, thereby limiting their suitability for neuroscience applications. In this work, we introduce NeuroTorch, a comprehensive ML pipeline specifically designed to assist neuroscientists in leveraging ML techniques using biologically inspired neural network models. NeuroTorch enables the training of recurrent neural networks equipped with either spiking or firing-rate dynamics, incorporating additional biological constraints such as Dale's law and synaptic excitatory-inhibitory balance. The pipeline offers various learning methods, including backpropagation through time and eligibility trace forward propagation, aiming to allow neuroscientists to effectively employ ML approaches. To evaluate the performance of NeuroTorch, we conducted experiments on well-established public datasets for classification tasks, namely MNIST, Fashion-MNIST, and Heidelberg. Notably, NeuroTorch achieved accuracies that replicated the results obtained using the Norse and SpyTorch packages. Additionally, we tested NeuroTorch on real neuronal activity data obtained through volumetric calcium imaging in larval zebrafish. On training sets representing 9.3 minutes of activity under darkflash stimuli from 522 neurons, the mean proportion of variance explained for the spiking and firing-rate neural network models, subject to Dale's law, exceeded 0.97 and 0.96, respectively. Our analysis of networks trained on these datasets indicates that both Dale's law and spiking dynamics have a beneficial impact on the resilience of network models when subjected to connection ablations. NeuroTorch provides an accessible and well-performing tool for neuroscientists, granting them access to state-of-the-art ML models used in the field without requiring in-depth expertise in computer science. | | 9:03p |
Can we infer excitation-inhibition balance from the spectrum of population activity?
Networks in the brain most of times operate in an excitation-inhibition (EI) balanced state. Altered EI balance is often associated with a change in brain state and impaired information processing. Given its importance, it is crucial to establish non-invasive measures of the EI balances. In this regard, previous studies have suggested that the relative EI balance can be inferred from the spectrum of the population signals such as Local Field Potentials (LFPs), Electroencephalogram (EEG) and Magnetoencephalography (MEG). This idea exploits the fact that in most cases excitatory and inhibitory synapses have quite different time constants. However, it is not clear to what extent spectral slope of population activity is related to the network parameters that define the EI balance e.g. the excitatory and inhibitory conductance). To address this question we simulated two different types of recurrent networks and measured spectral slope for a wide range of network parameters. Our results show that slope of spectrum cannot predict the ratio of excitatory and inhibitory synaptic conductance. Only in a small set of simulations a change in the spectral slope was consistent with the corresponding change in the synaptic weights or inputs to the network. Thus, our results show that we should be careful in interpreting the change in the slope of the population activity spectrum. | | 10:16p |
Diversity of set-related neuronal activity in the dorsal premotor cortex of monkeys during a path-planning task
Actions involve multiple levels. The dorsal premotor area (PMd) of the primate cerebral cortex is involved in the preparation of actions based on perceptual information. In this study, we recorded neuronal activity from the PMd of monkeys while they performed a path-finding task. In the task, the animals were required to move a cursor step by step to a goal in a maze-like display, and the arm movement and the direction of the cursor operation were dissociated. We observed neurons involved in the preparation of a single arm movement and neurons involved in the preparation of a single cursor operation. Cursor operation-related neurons were also obtained from the lateral prefrontal cortex (lPFC), but the PMd neurons showed more preparatory properties during the execution period than the lPFC neurons. Furthermore, we found neurons involved in the preparation of a specific sequence of cursor movements. The PMd included not only all types of single-shot preparatory neurons but also preparatory neurons for a variety of complex sequences for arm movements and cursor manipulation. These results suggest that the PMd contains diverse neurons involved in different levels of action preparation. Such diversity is one of the critical neural bases for robust goal-directed behavior in complex environments. | | 10:16p |
Electrophysiological correlates of cognitive reserve in healthy older adults at different cognitive states
High cognitive reserve (CR) is associated with a set of lifestyle factors such as high education level and occupational attainment. Studies suggest that CR is linked to enhanced executive control functions. Nevertheless, it is unclear what are the functional neural activity patterns linked to high CR and to what extent they are steady across different cognitive states. The aim of the present study was to investigate electrophysiological differences between low CR (LCR) and high CR (HCR) at rest and during the performance of two cognitive control tasks with different difficulty level. Thus, 67 older adults performed an experimental session consisting of two spatial stimulus-response compatibility (SRC) tasks (i.e., the Simon task, and the more demanding spatial Stroop task), and a resting state during an electroencephalogram (EEG) recording. Cognitive control was better in HCR than LCR group, as revealed by higher accuracy in HCR compared to LCR group in incongruent conditions of the tasks. Moreover, event-related brain potentials (ERP) showed earlier latencies (P300) in HCR than LCR and time/frequency analysis showed higher alpha activity in HCR than LCR during the performance of the tasks, while no differences were observed at rest within any of the analyzed frequency bands. Higher P300 frontalization was observed in LCR than HCR in the more difficult task but it was not related to frontalization within a specific frequency band. Overall, results showed that electrophysiological differences between high and low CR depend on the cognitive state, with greater CR-related differences emerging at increased task demands. | | 10:49p |
Investigating the role of sensorimotor spatial dependencies in shaping conscious access to virtual 3D objects
According to sensorimotor accounts of perceptual experience, the subjective veridicality of an object (the sense of its 'presence') builds up gradually as one learns how changes in sensory inputs depend on bodily movements. To investigate how sensorimotor interactions shape visual experience, we designed a virtual-reality-based study that allowed us to manipulate the complexity of spatial dependencies governing interactions with unfamiliar 3D objects. Participants had to learn to manually control fully visible objects that could move in congruent, opposite, novel (orthogonal), or random directions in response to their movements. The sensorimotor control tasks occurred alternately with a continuous flash suppression (CFS) task evaluating the access of stationary objects to visual awareness, operationalised as the time taken for a 3D object to break the interocular suppression. We hypothesised that objects whose motion was experienced as depending on actions in a lawful, and thus encodable, manner (i.e., according to a congruent, opposite, or novel - but not random - dependency) would overcome suppression faster than objects moving randomly in response to actions (for which there is no world-related statistical structure to learn). However, while performance in the sensorimotor tasks consistently decreased along with the difficulty of the conditions (i.e., congruent > opposite > novel > random), the pre-registered analysis yielded no significant differences in breakthrough times of objects manipulated under different coupling rules. An exploratory analysis assessing whether the acquisition of 'sensorimotor mastery' was associated with reduced breakthrough times also revealed no significant effects. Thus, our results suggest that one's knowledge of how an object responds to action does not play a salient role in determining conscious access to visual stimuli. This extends previous evidence for a general ineffectiveness of sensorimotor spatial manipulations in interocular suppression paradigms. Notably, in all conditions, object movement remained tightly coupled (i.e., contingent) to the participant's actions = and given such stimuli have already been shown to break suppression faster than uncoupled/pre-recorded visual inputs - it is possible that sensorimotor contingency was a sufficiently salient factor to override any influences related to how identifiable specific spatial dependencies were. | | 10:49p |
Integration of head and body orientations in the macaque superior temporal sulcus is specific to upright bodies
The neural processing of faces and bodies is often studied separately, despite their natural integration in perception. Unlike prior research on the neural selectivity for either head or body orientation, we investigated their interaction in macaque superior temporal sulcus (STS) using a monkey avatar with diverse head-body orientation angles. STS neurons showed selectivity for specific combinations of head-body orientations. Anterior STS (aSTS) neurons enabled more reliable decoding of head-body configuration angles compared to middle STS neurons. Decoding accuracy in aSTS was lowest for head-body angle pairs differing only in sign (e.g. head-body orientation difference of +/- 90 degrees relative to the anatomical midline), and highest for aligned (0 degrees) head-body orientations versus those with maximum angular difference. Inverted bodies showed diminished decoding of head-body orientation angle compared to upright bodies. These findings show that aSTS integrates head and body orientation cues, revealing configuration-specific neural mechanisms, and advance our understanding of social perception. | | 10:49p |
A quantitative spatial atlas of transcriptomic, morphological, and electrophysiological cell type densities in the mouse brain
Brain cells can be classified into transcriptomic, morphological, and electrophysiological types. We derived a quantitative spatial atlas of the distributions of these classes within the mouse brain. To do so, we first generated a 3D atlas of transcriptomic cell type densities, by scaling regional estimates of densities from brain slices using cell counts and slice dimensions. Adjustments for regions with high cell density, such as the cerebellum, were made using the average Nissl intensities as a density modifier on a voxel-by-voxel basis. To connect the transcriptomic-type signatures to cellular function (morphological-electrophysiological types), we leveraged patch-sequencing datasets, which integrate mRNA counts, morphology reconstructions, and electrophysiological recordings from single cortical neurons. We aligned mRNA counts with the established classifications of transcriptomic types, classified neuron morphologies according to morphological types, and derived electrophysiological types using K-means clustering. The resulting 3D atlas and computational framework can be used to probe neuronal cell-type diversity and its functional implications, setting the stage for further explorations into the cellular basis of brain function. |
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