bioRxiv Subject Collection: Neuroscience's Journal
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Saturday, July 13th, 2024
| Time |
Event |
| 10:16a |
Inferring illness causes recruits the animacy semantic network
Inferring the causes of illness is universal across human cultures and is essential for survival. Here we use this phenomenon as a test case for understanding the neural basis of implicit causal inference. Participants (n=20) undergoing fMRI read two-sentence vignettes that encouraged them to make causal inferences about illness or mechanical failure (causal control) as well as non-causal vignettes. All vignettes were about people and were matched on linguistic variables. The same participants performed localizers: language, logical reasoning, and mentalizing. Inferring illness causes selectively engaged a portion of precuneus (PC) previously implicated in the semantic representation of animates (e.g., people, animals). This region was near but not the same as PC responses to mental states, suggesting a neural mind/body distinction. No cortical areas responded to causal inferences across domains (i.e., illness, mechanical), including in individually localized language and logical reasoning networks. Together, these findings suggest that implicit causal inferences are supported by content-specific semantic networks that encode causal knowledge. | | 10:16a |
A conserved code for anatomy: Neurons throughout the brain embed robust signatures of their anatomical location into spike trains.
Neurons in the brain are known to encode diverse information through their spiking activity, primarily reflecting external stimuli and internal states. However, whether individual neurons also embed information about their own anatomical location within their spike patterns remains largely unexplored. Here, we show that machine learning models can predict a neuron's anatomical location across multiple brain regions and structures based solely on its spiking activity. Analyzing high-density recordings from thousands of neurons in awake, behaving mice, we demonstrate that anatomical location can be reliably decoded from neuronal activity across various stimulus conditions, including drifting gratings, naturalistic movies, and spontaneous activity. Crucially, anatomical signatures generalize across animals and even across different research laboratories, suggesting a fundamental principle of neural organization. Examination of trained classifiers reveals that anatomical information is enriched in specific interspike intervals as well as responses to stimuli. Within the visual isocortex, anatomical embedding is robust at the level of layers and primary versus secondary but does not robustly separate individual secondary structures. In contrast, structures within the hippocampus and thalamus are robustly separable based on their spike patterns. Our findings reveal a generalizable dimension of the neural code, where anatomical information is multiplexed with the encoding of external stimuli and internal states. This discovery provides new insights into the relationship between brain structure and function, with broad implications for neurodevelopment, multimodal integration, and the interpretation of large-scale neuronal recordings. Immediately, it has potential as a strategy for in-vivo electrode localization. | | 10:16a |
Exploring Anatomical Links Between the Crow's Nidopallium Caudolaterale and its Song System
Crows are corvid songbirds that exhibit remarkable cognitive control over their actions, including their vocalizations. They can learn to vocalize on command and the activity of single neurons from the crow's associative telencephalic structure nidopallium caudolaterale (NCL) is correlated with the execution of this vocal and many non-vocal skilled behaviors. However, it remains unknown if specific anatomical adaptations that directly link the crow NCL to any of the nuclei of the crow's 'song system' exist. To address this issue, we used fluorescent tracers along with histological staining methods (Nissl-, myelin-, and anti tyrosine hydroxylase) to characterize the connectivity of the crow's NCL in relation to its song system nuclei. We found that the NCL sends dense projections into the dorsal intermediate arcopallium (AID) directly adjacent to and engulfing the robust nucleus of the arcopallium (RA), which is the telencephalic motor output of the song system. Similarly, we demonstrate dense NCL projections into the striatum surrounding the basal ganglia song nucleus 'area X'. Both of these descending projections mirror the projections of the nidopallial song nucleus HVC (proper name) into RA and area X, with extremely sparse NCL fibers extending into area X. Furthermore, we characterized the distribution of cells projecting from the lateral part of the magnocellular nucleus of the anterior nidopallium (MAN) to NCL. Notably, a separate medial population of MAN cells projects to HVC. These two sets of connections - MAN to NCL and MAN to HVC - run in parallel but do not overlap. Taken together, our findings support the hypothesis that the NCL is part of a 'general motor system' that parallels the song system but exhibits only minimal monosynaptic interconnections with it. | | 11:37a |
Synergistic reinforcement learning by cooperation of the cerebellum and basal ganglia
The cerebral cortex, cerebellum, and basal ganglia play a central role in flexible learning in mammals. However, how these three structures work together is not fully understood. Recently, it has been suggested that reinforcement learning may be implemented not only in the basal ganglia but also in the cerebellum, as the activity of cerebellar climbing fibers represents reward prediction error. If the same learning mechanism via reward prediction error occurs simultaneously in the basal ganglia and cerebellum, it remains unclear how these two regions co-function. Here, we recorded neuronal activity in the output of cerebellum and basal ganglia, the cerebellar nuclei and substantia nigra pars reticulata, respectively, from ChR2 transgenic rats with high-density Neuropixels probes while optogenetically stimulating the cerebral cortex point-by-point. The temporal response patterns could be categorized into two classes in both cerebellar nuclei and substantia nigra pars reticulata. Among them, the fast excitatory response of the cerebellar nuclei due to the input of mossy fibers and the inhibitory response of the substantia nigra pars reticulata via the direct pathway were synchronized. This coincidence, reproduced in a spiking network simulation based on connectome data, was expected to synchronously activate the cerebral cortex via the thalamus. To further investigate the significance of this synchronous positive feedback, we constructed a reservoir model that mimics the time course of the activity dynamics of cerebral cortex and temporal responses of cerebellar nuclei and substantia nigra pars reticulata. Plasticity of both parallel fiber inputs to Purkinje cell and corticostriatal synapses onto the striatal neurons of the direct pathway was essential for successful learning of a reinforcement learning task. Notably, learning was inhibited when the timing of the cerebellar or basal ganglia output was delayed from the real data by 10 ms; the larger this delay, the slower the learning rate. This necessary temporal precision was observed only when the cerebral cortex operated in the {beta}-to-{gamma} frequency range. These results indicate that coordinated output of the cerebellum and basal ganglia, with input from the cerebral cortex in a narrow frequency band, facilitates brain-wide synergistic reinforcement learning. Thus, our findings contribute to a holistic understanding of the interactions among the cerebellum, basal ganglia, and cerebral cortex. | | 12:51p |
Transient cortical Beta-frequency oscillations associated with contextual novelty in high density mouse EEG
Beta-frequency oscillations (20-30 Hz) are prominent in both human and rodent electroencephalogram (EEG) recordings. Discrete epochs of beta (or Beta2) oscillations are prevalent in the hippocampus and other brain areas during exploration of novel environments. However, little is known about the spatial distribution and temporal relationships of beta oscillations across the cortex in response to novelty. To investigate this, mice fitted with 30-channel EEG-style multi-electrode arrays underwent a single recording session in a novel environment. While changes to spectral properties of cortical oscillations were minimal, there was a profound increase in the rate of beta bursts during the initial part of the recording session, when the environment was most novel. This was true across the cortex but most notable in recording channels situated above the retrosplenial cortex. Additionally, novelty was associated with greater connectivity between retrosplenial areas and the rest of the cortex, specifically in the beta frequency range. However, it was also found that the cortex in general, is highly modulated by environmental novelty. This data further suggests the retrosplenial cortex is an important hub for distinguishing environmental context and highlights the diversity of functions for beta oscillations across the brain, which can be observed using high-density EEG. | | 12:51p |
The neurovascular coupling response of the aged brain is brain-state dependent.
Brain aging lead to reduced cerebral blood flow and cognitive decline, but how normal aging affects neurovascular coupling (NVC) in the awake brain is unclear. Here, we investigated NVC in relation to calcium changes in vascular mural cells (VMCs) in awake adult and aged mice. We show that NVC responses are reduced and prolonged in the aged brain and that this is more pronounced at the capillary level than in arterioles. However, the overall NVC response, measured as the time integral of vasodilation, is the same in two age groups. In adult, but not in aged mice, the NVC response correlated with Ca2+ signaling in VMCs, while the overall Ca2+ kinetics were slower in aged than in adult mice. In particular, the rate of Ca2+ transport, and the Ca2+ sensitivity of VMCs were reduced in aged mice, explaining the reduced and prolonged vasodilation. Spontaneous locomotion was less frequent and reduced in aged mice as compared to young adult mice, and this was reflected in the 'slow but prolonged' NVC and vascular Ca2+ responses. Taken together, our data characterize the NVC in the aged awake brain as slow but prolonged, and underscoring the importance of brain state in understanding age-related mechanisms. | | 7:17p |
Microglia-specific transduction via AAV11 armed with IBA1 promoter and miRNA-9 targeting sequences
Microglia, as resident immune cells in the central nervous system (CNS), are closely related to human health and the pathogenesis of various CNS diseases, making them compelling targets for therapeutic interventions. However, functional and therapeutic studies of microglia remain significant challenges largely due to the lack of tools capable of efficiently and specifically transducing microglia. Herein, we evaluated the specificity and efficiency of various adeno-associated virus (AAV) vectors armed with the mIBA1 promoter and miRNA-9 targeting sequences in transducing microglia within the caudate putamen (CPu) brain region, and found that AAV11 mediates more specific and efficient transduction of microglia. Subsequently, we further demonstrated that AAV11 also exhibits high transduction specificity for microglia across various brain areas and within the spinal cord. Finally, by reducing the injection dosage, we employed AAV11 for sparse labeling of microglia. This work provides a promising tool for advancing both the functional investigation and therapeutic targeting of microglia. | | 10:45p |
Loss of the lysosomal lipid flippase ATP10B leads to progressive dopaminergic neurodegeneration and Parkinsonian motor deficits
Background ATP10B, a transmembrane lipid flippase located in late endosomes and lysosomes, facilitates the export of glucosylceramide and phosphatidylcholine by coupling this process to ATP hydrolysis. Recently, loss-of-function mutations in the ATP10B gene have been identified in Parkinsons disease patients, pointing to ATP10B as a candidate genetic risk factor. Previous studies have shown compromised lysosomal functionality upon ATP10B knockdown in human cell lines and primary cortical neurons. However, its role in vivo and specifically in the nigrostriatal dopaminergic system remains poorly understood. Methods To investigate the role ATP10B in PD neuropathology, we induced ATP10B knockdown specifically in substantia nigra pars compacta neurons of rats using viral vector technology. Two different microRNA-based shRNA constructs targeting distinct regions of the ATP10B mRNA were used to cross-validate the findings. Behavioral evaluation, dopamine transporter 18F-FE-PE2I positron emission tomography imaging and neuropathological examination of the nigrostriatal pathway at one year post-injection were conducted. Additionally, midbrain neuronal cultures derived from ATP10B knock-out human induced pluripotent stem cells clones were used to study the impact of ATP10B loss in dopaminergic neurons in a more translational model. Results ATP10B knockdown in rat brain induced Parkinsonian motor deficits, and longitudinal striatal dopamine transporter 18F-FE-PE2I PET imaging revealed a progressive decrease in binding potential. Immunohistochemical analysis conducted one year post-injection confirmed the loss of dopaminergic terminals in the striatum, alongside a loss of dopaminergic neurons in the substantia nigra pars compacta. The expression of LAMP1, LAMP2a, cathepsin B and glucocerebrosidase was studied by immunofluorescence in the surviving dopaminergic neurons. A decrease in lysosomal numbers and an increase in lysosomal volume were observed more consistently in one of the knockdown constructs. The vulnerability of dopaminergic neurons to ATP10B loss-of-function was also observed in midbrain neuronal cultures derived from ATP10B knock-out human induced pluripotent stem cells clones, which showed a significant reduction in TH-positive neurons. Conclusion Taken together, our findings demonstrate that ATP10B depletion detrimentally impacts the viability of dopaminergic neurons both in vivo and in vitro. Moreover, a broader impact on the functionality of the nigrostriatal pathway was evidenced as rats with ATP10B knockdown exhibited motor impairments similar to those observed in PD patients. | | 10:45p |
Taming a behavioral monster: Resonant song recognition and the evolution of acoustic communication in crickets
Rare behavioral phenotypes--behavioral monsters--can challenge hypotheses about the evolution of the neural networks that drive behavior. In crickets, the diversity of song recognition behaviors is thought to be based on the modification of a shared neural network. We here report on a cricket with a novel resonant song recognition pattern that challenges this hypothesis. Females of the species Anurogryllus muticus respond to pulse patterns with the period of the male song, but also to song at twice the period. To identify the mechanisms underlying this multi-peaked recognition, we first explored minimal models of resonant behaviors. Though all of the three simple models tested (autocorrelation, rebound, resonate and fire) produced some kind of resonant behavior, only a single-neuron model with an oscillating membrane qualitatively matched the Anurogryllus behavior with regard to both period and duty cycle tuning. Surprisingly, the rebound model, a minimal model of the core mechanism for song recognition in crickets, fails to reproduce the preference for higher duty cycles observed in the behavior, questioning the universality of the core algorithm. However, the behavior is reproduced with a network model that contains all computations from the song recognition network of crickets, revealing the importance of an additional computation not part of the core mechanism: Following the core rebound mechanism in which post-inhibitory rebounds give rise to the resonant period tuning, feed-forward inhibition further shapes the tuning, resulting in the observed behavioral profile. Overall, this shows how unusual behavioral phenotypes can evolve by combining different nonlinear computations at the level of single cells and networks. | | 10:45p |
Identification of whole-body reaching movement phenotypes in young and older active adults: an unsupervised machine learning approach
Studies reported age-related motor control modifications in whole-body movement in several aspects of spatiotemporal movement organization by comparing young and older adults. However, studies on motor control involve high complexity and high-dimensional data of different natures, in which machine learning has proved to be effective. Furthermore, conventional studies focus on comparisons of movement parameters based on a priori grouping, whereas unsupervised machine learning allows the identification of inherent groupings within the dataset. The current investigation was carried out by using the unsupervised machine learning on motor control features across age-groups. An important question was whether we could identify different movement patterns based on motor control features and whether they were age-dependent or independent. We investigated motor control parameters variations in a whole-body reaching movement across young and active older adults including woman and man (n=19). We applied the K-means clustering algorithm to segment the kinematic data (21 features) of all individuals. We propose a methodology applying the latest recommendations for clustering methods in the field of whole-body movement motor control. Analysis revealed two distinct motor control patterns which were age independent. The first pattern exhibited higher shoulder, ankle and knee angular excursions, along with a higher vertical velocity of center of mass (CoM), compared to the second pattern, which had higher hip and back angular excursions, along with a lower vertical velocity CoM. The clustering methodology demonstrated its effectiveness to identify distinct motor patterns based solely on motor control features independently of age-grouping.
Significance StatementO_LIK-means clustering algorithm enabled us to identify two distinct age-independent motor patterns: a first pattern with high shoulder, ankle and knee angular excursions, and vertical velocity of CoM; a second pattern with high hip and back angular excursions and low vertical velocity of CoM.
C_LIO_LIDemonstrates how unsupervised machine learning can identify motor patterns and proposes a methodology to apply it in the field of whole-body movement motor control.
C_LIO_LIProves the complementary contribution of unsupervised machine learning to conventional approach for motor control studies, which enables to process the high complexity and dimensionality of movements.
C_LIO_LIAdvances understanding of motor behaviours through unsupervised machine learning analysis of whole-body reaching movements.
C_LI | | 10:45p |
Exploring For Gloss: The Role of Active Exploration in Visual Material Perception
Image motion has been found to contribute to the perception of visual material properties, and motion signals are generated while actively exploring objects. Yet, little is known about the specific visual cues produced through exploration and how exploration, in turn, impacts visual material perception. Using virtual reality and real-time hand tracking, we investigated the influence of material on exploratory hand motion and vice versa. Participants either observed or actively explored objects varying in gloss or in lightness while performing a matching task. We compared the perceptual judgments of actively exploring and observing participants and analysed their manual exploration patterns during the two material judgment tasks in the interactive condition. Results showed systematic variation in exploration patterns based on visual task and material property: participants spent more time exploring objects when judging gloss than when judging lightness, and glossier objects were explored longer. This increased exploration during gloss judgments could suggest a strategic prioritisation of relevant cues for gloss judgments, with observers actively generating highlight movements through larger movements and object rotation to facilitate their gloss judgements. Our study demonstrates that visual material properties impact how individuals interact with objects, and that active exploration influences the perception of visual material properties. | | 11:17p |
A systematic evaluation of dynamic functional connectivity methods using simulation data
Numerous dynamic functional connectivity (dFC) methods have been proposed to study time-resolved network reorganization in rest and task fMRI. However, a comprehensive comparison of their performance is lacking. In this study, we compared the efficacy of seven dFC methods (and their enhanced versions) to track transient network reconfiguration using simulation data. The seven methods include flexible least squares (FLS), dynamic conditional correlation (DCC), general linear Kalman filter (GLKF), multiplication of temporal derivatives (MTD), sliding-window functional connectivity with L1-regularization (SWFC), hidden Markov models (HMM), and hidden semi-Markov models (HSMM). Multiple datasets of non-fMRI-BOLD and fMRI-BOLD signals with predefined covariance structures, signal-to-noise ratio levels, and sojourn time distributions were simulated. We adopted inter-subject analysis to eliminate the effects of signals of non-interest, resulting in enhanced methods: ISSWFC, ISMTD, ISDCC, ISFLS, ISKF, ISHMM, and ISHSMM. Efficacy was defined as the spatiotemporal association between simulated and estimated data. We found that all enhanced dFC methods outperformed their original versions. Efficacies depend on several factors, such as considering the neurovascular effect in simulated data, the covariance structure between two time series, state sojourn distribution, and signal-to-noise ratio levels. These results highlight the importance of selecting appropriate dFC methods in fMRI study. |
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