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Jörn Alexander Quent Posts

2018/06/17: Checking slopes of each participant

I am currently writing up my first year report. The data set at this point includes 23 participants (aim n = 24) and I am really happy to report that I found a significant quadratic relationship between object/location expectancy and memory performance. Now, the question is whether the quadratic effect is consistent across participants or whether some participants even show the reverse effect. Fortunately, the effect seems to be very consistent. All participants show a positive quadratic effect. Besides that Bradley Love gave a talk about memory compression and the role of the mPFC in it at the Chaucher Club…

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2018/06/08: Psychology and Brain 2018 in Gießen and new ideas

Psychology and Brain Last weekend, I went to Psychology and Brain conference, which was really interesting and an inspiration for a couple of new projects. First of all, I was really pleased that there was a symposium on VR in biological psychology. On that symposium, Johannes Fuß among others presented work attempting to bridge the gap between animal and human research, which inspired me to think about a human version of the task used in Tse et al. (2007) using immersive VR. During the conference, I also saw the need to organise a community and foster exchange among cognitive neuroscientist…

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2018/05/29: Reflections on failures and open notebook

My last post was more than twenty days ago. The reason for that was that I was just very busy and had to prioritise instance the pre-registration of the second experiment (schemaVR2, see here), which included a power analysis. In addition to starting the data collection for schemaVR2, I also worked on a syllabus for a summer teaching job and a poster for Pyschologie und Gehirn (Psychology and Brain), which is on the automaticity of word recognition (see here). Long story short, I did not have enough time. In this entry, I want to reflect firstly on my experiences while…

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2018/05/02: End of schemaVR1 and start of schemaVR2

Today, I finished the data collection for schemaVR1. I collected 17 instead of 16 participants because I wanted to show the experiment to someone who then agreed to formally take part in this experiment. The two major the results of this experiment are that the locations of objects that are generally unexpected in a kitchen are remembered better (measured by 3D location recall and 3AFC location recognition) than the locations of objects that are expected in a kitchen. This can already be seen in the interim analysis (N = 9) that I uploaded here. The second result, which was only…

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2018/04/12: Interim results and future plans

I am currently caught up with collecting data for my first experiment, which I will henceforth call schemaVR1, working on my first year report and analysing the interim results. I have collected data from eight participant so far and already got number of significant results. This is quite impressive considering that I also have only twenty stimuli/trials. I will upload the pre-processing script alongside a script analysing the interim results in the next days in a separate GitHub repository, where I will provide more details, but a very robust, and already significant, finding is that the locations of unexpected objects…

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2018/03/22: General update and plan for the future

Even though the last post is basically a month ago, I am still committed to this diary. Therefore I thought to provide an update. I spent the last month with finishing the experiment and preparing its pre-registration. In that progress, I have started working on the R script that analyses the data to include it in the pre-registration. I want to use mixed linear models to analyse the data so that I can model the performance on individual trials. To really understand these models, I simulated data, which can be found here. This worked quite well though I still need…

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2018/02/19: 3D location recall task in VR

As noted in the previous post, I want to create a 3D location recall task. I want that people are able to pick up objects from the floor and place them at the locations at which they think the objects were during encoding. I found a good YouTube tutorial (see here) and adapted the respective script (see here), which needs to be added to the wand controllers to work. My version of the script will be uploaded later when it finished. The basic approach is to make the target object a child of the wand controller and to make it…

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