Abstract
The presence of diffuse Focal Axonal Swellings (FAS) is a hallmark cellular feature in many neurological diseases and traumatic brain injury. Among other things, the FAS have a significant impact on spike-train encodings that propagate through the affected neurons, leading to compromised signal processing on a neuronal network level. This work merges, for the first time, three fields of study: (i) signal processing in excitatory-inhibitory (EI) networks of neurons via population codes, (ii) decision-making theory driven by the production of evidence from stimulus, and (iii) compromised spike-train propagation through FAS. As such, we demonstrate a mathematical architecture capable of characterizing compromised decision-making driven by cellular mechanisms. The computational model also leads to several novel predictions and diagnostics for understanding injury level and cognitive deficits, including a key finding that decision-making reaction times, rather than accuracy, are indicative of network level damage. The results have a number of translational implications, including that the level of network damage can be characterized by the reaction times in simple cognitive and motor tests.
Similar content being viewed by others
References
Adalbert, R., Nogradi, A., Babetto, E., Janeckova, L., Walker, S.A., Kerschensteiner, M., Misgeld, T., & Coleman, M.P. (2009). Severely dystrophic axons at amyloid plaques remain continuous and connected to viable cell bodies. Brain, 132, 402– 416.
Adams, J.H., Jennett, B., Murray, L.S., Teasdale, G.M., Gennarelli, T.A., & Graham, D.I. (2011). Neuropathological findings in disabled survivors of a head injury. Journal of Neurotrauma, 28, 701–709.
Adle-Biassette, H., Chretien, F., Wingertsmann, L., Hery, C., Ereau, T., Scaravilli, F., Tardieu, M., & Gray, F. (1999). Neuronal apoptosis does not correlate with dementia in hiv infection but is related to microglial activation and axonal damage. Neuropathology and Applied Neurobiology, 25, 123–133.
Barnes, D.E., Kaup, A., Kirby, K., Byers, A.L., Diaz-Arrastia, R., & Yaffe, K. (2014). Traumatic brain injury and risk of dementia in older veterans. Neurology, 83, 312–319.
Blumbergs, P., Scott, G., Manavis, J., Wainwright, H., Simpson, D., & McLean, A. (1995). Topography of axonal injury as defined by amyloid precursor protein and the sector scoring method in mild and severe closed head injury. Journal of Neurotrauma, 12, 565–572.
Bogacz, R., Brown, E., Moehlis, J., Holmes, P., & Cohen, J.D. (2006). The physics of optimal decision making: a formal analysis of models of performance in two-alternative forced-choice tasks. Psychological Review, 113(4), 700–765.
Brette, R., Rudolph, M., Carnevale, T., Hines, M., Beeman, D., Bower, J.M., Diesmann, M., Morrison, A., Goodman, P.H., Harris, F.C. Jr, Zirpe, M., Natschläger, T., Pecevski, D., Ermentrout, B., Djurfeldt, M., Lansner, A., Rochel, O., Vieville, T., Muller, E., Davison, A.P., Boustani, S.E., & Destexhe, A. (2007). Simulation of networks of spiking neurons: a review of tools and strategies. Journal of Computational Neuroscience, 23(3), 349–398.
Browne, K.D., Chen, X.H., Meaney, D.F., & Smith, D.H. (2011). Mild traumatic brain injury and diffuse axonal injury in swine. Journal of Neurotrauma, 28(9), 1747–1755.
Brunton, B.W., Botvinick, M.M., & Brody, C.D. (2013). Rats and humans can optimally accumulate evidence for decision-making. Science, 340, 95–98.
Chen, Y.C., Smith, D.H., & Meaney, D. (2009). In-vitro approaches for studying blast-induced traumatic brain injury. Journal of Neurotrauma, 26(6), 861–876.
Christman, C., Grady, M., Walker, S., Hol-Loway, K., & Povlishock, J. (1994). Ultra-structural studies of diffuse axonal injury in humans. Journal of Neurotrauma, 11, 173–186.
Coleman, M. (2005). Axon degeneration mechanisms: commonality amid diversity. Nature Reviews Neuroscience, 6(11), 889–898.
Daianu, M., Jacobs, R.E., Town, T., & Thompson, P.M. (2016). Axonal diameter and density estimated with 7-tesla hybrid diffusion imaging in transgenic alzheimer rats. SPIE Proceedings, 9784, 1–6.
Dayan, P., & Abbot, L. (2001). Theoretical neuroscience. Cambridge: MIT.
del Razo, M.J., Morofuji, Y., Meabon, J.S., Huber, B.R., Peskind, E.R., Banks, W.A., Mourad, P.D., LeVeque, R.J., & Cook, D.G. (2016). Computational and in vitro studies of blast-induced blood-brain barrier disruption. SIAM Journal on Scientific Computing, 38(3), 347–374.
Dikranian, K., Cohen, R., Donald, C.M., Pan, Y., Brakefield, D., Bayly, P., & Parsadanian, A. (2008). Mild traumatic brain injury to the infant mouse causes robust white matter axonal degeneration which precedes apoptotic death of cortical and thalamic neurons. Experimental Neurology, 211, 551–560.
Ditterich, J. (2006). Stochastic models of decisions about motion direction: behavior and physiology. Neural Networks, 19, 981–1012.
Edlow, B.L., Copen, W.A., Izzy, S., van der Kouwe, A., Glenn, M.B., Greenberg, S.M., Greer, D.M., & Wu, O. (2016). Longitudinal diffusion tensor imaging detects recovery of fractional anisotropy within traumatic axonal injury lesions. Neurocritical Care, 24(3), 342–352.
Fainaru-Wada, M., & Fainaru, S. (2013). League of denial: the nfl, concussions, and the battle for truth. Crown Archetype.
Faul, M., Xu, L., Wald, M.M., & Coronado, V.G. (2010). Traumatic brain injury in the united states: emergency department visits, hospitalizations, and deaths. Atlanta: Centers for Disease Control and Prevention, National Center for Injury Prevention and Control.
Fayanz, I., & Tator, C.H. (2000). Modeling axonal injury in vitro: injury and regeneration following acute neuritic trauma. Journal of Neuroscience Methods, 102, 69–79.
Friese, M.A., Schattling, B., & Fugger, L. (2014). Mechanisms of neurodegeneration and axonal dysfunction in multiple sclerosis. Nature Reviews Neurology, 10, 225–238.
Galvin, J.E., Uryu, K., Lee, V.M., & Trojanowski, J.Q. (1999). Axon pathology in parkinson’s disease and lewy body dementia hippocampus contains α-, β-, and γ -synuclein. Proceedings of National Academy of Science, 96, 13450–13455.
Grady, M., Mclaughlin, M., Christman, C., Valadaka, A., Flinger, C., & Povlishock, J. (1993). The use of antibodies against neurofilament subunits for the detection of diffuse axonal injury in humans. Journal of Neuropathology and Experimental Neurology, 52, 143–152.
Gupta, R., & Sen, N. (2016). Traumatic brain injury: a risk factor for neurodegenerative diseases. Reviews in the Neurosciences, 27(1), 93–100.
Hanell, A., Greer, J.E., McGinn, M.J., & Povlishock, J.T. (2015). Traumatic brain injury-induced axonal phenotypes react differently to treatment. Acta Neuropathologica, 129, 317–332.
Hay, J., Johnson, V.E., Smith, D.H., & Stewart, W. (2016). Chronic traumatic encephalopathy: the neuropathological legacy of traumatic brain injury. Annual Review of Pathology: Mechanisms of Disease, 11, 21–45.
Hellman, A.N., Vahidi, B., Kim, H.J., Mismar, W., Steward, O., Jeonde, N.L., & Venugopalan, V. (2010). Examination of axonal injury and regeneration in micropatterned neuronal culture using pulsed laser microbeam dissection. Lab on a Chip, 16, 2083–2092.
Hemphill, M., Dabiri, B., Gabriele, S., Kerscher, L., Franck, C., Goss, J., Alford, P., & Parker, K. (2011). A possible role for integrin signaling in diffuse axonal injury. PLos ONE, 6(7), e22899.
Hemphill, M., Dauth, S., Yu, C.J., Dabiri, B., & Parker, K. (2015). Traumatic brain injury and the neuronal microenvironment: a potential role for neuropathological mechanotransduction. Neuron, 86(6), 1177–1192.
Henninger, N., Bouley, J., Sikoglu, E.M., An, J., Moore, C.M., King, J.A., Bowser, R., Freeman, M.R., & Brown, R.H. Jr (2016). Attenuated traumatic axonal injury and improved functional outcome after traumatic brain injury in mice lacking sarm1. Brain, 139(4), 1–12.
Herwerth, M., Kalluri, S.R., Srivastava, R., Kleele, T., Kenet, S., Illes, Z., Merkler, D., Bennett, J.L., Misgeld, T., & Hemmer, B. (2016). In vivo imaging reveals rapid astrocyte depletion and axon damage in a model of neuromyelitis optica-related pathology. Annals of Neurology, 79, 794–805.
Higham, D. (2001). An algorithmic introduction to numerical simulation of stochastic differential equations. SIAM Review, 43(3), 525 (546).
Hill, C.S., Coleman, M.P., & Menon, D.K. (2016). Traumatic axonal injury: mechanisms and translational opportunities. Trends in Neuroscience, 39(5), 311–324.
Ikonomovic, M.D., Uryu, K., Abrahamson, E.E., Ciallella, J.R., Trojanowski, J.Q., Lee, V.M.Y., Clark, R.S., Marione, D.W., Wisniewski, S.R., & DeKosky, S.T. (2004). Alzheimer’s pathology in human temporal cortex surgically excised after severe brain injury. Experimental Neurology, 190, 192–203.
Johnson, V.E., Stewart, W., & Smith, D.H. (2010). Traumatic brain injury and amyloid-β pathology: a link to alzheimer’s disease? Nature Reviews Neuroscience, 11, 361–370.
Johnson, V.E., Stewart, W., & Smith, D.H. (2012). Widespread tau and amyloid-beta pathology many years after a single traumatic brain injury in humans. Brain Pathology, 22, 142–149.
Johnson, V.E., Stewart, W., & Smith, D.H. (2013). Axonal pathology in traumatic brain injury. Experimental Neurology, 246, 35–43.
Jones, L., Fontanini, A., Sadacca, B., Miller, P., & Katz, D. (2007). Natural stimuli evoke dynamic sequences of states in sensory cortical ensembles. Proc. Natl. Acad. Sci. USA, 104, 18772–18777.
Jorge, R.E., Acion, L., White, T., Tordesillas-Gutierrez, D., Pierson, R., Crespo-Facorro, B., & Magnotta, V. (2012). White matter abnormalities in veterans with mild traumatic brain injury. American Journal of Psychiatry, 169(12), 1284–1291.
Jorm, A.F., & Jolley, D. (1998). The incidence of dementia: a meta analysis. Neurology, 51, 728–733.
Laurent, G. (1999). A systems perspective on early olfaction coding. Science, 286, 723–728.
Laurent, G. (2002). Olfactory network dynamics and the coding of multidimensional signals. Nature Reviews Neuroscience, 3, 884–895.
Karlsson, P., Haroutounian, S., Polydefkis, M., Nyengaard, J.R., & Jensen, T.S. (2016). Structural and functional characterization of nerve fibres in polyneuropathy and healthy subjects. Scandinavian Journal of Pain, 10, 28–35.
Katz, L.N., Yates, J.L., Pillow, J.W., & Huk, A.C. (2016). Dissociated functional significance of decision- related activity in the primate dorsal stream. Nature, 535, 285–288.
Kinnunen, K.M., Greenwood, R., Powell, J.H., Leech, R., Hawkins, P.C., Bonnelle, V., Patel, M.C., Counsell, S.J., & Sharp, D.J. (2011). White matter damage and cognitive impairment after traumatic brain injury. Brain, 134(2), 1–15.
Kolaric, K.V., Thomson, G., Edgar, J.M., & Brown, A.M. (2013). Focal axonal swellings and associated ultrastructural changes attenuate conduction velocity in central nervous system axons: a computer modeling study. Physiological Reports, 1(3), e00059.
Krstic, D., & Knuesel, I. (2012). Deciphering the mechanism underlying late-onset alzheimer disease. Nature Reviews Neuroscience, 9(1), 25–34.
Lachance, M., Longtin, A., Morris, C.E., Yu, N., & Joós, B. (2014). Stimulation-induced ectopicity and propagation windows in model damaged axons. Journal of Computational Neuroscience, 37, 523–531.
Laukka, J.J., Kamholz, J., & Bessert, D. (2016). Novel pathologic findings in patients with pelizaeus-merzbacher disease. Neuroscience Letters.
Lauria, G., Morbin, M., Lombardi, R., Borgna, M., Mazzoleni, G., Sghirlanzoni, A., & Pareyson, D. (2003). Axonal swellings predict the degeneration of epidermal nerve fibers in painful neuropathies. Neurology, 61, 631–636.
Liberski, P.P., & Budka, H. (1999). Neuroaxonal pathology in creutzfeldt-jakob disease. Acta Neuropathology, 97, 329–334.
LoBue, C., Denney, D., Hynan, L.S., Rossetti, H.C., Lacritz, L.H., Hart, J. Jr, Womack, K.B., Woon, F.L., & Cullum, C.M. (2016). Self-reported traumatic brain injury and mild cognitive impairment: increased risk and earlier age of diagnosis. Journal of Alzheimer’s Disease, 51, 727–736.
Louis, E.D., Faust, P.L., Vonsattel, J., Honig, L.S., Rajput, A., Rajput, A., Pahwa, R., Lyons, K.E., Ross, G.W., Elble, R.J., Erickson-Davis, C., Moskowitz, C.B., & Lawton, A. (2009). Torpedoes in parkinson’s disease, alzheimer’s disease, essential tremor, and control brains. Movement Disorders, 24 (11), 1600–1605.
Magdesian, M.H., Sanchez, F., Lopez, M., Thostrup, P., Durisic, N., Belkaid, W., Liazoghli, D., Grütter, P., & Colman, R. (2012). Atomic force microscopy reveals important differences in axonal resistance to injury. Biophysical Journal, 103(3), 405–414.
Magdesian, M.H., Lopez-Ayon, G.M., Mori, M., Boudreau, D., Goulet-Hanssens, A., Sanz, R., Miyahara, Y., Barrett, C.J., Fournier, A.E., Koninck, Y.D., & Grütter, P. (2016). Rapid mechanically controlled rewiring of neuronal circuits. The Journal of Neuroscience, 36(3), 979–987.
Maia, P.D., & Kutz, J.N. (2014a). Compromised axonal functionality after neurodegeneration, concussion and/or traumatic brain injury. Journal of Computational Neuroscience, 27, 317–332.
Maia, P.D., & Kutz, J.N. (2014b). Identifying critical regions for spike propagation in axon segments. Journal of Computational Neuroscience, 36(2), 141–155.
Maia, P.D., Hemphill, M.A., Zehnder, B., Zhang, C., Parker, K.K., & Kutz, J.N. (2015). Diagnostic tools for evaluating the impact of focal axonal swellings arising in neurodegenerative diseases and/or traumatic brain injury. Journal of Neuroscience Methods, 253, 233–243.
Maxwell, W.L., Povlishock, J.T., & Graham, D.L. (1997). A mechanistic analysis of nondisruptive axonal injury: a review. Journal of Neurotrauma, 17(7), 419–440.
Menon, D.K., & Maas, A.I.R. (2015). Progress, failures and new approaches for tbi research. Nature Reviews Neuroloy, 11, 71– 72.
Millecamps, S., & Julien, J. (2013). Axonal transport deficits and neurodegenerative diseases. Nature Reviews Neuroscience, 14(161), 161–176.
Morrison, B., Elkin, B.S., Dolle, J.P., & Yarmush, M.L. (2011). In vitro models of traumatic brain injury. Annual Reviews in Biomedical Engineering, 13(1), 91–126.
Nikic, I., Merkler, D., Sorbara, C., Brinkoetter, M., Kreutzfeld, M., Bareyre, F., Bruck, W., Bishop, D., Misgeld, T., & Kerschensteiner, M. (2011). A reversible form of axon damage in experimental autoimmune encephalomyelitis and multiple sclerosis. Nature Medicine, 17(4), 495–499.
Park, H.J., & Friston, K. (2013). Structural and functional brain networks: from connections to cognition. Science, 342, 1238,411–1–1238,411–8.
Patterson, B.W., Elbert, D.L., Mawuenyega, K.G., Kasten, T., Ovod, V., Ma, S., Xiong, C., Chott, R., Yarasheski, K., Sigurdson, W., Zhang, L., Goate, A., Benzinger, T., Morris, J.C., Holtzman, D., & Bateman, R.J. (2015). Age and amyloid effects on human central nervous system amyloid-beta kinetics. American Neurological Association, 78(3), 439–453.
Petersen, R.C. (2004). Mild cognitive impairment as a diagnostic entity. Journal of Internal Medicine, 256, 183–194.
Povlishock, J.T., & Katz, D.I. (2005). Update of neuropathology and neurological recovery after traumatic brain injury. Journal of Head Trauma Rehabilitation, 20(1), 76–94.
Qiu, C., Kivipelto, M., & von Strauss, E. (2009). Epidemiology of alzheimer’s disease: occurrence, determinants, and strategies toward intervention. Dialogues in Clinical Neuroscience, 11(2), 111–128.
Rabinovich, M., Huerta, R., Varona, P., & Afraimovich, V. (2008). Transient cognitive dynamics, metastability, and decision making. PLoS Computational Biology, 4, e1000,072.
Rabinovich, M., Volkovskii, A., Lecanda, P., Huerta, R., Abarbanel, H., & Laurent, G. (2001). Dynamical encoding by networks of competing neuron groups: Winnerless competition. Physical Review Letters, 87, 068102.
Ratcliff, R., & Rouder, J.N. (1998). Modeling response times for two-choice decisions. Psychological Science, 9(5), 347–356.
Reeves, T.M., Smith, T.L., Williamson, J.C., & Phillips, L.L. (2012). Unmyelinated axons show selective rostrocaudal pathology in the corpus callosum after traumatic brain injury. Journal of Neuropathology & Experimental Neurology, 71(3), 198–210.
Riffell, J.A., Shlizerman, E., Sanders, E., Abrell, L., Medina, B., Hinterwirth, A.J., & Kutz, J.N. (2014). Flower discrimination by pollinators in a dynamic chemical environment. Science, 344, 1515–1518.
Roozenbeek, B., Maas, A.I.R., & Menon, D.K. (2013). Changing patterns in the epidemiology of traumatic brain injury. Nature Reviews Neurology, 9, 231–236.
Rubovitch, V., Ten-Bosch, M., Zohar, O., Harrison, C., Tempel-Brami, C., Stein, E., Hoffer, B., Balaban, C., Schreiber, S., Chiu, W., & Pick, C. (2011). A mouse model of blast-induced mild traumatic brain injury. Experimental Neurology, 232(2), 280–289.
Rudy, S., Maia, P.D., & Kutz, J.N. (2016). Cognitive and behavioral deficits arising from neurodegeneration and traumatic brain injury: a model for the underlying role of focal axonal swellings in neuronal networks with plasticity. Journal of Systems and Integrative Neuroscience.
Shadlen, M.N., & Kiani, R. (2013). Decision making as a window on cognition. Neuron, 80(3), 791–332.
Shadlen, M.N., & Shohamy, D. (2016). Decision making and sequential sampling from memory. Neuron, 90, 927–939.
Shadlen, M.N., Hanks, T.D., Churchland, A.K., Kiani, R., & Yang, T. (2007). The speed and accuracy of a simple perceptual decision: a mathematical primer. Ch 10.
Sharp, D.J., Scott, G., & Leech, R. (2014). Network dysfunction after traumatic brain injury. Nature Reviews Neurology, 10, 156–166.
Shlizerman, E., Riffell, J.A., & Kutz, J.N. (2014). Data-driven inference of network connectivity for modeling the dynamics of neural codes in the insect antennal lobe. Frontiers in Computational Neuroscience, 8(70), 1–15.
Skandsen, T., Kvistad, K.A., Solheim, O., Strand, I.H., Folvik, M., & Vik, A. (2010). Prevalence and impact of diffuse axonal injury in patients with moderate and severe head injury: a cohort study of early magnetic resonance imaging findings and 1-year outcome. Journal of Neurosurgery, 113(3), 556–563.
Smith, D., Wolf, J., Lusardi, T., Lee, V., & Meaney, D. (1999). High tolerance and delayed elastic response of cultured axons to dynamic stretch injury. The Journal of Neuroscience, 19(11), 4263–4269.
Tagliaferro, P., & Burke, R.E. (2016). Retrograde axonal degeneration in parkinson disease. Journal of Parkinson’s Disease, 6, 1–15.
Tang-Schomer, M.D., Patel, A., Bass, P.W., & Smith, D.H. (2010). Mechanical breaking of microtubules in axons during dynamic stretch injury underlies delayed elasticity, microtubule disassembly, and axon degeneration. The FASEB Journal, 24(5), 1401–1410.
Tang-Schomer, M.D., Johnson, V.E., Baas, P.W., Stewart, W., & Smith, D.H. (2012). Partial interruption of axonal transport due to microtubule breakage accounts for the formation of periodic varicosities after traumatic axonal injury. Experimental Neurology, 233, 364–372.
Thies, W., & Bleiler, L. (2013). Alzheimer’s disease facts and figures. Alzheimer’s & Dementia, 9(2), 208–245.
Trapp, B.D., & Nave, K.A. (2008). Multiple sclerosis: an immune or neurodegenerative disorder? Annual Review Neuroscience, 31(1), 247–269.
Tsai, J., Grutzendler, J., Duff, K., & Gan, W.B. (2004). Fibrillar amyloid deposition leads to local synaptic abnormalities and breakage of neuronal branches. Nature Neuroscience, 7, 1181–1183.
Victor, J.D., & Purpura, K.P. (1997). Metric space analysis of spike trains: theory, algorithms and application. Network: Computational Neural Systems, 8, 127–164.
Wang, J., Hamm, R.J., & Povlishock, J.T. (2011). Traumatic axonal injury in the optic nerve: evidence for axonal swelling, disconnection, dieback and reorganization. Journal of Neurotrauma, 28(7), 1185–1198.
Watts, D.J., & Strogatz, S.H. (1998). Collective dynamics of ‘small-world’ networks. Nature, 393(6684), 440–442.
Wulfram Gerstner Werner, M., Kistler, R.N., & Paninski, L. (2014). Neuronal dynamics. Cambridge: Cambridge University Press.
Xiong, Y., Mahmood, A., & Chopp, M. (2013). Animal models of traumatic brain injury. Nature Reviews Neuroscience, 14(22), 128–142.
Yue, J.K., Vassar, M.J., Lingsma, H.F., Cooper, S.R., Okonkwo, D.O., Valadka, A.B., Gordon, W.A., Maas, A.I.R., Mukherjee, P., Yuh, E.L., Puccio, A.M., Schnyer, D.M., Manley, G.T., Casey, S.S., Cheong, M., Dams-O’Connor, K., Hricik, A.J., Knight, E.E., Kulubya, E.S., Menon, D.K., Morabito, D.J., Pacheco, J.L., & Sinha, T.K. (2013). Transforming research and clinical knowledge in traumatic brain injury pilot: multicenter implementation of the common data elements for traumatic brain injury. Journal of Neurotrauma, 30, 1831–1844.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Additional information
Action Editor: Jonathan David Victor
Appendix
Appendix
1.1 Additional histogram panels
For sake of completeness, we provide additional histogram panels for different coherence levels, injury levels and FAS distributions in Figs. 14, 15 and 16. Histogram panels follow the structure and conventions from Fig. 11 with the 9 possible outcomes of [Before vs After] annotated in the title of each subplot.
Rights and permissions
About this article
Cite this article
Maia, P.D., Kutz, J.N. Reaction time impairments in decision-making networks as a diagnostic marker for traumatic brain injuries and neurological diseases. J Comput Neurosci 42, 323–347 (2017). https://doi.org/10.1007/s10827-017-0643-y
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10827-017-0643-y