As the central regulator of the human body, the brain orchestrates a wide range of vital physiological and cognitive functions. Accordingly, brain research spans multiple disciplines, including molecular biology, cellular neuroscience, bioelectrical signaling, and functional imaging. Among these, biomechanics plays a critical yet often underappreciated role. Understanding the brain’s mechanical behavior is essential for uncovering fundamental physiological and pathological processes, such as cortical folding during brain development [[1], [2], [3], [4], [5], [6]], traumatic brain injury (TBI) [7,8], and neurological disease progression [9,10]. For example, studies have shown that cortical folding arises from mechanical buckling, driven by compressive forces generated through differential growth between gray and white matter [[11], [12], [13]]. In the case of TBI, external impacts induce rapid and excessive shear deformation, leading to immediate tissue damage and long-term degeneration [[14], [15], [16]]. Similarly, neurodegenerative diseases such as Alzheimer’s disease (AD) involve progressive tissue degradation, often initiated by aging-related mechanical changes or the spread of toxic proteins [10,17]. Beyond its role in mechanical understanding, biomechanics also holds increasing promise in brain disorders diagnosis. Variations in tissue stiffness have been correlated with pathological conditions such as brain tumors [10,17], epilepsy [18,19], and dementia [20], which offers opportunities for noninvasive disease detection and monitoring. Accurate characterization of brain mechanical properties is therefore indispensable for effectively analyzing the underlying mechanics of these complex phenomena and supporting clinical applications.

Mechanical testing of brain tissue, however, presents significant challenges due to the tissue’s complex mechanical characteristics. Brain tissue is ultrasoft, fragile, biphasic, and exhibits pronounced anatomical and microstructural heterogeneity [21]. These attributes complicate both sample preparation and experimental execution. For instance, its fragility constrains the range of applicable deformation to preserve tissue integrity during tests [22,23]. Anatomical variability restricts consistent sampling, while the ultrasoft nature and potential dehydration of fluidic components can cause dimensional change under the tissue’s weight [[24], [25], [26]]. Over the past decades, a variety of testing techniques have been developed to assess brain mechanics at different spatial and temporal scales. These techniques ensure diverse characterizations in brain tissue tailored to specific research objectives. Atomic force microscopy (AFM), for example, enables the measurement of cellular and subcellular mechanical properties, thereby facilitating the investigation of the microstructural relevance to macroscale brain properties [27]. Indentation (IND) offers a versatile platform for probing brain mechanical properties, enabling the assessment of spatially resolved modulus and time-dependent viscoelastic behaviors [28]. Oscillatory shear testing (OST) allows for the evaluation of frequency-dependent viscoelastic properties, aiding the study of the underlying biomechanism in TBI [29]. Meanwhile, continuous stress-strain data collected through axial mechanical testing (AMT) support the development of hyperelastic constitutive models [30], which are essential for simulating convoluted physiological phenomena such as cortical folding during brain development [12,31,32]. Despite these achievements, reported mechanical parameters vary widely across studies—often differing by several orders of magnitude—posing significant barriers to both inter- and intra-study comparisons of brain tissue mechanics.

Due to ethical limitations and logistical constraints on human brain experimentation, animal models have been extensively employed to study brain mechanics [33]. Brains from species such as rodents [34,35], pigs [36,37], and bovines [38,39] are often employed as surrogates for the human brain. However, growing evidence indicates notable interspecies differences, not only in anatomical structure but also in mechanical behavior [40]. Variations in the mechanical properties of gray and white matter, strain-rate sensitivity, and regional stiffness patterns can differ remarkably across species [41,42]. These unignorable discrepancies raise important concerns about the validity of directly translating findings from animal models to humans. The emergence of noninvasive techniques such as magnetic resonance elastography (MRE) and ultrasound elastography (USE) has enabled direct measurement of human brain mechanical properties in vivo [43]. These approaches support population-level studies and facilitate statistically robust investigations into how mechanical properties vary with age, gender, and disease [43]. Their noninvasive nature also allows for repeated and continuous measurements of the same individuals over time [44]. Despite these advantages, current noninvasive methods are limited to capturing relatively simple mechanical quantities—such as shear stiffness, storage, and loss moduli—within small deformation ranges to ensure participant safety and comfort. In addition, the shear-related properties derived from these techniques often show noticeable discrepancies compared to those obtained through invasive approaches. This inconsistency naturally raises concerns regarding the comparability and reliability of the reported mechanical data. More broadly, it points to a longstanding issue in brain testing: the divergence of testing outcomes obtained under different experimental conditions, including in vivo, ex vivo, in vitro, and in situ settings [45].

In this review, we aim to provide a comprehensive summary of the current state of brain tissue mechanical testing. We begin by introducing six widely used experimental techniques, including AFM, IND, AMT, OST, MRE, and USE. Each method is summarized in terms of its working principles, measurable mechanical parameters, advantages, and limitations, as well as representative studies. Next, we collect and analyze existing data on human brain mechanics from peer-reviewed studies, categorizing them based on whether the methods are invasive or noninvasive, and discussing key sensitivity factors that influence the testing outcomes. Finally, we provide a comparative discussion between invasive and noninvasive techniques, as well as in vivo versus ex vivo testing. The review is structured as follows: Section 2 introduces the experimental techniques; Section 3 summarizes human brain tissue mechanical data from the literature; and Section 4 concludes with key insights and perspectives for future research on brain tissue mechanical testing and characterization.