Non-Linear Frequency Dependence of Neurovascular Coupling in the Cerebellar Cortex Implies Vasodilation-Vasoconstriction Competition

Neurovascular coupling dysfunction in high myopia patients: Evidence from a multi-modal magnetic resonance imaging analysis

BACKGROUND AND PURPOSE

To investigate neurovascular coupling dysfunction in high myopia (HM) patients.

MATERIALS AND METHODS

A total of 37 HM patients and 36 healthy controls were included in this study. Degree centrality (DC), regional homogeneity (ReHo), amplitude of low-frequency fluctuations (ALFF), and fractional ALFF (fALFF) maps were employed to represent neuronal activity. Cerebral blood perfusion was characterized by cerebral blood flow (CBF). The correlation coefficient was calculated to reflect the relationship between neuronal activity and cerebral blood perfusion. Pearson partial correlation analysis was utilized to evaluate the association between HM dysfunction and clinical indicators.

RESULTS

HM patients exhibited significant alterations in neurovascular coupling across 37 brain regions compared to healthy controls. The brain regions with marked changes varied among the four neurovascular coupling patterns, including the middle frontal gyrus, superior occipital gyrus, middle occipital gyrus, and fusiform gyrus. Additionally, the superior frontal gyrus orbital part, medial superior frontal gyrus, inferior occipital gyrus, and dorsolateral superior frontal gyrus displayed significant changes in three coupling patterns. In HM patients, the ReHo-CBF changes in the inferior frontal gyrus orbital part were positively correlated with best-corrected visual acuity (BCVA) and refractive diopter changes. Similarly, the ALFF-CBF changes in the inferior frontal gyrus orbital part showed a positive correlation with refractive diopter changes. ReHo-CBF and ALFF-CBF alterations in the paracentral lobule were positively correlated with BCVA and refractive diopter changes.

CONCLUSION

Our findings underscore the abnormal alterations in neurovascular coupling across multiple brain regions in HM patients. These results suggest that neurovascular dysfunction in HM patients may be associated with an aberrant visual regulation mechanism.

A multi-layer mean-field model of the cerebellum embedding microstructure and population-specific dynamics

Mean-field (MF) models are computational formalism used to summarize in a few statistical parameters the salient biophysical properties of an inter-wired neuronal network. Their formalism normally incorporates different types of neurons and synapses along with their topological organization. MFs are crucial to efficiently implement the computational modules of large-scale models of brain function, maintaining the specificity of local cortical microcircuits. While MFs have been generated for the isocortex, they are still missing for other parts of the brain. Here we have designed and simulated a multi-layer MF of the cerebellar microcircuit (including Granule Cells, Golgi Cells, Molecular Layer Interneurons, and Purkinje Cells) and validated it against experimental data and the corresponding spiking neural network (SNN) microcircuit model. The cerebellar MF was built using a system of equations, where properties of neuronal populations and topological parameters are embedded in inter-dependent transfer functions. The model time constant was optimised using local field potentials recorded experimentally from acute mouse cerebellar slices as a template. The MF reproduced the average dynamics of different neuronal populations in response to various input patterns and predicted the modulation of the Purkinje Cells firing depending on cortical plasticity, which drives learning in associative tasks, and the level of feedforward inhibition. The cerebellar MF provides a computationally efficient tool for future investigations of the causal relationship between microscopic neuronal properties and ensemble brain activity in virtual brain models addressing both physiological and pathological conditions.

Anisotropy and Frequency Dependence of Signal Propagation in the Cerebellar Circuit Revealed by High-Density Multielectrode Array Recordings

The cerebellum is one of the most connected structures of the central nervous system and receives inputs over an extended frequency range. Nevertheless, the frequency dependence of cerebellar cortical processing remains elusive. In this work, we characterized cerebellar cortex responsiveness to mossy fibers activation at different frequencies and reconstructed the spread of activity in the sagittal and coronal planes of acute mouse cerebellar slices using a high-throughput high-density multielectrode array (HD-MEA). The enhanced spatiotemporal resolution of HD-MEA revealed the frequency dependence and spatial anisotropy of cerebellar activation. Mossy fiber inputs reached the Purkinje cell layer even at the lowest frequencies, but the efficiency of transmission increased at higher frequencies. These properties, which are likely to descend from the topographic organization of local inhibition, intrinsic electroresponsiveness, and short-term synaptic plasticity, are critical elements that have to be taken into consideration to define the computational properties of the cerebellar cortex and its pathological alterations.

A task-general connectivity model reveals variation in convergence of cortical inputs to functional regions of the cerebellum

While resting-state fMRI studies have provided a broad picture of the connectivity between human neocortex and cerebellum, the degree of convergence of cortical inputs onto cerebellar circuits remains unknown. Does each cerebellar region receive input from a single cortical area or convergent inputs from multiple cortical areas? Here, we use task-based fMRI data to build a range of cortico-cerebellar connectivity models, each allowing for a different degree of convergence. We compared these models by their ability to predict cerebellar activity patterns for novel Task Sets. Models that allow some degree of convergence provided the best predictions, arguing for convergence of multiple cortical inputs onto single cerebellar voxels. Importantly, the degree of convergence varied across the cerebellum with the highest convergence observed in areas linked to language, working memory, and social cognition. These findings suggest important differences in the way that functional subdivisions of the cerebellum support motor and cognitive function.

Functional Deficiency of Interneurons and Negative BOLD fMRI Response

The functional deficiency of the inhibitory system typically appears during development and can progress to psychiatric disorders or epilepsy, depending on its severity, in later years. It is known that interneurons, the major source of GABAergic inhibition in the cerebral cortex, can make direct connections with arterioles and participate in the regulation of vasomotion. The goal of this study was to mimic the functional deficiency of interneurons through the use of localized microinjections of the GABA antagonist, picrotoxin, in such a concentration that it did not elicit epileptiform neuronal activity. First, we recorded the dynamics of resting-state neuronal activity in response to picrotoxin injections in the somatosensory cortex of an awake rabbit; second, we assessed the altered neuronal and hemodynamic responses to whisker stimulation using BOLD fMRI and electrophysiology recordings; third, we evaluated brain tissue oxygen levels before and after picrotoxin injection. Our results showed that neuronal activity typically increased after picrotoxin administration, the BOLD responses to stimulation became negative, and the oxygen response was nearly abolished. Vasoconstriction during the resting baseline was not observed. These results indicate that picrotoxin provoked imbalanced hemodynamics either due to increased neuronal activity, decreased vascular response, or a combination of both.

Computational models of neurotransmission at cerebellar synapses unveil the impact on network computation

The neuroscientific field benefits from the conjoint evolution of experimental and computational techniques, allowing for the reconstruction and simulation of complex models of neurons and synapses. Chemical synapses are characterized by presynaptic vesicle cycling, neurotransmitter diffusion, and postsynaptic receptor activation, which eventually lead to postsynaptic currents and subsequent membrane potential changes. These mechanisms have been accurately modeled for different synapses and receptor types (AMPA, NMDA, and GABA) of the cerebellar cortical network, allowing simulation of their impact on computation. Of special relevance is short-term synaptic plasticity, which generates spatiotemporal filtering in local microcircuits and controls burst transmission and information flow through the network. Here, we present how data-driven computational models recapitulate the properties of neurotransmission at cerebellar synapses. The simulation of microcircuit models is starting to reveal how diverse synaptic mechanisms shape the spatiotemporal profiles of circuit activity and computation.

Modulating swallowing-related functional connectivity and behavior via modified pharyngeal electrical stimulation: A functional near-infrared spectroscopy evidence

Introduction

Modified pharyngeal electrical stimulation (mPES) is a novel therapeutic modality for patients with neurogenic dysphagia. However, the underlying neural mechanism remains poorly understood. This study aimed to use functional near-infrared spectroscopy (fNIRS) to explore the influence of mPES on swallowing-related frequency-specific neural networks and ethology.

Methods

Twenty-two healthy right-handed volunteers participated in the study. Each participant was randomly assigned to either the sham or the mPES group and provided a 10-min intervention program every day for 5 days. Oxyhemoglobin and deoxyhemoglobin concentration changes verified by fNIRS were recorded on days 1, 3, and 5. Five characteristic frequency signals (0.0095-2 Hz) were identified using the wavelet transform method. To calculate frequency-specific functional connectivity, wavelet phase coherence (WPCO) was adopted. Furthermore, behavioral performance was assessed pre- and post-mPES using a 150 ml-water swallowing stress test.

Results

Compared with sham stimulation on day 1, the significantly decreased WPCO values were mainly associated with the dorsolateral prefrontal lobe, Broca's area, and middle temporal lobe. Compared with the sham mPES on day 1, the mPES showed a noticeable effect on the total swallow duration. Compared with the baseline, the WPCO values on days 3 and 5 showed a stepwise decrease in connectivity with the application of mPES. Furthermore, the decreased WPCO was associated with a shortened time per swallow after mPES.

Conclusions

The mPES could modulate swallowing-related frequency-specific neural networks and evoke swallowing cortical processing more efficiently. This was associated with improved performance in a water swallowing stress test in healthy participants.