Traumatic brain injury alterations in the functional connectome are associated with neuroinflammation but not tau in a P30IL tauopathy mouse model

The impact of neuroinflammation on neuronal integrity

Neuroinflammation, characterized by a complex interplay among innate and adaptive immune responses within the central nervous system (CNS), is crucial in responding to infections, injuries, and disease pathologies. However, the dysregulation of the neuroinflammatory response could significantly affect neurons in terms of function and structure, leading to profound health implications. Although tremendous progress has been made in understanding the relationship between neuroinflammatory processes and alterations in neuronal integrity, the specific implications concerning both structure and function have not been extensively covered, with the exception of perspectives on glial activation and neurodegeneration. Thus, this review aims to provide a comprehensive overview of the multifaceted interactions among neurons and key inflammatory players, exploring mechanisms through which inflammation influences neuronal functionality and structural integrity in the CNS. Further, it will discuss how these inflammatory mechanisms lead to impairment in neuronal functions and architecture and highlight the consequences caused by dysregulated neuronal functions, such as cognitive dysfunction and mood disorders. By integrating insights from recent research findings, this review will enhance our understanding of the neuroinflammatory landscape and set the stage for future interventions that could transform current approaches to preserve neuronal integrity and function in CNS-related inflammatory conditions.

Ultrasound Modulates Calcium Activity in Cultured Neurons, Glial Cells, Endothelial Cells and Pericytes

OBJECTIVE

Ultrasound is being researched as a method to modulate the brain. Studies of the interaction of sound with neurons support the hypothesis that mechanosensitive ion channels play an important role in ultrasound neuromodulation. The response of cells other than neurons (e.g., astrocytes, pericytes and endothelial cells) have not been fully characterized, despite playing an important role in brain function.

METHODS

To address this gap in knowledge, we examined cultured murine primary cortical neurons, astrocytes, endothelial cells and pericytes in an in vitro widefield microscopy setup during application of a 500 ms burst of 250 kHz focused ultrasound over a pressure range known to elicit neuromodulation. We examined cell membrane health in response to a range of pulses and used optical calcium indicators in conjunction with pharmacological antagonists to selectively block different groups of thermo- and mechanosensitive ion channels known to be responsive to ultrasound.

RESULTS

All cell types experienced an increase in calcium fluorescence in response to ultrasound. Gadolinium (Gad), 2-aminoethoxydiphenyl borate (2-APB) and ruthenium red (RR) reduced the percentage of responding neurons and magnitude of response. The percentage of astrocytes responding was significantly lowered only by Gad, whereas both 2-APB and Gad decreased the amplitude of the fluorescence response. 2-APB decreased the percentage of responding endothelial cells, whereas only Gad reduced the magnitude of responses. Pericytes exposed to RR or Gad were less likely to respond to stimulation. RR had no detectable effect on the magnitude of the pericyte responses while 2-APB and Gad significantly decreased the fluorescence intensity, despite not affecting the percentage responding.

CONCLUSION

Our study highlights the role of non-neuronal cells during FUS neuromodulation. All of the investigated cell types are sensitive to mechanical ultrasound stimulation and rely on mechanosensitive ion channels to undergo ultrasound neuromodulation.

Brain-wide mapping of resting-state networks in mice using high-frame rate functional ultrasound

Functional ultrasound (fUS) imaging is a method for visualizing deep brain activity based on cerebral blood volume changes coupled with neural activity, while functional MRI (fMRI) relies on the blood-oxygenation-level-dependent signal coupled with neural activity. Low-frequency fluctuations (LFF) of fMRI signals during resting-state can be measured by resting-state fMRI (rsfMRI), which allows functional imaging of the whole brain, and the distributions of resting-state network (RSN) can then be estimated from these fluctuations using independent component analysis (ICA). This procedure provides an important method for studying cognitive and psychophysiological diseases affecting specific brain networks. The distributions of RSNs in the brain-wide area has been reported primarily by rsfMRI. RSNs using rsfMRI are generally computed from the time-course of fMRI signals for more than 5 min. However, a recent dynamic functional connectivity study revealed that RSNs are still not perfectly stable even after 10 min. Importantly, fUS has a higher temporal resolution and stronger correlation with neural activity compared with fMRI. Therefore, we hypothesized that fUS applied during the resting-state for a shorter than 5 min would provide similar RSNs compared to fMRI. High temporal resolution rsfUS data were acquired at 10 Hz in awake mice. The quality of the default mode network (DMN), a well-known RSN, was evaluated using signal-noise separation (SNS) applied to different measurement durations of rsfUS. The results showed that the SNS did not change when the measurement duration was increased to more than 210 s. Next, we measured short-duration rsfUS multi-slice measurements in the brain-wide area. The results showed that rsfUS with the short duration succeeded in detecting RSNs distributed in the brain-wide area consistent with RSNs detected by 11.7-T MRI under awake conditions (medial prefrontal cortex and cingulate cortex in the anterior DMN, retrosplenial cortex and visual cortex in the posterior DMN, somatosensory and motor cortexes in the lateral cortical network, thalamus, dorsal hippocampus, and medial cerebellum), confirming the reliability of the RSNs detected by rsfUS. However, bilateral RSNs located in the secondary somatosensory cortex, ventral hippocampus, auditory cortex, and lateral cerebellum extracted from rsfUS were different from the unilateral RSNs extracted from rsfMRI. These findings indicate the potential of rsfUS as a method for analyzing functional brain networks and should encourage future research to elucidate functional brain networks and their relationships with disease model mice.