Neuropsychiatric disorders are a serious public health concern, given that they are the leading cause of disability and account for millions of deaths worldwide. Despite thorough research efforts during the past few years, our understanding of the complex biological mechanistic processes underlying these conditions remains mainly unknown. Recently, a study by researchers at RIKEN BSI aimed to explore how locomotion and brain behavior relate to complex mechanisms underlying autism in mice, using virtual reality-based real-time imaging of Functional connectivity (FC) dynamics in mouse cortex. The researchers found that different locomotion states in autistic mice were associated with changes in FC, particularly in the motor area, implying that motor clumsiness is related to abnormal FC in the motor area. This study provides further insights into the neurobiology of autism and offers this promising virtual reality system for improvements in the field of neuroscience and treatments of neuropsychiatric disorders.
The Importance of Studying Functional Connectivity and its Dynamics
Functional connectivity (FC) is referred to as the synchronization between spatially remote neurophysiological events, and, more simply, it refers to the statistical links between different regions in the brain. FC dynamics refer to the changes in these links in response to behavioral state changes or transitions. FC and FC dynamics are, therefore, indicative of neural coordination and communication between the different regions of the brain. Studying and understanding functional connectivity is crucial not only for understanding the mechanisms of various neurobiological processes like cognitive function, motor control, and sensory perceptions but also for understanding the mechanisms underlying neurological disorders, including autism spectrum disorder (ASD). However, measuring FC is complex, and existing methods cannot correctly quantify it. The conventional technique – functional magnetic resonance imaging (fMRI) – does work under high spatial resolution. However, its temporal resolution is very low, implying it cannot capture information about complex and dynamic behaviors like locomotion and whole-body movement.
The paper by Nakai et al., published in Cell Reports, addresses the issue by offering a novel approach to studying FC using a virtual reality-based system that offers real-time imaging. This new system allows for a better understanding of the fast dynamics of FC in various neurobiological processes and how FC disruptions can be associated with neuropsychiatric disorders, particularly ASD.
Utilizing Virtual Reality to Study FC Dynamics in Mouse Models with ASD
The newly-developed virtual reality-based system for real-time imaging allowed the mouse to move freely in a VR setup. Simultaneously, calcium cation (Ca2+) signals were measured in the dorsal cortex through mesoscopic Ca2+ imaging. This way, the system was utilized in order to provide real-time imaging of FC during mouse locomotion.
The key finding was that altered FC dynamics were linked with locomotion states in mouse models with ASD relative to control mouse models. Essentially, a rapid shift of the FC patterns was observed within the motor area in autistic mice when they transitioned from rest to locomotion states. This was not observed for the control mice. This shift could be explained by a reduced number of active neurons and an increased correlation between the less-abundant active neurons in ASD brains. Additionally, the degree and extent of the alterations in FC dynamics were positively correlated with the increasing severity of ASD in the mice. It is clear that these results could demonstrate that motor clumsiness in individuals with autism could be linked to altered FC in the motor area of the brain. Moreover, they also highlight the importance and scope of examining behaviors, transitions, and dynamics and moving ahead from conventional neuroscience research examining only the resting state.
An Augmented Understanding of Neural Mechanisms Underlying ASD
Given the remarkable findings (as described in the previous section), the researchers advanced explanations for and discussed the implications of the findings, proposing an augmented understanding of the neural mechanisms underlying autism. Firstly, it was observed that 15q dup ASD mice had hyperconnected and less modular cortical networks compared to control mice. This indicates that the altered FC dynamics observed in the motor area during locomotion may be due to abnormalities in the cortical network of individuals with autism. More precisely, the rapid reorganization and modularization of cortical networks during locomotion are responsible for the altered FC dynamics in the motor area.
During locomotion, it is known that the brain quickly reorganizes and coordinates the activity of different regions involved in motor control, allowing correct and coordinated movement. The researchers found that this quick reorganization of cortical networks is linked with the modularization of the motor cortex, suggesting that movement is coordinated by specific groups of neurons interacting with each other. But, in ASD mice, the modularization with respect to locomotion is dysregulated, causing hyperconnected yet fewer modular cortical networks. This may explain the inefficient or non-smooth movement of ASD mice, analogous to the motor symptoms of autistic humans.
Implications, Future Outlook, and Limitations
The study also used a support vector machine (SVM) algorithm, which utilizes machine learning, to group the ASM mouse model based on the signals from FC data obtained through mesoscopic calcium imaging. Specifically, they classified the ASD genotype of the mouse model, illustrating the potential of using the SVM and virtual reality-based imaging for ASD diagnosis. Regardless, the study was crucial for better understanding the neural mechanisms underlying diseases like ASD and provided scope for future work in this field. For instance, additional mouse models could be examined to gain further insights into this VR-based imaging system and check for potential therapeutics to reverse the FC abnormalities.
However, the study also has its limitations. One major limitation is that only the activity of the dorsal cortex was visualized using mesoscopic Ca2+ imaging, meaning that the FC dynamics in other cortical regions were not measured. Also, the monitored neural activity signals came only from layer 1 and layer 2/3, which contain the cell bodies and dendrites of local pyramidal neurons and the superficial axons innervating them.
Conclusion
To conclude, this is a revolutionary study that offers a novel and unique approach to studying neurobiological mechanisms – through the use of VR-based real-time imaging (mesoscopic Ca2+ imaging), gaining the benefit of accurately capturing FC dynamics, something to which fMRI is limited. It also provides a direction as to what future work is required in the field and the need for improved technology to address the study’s limitations.
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Diyan Jain is a second-year undergraduate majoring in Biotechnology at Imperial College, London, and currently interning as a scientific content writer at CBIRT. His passion for writing and science has led him to pursue this opportunity to communicate cutting-edge research and discoveries engagingly to a broader public. Diyan is also working on a personal research project to evaluate the potential for genome sequencing studies and GWAS to identify disease likelihood and determine personalized treatments. With his fascination for bioinformatics and science communication, he is committed to delivering high-quality content a CBIRT.
