In cognitive neuroscience, we’re interested in what guides human attention. We distinguish between influences from high-level cognition (e.g. current goals), and low-level visual features. There are highly sophisticated models of how visual features such as intensity, colour, and movement guide human attention. Computerised implementations of these models allow computers to mimic human eye movements. Turns out Taylor Swift’s amazing videos are an excellent example!
Gazepoint is a relatively small player on the eye-tracking market. They sell two devices: the 60 Hz GP3 at a price of $695, and the 150 Hz GP3 HD at $1995 (both of those prices exclude VAT and shipping). Because of its relatively low price, the basic GP3 is an appealing model for researchers on a budget. As of today, PyGaze supports Gazepoint’s trackers through their OpenGaze API. Download the new code from GitHub, and have fun!
Although it sounds like a lot of effort, creating a Twitter bot is actually really easy! This tutorial, along with some simple tools, can help you create Twitter bots that respond when they see certain phrases, or that periodically post a tweet. These bots work with Markov chains, which can generate text that looks superficially good, but is actually quite nonsensical. You can make the bots read your favourite texts, and they will produce new random text in the same style!
Introducing MPy150: an easy-to-use Python library for using a BIOPAC MP150. Sample code included!
The EyeTribe tracker is really cheap, and you can now use it in Python and in Matlab. It’s not as bad as you would expect from its price, and you could probably use it in fixation or pupillometry studies. For in-depth info, read this validation study.
PyGaze Analyser is a new (basic) tool to create gaze data visualisations such as heatmaps. The code is open source and free to use. Read the post for example images and the download link!