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Event

Psychology: monthly research talk series

When

Wednesday 18 January 2023

1.00pm - 2.15pm

Cost

Free

Where

B001, Business School

Organiser

Psychology

We run a monthly research talk series, to share news about the most up-to-date and exciting research taking place in psychology. These talks are open to all and we welcome all staff, students and visitors to join us.

Unless otherwise stated, talks take place from 12-1pm in B001, which is the lecture theatre on the ground floor of the Business building. All talks last for approximately 45 minutes, followed by 15 minutes for questions, and then informal refreshments and socialising with the speaker.  

If you are new to visiting Edge Hill University, you can find travel information on how to find us here. Please also find our campus map. The Business School is denoted as building 16 on here. This building is fully-accessible, and includes a lift to all floors and accessible toilets.

January 2023

Speakers

Dr Christian Keitel

University of Stirling & University of Dundee

Abstract

Changes in brain state over time impact our perception and may influence performance. I will present some findings that show that cortical state influences perception beyond the stimulus detected-vs-not-detected dichotomy, and characterise the fluctuations themselves more closely in the process. I will also tell you why we may want to consider them more rigorously in our data analysis using the example of pre-stimulus alpha oscillations. Drawing on another set of recent results, I will review arousal-linked neuromodulation as one likely source of cortical state fluctuations. Against a previously held notion of arousal as a global influence on cortical state, our analysis of simultaneous pupil and MEG recordings show diverse neuromodulatory influences that differ depending on the targeted cortical region, can express in brain oscillations of different frequency bands or as broadband effects, and vary in their timing. Taken together, these results give a better understanding of how, when and where brain state changes manifest, what their perceptual consequences are and where some of them may originate.

Dr Victoria Nicholls   

MRC-CBU Cambridge

Headshot of Dr Victoria Nicolls, MRC-CBU Cambridge

Abstract

Our ability to recognise objects is impacted by the environment we find these objects in. This occurs through initial coding of global scene context, enabling the generation of predictions about potential objects in the environment. When correct, these predictions facilitate object recognition, but when these predictions are violated object recognition is impeded.

While these studies establish that visual contexts impact the processing of objects, they have done so using carefully controlled paradigms and situations, which involved removing the participant from ‘the wild’, instead presenting participants with visual depictions of the world. However, there are differences in how fundamental neural processes function in natural compared to controlled situations. For example, the selectivity of orientation cells in V1 and place cells in the hippocampus change between controlled and naturalistic environments. This raises a critical question of to what extent do research findings translate into real-world environments? To determine how objects are recognised in a real-world context, it is crucial to move our experiments into the real-world. In this research, we asked how the visual context influenced object recognition in real-world settings through a combination of mobile electroencephalography (mEEG) and augmented reality (AR). During the experiment, participants approached AR objects placed either in an indoor or an outdoor environment while mEEG was recorded.  We analysed the ERP data (aligned to the appearance of the objects) with bootstrap t-tests and hierarchical generalised linear mixed models. Similarly to laboratory experiments, we found scene-object congruency effects in the N300 time window over posterior electrodes. Overall our findings suggest that visual contexts constrain our predictions of likely objects even in real-world environments, helping to bridge between research in laboratory and real life situations.

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