Brain Primer

Measuring Neural Physiology

  • Reviewed27 Feb 2023
  • Author Susan Rojahn
  • Source BrainFacts/SfN
Person laying down for medical procedure
Shutterstock.com via Roman Zaiets

Brains act as centralization hubs that process and govern everything we experience and do. To do this is no easy feat, and we are steadily coming to better understand how we carry out this major undertaking.

Information is conveyed along the neuronal pathways that crisscross through our brains as electrical activity traveling down axons. To study this activity, researchers measure changes in the electrical charge of individual neurons using techniques of electrophysiology. A thin glass electrode is placed inside a neuron to measure the voltage across its cell membrane, which changes when the neuron is activated. This technique can measure neuronal activity inside the brains of living lab animals such as rats or mice, enabling scientists to study how neurons transmit electrical information in their normal physical context. Alternatively, a slice of brain can be kept “alive” for a short time in a Petri dish, if the right environment (temperature, pH, ion concentrations, etc.) is provided. In an isolated brain slice, researchers can better identify the exact cell they are recording from and can infuse drugs into the Petri dish to determine their effects on the brain.

Using these methods, scientists have made critical discoveries about synaptic plasticity — the capacity of a synapse to become stronger or weaker in response to sensory inputs or other activity. For example, repeatedly stimulating a neuron by training an animal in a particular task, or by direct electrical stimulation, increases the synaptic strength and the chance that the downstream neuron will react to the incoming signal.

A disadvantage of electrophysiology, as described above, is that the techniques are highly invasive. However, another method, called electroencephalography or EEG, is able to record human brain activity without invasive or harmful procedures. In EEG, about 20 thin metal discs are placed on the scalp. Each disk is connected by thin wires to a machine that records the activity of neurons near the brain surface. This approach has been especially useful for understanding epilepsy and the stages of sleep. However, it does not provide information at the level of individual neurons.

Researchers who need to look at individual neurons in a living brain can use a technique called two-photon microscopy. A lab animal such as a fly or mouse must be genetically modified so that some of its neurons produce a protein that glows when a laser beam shines on them. Two-photon microscopy has enabled scientists to understand changes in the brain during normal processes like learning, as well as changes that occur over the course of a disease — for example, watching how the branches on neurons near Alzheimer’s-like plaques break down over time.


 Adapted from the 8th edition of Brain Facts by Susan Rojahn.

CONTENT PROVIDED BY

BrainFacts/SfN

Bao, W., Jia, H., Finnema, S., Cai, Z., Carson, R. E., & Huang, Y. H. (2017). PET Imaging for Early Detection of Alzheimer's Disease: From Pathologic to Physiologic Biomarkers. PET clinics, 12(3), 329–350. https://doi.org/10.1016/j.cpet.2017.03.001 

Berman, M. G., Jonides, J., & Nee, D. E. (2006). Studying Mind and Brain with fMRI. Social cognitive and affective neuroscience, 1(2), 158–161. https://doi.org/10.1093/scan/nsl019 

Bögershausen, N., & Wollnik, B. (2013). Unmasking Kabuki syndrome. Clinical genetics, 83(3), 201–211. https://doi.org/10.1111/cge.12051 

Boyden E. S. (2015). Optogenetics and the Future of Neuroscience. Nature neuroscience, 18(9), 1200–1201. https://doi.org/10.1038/nn.4094 

Caraci, F., Leggio, G. M., Salomone, S., & Drago, F. (2017). New Drugs in Psychiatry: Focus on New Pharmacological Targets. F1000Research, 6, 397. https://doi.org/10.12688/f1000research.10233.1 

Carter M. and Shieh J. C. (2015). Guide to Research Techniques in Neuroscience. Academic Press. p 164.

Carter N. P. (2007). Methods and Strategies for Analyzing Copy Number Variation Using DNA Microarrays. Nature genetics, 39(7 Suppl), S16–S21. https://doi.org/10.1038/ng2028 

Chefer, V. I., Thompson, A. C., Zapata, A., & Shippenberg, T. S. (2009). Overview of Brain Microdialysis. Current protocols in neuroscience, Chapter 7, Unit 7.1. https://doi.org/10.1002/0471142301.ns0701s47 

Clancy, S. (2008). Copy Number Variation. Nature Education, 1(1):95. https://www.nature.com/scitable/topicpage/copy-number-variation-445/ 

Cohen M. X. (2017). Where Does EEG Come From and What Does It Mean?. Trends in neurosciences, 40(4), 208–218. https://doi.org/10.1016/j.tins.2017.02.004 

Courtney, K. E., & Ray, L. A. (2014). Methamphetamine: An Update on Epidemiology, Pharmacology, Clinical Phenomenology, and Treatment Literature. Drug and alcohol dependence, 143, 11–21. https://doi.org/10.1016/j.drugalcdep.2014.08.003

Cui, X., Bray, S., Bryant, D. M., Glover, G. H., & Reiss, A. L. (2011). A Quantitative Comparison of NIRS and fMRI Across Multiple Cognitive Tasks. NeuroImage, 54(4), 2808–2821. https://doi.org/10.1016/j.neuroimage.2010.10.069 

Flagel, S. B., Chaudhury, S., Waselus, M., Kelly, R., Sewani, S., Clinton, S. M., Thompson, R. C., Watson, S. J., Jr, & Akil, H. (2016). Genetic Background and Epigenetic Modifications in the Core of the Nucleus Accumbens Predict Addiction-like Behavior in a Rat Model. Proceedings of the National Academy of Sciences of the United States of America, 113(20), E2861–E2870. https://doi.org/10.1073/pnas.1520491113 

Gratten, J., Wray, N. R., Keller, M. C., & Visscher, P. M. (2014). Large-scale genomics unveils the genetic architecture of psychiatric disorders. Nature neuroscience, 17(6), 782–790. https://doi.org/10.1038/nn.3708 

Hämäläinen, M., Hari, R., Ilmoniemi, R. J., Knuutila, J., & Lounasmaa, O. V. (1993). Magnetoencephalography—Theory, Instrumentation, and Applications to Noninvasive Studies of the Working Human Brain. Reviews of modern Physics, 65(2), 413. https://journals.aps.org/rmp/abstract/10.1103/RevModPhys.65.413 

Hanrieder, J., Phan, N. T., Kurczy, M. E., & Ewing, A. G. (2013). Imaging Mass Spectrometry in Neuroscience. ACS chemical neuroscience, 4(5), 666–679. https://doi.org/10.1021/cn400053c 

Heather, J. M., & Chain, B. (2016). The Sequence of Sequencers: The History of Sequencing DNA. Genomics, 107(1), 1–8. https://doi.org/10.1016/j.ygeno.2015.11.003 

Heidenreich, M., & Zhang, F. (2016). Applications of CRISPR-Cas Systems in Neuroscience. Nature reviews. Neuroscience, 17(1), 36–44. https://doi.org/10.1038/nrn.2015.2

Herbst, S. M., Proepper, C. R., Geis, T., Borggraefe, I., Hahn, A., Debus, O., Haeussler, M., von Gersdorff, G., Kurlemann, G., Ensslen, M., Beaud, N., Budde, J., Gilbert, M., Heiming, R., Morgner, R., Philippi, H., Ross, S., Strobl-Wildemann, G., Muelleder, K., Vosschulte, P., … Hehr, U. (2016). LIS1-associated Classic Lissencephaly: A Retrospective, Multicenter Survey of the Epileptogenic Phenotype and Response to Antiepileptic Drugs. Brain & development, 38(4), 399–406. https://doi.org/10.1016/j.braindev.2015.10.001 

Hopf, F. W., & Lesscher, H. M. (2014). Rodent Models for Compulsive Alcohol Intake. Alcohol (Fayetteville, N.Y.), 48(3), 253–264. https://doi.org/10.1016/j.alcohol.2014.03.001 

Johnson, A. C., & Greenwood-Van Meerveld, B. (2016). The Pharmacology of Visceral Pain. Advances in pharmacology (San Diego, Calif.), 75, 273–301. https://doi.org/10.1016/bs.apha.2015.11.002 

Kandel, E. R., Dudai, Y., & Mayford, M. R. (2014). The Molecular and Systems Biology of Memory. Cell, 157(1), 163–186. https://doi.org/10.1016/j.cell.2014.03.001 

Lee, G. J., Park, J. H., & Park, H. K. (2008). Microdialysis Applications in Neuroscience. Neurological research, 30(7), 661–668. https://doi.org/10.1179/174313208X289570 

Leroy, A., Foucher, J. R., Pins, D., Delmaire, C., Thomas, P., Roser, M. M., Lefebvre, S., Amad, A., Fovet, T., Jaafari, N., & Jardri, R. (2017). fMRI Capture of Auditory Hallucinations: Validation of the Two-Steps Method. Human brain mapping, 38(10), 4966–4979. https://doi.org/10.1002/hbm.23707 

Liu, Z., Ding, L., & He, B. (2006). Integration of EEG/MEG with MRI and fMRI. IEEE engineering in medicine and biology magazine : the quarterly magazine of the Engineering in Medicine & Biology Society, 25(4), 46–53. https://doi.org/10.1109/memb.2006.1657787 

Lodish H., Berk A., Zipurksy S. L. et. al., editors. (2000). Molecular Cell Biology, 4th edition. Freeman, p 94, 140, 147-148, 268-269.

Malik, A. N., Vierbuchen, T., Hemberg, M., Rubin, A. A., Ling, E., Couch, C. H., Stroud, H., Spiegel, I., Farh, K. K., Harmin, D. A., & Greenberg, M. E. (2014). Genome-wide Identification and Characterization of Functional Neuronal Activity-Dependent Enhancers. Nature neuroscience, 17(10), 1330–1339. https://doi.org/10.1038/nn.3808 

Mayford, M., Siegelbaum, S. A., & Kandel, E. R. (2012). Synapses and Memory Storage. Cold Spring Harbor perspectives in biology, 4(6), a005751. https://doi.org/10.1101/cshperspect.a005751 

Maze, I., Shen, L., Zhang, B., Garcia, B. A., Shao, N., Mitchell, A., Sun, H., Akbarian, S., Allis, C. D., & Nestler, E. J. (2014). Analytical Tools and Current Challenges in the Modern Era of Neuroepigenomics. Nature neuroscience, 17(11), 1476–1490. https://doi.org/10.1038/nn.3816 

National Human Genome Research Institute. (July 2017). An Overview of the Human Genome Project. Accessed July 17, 2017 at https://www.genome.gov/12011238/an-overview-of-the-human-genome-project/

National Institute of Mental Health. (2017). Brain Stimulation Therapies. Accessed July 17, 2017 at https://www.nimh.nih.gov/health/topics/brain-stimulation-therapies/brain-stimulation-therapies.shtml

Olgiati, S., Quadri, M., & Bonifati, V. (2016). Genetics of Movement Disorders in the Next-Generation Sequencing Era. Movement disorders, 31(4), 458–470. https://doi.org/10.1002/mds.26521 

Perry, R. H., Blessed, G., Perry, E. K., & Tomlinson, B. E. (1980). Histochemical Observations on Cholinesterase Activities in the Brains of Elderly Normal and Demented (Alzheimer-type) Patients. Age and ageing, 9(1), 9–16. https://doi.org/10.1093/ageing/9.1.9 

Purves D, Augustine GJ, Fitzpatrick D, et al., editors. (2008). Neuroscience. 4th edition. Sinauer Associates, Inc. p 3-5, 16-17, 19-21, 25-27, 181-187, 465, 559, 673-674, 715-717.

Sejnowski, T. J., Koch, C., & Churchland, P. S. (1988). Computational Neuroscience. Science (New York, N.Y.), 241(4871), 1299–1306. https://doi.org/10.1126/science.3045969 

Sokolowski M. B. (2001). Drosophila: Genetics Meets Behaviour. Nature reviews. Genetics, 2(11), 879–890. https://doi.org/10.1038/35098592 

Svoboda, K., & Yasuda, R. (2006). Principles of Two-Photon Excitation Microscopy and its Applications to Neuroscience. Neuron, 50(6), 823–839. https://doi.org/10.1016/j.neuron.2006.05.019 

Turek, F. W., Pinto, L. H., Vitaterna, M. H., Penev, P. D., Zee, P. C., & Takahashi, J. S. (1995). Pharmacological and Genetic Approaches for the Study of Circadian Rhythms in Mammals. Frontiers in neuroendocrinology, 16(3), 191–223. https://doi.org/10.1006/frne.1995.1007 

US National Library of Medicine, National Institutes of Health. (2017). Genetics Home Reference – Huntington Disease. Accessed July 17, 2017 at https://ghr.nlm.nih.gov/condition/huntington-disease#genes

Usdin, K., & Kumari, D. (2015). Repeat-mediated Epigenetic Dysregulation of the FMR1 Gene in the Fragile X-related Disorders. Frontiers in genetics, 6, 192. https://doi.org/10.3389/fgene.2015.00192 

Yoshino, K., Oka, N., Yamamoto, K., Takahashi, H., & Kato, T. (2013). Functional Brain Imaging Using Near-infrared Spectroscopy During Actual Driving on an Expressway. Frontiers in human neuroscience, 7, 882. https://doi.org/10.3389/fnhum.2013.00882 
 

Ask An Expert

Ask a neuroscientist your questions about the brain.

Submit a Question

BrainFacts Book

Download a copy of the newest edition of the book, Brain Facts: A Primer on the Brain and Nervous System.

Download

Educator Resources

Explain the brain to your students with a variety of teaching tools and resources.

Explore