The Fundamental and Applied Electroencephalography Laboratory

A specialist Brain Research & Imaging Centre (BRIC) laboratory that is enhancing our research into perceptual, motor, cognitive, and social abilities
EEG Lab

The Fundamental and Applied Electroencephalography Laboratory

A specialist Brain Research & Imaging Centre (BRIC) laboratory that is enhancing our research into perceptual, motor, cognitive, and social abilities
Electroencephalography (EEG) records the brain’s electrical activity with millisecond precision, giving researchers a unique view of how the brain supports perception, thought, movement, emotion, and social interaction. By studying these fast-changing signals, we can better understand how the brain works in everyday life and how it is affected in mental health conditions.
The Fundamental and Applied Electroencephalography laboratory in the Brain Research & Imaging Centre (BRIC) led by Dr Giorgio Ganis, houses stationary, MRI-compatible, and mobile EEG systems. This state-of-the-art facility provides an integrated environment where EEG can be used on its own or combined with other brain-imaging and stimulation techniques, fostering collaboration, innovation, and new research opportunities. Importantly, the lab also contributes to teaching and community engagement, providing a hands-on environment for training and supporting our Human Neuroscience undergraduate and postgraduate programmes.
Perceptual, motor, cognitive, and social abilities are critical for people’s interactions with the physical and social world in their everyday lives.
Electroencephalography (EEG) measures electrical activity in the brain with high temporal resolution. This means that we can find out more about the neural processes that support these abilities, advancing not only basic research but, ultimately, research in mental health and other applied fields.
 
 

Investigating the neural bases of perceptual, motor, cognitive, and social abilities

A key focus of the lab is the development of multimodal approaches that integrate EEG with complementary techniques to study the brain’s dynamics in real time. Recent work led by Dr Giorgio Ganis , in collaboration with Dr Suraya Dunsford and Professor Elsa Fouragnan , has combined EEG, fMRI, and transcranial ultrasound stimulation (TUS) to investigate how ultrasound influences activity in the visual cortex, advancing its use as a non-invasive tool to modulate brain function. This research is further extended by Dr Paolo Di Luzio, who applies a similar multimodal framework to examine how deep brain circuits involved in action control are modulated across different timescales. Another example of this multimodal strategy involves simultaneous EEG–fMRI, enabled by the lab’s state-of-the-art systems and the complementary expertise of Dr Andrea Pisauro and Professor Elsa Fouragnan. This capability combines high temporal and spatial precision, offering new opportunities to explore how brain networks interact in real time.
The lab also contributes to hyperbaric neuroscience, through a collaboration between BRIC and DDRC Healthcare led by Professor Stephen Hall and Professor Gary Smerdon. This research uses mobile EEG to study how changes in oxygen levels – both reduced (hypoxia) and increased (hyperoxia) – affect cognition, behaviour, and neural activity. The work provides insight into how oxygen influences brain function and how hyperbaric oxygen therapy (HBOT) might support treatments for neurological conditions.
Another methodological direction within the lab focuses on EEG-based neurofeedback and brain–computer interface technologies. Dr Krithika Anil is a key contributor in this area, investigating how individuals learn to self-regulate brain rhythms and how such training can support people with conditions such as Parkinson’s disease. Her research also examines how psychological factors, including self-efficacy and emotion, influence neurofeedback performance, combining cutting-edge EEG techniques with an emphasis on human learning and motivation.
The lab is also exploring innovative approaches to EEG acquisition through a new collaboration with Dr Om Prakash Singh . This partnership aims to test the potential of microneedle electrode technology for EEG applications, with the goal of improving signal quality and participant comfort in future neuroimaging studies.
Examples of complementary research within the wider network of EEG studies at the University explore how the brain perceives and interprets the world. Dr Charles Or focuses on visual perception, examining how the brain recognises faces, movement, and complex visual patterns through the combined use of EEG, eye-tracking, and behavioural methods. Dr Matt Roser studies how the brain evaluates the plausibility of physical interactions and directs attention to meaningful events, with a broader interest in how these processes can be affected by brain injury.
Dr Matthew Hudson investigates the neural mechanisms that support social interaction, focusing on how the brain predicts and interprets other people’s actions. His research applies predictive-coding models to social perception, using EEG and functional near-infrared spectroscopy (fNIRS) to study how expectations about others’ goals and intentions shape sensorimotor and frontal-cortex activity. He also examines how these predictive processes differ in autism, contributing to theoretical accounts such as the “double empathy” framework. Complementary work explores the neural basis of vicarious embarrassment (“cringe”), revealing how social emotions are processed even when we are not directly involved in the events we witness. Together, their expertise complements the lab’s core interests and strengthens the University’s growing EEG research community.
Under the leadership of Dr Giorgio Ganis, the EEG Lab is actively engaged in open-science and international replication initiatives that promote transparency and rigour across the EEG research community, including leadership of one of the EEGManyLabs projects. The lab also contributes to the development of frameworks and software tools for improving standards in EEG research publication through the ARTEM-IS initiative. Together, these efforts foster cross-lab collaboration, shared best practices, and greater reproducibility in cognitive neuroscience.
Finally, the EEG Lab provides an active training and outreach environment. It supports undergraduate, postgraduate, and doctoral research, including PhD projects on social cognition (Tigan Schofield), visual neuroscience (Claire Vanbuckhave), pain (Sam Mugglestone), hyperbaric neuroscience (Daniel Graham), and sleep and cognition (Hannah Windmill). As part of BRIC, the lab also engages in community and public science events, helping to broaden understanding of how brain research informs mental health and human performance.
EEG Lab
EEG Lab
EEG lab

Researchers

Key publications

Ward E, Ganis G & Bach P 2019. Spontaneous vicarious perception of the content of others’ visual perspective. Current Biology 29(5) 874-880.

Hsu CW, Begliomini C, Dall'Acqua T, Ganis G 2019. The effect of mental countermeasures on neuroimaging-based concealed information tests. Human Brain Mapping 40(10):2899-2916.

Zabelina DL, Ganis G 2018. Creativity and cognitive control: Behavioral and ERP evidence that divergent thinking, but not real-life creative achievement, relates to better cognitive control. Neuropsychologia 118, 20-28.

Ganis G, Bridges D, Hsu CW, Schendan HE 2016. Is anterior N2 enhancement a reliable electrophysiological index of concealed information? Neuroimage 143, 152-165.

Battaglini L, Casco C, Isaacs BR, Bridges D & Ganis G 2016. Electrophysiological correlates of motion extrapolation: An investigation on the CNV. Neuropsychologia. 95, 86-93.

Battaglini, L., Casco, C., Isaacs, B. R., Bridges, D., & Ganis, G. (2017). Electrophysiological correlates of motion extrapolation: An investigation on the CNV. Neuropsychologia, 95, 86-93.

Ganis, G., Bridges, D., Hsu, C. W., & Schendan, H. E. (2016). Is anterior N2 enhancement a reliable electrophysiological index of concealed information? Neuroimage, 143, 152-165.

Ganis, G., & Kutas, M. (2003). An electrophysiological study of scene effects on object identification. Brain Res Cogn Brain Res, 16(2), 123-144.

Ganis, G., Kutas, M., & Sereno, M. I. (1996). The search for "common sense": an electrophysiological study of the comprehension of words and pictures in reading. J Cogn Neurosci, 8(2), 89-106.

Ganis, G., & Schendan, H. E. (2008). Visual mental imagery and perception produce opposite adaptation effects on early brain potentials. Neuroimage, 42(4), 1714-1727.

Ganis, G., & Schendan, H. E. (2012). Concealed semantic and episodic autobiographical memory electrified. Front Hum Neurosci, 6, 354.

Ganis, G., Smith, D., & Schendan, H. E. (2012). The N170, not the P1, indexes the earliest time for categorical perception of faces, regardless of interstimulus variance. Neuroimage, 62(3), 1563-1574.

Schendan, H. E., & Ganis, G. (2012). Electrophysiological potentials reveal cortical mechanisms for mental imagery, mental simulation, and grounded (embodied) cognition. Front Psychol, 3, 329.

Schendan, H. E., & Ganis, G. (2013). Face-specificity is robust across diverse stimuli and individual people, even when interstimulus variance is zero. Psychophysiology, 50(3), 287-291.

Schendan, H. E., Ganis, G., & Kutas, M. (1998). Neurophysiological evidence for visual perceptual categorization of words and faces within 150 ms. Psychophysiology, 35(3), 240-251.

Zabelina, D. L., & Ganis, G. (2018). Creativity and cognitive control: Behavioral and ERP evidence that divergent thinking, but not real-life creative achievement, relates to better cognitive control. Neuropsychologia, 118(Pt A), 20-28.

Sambrook, T.D, Roser, M., Goslin, J. (2012). Prospect theory does not describe the feedback-related negativity value function. Psychophysiology, 49(12), 1533-44.

Marrett, N. E., de-Wit, L. H., Roser, M. E., Kentridge, R. W., Milner, A. D., & Lambert, A. J. (2011). Testing the dorsal stream attention hypothesis: Electrophysiological correlates and the effects of ventral stream damage. Visual Cognition, 19(9), 1089-1121. (THIS COMBINES fMRI, PATIENTS AND EEG).

Roser, M.E., Fugelsang, J., Handy, T.C., Dunbar, K.N., & Gazzaniga, M.S. (2009). Representations of physical plausibility revealed by event-related potentials. NeuroReport, 20,1081-1086.

Rhodes E. Gaetz W, Marsden J and Hall SD. (2018). Transient alpha and beta synchrony underlies preparatory recruitment of directional motor networks. Journal of Cognitive Neuroscience, 0(6):867-875. doi: 10.1162/jocn_a_01250.

Gaetz W, Rhodes E, Bloy L, Blaskey L, Jackel CR, Brodkin ES, Waldman A, Embick D, Hall S, Roberts TP. (2019). Evaluating motor cortical oscillations and age-related change in autism spectrum disorder. Neuroimage. 11:116349. doi: 10.1016/j.neuroimage.2019.116349.

Prokic E., Woodhall, GL, Williams AC, Stanford IM, Hall SD. (2019). Bradykinesia is driven by cumulative beta power during continuous movement and alleviated by GABAergic modulation in Parkinson’s disease. Frontiers in Neurology 10: 1298. https://doi.org/10.3389/fneur.2019.01298.

Hall SD, Prokic EJ, McAllister CJ, Ronnqvist KC, Williams AC, Witton C, Woodhall GL, Stanford IM.(2014). GABA-mediated changes in inter-hemispheric beta frequency activity in early-stage Parkinson’s disease. Neuroscience 281 :68-76.

Rossiter HE, Worthen SF, Hall SD & Furlong PL. (2013). Gamma Oscillatory Amplitude EncodesStimulus Intensity in Primary Somatosensory Cortex. Frontiers in Human Neuroscience. 15;7:362

Ronnqvist KC, McAllister CJ, Woodhall GL, Stanford & Hall SD. (2013). A multimodal perspectiveon the composition of cortical oscillations. Frontiers in Human Neuroscience. 7, 132.

Mcallister CJ, Ronnqvist KC, Woodhall GL, Stanford IM, Furlong PL & Hall SD. (2013). OscillatoryBeta Activity Mediates Neuroplastic Effects of Motor Cortex Stimulation in Humans. Journal of Neuroscience 33(18):7919-7927

Hall SD, Stanford IM, Yamawaki N, McAllister CJ, Rönnqvist KC, Woodhall GL & Furlong PL.(2011) The role of GABAergic modulation in motor function related neuronal network activity. NeuroImage. 56(3):1506-10.

Worthen SF, Furlong PL, Hall SD, Aziz Q & Hobson AR. (2011) Primary and secondary somatosensory cortex responses to anticipation and pain: a magnetoencephalography study. European Journal of Neuroscience. 33(5): 946-59

Hall SD, Yamawaki N, Fisher AE, Clauss RP, Woodhall GL & Stanford IM. (2010). Desynchronisation of pathological low-frequency brain activity by the hypnotic drug zolpidem. Clinical Neurophysiology. 121(4): 549-55.

Hall SD, Barnes GR, Furlong PL, Seri S & Hillebrand A. (2010) Neuronal network pharmacodynamics of GABAergic modulation in the human cortex determined using pharmaco-MEG. Human Brain Mapping. 31(4): 581-94.

Sambrook, T.D., Wills, A.J., Hardwick, B., & Goslin, J. (2018). Model-free and model-based reward prediction errors in EEG. NeuroImage, 178, 162-171.

Wills, A.J., Lavric, A., Hemmings, Y., & Surrey, E. (2014). Attention, predictive learning, and the inverse base-rate effect: Evidence from event-related potentials. NeuroImage, 87, 61-71.

Wills, A.J., Lavric, A., Croft, G., & Hodgson, T.L. (2007). Predictive learning, prediction errors and attention: Evidence from event-related potentials and eye tracking. Journal of Cognitive Neuroscience, 19, 843-854.

 
 
 

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