Exploring the Complexity of the Human Brain: Cell Types, Numbers, and Lobar Functions

Abstract

Keywords:Neuron, Glial Cells, Brain, Brain Lobes, Interneuron

Introduction

The human brain, an exquisitely intricate organ, acts as the central command center for cognition, emotion, and sensory perception. It orchestrates a remarkable array of functions, ranging from basic survival mechanisms to the most complex aspects of human thought and behavior [1]. Comprising billions of neurons alongside an equally vast number of supporting glial cells, the brain’s elaborate network underpins every facet of our mental and physical experiences. Neurons serve as the primary communicators, transmitting electrical and chemical signals across complex neural circuits, enabling everything from simple reflexes to advanced problem-solving [2]. Meanwhile, glial cells, such as astrocytes, oligodendrocytes, and microglia, play critical roles in maintaining homeostasis, providing structural support, and facilitating communication within this neural framework [3].

Understanding the cellular composition of the brain, specifically the variety and quantity of its cells, has emerged as one of the most profound and elusive questions in neuroscience. This cellular diversity is not merely a matter of counting cells; it involves unraveling the distinct functional roles of various cell types and their intricate interactions. Each type of cell contributes uniquely to the overall functionality of the brain, and the balance and distribution of these cells can profoundly impact brain health and disease [4]. The quest to accurately enumerate the number of cells in the human brain extends beyond mere academic curiosity; it has significant implications for both fundamental and clinical neuroscience [3]. A precise understanding of cell numbers and types offers critical insights into brain structure and function, shaping our theories of brain development, aging, and neuroplasticity [5]. This review seeks to provide a comprehensive overview of the cell types and quantities within the human brain, illuminating the remarkable complexity that defines our most vital organ.

History of Cell Counting Methods

Brain cell counting has evolved through three distinct historical phases. Initially, data collection was limited to specific brain regions, primarily the cerebral cortex. During this period, which extended until the 1970s, some researchers expressed uncertainty about the absolute number of brain cells, while others estimated or theorized GNRs for the whole brain. The second phase saw the emergence of more comprehensive estimates for total cell counts, including glial cells, ranging from 40 to 130 billion and neurons ranging from 70 to 85 billion [6,7]. Despite these estimates suggesting a glial-to-neuron ratio (GNR) of approximately 1:1, this information was either overlooked or not effectively communicated. Consequently, the exaggerated ratios of 10:1 or even 50:1 persisted in major textbooks and reviews, with this misconception remaining largely unchallenged from the 1960s until 2009. This incorrect GNR had, unfortunately, become accepted as “common knowledge.” In the third phase, Azevedo, et al.’s study (2009), showed that the previous textbook claims about the number of glial cells versus neurons were incorrect. This study confirmed that the earlier estimates of roughly equal numbers of neurons and glial cells previously reported by Blinkov and Glezer (1968) and Haug (1986) were more accurate, leading to a correction in the understanding of brain cell counts [6,8].

Overview of Cell Counting Methods

There are three different methods used to estimate the number of cells in the brain which are histology/stereology, DNA extraction and “direct enumeration” of cells in homogenized brain tissue.

Histology/stereology

The histology method for estimating the number of brain cells begins with the fixation of brain tissue using a formaldehyde-based solution. This process preserves the cellular structure and prevents decay. Once fixed, the tissue is embedded in a supportive medium and sliced into thin sections. These thin slices are then stained with specific dyes that enhance the visibility of cells or subcellular components and counted under a microscope. There are two main approaches to this counting process: the model-based approach, known as profile counting and the design-based approach, or stereology. In model-based approach, subcellular particles (usually nuclei or nucleoli) are counted in thin sections, then extrapolates to estimate total cell numbers. [9-11]. The design-based approach (stereology) takes random samples within these sections so that the samples are representative of the particle density [12-15].

DNA extraction

DNA extraction methods involve isolating the DNA contained within cells, allowing researchers to analyze genetic material for various applications [16]. This process typically begins with cell lysis, where the cell membrane is broken down to release the DNA. Following lysis, different purification techniques, such as phenol- chloroform extraction or silica-based methods, are employed to separate the DNA from proteins and other cellular components [17]. Once the DNA is extracted, researchers can calculate cell numbers by using the known average DNA content per cell nucleus, which is specific to the organism and cell type being studied. By quantifying the extracted DNA, scientists can derive the total number of cells in the sample, providing valuable insights for studies in genetics, cell biology, and molecular research [18].

Homogenization

This method was initially developed in the 1950s and involved weighing dissected chilled tissue, homogenizing it, and diluting it in a known volume of medium [19]. The tissue was then stained with methylene blue, mixed, and aliquots were counted using a hemocytometer. However, this approach had significant limitations, including the rapid degradation of unfixed cells and the inability to distinguish between different cell types [19]. Further modification of this method was introduced in 2005 and was called “isotropic fractionator” [8,20]. This include nuclei visualization using a fluorescent nuclear stain (4′,6-Diamidino-2-Phenylindole, DAPI), and neuronal and non-neuronal cell nuclei are differentiated using a neuron-specific antibody, anti-NeuN [21]. This method is advantageous because it is easy, fast, and accurate, producing cell estimates that are independent of tissue volume or cell density, and it effectively addresses the heterogeneity of brain tissues.

The Number of Lobes and Cellular Count in the Human Brain.

In the early 20th century, neuroscientist Korbinian Brodmann (1868-1918) identified 52 distinct lobes of the human brain (Figure 1), each contributing significantly to various cognitive functions. These lobes facilitate critical processes such as motor control, emotion regulation, and decision-making, illustrating how different regions collaborate to support complex behaviours (Table 1). Understanding these lobes provides valuable insights into how the brain orchestrates a wide range of functions, revealing the intricacies of its operational dynamics. By mapping these connections and examining how they interact, researchers can better understand both normal brain function and the disruptions that can lead to neurological and psychiatric disorders.

Figure 1:Types of lobes of human brain.

Source: Linda, 2016

Table 1:Types of lobes of human brain

At the heart of the human brain lies the brain’s cellular composition, which is essential for their functionality. Quantitative neuroscience researchers have employed histological methods to estimate the number of neurons in the human brain, providing valuable insights into its complex architecture. Estimates vary widely, with figures ranging from 30 billion to 70-80 billion, and reaching up to 85 billion [6,7,22]. More recent studies using the isotropic fractionator method have corroborated these estimates, suggesting there are between 67 and 86 billion neurons [8,20]. In terms of glial cells, early estimates by Blinkov and Glezer (1968) suggested a total of 100-130 billion glial cells in the human brain. However, Haug’s own measurements indicated a lower estimate of 40-50 billion glial cells [6]. Current estimates derived from the isotropic fractionator method suggest that the total number of glial cells is likely below 85 billion, since this total includes approximately 20-25 billion endothelial cells. Thus, these findings align more closely with Haug’s estimates of 40-50 billion glial cells rather than those of Blinkov and Glezer.

Factor Affecting Variation of Number of Brain Cells Among Human

Variations in the number of neurons among humans arise from a complex interplay of factors, including genetics, age, and health conditions. Each individual’s genetic makeup can lead to distinct differences in brain structure and neuronal density [23]. For instance, genetic variations can influence the production of growth factors and neurotransmitters that are critical for neuron development and connectivity. This can result in differing neuronal densities in key areas such as the prefrontal cortex, responsible for decision-making, impulse control, and higher cognitive functions, and the hippocampus, which plays a crucial role in memory formation and spatial navigation [24]. Research has shown that these variations not only affect brain structure but also correlate with cognitive abilities, emotional regulation, and learning capacity. For example, individuals with a higher density of neurons in the hippocampus may have better memory retention and spatial awareness [25]. Additionally, as individuals age, they typically experience a decline in neuron numbers due to natural aging processes, including oxidative stress, inflammation, and reduced neurogenesis. This decline can manifest as slower processing speeds, decreased memory capacity, and increased difficulty in learning new information, highlighting the critical importance of maintaining neuron health throughout life to support cognitive function and emotional well-being [26].

Health conditions play a pivotal role in neuronal variability, particularly neurodegenerative diseases such as Alzheimer’s and Parkinson’s. These disorders are characterized by the progressive loss of neurons, particularly in regions essential for cognitive function and motor control [27]. In Alzheimer’s disease, substantial neuron loss occurs in the hippocampus, which severely impacts memory, learning, and the ability to form new memories. Additionally, the accumulation of amyloid plaques and tau tangles in the brain further contributes to neuronal damage and cognitive decline [28]. In contrast, Parkinson’s disease primarily affects the substantia nigra, where the loss of dopamine-producing neurons leads to hallmark motor symptoms such as tremors, rigidity, and bradykinesia (slowness of movement). The extent of neuron loss in these critical areas serves as a vital indicator of disease severity and progression, enabling healthcare providers to tailor treatment strategies accordingly [29].

Lifestyle and environmental factors also significantly influence neuron count and overall brain health. Regular physical activity has been shown to promote neurogenesis, the process by which new neurons are created, and improve brain plasticity, which is essential for learning, memory, and recovery from injury. Exercise enhances blood flow to the brain, increases levels of neurotrophic factors like BDNF (brain-derived neurotrophic factor), and reduces inflammation, all of which contribute to neuronal health [30]. A balanced diet rich in omega-3 fatty acids, antioxidants, and essential vitamins supports neuronal integrity and can mitigate age-related cognitive decline. For example, omega-3 fatty acids found in fish have been linked to improved cognitive function and may help protect against neurodegeneration [31]. Engaging in intellectually stimulating activities, such as reading, solving puzzles, or learning new skills, has also been associated with enhanced cognitive function and resilience against decline [32]. Conversely, exposure to environmental toxins, chronic stress, and substance abuse can lead to neuronal damage and loss, heightening the risk of cognitive decline and neurodegenerative diseases [33].

Human Brain Structural Changes During Aging

The aging process significantly affects the brain, resulting in a gradual decline in both its volume and weight. Research indicates that, after reaching the age of 40, this decline occurs at an approximate rate of 5% per decade [34]. This rate of decline may accelerate further after the age of 70, leading to more pronounced changes in brain structure and function [35].

The impact of aging is not distributed evenly across the various regions of the brain [36]. The prefrontal cortex, which is crucial for executive functions such as decision-making, impulse control, and social interactions, is the area most severely affected by aging [37]. Following the prefrontal cortex, the striatum, an essential component of the brain’s reward system and movement regulation, shows notable changes. Other regions experiencing decline include the temporal lobe, involved in processing auditory information and forming memories; the cerebellar vermis and cerebellar hemispheres, which are vital for coordination, balance, and motor learning; and the hippocampus, a key region for memory consolidation and spatial navigation [38].

Interestingly, the prefrontal white matter, which consists of myelinated axons that facilitate communication between different brain regions, also demonstrates deterioration, potentially affecting overall cognitive efficiency [39]. In contrast, the occipital cortex, responsible for visual processing, appears to be the least affected by age-related changes. This specific pattern of brain aging aligns closely with the cognitive alterations frequently observed in older adults, such as memory decline, slower processing speeds, and diminished executive functioning [37]. Some studies further highlight the vulnerability of the hippocampus to age-related decline, underscoring its critical role in memory and learning processes [40].

In addition to these general trends, research has identified notable gender differences in how aging impacts the brain. Men often exhibit greater declines in the frontal and temporal lobes, which can affect cognitive abilities and emotional regulation. Conversely, women tend to experience more pronounced effects in the hippocampus and parietal lobes, regions associated with memory and spatial awareness [41,42].

Types of Cells in the Human Brain

The human brain composed of a variety of cell types (Table 2) that can be broadly classified into two primary groups: neurons and glial cells. These distinct cell types share a common origin, arising from neural stem cells through a process known as neurogenesis [43]. This fundamental biological process underscores the brain’s remarkable ability for development and regeneration, allowing for the formation of intricate networks that are essential for cognitive functions and effective neural communication. Neurons, the brain’s primary signaling cells, are specialized for the transmission of electrical impulses throughout the nervous system. They play a pivotal role in processing and relaying information, which is crucial for everything from reflex actions to complex thought processes. The functionality of neurons depends on their ability to communicate with one another and with other types of cells, forming an extensive network that underlies all aspects of behavior and cognition [44]. Neurons can be further categorized into three main types: motor neurons, sensory neurons, and interneurons. Motor neurons are responsible for controlling muscle movements and enabling actions, making them essential for voluntary and involuntary motor functions [45]. Sensory neurons, on the other hand, transmit sensory information from various parts of the body to the brain, allowing us to perceive and interact with our environment [46]. Interneurons serve as connectors within the neural network, facilitating communication between sensory and motor neurons, as well as among other interneurons. Among interneurons, a rich diversity of subtypes exists, each with specialized functions. These various interneuron types are critical for modulating neural activity and ensuring the brain operates efficiently. Some interneurons are involved in reflex actions, rapidly processing sensory input to produce immediate responses, while others contribute to higher-order cognitive functions, such as learning and memory [47].

Table 2:Types of cells in the human brain.

Glial cells, often overshadowed by the more widely known neurons, are essential for supporting and maintaining the overall health of the nervous system. They can be divided into several distinct types, including astrocytes, oligodendrocytes, ependymal cells, and microglia. Each type of glial cell has unique functions that contribute to the overall functioning of the brain and spinal cord [48]. Astrocytes are the most abundant type of glial cell and provide structural support to neurons, helping to maintain the architecture of the brain. They also play a critical role in maintaining the blood-brain barrier, which protects the brain from harmful substances while allowing essential nutrients to pass through. This barrier is vital for maintaining a stable environment for neuronal function, ensuring that neurons can operate optimally [49]. Oligodendrocytes are specialized glial cells that produce myelin, a fatty substance that insulates neuronal axons. This myelination is crucial for enhancing the speed and efficiency of electrical signal transmission along the neurons. By insulating axons, oligodendrocytes facilitate rapid communication between different brain regions, which is essential for coordinated actions and cognitive processing [50]. Ependymal cells line the ventricles of the brain and are involved in the production and circulation of cerebrospinal fluid (CSF). This fluid serves multiple purposes, including cushioning the brain, removing waste, and delivering nutrients. The proper functioning of ependymal cells is critical for maintaining the brain’s internal environment and protecting it from injury [51]. Microglia, the immune cells of the brain, are responsible for monitoring the health of neuronal environments. They play a crucial role in responding to injury and disease, acting as first responders to inflammation and helping to clear cellular debris. This function is vital for maintaining brain health, as microglia can protect neurons from damage and facilitate recovery following injury [52].

The human brain is a highly complex organ composed of a diverse array of cell types, each contributing to its intricate functions. Neurons are the primary signalling units, specialized for transmitting information throughout the nervous system. They can be classified into various types, with each playing unique roles in processing, integrating, and relaying signals. This diversity in neuronal architecture enables the brain to perform a vast range of cognitive and motor functions, highlighting the essential nature of neurons in maintaining brain health and functionality. In addition to neurons, glial cells play crucial supporting roles in the brain’s ecosystem. Astrocytes contribute to nutrient transport, maintaining the blood-brain barrier, and modulating synaptic activity, while oligodendrocytes are responsible for myelinating axons, which enhances signal transmission speed. Microglia serve as the brain’s immune cells, monitoring for injury and infection, and ependymal cells help produce and circulate cerebrospinal fluid. Together, these glial cells create a supportive environment that ensures optimal neuronal function and overall brain health. The interaction between neurons and glial cells is fundamental to the brain’s adaptability and resilience. Furthermore, the dynamic communication between these cell types is essential for processes such as learning and memory, underscoring the importance of their collaboration in maintaining cognitive function and homeostasis. Understanding the diverse types of brain cells and their interrelationships is vital for advancing our knowledge of brain function and developing targeted therapies for neurological disorders. As research continues to unveil the complexities of these cellular interactions, it opens new avenues for innovative treatments aimed at addressing conditions such as neurodegenerative diseases, traumatic brain injuries, and psychiatric disorders. Ultimately, a comprehensive understanding of brain cell types will enhance our ability to foster brain health and improve outcomes for individuals affected by neurological challenges.

Contributions

Mohd Iskandar Jumat: Conceptualization, Writing - original draft, Writing - review & editing. Florisa Landa: Writing - review & editing. Nur Shafawati Saili: Writing - review & editing. Siti Azmah Jambo: Writing - review & editing. Dianah Florentius: Writing - review & editing. Nuryasmin Ezzaty: Writing & data collection. Raz Haziqah Hani Razali: Writing & data collection. Brenda Son Pei Chui: Writing & data collection. Aziera Farhanah Adihidayah Suardi: Writing & data collection. Sze-Huey Sang: Writing & data collection. Mike KS Chan: Supervision, editing & reviewing. Michelle BF Wong: Supervision, editing & reviewing. Jonathan RT Lakey: Supervision, editing & reviewing. Thomas Skutella: Supervision, editing & reviewing.

Conflict of Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

References

1. Wang Y, Pan Y and Li H (2020) What is brain health and why is it important? 371:m3683.
2. Rasband MN (2016) Glial Contributions to Neural Function and Disease, Mol Cell Proteomics 15(2): 355-361.
3. Bartheld CSV, Bahney J, Herculano Houzel S (2016) The search for true numbers of neurons and glial cells in the human brain: A review of 150 years of cell counting, J Comp Neurol 524(18): 3865-3895.
4. Jiang X and Nardelli J (2016) Cellular and molecular introduction to brain development, Neurobiol Dis 92(Pt A): 3-17.
5. Kolb B and Gibb R (2011) Brain plasticity and behaviour in the developing brain, J Can Acad Child Adolesc Psychiatry 20(4): 265-276.
6. Haug H (1986) History of neuromorphometry, J Neurosci Methods 18(1-2): 1-17.
7. Williams RW and Herrup K (1988) The control of neuron number, Annu Rev Neurosci 11: 423-453.
8. Azevedo FA, Carvalho LR, Grinberg LT, Farfel JM, and Ferretti RE, (2009) Equal numbers of neuronal and nonneuronal cells make the human brain an isometrically scaled-up primate brain, J Comp Neurol 513(5): 532-541.
9. Abercrombie M (1946) Estimation of nuclear population from microtome sections, Anat Rec 94: 239-247.
10. Konigsmark BW and Murphy EA (1970) Neuronal populations in the human brain, Nature 228(5278) :1335-1336.
11. Clarke PG and Oppenheim RW (1995) Neuron death in vertebrate development: in vitro methods Methods Cell Biol 46:277-321.
12. Haug H (1984) Effect of secular acceleration on the human brain weight and its changes during aging: Gegenbaurs Morphol Jahrb 130(4): 481-500.
13. Haug H (1987) Brain sizes, surfaces, and neuronal sizes of the cortex cerebri: a stereological investigation of man and his variability and a comparison with some mammals (primates, whales, marsupials, insectivores, and one elephant), Am J Anat 180(2): 126-142.
14. Williams RW, Rakic P (1988) Three-dimensional counting: an accurate and direct method to estimate numbers of cells in sectioned material, J Comp Neurol 278(3): 344-352.
15. Schmitz C and Hof PR (2005) Design-based stereology in neuroscience, Neuroscience 130(4): 813-831.
16. Heller IH and Elliott KA (1954) Desoxyribonucleic acid content and cell density in brain and human brain tumors, Can J Biochem Physiol 32(5): 584-592.
17. Zamenhof S, Bursztyn H, Rich K and Zamenhof PJ (1964) The Determination of Deoxyribonucleic Acid and of Cell Number in Brain, J Neurochem 11: 505-509.
18. Mares V, Crkovska J, Marsak TL and Stipek S (1985) DNA content in nerve-cell nucleus. A biochemical and cytophotometric study of the rat cerebrum, Neuroscience 16(1): 45-47.
19. Nurnberger JI and Gordon MW (1956) The cell density of neural tissues: direct counting method and possible applications as a biologic referent, Prog Neurobiol 2(1957): 100-128; discussion 128-38.
20. Andrade Moraes CH, Oliveira Pinto AV, Castro Fonseca E, Da Silva CG, Guimaraes DM, et al, (2013) Cell number changes in Alzheimer's disease relate to dementia, not to plaques and tangles, Brain 136(Pt 12): 3738-3752.
21. Herculano Houzel S, Lent R (2005) Isotropic fractionator: a simple, rapid method for the quantification of total cell and neuron numbers in the brain, J Neurosci 25(10): 2518-2521.
22. Szentagothai J (1983) The modular architectonic principle of neural centers, Rev Physiol Biochem Pharmacol 98: 11-61.
23. Douet V, Chang L, Cloak C and Ernst T (2014) Genetic influences on brain developmental trajectories on neuroimaging studies: from infancy to young adulthood, Brain Imaging Behav 8(2): 234-250.
24. Seidlitz J, Mallard TT, Vogel JW, Lee YH, Warrier V, et al (2023) The molecular genetic landscape of human brain size variation, Cell Rep 42(11): 113439.
25. Toda T, Parylak SL, Linker SB, Gage FH (2019) The role of adult hippocampal neurogenesis in brain health and disease, Mol Psychiatry 24(1): 67-87.
26. Maldonado E, Morales Pison S, Urbina F, Solari A (2023) Aging Hallmarks and the Role of Oxidative Stress, Antioxidants (Basel) 12(3).
27. Ayeni EA, Aldossary AM, Ayejoto DA, Gbadegesin LA, Alshehri AA, et al (2022) Neurodegenerative Diseases: Implications of Environmental and Climatic Influences on Neurotransmitters and Neuronal Hormones Activities, Int J Environ Res Public Health 19(19).
28. DeTure MA and Dickson DW (2019) The neuropathological diagnosis of Alzheimer's disease, Mol Neurodegener 14(1): 32.
29. Ramesh S and Arachchige A (2023) Depletion of dopamine in Parkinson's disease and relevant therapeutic options: A review of the literature, AIMS Neurosci 10(3): 200-231.
30. Vecchio LM, Meng Y, Xhima K, Lipsman N, Hamani C, (2018) The Neuroprotective Effects of Exercise: Maintaining a Healthy Brain Throughout Aging, Brain Plast 4(1): 7-52.
31. Loong S, Barnes S, Gatto NM, Chowdhury S and Lee GJ (2023) Omega-3 Fatty Acids, Cognition, and Brain Volume in Older Adults, Brain Sci 13(9).
32. Weaver AN and Jaeggi SM (2021) Activity Engagement and Cognitive Performance Amongst Older Adults, Front Psychol 12: 620867.
33. Kumar NN, Chan YL, Chen H, Oliver BG (2023) Editorial: Effects of environmental toxins on brain health and development, Front Mol Neurosci 16: 1149776.
34. Svennerholm L, Bostrom K and Jungbjer B (1997) Changes in weight and compositions of major membrane components of human brain during the span of adult human life of Swedes, Acta Neuropathol 94(4): 345-352.
35. Scahill RI, Frost C, Jenkins R, Whitwell JL, Rossor MN, (2003) A longitudinal study of brain volume changes in normal aging using serial registered magnetic resonance imaging, Arch Neurol 60(7): 989-994.
36. Trollor JN and Valenzuela MJ (2001) Brain ageing in the new millennium, Aust N Z J Psychiatry 35(6): 788-805.
37. Peters R (2006) Ageing and the brain, Postgrad Med J 82(964): 84-88.
38. Barnes CA (2003) Long-term potentiation and the ageing brain, Philos Trans R Soc Lond B Biol Sci 358(1432): 765-772.
39. Murman DL (2015) The Impact of Age on Cognition, Semin Hear 36(3): 111-121.
40. Roux CM, Leger M, Freret T (2021) Memory Disorders Related to Hippocampal Function: The Interest of 5-HT(4)Rs Targeting, Int J Mol Sci 22(21).
41. Murphy DG, DeCarli C, McIntosh AR, Daly E, Mentis MJ, et al (1996) Sex differences in human brain morphometry and metabolism: an in vivo quantitative magnetic resonance imaging and positron emission tomography study on the effect of aging, Arch Gen Psychiatry 53(7): 585-594.
42. Compton J, Amelsvoort TV, Murphy D (2001) HRT and its effect on normal ageing of the brain and dementia, Br J Clin Pharmacol 52(6): 647-653.
43. Ghosh HS (2019) Adult Neurogenesis and the Promise of Adult Neural Stem Cells, J Exp Neurosci 13 1179069519856876.
44. (1997) The principles of nerve cell communication, Alcohol Health Res World 21(2): 107-108.
45. Stifani N (2014) Motor neurons and the generation of spinal motor neuron diversity, Front Cell Neurosci 8: 293.
46. Abraira VE and Ginty DD (2013) The sensory neurons of touch, Neuron 79(4): 618-639.
47. DeFelipe J, Lopez Cruz PL, Benavides Piccione R, Bielza C, Larranaga P, et al, (2013) New insights into the classification and nomenclature of cortical GABAergic interneurons, Nat Rev Neurosci 14(3): 202-216.
48. Jakel S and Dimou L (2017) Glial Cells and Their Function in the Adult Brain: A Journey through the History of Their Ablation, Front Cell Neurosci 11: 24.
49. Gradisnik L and Velnar T (2023) Astrocytes in the central nervous system and their functions in health and disease: A review, World J Clin Cases 11(15): 3385-3394.
50. Simons M and Nave KA (2015) Oligodendrocytes: Myelination and Axonal Support, Cold Spring Harb Perspect Biol 8(1): a020479.
51. Jimenez AJ, Dominguez Pinos MD, Guerra MM, Fernandez Llebrez P, Perez Figares JM (2014) Structure and function of the ependymal barrier and diseases associated with ependyma disruption, Tissue Barriers 2: e28426.
52. Colonna M and Butovsky O (2017) Microglia Function in the Central Nervous System During Health and Neurodegeneration, Annu Rev Immunol 35: 441-468.
53. Llorente V, Velarde P, Desco M, Gomez Gaviro MV (2022) Current Understanding of the Neural Stem Cell Niches, Cells 11(19).
54. Nolan M, Scott C, Hof PR and Ansorge O (2024) Betz cells of the primary motor cortex, J Comp Neurol 532(1): e25567.
55. Tyan L, Chamberland S, Magnin E, Camire O, and Francavilla R, et al (2014) Dendritic inhibition provided by interneuron-specific cells controls the firing rate and timing of the hippocampal feedback inhibitory circuitry, J Neurosci 34(13): 4534-4547.
56. Dijkstra AA, Lin LC, Nana AL, Gaus SE and Seeley WW (2018) Von Economo Neurons and Fork Cells: A Neurochemical Signature Linked to Monoaminergic Function, Cereb Cortex 28(1): 131-144.
57. Bradl M and Lassmann H (2010) Oligodendrocytes: biology and pathology, Acta Neuropathol 119(1): 37-53.
58. Inutsuka A and Yamanaka A (2013) The physiological role of orexin/hypocretin neurons in the regulation of sleep/wakefulness and neuroendocrine functions, Front Endocrinol (Lausanne) 4: 18.
59. Maejima T, Tsuno Y, Miyazaki S, Tsuneoka Y, Hasegawa E, et al (2021) GABA from vasopressin neurons regulates the time at which suprachiasmatic nucleus molecular clocks enable circadian behavior, Proc Natl Acad Sci U S A 118(6).
60. Yamawaki N and Shepherd GM (2015) Synaptic circuit organization of motor corticothalamic neurons, J Neurosci 35(5): 2293-307.
61. Bentsen MA, Mirzadeh Z and Schwartz MW, (2019) Revisiting How the Brain Senses Glucose-And Why, Cell Metab 29(1): 11-17.
62. van der Heijden ME, Rey Hipolito AG, Kim LH, Kizek DJ, Perez RM, et al (2023) Sillitoe, Glutamatergic cerebellar neurons differentially contribute to the acquisition of motor and social behaviors, Nat Commun 14(1): 2771.
63. Gonzalez Perez O (2012) Neural stem cells in the adult human brain, Biol Biomed Rep 2(1): 59-69.
64. Bonfanti L and Seki T (2021) The PSA-NCAM-Positive "Immature" Neurons: An Old Discovery Providing New Vistas on Brain Structural Plasticity, Cells 10(10).
65. Smith JE, Co C, Yin X, Sizemore GM, Liguori A, et al (2004) Involvement of cholinergic neuronal systems in intravenous cocaine self-administration, Neurosci Biobehav Rev 27(8): 841-50.
66. Charnay Y and Leger L, (2010) Brain serotonergic circuitries, Dialogues Clin Neurosci 12(4): 471-487.
67. Bolborea M and Dale N (2013) Hypothalamic tanycytes: potential roles in the control of feeding and energy balance, Trends Neurosci 36(2): 91-100.
68. Hwang E, Scarlett JM, Baquero AF, Bennett CM, Dong Y, et al, (2022) Sustained inhibition of NPY/AgRP neuronal activity by FGF1, JCI Insight 7(17).
69. Verney C (1999) Distribution of the catecholaminergic neurons in the central nervous system of human embryos and fetuses, Microsc Res Tech 46(1): 24-47.
70. Gil Sanz C, Franco SJ, Martinez Garay I, Espinosa A, Harkins Perry S, et al (2013) Cajal-Retzius cells instruct neuronal migration by coincidence signaling between secreted and contact-dependent guidance cues, Neuron 79(3): 461-477.
71. Lee CK and Huguenard JR (2011) Martinotti cells: community organizers, Neuron 69(6): 1042-1045.
72. Yanez IB, Munoz A, Contreras J, Gonzalez J, Rodriguez Veiga E, et al (2005) Double bouquet cell in the human cerebral cortex and a comparison with other mammals, J Comp Neurol 486(4): 344-360.
73. Dillon NR, Manning L, Hirono K and Doe CQ (2024) Seven-up acts in neuroblasts to specify adult central complex neuron identity and initiate neuroblast decommissioning, Development 151(3).
74. Muller C and Remy S (2018) Septo-hippocampal interaction, Cell Tissue Res 373(3): 565-575.
75. Lee HJ, Weitz AJ, Bernal Casas D, Duffy BA, Choy M (2016) Activation of Direct and Indirect Pathway Medium Spiny Neurons Drives Distinct Brain-wide Responses, Neuron 91(2): 412-424.
76. Englund C, Kowalczyk T, Daza RA, Dagan A and Lau C, et al (2006) Unipolar brush cells of the cerebellum are produced in the rhombic lip and migrate through developing white matter, J Neurosci 26(36): 9184-9195.
77. Grieves RM, Jedidi Ayoub S, Mishchanchuk K, Liu A, Renaudineau S, (2020) The place-cell representation of volumetric space in rats, Nat Commun 11(1): 789.
78. Benabid A and Peduto L (2020) Mesenchymal perivascular cells in immunity and disease, Curr Opin Immunol 64: 50-55.
79. Jessen KR, Mirsky R and Lloyd AC (2015) Schwann Cells: Development and Role in Nerve Repair, Cold Spring Harb Perspect Biol 7(7): a020487.
80. Brown LS, Foster CG, Courtney JM, King NE, Howells DW, et al (2019) Pericytes and Neurovascular Function in the Healthy and Diseased Brain, Front Cell Neurosci 13: 282.
81. Masoli S, Ottaviani A, Casali S, D Angelo E, et al (2020) Cerebellar Golgi cell models predict dendritic processing and mechanisms of synaptic plasticity, PLoS Comput Biol 16(12): e1007937.
82. Kiyokage E, Pan YZ, Shao Z, Kobayashi K, Szabo G, et al, (2010) Molecular identity of periglomerular and short axon cells, J Neurosci 30(3): 1185-1196.
83. Osorno T, Rudolph S, Nguyen T, Kozareva V, Nadaf NM, et al, (2022) Candelabrum cells are ubiquitous cerebellar cortex interneurons with specialized circuit properties, Nat Neurosci 25(6): 702-713.
84. Armstrong C and Soltesz I (2012) Basket cell dichotomy in microcircuit function, J Physiol 590(4): 683-694.
85. Miyazaki T and Yamasaki M, Tanaka KF and Watanabe M (2021) Compartmentalized Input-Output Organization of Lugaro Cells in the Cerebellar Cortex, Neuroscience 462: 89-105.
86. Ramon Moliner E and Nauta WJ (1966) The isodendritic core of the brain stem, J Comp Neurol 126(3): 311-335.
87. Armstrong C, Krook Magnuson E and Soltesz I (2012) Neurogliaform and Ivy Cells: A Major Family of nNOS Expressing GABAergic Neurons, Front Neural Circuits 6: 23.
88. Dun W and Boyden PA (2008) The Purkinje cell; 2008 style, J Mol Cell Cardiol 45(5): 617-624.
89. Overstreet Wadiche L, McBain CJ (2015) Neurogliaform cells in cortical circuits, Nat Rev Neurosci 16(8): 458-468.
90. Chinta SJ and Andersen JK (2005) Dopaminergic neurons, Int J Biochem Cell Biol 37(5): 942-946.
91. Brown CH, Bains JS, Ludwig M, Stern JE (2013) Physiological regulation of magnocellular neurosecretory cell activity: integration of intrinsic, local and afferent mechanisms, J Neuroendocrinol 25(8): 678-710.
92. Sofroniew MV and Vinters HV (2010) Astrocytes: biology and pathology, Acta Neuropathol 119(1): 7-35.
93. Consalez GG, Goldowitz D, Casoni F and Hawkes R (2020) Origins, Development, and Compartmentation of the Granule Cells of the Cerebellum, Front Neural Circuits 14: 611841.
94. Compans B and Burrone J (2023) Chandelier cells shine a light on the formation of GABAergic synapses, Curr Opin Neurobiol 80: 102697.
95. Cossart R (2014) Operational hub cells: a morpho-physiologically diverse class of GABAergic neurons united by a common function, Curr Opin Neurobiol 26: 51-56.
96. Lim L, Mi D, Llorca A and Marin O (2018) Development and Functional Diversification of Cortical Interneurons, Neuron 100(2): 294-313.
97. Muller RU, Ranck JB and Taube JS (1996) Head direction cells: properties and functional significance, Curr Opin Neurobiol 6(2): 196-206.
98. Moser MB, Rowland DC and Moser EI (2015) Place cells, grid cells, and memory, Cold Spring Harb Perspect Biol 7(2): a021808.
99. Kee N, Sivalingam S, Boonstra R and Wojtowicz JM (2002) The utility of Ki-67 and BrdU as proliferative markers of adult neurogenesis, J Neurosci Methods 115(1): 97-105.
100. Kucenas S (2015) Perineurial glia, Cold Spring Harb Perspect Biol 7(6).
101. Leung AW and Li JYH (2018) The Molecular Pathway Regulating Bergmann Glia and Folia Generation in the Cerebellum, Cerebellum 17(1): 42-48.
102. Boldog E, Bakken TE, Hodge RD, Novotny M, Aevermann BD, et al. (2018) Transcriptomic and morphophysiological evidence for a specialized human cortical GABAergic cell type, Nat Neurosci 21(9): 1185-1195.
103. Houser CR, Peng Z, Wei X, Huang CS, Mody I (2021) Mossy Cells in the Dorsal and Ventral Dentate Gyrus Differ in Their Patterns of Axonal Projections, J Neurosci 41(5): 991-1004.
104. Silvin A, Qian J and Ginhoux F (2023) Brain macrophage development, diversity and dysregulation in health and disease, Cell Mol Immunol 20(11): 1277-1289.
105. Lodato S, Rouaux C, Quast KB, Jantrachotechatchawan C, Studer M, et al (2011) Excitatory projection neuron subtypes control the distribution of local inhibitory interneurons in the cerebral cortex, Neuron 69(4): 763-779.
106. Dietrich J, Noble M and Mayer Proschel M (2002) Characterization of A2B5+ glial precursor cells from cryopreserved human fetal brain progenitor cells, Glia 40(1): 65-77.
107. Osorio MJ, Mariani JN, Zou L, Schanz SJ, Heffernan K, et al (2023) Glial progenitor cells of the adult human white and grey matter are contextually distinct, Glia 71(3): 524-540.
108. Lau J, Farzi A, Qi Y, Heilbronn R, Mietzsch M, et al, (2018) CART neurons in the arcuate nucleus and lateral hypothalamic area exert differential controls on energy homeostasis, Mol Metab 7: 102-118.
109. Garcia AF, Crummy EA, Webb IG, Nooney MN and Ferguson SM (2021) Distinct populations of cortical pyramidal neurons mediate drug reward and aversion, Nat Commun 12(1): 182.
110. De Zeeuw CI, Simpson JI, Hoogenraad CC, Galjart N, Koekkoek SK, (1998) Microcircuitry and function of the inferior olive, Trends Neurosci 21(9): 391-400.
111. Baumel Y, Jacobson GA and Cohen D (2009) Implications of functional anatomy on information processing in the deep cerebellar nuclei, Front Cell Neurosci 3: 14.
112. Amador Arjona A, Cimadamore F, Huang CT, Wright R, Lewis S, et al (2015) SOX2 primes the epigenetic landscape in neural precursors enabling proper gene activation during hippocampal neurogenesis, Proc Natl Acad Sci U S A 112(15): E1936-E1945.
113. Sun HY, Lyons SA and Dobrunz LE (2005) Mechanisms of target-cell specific short-term plasticity at Schaffer collateral synapses onto interneurones versus pyramidal cells in juvenile rats, J Physiol 568(Pt 3): 815-840.
114. Xu Q, Cobos I, De La Cruz E, Rubenstein JL, Anderson SA (2004) Origins of cortical interneuron subtypes, J Neurosci 24(11): 2612-2622.
115. Kearns NA, Iatrou A, Flood DJ, De Tissera S, Mullaney ZM, et al (2023) Dissecting the human leptomeninges at single-cell resolution, Nat Commun 14(1): 7036.
116. Hill RA and Nishiyama A, (2014) NG2 cells (polydendrocytes): listeners to the neural network with diverse properties, Glia 62(8): 1195-1210.