bioRxiv Subject Collection: Neuroscience's Journal
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Sunday, December 10th, 2023
| Time |
Event |
| 12:45a |
Exploring white matter dynamics and morphology through interactive numerical phantoms: The White Matter Generator
Brain white matter is a dynamic environment that continuously adapts and reorganizes in response to stimuli and pathological changes. Glial cells, especially, play a key role in tissue repair, inflammation modulation, and neural recovery. The movements of glial cells and changes in their concentrations can influence the surrounding axon morphology. We introduce the White Matter Generator (WMG) tool to enable the study of how axon morphology is influenced through such dynamical processes, and how this, in turn, influences the diffusion-weighted MRI signal. This is made possible by allowing interactive changes to the configuration of the phantom generation throughout the optimisation process. The phantoms can consist of axons, myelinated axons, and cell clusters, separated by extra-cellular space. Due to morphological flexibility and computational advantages during the optimisation, the tool uses ellipsoids as building blocks for all structures; chains of ellipsoids for axons, and individual ellipsoids for cell clusters. After optimisation, the ellipsoid representation can be converted to a mesh representation which can be employed in Monte-Carlo diffusion simulations. This offers an effective method for evaluating tissue microstructure models for diffusion-weighted MRI in controlled realistic white matter environments. Hence, the WMG offers valuable insights into white matter's adaptive nature and implications for diffusion-weighted MRI microstructure models, and thereby holds the potential to advance clinical diagnosis, treatment, and rehabilitation strategies for various neurological disorders and injuries. | | 1:16a |
Stimulus-reward contingencies drive long-lasting alterations in neocortical somatostatin inhibition during learning
Learning involves the association of discrete events in the world to infer causality, likely through a cascade of changes at input- and target-specific synapses. Transient or sustained disinhibition may initiate cortical circuit plasticity important for association learning, but the cellular networks involved have not been well-defined. Here we show that sensory association learning drives a durable, target-specific reduction in inhibition from somatostatin (SST)-expressing GABAergic neurons onto pyramidal (Pyr) neurons in superficial but not deep layers of mouse somatosensory cortex. Critically, SST-output was not altered when stimulus and rewards were unpaired, indicating that these neurons are not modified by sensory input alone. Depression of SST output onto Pyr neurons could be phenocopied by chemogenetic suppression of SST activity outside of the training context. Thus, neocortical SST neuron output is persistently modified by convergent sensory and reinforcement signals to selectively disinhibit superficial layers of sensory neocortex during learning. | | 3:21a |
Cortical tracking of postural sways during standing balance.
Maintaining an upright stance requires the integration of sensory inputs from the visual, vestibular and somatosensory-proprioceptive systems by the cortex to develop a corrective postural strategy. However, it is unclear whether and how the cerebral cortex monitors and controls postural sways. Here, we asked whether postural sways are encoded in ongoing cortical oscillations, giving rise to a form of corticokinematic coherence (CKC) in the context of standing balance. Center-of-pressure (CoP) and center of mass (CoM) fluctuations and electroencephalographic cortical activity were recorded as young healthy participants performed balance tasks during which sensory information was manipulated, by either removal or alteration. We found that postural sways are represented in ongoing SM1 cortical activity during challenging balance conditions, in the form of CKC at 1-6 Hz that was stronger for CoP compared with CoM fluctuations. Time delays between cortical activity and CoP features indicated that both afferent and efferent pathways contribute to CKC, wherein the brain would monitor the CoP velocity and control its position. Importantly, CKC was behaviorally relevant, as it predicted the increase in instability brought by alteration of sensory information. Our results demonstrate that human sensorimotor cortical areas take part in the closed-loop control of standing balance in challenging conditions. They demonstrate that CKC could serve as a neurophysiological marker of cortical involvement in maintaining balance. | | 3:21a |
Matrix Metalloproteinase-9 controls structural synaptic plasticity via BDNF-dependent signaling
Structural long-term potentiation (sLTP), an activity-dependent growth of dendritic spines that harbor excitatory synapses, is a major form of synaptic plasticity in learning and memory processes. The spine enlargement is influenced by the extracellular matrix and its proteolytic enzymes, among which matrix metalloproteinase 9 (MMP-9) is a prominent example. Here, we utilized two-photon microscopy and two-photon glutamate uncaging to demonstrate that MMP-9 activity is essential for sLTP and is rapidly (~seconds) released from dendritic spines in response to synaptic stimulation. MMP-9 has been postulated to play a pivotal role in the maturation of brain-derived neurotrophic factor (BDNF), a major protein involved in LTP that acts on TrkB receptor. We show that chemically or genetically inhibiting MMP-9 impairs TrkB activation, as measured by fluorescence lifetime imaging microscopy of FRET sensor. Furthermore, we provide evidence for in vitro cleavage of proBDNF into mature BDNF by MMP-9. Our findings point to autocrine mechanism of action of MMP-9 through BDNF maturation and TrkB activation during sLTP. | | 3:21a |
AI without networks
Contemporary Artificial Intelligence (AI) stands on two legs: large training data corpora and many-parameter artificial neural networks (ANNs). The data corpora are needed to represent the complexity and heterogeneity of the world. The role of the networks is less transparent due to the obscure dependence of the network parameters and outputs on the training data and inputs. This raises problems, ranging from technical-scientific to legal-ethical. We hypothesize that a transparent approach to machine learning is possible without using networks at all. By generalizing a parameter-free, statistically consistent data interpolation method, which we analyze theoretically in detail, we develop a framework for generative modeling. Given the growing usage of machine learning techniques in science, we demonstrate this framework with an example from the field of animal behavior. We applied this generative Hilbert framework to the trajectories of small groups of swimming fish. The framework outperforms previously developed state-of-the-art traditional mathematical behavioral models and contemporary ANN-based models in reproducing naturalistic behaviors. We do not suggest that the proposed framework will outperform networks in all applications, as over-parameterized networks can interpolate. However, our framework is theoretically sound, transparent, deterministic and parameter free: it does not require any compute-expensive training, does not involve optimization, has no model selection, and is easily reproduced and ported. We also propose an easily computed method of credit assignment based on this framework that could help address ethical-legal challenges raised by generative AI. | | 4:44a |
High-resolution awake mouse fMRI at 14 Tesla
High-resolution awake mouse fMRI remains challenging despite extensive efforts to address motion-induced artifacts and stress. This study introduces an implantable radiofrequency (RF) surface coil design that minimizes image distortion caused by the air/tissue interface of mouse brains while simultaneously serving as a headpost for fixation during scanning. Using a 14T scanner, high-resolution fMRI enabled brain-wide functional mapping of visual and vibrissa stimulation at 100x100x200m resolution with a 2s per frame sampling rate. Besides activated ascending visual and vibrissa pathways, robust BOLD responses were detected in the anterior cingulate cortex upon visual stimulation and spread through the ventral retrosplenial area (VRA) with vibrissa air-puff stimulation, demonstrating higher-order sensory processing in association cortices of awake mice. In particular, the rapid hemodynamic responses in VRA upon vibrissa stimulation showed a strong correlation with the hippocampus, thalamus, and prefrontal cortical areas. Cross-correlation analysis with designated VRA responses revealed early positive BOLD signals at the contralateral barrel cortex (BC) occurring 2 seconds prior to the air-puff in awake mice with repetitive stimulation, which was not detectable with the randomized stimulation paradigm. This early BC activation indicated learned anticipation through the vibrissa system and association cortices in awake mice under continuous training of repetitive air-puff stimulation. This work establishes a high-resolution awake mouse fMRI platform, enabling brain-wide functional mapping of sensory signal processing in higher association cortical areas. | | 12:17p |
Brain encoding of naturalistic, continuous, and unpredictable tactile events
Studies employing EEG to measure somatosensory responses have been typically optimized to compute event-related potentials in response to discrete events (ERPs). However, tactile interactions involve continuous processing of non-stationary inputs that change in location, duration, and intensity. To fill this gap, this study aims to demonstrate the possibility of measuring the neural tracking of continuous and unpredictable tactile information. Twenty-seven young adults (females = 15) were continuously and passively stimulated with a random series of gentle brushes on single fingers of each hand, which were covered from view. Thus, tactile stimulations were unique for each participant, and fingers were stimulated. An encoding model measured the degree of synchronization between brain activity and continuous tactile input, generating a temporal response function (TRF). Brain topographies associated with the encoding of each finger stimulation showed a contralateral response at central sensors starting at 50 ms and peaking at about 140 ms of lag, followed by a bilateral response at about 240 ms. A series of analyses highlighted that reliable tactile TRF emerged after just 3 minutes of stimulation. Our results demonstrated for the first time the possibility of using EEG to measure the neural tracking of a naturalistic, continuous, and unpredictable stimulation in the somatosensory domain. Crucially, this approach allows the study of brain activity following individualized, idiosyncratic tactile events. This approach can potentially foster novel ways for investigating tactile processing by replacing artificial laboratory constrained tasks with ecological real-world interactions. | | 12:17p |
Estrogenic control of reward prediction errors and reinforcement learning
Gonadal hormones act throughout the brain, and nearly all neuropsychiatric disorders vary in symptom severity with hormonal fluctuations over the reproductive cycle, gestation, and perimenopause. Yet the mechanisms by which hormones influence mental and cognitive processes are unclear. Exogenous estrogenic hormones modulate dopamine signaling in the nucleus accumbens core (NAcc), which instantiates reward prediction errors (RPEs) for reinforcement learning. Here we show that endogenous estrogenic hormones enhance RPEs and sensitivity to previous rewards by regulating expression of dopamine reuptake proteins in the NAcc. We trained rats to perform a temporal wagering task with different reward states; rats adjusted how quickly they initiated trials across states, balancing effort against expected rewards. Dopamine release in the NAcc reflected RPEs that predicted and causally influenced subsequent initiation times. When fertile, females more quickly adjusted their initiation times to match reward states due to enhanced dopaminergic RPEs in the NAcc. Proteomics revealed reduced expression of dopamine transporters in fertile stages of the reproductive cycle. Finally, genetic suppression of midbrain estrogen receptors eliminated hormonal modulation of behavior. Estrogenic hormones therefore control the rate of reinforcement learning by regulating RPEs via dopamine reuptake, providing a mechanism by which hormones influence neural dynamics for motivation and learning. | | 12:17p |
Dynamics of Adult Axin2 Cell Lineage Integration in Granule Neurons of the Dentate Gyrus
The Wnt pathway plays critical roles in neurogenesis. The expression of Axin2 is induced by Wnt/beta-catenin signaling, making this gene a sensitive indicator of canonical Wnt activity. We employed pulse-chase genetic lineage tracing with the Axin2-CreERT2 allele to follow the fate of Axin2-positive cells in the adult hippocampal formation. We found Axin2 expressed in astrocytes, neurons and endothelial cells, as well as in the choroid plexus epithelia. Simultaneously with tamoxifen induction of Axin2 fate mapping, the dividing cells were marked with 5-ethynyl-2-deoxyuridine (EdU). Tamoxifen induction resulted in significant increase of dentate gyrus granule cells three months later; however, none of these neurons contained EdU signal. Conversely, six months after the tamoxifen/EdU pulse-chase labeling, EdU-positive granule neurons were identified in each animal. Our data imply that Axin2 is expressed at several different stages of adult granule neuron differentiation and suggest that the process of integration of the adult-born neurons from certain cell lineages may take longer than previously thought. | | 12:17p |
Astrocytes regulate neuronal network burst frequency through NMDA receptors species- anddonor-specifically
Development of synaptic activity is a neuronal key characteristic that relies largely on interactions between neurons and astrocytes. Although astrocytes have known roles in regulating synaptic function and malfunction, the use of human or donor-specific astrocytes in disease models is still rare. Rodent astrocytes are routinely used to enhance neuronal activity in cell cultures, but less is known how human astrocytes influence neuronal activity. Here, we established human induced pluripotent stem cell (hiPSC)-derived neuron-astrocyte co-cultures and studied their functional development on microelectrode array (MEA). We used cell lines from 5 neurotypical control individuals and 3 pairs of monozygotic twins discordant for schizophrenia. A method combining Ngn2 overexpression and dual SMAD inhibition was used for neuronal differentiation. The neurons were co-cultured with hiPSC-derived astrocytes differentiated from 6-month-old astrospheres or rat astrocytes. We found that the hiPSC-derived co-cultures develop complex network bursting activity similarly to neuronal co-cultures with rat astrocytes. However, the effect of NMDA receptors on neuronal network burst frequency (NBF) differed between co-cultures containing human or rat astrocytes. By using co-cultures derived from patients with schizophrenia and unaffected individuals, we found lowered NBF in the affected cells. We continued to demonstrate how astrocytes from an unaffected individual rescue the lowered NBF in the affected neurons by increasing NMDA receptor activity. Our results indicate that astrocytes participate in the regulation of neuronal NBF through a mechanism involving NMDA receptors. These findings shed light on the importance of using human and donor-specific astrocytes in disease modeling. | | 12:17p |
Temporal Complexity of the BOLD-Signal In Preterm Versus Term Infants
Preterm birth causes alterations in cerebral development. We calculated the Hurst exponent (H) - a measure of temporal complexity - from resting state functional magnetic resonance signal in preterm and term born infants. Anatomical, fMRI, and diffusion weighted imaging data from 716 neonates born between 23-43 weeks gestational age were obtained from the Developing Human Connectome Project. H was assessed in brain tissues and 13 resting state networks. H signi[fi]cantly increased with age, and earlier birth age contributed to lower H values. In most brain regions, H begins below 0.5 at preterm age and crosses 0.5 at term age. Motor and sensory networks demonstrated the greatest increase in H. Correlations between indirect measures of myelination and H were moderate. Overall, H appears to re[fl]ect developmental processes in the neonatal brain, as BOLD signal in the preterm infant transforms from anticorrelated to correlated but is reduced compared to term born infants. |
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