Summary
The neural network controls physical activities. Recently scientists have found out that the neural network can be observed to show different levels of activation depending on an organism’s mental activity. Scientists have gone further to devise actual methods that detect brain activity in particular instances. The brain and the neural network never stop working; however, certain tasks cause the brain and the neural network to work faster, harder and more intensely (Garcia). These unique activities usually register or appear as spikes or dips in the never-ending sequence of brain activity. Genetically Encoded Voltage Indicators (GEVIs) are a promising innovation in detecting these said peaks, which are of interest to scientists (Gong et al.). Testing on awake mice and flies is underway to prove that this method works and someday can be made safe and reliable for use on a complex, highly intelligent organism like a human being.
GEVIs employs the technology of fluorescent voltage sensors, which works by tracking subcellular and cellular electrophysiological activity with at a hundredth of a second scale resolution in neuron types that have been identified (Gong et al.). The study aims to show what particular behavior or certain stimuli do to the neural network regarding activity spike. Using mice is a typical example of a mammalian brain, and the flies act as a control for the experiment to prove the difference in the two brain types (Gong et al.). The process hence involves two proteins; the work of the first protein is to detect neural voltage potential while the work of the second protein is to amplify the signal produced (Gong et al.). The output detection is in the form of line graphs or charts that show the spikes and dips, which are representations of the neural activity. GEVIs are an improvement because the previous ones were slow in detecting signals and did not cover certain ranges since they were not sensitive to detect the smallest ranges in activity.
Background and Perspective
In every second, about 100 billion neurons in the brain have the ability to burst out electricity, which is known as an action potential. It had been a great challenge to monitor or view the exciting activity of the brain. From the existing literature, neuronal activity sensors are not a new technology though the previous inventions were quite slow and had a limited scope of providing a holistic view (Akemann). Therefore, researchers have discovered better techniques that can keep up with the neurons and have a resolution of up to 0.2 milliseconds.
This invention is an overwhelming idea, and it has got a good number of scientists talking. In a review done by Ken Kingery, unlike the report made by the inventors of this system, he takes a different angle by engaging the reader on the background of this idea. He talks about the defining moment and the spark of genius that leads to GEVIs as we know it today (Kingery). He states that the amount of light used earlier in the experiment was not enough, and hence it needed to be amplified by invoking the brightest fluorescing protein available at that time (Kingery). It is a very optimistic review that gives hope for further development of this brilliant idea. In another review by Rosa Garcia, which focuses on neuroimaging, it involves the processes that take place in the spatial output of brain activity of the samples in question. She rather outlines a disadvantage that the system cannot be used for extended periods of time.
The working of the high-speed fluorescent voltage sensors is achieved by combining two proteins, which are Acetabularia acetabulum and the mNeonGreen fluorescent. The Ace senses the fast neural change of the voltage potential. This protein is fungus-derived and responds up to six times more quickly to the voltage changes compared to the older versions ("Cohen Lab"). The second protein, mNeonGreen, causes the visual change in voltage potential after it has been activated by another protein that provides the necessary imaging output (Garcia). The output is made possible by a fluorescent marker that displays the brain in action. The Ace-mNeon indicators will now enable imaging of the high fidelity spectrum of the fast and individual spikes of the flies and mice due to their rapid and superior kinetics
Despite this technique being an astounding discovery, it still has a drawback in that it cannot be used for an extended amount of time because the proteins lose their sensitivity in the presence of continuous exposure to light (Garcia). However, this challenge can be curbed by short and multiple exposures to light, which should be able to sustain the neuronal sensor for a much longer period. Though it is also hard to quantify how short, or long the exposure should be, it is a challenge that can be worked on further just as the genetically encoded calcium indicators were in the previous years; therefore, there is room for improvement to make it a better tool for use to achieve the primary objective of the tool.
Methods and Results
First, two proteins are fused to enable illumination. The process begins by first enabling fluorescence resonance energy transfer (FRET) by fusing the Acetabularia acetabulum rhodopsin (Ace II) with the mNeonGreen (12) fluorescent protein (Gong et al.). The fusing is important because it provides “fast kinetics of a rhodopsin VSD with a bright fluorophore thus provides high accuracy and readouts at levels of illumination much lower than what conventional methods like arch indicators use, (Gong et al.).
The indicators then detect the neural activity compared to the fluorescence changes. Neural activity translates into changes in fluorescence; these changes are identified by Ace indicators. The Ace mutants that are created, Ace1Q and Ace2N with an inactivated proton pump, provide sharp peaks in fluorescence (Gong et al.). They yield superior FRET acceptors when they are paired with yellow or green emitters. Each peak represents a moment of neural activity.
The spikes that are viewed as output are then examined. The Ace provided accurate timing of the spike. The examination on awake mice was used to determine whether the individual cells, which are “ongoing fluctuations in the baseline of the mNeon emissions, reflect the subthreshold membrane of voltage dynamics” (Gong et al.). The visually evoked responses are studied since they “represent dendritic and high-speed membrane potential dynamics of an active brain” (Gong et al.).
The results are then keenly studied to deduce a precise analysis. Results come in a series of functions, with ever-changing parameters as per the neurologist’s desired reading. The most basic of results is interpreted regarding fluorescent intensity as a function of time in milliseconds. Fluorescence change can also be given in a line graph as a function of voltage, where Ace2N-mNeon indicator shows the largest variance on fluorescence because it is the most sensitive of the indicators compared to the other indicators for the same voltage range (Gong et al.). Also, the spatial maps with fluorescent signals, Ace2N-mNeon, show a more vivid detection of fluorescent changes at less than -15%. Just by looking at Ace1Q-mNeon's spatial mapping, it shows more dominance in detecting fluorescence changed between 0 to -10% F/F, which is at a lower integrity (Gong et al.).
The reason live mice are preferred because data shows that spike activity for an in vivo specimen is more vivid at less than 3% fluorescence change compared to a sliced sample, even at just less than 10% fluorescence change (Wachowiak and Knöpfel). Stimuli changes are evoked from the mice and flies mainly by odor, but the test is not conclusive in showing what specific odors elicit regarding reaction from the test subject (Mutoh). The test could also use a wider range of external stimuli just to get a feel of diversity in this tool.
Analysis
In general, this technique is quite overwhelming since it depicts a great optimism in the world of science and it holds so much importance since it is ripe for more research and scientific advancements. There is a plethora of data to be collected and sampled by classical statistical methods. Having this wide range of data enabled neurologists to get a three-dimensional feel of the inner workings of the neural network. It is commendable just how much data can be derived from using GEVIs. Its results live up to its billing as a promising method that might one day map out effects of external stimuli to brain activity (Gong et al.). This approach should, however, pick a wider range of stimuli from pain, light, temperature and stress.
The data could also do with a bit of simplification to hold relevance with a larger audience. The study should have also included effects (if any) on the test subjects. All in all, this technique shows high promise in the wider area of neural science, medicine, and psychology. This technique, if further improved on primitive mammals and then to humans themselves, would change everything as we know it. This is an exciting idea because if a neural reaction can be observed from certain stimuli, then it would be possible to determine what would happen if the neural reaction is reverse engineered to drive the human brain towards the desired stimuli.
Works Cited
Akemann, Walther, et al. "Two-photon voltage imaging using a genetically encoded voltage
indicator." Scientific Reports 3 (2013). Web. 29 Mar. 2016.
"Cohen Lab". Cohenweb.rc.fas.harvard.edu. N.p., 2016. Web. 29 Mar. 2016.
Garcia, Rosa. "The Ultimate Neuronal Activity Sensor Is Here." Labcritics. N.p., 2015. Web. 29
Mar. 2016.
Gong, Yiyang, et al. "High-speed recording of neural spikes in awake mice and flies with a
fluorescent voltage sensor." Science 350.6266 (2015): 1361-1366. Web. 29 Mar. 2016.
Kingery, Ken. "Sensor Sees Nerve Action As It Happens: Technique Provides First Real-Time,
Eagle-Eye View Of Neural Activity In Mammal Brains." ScienceDaily. N.p., 2016. Web.
31 Mar. 2016.
Mutoh, Hiroki, Walther Akemann, and Thomas Knöpfel. "Genetically encoded Voltage
indicators." Optical Probes in Biology 6 (2015): 229. Web. 29 Mar. 2016.
Wachowiak, Matt, and Thomas Knöpfel. "Optical Imaging Of Brain Activity In Vivo Using
Genetically Encoded Probes." CRC Press/Taylor & Francis (2009): n. page. Web. 29
Mar. 2016.
