scholarly journals Piezo2—peripheral baroreceptor channel expressed in select neurons of the mouse brain: a putative mechanism for synchronizing neural networks by transducing intracranial pressure pulses

2021 ◽  
Vol 20 (4) ◽  
pp. 825-837
Author(s):  
Jigong Wang ◽  
Owen P. Hamill
Author(s):  
Jigong Wang ◽  
Owen P. Hamill

ABSTRACTPiezo2 expression in the normal, young adult mouse brain was examined using an anti-PIEZO2 Ab generated against a C-terminal fragment of the human PIEZO2 protein. As a positive control for Ab staining of mouse neurons, the Ab was shown to stain the majority (~90%) of mouse dorsal root ganglia (DRG) neurons, consistent with recent in situ hybridization and transcriptomic studies that also indicate Piezo2 gene expression in ~90% mouse DRG neurons. As a negative control and stringent test for specificity, the Ab failed to stain DRG satellite glial cells, which do not express Piezo2 but rather its paralog, Piezo1. In slices of brains isolated from the same mice as the DRG, the Ab displayed high selectivity in staining only specific neuron types, including some pyramidal neurons in the neocortex and hippocampus, Purkinje cells in the cerebellar cortex, and most notably mitral cells within the olfactory bulb. Given the demonstrated role of Piezo2 channels in peripheral neurons as a low-threshold pressure sensor (i.e., ≤ 5 mm Hg) critical for gentle touch, proprioception, and the regulation of breathing and blood pressure, its expression in select brain neurons has interesting implications. In particular, we propose that the pressure sensitive channel may provide specific brain neurons with an intrinsic resonance that acts to synchronize their firing with the normal pulsatile changes in intracranial pressure (ICP) associated with breathing and cardiac cycles. This novel mechanism could serve to increase the robustness of the respiration entrained oscillations that have been recorded in both rodent and human brains across widely distributed neuronal networks. The idea of a “global rhythm” within the brain has been mainly related to the effect of nasal airflow activating mechanosensitive neurons within the olfactory epithelium, which in turn synchronize, through direct synaptic connections, mitral neurons within the olfactory bulb and then through their projections, the activity of neural networks in other brain regions, including the hippocampus and neocortex. Our proposed, non-synaptic, intrinsic resonance mechanism for tracking pulsatile ICP changes would have the advantage that spatially separated brain networks could be globally synchronized effectively at the speed of sound.


2021 ◽  
Author(s):  
Jigong wang ◽  
owen peter hamill

Abstract Piezo2 expression in mouse brain was examined using an anti-PIEZO2 antibody (Ab) generated against a C-terminal fragment of the human PIEZO2 protein. As a positive control for Ab staining of mouse neurons, the Ab stained a majority of mouse dorsal root ganglion (DRG) neurons, consistent with recent in situ hybridization and single cell RNA sequencing studies of Piezo2 expression. As a negative control and test for specificity, the Ab failed to stain human erythrocytes, which selectively express PIEZO1. In brain slices isolated from the same mice as the DRG, the Ab displayed high selectivity in staining specific neuron types, including pyramidal neurons in the neocortex and hippocampus, Purkinje cells in the cerebellar cortex and mitral cells in the olfactory bulb. Given the demonstrated role of Piezo2 channels in peripheral neurons as a low-threshold pressure sensor (i.e., ≤ 5 mm Hg) critical for the regulation of breathing and blood pressure, its expression in select brain neurons has interesting implications. In particular, we hypothesize that Piezo2 provides select brain neurons with an intrinsic resonance enabling their entrainment by the normal intracranial pressure (ICP) pulses (~ 5 mm Hg) associated with breathing and cardiac cycles. This mechanism could serve to increase the robustness of respiration-entrained oscillations previously reported across widely distributed neuronal networks in both rodent and human brains. This idea of a “global brain rhythm” has previously been thought to arise from the effect of nasal airflow activating mechanosensitive neurons within the olfactory epithelium, which then synaptically entrain mitral cells within the olfactory bulb and through their projections, neural networks in other brain regions, including the hippocampus and neocortex. Our proposed, non-synaptic, intrinsic mechanism in which Piezo2 tracks the “metronome-like” ICP pulses would have the advantage that spatially separated brain networks could also be synchronized by a physical force that is rapidly transmitted throughout the brain.


2000 ◽  
Vol 142 (4) ◽  
pp. 407-412 ◽  
Author(s):  
Z. Mariak ◽  
M. Swiercz ◽  
J. Krejza ◽  
J. Lewko ◽  
T. Lyson

2021 ◽  
Vol 15 ◽  
Author(s):  
Xinglong Wu ◽  
Yuhang Tao ◽  
Guangzhi He ◽  
Dun Liu ◽  
Meiling Fan ◽  
...  

Deep convolutional neural networks (DCNNs) are widely utilized for the semantic segmentation of dense nerve tissues from light and electron microscopy (EM) image data; the goal of this technique is to achieve efficient and accurate three-dimensional reconstruction of the vasculature and neural networks in the brain. The success of these tasks heavily depends on the amount, and especially the quality, of the human-annotated labels fed into DCNNs. However, it is often difficult to acquire the gold standard of human-annotated labels for dense nerve tissues; human annotations inevitably contain discrepancies or even errors, which substantially impact the performance of DCNNs. Thus, a novel boosting framework consisting of a DCNN for multilabel semantic segmentation with a customized Dice-logarithmic loss function, a fusion module combining the annotated labels and the corresponding predictions from the DCNN, and a boosting algorithm to sequentially update the sample weights during network training iterations was proposed to systematically improve the quality of the annotated labels; this framework eventually resulted in improved segmentation task performance. The microoptical sectioning tomography (MOST) dataset was then employed to assess the effectiveness of the proposed framework. The result indicated that the framework, even trained with a dataset including some poor-quality human-annotated labels, achieved state-of-the-art performance in the segmentation of somata and vessels in the mouse brain. Thus, the proposed technique of artificial intelligence could advance neuroscience research.


2000 ◽  
Vol 142 (4) ◽  
pp. 401-406 ◽  
Author(s):  
M. Swiercz ◽  
Z. Mariak ◽  
J. Krejza ◽  
J. Lewko ◽  
P. Szydlik

2010 ◽  
Vol 14 (2) ◽  
pp. 229-237 ◽  
Author(s):  
Sunghan Kim ◽  
Xiao Hu ◽  
David McArthur ◽  
Robert Hamilton ◽  
Marvin Bergsneider ◽  
...  

Author(s):  
Richard Bolander ◽  
Cynthia Bir ◽  
Pamela VandeVord

Blast associated injuries have been quantified into different classes based on the type of trauma that they create [1]. Of these types of trauma, the neuropathology invoked by shock wave exposure is the most ambiguous [1]. The properties associated with shock wave exposure have lead to multiple hypothesized mechanisms for brain trauma including: acceleration-based damage, a thoracic squeeze resulting in pressure pulses to the brain, or transference of energy from the shock wave into the brain via the skull [2, 3].


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