This work was supported by a grant from the Natural Sciences and Engineering Research Council of Canada (NSERC: RGPIN-2017-06131) to C.P. C. P. is a FRSQ Chercheur-Boursier. We also thank the Plateforme d&rsquo;Outils Mol&eacute;culaires (https://www.neurophotonics.ca/fr/pom) for the production of the viral vectors used in this study.

All experiments were done in accordance with the Institutional Animal Care and Use Committees of the University of California, San Diego, and the Canadian Guide for the Care and Use of Laboratory Animals and were approved by the Universit&#233; Laval Animal Protection Committee.&#160;
1. Alignment of the optical path between the CMOS (complementary metal oxide semiconductor) camera and the individual or branching patch cord
<ol>
	<li>Loosen all screws on the 5-axis translator (11, Figure 2B).</li>
	<li>Screw in the patch cord (12, Figure 2B) to the adaptor [SMA (sub-miniature A) or FC (fiber optic connector)] that is affixed to the 5-axis translator.</li>
	<li>Turn on the 470 nm excitation light (1, Figure 2B) at low power (100 &#181;W), and place the tip of the patchcord pointing to an autofluorescent plastic slide. This does not have any bearing on future recordings but is solely for visualizing the alignment process.</li>
	<li>Record from the CMOS camera (13, Figure 2B) in live mode. Increase the gain or adjust the lookup table (LUT) until the image is not entirely black. The point is to be able to see an image at the focal point of the objective (10, Figure 2B).</li>
	<li>Advance the 5-axis translator towards the objective, ensuring that the 470 nm light is centered on the fiber at the SMA or FC end of the patch cord, until an image can be resolved on the camera.</li>
	<li>Adjust the X and Y axes until the image is centered and well-resolved.</li>
	<li>Visualize the light emitted from the ferrule-end of the patch cord. It should appear as an isotropic circle. If a branching patch cord is used, the amount of light emitted at the ferrule-ends of each patch cord should be similar. If the circle is not isotropic or the emitted light is unequal, adjust the 5-axis translator in the X-Y axis.</li>
</ol>
2. Setup of ROIs around fibers for measurement of mean fluorescent intensity
<ol>
	<li>Turn on all the excitation lights to better visualize the fibers. Adjust the camera gain such that no pixels are saturated and a clear image of the fibers are present.</li>
	<li>Live record or take a preliminary image.</li>
	<li>Draw ROIs around the fibers and keep them for the measurement of the mean intensity values during recordings (Figure 2A).</li>
	<li>For multiple fiber recordings, test for independence in signals.
	<ol>
		<li>Live record from all fibers.</li>
		<li>Point one fiber towards a light source and tap with a finger. Very large fluctuations should occur solely in that channel (acceptable leakage 1:1000).</li>
		<li>If the signals are not independent, redraw more conservative ROIs and repeat the independence test.</li>
	</ol>
	</li>
	<li>To label and keep track of which ROI corresponds to which fiber, colored tape or nail polish can be applied to the end of the fibers. Take a picture prior to the start of any experiment as a secondary reminder.</li>
</ol>
3. Setup of recording arena
<ol>
	<li>Hang the patch cord above the arena using stands, clamps, or holders.</li>
	<li>Make sure that the animal can freely move throughout the entire arena, uninhibited by the length of the fiber.</li>
	<li>Whether an operant box or open field is used, ensure that the patch cord will be able to reach the animal with minimal bending. If this requires a nose poke, ensure that there is enough room overhead to prevent bending of the fiber. Avoid any excessive bending or twisting of the patch cord.</li>
</ol>
4. In vivo recordings
NOTE: The procedure of optic fiber cannula implantation for fiber photometry experiments is identical to the procedure for optogenetics as described in Sparta et al15. We recommend using dental cement (see Table of Materials), which provides robust anchoring of the headcap to the skull bone. Dental cement will be particularly useful in cases where anchoring screws cannot be used.
<ol>
	<li>Visually inspect the distal end of the fibers of the patch cord by eye and with a minifiber microscope. If the surface of the fibers is scratched, repolish the fibers using fiber polishing/lapping film with fine grit (1 &#181;m and 0.3 &#181;m).</li>
	<li>Clean the distal ends of the patch cord with 70% ethanol and a cotton tip applicator.</li>
	<li>Clean the fiber-optic cannulas using 70% ethanol and a cotton tip applicator.</li>
	<li>Connect the ferrule end of the patch cord to the implanted fiber using a ceramic split-sleeve covered with a black shrink tube. During the connection, make sure that the sleeve is tight, otherwise use a new sleeve. 
	NOTE: There will be a large amount of signal loss if there is any space between the patch cord ferrule and the implant, and the recordings will not work.</li>
	<li>Allow the animal to recover for a few minutes prior to the start of behavioral testing.</li>
	<li>Start recording the optical signal and run the experiment.</li>
	<li>While recording, keep a careful eye on the live-trace to ensure quality recordings. The signal is expected to rapidly decrease as a function of time in the first 2 min of recording. This effect is caused by heat-mediated LED decay, whereby the increase in heat increases the resistance of the optical element.</li>
	<li>If a jump in the signal that exceeds the on/off kinetics of GCaMP occurs, this is often an indication that the sleeve is not tight enough and the space between the patch cord and the implant is changing. In this case, stop the experiment and reconnect the animal using a new sleeve.</li>
</ol>
5. Fiber photometry data analysis
NOTE: This is a method for data analysis that works well for most recordings. However, alternative approaches can be implemented. Example code for data analysis can be found here: https://github.com/katemartian/Photometry_data_processing.
<ol>
	<li>Extract mean fluorescence intensity values recorded from 470 nm (Int470) and 410 nm (Int410) LEDs, corresponding to each individual fiber.</li>
	<li>Smooth each signal using a moving mean algorithm (Figure 3A).</li>
	<li>Perform baseline correction of each signal (Figure 3A and 3B) using the adaptive iteratively reweighted Penalized Least Squares (airPLS) algorithm (https://github.com/zmzhang/airPLS) to remove the slope and low frequency fluctuations in signals.</li>
	<li>Standardize each signal using the mean value and standard deviation (Figure 3C): 
	<img alt="Equation 1" src="/files/ftp_upload/60278/60278equ01v2.jpg" /></li>
	<li>Using non-negative robust linear regression, fit standardized zInt410 to zInt470 signals (Figure 3D) to the regression function: 
	<img alt="Equation 2" src="/files/ftp_upload/60278/60278equ02v2.jpg" />
	<ol>
		<li>Use the parameters of the linear regression (a, b) to find new values of zInt410 fitted to zInt470 (fitInt410, Figure 3D,E): 
		<img alt="Equation 3" src="/files/ftp_upload/60278/60278equ03v2.jpg" /></li>
	</ol>
	</li>
	<li>Calculate the normalized dF/F (z dF/F) (Figure 3F): 
	<img alt="Equation 4" src="/files/ftp_upload/60278/60278equ04v2.jpg" /></li>
</ol>
6. Simultaneous dual-color recordings
<ol>
	<li>Add to the photometry system a 560 nm LED to excite the red fluorescent calcium sensor and appropriate dichroic mirrors and filters (see Kim et al., 2016 for detailed description)12.</li>
	<li>Add an image splitter between the objective and the CMOS camera to separate the green and red emission wavelengths (see Figure 5). The image splitter will form two mirrored images on the camera sensor, corresponding to the red and green signals (e.g., a patch cord with 3 branches will create an image with 6 fibers).</li>
	<li>Draw ROIs around all fibers in both colors as detailed above. Make sure to clearly identify each ROI with the corresponding fiber and channel (green and red) (Figure 4A).</li>
	<li>Trigger simultaneous excitation with 470 nm and 560 nm LEDs and alternate them with 410 nm LED (Figure 5A).</li>
</ol>
7. Dual color data analysis
<ol>
	<li>Follow the steps in Section 5 to find fitInt410 for the Int470 signal and calculate z dF/F.</li>
	<li>Because the isosbestic point for red-shifted GECIs is generally unknown, the signal recorded with 410 nm LED in the green channel can be used for movement correction across both channels. Follow the steps in Section 5 to find fitInt410 for the Int560 signal and calculate z dF/F.</li>
</ol>

<ol>
	<li>Gunaydin, L. A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Natural+Neural+Projection+Dynamics+Underlying+Social+Behavior.">Natural Neural Projection Dynamics Underlying Social Behavior.</a> Cell. 157 (7), 1535-1551 (2014).</li><li>Proulx, C. D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+neural+pathway+controlling+motivation+to+exert+effort.">A neural pathway controlling motivation to exert effort.</a> Proceedings of the National Academy of Sciences of the United States of America. 115 (22), 5792-5797 (2018).</li><li>Muir, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=In+Vivo+Fiber+Photometry+Reveals+Signature+of+Future+Stress+Susceptibility+in+Nucleus+Accumbens.">In Vivo Fiber Photometry Reveals Signature of Future Stress Susceptibility in Nucleus Accumbens.</a> Neuropsychopharmacology. 43 (2), 255-263 (2017).</li><li>Wang, D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Learning+shapes+the+aversion+and+reward+responses+of+lateral+habenula+neurons.">Learning shapes the aversion and reward responses of lateral habenula neurons.</a> eLife. 6, (2017).</li><li>de Jong, J. W., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+Neural+Circuit+Mechanism+for+Encoding+Aversive+Stimuli+in+the+Mesolimbic+Dopamine+System.">A Neural Circuit Mechanism for Encoding Aversive Stimuli in the Mesolimbic Dopamine System.</a> Neuron. 101 (1), 133-151 (2018).</li><li>Lerner, T. N., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Intact-Brain+Analyses+Reveal+Distinct+Information+Carried+by+SNc+Dopamine+Subcircuits.">Intact-Brain Analyses Reveal Distinct Information Carried by SNc Dopamine Subcircuits.</a> Cell. 162 (3), 635-647 (2015).</li><li>Calipari, E. S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=In+vivo+imaging+identifies+temporal+signature+of+D1+and+D2+medium+spiny+neurons+in+cocaine+reward.">In vivo imaging identifies temporal signature of D1 and D2 medium spiny neurons in cocaine reward.</a> Proceedings of the National Academy of Sciences of the United States of America. 113 (10), 2726-2731 (2016).</li><li>Gonz&#225;lez, A. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Inhibitory+Interplay+between+Orexin+Neurons+and+Eating.">Inhibitory Interplay between Orexin Neurons and Eating.</a> Current Biology. 26 (18), 2486-2491 (2016).</li><li>Chen, T. -. W., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Ultrasensitive+fluorescent+proteins+for+imaging+neuronal+activity.">Ultrasensitive fluorescent proteins for imaging neuronal activity.</a> Nature. 499 (7458), 295-300 (2013).</li><li>Barker, D. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Lateral+Preoptic+Control+of+the+Lateral+Habenula+through+Convergent+Glutamate+and+GABA+Transmission.">Lateral Preoptic Control of the Lateral Habenula through Convergent Glutamate and GABA Transmission.</a> Cell Reports. 21 (7), 1757-1769 (2017).</li><li>Siciliano, C. A., Tye, K. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Leveraging+calcium+imaging+to+illuminate+circuit+dysfunction+in+addiction.">Leveraging calcium imaging to illuminate circuit dysfunction in addiction.</a> Alcohol. 74, 47-63 (2018).</li><li>Kim, C. K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Simultaneous+fast+measurement+of+circuit+dynamics+at+multiple+sites+across+the+mammalian+brain.">Simultaneous fast measurement of circuit dynamics at multiple sites across the mammalian brain.</a> Nature Methods. 13 (4), 325-328 (2016).</li><li>Sych, Y., Chernysheva, M., Sumanovski, L. T., Helmchen, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High-density+multi-fiber+photometry+for+studying+large-scale+brain+circuit+dynamics.">High-density multi-fiber photometry for studying large-scale brain circuit dynamics.</a> Nature Methods. 16 (6), 553-560 (2019).</li><li>Akam, T., Walton, M. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=pyPhotometry:+Open+source+Python+based+hardware+and+software+for+fiber+photometry+data+acquisition.">pyPhotometry: Open source Python based hardware and software for fiber photometry data acquisition.</a> Scientific Reports. 9 (1), 3521 (2019).</li><li>Sparta, D. R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Construction+of+implantable+optical+fibers+for+long-term+optogenetic+manipulation+of+neural+circuits.">Construction of implantable optical fibers for long-term optogenetic manipulation of neural circuits.</a> Nature Protocol. 7 (1), 12-23 (2011).</li><li>Stamatakis, A. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Lateral+Hypothalamic+Area+Glutamatergic+Neurons+and+Their+Projections+to+the+Lateral+Habenula+Regulate+Feeding+and+Reward.">Lateral Hypothalamic Area Glutamatergic Neurons and Their Projections to the Lateral Habenula Regulate Feeding and Reward.</a> The Journal of Neuroscience. 36 (2), 302-311 (2016).</li><li>Tervo, G. D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+Designer+AAV+Variant+Permits+Efficient+Retrograde+Access+to+Projection+Neurons.">A Designer AAV Variant Permits Efficient Retrograde Access to Projection Neurons.</a> Neuron. 92 (2), 372-382 (2016).</li><li>Yu, K., da Silva, P., Albeanu, D. F., Li, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Central+Amygdala+Somatostatin+Neurons+Gate+Passive+and+Active+Defensive+Behaviors.">Central Amygdala Somatostatin Neurons Gate Passive and Active Defensive Behaviors.</a> The Journal of Neuroscience. 36 (24), 6488-6496 (2016).</li><li>Falkner, A. L., Grosenick, L., Davidson, T. J., Deisseroth, K., Lin, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Hypothalamic+control+of+male+aggression-seeking+behavior.">Hypothalamic control of male aggression-seeking behavior.</a> Nature Neuroscience. 19 (4), 596-604 (2016).</li><li>Ren, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Anatomically+Defined+and+Functionally+Distinct+Dorsal+Raphe+Serotonin+Sub-systems.">Anatomically Defined and Functionally Distinct Dorsal Raphe Serotonin Sub-systems.</a> Cell. 175 (2), 472-487 (2018).</li><li>Barnett, L. M., Hughes, T. E., Drobizhev, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Deciphering+the+molecular+mechanism+responsible+for+GCaMP6m&#8217;s+Ca2+-dependent+change+in+fluorescence.">Deciphering the molecular mechanism responsible for GCaMP6m&#8217;s Ca2+-dependent change in fluorescence.</a> PLOS ONE. 12 (2), 0170934 (2017).</li><li>Sun, F., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+Genetically+Encoded+Fluorescent+Sensor+Enables+Rapid+and+Specific+Detection+of+Dopamine+in+Flies,+Fish,+and+Mice.">A Genetically Encoded Fluorescent Sensor Enables Rapid and Specific Detection of Dopamine in Flies, Fish, and Mice.</a> Cell. 174 (2), 481-496 (2018).</li><li>Patriarchi, T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Ultrafast+neuronal+imaging+of+dopamine+dynamics+with+designed+genetically+encoded+sensors.">Ultrafast neuronal imaging of dopamine dynamics with designed genetically encoded sensors.</a> Science. 360 (6396), (2018).</li><li>Feng, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+Genetically+Encoded+Fluorescent+Sensor+for+Rapid+and+Specific+In+Detection+of+Norepinephrine.">A Genetically Encoded Fluorescent Sensor for Rapid and Specific In Detection of Norepinephrine.</a> Neuron. 102 (4), 745-761 (2019).</li><li>Akerboom, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Genetically+encoded+calcium+indicators+for+multi-color+neural+activity+imaging+and+combination+with+optogenetics.">Genetically encoded calcium indicators for multi-color neural activity imaging and combination with optogenetics.</a> Frontiers in Molecular Neuroscience. 6, 1-29 (2013).</li><li>Dana, H., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Sensitive+red+protein+calcium+indicators+for+imaging+neural+activity.">Sensitive red protein calcium indicators for imaging neural activity.</a> eLife. 5, (2016).</li><li>Wang, H., Jing, M., Li, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Lighting+up+the+brain:+genetically+encoded+fluorescent+sensors+for+imaging+neurotransmitters+and+neuromodulators.">Lighting up the brain: genetically encoded fluorescent sensors for imaging neurotransmitters and neuromodulators.</a> Current Opinion in Neurobiology. 50, 171-178 (2018).</li><li>Lu, L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Wireless+optoelectronic+photometers+for+monitoring+neuronal+dynamics+in+the+deep+brain.">Wireless optoelectronic photometers for monitoring neuronal dynamics in the deep brain.</a> Proceedings of the National Academy of Sciences. 115 (7), 1374-1383 (2018).</li><li>Jennings, J. H., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Visualizing+Hypothalamic+Network+Dynamics+for+Appetitive+and+Consummatory+Behaviors.">Visualizing Hypothalamic Network Dynamics for Appetitive and Consummatory Behaviors.</a> Cell. 160 (3), 516-527 (2014).</li></ol>

Sage Aronson is the CEO and founder of Neurophotometrics Ltd., which sells multi-fiber photometry systems.

Fiber photometry is an accessible approach that allows researchers to record bulk-calcium dynamics from defined neuronal populations in freely-moving animals. This method can be combined with a wide range of behavioral tests, including &#8220;movement heavy&#8221; tasks such as forced swim tests2, fear-conditioning18, social interactions1,4, and others7,8<su...

The ability to correlate neural responses with specific aspects of an animal&rsquo;s behavior is critical to understand the role a particular group of neurons plays in directing or responding to an action or stimulus. Given the complexity of animal behavior, with the myriad of internal states and external stimuli that can affect even the simplest of actions, recording a signal with single-trial resolution equips researchers with the necessary tools to overcome these limitations.
Fiber photometry has become the technique of choice for many researchers in the field of systems neuroscience because of its relative simplicity compared to other in vivo recording techniques, its high signal-to-noise ratio, and the ability to record in a variety of behavioral paradigms1,2,3,4,5,6,7,8. Unlike traditional electrophysiological methods, photometry is the optical approach most commonly used in conjunction with genetically-encoded calcium indicators (GECIs, the GCaMP series)9. GECIs change their ability to fluoresce based on whether or not they are bound to calcium. Because the internal concentration of calcium in neurons is very tightly regulated and voltage-gated calcium channels open when a neuron fires an action potential, transient increases in internal calcium concentration, which result in transient increases in the ability of a GECI to fluorescence, can be a good proxy for neuronal firing9.
With fiber photometry, excitation light is directed down a thin, multimode optic fiber into the brain, and an emission signal is collected back up through the same fiber. Because these optic fibers are lightweight and bendable, an animal can move largely unhindered, making this technique compatible with a wide array of behavioral tests and conditions. Some conditions, such as rapid movements or bending of the fiber-optic patch cord beyond the radius at which it can maintain total internal reflection, can introduce signal artifacts. To disambiguate signal from noise, we can exploit a property of GCaMP known as the &ldquo;isosbestic point.&rdquo; Briefly, with GCaMP, as the wavelength of the excitation light is shifted to the left, its emission in the calcium-bound state decreases and the emission in the calcium-unbound state marginally increases. The point at which the relative intensity of these two emissions are equal is termed the isosbestic point. When GCaMP is excited at this point, its emission is unaffected by changes in internal calcium concentrations, and variance in the signal is most often due to attenuation of the signal from overbending of the fiber-optic patch cord or movement of the neural tissue relative to the implanted fiber.
Single unit electrophysiology is still the gold standard for freely-moving in vivo recordings due to its single-cell and single-spike level resolution. However, it can be difficult to pinpoint the molecular identity of the cells being recorded, and the post-hoc analysis can be quite laborious. While fiber photometry does not have single-cell resolution, it does allow researchers to ask questions impossible to address with traditional techniques. Combining viral strategies with transgenic animals, the expression of GECIs can be directed to genetically-defined neuronal types to record population- or projection-defined neural activity, which can be performed by monitoring calcium signal directly at axon terminals10,11. Moreover, by implanting multiple fiber-optic cannulas, it is possible to simultaneously monitor neural activity from several brain regions and pathways in the same animal12,13.
In this manuscript, we describe a technique for single and multi-fiber photometry, how to correct for calcium-independent artifacts, and detail how to perform mono- and dual-color recordings. We also provide examples of the types of questions it enables one to ask and their increasing levels of complexity (see Figure 1). The fiber photometry setup for multi-fiber recordings detailed in this protocol can be built using a list of materials found at https://sites.google.com/view/multifp/hardware (Figure 2).
It is essential that the system be equipped for both 410 nm and 470 nm excitation wavelengths for calcium-independent and calcium-dependent fluorescence emission from GCaMP6 or its variants. For custom-built setups or if there is no available software to run the system, the free, open source program Bonsai (http://www.open-ephys.org/bonsai/) can be used. Alternatively, fiber photometry can be run through MATLAB (e.g., https://github.com/deisseroth-lab/multifiber)12 or other programming language14. The software and hardware of the system should allow manipulation of both the 410 nm and 470 nm LEDs and the camera, extraction of images (Figure 2), and calculation of the mean fluorescent intensity in the regions of interest (ROIs) drawn around the fibers on the images. The output should be a table of mean intensity values recorded with the 470 nm and 410 nm LEDs from each fiber in the patch cord. When performing multi-fiber experiments, 400 &micro;m bundled fibers may limit the movement of mice. In such cases, we recommend using 200 &micro;m patch cords, which provide more flexibility. It may also be possible to use smaller dummy cables during training of mice.
It is crucial to be able to extract time points for events of interest during fiber photometry acquisition. If the system does not readily provide a built-in system to integrate TTLs for specific events, an alternative strategy is to assign a time stamp to individual time points recorded to align with specific times and events during the experiment. Time stamping can be done using the computer clock.

<table>
	<tbody>
		<tr>
			<td>1/4&#34;-20 Stainless Steel Cap Screw, 1&#34; Long</td>
			<td>Thorlabs</td>
			<td>SH25S100</td>
			<td></td>
		</tr>
		<tr>
			<td>1/4&#34;-20 Stainless Steel Cap Screw, 1/2&#34; Long</td>
			<td>Thorlabs</td>
			<td>SH25S050</td>
			<td></td>
		</tr>
		<tr>
			<td>1/4&#34;-20 Stainless Steel Cap Screw, 3/8&#34; Long</td>
			<td>Thorlabs</td>
			<td>SH25S038</td>
			<td></td>
		</tr>
		<tr>
			<td>1000 &#181;m, 0.50 NA, SMA-SMA Fiber Patch Cable</td>
			<td>Thorlabs</td>
			<td>M59L01</td>
			<td></td>
		</tr>
		<tr>
			<td>12.7 mm Optical Post</td>
			<td>Thorlabs</td>
			<td>TR30/M</td>
			<td></td>
		</tr>
		<tr>
			<td>12.7 mm Pedestal Post Holder</td>
			<td>Thorlabs</td>
			<td>PH20EM</td>
			<td></td>
		</tr>
		<tr>
			<td>15 V, 2.4 A Power Supply Unit with 3.5 mm Jack Connector for T-Cube</td>
			<td>Thorlabs</td>
			<td>KPS101</td>
			<td></td>
		</tr>
		<tr>
			<td>20x objective</td>
			<td>Thorlabs</td>
			<td>RMS20X</td>
			<td>#10 in Figure 2, #11 in Figure 5</td>
		</tr>
		<tr>
			<td>30 mm Cage Cube with Dichroic Filter Mount</td>
			<td>Thorlabs</td>
			<td>CM1-DCH/M</td>
			<td>#8-9 in Figure 2, #8-10 in Figure 5</td>
		</tr>
		<tr>
			<td>405 nm LED</td>
			<td>Doric Lenses</td>
			<td>CLED_405</td>
			<td>#2 in Figure 2</td>
		</tr>
		<tr>
			<td>410 nm bandpass filter</td>
			<td>Thorlabs</td>
			<td>FB410-10</td>
			<td>#5 in Figure 2; #7 in Figure 5</td>
		</tr>
		<tr>
			<td>465 nm. LED</td>
			<td>Doric Lenses</td>
			<td>CLED_465</td>
			<td>#1 in Figure 2</td>
		</tr>
		<tr>
			<td>470 nm bandpass filter</td>
			<td>Thorlabs</td>
			<td>FB470-10</td>
			<td>#4 in Figure 2; #6 in Figure 5</td>
		</tr>
		<tr>
			<td>560 nm bandpass filter</td>
			<td>Semrock</td>
			<td>FF01-560/14-25</td>
			<td>#5 in Figure 5</td>
		</tr>
		<tr>
			<td>560 nm LED</td>
			<td>Doric Lenses</td>
			<td>CLED_560</td>
			<td>#1 in Figure 3</td>
		</tr>
		<tr>
			<td>5-axis kinematic Mount</td>
			<td>Thorlabs</td>
			<td>K5X1</td>
			<td>#11 in Figure 2, #12 in Figure 5</td>
		</tr>
		<tr>
			<td>Achromatic Doublet</td>
			<td>Thorlabs</td>
			<td>AC254-035-A-ML</td>
			<td>#7 in Figure 2</td>
		</tr>
		<tr>
			<td>Adaptor for 405 collimator</td>
			<td>Thorlabs</td>
			<td>AD11F</td>
			<td>#3 in Figure 2; #4 in Figure 5</td>
		</tr>
		<tr>
			<td>Adaptor for ajustable collimator</td>
			<td>Thorlabs</td>
			<td>AD127-F</td>
			<td>#3 in Figure 2; #4 in Figure 5</td>
		</tr>
		<tr>
			<td>Aluminum Breadboard</td>
			<td>Thorlabs</td>
			<td>MB1824</td>
			<td></td>
		</tr>
		<tr>
			<td>Clamping Fork</td>
			<td>Thorlabs</td>
			<td>CF125</td>
			<td></td>
		</tr>
		<tr>
			<td>Cube connector</td>
			<td>Thorlabs</td>
			<td>CM1-CC</td>
			<td></td>
		</tr>
		<tr>
			<td>Dual 493/574 dichroic</td>
			<td>Semrock</td>
			<td>FF493/574-Di01-25x36</td>
			<td>#10 in Figure 5</td>
		</tr>
		<tr>
			<td>Emission filter for GCaMP6</td>
			<td>Semrock</td>
			<td>FF01-535/22-25</td>
			<td>#6 in Figure 2</td>
		</tr>
		<tr>
			<td>Enclosure with Black Hardboard Panels</td>
			<td>Thorlabs</td>
			<td>XE25C9</td>
			<td></td>
		</tr>
		<tr>
			<td>Externally SM1-Threaded End Cap for Machining</td>
			<td>Thorlabs</td>
			<td>SM1CP2M</td>
			<td></td>
		</tr>
		<tr>
			<td>Fast-change SM1 Lens Tube Filter Holder</td>
			<td>Thorlabs</td>
			<td>SM1QP</td>
			<td>#4-6 in Figure 2, #5-7 in Figure 5</td>
		</tr>
		<tr>
			<td>Fixed Collimator for 405 nm light</td>
			<td>Thorlabs</td>
			<td>F671SMA-405</td>
			<td>#3 in Figure 2; #4 in Figure 5</td>
		</tr>
		<tr>
			<td>Fixed collimator for 470 and 560 nm light</td>
			<td>Thorlabs</td>
			<td>F240SMA-532</td>
			<td>#3 in Figure 2; #4 in Figure 5</td>
		</tr>
		<tr>
			<td>Green emission filter</td>
			<td>Semrock</td>
			<td>FF01-520/35-25</td>
			<td>In light beam splitter</td>
		</tr>
		<tr>
			<td>High-Resolution USB 3.0 CMOS Camera</td>
			<td>Thorlabs</td>
			<td>DCC3260M</td>
			<td>#13 in Figure 2, #15 in Figure 5</td>
		</tr>
		<tr>
			<td>Light beam splitter</td>
			<td>Neurophotometrics</td>
			<td>SPLIT</td>
			<td>#14 in Figure 5</td>
		</tr>
		<tr>
			<td>Longpass Dichroic Mirror, 425 nm Cutoff</td>
			<td>Thorlabs</td>
			<td>DMLP425R</td>
			<td>#8 in Figure 2, #9 in Figure 5</td>
		</tr>
		<tr>
			<td>Longpass Dichroic Mirror, 495 nm Cutoff</td>
			<td>Semrock</td>
			<td>FF495-Di03</td>
			<td>#9 in Figure 2, #8 in Figure 5</td>
		</tr>
		<tr>
			<td>Metabond dental cement</td>
			<td>C&#38;B</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>M8 - M8 cable</td>
			<td>Doric Lenses</td>
			<td>Cable_M8-M8</td>
			<td></td>
		</tr>
		<tr>
			<td>Optic fiber cannulas</td>
			<td>Doric Lenses</td>
			<td></td>
			<td>Need to specify that these will be used to photometry experiments requiring low autofluorescence</td>
		</tr>
		<tr>
			<td>Optic fiber Patchcords</td>
			<td>Doric Lenses</td>
			<td></td>
			<td>Need to specify that these will be used to photometry experiments requiring low autofluorescence</td>
		</tr>
		<tr>
			<td>Red emission filter</td>
			<td>Semrock</td>
			<td>FF01-600/37-25</td>
			<td>In light beam splitter</td>
		</tr>
		<tr>
			<td>T7 LabJack</td>
			<td>LabJack</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>T-cube LED Driver</td>
			<td>Thorlabs</td>
			<td>LEDD1B</td>
			<td></td>
		</tr>
		<tr>
			<td>USB 3.0 I/O Cable, Hirose 25, for DCC3240</td>
			<td>Thorlabs</td>
			<td>CAB-DCU-T3</td>
			<td></td>
		</tr>
	</tbody>
</table>

multi-fiber photometry to record neural activity in freely-moving animals

Recording the activity of a group of neurons in a freely-moving animal is a challenging undertaking. Moreover, as the brain is dissected into smaller and smaller functional subgroups, it becomes paramount to record from projections and/or genetically-defined subpopulations of neurons. Fiber photometry is an accessible and powerful approach that can overcome these challenges. By combining optical and genetic methodologies, neural activity can be measured in deep brain structures by expressing genetically-encoded calcium indicators, which translate neural activity into an optical signal that can be easily measured. The current protocol details the components of a multi-fiber photometry system, how to access deep brain structures to deliver and collect light, a method to account for motion artifacts, and how to process and analyze fluorescent signals. The protocol details experimental considerations when performing single and dual color imaging, from either single or multiple implanted optic fibers.

Neural correlates of behavioral responses can vary depending on a variety of factors. In this example, we used in vivo fiber photometry to measure the activity of axon terminals from the lateral hypothalamic area (LHA) that terminate in the lateral habenula (LHb). Wild type mice were injected with an adeno-associated virus (AAV) encoding GCaMP6s (AAV-hSyn-GCaMP6s) in the LHA and an optic fiber was implanted with the tip immediately above the LHb (Figure 4A). GCaMP6s expressi...

Watch this Scientific Journal Video about Multi-Fiber Photometry to Record Neural Activity in Freely-Moving Animals at JoVE.com

Multi-Fiber Photometry to Record Neural Activity in Freely-Moving Animals

This protocol details how to implement and perform multi-fiber photometry recordings, how to correct for calcium-independent artifacts, and important considerations for dual-color photometry imaging.

Recording the activity of a group of neurons in a freely-moving animal is a challenging undertaking. Moreover, as the brain is dissected into smaller and ...

multi-fiber-photometry-to-record-neural-activity-freely-moving

Universidad de Cartagena UDEC

Research

JoVE Journal

Neuroscience

35.6K Views.  Université Laval. This protocol details how to implement and perform multi-fiber photometry recordings, how to correct for calcium-independent artifacts, and important considerations for dual-color photometry imaging.

Video: Multi-Fiber Photometry to Record Neural Activity in Freely-Moving Animals

Electrode Fabrication and Implantation in Aplysia californica for Multi-channel Neural and Muscular Recordings in Intact, Freely Behaving Animals

Recording from key nerves and muscles of Aplysia during feeding behavior allows us to study the patterns of neural control in an intact animal. Simultaneously recording from multiple nerves and muscles gives us precise information about the timing of neural activity. Previous recording methods have worked for two electrodes, but the study of additional nerves or muscles required combining and averaging the recordings of multiple animals, which made it difficult to determine fine details of timing and phasing, because of variability from response to response, and from animal to animal. Implanting four individual electrodes has a very low success rate due to the formation of adhesions that prevent animals from performing normal feeding movements. We developed a new method of electrode fabrication that reduces the bulk of the electrodes inside the animal allowing for normal feeding movements. Using a combination of glues to attach the electrodes results in a more reliable insulation of the electrode which lasts longer, making it possible to record for periods as long as a week. The fabrication technique that we describe could be extended to incorporate several additional electrodes, and would be applicable to vertebrate animals.

Electrode Fabrication and Implantation in Aplysia californica for Multi-channel Neural and Muscular Recordings in Intact, Freely Behaving Animals

A technique is described for implanting four in vivo electrodes to monitor the neuromuscular control of feeding behavior in Aplysia californica.

Recording from key nerves and muscles of Aplysia during feeding behavior allows us to study the patterns of neural control in an intact animal.  ...

High-density EEG Recordings of the Freely Moving Mice using Polyimide-based Microelectrode

Electroencephalogram (EEG) indicates the averaged electrical activity of the neuronal populations on a large-scale level. It is widely utilized as a noninvasive brain monitoring tool in cognitive neuroscience as well as a diagnostic tool for epilepsy and sleep disorders in neurology. However, the underlying mechanism of EEG rhythm generation is still under the veil. Recently introduced polyimide-based microelectrode (PBM-array) for high resolution mouse EEG1 is one of the trials to answer the neurophysiological questions on EEG signals based on a rich genetic resource that the mouse model contains for the analysis of complex EEG generation process. This application of nanofabricated PBM-array to mouse skull is an efficient tool for collecting large-scale brain activity of transgenic mice and accommodates to identify the neural correlates to certain EEG rhythms in conjunction with behavior. However its ultra-thin thickness and bifurcated structure cause a trouble in handling and implantation of PBM-array. In the presented video, the preparation and surgery steps for the implantation of PBM-array on a mouse skull are described step by step. Handling and surgery tips to help researchers succeed in implantation are also provided.

In this article, we described the surgery procedure and handling tips for implantation of ultra-thin polyimide-based microelectrode array (PBM-array) on the mouse skull for acquisition of high-density encephalography (EEG) in a mouse model.

Electroencephalogram (EEG) indicates the averaged electrical activity of the neuronal populations on a large-scale level. It is widely utilized as a ...

Design and Assembly of an Ultra-light Motorized Microdrive for Chronic Neural Recordings in Small Animals

The ability to chronically record from populations of neurons in freely behaving animals has proven an invaluable tool for dissecting the function of neural circuits underlying a variety of natural behaviors, including navigation1 , decision making 2,3, and the generation of complex motor sequences4,5,6. Advances in precision machining has allowed for the fabrication of light-weight devices suitable for chronic recordings in small animals, such as mice and songbirds. The ability to adjust the electrode position with small remotely controlled motors has further increased the recording yield in various behavioral contexts by reducing animal handling.6,7
 Here we describe a protocol to build an ultra-light motorized microdrive for long-term chronic recordings in small animals. Our design evolved from an earlier published version7, and has been adapted for ease-of use and cost-effectiveness to be more practical and accessible to a wide array of researchers. This proven design 8,9,10,11 allows for fine, remote positioning of electrodes over a range of ~ 5 mm and weighs less than 750 mg when fully assembled. We present the complete protocol for how to build and assemble these drives, including 3D CAD drawings for all custom microdrive components.

The design, fabrication and assembly of an ultra-light motorized microdrive is described. The device provides a cost-effective and easy-to-use solution for chronic recordings of single units in small behaving animals.

The ability to chronically record from populations of neurons in freely behaving animals has proven an invaluable tool for dissecting the function of ...

Multi-unit Recording Methods to Characterize Neural Activity in the Locust (Schistocerca Americana) Olfactory Circuits

Detection and interpretation of olfactory cues are critical for the survival of many organisms. Remarkably, species across phyla have strikingly similar olfactory systems suggesting that the biological approach to chemical sensing has been optimized over evolutionary time1. In the insect olfactory system, odorants are transduced by olfactory receptor neurons (ORN) in the antenna, which convert chemical stimuli into trains of action potentials. Sensory input from the ORNs is then relayed to the antennal lobe (AL; a structure analogous to the vertebrate olfactory bulb). In the AL, neural representations for odors take the form of spatiotemporal firing patterns distributed across ensembles of principal neurons (PNs; also referred to as projection neurons)2,3. The AL output is subsequently processed by Kenyon cells (KCs) in the downstream mushroom body (MB), a structure associated with olfactory memory and learning4,5. Here, we present electrophysiological recording techniques to monitor odor-evoked neural responses in these olfactory circuits.
First, we present a single sensillum recording method to study odor-evoked responses at the level of populations of ORNs6,7. We discuss the use of saline filled sharpened glass pipettes as electrodes to extracellularly monitor ORN responses. Next, we present a method to extracellularly monitor PN responses using a commercial 16-channel electrode3. A similar approach using a custom-made 8-channel twisted wire tetrode is demonstrated for Kenyon cell recordings8. We provide details of our experimental setup and present representative recording traces for each of these techniques.

Multi-unit Recording Methods to Characterize Neural Activity in the Locust Schistocerca Americana Olfactory Circuits

We demonstrate variations of the extracellular multi-unit recording technique to characterize odor-evoked responses in the first three stages of the invertebrate olfactory pathway. These techniques can easily be adapted to examine ensemble activity in other neural systems as well.

Detection and interpretation of olfactory cues are critical for the survival  of many organisms. Remarkably, species across phyla have strikingly similar ...

Recording Single Neurons' Action Potentials from Freely Moving Pigeons Across Three Stages of Learning

While the subject of learning has attracted immense interest from both behavioral and neural scientists, only relatively few investigators have observed single-neuron activity while animals are acquiring an operantly conditioned response, or when that response is extinguished. But even in these cases, observation periods usually encompass only a single stage of learning, i.e. acquisition or extinction, but not both (exceptions include protocols employing reversal learning; see Bingman&#160;et al.1 for an example). However, acquisition and extinction entail different learning mechanisms and are therefore expected to be accompanied by different types and/or loci of neural plasticity.
Accordingly, we developed a behavioral paradigm which institutes three stages of learning in a single behavioral session and which is well suited for the simultaneous recording of single neurons&#39; action potentials. Animals are trained on a single-interval forced choice task which requires mapping each of two possible choice responses to the presentation of different novel visual stimuli (acquisition). After having reached a predefined performance criterion, one of the two choice responses is no longer reinforced (extinction). Following a certain decrement in performance level, correct responses are reinforced again (reacquisition). By using a new set of stimuli in every session, animals can undergo the acquisition-extinction-reacquisition process repeatedly. Because all three stages of learning occur in a single behavioral session, the paradigm is ideal for the simultaneous observation of the spiking output of multiple single neurons. We use pigeons as model systems, but the task can easily be adapted to any other species capable of conditioned discrimination learning.

Learning new stimulus-response associations engages a wide range of neural processes which are ultimately reflected in changing spike output of individual neurons. Here we describe a behavioral protocol allowing for the continuous registration of single-neuron activity while animals acquire, extinguish, and reacquire a conditioned response within a single experimental session.

While the subject of learning has attracted immense interest from both behavioral and neural scientists, only relatively few investigators have observed ...

Neural Activity Propagation in an Unfolded Hippocampal Preparation with a Penetrating Micro-electrode Array

This protocol describes a method for preparing a new in vitro flat hippocampus preparation combined with a micro-machined array to map neural activity in the hippocampus. The transverse hippocampal slice preparation is the most common tissue preparation to study hippocampus electrophysiology. A longitudinal hippocampal slice was also developed in order to investigate longitudinal connections in the hippocampus. The intact mouse hippocampus can also be maintained in vitro because its thickness allows adequate oxygen diffusion. However, these three preparations do not provide direct access to neural propagation since some of the tissue is either missing or folded. The unfolded intact hippocampus provides both transverse and longitudinal connections in a flat configuration for direct access to the tissue to analyze the full extent of signal propagation in the hippocampus in vitro. In order to effectively monitor the neural activity from the cell layer, a custom made penetrating micro-electrode array (PMEA) was fabricated and applied to the unfolded hippocampus. The PMEA with 64 electrodes of 200 &#181;m in height could record neural activity deep inside the mouse hippocampus. The unique combination of an unfolded hippocampal preparation and the PMEA provides a new in-vitro tool to study the speed and direction of propagation of neural activity in the two-dimensional CA1-CA3 regions of the hippocampus with a high signal to noise ratio.

We have developed an in vitro unfolded hippocampus which preserves CA1-CA3 array of neurons. Combined with the penetrating micro-electrode array, neural activity can be monitored in both the longitudinal and transverse orientations. This method provides advantages over hippocampal slice preparations as the propagation in the entire hippocampus can be recorded simultaneously.

This protocol describes a method for preparing a new in vitro flat hippocampus preparation combined with a micro-machined array to map neural activity in ...

A Novel Behavioral Assay to Investigate Gustatory Responses of Individual, Freely-moving Bumble Bees (Bombus terrestris)

Generalist pollinators like the buff-tailed bumble bee, Bombus terrestris, encounter both nutrients and toxins in the floral nectar they collect from flowering plants. Only a few studies have described the gustatory responses of bees toward toxins in food, and these experiments have mainly used the proboscis extension response on restrained honey bees. Here, a new behavioral assay is presented for measuring the feeding responses of freely-moving, individual worker bumble bees to nutrients and toxins. This assay measures the amount of solution ingested by each bumble bee and identifies how tastants in food influence the microstructure of the feeding behavior.
The solutions are presented in a microcapillary tube to individual bumble bees that have been previously starved for 2-4 hr. The behavior is captured on digital video. The fine structure of the feeding behavior is analyzed by continuously scoring the position of the proboscis (mouthparts) from video recordings using event logging software. The position of the proboscis is defined by three different behavioral categories: (1) proboscis is extended and in contact with the solution, (2) proboscis is extended but not in contact with the solution and (3) proboscis is stowed under the head. Furthermore the speed of the proboscis retracting away from the solution is also estimated.
In the present assay the volume of solution consumed, the number of feeding bouts, the duration of the feeding bouts and the speed of the proboscis retraction after the first contact is used to evaluate the phagostimulatory or the deterrent activity of the compounds tested.
This new taste assay will allow researchers to measure how compounds found in nectar influence the feeding behavior of bees and will also be useful to pollination biologists, toxicologists and neuroethologists studying the bumble bee&#39;s taste system.

A Novel Behavioral Assay to Investigate Gustatory Responses of Individual, Freely-moving Bumble Bees Bombus terrestris

A novel behavioral assay is described for investigating the short term gustatory responses of the mouthparts of freely-moving bumble bees (Bombus terrestris) toward nutrients and toxins in solution.

Generalist pollinators like the buff-tailed bumble bee, Bombus terrestris, encounter both nutrients and toxins in the floral nectar they collect from ...

Recording EEG in Freely Moving Neonatal Rats Using a Novel Method

EEG is a useful method to detect electrical activity in the brain. Moreover, it is a widely used diagnostic tool for various neurological conditions, such as epilepsy and neurodegenerative disorders. However, it is technically difficult to obtain EEG recordings in neonates as it requires specialized handling and great care. Here, we present a novel method to record EEG in neonatal rat pups (P8-P15). We designed a simple and reliable electrode using computer pin loci; it can be easily implanted into the skull of a rat pup to record high-quality EEG signals in the normal and epileptic brain. Pups were given an intraperitoneal (i.p.) injection of the neurotoxin kainic acid (KA) to induce epileptic seizures. The surgical implantation performed in this procedure is less expensive than other EEG procedures for neonates. This method allows one to record high-quality and stable EEG signals for more than 1 week. Furthermore, this procedure can also be applied to adult rats and mice to study epilepsy or other neurological disorders.

Here, we introduce a novel technique designed to record electroencephalography (EEG) in freely moving neonatal epileptic pups and describe its procedures, features, and applications. This method allows one to record EEG for more than 1 week.

EEG is a useful method to detect electrical activity in the brain. Moreover, it is a widely used diagnostic tool for various neurological conditions, such ...

Time-dependent Increase in the Network Response to the Stimulation of Neuronal Cell Cultures on Micro-electrode Arrays

Micro-electrode arrays (MEAs) can be used to investigate drug toxicity, design paradigms for next-generation personalized medicine, and study network dynamics in neuronal cultures. In contrast with more traditional methods, such as patch-clamping, which can only record activity from a single cell, MEAs can record simultaneously from multiple sites in a network, without requiring the arduous task of placing each electrode individually. Moreover, numerous control and stimulation configurations can be easily applied within the same experimental setup, allowing for a broad range of dynamics to be explored. One of the key dynamics of interest in these in vitro studies has been the extent to which cultured networks display properties indicative of learning. Mouse neuronal cells cultured on MEAs display an increase in response following training induced by electrical stimulation. This protocol demonstrates how to culture neuronal cells on MEAs; successfully record from over 95% of the plated dishes; establish a protocol to train the networks to respond to patterns of stimulation; and sort, plot, and interpret the results from such experiments. The use of a proprietary system for stimulating and recording neuronal cultures is demonstrated. Software packages are also used to sort neuronal units. A custom-designed graphical user interface is used to visualize post-stimulus time histograms, inter-burst intervals, and burst duration, as well as to compare the cellular response to stimulation before and after a training protocol. Finally, representative results and future directions of this research effort are discussed.

Mouse neuronal cells cultured on multi-electrode arrays display an increase in response following electrical stimulation. This protocol demonstrates how to culture neurons, how to record activity, and how to establish a protocol to train the networks to respond to patterns of stimulation.

Micro-electrode arrays (MEAs) can be used to investigate drug toxicity, design paradigms for next-generation personalized medicine, and study network ...

Simultaneous Recordings of Cortical Local Field Potentials, Electrocardiogram, Electromyogram, and Breathing Rhythm from a Freely Moving Rat

Monitoring the physiological dynamics of the brain and peripheral tissues is necessary for addressing a number of questions about how the brain controls body functions and internal organ rhythms when animals are exposed to emotional challenges and changes in their living environments. In general experiments, signals from different organs, such as the brain and the heart, are recorded by independent recording systems that require multiple recording devices and different procedures for processing the data files. This study describes a new method that can simultaneously monitor electrical biosignals, including tens of local field potentials in multiple brain regions, electrocardiograms that represent the cardiac rhythm, electromyograms that represent awake/sleep-related muscle contraction, and breathing signals, in a freely moving rat. The recording configuration of this method is based on a conventional micro-drive array for cortical local field potential recordings in which tens of electrodes are accommodated, and the signals obtained from these electrodes are integrated into a single electrical board mounted on the animal's head. Here, this recording system was improved so that signals from the peripheral organs are also transferred to an electrical interface board. In a single surgery, electrodes are first separately implanted into the appropriate body parts and the target brain areas. The open ends of all of these electrodes are then soldered to individual channels of the electrical board above the animal's head so that all of the signals can be integrated into the single electrical board. Connecting this board to a recording device allows for the collection of all of the signals into a single device, which reduces experimental costs and simplifies data processing, because all data can be handled in the same data file. This technique will aid the understanding of the neurophysiological correlates of the associations between central and peripheral organs.

This study introduces a method for the simultaneous recording of local field potentials in the brain, electrocardiograms, electromyograms, and breathing signals of a freely moving rat. This technique, which reduces experimental costs and simplifies data analysis, will contribute to the understanding of the interactions between the brain and peripheral organs.

Monitoring the physiological dynamics of the brain and peripheral tissues is necessary for addressing a number of questions about how the brain controls ...

Multi-Fiber Photometry to Record Neural Activity in Freely-Moving Animals

Summary

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Chapters in this video

Electrode Fabrication and Implantation in Aplysia californica for Multi-channel Neural and Muscular Recordings in Intact, Freely Behaving Animals

High-density EEG Recordings of the Freely Moving Mice using Polyimide-based Microelectrode

Design and Assembly of an Ultra-light Motorized Microdrive for Chronic Neural Recordings in Small Animals

Multi-unit Recording Methods to Characterize Neural Activity in the Locust (Schistocerca Americana) Olfactory Circuits

Recording Single Neurons' Action Potentials from Freely Moving Pigeons Across Three Stages of Learning

Neural Activity Propagation in an Unfolded Hippocampal Preparation with a Penetrating Micro-electrode Array

A Novel Behavioral Assay to Investigate Gustatory Responses of Individual, Freely-moving Bumble Bees (Bombus terrestris)

Recording EEG in Freely Moving Neonatal Rats Using a Novel Method

Time-dependent Increase in the Network Response to the Stimulation of Neuronal Cell Cultures on Micro-electrode Arrays

Simultaneous Recordings of Cortical Local Field Potentials, Electrocardiogram, Electromyogram, and Breathing Rhythm from a Freely Moving Rat