Skip to main content

HAMr: A Mechanical Impactor for Repeated Dynamic Loading of In vitro Neuronal Networks


A new tool for exploring the effects of repeated low-amplitude mechanical impacts onto in vitro neuronal networks is presented. The experimental setup, HAMr, is specifically designed to allow variability in impact conditions while ensuring a highly repeatable result. HAMr’s functionality to induce inflammation related to mild traumatic brain injuries has been validated by assessing its capability to induce elevated expression of the inflammatory protein IL-1 β in in vitro neuronal cell cultures. The two main results obtained for the inflammatory response in dissociated cortical networks, presented for a range of impact force amplitude and total number of impacts, can be summarized as follows. First, the results demonstrate a strong correlation between ensuing inflammation level and numbers of impact. Second, the results indicate a possible existence of a safe threshold of number of impacts that does not initiate an inflammatory response.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7


  1. Lee SJ, King MA, Sun J, Xie HK, Subhash G, Sarntinoranont M (2014) Measurement of viscoelastic properties in multiple anatomical regions of acute rat brain tissue slices. J Mech Behav Biomed Mater 29:213–224

    Article  Google Scholar 

  2. Langlois JA, Rutland-Brown W, Wald MM (2006) The epidemiology and impact of traumatic brain injury: a brief overview. J Head Trauma Rehabil 21(5):375–378

    Article  Google Scholar 

  3. Shenton ME, Hamoda HM, Schneiderman JS, Bouix S, Pasternak O, Rathi Y, Zafonte R (2012) A review of magnetic resonance imaging and diffusion tensor imaging findings in mild traumatic brain injury. Brain Imaging Behav 6(2):137–192

    Article  Google Scholar 

  4. Thurman D (2001) The epidemiology and economics of head trauma. Head trauma: basic, preclinical, and clinical directions, vol 327. Wiley and Sons, New York, p 347

    Google Scholar 

  5. Morrison B III, Saatman KE, Meaney DF, McIntosh TK (1998) In vitro central nervous system models of mechanically induced trauma: a review. J Neurotrauma 15(11):911–928

    Article  Google Scholar 

  6. Meaney DF, Smith DH (2011) Biomechanics of concussion. Clin Sports Med 30(1):19–31

    Article  Google Scholar 

  7. Laplaca MC, Lee VMY, Thibault LE (1997) An in vitro model of traumatic neuronal injury: loading rate-dependent changes in acute cytosolic calcium and lactate dehydrogenase release. J Neurotrauma 14(6):355–368

    Article  Google Scholar 

  8. LaPlaca MC, Cullen DK, McLoughlin JJ, Cargill RS II (2005) High rate shear strain of three-dimensional neural cell cultures: a new in vitro traumatic brain injury model. J Biomech 38(5):1093–1105

    Article  Google Scholar 

  9. Pervin F, Chen WW (2009) Dynamic mechanical response of bovine gray matter and white matter brain tissues under compression. J Biomech 42(6):731–735

    Article  Google Scholar 

  10. Sarntinoranont M, Lee SJ, Hong Y, King MA, Subhash G, Kwon J, Moore DF (2012) High-strain-rate brain injury model using submerged acute rat brain tissue slices. J Neurotrauma 29(2):418–429

    Article  Google Scholar 

  11. Ravindran S, Koohbor B, Kidane A (2015) On the Meso-macro scale deformation of low carbon steel. In: Advancement of Optical Methods in Experimental Mechanics, vol 3. Springer International Publishing, pp 409–414

  12. Upton ML, Gilchrist CL, Guilak F, Setton LA (2008) Transfer of macroscale tissue strain to microscale cell regions in the deformed meniscus. Biophys J 95(4):2116–2124

    Article  Google Scholar 

  13. Weber JT, Rzigalinski BA, Willoughby KA, Moore SF, Ellis EF (1999) Alterations in calcium-mediated signal transduction after traumatic injury of cortical neurons. Cell Calcium 26(6):289–299

    Article  Google Scholar 

  14. Nyein MK, Jason AM, Yu L, Pita CM, Joannopoulos JD, Moore DF, Radovitzky RA (2010) In silico investigation of intracranial blast mitigation with relevance to military traumatic brain injury. Proc Natl Acad Sci 107(48):20703–20708

    Article  Google Scholar 

  15. Rowson S, Brolinson G, Goforth M, Dietter D, Duma S (2009) Linear and angular head acceleration measurements in collegiate football. J Biomech Eng 131(6):061016

    Article  Google Scholar 

  16. Bayly PV, Cohen TS, Leister EP, Ajo D, Leuthardt EC, Genin GM (2005) Deformation of the human brain induced by mild acceleration. J Neurotrauma 22(8):845–856

    Article  Google Scholar 

  17. Nahum AM, Smith R, Ward CC (1977) Intracranial pressure dynamics during head impact. In: Proceedings of the 21st Annual Stapp Car Crash Conference. Society of Automotive Engineers

  18. Dash PK, Zhao J, Hergenroeder G, Moore AN (2010) Biomarkers for the diagnosis, prognosis, and evaluation of treatment efficacy for traumatic brain injury. Neurotherapeutics 7 (1):100–114

    Article  Google Scholar 

  19. Raghavendra Rao VL, Dhodda VK, Song G, Bowen KK, Dempsey RJ (2003) Traumatic brain injury-induced acute gene expression changes in rat cerebral cortex identified by GeneChip analysis. J Neurosci Res 71(2):208–219

    Article  Google Scholar 

  20. Woodcock T, Morganti-Kossmann MC (2013) The role of markers of inflammation in traumatic brain injury. Front Neurol 4(18)

  21. Frugier T, Morganti-Kossmann MC, O’Reilly D, McLean CA (2010) In situ detection of inflammatory mediators in post mortem human brain tissue after traumatic injury. J Neurotrauma 27(3):497–507

    Article  Google Scholar 

  22. Fan L, Young PR, Barone FC, Feuerstein GZ, Smith DH, McIntosh TK (1995) Experimental brain injury induces expression of interleukin-1 β mRNA in the rat brain. Brain Res Mol Brain Res 30(1):125–130

    Article  Google Scholar 

  23. Kinoshita K, Chatzipanteli K, Vitarbo E, Truettner JS, Alonso OF, Dietrich WD (2002) Interleukin-1 β messenger ribonucleic acid and protein levels after fluid-percussion brain injury in rats: importance of injury severity and brain temperature. Neurosurgery 51(1):195–203

    Article  Google Scholar 

  24. Lu KT, Wang YW, Wo YYP, Yang YL (2005) Extracellular signal-regulated kinase-mediated IL-1-induced cortical neuron damage during traumatic brain injury. Neurosci Lett 386(1):40–45

    Article  Google Scholar 

  25. Kamm K, Vanderkolk W, Lawrence C, Jonker M, Davis AT (2006) The effect of traumatic brain injury upon the concentration and expression of interleukin-1 β and interleukin-10 in the rat. J Trauma 60:152–157

    Article  Google Scholar 

  26. Brewer GJ, Boehler MD, Jones TT, Wheeler BC (2008) NbActiv4 medium improvement to Neurobasal/B27 increases neuron synapse densities and network spike rates on multielectrode arrays. J Neurosci Methods 170 (2):181–187

    Article  Google Scholar 

  27. Brewer GJ, Boehler MD, Pearson RA, DeMaris AA, Ide AN, Wheeler BC (2009) Neuron network activity scales exponentially with synapse density. Journal of Neural Engineering 6(1):014001

    Article  Google Scholar 

Download references


We would like to thank Anton Schuetze-Coburn, Michael Ray and Rodney Yates for help with machining and design of HAMr, the USC Viterbi Machine Shop and the WSU Spokane Microscopy Core Lab for access to their equipment. Parijat Sengupta’s work was supported by the ISP/Applied Sciences Laboratory, WSU

Author information

Authors and Affiliations


Corresponding author

Correspondence to V. Eliasson.

Appendix A: Biological Methods

Appendix A: Biological Methods

A.1 Preparation of Cortical Networks for Impact Experiments

Cortices isolated from embryonic day-18 C57BL/6 (CRL line) mice brain (BrainBits LLC, Springfield, IL) were used to make 2-dimensional neuronal networks used in this study. Under sterile conditions, cortical tissue was digested at 30 C for 25 minutes in 2 mg/ml papain solution in Hibernate-E minus Ca 2+ (Brain Bits LLC, Springfield, IL), mechanically dissociated in Hibernate-E medium (Brain Bits LLS, Springfield, IL) supplemented with 0.5 mM Glutamax (Life Technologies, Carlsbad, CA), and strained with a 40 μm cell strainer (BD Biosciences, San Jose, CA) to remove debris and tissue fragments [26, 27]. Cells were spun down at 200 g for 3 minutes and the pellet was re-suspended in warm Dulbecco’s Modified Eagles Medium (DMEM) with high glucose (Cat #D-6429, Sigma, St. Louis, MO) supplemented with 10 % fetal bovine serum (FBS) and 0.5 mM Glutamax. Approximately 105 cells in 40 μl were plated on poly-D-lysine coated 35 mm diameter glass-bottomed circular imaging dishes (MatTek Corporation, Ashland, MA). Cells were incubated inside a 5 % CO 2 incubator at 37 C. After 1.5 hours, 2 ml warm pre-equilibrated media was added to the cultures. After 4 hours half of the growth medium was replaced with NbActiv4 (Brain Bits LLC, Springfield, IL) medium. By day 3 in vitro (DiV-03) cells formed an intricate network with numerous connections. Cells were maintained in culture by feeding every third day by replacing half of the culture medium with warm, fresh NbActiv4 medium pre-equilibrated in the incubator. A cocktail of penicillin/streptomycin and gentamicin was used to keep cultures free from microbial contamination an bacterial infection. All experiments reported here used DIV-15 to DIV-20 cultures. Cell type analyses for these networks using immunostaining with neuronal marker NeuN (ABN78 from Millipore, Billerica, MA), a suitable Alexa-633 conjugated secondary antibody (Life Technologies, Carlsbad, CA) and cell nuclei marker Hoechst (Fig. 8) show that 44±3 % (n=6 isolations) of cells are neurons in these networks between DIV-11 and DIV-24 in culture. For the impact experiments, networks were taken out of the incubator for pressure pulse exposure and then again returned to the incubator for 4 hours. Impact-exposed networks were then fixed, immunostained for IL-1 β protein and other cellular markers, and then imaged using a fluorescence microscope.

Fig. 8
figure 8

A DIV-17 dissociated cortical network immunostained for neuronal nuclei marker, NeuN and cell nuclei marker, Hoechst. Scale bar: 100 μ m

A.2 Determination of IL-1 β Expression Levels in Neurons

IL-1 β expression levels in neurons were determined by immunostaining these networks with suitable antibodies. After impact experiment and incubation, networks were washed twice with warm phosphate buffered saline (PBS) solution, and then fixed with 3.7 % paraformaldehyde (PFA) solution in PBS for 20 minutes at room temperature. Samples were washed thrice with PBS/50 mM glycine solution to neutralize PFA, and then treated with 0.25 % Triton-X for 10 minutes to make cell membranes permeable. A blocking solution made of 3 % bovine serum albumin (BSA), 5 % goat serum and 50mM glycine in PBS was used to minimize nonspecific labeling with antibodies. Then each network was treated with 2-3 drops of Image-IT FX (Life Technologies, Carlsbad, CA) for 30 minutes at room temperature in humid environment. For immunostaining, networks were first incubated with primary antibody (IL-1 β, goat, AF-401-NA, (R&D Systems, Minneapolis, MN); Cy3 conjugated MAP-2, rabbit, AB2290C3 (Millipore, Billerica, MA); NeuN, rabbit, ABN78 (Millipore, Billerica, MA); Alexa-488 conjugated NeuN, rabbit, ABN78A4 (Millipore, Billerica, MA)) for 2 hours, washed tree times with PBS, and then treated with a suitable donkey anti-goat Alexa-633 or Alexa-488 labelled secondary antibody (Life Technologies, Carlsbad, CA) for 2 hours. All reactions were done at room temperature. Samples were washed twice and then labelled with NucBlue reagent (Life Technologies, Carlsbad, CA). Immunostained samples were stored at 4 C and were imaged within three days of preparation.

For fluorescence imaging experiments a fluorescence microscope (Axio Imager M2, Zeiss) coupled to X-Cite Series 120Q (EXFO) illumination system and a digital camera (Axio Cam MRm, Zeiss) was used. For all experiments the detector gain and the channel exposure times used for recording images from immunostained samples were kept constant. For every network, 6-10 fields (1000 μ m×800 μm for fluorescence microscope) were imaged from different regions of the network. Higher fluorescence intensity was interpreted as higher concentration of IL-1 β protein.

Image processing and analyses were done using ImageJ software (National Institutes of Health, MD). For every image, neuronal cell bodies were selected (∼50 cells per image, 4-6 images per network) using Region of Interest (ROI) Manager tool, and average fluorescence intensity for each ROI was measured. Finally, data from multiple networks were combined, and the change in fluorescence intensity is presented as percent increase using the average values of non-impactor exposed samples as controls. All experiments were done using 4 independent cell isolations. Data from all preparations were combined and presented as average ± standard deviation.

Rights and permissions

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Koumlis, S., Buecker, D., Moler, G. et al. HAMr: A Mechanical Impactor for Repeated Dynamic Loading of In vitro Neuronal Networks. Exp Mech 55, 1441–1449 (2015).

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: