Highly specific & validated brain tests meet the precision and objectivity of EEG-based neuroimaging, processed and summarized into a user-friendly report.
The VoxNeuro Advantage
VoxNeuro’s Cognitive Health Assessment™, like CT and MRI scans, are a form of neuroimaging. The EEG-based neuroimaging assessment uses neuropsychological testing to trigger a patient’s neurological responses. The 45-minute test is designed to challenge one or more cognitive abilities at a time, and the patient’s real-time brain responses are recorded throughout the duration of the test. The data collected produces a visual recording of the patient’s brain activity. Within each recording, neuro-markers are tracked that indicate the performance of a patient’s brain. These neuro-markers are called event related potentials, or ERPs for short.
The figure above shows example brain waveforms recorded by VoxNeuro’s Cognitive Health Assessment EEG methodologies comparing the brain responses of healthy controls to a patient who has suffered a concussion. The N1, indicative of auditory and visual processing, and MMN, indicative of automatic attention, ERP responses in the patient’s data are significantly reduced compared to healthy controls.
Comparing methods of assessing brain health
Healthcare professionals commonly use the following tools to help assess and diagnose brain conditions or injuries:
1. Behavioural and neuropsychological tests: used to measure symptoms, mood and behavioural changes
2. Traditional neuroimaging: magnetic resonance imaging (MRI) and computed tomography (CT) scans are useful in identifying structural injuries associated with the brain. For example, injuries such as skull fractures, brain tumors, and lesions
How Cognitive Health Assessments™ are different from traditional EEG
Quantitative EEG (qEEG) is an improvement on traditional EEG. It produces digital recordings, allowing clinicians to analyze the data on the computer, instead of simply looking at the brain waves in a static image. EEG testing available in most hospitals and clinics only measure “resting state”, which is exactly as it sounds – measuring a patient’s brain activity when they are at rest & not actively engaging in or completing any tasks.
Instead of relying on “resting state” EEG testing, VoxNeuro’s Cognitive Health Assessments™ drive active engagement. Each test in the assessment can be thought of as a performance-test for the brain’s core functions. By measuring each core function while the patient is actively engaged with the test, VoxNeuro is able to provide objective data to confirm which functions require rehabilitation or treatment, and which functions are performing at healthy levels.
Dr. John F. Connolly is the Chief Science Officer and co-founder of VoxNeuro. Dr. Connolly earned his PhD from the Institute of Psychiatry, Psychology & Neuroscience at King’s College, London. He currently holds the Senator William McMaster Chair in Cognitive Neuroscience, is the founding director of the ARiEAL Research Centre, and co-directs the Language, Memory and Brain Lab. He is an author on over 330 articles, chapters, and presentations, most of which involve EEG/ERP, MEG and MRI studies of cognition in health and brain pathology.
The scientific breakthrough in brain assessment.
In 1999, Dr. Connolly was the first person in the world to demonstrate that a patient (mis)diagnosed as being in a vegetative state (now referred to as Unresponsive Wakefulness Syndrome) was actually in a locked-in state, meaning the patient was fully functioning cognitively but experiencing near-complete physical paralysis. After 9 months of successful cognitive rehabilitation efforts, the patient had regained complete motor control and was discharged, walking himself out of the hospital. This landmark case led to the development of EEG-based methods of assessing conscious states and mental functions in patient populations including autism, Unresponsive Wakefulness Syndrome (vegetative state), coma, and concussion. This research forms the foundation of VoxNeuro’s Cognitive Health Assessments™.
The following collection of publications and peer reviewed journals document the evidence based research behind the methods performed in VoxNeuro’s Cognitive Health Assessments™ (CHA).
Neurophysiological markers of cognitive deficits and recovery in concussed adolescents
Ruiter, K. I., Boshra, R., DeMatteo, C., Noseworthy, M., Connolly, J. C. (2020)
Brain Research, 146998
On the time-course of functional connectivity: theory of a dynamic progression of concussion effects
Boshra, R., Ruiter, K. I., Sonnadara, R., Reilly, J. P., Connolly, J. C. (2020)
Brain Communications, fcaa063
Neurophysiological Correlates of Concussion: Deep Learning for Clinical Assessment
Boshra, R., Ruiter, K. I., DeMatteo, C., Reilly, J. P., Connolly, J. C. (2019)
Nature Scientific Reports, 9 (17341)
From Group-Level Statistics to Single-Subject Prediction: Machine Learning Detection of Concussion in Retired Athletes
Boshra, R., Dhindsa, K., Boursalie, O., Ruiter, K. I., Sonnadara, R., Samavi, R., Doyle, T. E., Reilly, J. P., Connolly, J. F. (2019)
Disruption of Function: Neurophysiological markers of cognitive deficits in retired football players
Ruiter, K. I., Boshra, R., Doughty, M., Noseworthy, M., Connolly, J. F. (2019)
Clinical Neurophysiology, 130(1): 111-121
Disorders of Consciousness
Global Aphasia: An innovative assessment approach
Connolly, J. F., Mate-Kole, C., Joyce, B. M. (1999)
Archives of Physical Medicine and Rehabilitation, 80(10): 1309-1315
Linking neurophysiological and neuropsychological measures for aphasia assessment
Marchand, Y., D’Arcy, R., Connolly, J. F. (2002)
Clinical Neurophysiology, 113(11)
Development of a point of care system for automated coma prognosis: a prospective cohort study protocol
Connolly, J. F., Reilly, J. P., Fox-Robichaud, A., Britz, P., Blain-Moraes, S., Sonnadara, R., Hamielec, C., Herrera-Diaz, A., Boshra, R. (2019)
BMJ Open, 9(7)
Automatic and continuous assessment of ERPs for mismatch negativity detection
Armanfard, N., Kameili, M., Reilly, J. P., Mah, R., Connolly, J. F. (2016)
Automatic and continuous assessment of ERPs for mismatch negativity detection
Blain-Moraes, S., Boshra, R., Kan Ma, H., Mah, R., Ruiter, K. I., Avidan, M., Connolly, J. F., Mashour, G. A. (2016)
Frontiers in Human Neuroscience
Pediatric Communication Impairments
Assessment of children’s receptive vocabulary using event related potentials; Development of clinically validated test
Byrne, J. M., Dywan, C. A., Connolly, J. F. (1995).
Child Neuropsychology, 1(3): 211-223
Assessing adult receptive vocabulary with event related potentials: An investigation of cross-modal and cross-form priming
Connolly, J. F., Byrne, J. M., Dywan, C. A. (1995)
Journal of Clinical and Experimental Neuropsychology, 17(4)
An innovative method to assess the receptive vocabulary of children with cerebral palsy using event-related potentials
Byrne, J. M., Dywan, C. A., Connolly, J. F. (1995)
Journal of Clinical and Experimental Neuropsychology, 17(1): 9-19
Brain activity and language assessment using event-related potentials: development of a clinical protocol
Byrne, J. M., Connolly, J. F., MacLean, S. E., Dooley, J. M., Gordon, K. E., Beattie, T. L. (1999)
Developmental Medicine & Clinical Neurology, 41(11)
Brain Activity and Cognitive Status in Pediatric Patients: Development of a Clinical Assessment Protocol
Byrne, J. M., Connolly, J. F., MacLean, S. E., Beattie, T. L., Dooley, J. M., Gordon, K. E. (2001)
Journal of Child Neurology, 16(5): 325-332
Electrophysiological evidence for the integral nature of tone in Mandarin spoken word recognition
Ho, A., Boshra, R., Schmidtke, D., Oralova, G., Moro, A. L., Service, E., Connolly, J. F. (2019)
Neuropsychologia, 131: 325-332
Electroencephalography & Event-Related Potential Literature
1. Byrne, J.M., Connolly, J.F., McLean, S.E., Beattie, T.L., Dooley, J.M., & Gordon, K.E. (2001). Brain activity and cognitive status in pediatric patients: Development of a clinical assessment protocol. Journal of Child Neurology, 16, 325-332. DOI: 10.1177/088307380101600504
2. Connolly, J.F., D’Arcy, R.C.N., Newman, R.L., & Kemps, R. (2000). The application of cognitive event-related brain potentials (ERPs) in language- impaired individuals: Review and case studies (Invited Review: Ed. Dr. J. Polich). International Journal of Psychophysiology, 38, 55-70.
3. Connolly, J.F. & D’Arcy, R.C.N. (2000). Innovations in neuropsychological assessment using event-related brain potentials (Invited Review). International Journal of Psychophysiology, 37, 31-47. DOI: 10.1016/S0167-8760(00)00093-3
4. D’Arcy, R.C.N. & Connolly, J.F. (1999). An event-related brain potential study of receptive speech comprehension using a modified Token Test. Neuropsychologia, 37, 1477-1489. DOI: 0.1016/S0028-3932(99)00057-3
5. D’Arcy, R.C.N., Connolly, J.F., & Eskes, G. A. (2000). Evaluation of reading comprehension with neuropsychological and event-related brain potential (ERP) methods. Journal of the International Neuropsychological Society, 6, 556-567. LINK: researchgate.net
6. Duncan CC, Barry RJ, Connolly JF, et al. Event-related potentials in clinical research: guidelines for eliciting, recording, and quantifying mismatch negativity, P300, and N400. Clin Neurophysiol. 2009;120(11):1883–1908. DOI: 10.1016/j.clinph.2009.07.045
7. Frishkoff, G., Sydes, J., Mueller, K., Frank, R., Curran, T., Connolly, J., Kilborn, K., Molfese, D., Perfetti, C., & Malony, A. (2011). Minimal Information for Neural Electromagnetic Ontologies (MINEMO): A standards- compliant method for analysis and integration of event-related potentials (ERP) data. Standards in Genomic Sciences, 5(2): 211–223. DOI: 10.4056/sigs.2025347
8. Folstein JR, Van Petten C. Influence of cognitive control and mismatch on the N2 component of the ERP: a review. Psychophysiology. 2008;45(1):152–170.
9. Harker, K.T. & Connolly, J.F. (2007). Assessment of visual working memory using event-related potentials. Clinical Neurophysiology, 118, 2479–2488. DOI: 10.1016/j.clinph.2007.07.026
10. Heil M, Osman A, Wiegelmann J, Rolke B, Hennighausen E. N200 in the Eriksen-task: Inhibitory executive process? J Psychophysiol. 2000;14(4):218–218.
11. Kok A. On the utility of P3 amplitude as a measure of processing capacity. Psychophysiology. 2001;38(3):557–577.
12. Kutas M, McCarthy G, Donchin E. Augmenting mental chronometry: the P300 as a measure of stimulus evaluation time. Science. 1977;197(4305):792–795.
13. Lefebvre, C.D., Marchand, Y., Eskes, G.A., & Connolly, J.F. (2005). Assessment of working memory abilities using an event-related brain potential (ERP)-compatible digit span backward task. Clinical Neurophysiology, 116, 1665-1680. DOI: 10.1016/j.clinph.2005.03.015
14. Light GA, Swerdlow NR, Braff DL. Preattentive sensory processing as indexed by the MMN and P3a brain responses is associated with cognitive and psychosocial functioning in healthy adults. J Cogn Neurosci. 2007;19(10):1624–1632.
15. Lim CL, Gordon E, Rennie C, et al. Dynamics of SCR, EEG, and ERP activity in an oddball paradigm with short interstimulus intervals. Psychophysiology. 1999;36(5):543–551.
16. Marchand, Y., Lefebvre, C., & Connolly, J.F. (2006). Correlating digit span performance and event-related potentials to assess working memory. International Journal of Psychophysiology, 62, 280-289. DOI: 10.1016/j.ijpsycho.2006.05.007
17. Näätänen R, Gaillard AWK. 5 The orienting reflex and the N2 deflection of the event-related potential (ERP). 1983 Epub.
18. Näätänen R, Gaillard AWK, Mäntysalo S. Early selective-attention effect on evoked potential reinterpreted. Acta Psychol (Amst). 1978;42(4):313–329.
19. Näätänen R, Paavilainen P, Rinne T, Alho K. The mismatch negativity (MMN) in basic research of central auditory processing: a review. Clin Neurophysiol. 2007;118(12):2544–2590.
20. Näätänen R, Picton T. The N1 wave of the human electric and magnetic response to sound: a review and an analysis of the component structure. Psychophysiology. 1987;24(4):375–425.
21. Patel SH, Azzam PN. Characterization of N200 and P300: selected studies of the event-related potential. Int J Med Sci. 2005;2(4):147–147.
22. Polich J. Updating P300: an integrative theory of P3a and P3b. Clin Neurophysiol. 2007;118(10):2128–2148.
23. Polich J. Task difficulty, probability, and inter-stimulus interval as determinants of P300 from auditory stimuli. Electroencephalogr Clin Neurophysiol Potentials Sect. 1987;68(4):311–320.
24. Polich J. Normal variation of P300 from auditory stimuli. Electroencephalogr Clin Neurophysiol Potentials Sect. 1986;65(3):236–240.
25. Polich J, Howard L, Starr A. P300 latency correlates with digit span. Psychophysiology. 1983;20(6):665–669.26. Reinvang, I. (1999). Cognitive event-related potentials in neuropsychological assessment. Neuropsychol. Rev. 9, 231–248.
26. Reinvang, I. (1999). Cognitive event-related potentials in neuropsychological assessment. Neuropsychol. Rev. 9, 231–248.
Concussion Event-Related Potential Literature
1. Baillargeon A, Lassonde M, Leclerc S, Ellemberg D. Neuropsychological and neurophysiological assessment of sport concussion in children, adolescents and adults. Brain Inj. 2012;26(3):211–220.
2. Broglio SP, Moore RD, Hillman CH. A history of sport-related concussion on event-related brain potential correlates of cognition. Int J Psychophysiol. 2011;82(1):16–23.
3. Broglio SP, Pontifex MB, O’Connor P, Hillman CH. The persistent effects of concussion on neuroelectric indices of attention. J Neurotrauma. 2009;26(9):1463–1470.
4. De Beaumont L, Lassonde M, Leclerc S, Théoret H. Long-term and cumulative effects of sports concussion on motor cortex inhibition. Neurosurgery. 2007;61(2):329–337.
5. De Beaumont L, Theoret H, Mongeon D, et al. Brain function decline in healthy retired athletes who sustained their last sports concussion in early adulthood. Brain. 2009;132(3):695–708.
6. De Beaumont L, Beauchemin M, Beaulieu C, Jolicoeur P. Long-term attenuated electrophysiological response to errors following multiple sports concussions. Journal of clinical and experimental neuropsychology. 2013 Jul 1;35(6):596-607.
7. Dupuis F, Johnston KM, Lavoie M, Lepore F, Lassonde M. Concussions in athletes produce brain dysfunction as revealed by event-related potentials. Neuroreport. 2000;11(18):4087–4092.
8. Ellemberg D, Henry LC, Macciocchi SN, Guskiewicz KM, Broglio SP. Advances in sport concussion assessment: from behavioral to brain imaging measures. Journal of neurotrauma. 2009 Dec 1;26(12):2365-82.
9. Gaetz M, Goodman D, Weinberg H. Electrophysiological evidence for the cumulative effects of concussion. Brain Inj. 2000;14(12):1077–1088.
10. Gawryluk, J.R., D’Arcy, R.C.N., Connolly, J.F., & Weaver, D.F. (2010). Improving the clinical assessment of consciousness with advances in electrophysiological and neuroimaging techniques. BMC Neurology, 10:11. DOI: 10.1186/1471-2377-10-11
11. Gosselin N, Bottari C, Chen J-K, et al. Evaluating the cognitive consequences of mild traumatic brain injury and concussion by using electrophysiology. Neurosurg Focus. 2012;33(6):E7–E7.
12. Johnston KM. New investigative tools in concussion. British Journal of Sports Medicine. 2001 Oct 1;35(5):371-.
13. Harrison, A. & Connolly, J.F. (2013). Finding a way in: a review and practical evaluation of fMRI and EEG in disorders of consciousness. Neuroscience and Biobehavioral Reviews, 37(8):1403-1419. DOI: 10.1016/j.neubiorev.2013.05.004.
14. Henry LC, Tremblay S, De Beaumont L. Long-term effects of sports concussions: bridging the neurocognitive repercussions of the injury with the newest neuroimaging data. The Neuroscientist. 2017 Oct;23(5):567-78.
15. Hudac CM, Cortesa CS, Ledwidge PS, Molfese DL. History of concussion impacts electrophysiological correlates of working memory. International journal of psychophysiology. 2017 Oct 10.
16. Ledwidge PS, Molfese DL. Long-term effects of concussion on electrophysiological indices of attention in varsity college athletes: An event-related potential and standardized low-resolution brain electromagnetic tomography approach. Journal of neurotrauma. 2016 Dec 1;33(23):2081-90.
17. Lovell, M. R., Collins, M. W., Iverson, G. L., Field, M., Maroon, J. C., Cantu, R., … & Fu, F. H. (2003). Recovery from mild concussion in high school athletes. Journal of neurosurgery, 98(2), 296-301.
18. Mizrahi, E. M., & Kellaway, P. (1984). Cerebral concussion in children: assessment of injury by electroencephalography. Pediatrics, 73(4), 419-425.
19. Pratap‐Chand, R., Sinniah, M., & Salem, F. A. (1988). Cognitive evoked potential (P300): a metric for cerebral concussion. Acta Neurologica Scandinavica, 78(3), 185-189.
20. Moore DR, Pindus DM, Raine LB, Drollette ES, Scudder MR, Ellemberg D, Hillman CH. The persistent influence of concussion on attention, executive control and neuroelectric function in preadolescent children. International Journal of Psychophysiology. 2016 Jan 1;99:85-95.
21. Ozen, L. J., Itier, R. J., Preston, F. F., & Fernandes, M. A. (2013). Long-term working memory deficits after concussion: electrophysiological evidence. Brain injury, 27(11), 1244-1255.22.
22. Thériault M, De Beaumont L, Tremblay S, Lassonde M, Jolicoeur P. Cumulative effects of concussions in athletes revealed by electrophysiological abnormalities on visual working memory. Journal of clinical and experimental neuropsychology. 2011 Jan 5;33(1):30-41.
Disorders of Consciousness & Coma Event-Related Potential Literature
1. ArmanFard, N., Komeili, M., Reilly, J. & Connolly, J. (2018). A machine learning framework for automatic and continuous MMN detection with preliminary results for coma outcome prediction. IEEE Journal of Biomedical and Health Informatics [Epud ahead of print]. DOI: 10.1109/JBHI.2018.2877738.
2. Blain-Moraes, S., Boshra, R., Ma, H.K., Mah, R., Ruiter, K., Avidan, M., Connolly, J.F. and Mashour, G.A. (2016). Normal brain response to propofol in advance of recovery from unresponsive wakefulness syndrome. Frontiers in Human Neuroscience. 2016 June 2; 10:248. DOI: 10.3389/fnhum.2016.00248
3. Connolly, J.F., Mate-Kole, C.C., & Joyce, B.M. (1999). Global aphasia: An innovative assessment approach. Archives of Physical Medicine and Rehabilitation, 80, 1309-1315. LINK: archives.pmr.org
4. Connolly, J.F., Major, A., Allen, S., & D’Arcy, R.C.N. (1999). Performance on WISC-III and WAIS-R NI vocabulary subtests assessed with event-related brain potentials: An innovative method of assessment. Journal of Clinical and Experimental Neuropsychology, 21, 444-464. DOI: 10.1076/jcen.21.4.444.879
5. Connolly, J.F, Marchand, Y., Major, A., & D’Arcy, R.C.N. (2006). Event- related brain potentials as a measure of performance on WISC-III and WAIS- R NI Similarities sub-tests. Journal of Clinical & Experimental Neuropsychology, 28, 1327-1345. DOI: 10.1080/13803390500428484
6. Fischer C, Luaute J, Morlet D. Event-related potentials (MMN and novelty P3) in permanent vegetative or minimally conscious states. Clin Neurophysiol. 2010;121(7):1032–1042.
7. Mah, R., & Connolly, J. (2018). A framework for the extended monitoring of levels of cognitive function in unresponsive patients. PLoS ONE, 13(7): e0200793. DOI: 10.1371/journal.pone.0200793
8. Morlet D, Fischer C. MMN and novelty P3 in coma and other altered states of consciousness: a review. Brain Topogr. 2014;27(4):467–479
9. Wang, J.T., Young, G.B., & Connolly, J.F. (2004). Prognostic value of evoked responses and event-related brain potentials in coma. Canadian Journal of Neurological Sciences, 31, 438- 450. DOI: 10.1017/S0317167100003619
10. Young, G.B., Wang, J.T., & Connolly, J.F. (2004). Prognostic determination in anoxic-ischemic and traumatic encephalopathies. Journal of Clinical Neurophysiology, 21, 379-390. Link: europepmc.org/abstract/med/15592010
Stroke Event-Related Potential Literature
1. D’Arcy, R.C.N., Marchand, Y., Eskes, G.A., Harrison, E.R., Phillips, S. J., Major, A., & Connolly, J.F. (2003). Electrophysiological assessment of language function following stroke. Clinical Neurophysiology, 114, 662-672. DOI: 10.1016/S1388-2457(03)00007-5
Pain Event-Related Potential Literature
1. Dick, B.D., Connolly, J.F., McGrath, P.J., Finley, G.A., Stroink, G., Houlihan, M.E., & Clark, A.J. (2003). The disruptive effect of chronic pain on mismatch negativity. Clinical Neurophysiology, 114, 1497-1506. DOI: 10.1016/S1388-2457(03)00133-0
2. Dick, B.D., Connolly, J.F., Houlihan, M.E., McGrath, P.J., Finley, G.A., Stroink, G., & Clark, A. J. (2006). Effects of experimental pain on Mismatch Negativity. Journal of Psychophysiology, 20(1), 21-31. DOI: 10.1027/0269-8803.20.1.21
3. Houlihan, M.E., McGrath, P.J., Connolly, J.F., Stroink, G., Finley G.A., Dick, B., & Phi, T.T. (2004). Assessing the effect of pain on demands for attentional resources using ERPs. International Journal of Psychophysiology, 51, 181-187. DOI: 10.1016/j.ijpsycho.2003.08.001
4. Troche, S.J., Houlihan, M.E., Connolly, J.F., Dick, B.D., McGrath, P.J., Finley, G.A. and Stroink, G. (2014). The effect of pain on involuntary and voluntary capture of attention. European Journal of Pain, Article first published online: 23 JUL 2014 | DOI: 10.1002/ejp.553