You're viewing our updated article page. If you need more time to adjust, you can return to the old layout.

PERSPECTIVE article

Front. Neurosci., 10 February 2026

Sec. Neurodegeneration

Volume 20 - 2026 | https://doi.org/10.3389/fnins.2026.1775240

Cerebrospinal fluid dynamics and brain function regulation: from homeostasis to neurological disorders

  • 1. Department of Systems Science, Faculty of Arts and Sciences, Beijing Normal University, Zhuhai, China

  • 2. International Academic Center of Complex Systems, Beijing Normal University, Zhuhai, China

  • 3. School of Systems Science, Beijing Normal University, Beijing, China

Article metrics

View details

522

Views

29

Downloads

Abstract

Cerebrospinal fluid (CSF) is increasingly recognized as an active regulator of brain function rather than a passive mechanical buffer. Beyond its classical roles in cushioning the brain and removing metabolic waste, CSF participates in a tightly coupled system linking neural activity, vascular dynamics, molecular signaling, and tissue mechanics. Here, we present an integrated theoretical framework that unifies three major conceptual strategies in contemporary CSF research: metabolic clearance, neuromodulatory signaling, and bidirectional coupling between fluid dynamics and neural activity. We argue that these processes form a closed-loop regulatory system in which brain state governs CSF flow, while CSF dynamics reciprocally shape neural function and long-term brain health. Disruptions to this integrated CSF-brain system underlie a wide spectrum of neurological disorders, including Alzheimer’s disease, stroke, sleep disorders, and hydrocephalus. By synthesizing evidence across scales and disciplines, this framework provides a coherent conceptual foundation for future experimental, diagnostic, and therapeutic advances targeting CSF physiology.

Introduction

For much of the twentieth century, cerebrospinal fluid (CSF) was regarded as a biologically inert medium whose primary functions were mechanical protection and waste removal (Nabiuni et al., 2012; Gato et al., 2005). This reductionist view is no longer tenable. Advances in neuroimaging, molecular neuroscience, and systems physiology have revealed CSF as a dynamic circulatory and signaling system that is deeply integrated with neural activity, vascular pulsatility, and astroglial function (Jessen et al., 2015; Iliff et al., 2012). Rather than serving merely as background fluid, CSF actively participates in maintaining brain homeostasis, coordinating metabolic processes, and modulating neural circuits.

A central insight driving this paradigm shift is the recognition that CSF dynamics are state-dependent. Cardiac pulsation and respiration provide fundamental drivers of fluid movement (Kiviniemi et al., 2016), but brain-state transitions, particularly the sleep-wake cycle profoundly shape the spatiotemporal patterns of CSF flow (Fultz et al., 2019). These patterns, in turn, regulate solute transport (Iliff et al., 2012), molecular signaling (Nedergaard and Goldman, 2020), and mechanical coupling between brain tissue and its surrounding fluid environment. Understanding CSF function therefore requires a systems-level perspective that integrates fluid dynamics, cellular mechanisms, and electrophysiology.

In this manuscript, we propose an integrated conceptual framework that unifies three dominant strategies in CSF research (Figure 1): (i) metabolic clearance via glymphatic transport (Iliff et al., 2012; Hablitz et al., 2020), (ii) neuromodulatory signaling through CSF-borne molecules (Nedergaard and Goldman, 2020; Myung et al., 2018), and (iii) bidirectional coupling between CSF dynamics and neural activity (Fultz et al., 2019; Bojarskaite et al., 2020). We argue that these strategies represent interdependent components of a single regulatory loop rather than independent phenomena. This unified view clarifies the pathophysiological basis of diverse neurological disorders from Alzheimer’s disease, where impaired glymphatic clearance is linked to sleep disruption and amyloid-β accumulation (Ju et al., 2014; Holth et al., 2019), to idiopathic intracranial hypertension and normal pressure hydrocephalus, where altered fluid dynamics directly impact neural function (de Souza Bezerra et al., 2018) and highlights new opportunities for diagnosis and therapy.

FIGURE 1

Infographic illustrating cerebrospinal fluid (CSF) dynamics and brain function, showing CSF influx via arteries, Aquaporin-4 (AQP4) transport, interstitial fluid flow, solute clearance, and links to Alzheimer’s disease, hydrocephalus, and sleep disorders.

Strategies for studying CSF dynamics and brain function. Schematic overview of CSF production and circulation, the glymphatic clearance pathway, CSF-brain signaling interfaces, and clinical applications in neurological disorders.

CSF production, circulation, and state-dependent dynamics

Cerebrospinal fluid is primarily produced by the choroid plexus at a rate of approximately 500–600 mL per day in adults, resulting in complete turnover several times daily (Oreskovic and Klarica, 2010; Brinker et al., 2014). From the ventricular system, CSF circulates through subarachnoid spaces and perivascular compartments before being absorbed via arachnoid granulations and meningeal lymphatic pathways (Jessen et al., 2015; Iliff et al., 2012). Importantly, this circulation is not passive. CSF motion is driven by arterial pulsatility, respiratory pressure gradients, and slow volumetric changes in brain tissue associated with neural activity (Plog and Nedergaard, 2018; Ringstad et al., 2017; Mestre et al., 2018; Dreha-Kulaczewski et al., 2015).

Sleep represents a critical modulatory state for CSF dynamics. During slow-wave sleep, reductions in noradrenergic tone lead to expansion of the interstitial space, facilitating increased CSF influx and enhanced solute transport (Kiviniemi et al., 2016; Lee et al., 2015). These state-dependent changes underscore the principle that CSF flow is actively regulated by brain physiology rather than imposed solely by peripheral forces (Kiviniemi et al., 2016; Ringstad et al., 2017).

Metabolic clearance as an emergent systems process

The discovery of the glymphatic system provided a mechanistic explanation for how CSF participates in metabolic waste removal (Iliff et al., 2013a; Xie et al., 2013). Convective CSF flow along perivascular spaces enables the clearance of interstitial solutes, including amyloid-β and tau (Nedergaard and Goldman, 2020; Iliff et al., 2013a; Abbott et al., 2018). Astrocytic aquaporin-4 (AQP4) channels, polarized at perivascular end-feet, play a critical role in facilitating fluid exchange between CSF and interstitial compartments (Harrison et al., 2018; Zeppenfeld et al., 2017).

Within the integrated framework proposed here, glymphatic clearance is not an isolated function but an emergent property of coordinated neural, vascular, and glial activity (Nedergaard and Goldman, 2020; Rasmussen et al., 2022; Simon and Iliff, 2016). Neural oscillations and vascular pulsatility drive CSF motion, while astrocytic regulation of water permeability tunes exchange efficiency (Hablitz et al., 2020; Munk et al., 2019; Rasmussen et al., 2022). Disruptions at any level, sleep fragmentation, vascular stiffening, or loss of AQP4 polarity can impair clearance and promote pathological protein accumulation (Nedergaard and Goldman, 2020; Munk et al., 2019; Zeppenfeld et al., 2017; Simon and Iliff, 2016).

CSF as a neuromodulatory and signaling medium

In addition to transporting solutes, CSF serves as a distributed signaling medium containing hormones, growth factors, cytokines, metabolites, and extracellular vesicles (Lehtinen et al., 2011; Wu et al., 2020; Candelario and Steindler, 2014). The molecular composition of CSF varies with circadian rhythm, behavioral state, and disease, reflecting ongoing neural and systemic processes (Blennow and Zetterberg, 2018; Johanson et al., 2008; Sankowski et al., 2015). Factors such as insulin-like growth factor-1 and brain-derived neurotrophic factor link CSF composition to synaptic plasticity, myelination, and cognitive function (Lehtinen et al., 2011; Louveau et al., 2015; Da Mesquita et al., 2018).

Crucially, CSF signaling feeds back onto neural circuits, influencing excitability and network synchronization (Johanson et al., 2008; Sankowski et al., 2015; Simon et al., 2017). Through this feedback, CSF composition can modulate the same brain states that govern its own circulation, embedding signaling within the broader CSF-brain regulatory loop (Blennow and Zetterberg, 2018; Louveau et al., 2015; Wu et al., 2020).

Bidirectional coupling between CSF dynamics and neural activity

Emerging evidence demonstrates tight coupling between CSF motion and neural oscillations (Fultz et al., 2019; Hablitz and Nedergaard, 2021). Functional imaging studies reveal coordinated fluctuations in CSF flow, cerebral blood volume, and electrophysiological activity, particularly during sleep (Thomas, 2019; Iliff et al., 2013b; Kedarasetti et al., 2020). These observations suggest that CSF dynamics are actively synchronized with neural rhythms to optimize metabolic clearance and molecular transport (Fultz et al., 2019; Holter et al., 2017; van Veluw et al., 2020).

Pathological alterations in CSF dynamics directly perturb neural function (Mortensen et al., 2019). In normal pressure hydrocephalus, abnormal CSF pulsatility is associated with slowed cortical rhythms and cognitive impairment, which can be partially reversed by restoring CSF flow (Holter et al., 2017; Asgari et al., 2016; Mortensen et al., 2019). Such findings highlight bidirectional coupling as the organizing principle linking clearance and signaling within a unified system (Fultz et al., 2019; van Veluw et al., 2020; Hablitz and Nedergaard, 2021; Winer et al., 2019).

Neurological disorders as failures of the integrated CSF-brain system

From this systems perspective, neurological diseases can be reinterpreted as breakdowns of integrated CSF-brain regulation (Tarasoff-Conway et al., 2015; de Leon et al., 2017; Bothwell et al., 2019). In Alzheimer’s disease, impaired state-dependent CSF flow and glymphatic clearance promote toxic protein accumulation (Nedergaard and Goldman, 2020; Tarasoff-Conway et al., 2015; Reeves et al., 2020), while altered CSF signaling further disrupts synaptic function (de Leon et al., 2017; Yun et al., 2020). In stroke and traumatic brain injury, dysregulated CSF dynamics contribute to cerebral edema and secondary injury (Yun et al., 2020; Gaberel et al., 2014). Sleep disorders impair CSF-mediated clearance, potentially accelerating neurodegeneration (Lee et al., 2015; Xie et al., 2013) while hydrocephalus represents a global failure of CSF circulation and absorption (Strahle et al., 2011; Karimy et al., 2017; Jiang et al., 2017).

Viewing these conditions through a unified framework emphasizes shared mechanisms and suggests that therapeutic interventions targeting CSF dynamics may yield broad benefits across traditionally distinct disorders (Tarasoff-Conway et al., 2015; Reeves et al., 2020; Bothwell et al., 2019).

Technological and therapeutic implications

The emergence of an integrated CSF-brain framework has been accompanied by rapid technological advances that now make it possible to interrogate, model, and manipulate CSF dynamics with unprecedented precision. These developments are accelerating the translation of conceptual insights into clinical and therapeutic applications.

Advanced Imaging and Quantification of CSF Dynamics: non-invasive neuroimaging has become central to characterizing CSF circulation and its coupling to brain activity. Phase-contrast MRI enables quantitative measurement of CSF flow velocities and pulsatility across ventricular and subarachnoid compartments (Battal et al., 2011), while time-resolved three-dimensional sequences provide spatial maps of flow vectors (Yamada et al., 2008). Diffusion-based techniques, including tensor-valued diffusion encoding, allow indirect assessment of perivascular space geometry and glymphatic transport efficiency (Schirge et al., 2025; Taoka et al., 2017). When combined with functional MRI and electroencephalography, these approaches enable simultaneous mapping of neural activity, vascular dynamics, and CSF motion, offering a systems-level view of fluid-brain interactions (Fultz et al., 2019).

Emerging ultra-fast imaging sequences and low-dose contrast protocols hold promise for capturing state-dependent CSF dynamics in humans, including sleep-associated oscillations that were previously accessible only in animal models (Ringstad et al., 2017; Lee et al., 2015). Such advances are essential for validating glymphatic function as a clinically relevant biomarker (Iliff et al., 2012).

Implantable and Wearable Monitoring Technologies: Miniaturized, wireless implantable sensors are transforming the monitoring of intracranial pressure, CSF composition, and biochemical markers in real time (Deng et al., 2025; Zhou et al., 2025). These devices allow continuous assessment of CSF dynamics in patients with hydrocephalus, traumatic brain injury, or subarachnoid hemorrhage, enabling personalized and adaptive management strategies. Parallel advances in wearable sleep and respiration monitoring provide complementary data on physiological drivers of CSF flow, facilitating integrated analysis across behavioral and fluid-dynamic domains (Chong et al., 2022).

Computational Modeling and Digital Twins: computational models integrating fluid mechanics, tissue biomechanics, vascular dynamics, and electrophysiology are increasingly used to interpret experimental data and predict therapeutic outcomes (Lakin et al., 2003; Vinje et al., 2019). Patient-specific models derived from imaging data enable simulation of CSF flow under different physiological and pathological conditions, supporting surgical planning and optimization of shunt placement in hydrocephalus (Sweetman and Linninger, 2011; Spijkerman et al., 2019). More broadly, the development of “digital twin” models of the CSF-brain system may allow in silico testing of interventions aimed at restoring normal fluid-neural coupling (Kissas et al., 2020).

Cerebrospinal fluid-Targeted Therapeutic Strategies: the recognition of CSF as an active regulatory medium has opened new therapeutic avenues. Pharmacological modulation of CSF production at the choroid plexus, for example through targeting ion transporters or metabolic pathways (Damkier et al., 2013), offers alternatives to purely mechanical interventions. Modulation of astrocytic AQP4 expression or polarization represents another promising strategy to enhance glymphatic clearance (Iliff et al., 2012) or control cerebral edema (Papadopoulos et al., 2004), though achieving spatial and temporal specificity remains a challenge (Rasmussen et al., 2022).

Beyond modulation, the CSF circulation itself is being harnessed as a therapeutic delivery route. Intrathecal and intraventricular drug delivery bypass the blood brain barrier and enable global distribution of small molecules, biologics, and gene therapy vectors (Pardridge, 2020; Bleyer and Poplack, 1979; Peyrl et al., 2014; Maurizi et al., 2014; Al Shaer et al., 2024; Greenberg et al., 2022; D’Avanzo et al., 2020). Convection-enhanced delivery (Vogelbaum and Aghi, 2015) and nanoparticle-based carriers (Ekhator et al., 2023) further exploit CSF flow patterns to improve targeting efficiency and reduce systemic toxicity. These approaches are particularly attractive for diffuse neurodegenerative diseases (Kariolis et al., 2020) and leptomeningeal pathologies (Glantz et al., 1999).

Neuromodulation and State-Based Interventions: non-invasive neuromodulatory techniques, including transcranial electrical and magnetic stimulation, are increasingly explored as tools to influence CSF dynamics indirectly by altering neural and vascular rhythms (Rasmussen et al., 2022). By entraining slow oscillations or modifying sleep architecture, such interventions may enhance glymphatic clearance and optimize CSF-mediated signaling (Xie et al., 2013). Behavioral interventions, especially sleep optimization and respiratory therapy, represent low-risk strategies that directly leverage physiological drivers of CSF flow (Holth et al., 2017; Lilius et al., 2019).

Collectively, these technological and therapeutic developments reflect a shift from treating CSF abnormalities as isolated mechanical problems to targeting the CSF-brain system as an integrated, dynamic regulator of neural health.

Conclusion

Cerebrospinal fluid is a central component of an integrated brain regulatory system that links metabolism, signaling, and mechanics through bidirectional coupling with neural activity. Recognizing clearance, neuromodulation, and fluid-neural interactions as elements of a single closed-loop framework provides a coherent theoretical foundation for future research. By targeting CSF physiology as a systems-level process, new strategies may emerge for preserving brain health and treating neurological disease.

Statements

Data availability statement

The original contributions presented in this study are included in this article/supplementary material, further inquiries can be directed to the corresponding author.

Author contributions

YY: Writing – original draft, Writing – review & editing. HJ: Writing – original draft, Writing – review & editing. HL: Funding acquisition, Resources, Supervision, Writing – review & editing.

Funding

The author(s) declared that financial support was received for this work and/or its publication. This work was supported by the National Natural Science Foundation of China (NSFC) under grant number 32371079.

Conflict of interest

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The author(s) declared that generative AI was not used in the creation of this manuscript.

Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

References

  • 1

    Abbott N. J. Pizzo M. E. Preston J. E. Janigro D. Thorne R. G. (2018). The role of brain barriers in fluid movement in the CNS: is there a ‘glymphatic’ system?Acta Neuropathologica135387407. 10.1007/s00401-018-1812-4

  • 2

    Al Shaer D. Al Musaimi O. Albericio F. de la Torre B. G. (2024). 2023 FDA TIDES (Peptides and Oligonucleotides) harvest.Pharmaceuticals17:243. 10.3390/ph17020243

  • 3

    Asgari M. de Zelicourt D. Kurtcuoglu V. (2016). Glymphatic solute transport does not require bulk flow.Sci. Rep.6:38635. 10.1038/srep38635

  • 4

    Battal B. Kocaoglu M. Bulakbasi N. Husmen G. Sanal H. T. Tayfun C. (2011). Cerebrospinal fluid flow imaging by using phase-contrast MR technique.Br. J. Radiol.84758765. 10.1259/bjr/66206791

  • 5

    Blennow K. Zetterberg H. (2018). The past and the future of Alzheimer’s disease fluid biomarkers.J. Alzheimers Dis.6211251140. 10.3233/jad-170773

  • 6

    Bleyer W. A. Poplack D. G. (1979). Intra-ventricular versus intralumbar methotrexate for central-nervous-system leukemia-prolonged remission with the ommaya reservoir.Med. Pediatr. Oncol.6207213. 10.1002/mpo.2950060304

  • 7

    Bojarskaite L. Bjornstad D. M. Pettersen K. H. Cunen C. Hermansen G. H. Abjorsbraten K. S. et al (2020). Astrocytic Ca2+ signaling is reduced during sleep and is involved in the regulation of slow wave sleep.Nat. Commun.11:3240. 10.1038/s41467-020-17062-2

  • 8

    Bothwell S. W. Janigro D. Patabendige A. (2019). Cerebrospinal fluid dynamics and intracranial pressure elevation in neurological diseases.Fluids Barriers Cns16:9. 10.1186/s12987-019-0129-6

  • 9

    Brinker T. Stopa E. Morrison J. Klinge P. (2014). A new look at cerebrospinal fluid circulation.Fluids Barriers CNS11:10. 10.1186/2045-8118-11-10

  • 10

    Candelario K. M. Steindler D. A. (2014). The role of extracellular vesicles in the progression of neurodegenerative disease and cancer.Trends Mol. Med.20368374. 10.1016/j.molmed.2014.04.003

  • 11

    Chong P. L. H. Garic D. Shen M. D. Lundgaard I. Schwichtenberg A. J. (2022). Sleep, cerebrospinal fluid, and the glymphatic system: A systematic review.Sleep Med. Rev.61:101572. 10.1016/j.smrv.2021.101572

  • 12

    Da Mesquita S. Louveau A. Vaccari A. Smirnov I. Cornelison R. C. Kingsmore K. M. et al (2018). Functional aspects of meningeal lymphatics in ageing and Alzheimer’s disease.Nature560185191. 10.1038/s41586-018-0368-8

  • 13

    Damkier H. H. Brown P. D. Praetorius J. (2013). Cerebrospinal fluid secretion by the choroid plexus.Physiol. Rev.9318471892. 10.1152/physrev.00004.2013

  • 14

    D’Avanzo F. Rigon L. Zanetti A. Tomanin R. (2020). Mucopolysaccharidosis type II: One hundred years of research, diagnosis, and treatment.Int. J. Mol. Sci.21:1258. 10.3390/ijms21041258

  • 15

    de Leon M. J. Li Y. Okamura N. Tsui W. H. Saint-Louis L. A. Glodzik L. et al (2017). Cerebrospinal fluid clearance in Alzheimer disease measured with dynamic PET.J. Nuclear Med.5814711476. 10.2967/jnumed.116.187211

  • 16

    de Souza Bezerra M. L. Andorinho, de Freitas Ferreira A. C. de Oliveira-Souza R. (2018). Pseudotumor cerebri and glymphatic dysfunction.Front. Neurol.8:734. 10.3389/fneur.2017.00734

  • 17

    Deng M. Yin S. Wu H. Zhang Z. Qi X. Guo S. et al (2025). Minimally invasive micro-hole intervention for wireless intracranial pressure measurement.Adv. Healthc. Mate.10.1002/adhm.202505164Online ahead of print.

  • 18

    Dreha-Kulaczewski S. Joseph A. A. Merboldt K.-D. Ludwig H.-C. Gaertner J. Frahm J. (2015). Inspiration is the major regulator of human CSF flow.J. Neurosci.3524852491. 10.1523/jneurosci.3246-14.2015

  • 19

    Ekhator C. Qureshi M. Q. Zuberi A. W. Hussain M. Sangroula N. Yerra S. et al (2023). Advances and opportunities in nanoparticle drug delivery for central nervous system disorders: A review of current advances.Cureus15:e44302. 10.7759/cureus.44302

  • 20

    Fultz N. E. Bonmassar G. Setsompop K. Stickgold R. A. Rosen B. R. Polimeni J. R. et al (2019). Coupled electrophysiological, hemodynamic, and cerebrospinal fluid oscillations in human sleep.Science366628631. 10.1126/science.aax5440

  • 21

    Gaberel T. Gakuba C. Goulay R. De Lizarrondo S. M. Hanouz J.-L. Emery E. et al (2014). Impaired glymphatic perfusion after strokes revealed by contrast-enhanced MRI a new target for fibrinolysis?Stroke4530923096. 10.1161/strokeaha.114.006617

  • 22

    Gato A. Moro J. A. Alonso M. I. Bueno D. De La Mano A. Martín C. (2005). Embryonic cerebrospinal fluid regulates neuroepithelial survival, proliferation, and neurogenesis in chick embryos.Anat. Rec. A. Discov. Mol. Cell. Evol. Biol.284475484. 10.1002/ar.a.20185

  • 23

    Glantz M. J. Jaeckle K. A. Chamberlain M. C. Phuphanich S. Recht L. Swinnen L. J. et al (1999). A randomized controlled trial comparing intrathecal sustained-release cytarabine (DepoCyt) to intrathecal methotrexate in patients with neoplastic meningitis from solid tumors.Clin. Cancer Res.533943402.

  • 24

    Greenberg S. M. Ziai W. C. Cordonnier C. Dowlatshahi D. Francis B. Goldstein J. N. et al (2022). 2022 guideline for the management of patients with spontaneous intracerebral hemorrhage: A guideline from the american heart association/American stroke association.Stroke53E282E361. 10.1161/str.0000000000000407

  • 25

    Hablitz L. M. Nedergaard M. (2021). The glymphatic system: A novel component of fundamental neurobiology.J. Neurosci.4176987711. 10.1523/jneurosci.0619-21.2021

  • 26

    Hablitz L. M. Pla V. Giannetto M. Vinitsky H. S. Staeger F. F. Metcalfe T. et al (2020). Circadian control of brain glymphatic and lymphatic fluid flow.Nat. Commun.11:4411. 10.1038/s41467-020-18115-2

  • 27

    Harrison I. F. Siow B. Akilo A. B. Evans P. G. Ismail O. Ohene Y. et al (2018). Non-invasive imaging of CSF-mediated brain clearance pathways via assessment of perivascular fluid movement with diffusion tensor MRI.Elife7:e34028. 10.7554/eLife.34028

  • 28

    Holter K. E. Kehlet B. Devor A. Sejnowski T. J. Dale A. M. Omholt S. W. et al (2017). Interstitial solute transport in 3D reconstructed neuropil occurs by diffusion rather than bulk flow.Proc. Natl. Acad,. Sci. U S A.11498949899. 10.1073/pnas.1706942114

  • 29

    Holth J. K. Fritschi S. K. Wang C. Pedersen N. P. Cirrito J. R. Mahan T. E. et al (2019). The sleep-wake cycle regulates brain interstitial fluid tau in mice and CSF tau in humans.Science363880883. 10.1126/science.aav2546

  • 30

    Holth J. Patel T. Holtzman D. M. (2017). Sleep in Alzheimer’s disease - beyond amyloid.Neurobiol. Sleep Circadian Rhythms2414. 10.1016/j.nbscr.2016.08.002

  • 31

    Iliff J. J. Lee H. Yu M. Feng T. Logan J. Nedergaard M. et al (2013a). Brain-wide pathway for waste clearance captured by contrast-enhanced MRI.J. Clin. Invest.12312991309. 10.1172/jci67677

  • 32

    Iliff J. J. Wang M. Liao Y. Plogg B. A. Peng W. Gundersen G. A. et al (2012). A paravascular pathway facilitates CSF Flow through the brain parenchyma and the clearance of interstitial solutes, including amyloid β.Sci. Transl. Med.4:14ra111. 10.1126/scitranslmed.3003748

  • 33

    Iliff J. J. Wang M. Zeppenfeld D. M. Venkataraman A. Plog B. A. Liao Y. et al (2013b). Cerebral arterial pulsation drives paravascular CSF-interstitial fluid exchange in the murine brain.J. Neurosci.331819018199. 10.1523/jneurosci.1592-13.2013

  • 34

    Jessen N. A. Munk A. S. F. Lundgaard I. Nedergaard M. (2015). The glymphatic system: A beginner’s guide.Neurochem. Res.4025832599. 10.1007/s11064-015-1581-6

  • 35

    Jiang Q. Zhang L. Ding G. Davoodi-Bojd E. Li Q. Li L. et al (2017). Impairment of the glymphatic system after diabetes.J. Cereb. Blood Flow Metab.3713261337. 10.1177/0271678x16654702

  • 36

    Johanson C. E. Duncan J. A. III Klinge P. M. Brinker T. Stopa E. G. Silverberg G. D. (2008). Multiplicity of cerebrospinal fluid functions: New challenges in health and disease.Cerebrospinal Fluid Res.5:10. 10.1186/1743-8454-5-10

  • 37

    Ju Y.-E. S. Lucey B. P. Holtzman D. M. (2014). Sleep and Alzheimer disease pathology-a bidirectional relationship.Nat. Rev. Neurol.10115119. 10.1038/nrneurol.2013.269

  • 38

    Karimy J. K. Zhang J. Kurland D. B. Theriault B. C. Duran D. Stokum J. A. et al (2017). Inflammation-dependent cerebrospinal fluid hypersecretion by the choroid plexus epithelium in posthemorrhagic hydrocephalus.Nat. Med.239971003. 10.1038/nm.4361

  • 39

    Kariolis M. S. Wells R. C. Getz J. A. Kwan W. Mahon C. S. Tong R. et al (2020). Brain delivery of therapeutic proteins using an Fc fragment blood-brain barrier transport vehicle in mice and monkeys.Sci. Transl. Med.12:aay1359. 10.1126/scitranslmed.aay1359

  • 40

    Kedarasetti R. T. Turner K. L. Echagarruga C. Gluckman B. J. Drew P. J. Costanzo F. (2020). Functional hyperemia drives fluid exchange in the paravascular space.Fluids Barriers CNS17:52. 10.1186/s12987-020-00214-3

  • 41

    Kissas G. Yang Y. Hwuang E. Witschey W. R. Detre J. A. Perdikaris P. (2020). Machine learning in cardiovascular flows modeling: Predicting arterial blood pressure from non-invasive 4D flow MRI data using physics-informed neural networks.Comput. Methods Appl. Mechanics Eng.358:112623. 10.1016/j.cma.2019.112623

  • 42

    Kiviniemi V. Wang X. Korhonen V. Keinanen T. Tuovinen T. Autio J. et al (2016). A Ultra-fast magnetic resonance encephalography of physiological brain activity - Glymphatic pulsation mechanisms?J. Cereb. Blood Flow Metab.3610331045. 10.1177/0271678x15622047

  • 43

    Lakin W. D. Stevens S. A. Tranmer B. I. Penar P. L. (2003). A whole-body mathematical model for intracranial pressure dynamics.J. Math. Biol.46347383. 10.1007/s00285-002-0177-3

  • 44

    Lee H. Xie L. Yu M. Kang H. Feng T. Deane R. et al (2015). The effect of body posture on brain glymphatic transport.J. Neurosci.351103411044. 10.1523/jneurosci.1625-15.2015

  • 45

    Lehtinen M. K. Zappaterra M. W. Chen X. Yang Y. J. Hill A. D. Lun M. et al (2011). The cerebrospinal fluid provides a proliferative niche for neural progenitor cells.Neuron69893905. 10.1016/j.neuron.2011.01.023

  • 46

    Lilius T. O. Blomqvist K. Hauglund N. L. Liu G. Staeger F. F. Baerentzen S. et al (2019). Dexmedetomidine enhances glymphatic brain delivery of intrathecally administered drugs.J. Controlled Release3042938. 10.1016/j.jconrel.2019.05.005

  • 47

    Louveau A. Smirnov I. Keyes T. J. Eccles J. D. Rouhani S. J. Peske J. D. et al (2015). Structural and functional features of central nervous system lymphatic vessels.Nature523337341. 10.1038/nature14432

  • 48

    Maurizi P. Russo I. Rizzo D. Chiaretti A. Coccia P. Attina G. et al (2014). Safe lumbar puncture under analgo-sedation in children with acute lymphoblastic leukemia.Int. J. Clin. Oncol.19173177. 10.1007/s10147-013-0521-1

  • 49

    Mestre H. Tithof J. Du T. Song W. Peng W. Sweeney A. M. et al (2018). Flow of cerebrospinal fluid is driven by arterial pulsations and is reduced in hypertension.Nat. Commun.9:4878. 10.1038/s41467-018-07318-3

  • 50

    Mortensen K. N. Sanggaard S. Mestre H. Lee H. Kostrikov S. Xavier A. L. R. et al (2019). Impaired glymphatic transport in spontaneously hypertensive rats.J. Neurosci.3963656377. 10.1523/jneurosci.1974-18.2019

  • 51

    Munk A. S. Wang W. Bechet N. B. Eltanahy A. M. Cheng A. X. Sigurdsson B. et al (2019). PDGF-B is required for development of the glymphatic system.Cell Rep.2629552969. 10.1016/j.celrep.2019.02.050

  • 52

    Myung J. Schmal C. Hong S. Tsukizawa Y. Rose P. Zhang Y. et al (2018). The choroid plexus is an important circadian clock component.Nat. Commun.9:1062. 10.1038/s41467-018-03507-2

  • 53

    Nabiuni M. Rasouli J. Parivar K. Kochesfehani H. M. Irian S. Miyan J. A. (2012). In vitro effects of fetal rat cerebrospinal fluid on viability and neuronal differentiation of PC12 cells.Fluids Barriers CNS9:8. 10.1186/2045-8118-9-8

  • 54

    Nedergaard M. Goldman S. A. (2020). Glymphatic failure as a final common pathway to dementia.Science3705056. 10.1126/science.abb8739

  • 55

    Oreskovic D. Klarica M. (2010). The formation of cerebrospinal fluid: Nearly a hundred years of interpretations and misinterpretations.Brain Res. Rev.64241262. 10.1016/j.brainresrev.2010.04.006

  • 56

    Papadopoulos M. C. Manley G. T. Krishna S. Verkman A. S. (2004). Aquaporin-4 facilitates reabsorption of excess fluid in vasogenic brain edema.Faseb J.1812911293. 10.1096/fj.04-1723fje

  • 57

    Pardridge W. M. (2020). Blood-brain barrier and delivery of protein and gene therapeutics to brain.Front. Aging Neurosci.11:373. 10.3389/fnagi.2019.00373

  • 58

    Peyrl A. Chocholous M. Azizi A. A. Czech T. Dorfer C. Mitteregger D. et al (2014). Safety of Ommaya reservoirs in children with brain tumors: A 20-year experience with 5472 intraventricular drug administrations in 98 patients.J. Neuro-Oncol.120139145. 10.1007/s11060-014-1531-1

  • 59

    Plog B. A. Nedergaard M. (2018). The glymphatic system in central nervous system health and disease: Past, present, and future.Annu. Rev. Pathol. Mech. Dis.13379394. 10.1146/annurev-pathol-051217-111018

  • 60

    Rasmussen M. K. Mestre H. Nedergaard M. (2022). Fluid transport in the brain.Physiol. Rev.10210251151. 10.1152/physrev.00031.2020

  • 61

    Reeves B. C. Karimy J. K. Kundishora A. J. Mestre H. Cerci H. M. Matouk C. et al (2020). Glymphatic system impairment in Alzheimer’s disease and idiopathic normal pressure hydrocephalus.Trends Mol. Med.26285295. 10.1016/j.molmed.2019.11.008

  • 62

    Ringstad G. Vatnehol S. A. S. Eide P. K. (2017). Glymphatic MRI in idiopathic normal pressure hydrocephalus.Brain14026912705. 10.1093/brain/awx191

  • 63

    Sankowski R. Mader S. Valdes-Ferrer S. I. (2015). Systemic inflammation and the brain: Novel roles of genetic, molecular, and environmental cues as drivers of neurodegeneration.Front. Cell. Neurosci.9:28. 10.3389/fncel.2015.00028

  • 64

    Schirge P. M. Perneczky R. Taoka T. Ruiz-Rizzo A. L. Ersoezlue E. Forbrig R. et al (2025). Perivascular space and white matter hyperintensities in Alzheimer’s disease: Associations with disease progression and cognitive function.Alzheimers Res. Ther.17:62. 10.1186/s13195-025-01707-9

  • 65

    Simon D. W. McGeachy M. J. Bayir H. Clark R. S. B. Loane D. J. Kochanek P. M. (2017). The far-reaching scope of neuroinflammation after traumatic brain injury.Nat. Rev. Neurol.13171191. 10.1038/nrneurol.2017.13

  • 66

    Simon M. J. Iliff J. J. (2016). Regulation of cerebrospinal fluid (CSF) flow in neurodegenerative, neurovascular and neuroinflammatory disease.Biochim. Biophys. Acta-Mol. Basis Dis.1862442451. 10.1016/j.bbadis.2015.10.014

  • 67

    Spijkerman J. M. Geurts L. J. Siero J. C. W. Hendrikse J. Luijten P. R. Zwanenburg J. J. M. (2019). Phase contrast MRI measurements of net cerebrospinal fluid flow through the cerebral aqueduct are confounded by respiration.J. Magnetic Resonance Imaging49433444. 10.1002/jmri.26181

  • 68

    Strahle J. Muraszko K. M. Kapurch J. Bapuraj J. R. Garton H. J. L. Maher C. O. (2011). Chiari malformation Type I and syrinx in children undergoing magnetic resonance imaging clinical article.J. Neurosurg. Pediatr.8205213. 10.3171/2011.5.Peds1121

  • 69

    Sweetman B. Linninger A. A. (2011). Cerebrospinal fluid flow dynamics in the central nervous system.Ann. Biomed. Eng.39484496. 10.1007/s10439-010-0141-0

  • 70

    Taoka T. Masutani Y. Kawai H. Nakane T. Matsuoka K. Yasuno F. et al (2017). Evaluation of glymphatic system activity with the diffusion MR technique: Diffusion tensor image analysis along the perivascular space (DTI-ALPS) in Alzheimer’s disease cases.Jpn. J. Radiol.35172178. 10.1007/s11604-017-0617-z

  • 71

    Tarasoff-Conway J. M. Carare R. O. Osorio R. S. Glodzik L. Butler T. Fieremans E. et al (2015). Clearance systems in the brain-implications for Alzheimer disease.Nat. Rev. Neurol.11457470. 10.1038/nrneurol.2015.119

  • 72

    Thomas J. H. (2019). Fluid dynamics of cerebrospinal fluid flow in perivascular spaces.J. R. Soc. Interface16:20190572. 10.1098/rsif.2019.0572

  • 73

    van Veluw S. J. Hou S. S. Calvo-Rodriguez M. Arbel-Ornath M. Snyder A. C. Frosch M. P. et al (2020). Vasomotion as a driving force for paravascular clearance in the awake mouse brain.Neuron105549561. 10.1016/j.neuron.2019.10.033

  • 74

    Vinje V. Ringstad G. Lindstrom E. K. Valnes L. M. Rognes M. E. Eide P. K. et al (2019). Respiratory influence on cerebrospinal fluid flow-a computational study based on long-term intracranial pressure measurements.Sci. Rep.9:9732. 10.1038/s41598-019-46055-5

  • 75

    Vogelbaum M. A. Aghi M. K. (2015). Convection-enhanced delivery for the treatment of glioblastoma.Neuro-Oncology17II3II8. 10.1093/neuonc/nou354

  • 76

    Winer J. R. Mander B. A. Helfrich R. F. Maass A. Harrison T. M. Baker S. L. et al (2019). Sleep as a potential biomarker of Tau and β-amyloid burden in the human brain.J. Neurosci.3963156324. 10.1523/jneurosci.0503-19.2019

  • 77

    Wu C.-Y. Bawa K. K. Ouk M. Leung N. Yu D. Lanctot K. L. et al (2020). Neutrophil activation in Alzheimer’s disease and mild cognitive impairment: A systematic review and meta-analysis of protein markers in blood and cerebrospinal fluid.Ageing Res. Rev.62:101130. 10.1016/j.arr.2020.101130

  • 78

    Xie L. Kang H. Xu Q. Chen M. J. Liao Y. Thiyagarajan M. et al (2013). Sleep drives metabolite clearance from the adult brain.Science342373377. 10.1126/science.1241224

  • 79

    Yamada S. Miyazaki M. Kanazawa H. Higashi M. Morohoshi Y. Bluml S. et al (2008). Visualization of cerebrospinal fluid movement with spin labeling at MR imaging: preliminary results in normal and pathophysiologic conditions.Radiology249644652. 10.1148/radiol.2492071985

  • 80

    Yun J.-Y. Boedhoe P. S. W. Vriend C. Jahanshad N. Abe Y. Ameis S. H. et al (2020). Brain structural covariance networks in obsessive-compulsive disorder: A graph analysis from the ENIGMA Consortium.Brain143684700. 10.1093/brain/awaa001

  • 81

    Zeppenfeld D. M. Simon M. Haswell D. D’Abreo D. Murchison C. Quinn J. F. et al (2017). Association of perivascular localization of aquaporin-4 with cognition and Alzheimer disease in aging brains.JAMA Neurol.749199. 10.1001/jamaneurol.2016.4370

  • 82

    Zhou L. Liu P. Liu J. Yuan W. Wu Z. Xu D. et al (2025). Wireless battery-free ultrathin lithium-niobate resonator as wearable and implantable electronics for continuous monitoring of mechanical vital signs.Nat. Commun.17:642. 10.1038/s41467-025-67413-0

Summary

Keywords

brain function, cerebrospinal fluid, clinical medicine, fluid dynamics, neuroscience

Citation

Yang Y, Jia H and Liu H (2026) Cerebrospinal fluid dynamics and brain function regulation: from homeostasis to neurological disorders. Front. Neurosci. 20:1775240. doi: 10.3389/fnins.2026.1775240

Received

25 December 2025

Revised

28 January 2026

Accepted

28 January 2026

Published

10 February 2026

Volume

20 - 2026

Edited by

Miren Altuna, Fundación CITA Alzhéimer, Spain

Reviewed by

Tetsuro Ishida, Independent Researcher, Sapporo, Japan

Updates

Copyright

*Correspondence: He Liu,

†These authors have contributed equally to this work

Disclaimer

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Outline

Figures

Cite article

Copy to clipboard


Export citation file


Share article

Article metrics