Skip to main content
SpringerLink
Log in

Functional connectivity as a neural correlate of cognitive rehabilitation programs’ efficacy: A systematic review

  • Published:
Current Psychology Aims and scope Submit manuscript

Abstract

Researchers who have been assessing the efficacy of cognitive rehabilitation (CR) programs are expressing a growing concern with the validity of the assessment protocols and have tried to improve them by including multidomain measures in addition to cognitive and behavioral ones. Within this scope, changes in brain functioning associated with CR are being reported through the analysis of neural correlates. Nonetheless, the influence of CR on functional connectivity (FC) and its relationship with the behavioral outcomes conventionally used are still unclear. A systematic review of the literature was performed, up to January 2021, through a search on EBSCOhost, PubMed, and Web of Science, which targeted empirical studies assessing the efficacy of CR programs in adults, with FC as an outcome. This review included 51 studies, whose methodological quality was assessed through Cicerone’s classification. We present the characteristics of the studies, the cognitive rehabilitation programs, as well as the techniques, protocols and methods used to measure FC. All of the CR programs used in the studies were associated with significant improvements in FC, and the majority of these programs were also related to significant improvements in behavioral outcomes. In addition, 32 studies that analyzed the relationship between behavioral and neural outcomes had reported that changes in FC were significantly associated with improvements in behavioral outcomes, namely in cognitive functioning, quality of life, and affective domains. Despite the high methodological heterogeneity of the studies, FC seems to be a proper indicator of the efficacy of CR programs, unveiling the importance of its use combined with behavioral outcomes.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

Data Availability

All data and materials support the published claims and comply with field standard.

Code Availability

Not applicable.

References

  • Albert, K., Potter, G., Boyd, B., Kang, H., & Taylor, W. (2019). Brain network functional connectivity and cognitive performance in major depressive disorder. Journal of Psychiatric Research, 110, 51–56. https://doi.org/10.1016/j.jpsychires.2018.11.020

    Article  PubMed  Google Scholar 

  • Andrews, G. (1999). Efficacy, effectiveness and efficiency in mental health service delivery. Australian and New Zealand Journal of Psychiatry, 33, 316–322.

    Article  PubMed  Google Scholar 

  • *Bajaj, J., Ahluwalia, V., Thacker, L., Fagan, A., Gavis, E., Lennon, M., Heuman, D., Fuchs, M., & Wade, J. (2017). Brain training with video games in covert hepatic encephalopathy. The American Journal of Gastroenterology, 122(2), 316–324. https://doi.org/10.1038/ajg.2016.544

    Article  Google Scholar 

  • *Balkom, T., Heuvel, O., Berendse, H., Werf, Y., & Vriend, C. (2020). The effects of cognitive training on brain network activity and connectivity in aging and neurodegenerative diseases: A systematic review. Neuropsychology Review, 30, 267–286. https://doi.org/10.1007/s11065-020-09440-w

    Article  PubMed  PubMed Central  Google Scholar 

  • Barban, F., Mancini, M., Cercignani, M., Adriano, F., Perri, R., Annicchiarico, R., Carlesimo, G., Ricci, C., Lombardi, M., Teodonno, V., Serra, L., Giulietti, G., Fadda, L., Federici, A., Caltagirone, C., & Bozzali, M. (2017). A pilot study on brain plasticity of functional connectivity modulated by cognitive training in mild Alzheimer’s disease and mild cognitive impairment. Brain Sciences, 7, 50. https://doi.org/10.3390/brainsci7050050

    Article  PubMed  PubMed Central  Google Scholar 

  • Barlow, D. H., Nock, M. K., & Hersen, M. (2009). Single case experimental designs: Strategies for studying behavior change (3rd ed.). Pearson.

    Google Scholar 

  • Bauer, R. M. (2007). Evidence-based practice in psychology: Implications for research and research training. Journal of Clinical Psychology, 63, 685–694. https://doi.org/10.1002/jclp.2037

    Article  PubMed  Google Scholar 

  • Bodagnova, Y., Yee, M. K., Ho, V. T., & Cicerone, K. D. (2015). Computerized cognitive rehabilitation of attention and executive function in acquired brain injury: A systematic review. Journal of Head Trauma Rehabilitation, 31, 419–433. https://doi.org/10.1097/HTR.0000000000000203

    Article  Google Scholar 

  • *Bonavita, S., Sacco, R., Della Corte, M., Esposito, S., Sparaco, M., d’Ambrosio, A., Docimo, R., Bisecco, A., Lavorgna, L., Corbo, D., Cirillo, S., Gallo, A., Esposito, F., & Tedeschi, G. (2015). Computer-aided cognitive rehabilitation improves cognitive performances and induces brain functional connectivity changes in relapsing remitting multiple sclerosis patients: An exploratory study. Journal of Neurology, 262, 91–100. https://doi.org/10.1007/s00415-014-7528-z

    Article  PubMed  Google Scholar 

  • Campanella, S. (2016). Neurocognitive rehabilitation for addiction medicine: From neurophysiological markers to cognitive rehabilitation and relapse prevention. In H. Ekhtiari & M. Paulus (Eds.), Neuroscience for addiction medicine: From prevention to rehabilitation – Methods and interventions (pp. 85–103). Elsevier. https://doi.org/10.1016/bs.pbr.2015.07.014

    Chapter  Google Scholar 

  • *Cao, W., Cao, X., Hou, C., Li, T., Cheng, Y., Jiang, L., Luo, C., Li, C., & Yao, D. (2016). Effects of cognitive training on resting-state functional connectivity of default mode, salience, and central executive networks. Frontiers in Aging Neuroscience, 8, 70. https://doi.org/10.3389/fnagi.2016.00070

    Article  PubMed  PubMed Central  Google Scholar 

  • Casaletto, K., & Heaton, R. (2017). Neuropsychological assessment: Past and future. Journal of the International Neuropsychological Society, 23, 778–790. https://doi.org/10.1017/S1355617717001060

    Article  PubMed  PubMed Central  Google Scholar 

  • *Castellanos, N. P., Paúl, N., Ordóñ Ez, V. E., Demuynck, O., Bajo, R., Campo, P., Bilbao, A., Ortiz, T., & del-Pozo, F., & Maestú, F. (2010). Reorganization of functional connectivity as a correlate of cognitive recovery in acquired brain injury. Brain, 133(8), 2365–2381. https://doi.org/10.1093/brain/awq174

    Article  PubMed  Google Scholar 

  • *Castellanos, N. P., Leyva, I., Buldú, J., Bajo, R., Paúl, N., Cuesta, P., Ordoñez, V., Pascua, C., Boccaletti, S., Maestú, F., & del-Pozo, F. (2011). Principles of recovery from traumatic brain injury: Reorganization of functional networks. NeuroImage, 55, 1189–1199. https://doi.org/10.1016/j.neuroimage.2010.12.046

    Article  PubMed  Google Scholar 

  • *Cerasa, A., Gioia, M., Valentino, P., Nisticò, R., Chiriaco, C., Pirritano, D., Tomaiuolo, F., Mangone, G., Trotta, M., Talarico, T., Bilotti, G., & Quattrone, A. (2013). Computer-assisted cognitive rehabilitation of attention deficits for multiple sclerosis: A randomized trial with fMRI correlates. Neurorehabilitation and Neural Repair, 27(4), 284–a295. https://doi.org/10.1177/1545968312465194

    Article  PubMed  Google Scholar 

  • *Cerasa, A., Gioia, M., Salsone, M., Donzuso, G., Chiriaco, C., Realmuto, S., Nicoletti, A., Bellavia, G., Branco, A., D’amelio, M., Zappia, M., & Quattrone, A. (2014). Neurofunctional correlates of attention rehabilitation in Parkinson’s disease: An explorative study. Neurological Sciences, 35(8), 1173–1180. https://doi.org/10.1007/s10072-014-1666-z

    Article  PubMed  Google Scholar 

  • *Chapman, S., Aslan, S., Spence, J., Hart Jr., J., Bartz, E., Dibehbani, N., Keebler, M., Gardner, C., Strain, J., DeFina, L., & Lu, H. (2013). Neural mechanisms of brain plasticity with complex cognitive training in healthy seniors. Cerebral Cortex, 25(2), 396–405. https://doi.org/10.1093/cercor/bht234

    Article  PubMed  PubMed Central  Google Scholar 

  • *Chapman, S., Spence, J., Aslan, S., & Keebler, M. (2017). Enhancing innovation and underlying neural mechanisms via cognitive training in health older adults. Frontiers in Aging Neuroscience, 9, 314 https://doi.org/10.3389/fnagi.2017.00314

    Article  PubMed  PubMed Central  Google Scholar 

  • Chaytor, N., & Schmitter-Edgecombe, M. (2003). The ecological validity of neuropsychological tests: A review of the literature on everyday cognitive skills. Neuropsychology Review, 13(4), 181–197 https://doi.org/1040-7308/03/1200-0181/0

    Article  PubMed  Google Scholar 

  • Cho, H., Kim, K., & Jung, J. (2015). Effects of computer assisted cognitive rehabilitation on brain wave, memory and attention of stroke patients: A randomized control trial. Journal of Physical Therapy Science, 27, 1029–1032. https://doi.org/10.1589/jpts.27.1029

    Article  PubMed  PubMed Central  Google Scholar 

  • Cho, H., Kim, K., & Jung, J. (2016). Effects of neurofeedback and computer-assisted cognitive rehabilitation on relative brain wave ratios and activities of daily living of stroke patients. Journal of Physical Therapy Science, 28, 2154–2158. https://doi.org/10.1589/jpts.28.2154

    Article  PubMed  PubMed Central  Google Scholar 

  • Cicerone, K., Dahlberg, C., Kalmar, K., Langenbahn, D., Malec, J., Bergquist, T., Felicetti, T., Giacino, J., Harley, J., Harrington, D., Herzog, J., Kneipp, S., Laatsch, L., & Morse, P. (2000). Evidence-based cognitive rehabilitation: Recommendations for clinical practice. Archives of Physical Medicine and Rehabilitation, 28(12), 1596–1615 https://doi.org/10.1053/apmr.2000.19240

    Article  Google Scholar 

  • Cicerone, K. D., Langenbahn, D. M., Braden, C., Malec, J. F., Kalmar, K., Fraas, M., Felicetti, T., Laatsch, L., Harley, J., Bergquist, T., Azulay, J., Cantor, J., & Ashman, T. (2011). Evidence-based cognitive rehabilitation: Updated review of the literature from 2003 through 2008. Archives of Physical and Medical Rehabilitation, 92, 519–530. : https://doi.org/10.1016/j.apmr.2010.11.015

  • Connolly, J., & D'Arcy, R. (2000). Innovations in neuropsychological assessment using event-related brain potentials. International Journal of Psychophysiology, 37(1), 31–47. https://doi.org/10.1016/s0167-8760(00)00093-3

    Article  PubMed  Google Scholar 

  • *De Giglio, L., Tona, F., De Luca, F., Petsas, N., Prosperini, L., Bianchi, V., Pozzilli, C., & Pantano, P. (2016). Multiple sclerosis: Changes in thalamic resting-state functional connectivity induced by a home-based cognitive rehabilitation program. Radiology, 280(1), 202–211. https://doi.org/10.1148/radiol.2016150710

    Article  PubMed  Google Scholar 

  • *De Marco, M., Meneghello, F., Duzzi, D., Rigon, J., Pilosio, C., & Venneri, A. (2016). Cognitive stimulation of the default-mode network modulates functional connectivity in healthy aging. Brain Research Bulletin, 121, 26–41. https://doi.org/10.1016/j.brainresbull.2015.12.001

    Article  PubMed  Google Scholar 

  • *De Marco, M., Meneghello, F., Pilosio, C., Rigon, J., & Venneri, A. (2018). Up-regulation of DMN connectivity in mild cognitive impairment via network-based cognitive training. Current Alzheimer Research, 15(6), 578–589. https://doi.org/10.2174/1567205015666171212103323

    Article  PubMed  PubMed Central  Google Scholar 

  • de Vroege, L., Vergeest, A., & Kop, W. (2021). Letter to the editor – Towards an outpatient model of care for motor functional neurological disorders: A neuropsychiatric perspective. Neuropsychiatric Disease and Treatment, 17, 1055–1056. https://doi.org/10.2147/NDT.S312567

    Article  PubMed  PubMed Central  Google Scholar 

  • Demirakca, T., Cardinale, V., Dehn, S., Ruf, M., & Ende, G. (2016). The exercising brain: Changes in functional connectivity induced by an integrated multimodal cognitive and whole-body coordination training. Neural Plasticity, 8240894. https://doi.org/10.1155/2016/8240894

  • *Deng, L., Cheng, Y., Cao, X., Feng, W., Zhu, H., Jiang, L., Wu, W., Tong, S., Sun, J., & Li, C. (2019). The effect of cognitive training on the brain’s local connectivity organization in healthy older adults. Scientific Reports, 9, 9033. https://doi.org/10.1038/s41598-019-45463-x

    Article  PubMed  PubMed Central  Google Scholar 

  • *Díez-Cirarda, M., Ojeda, N., Peña, J., Cabrera-Zubizarreta, A., Lucas-Jiménez, O., Gómez-Esteban, J., Goméz-Beldarrain, M., & Ibarretxe-Bilbao, N. (2016). Increased brain connectivity and activation after cognitive rehabilitation in Parkinson’s disease: A randomized controlled trial. Brain imaging and behavior, 11¸ 1640–1651. https://doi.org/10.1007/s11682-016-9639-x

  • *Díez-Cirarda, M., Ojeda, N., Peña, J., Cabrera-Zubizarreta, A., Lucas-Jiménez, O., Gómez-Esteban, J., Goméz-Beldarrain, A., & Ibarretxe-Bilbao, N. (2018). Long-term effects of cognitive rehabilitation on brain, functional outcome and cognition in Parkinson’s disease. European Journal of Neurology, 25, 5–12. https://doi.org/10.1111/ene.13472

    Article  PubMed  Google Scholar 

  • Dores, A. R., Therapy 2.0 team, Barbosa, F., & Silva, R. (2017). Therapy 2.0: Chegar mais perto dos que estão longe [Therapy 2.0: Getting Closer to Those Who Are Far]. Revista de Estudios e Investigación en Psicologia y Educación, 09, 47–49. https://doi.org/10.17979/reipe.2017.0.09.2451

  • Dores, A. R., Mendes, L., Carvalho, I. P., Guerreiro, S., Almeida, I., & Barbosa, F. (2018). Significance of virtual reality-based rehabilitation in acquired brain injury. In I. Management Association (Ed.), Virtual and augmented reality: Concepts, methodologies, tools, and applications (pp. 1586–1601). IGI-Global. https://doi.org/10.4018/978-1-5225-5469-1.ch074

    Chapter  Google Scholar 

  • *Dresler, M., Shirer, W., Konrad, B., Müller, N., Wagner, I., Fernández, G., Czisch, M., & Greicius, M. (2017). Mnemonic training reshapes brain networks to support superior memory. Neuron, 93, 1227–1235. https://doi.org/10.1016/j.neuron.2017.02.003

    Article  PubMed  PubMed Central  Google Scholar 

  • Edgar, J., Keller, J., Heller, W., & Miller, G. (2007). Psychophysiology in research on psychopathology. In J. Cacioppo, L. Tassinary, & G. Bernston (Eds.), The handbook of psychophysiology (pp. 665–688). Cambridge University Press.

    Google Scholar 

  • *Ernst, A., Sourty, M., Roquet, D., Noblet, V., Gounot, D., Blanc, F., de Seze, J., & Manning, L. (2016a). Benefits from an autobiographical memory facilitation programme in relapsing-remitting multiple sclerosis patients: A clinical and neuroimaging study. Neuropsychological Rehabilitation, 28(7), 1110–1130. https://doi.org/10.1080/09602011.2016.1240697

    Article  PubMed  Google Scholar 

  • *Ernst, A., Sourty, M., Roquet, D., Noblet, V., Gounot, D., Blanc, F., de Seze, J., & Manning, L. (2016b). Functional and structural cerebral changes in key brain regions after a facilitation programme for episodic future thought in relapsing-remitting multiple sclerosis patients. Brain and Cognition, 105, 34–45. https://doi.org/10.1016/j.bandc.2016.03.007

    Article  PubMed  Google Scholar 

  • Friston, K. (2011). Functional and effective connectivity: A review. Brain Connectivity, 1(1), 13–36. https://doi.org/10.1089/brain.2011.0008

    Article  PubMed  Google Scholar 

  • García-Casal, J., Loizeau, A., Csipke, E., Franco-Martín, M., Perea-Bartolomé, M., & Orrell, M. (2017). Computer-based cognitive interventions for people living with dementia: A systematic literature review and meta-analysis. Aging & Mental Health, 21(5), 454–467. https://doi.org/10.1080/13607863.2015.1132677

    Article  Google Scholar 

  • Ge, S., Zhu, Z., Wu, B., & McConnell, E. (2018). Technology-based cognitive training and rehabilitation interventions for individuals with mild cognitive impairment: A systematic review. BMC Geriatrics, 18, 213. https://doi.org/10.1186/s12877-018-0893-1

    Article  PubMed  PubMed Central  Google Scholar 

  • Geraldo, A., Dores, A. R., Coelho, B., Ramião, E., Castro-Caldas, A., & Barbosa, F. (2018). Efficacy of ICT-based neurocognitive rehabilitation programs for acquired brain injury: A systematic review on its assessment methods. European Psychologist, 23, 250–264. https://doi.org/10.1027/1016-9040/a000319

    Article  Google Scholar 

  • Geraldo, A., Azeredo, A., Pasion, A., Dores, A. R., & Barbosa, F. (2019). Fostering advances to neuropsychological assessment based on the research domain criteria: The bridge between cognitive functioning and physiology. The Clinical Neuropsychologist, 33(2), 327–356. https://doi.org/10.1080/13854046.2018.1523467.

  • *Gimbel, S., Ettenhofer, M., Cordero, E., Roy, M., & Chan, L. (2020). Brain bases of recovery following cognitive rehabilitation for traumatic brain injury: A preliminary study. Brain Imaging and Behavior. https://doi.org/10.1007/s11682-020-00269-8

  • González-Villar, A., Pidal-Miranda, M., Arias, M., Rodríguez-Salgado, D., & Carrillo-de-la-Peña, M. (2017). Electroencephalographic evidence of altered top-down attentional modulation in fibromyalgia patients during a working memory task. Brain Topography, 30(4), 539–547. https://doi.org/10.1007/s10548-017-0561-3

    Article  PubMed  Google Scholar 

  • *Han, K., Davis, R., Chapman, S., & Krawczyk, D. (2017). Strategy-based reasoning training modulates cortical thickness and resting-state functional connectivity in adults with chronic traumatic brain injury. Brain and Behavior, e00687. https://doi.org/10.1002/brb3.687

  • *Han, K., Chapman, S., & Krawczyk. (2018a). Neuroplasticity of cognitive control networks following cognitive training for chronic traumatic brain injury. Neuroimage: Clinical, 18, 262–278. https://doi.org/10.1016/j.nicl.2018.01.30

    Article  PubMed  Google Scholar 

  • *Han, K., Martinez, D., Chapman, S., & Krawczyk. (2018b). Neural correlates of reduced depressive symptoms following cognitive training for chronic traumatic brain injury. Human Brain Mapping, 39(7), 2955–2971. https://doi.org/10.1002/hbm.24052

    Article  PubMed  PubMed Central  Google Scholar 

  • Higgins, J., & Green, S. (2011). Cochrane Handbook for Systematic Reviews of Interventions (version 5.1.0). Retrieved from https://handbook.cochrane.org

  • Howieson, D. (2019). Current limitations of neuropsychological tests and assessment procedures. The Clinical Neuropsychologist, 33(2), 200–208. https://doi.org/10.1080/13854046.2018.1552762

    Article  PubMed  Google Scholar 

  • *Hu, M., Wang, X., Zhang, W., Hu, X., & Chen, A. (2017). Neural interactions mediating conflict control and its training-induced plasticity. Neuroimage, 163, 390–397. https://doi.org/10.1016/j.neuroimage.2017.07.039

    Article  PubMed  Google Scholar 

  • *Iordan, A., Cooke, K., Moored, K., Katz, B., Buschkuehl, M., Jaeggi, S., Polk, T., Peltier, S., Jonides, J., & Reuter-Lorenz, P. (2020). Neural correlates of working memory training: Evidence for plasticity in older adults. NeuroImage, 217, 116887. https://doi.org/10.1016/j.neuroiamge.2020.116887

    Article  PubMed  Google Scholar 

  • *Joles, D., van Buchem, M., Crone, E., & Rombouts, E. (2013). Functional brain connectivity at rest changes after working memory training. Human Brain Mapping, 34(2), 396–406. https://doi.org/10.1002/hbm.21444

    Article  Google Scholar 

  • Kessels, R. (2019). Improving precision in neuropsychological assessment: Bridging the gap between classic paper-and-pencil tests and paradigms from cognitive neuroscience. The Clinical Neuropsychologist, 33(2), 357–368. https://doi.org/10.1080/13854046.2018.1518489

    Article  PubMed  Google Scholar 

  • *Kim, S., Park, E., Cha, H., Jung, J., Jung, T., & Change, Y. (2020). Effects of cognitive training in mild cognitive impairment measured by resting state functional imaging. Behavioral Sciences, 20, 175. https://doi.org/10.3390/bs10110175

    Article  Google Scholar 

  • Klados, M., Styliadis, C., Frantzidis, C., Paraskevopoulos, E., & Bamidis, P. (2016). Beta-band functional connectivity is reorganized in mild cognitive impairment after combined computerized physical and cognitive training. Frontiers in Neuroscience, 10, 55. 10.3389.fnins.2016.00055.

  • Konstantinou, N., Pettemeridou, E., Stamatakis, E., Seimenis, I., & Constantinidou, F. (2019). Altered resting functional connectivity is related to cognitive outcome inn males with moderate-severe traumatic brain injury. Frontiers in Neurology, 9, 1163. https://doi.org/10.3389/fneur.2018.01163

    Article  PubMed  PubMed Central  Google Scholar 

  • *Lampit, A., Hallock, H., Suo, C., Naismith, S., & Valenzuela, M. (2015). Cognitive training-induced short-term functional and long-term structural plastic change is related to gains in global cognition in healthy older adults: A pilot study. Frontiers in Aging Neuroscience, 7, 14. https://doi.org/10.3389/fnagi.2015.00014

    Article  PubMed  PubMed Central  Google Scholar 

  • *Langer, N., von Bastian, C., Wirz, H., Oberauer, K., & Jäncke, L. (2013). The effects of working memory training on functional brain network efficiency. Cortex, 49, 2424–2438. https://doi.org/10.1016/j.cortex.2013.01.008

    Article  PubMed  Google Scholar 

  • *Leavitt, V., Wylie, G., Girgis, P., DeLuca, J., & Chiaravalloti, N. (2014). Increased functional connectivity within memory networks following memory rehabilitation in multiple sclerosis. Brain Imaging and Behavior, 8, 304–402. https://doi.org/10.1007/s11682-012-9183-2

    Article  Google Scholar 

  • *Li, T., Yao, Y., Cheng, Y., Xu, B., Cao, X., Waxman, D., Feng, W., Shen, Y., Li, Q., Wang, J., Wu, W., Li, C., & Feng, J. (2016). Cognitive training can reduce the rate of cognitive aging: A neuroimaging cohort study. BMC Geriatrics, 16(12). https://doi.org/10.1186/s12877-016-0194-5

  • *Lin, Z., Tao, J., Gao, Y., Yin, D., Chen, A., & Chen, L. (2014). Analysis of central mechanism of cognitive training on cognitive impairment after stroke: Resting-state functional magnetic ressonance imaging study. Journal of International Medical Research, 42(3), 659–668. https://doi.org/10.1177/0300060513505809

    Article  PubMed  Google Scholar 

  • Lubrini, G., Martín-Montes, A., Díez-Ascaso, O., & Díez-Tejedor, E. (2019). Brain disease, connectivity, plasticity and cognitive therapy: A neurological view of mental disorders. Neurología, 33(3), 187–191. https://doi.org/10.1016/j.nrleng.2017.02.001

    Article  Google Scholar 

  • Marchand, Y., D’Arcy, R., & Connolly, J. (2002). Linking neurophysiological and neuropsychological measures for aphasia assessment. Clinical Neurophysiology, 113, 1715–1722. https://doi.org/10.1016/s1388-2457(02)00224-9

    Article  PubMed  Google Scholar 

  • *Martínez, K., Solana, A., Burgaleta, M., Hernández-Tamames, J., Alvarez-Linera, J., Róman, F., Alfayate, E., Privado, J., Escorial, S., Quiroga, M., Karama, S., Bellec, P., & Colom, R. (2013). Changes in resting-state functionally connected parietofrontal networks after videogame practice. Human Brain Mapping, 34(12), 3413–3457. https://doi.org/10.1002/hbm.22129

    Article  Google Scholar 

  • *Momi, M., Smeralda, C., Lorenzo, G., Neri, F., Rossi, S., Rossi, A., & Santarnecchi, E. (2020). Long-lasting connectivity changes induced by intensive first-person shooter gaming. Brain Imaging and Behavior. https://doi.org/10.1007/s11682-020-00350-2

  • *Moore, A., Carpenter II, S., James, R., Miller, T., Moore, J., Disbrow, E., & Ledbetter, C. (2020). Neuroimaging and neuropsychological outcomes following clinician-delivered cognitive training for six patients with mild brain injury: A multiple case study. Frontiers in Human Neuroscience, 14, 229. 10.389.Fnhum.2020.00229.

  • Musiat, P., & Tarrier, N. (2014). Collateral outcomes in e-mental health: A systematic review of the evidence for added benefits of computerized cognitive behavior therapy interventions for mental health. Psychological Medicine, 44, 3137–3150. https://doi.org/10.1017/S0033291714000245

    Article  PubMed  Google Scholar 

  • Nickels, L., Howard, D., & Best, W. (2011). On the use of different methodologies in cognitive neuropsychology: Drink deep and from several sources. Journal of Cognitive Neuropsychology, 28(7), 475–485. https://doi.org/10.1080/02643294.2012.672406

    Article  PubMed  Google Scholar 

  • Nordvik, J., Walle, K., Nyberg, C., Fiell, A., Walhovd, K., Westlye, L., & Tornas, S. (2014). Bridging the gap between clinical neuroscience and cognitive rehabilitation: The role of cognitive training, models of neuroplasticity and advanced neuroimaging in future brain injury rehabilitation. NeuroRehabilitation, 34(1), 81–85. https://doi.org/10.3233/NRE-131017

    Article  PubMed  Google Scholar 

  • *Ochmann, S., Dyrba, M., Grothe, M., Kasper, E., Webel, S., Hauenstein, K., & Teipel, S. (2017). Does functional connectivity provide a marker for cognitive rehabilitation effects in Alzheimer’s disease? An interventional study. Journal of Alzheimer’s Disease, 57, 1303–1313. https://doi.org/10.3233/JAD-160773

    Article  PubMed  PubMed Central  Google Scholar 

  • Ouzzani, M., Hammady, H., Fedorowicz, Z., & Elmagarmind, A. (2016). Rayyan – A web and mobile app for systematic reviews. Systematic Reviews, 5, 210. https://doi.org/10.1186/s13643-016-0384-4

    Article  PubMed  PubMed Central  Google Scholar 

  • *Pareto, D., Sastre-Garriga, J., Alonso, J., Galán, I., Arévalo, M., Renom, M., Montalban, X., & Rovira, A. (2018). Classic block design “pseudo”-resting-state fMRI changes after a neurorehabilitation program in patients with multiple sclerosis. Journal of Neuroimaging, 28(3), 313–319. https://doi.org/10.1111/jon.12500

    Article  PubMed  Google Scholar 

  • *Parisi, L., Rocca, M., Mattioli, F., Copetti, M., Capra, R., Valsasina, P., Stampatori, C., & Filippi, M. (2014a). Changes of brain resting state functional connectivity predict the persistence of cognitive rehabilitation effects in patients with multiple sclerosis. Multiple Sclerosis Journa, 20(6), 686–694. https://doi.org/10.1177/1352458513505692

    Article  Google Scholar 

  • *Parisi, L., Rocca, M., Valsasina, P., Panicari, L., Mattioli, F., & Fillipi, M. (2014b). Cognitive rehabillitation correlates with the functional connectivity of the anterior cingulate cortex in patientes with multiple sclerosis. Brain Imaging and Behavior, 8, 387–393. https://doi.org/10.1007/s11682-012-9160-9

    Article  PubMed  Google Scholar 

  • Patel, R., Spreng, R., & Turner, G. (2013). Functional brain changes following cognitive and motor skills training: A quantitative meta-analysis. Neurorehabilitation and Neural Repair, 27(3), 187–199. https://doi.org/10.1177/1545968312461718

    Article  PubMed  Google Scholar 

  • *Penadés, R., Pujol, N., Catalán, R., Massana, G., Rametti, G., García-Rizo, C., Bargalló, N., Gastó, C., Bernardo, M., & Junqué, C. (2013). Brain effects of cognitive remediation therapy in schizophrenia: A structural and functional neuroimaging study. Biological Psychiatry, 73, 1015–1023. https://doi.org/10.1016/j.biopsych.2013.01.017

    Article  PubMed  Google Scholar 

  • *Porter, S., Torres, I., Panenka, W., Rajwani, Z., Fawcett, D., Hyder, A., & Virji-Badul, N. (2017). Changes in brain-behavior relationships following a 3-month pilot cognitive intervention program for adults with traumatic brain injury. Heliyon, 3, e00373. https://doi.org/10.1016/j.heliyon.2017.e00373

    Article  PubMed  PubMed Central  Google Scholar 

  • *Ramsay, I., Roach, B., Fryer, S., Fisher, M., Loewy, R., Ford, J., Vinogradov, S., & Mathalon, D. (2020). Increased global cognition correlated with increased thalamo-temporal connectivity in response to targeted cognitive training for recent onset schizophrenia. Schizophrenia Research, 218, 131–137. https://doi.org/10.1016/j.schres.2020.01.020

    Article  PubMed  Google Scholar 

  • *Ross, L., Webb, C., Whitaker, C., Hicks, J., Schmidt, E., Samimy, S., Denis, N., & Visscher, K. (2019). The effects of useful field of view training on brain activity and connectivity. Journals of Gerontology: Psychological Sciences, 74(7), 1152–1162. https://doi.org/10.1093/geronb/gby041

    Article  Google Scholar 

  • Shamseer, L., Moher, D., Clarke, M., Ghersi, D., Liberati, A., Petticrew, M., Shekelle, P., Stewart, L., & & the PISMA-P Group. (2015). Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015: Elaboration and explanation. BMJ, 349, g7647. https://doi.org/10.1136/bmj.g7647

    Article  Google Scholar 

  • Sherman, D., Mauser, J., Nuno, M., & Sherzai, D. (2017). The efficacy of cognitive intervention in mild cognitive impairment (MCI): A meta-analysis of outcomes on neuropsychological measures. Neuropsychology Review, 27(4), 440–484. https://doi.org/10.1007/s11065-017-9363-3

    Article  PubMed  PubMed Central  Google Scholar 

  • *Simon, S., Hampstead, B., Nucci, M., Ferreira, L., Duran, F., Fonseca, L., Martin, M., Ávila, R., Porto, F., Brucki, S., Martins, C., Tascone, L., Amaro Jr., E., Busatto, G., & Bottino, C. (2020). Mnemonic strategy training modulates functional connectivity at rest in mild cognitive impairment: Results from a randomized controlled trial. Alzheimer’s & Dementia: Translational Research & Clinical Interventions, 6(1), e12075. https://doi.org/10.1002/trc2.12075

    Article  Google Scholar 

  • Smith, J. D. (2012). Single-case experimental designs: A systematic review of published research and current standards. Psychological Methods, 17, 510–550. https://doi.org/10.1037/a0029312

    Article  PubMed  Google Scholar 

  • *Strenziok, M., Parasuraman, R., Clarke, E., Cisler, D., Thompson, J., & Greenwood, P. (2014). Neurocognitive enhancement in older adults: Comparison of three cognitive training tasks to test a hypothesis of training transfer in brain connectivity. Neuroimage, 85, 1027–1039. https://doi.org/10.1016/j.neuroimage.2013.07.069

    Article  PubMed  Google Scholar 

  • *Takeuchi, H., Taki, Y., Hashizume, H., Sassa, Y., Nagase, T., Nouchi, R., & Kawashima, R. (2011). Effects of training of processing speed on neural systems. The Journal of Neuroscience, 31(34), 12139–12148. https://doi.org/10.1523/jneurosci.2948-11.2011

    Article  PubMed  PubMed Central  Google Scholar 

  • *Takeuchi, H., Taki, Y., Nouchi, R., Hashizume, H., Sekiguchi, A., Kotozaki, Y., Nakagawa, S., Miyauchi, C., Sassa, Y., & Kawashima, R. (2013). Effects of working memory training on functional connectivity and cerebral blood flow during rest. Cortex, 49¸ 2106–2125. https://doi.org/10.1016/j.cortex.2012.09.007.

  • *Takeuchi, H., Taki, Y., Nouchi, R., Hashizume, H., Sekiguchi, A., Kotozaki, Y., Nakagawa, S., Miyauchi, C., Sassa, Y., & Kawashima, R. (2014). Effects of multitasking-training on gray matter structure and resting state neural mechanisms. Human Brain Mapping, 35, 3646–3660. https://doi.org/10.1002/hbm.22427

    Article  PubMed  Google Scholar 

  • *Tang, Y., Xing, Y., Zhu, Z., He, Y., Li, F., Yang, J., Liu, Q., Li, F., Teipel, S., Zhao, G., & Jia, J. (2019). The effects of 7-week training in patients with vascular cognitive impairment, no dementia (the cog-VACCINE study): A randomized controlled trial. Alzheimer’s & Dementia: The Journal of Alzheimer’s Association, 15(5), 605–614. https://doi.org/10.1016/j.jalz.2019.01.009

    Article  Google Scholar 

  • Tate, R. L., Perdices, M., Rosenkoetter, U., Wakima, D., Godbee, K., Togher, L., & McDonald, S. (2013). Revision of a method quality rating scale for single-case experimental designs and n-of-1 trials: The 15-item risk of Bias in N-of-1 trials (RoBiNT) scale. Neuropsychological Rehabilitation, 23, 619–638. https://doi.org/10.1080/09602011.203.824383

    Article  PubMed  Google Scholar 

  • *Thompson, T., Waskom, M., & Gabrieli, J. (2016). Intensive working memory training produces functional changes in large-scale frontoparietal networks. Journal of Cognitive Neuroscience, 28(4), 575–588. https://doi.org/10.1162/jocn_A_00916

    Article  PubMed  PubMed Central  Google Scholar 

  • Thorton, K., & Carmody, D. (2005). Electroencephalogram biofeedback for reading disability and traumatic brain injury. Child and Adolescent Psychiatric Clinics of North America, 14, 137–162. https://doi.org/10.1016/j.chc.2004.07.01

    Article  Google Scholar 

  • van Paasschen, J., Clare, L., Yuen, K., Woods., R., Evans, S., Parkinson, C., Rugg, M., & Linden, D. (2013). Cognitive rehabilitation changes memory-related brain activity in people with Alzheimer disease. Neurorehabilitation and Neural Repair, 27(5), 448–459.  https://doi.org/10.1177/1545968312471902.

  • *Wahlin, A., Fordell, H., Ekman, U., Lenfeldt, N., & Malm, J. (2019). Rehabilitation in chronic spatial neglect strengthens resting-state connectivity. Acta Neurologica Scandinavica, 139, 254–259. https://doi.org/10.1111/ane.13048

    Article  PubMed  Google Scholar 

  • Yang, H., Chan, P., Chang, P., Chiu, H., Hsiao, H., Chu, H., & Chou, K. (2018). Memory-focused interventions for people with cognitive disorders: A systematic review and meta-analysis of randomized controlled studies. International Journal of Nursing Studies, 78, 44–51. https://doi.org/10.1016/j.ijnurstu.2017.08.005

    Article  PubMed  Google Scholar 

Download references

Funding

This study was funded by the FCT - Fundação para a Ciência e Tecnologia [Portuguese Foundation for Science and Technology], through a doctoral grant attributed to Andreia Geraldo (SFRH/BD/138723/2018) and through R&D Units funding (UIDB/05210/2020).

Author information

Authors and Affiliations

  1. Laboratory of Neuropsychophysiology, Faculty of Psychology and Education Sciences, University of Porto, Rua Alfredo Allen, 4200-135, Porto, Portugal

    Andreia Geraldo, Artemisa Rocha Dores & Fernando Barbosa

  2. School of Health, Polytechnic Institute of Porto, Porto, Portugal

    Artemisa Rocha Dores

  3. Institute of Health Sciences, Catholic University of Portugal, Lisbon, Lisbon, Portugal

    Alexandre Castro-Caldas

Authors
  1. Andreia Geraldo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Artemisa Rocha Dores
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Alexandre Castro-Caldas
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Fernando Barbosa
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Andreia Geraldo.

Ethics declarations

The authors do not have any interests that might be interpreted as influencing the research. The study was conducted according to APA ethical standards.

Conflict of Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Informed Consent

This manuscript does not imply the direct involvement of human participants; therefore no informed consents were signed.

Ethics Approval

This manuscript does not imply the direct involvement of human participants or animals.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Geraldo, A., Dores, A.R., Castro-Caldas, A. et al. Functional connectivity as a neural correlate of cognitive rehabilitation programs’ efficacy: A systematic review. Curr Psychol 42, 17918–17934 (2023). https://doi.org/10.1007/s12144-022-02989-0

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12144-022-02989-0

Keywords

Search

Navigation