Counting Neurons: Comparing Invasive and Noninvasive Techniques Volume 49- Issue 1

Jamal H Ali*

• Science Department, Borough of Manhattan Community College, The City University of New York, 199 Chambers St, USA

Received:February 22, 2023;   Published:March 08, 2023

*Corresponding author: Jamal H Ali, Science Department, Borough of Manhattan Community College, The City University of New York, 199 Chambers St, New York, USA

DOI: 10.26717/BJSTR.2023.49.007757

Abstract PDF

This article discusses the various techniques—categorized into invasive and noninvasive—used in neuroscience research for counting neurons and estimating their density. Invasive techniques involve physically removing and staining brain tissue to count neurons, while noninvasive techniques allow for the examination of brain structure and function in live animals or humans. Examples of invasive techniques include stereology, optical fractionator, manual cell counting, confocal microscopy, and electron microscopy. Examples of noninvasive techniques include magnetic resonance imaging (MRI), electroencephalography (EEG), and functional near-infrared spectroscopy (fNIRS). The advantages and disadvantages of each technique are summarized in Table 1. Recent advancements in noninvasive NIR spectroscopic technique to estimate neuron density are highlighted. Future research and technological advancement, especially in noninvasive techniques, could lead to a better understanding of neural circuits, their function, and our daily lives.

Keywords: Neurons; Non-Invasive; Invasive; Neurodegenerative Disease; Optical; NIR

Abbreviations: NIR-OS: NIR-Optical Spectroscopic; FNIRS: Functional Near-Infrared Spectroscopy; EED: Electroencephalography; MRI: Magnetic Resonance Imaging

The past 30 years have seen significant advancements in cell and neuron counting, greatly expanding our understanding of neural circuits and their function. With continued research and technological development, it is likely that even greater insights will be gained in the coming years. In neuroscience research, counting neurons provides vital information about the structure and function of the brain. Techniques for counting neurons are divided into two categories: invasive and noninvasive. Invasive techniques involve physically removing and, if necessary, staining brain tissue from an animal or human brain to identify and count the neurons. This provides accurate neuron counts but is destructive and can only be used on deceased animals or humans or when tissues are removed by biopsy. There are several methods used to count neurons or to estimate their density. One such method is stereology, which involves counting a representative sample of neurons in a defined area and extrapolating this number to estimate the total number of neurons in the region of interest [1,2]. Optical fractionator is a method that involves counting neurons in a series of systematically sampled tissue sections [3,4]. The optical fractionator method is highly reliable and can be used to estimate the total number of neurons in a given tissue volume. It involves counting neurons in a series of systematically sampled tissue sections using a combination of light microscopy and computer-assisted image analysis. This method can also be used to estimate the size, distribution, and spatial arrangement of individual neurons.

Manual cell counting methods involve visually identifying and counting neurons under a microscope [5]. This can be done in brain slices or in whole brains that have been cleared using different techniques. Confocal microscopy is a technique that is often used in neuroscience research to visualize and count neurons in tissue sections [6-8]. It uses a laser light source to scan the sample and create high-resolution, 3D images of the tissue. Finally, electron microscopy is a high-resolution imaging technique that can be used to visualize the ultrastructure of individual neurons and synapses, and to estimate the number of neurons in a given region of the brain [9- 11]. Conversely, noninvasive techniques do not require the removal of brain tissue and can be performed on live animals or humans. These techniques offer a way to examine brain structure and function in vivo. Magnetic resonance imaging (MRI) uses a powerful magnet and radio waves to create detailed images of the brain [12,13]. MRI can be used to study brain structure and function, and to investigate disease or injury-associated brain changes. Another non-invasive technique is electroencephalography (EEG), in which electrodes attached to the scalp are used to record electrical activity in the brain [14,15]. In addition to studying brain function and activity, EEG has been used to investigate a range of neurological and psychiatric disorders. Finally, functional near-infrared spectroscopy (fNIRS) is a non-invasive technique that uses light to measure changes in blood flow and oxygenation in the brain, which can be used to study brain function and activity [16,17]. These non-invasive techniques offer a potent means to study the brain without the need for invasive procedures, allowing for safer and more ethical research on live animals or humans.

Table 1. Summary of the advantages and disadvantages of
A) Invasive techniques and
B) Non-invasive techniques to investigate neuronal activities.

Note: summarizes the advantages and disadvantages of the aforementioned techniques.

It is critical to note that these non-invasive techniques cannot estimate the number of neurons in the human brain. However, these non-invasive techniques provide indirect measures of neuronal activity and brain function rather than directly estimating the number of neurons. For the first time, we recently estimated neuron density using NIR optical spectroscopic (NIR-OS) through noninvasive techniques that may provide valuable information about brain activity and connectivity [18]. Using Beer’s law and the Mie model, the density of neurons in the examined gray matter tissue sample was estimated as roughly 40,000 neurons/mg [18]. The estimated depth of penetration in the cerebral cortex at 800 nm is approximately 3.8 mm [18]. However, using longer and more suitable wavelengths could achieve deeper brain penetration [19]. The NIR-OS technique has potential advantages of being potentially non-invasive, simple, cheap, and fast, but as a newly developed technique, more work needs to be done to check its accuracy in estimating the number of neurons in a localized region.

It is critical to note that these non-invasive techniques cannot estimate the number of neurons in the human brain. However, these non-invasive techniques provide indirect measures of neuronal activity and brain function rather than directly estimating the number of neurons. For the first time, we recently estimated neuron density using NIR optical spectroscopic (NIR-OS) through noninvasive techniques that may provide valuable information about brain activity and connectivity [18]. Using Beer’s law and the Mie model, the density of neurons in the examined gray matter tissue sample was estimated as roughly 40,000 neurons/mg [18]. The estimated depth of penetration in the cerebral cortex at 800 nm is approximately 3.8 mm [18]. However, using longer and more suitable wavelengths could achieve deeper brain penetration [19]. The NIR-OS technique has potential advantages of being potentially non-invasive, simple, cheap, and fast, but as a newly developed technique, more work needs to be done to check its accuracy in estimating the number of neurons in a localized region.

I would like to acknowledge Dr. Emily Chan for her valuable discussion and insights into our manuscript. I am grateful for her feedback.

The author has no conflict of interest relevant to this study to declare.

1. Schmitz C, Hof PR (2005) Design-based stereology in neuroscience. Neuroscience 130(4): 813-831.
2. West MJ (1999) Stereological methods for estimating the total number of neurons and synapses: Issues of precision and bias. Trends in Neurosciences 22(2): 51-61.
3. Herculano-Houzel S (2011) Scaling of brain metabolism with a fixed energy budget per neuron: Implications for neuronal activity, plasticity and evolution. PloS one 6(3): e17514.
4. Kmita G, Zawadzki J (2020) Unbiased Estimation of Neuronal Numbers in Rat Hippocampus Using Optical Fractionator. Methods in molecular biology (Clifton, NJ), 2122: 47-56.
5. More HL, Chen J, Gibson E, Donelan JM, Beg MF (2011) A semi-automated method for identifying and measuring myelinated nerve fibers in scanning electron microscope images. Journal of neuroscience methods 201(1): 149-158.
6. Restelli F, Mathis AM, Höhne J, Mazzapicchi E, Acerbi F, et al. (2022) Confocal laser imaging in neurosurgery: A comprehensive review of sodium fluorescein-based CONVIVO preclinical and clinical applications. Front Oncol 12: 998384.
7. Kakaletri I, Linxweiler M, Ajlouni S, Charalampaki P (2022) Development implementation and Application of Confocal Laser Endomicroscopy in Brain, Head and Neck Surgery—A Review. Diagnostics 12(11): 2697.
8. Paddock S W (2000) Principles and practices of laser scanning confocal microscopy. Molecular biotechnology 16(2): 127-149.
9. Furuta T, Yamauchi K, Okamoto S, Takahashi M, Kakuta S, et al. (2021) Multi-scale light microscopy/electron microscopy neuronal imaging from brain to synapse with a tissue clearing method. ScaleSF iScience 25(1): 103601.
10. Zheng Z, Lauritzen JS, Perlman E, Camenzind GR , Matthew N et al. (2018) A Complete Electron Microscopy Volume of the Brain of Adult Drosophila melanogaster. Cell 174(3): 730-743.
11. Lewis AJ, Genoud C, Pont M, DJ van de Berg W, Frank S, et al. (2019) Imaging of post-mortem human brain tissue using electron and X-ray microscopy. Current Opinion in Structural Biology 58: 138-148.
12. Rosenbloom MJ, Pfefferbaum A (2008) Magnetic resonance imaging of the living brain: Evidence for brain degeneration among alcoholics and recovery with abstinence. Alcohol Res Health 31(4): 362-376.
13. Hemond CC, Bakshi R (2018) Magnetic Resonance Imaging in Multiple Sclerosis. Cold Spring Harb Perspect Med 8(5): a028969.
14. Reaves J, Flavin T, Mitra B, Mahantesh K, Nagaraju V (2021) Assessment And Application of EEG: A Literature Review. J Appl Bioinforma Comput Biol 10: 7.
15. Neto Emanuel, Allen Elena A, Aurlien Harald, Nordby Helge, Eichele Tom, et al. (2015) Spectral Features Discriminate between Alzheimer’s and Vascular Dementia Frontiers in Neurology 6: 25.
16. Karim H, Schmidt B, Dart D, Beluk N, Huppert T, et al. (2012) Functional near-infrared spectroscopy (fNIRS) of brain function during active balancing using a video game system. Gait Posture 35(3): 367-372.
17. Chen WL, Wagner J, Heugel N, Sugar J, Lee Y, et al. (2020) Functional Near-Infrared Spectroscopy and Its Clinical Application in the Field of Neuroscience: Advances and Future Directions. Frontiers in Neuroscience 14: 724.
18. Ali JH (2023) Spectral Optical Properties of Gray Matter in Human Male Brain Tissue Measured at 400–1100 nm. Optics 4(1): 1-10.
19. Shi L, Sordillo LA, Rodríguez-Contreras A, Alfano R (2016) Transmission in near-infrared optical windows for deep brain imaging. J Biophotonics 9(1-2): 38-43.