Abstract
Our objective was to determine differences in brain activation during a processing-speed task in individuals with SCI compared to a group of age-matched healthy controls and to a group of older healthy controls. Ten individuals with cervical SCI (C3–C5), 10 age-matched healthy controls and 10 older healthy controls participated in a cross-sectional study in which performance on neuropsychological tests of processing speed and brain activation were the main outcome measures. The brain areas used by the individuals with SCI during the processing-speed task differed significantly from the age-matched healthy controls, but were similar to the older control cohort, and included activation in frontal, parietal and hippocampal areas. This suggests that individuals with SCI may compensate for processing-speed deficits by relying on brain regions that classically support control cognitive processes such as executive control and memory.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References:
Aguilar J, Humanes-Valera D, Alonso-calvin E, Yague JG, Moxon KA, Oliviero A, Guglielmo F (2010) Spinal cord injury immediately changes the state of the brain. J Neurosci. https://doi.org/10.1523/JNEUROSCI.0379-10.2010
Allison DJ, Josse AR, Gabriel DA, Klentrou P, Ditor DS (2017) Targeting inflammation to influence cognitive function following spinal cord injury: a randomized clinical trial. Spinal Cord 55(1):26–32. https://doi.org/10.1038/sc.2016.96
Athanasiou A, Klados MA, Pandria N, Foroglou N, Kavazidi KR, Polyzoidis K, Bamidis PD (2017) A systematic review of investigations into functional brain connectivity following spinal cord injury. Front Hum Neurosci. https://doi.org/10.3389/fnhum.2017.00517
Bloch A, Tamir D, Vakil E, Zeilig G (2016) Specific deficit in implicit motor sequence learning following spinal cord injury. PLoS ONE 11(6):e0158396. https://doi.org/10.1371/journal.pone.0158396
Bombardier CH, Lee DC, Tan DL, Barber JK, Hoffman JM (2016) Comorbid traumatic brain injury and spinal cord injury: screening validity and effect on outcomes. Arch Phys Med Rehabil. https://doi.org/10.1016/j.apmr.2016.03.008
Chen G, Saad ZS, Britton JC, Pine DS, Cox RW (2013) Linear mixed-effects modeling approach to FMRI group analysis. NeuroImage 73:176–190. https://doi.org/10.1038/jid.2014.371
Chiaravalloti ND, Weber E, Wylie GR, Dyson-Hudson TA, Wecht JM (2020) Patterns of cognitive deficits in persons with spinal cord injury as compared both age-matched and older individuals without spinal cord injury. J Spinal Cord Med 43(1):88–97. https://doi.org/10.1080/10790268.2018.1543103
Cox RW (1996) AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. Computers and Biomedical Research, an International Journal 29(3):162–173
Craig A, Nicholson Perry K, Guest R, Tran Y, Dezarnaulds A, Hales A et al (2015) Prospective study of the occurrence of psychological disorders and comorbidities after spinal cord injury. Arch Phys Med Rehabil 96(8):1426–1434. https://doi.org/10.1016/j.apmr.2015.02.027
Cramer SC, Lastra L, Lacourse MG, Cohen MJ (2005) Brain motor system function after chronic, complete spinal cord injury. Brain. https://doi.org/10.1093/brain/awh648
Davidoff G, Morris J, Roth E, Bleiberg J (1985) Cognitive dysfunction and mild closed head injury in traumatic spinal cord injury. Arch Phys Med Rehabil 66(8):489–491
Dosenbach NUF, Fair DA, Cohen AL, Schlaggar BL, Petersen SE (2008) A dual-networks architecture of top-down control. Trends Cogn Sci. https://doi.org/10.1016/j.tics.2008.01.001
Eklund A, Dufort P, Villani M, LaConte S (2014) BROCCOLI: Software for fast fMRI analysis on many-core CPUs and GPUs. Front Neuroinform 8:24. https://doi.org/10.3389/fninf.2014.00024
Eklund A, Nichols TE, Knutsson H (2016) Cluster failure: Why fMRI inferences for spatial extent have inflated false-positive rates. Proc Natl Acad Sci USA. https://doi.org/10.1073/pnas.1602413113
Folstein MF, Folstein SE, McHugh PR (1975) “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. https://doi.org/10.1016/0022-3956(75)90026-6
Genova HM, Dobryakova E, Spirou A, Wylie G (2019) The modified letter comparison task manual. Kessler Foundation, East Hanover, NJ
Guggenmos M, Schmack K, Sekutowicz M, Garbusow M, Sebold M, Sommer C et al (2017) Quantitative neurobiological evidence for accelerated brain aging in alcohol dependence. Transl Psychiatry. https://doi.org/10.1038/s41398-017-0037-y
Gwak YS, Kim HY, Lee BH, Yang CH (2016) Combined approaches for the relief of spinal cord injury-induced neuropathic pain. Complement Ther Med 25:27–33. https://doi.org/10.1016/j.ctim.2015.12.021
Habeck C, Gazes Y, Razlighi Q, Steffener J, Brickman A, Barulli D et al (2016) The Reference Ability Neural Network Study: life-time stability of reference-ability neural networks derived from task maps of young adults. NeuroImage. https://doi.org/10.1016/j.neuroimage.2015.10.077
Habeck C, Steffener J, Barulli D, Gazes Y, Razlighi Q, Shaked D et al (2015) Making cognitive latent variables manifest: distinct neural networks for fluid reasoning and processing speed. J Cogn Neurosci. https://doi.org/10.1162/jocn_a_00778
Hou JM, Sun TS, Xiang ZM, Zhang JZ, Zhang ZC, Zhao M et al (2014) Alterations of resting-state regional and network-level neural function after acute spinal cord injury. Neuroscience. https://doi.org/10.1016/j.neuroscience.2014.07.045
Jegede AB, Rosado-Rivera D, Bauman WA, Cardozo CP, Sano M, Moyer JM et al (2010) Cognitive performance in hypotensive persons with spinal cord injury. Clin Auton Res 20(1):3–9. https://doi.org/10.1007/s10286-009-0036-z
Koutsouleris N, Davatzikos C, Borgwardt S, Gaser C, Bottlender R, Frodl T et al (2014) Accelerated brain aging in schizophrenia and beyond: a neuroanatomical marker of psychiatric disorders. Schizophr Bull. https://doi.org/10.1093/schbul/sbt142
Lenggenhager B, Pazzaglia M, Scivoletto G, Molinari M, Aglioti SM (2012) The sense of the body in individuals with spinal cord injury. PLoS ONE 7(11):e50757. https://doi.org/10.1371/journal.pone.0050757
Macciocchi SN, Seel RT, Thompson N (2013) The impact of mild traumatic brain injury on cognitive functioning following co-occurring spinal cord injury. Arch Clin Neuropsychol. https://doi.org/10.1093/arclin/act049
Molina B, Segura A, Serrano JP, Alonso FJ, Molina L, Pérez-Borrego YA et al (2018) Cognitive performance of people with traumatic spinal cord injury: a cross-sectional study comparing people with subacute and chronic injuries. Spinal Cord. https://doi.org/10.1038/s41393-018-0076-0
National Spinal Cord Injury Statistical Center (2019) Spinal cord injury facts and figures at a glance.
Park DC, Polk TA, Mikels JA, Taylor SF, Marshuetz C (2001) Cerebral aging: integration of brain and behavioral models of cognitive function. Dialogues Clin Neurosci 3(3):51
Raz N, Rodrigue KM (2006) Differential aging of the brain: patterns, cognitive correlates and modifiers. Neurosci Biobehav Rev. https://doi.org/10.1016/j.neubiorev.2006.07.001
Sabre L, Tomberg T, Kõrv J, Kepler J, Kepler K, Linnamägi Ü, Asser T (2016) Brain activation in the chronic phase of traumatic spinal cord injury. Spinal Cord. https://doi.org/10.1038/sc.2015.158
Sachdeva R, Gao F, Chan CCH, Krassioukov AV (2018) Cognitive function after spinal cord injury: a systematic review. Neurology 91(13):611–621. https://doi.org/10.1212/WNL.0000000000006244
Salthouse TA (1996) The processing-speed theory of adult age differences in cognition. Psychol Rev. https://doi.org/10.1037/0033-295X.103.3.403
Salthouse TA (2009) When does age-related cognitive decline begin? Neurobiol Aging. https://doi.org/10.1016/j.neurobiolaging.2008.09.023
Salthouse TA (2010) Selective review of cognitive aging. J Int Neuropsychol Soc. https://doi.org/10.1017/S1355617710000706
Santos Monteiro T, Beets IAM, Boisgontier MP, Gooijers J, Pauwels L, Chalavi S et al (2017) Relative cortico-subcortical shift in brain activity but preserved training-induced neural modulation in older adults during bimanual motor learning. Neurobiol Aging 58:54–67. https://doi.org/10.1016/j.neurobiolaging.2017.06.004
Scandola M, Aglioti SM, Avesani R, Bertagnoni G, Marangoni A, Moro V (2019) Anticipation of wheelchair and rollerblade actions in spinal cord injured people, rollerbladers, and physiotherapists. PLoS ONE. https://doi.org/10.1371/journal.pone.0213838
Schneider W, Eschman A, Zuccolotto A (2002) E-Prime user’s guide. Psychology Software Tools Inc., Pittsburg
Simó LS, Krisky CM, Sweeney JA (2005) Functional neuroanatomy of anticipatory behavior: dissociation between sensory-driven and memory-driven systems. Cereb Cortex. https://doi.org/10.1093/cercor/bhi073
Smith A (1982) Symbol digit modalities test: manual. Western Psychological Services, Los Angeles, CA
Sutherland MT, Ross TJ, Shakleya DM, Huestis MA, Stein EA (2011) Chronic smoking, but not acute nicotine administration, modulates neural correlates of working memory. Psychopharmacology. https://doi.org/10.1007/s00213-010-2013-6
Tombaugh TN, McIntyre NJ (1992) The mini-mental state examination: a comprehensive review. J Am Geriatr Soc. https://doi.org/10.1111/j.1532-5415.1992.tb01992.x
Tzourio C, Laurent S, Debette S (2014) Is hypertension associated with an accelerated aging of the brain? Hypertension. https://doi.org/10.1161/hypertensionaha.113.00147
Vance DE (2009) Speed of processing in older adults: a cognitive overview for nursing. J Neurosci Nurs. https://doi.org/10.1097/JNN.0b013e3181b6beda
Wecht JM, Bauman WA (2013) Decentralized cardiovascular autonomic control and cognitive deficits in persons with spinal cord injury. J Spinal Cord Med. https://doi.org/10.1179/2045772312y.0000000056
Wecht JM, Bauman WA (2018) Implication of altered autonomic control for orthostatic tolerance in SCI. Auton Neurosci Basic Clin. https://doi.org/10.1016/j.autneu.2017.04.004
Wood RL (2017) Accelerated cognitive aging following severe traumatic brain injury: a review. Brain Inj. https://doi.org/10.1080/02699052.2017.1332387
Wu J, Zhao Z, Sabirzhanov B, Stoica BA, Kumar A, Luo T et al (2014) Spinal cord injury causes brain inflammation associated with cognitive and affective changes: role of cell cycle pathways. J Neurosci 34(33):10989–11006. https://doi.org/10.1523/JNEUROSCI.5110-13.2014
Wylie GR, Javitt DC, Foxe JJ (2004) Don’t think of a white bear: an fMRI investigation of the effects of sequential instructional sets on cortical activity in a task-switching paradigm. Hum Brain Mapp 21(4):279–297. https://doi.org/10.1002/hbm.20003
Zarr N, Brown JW (2016) Hierarchical error representation in medial prefrontal cortex. NeuroImage 124:238–247. https://doi.org/10.1016/j.neuroimage.2015.08.063
Acknowledgements
This work was supported by the New Jersey Commission for Spinal Cord Research (Grant: CSCR13IRG018) and the Veterans Affairs Department of Rehabilitation Research & Development Service (Grants: B9212-C & B2020-C).
Author information
Authors and Affiliations
Corresponding author
Additional information
Handling Editor: Christoph M. Michel.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Wylie, G.R., Chiaravalloti, N.D., Weber, E. et al. The Neural Mechanisms Underlying Processing Speed Deficits in Individuals Who Have Sustained a Spinal Cord Injury: A Pilot Study. Brain Topogr 33, 776–784 (2020). https://doi.org/10.1007/s10548-020-00798-x
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10548-020-00798-x