Pesaresi A, La Cava P, Bonada M, Zeppa P, Melcarne A, Cofano F et al (2024) Combined fluorescence-guided surgery with 5-aminolevulinic acid and fluorescein in glioblastoma: technical description and report of 100 cases. Cancers 16(16):2771

CAS  PubMed  PubMed Central  Google Scholar 

Kersten-Oertel M, Chen SJ-S, Collins DL (2013) An evaluation of depth enhancing perceptual cues for vascular volume visualization in neurosurgery. IEEE Trans Vis Computer Graph 20(3):391–403

Google Scholar 

Simpson AL, Ma B, Vasarhelyi EM, Borschneck DP, Ellis RE, James SA (2014) Computation and visualization of uncertainty in surgical navigation. The Int J Med Robot Computer Assist Surg 10(3):332–343

Google Scholar 

Gregory RL (1977) Eye and brain : the psychology of seeing. 3d ed. London: Weidenfeld and Nicolson

Abeele S, Bock O (2001) Mechanisms for sensorimotor adaptation to rotated visual input. Exp Brain Res 139(2):248–253

CAS  PubMed  Google Scholar 

Harris CS (1965) Perceptual adaptation to inverted, reversed, and displaced vision. Psychol Rev 72(6):419–444

CAS  PubMed  Google Scholar 

Masia L, Casadio M, Sandini G, Morasso P (2009) Eye-hand coordination during dynamic visuomotor rotations. PLoS ONE 4(9):e7004. https://doi.org/10.1371/journal.pone.0007004

Article  CAS  PubMed  PubMed Central  Google Scholar 

Onceanu D, Stewart AJ (2011) Direct surgeon control of the computer in the operating room. Med Image Comput Comput Assist Interv 14(Pt 1):121–128

PubMed  Google Scholar 

Titov A, Kersten-Oertel M, Drouin S (2022) The effect of interactive cues on the perception of angiographic volumes in virtual reality. Computer Methods Biomech and Biomedical Engineering: Imaging & Visualization 10(4):357–365

Google Scholar 

Drouin S, DiGiovanni DA, Kersten-Oertel MA, Collins L (2018) Interaction driven enhancement of depth perception in angiographic volumes. IEEE Trans Vis Computer Graph 26(6):2247–2257

Google Scholar 

Malhotra S, Halabi O, Dakua SP, Padhan J, Paul S, Palliyali W (2023) Augmented reality in surgical navigation: a review of evaluation and validation metrics. Appl Sci 13(3):1629

CAS  Google Scholar 

Plazak J, Kersten-Oertel M (2018) A Survey on the Affordances of “Hearables.” Inventions 3(3):48

Google Scholar 

Wilson JP Jr, Fontenot L, Stewart C, Kumbhare D, Guthikonda B, Hoang S (2024) Image-guided navigation in spine surgery: from historical developments to future perspectives. J Clin Med 13(7):2036

PubMed  PubMed Central  Google Scholar 

Lex JR, Koucheki R, Toor J, Backstein DJ (2023) Clinical applications of augmented reality in orthopaedic surgery: a comprehensive narrative review. Int Orthop 47(2):375–391

PubMed  Google Scholar 

Kitaguchi D, Takeshita N, Hasegawa H, Ito M (2022) Artificial intelligence-based computer vision in surgery: recent advances and future perspectives. Annals Gastroenterol Surg 6(1):29–36

Google Scholar 

Chan HH, Haerle SK, Daly MJ, Zheng J, Philp L, Ferrari M et al (2021) An integrated augmented reality surgical navigation platform using multi-modality imaging for guidance. PLoS ONE 16(4):e0250558

CAS  PubMed  PubMed Central  Google Scholar 

Wildes TS, Mickle AM, Abdallah AB, Maybrier HR, Oberhaus J, Budelier TP et al (2019) Effect of electroencephalography-guided anesthetic administration on postoperative delirium among older adults undergoing major surgery: the ENGAGES randomized clinical trial. JAMA 321(5):473–483

PubMed  PubMed Central  Google Scholar 

Uda T (2023) Neuroimaging of brain tumor surgery and epilepsy. MDPI 13(12):1701

Google Scholar 

Lin Z, Lei C, Yang L (2023) Modern image-guided surgery: a narrative review of medical image processing and visualization. Sensors 23(24):9872

PubMed  PubMed Central  Google Scholar 

Almukhtar A, Caddick V, Naik R, Goble M, Mylonas G, Darzi A et al (2024) Objective assessment of cognitive workload in surgery: a systematic review. Annals Surg 281(6):942–951

Google Scholar 

Blinn JF (1977) Models of light reflection for computer synthesized pictures. In: Proceedings of the 4th annual conference on Computer graphics and interactive techniques 192–198

Allen RC, Rubin ML (1981) Chromostereopsis. Surv Ophthalmol 26(1):22–27

CAS  PubMed  Google Scholar 

Anderson EW, Potter KC, Matzen LE, Shepherd JF, Preston GA, Silva CT (2011) A user study of visualization effectiveness using EEG and cognitive load. Computer Graph Forum 30:791–800

Google Scholar 

Antonenko P, Paas F, Grabner R, Van Gog T (2010) Using electroencephalography to measure cognitive load. Educ Psychol Rev 22(4):425–438

Google Scholar 

Baijal S, Srinivasan N (2010) Theta activity and meditative states: spectral changes during concentrative meditation. Cogn Process 11(1):31–38

PubMed  Google Scholar 

Gevins A, Smith ME, Leong H, McEvoy L, Whitfield S, Du R et al (1998) Monitoring working memory load during computer-based tasks with EEG pattern recognition methods. Hum Factors 40(1):79–91

CAS  PubMed  Google Scholar 

Klimesch W (1999) EEG alpha and theta oscillations reflect cognitive and memory performance: a review and analysis. Brain Res Rev 29(2–3):169–195

CAS  PubMed  Google Scholar 

Jensen O, Tesche CD (2002) Frontal theta activity in humans increases with memory load in a working memory task. Eur J Neurosci 15(8):1395–1399

PubMed  Google Scholar 

Michels L, Moazami-Goudarzi M, Jeanmonod D, Sarnthein J (2008) EEG alpha distinguishes between cuneal and precuneal activation in working memory. Neuroimage 40(3):1296–1310

PubMed  Google Scholar 

Bird JJ, Manso L, Ribiero E, Ekart A, Faria D (2018) A study on mental state classification using EEG-based brain-machine interface.In: 9th International Conference on Intelligent Systems, IEEE, Portugal, 25–27 September 2018

Byrom B, McCarthy M, Schueler P, Muehlhausen W (2018) Brain monitoring devices in neuroscience clinical research: the potential of remote monitoring using sensors, wearables, and mobile devices. Clin Pharmacol Ther 104(1):59–71

PubMed  PubMed Central  Google Scholar 

Krigolson OE, Williams CC, Norton A, Hassall CD, Colino FL (2017) Choosing MUSE: validation of a low-cost, portable EEG system for ERP research. Front Neurosci 11:109

PubMed  PubMed Central  Google Scholar 

Negi S, Mitra R (2018) EEG Metrics to determine cognitive load and affective states: a pilot study. In: Proceedings of the 2018 ACM International Joint Conference and 2018 international symposium on pervasive and ubiquitous computing and wearable computers ACM

Dias RD, Ngo-Howard MC, Boskovski MT, Zenati MA, Yule SJ (2018) Systematic review of measurement tools to assess surgeons’ intraoperative cognitive workload. J British Surg 105(5):491–501

CAS  Google Scholar 

Oostenveld R, Fries P, Maris E, Schoffelen J-M (2011) FieldTrip: open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data. Comput Intell Neurosci 2011:1

Google Scholar 

Castro-Meneses LJ, Kruger J-L, Doherty S (2020) Validating theta power as an objective measure of cognitive load in educational video. Edu Tech Res Dev 68:181–202

Google Scholar 

Vasey MW, Thayer JF (1987) The continuing problem of false positives in repeated measures ANOVA in psychophysiology: a multivariate solution. Psychophysiology 24(4):479–486

CAS  PubMed  Google Scholar