Monthly Archives: March 2019

How to change brainwaves and emotions in your UX research design lab using sensory systems

In lines with my previous blog post regarding emotional research and design, at times you may want to control the lab setting to elicit certain brainwaves and emotions within the participants prior to lab testing. There are many reasons as to why you would want to do this, as you may already know. In the field of Psychology, Neuroscience, etc there are plenty of experimental research design that bess for manipulating emotions before and/or after task tests.

Anyone interested, there are many easy ways to do this. I highly recommend reading about Lang’s IAPS techniques, to start.

Needless to say that consent forms and research ethics regulations ought to be honored prior to running such experimental designs.

This video covers an eagle-eye view and some tips on the topic.



The new era of neuro-oriented HCI research

Human computer interaction (HCI) research has evolved significantly over the past few decades. HCI research has evolved from simple system-oriented approaches, to user-oriented research, to cognitive-oriented approaches.

Most recently, the role of emotions (emotion-oriented studies) in HCI has gained momentum (Julien, McKechnie, & Hart, 2005; Picard, 1997; Nahl & Bilal, 2007).

The expressions affective computing and emotional design were born to address the role of emotions in system designs to create systems that were more user-friendly (Picard, 2003). Today, systems are being developed that respond to emotions to help create a more effective and delightful human-computer interaction.

As Nahl and Bilal (2007) stated: “By making this adaptation process [the way in which users adapt to the information environment] explicit, the [social-biological information technology] model reveals how the ubiquitous information environment can be viewed as an affective information environment because all information needs, seeking, reception, and use is processed through emotions (p. 4).”

In my dissertation, I went further to claim that our industry is ready to establish itself in neuro-oriented research approach as well. This is a new era that I feel quite excited about. I call this the new era of neuro-oriented HCI research.

As mentioned earlier, research approaches have drastically changed and evolved in the field of HCI, evolving from the system-oriented approach to user-, cognitive-, and emotion-oriented approaches.

In my mind, the neuro-oriented approach involves research that studies the neural activities of the brain within the discipline of HCI. To provide a richer account, studying the brain and the neural reactions and activities ought to also be part of the research approach in the field of information systems.

Moreover, recently neuro-oriented research methods have found their way into studies in the field of Information Science (Gwizdka et al., 2013). In 2010, Neuro Information Systems (NeuroIS), a subfield of Neuro Information Systems, was started by a few researchers in the field of information systems (Dimoka et al., 2010). NeuroIS focuses on understanding the impact and the use of information technologies (Riedl et al., 2010).

There is a trend in evolving research methods towards richer approaches that include human brain activities. The overarching motivation to the neuro-oriented approach is the need of researchers to understand brain functions in HCI topics, and not only within the fields of neuroscience, for example. This approach will potentially help create better and more evolved information science models, theories, and improved HCI design systems.

I highly encourage the tech industry (or any other non-neurosicence disciplines) to help further open up to the neuro-oriented approach, to help design and build systems based on richer HCI data.



Striving to build AI/Robotics machines with higher level of reasoning? Kiss the traditional neuroscience goodbye!

Years ago I gave several talks on this topic but had to take a break in order to focus on the (traditional) Phd thesis. Now that it is all done, I am happy to resume work on my stance in ‘the integration of the traditional neuroscience and the non-traditional brain theories’… for reasons that I will try to articulate here.

For thousands of years, the theory of quantum consciousness has been discussed, explained, and explored by ancient spiritual traditions. Two of my all-time favorite modern scientists Karl Pribram and David Bohm positioned this theory further such that it would be understood and recognized by the (western) world. Regardless of the origin of the theory, it is utterly important to focus on the message that it strives to articulate.

While our traditional neuroscience does every effort in (what I call) bucketize the brain into bits and pieces (e.g. hippocampus does this and that), the quantum theory observes the brain as a holistic state of being, with consciousness, communicating through frequencies of quantum particles and energy.

If we believe that everything is made up of particles, along with frequencies floating in space that we interpret into things, then our traditional way of defining the brain falls apart. Quite frankly, I am not even sure how sure we are of the way in which we are trying to explain brain’s structures and functions.

For example, some of my oldest questions, have never been explained by the traditional neuroscientists: “What is information at the neurological, physical, tangible form? Where in the brain is information? What does information look like within the neurons?”

To my knowledge, and since I have asked these of many experts, no one seems to have a solid answer. Yet, everything that we do, see, chew, touch, hear, etc. can be categorized as information. In other words, the very thing that we are all made up of, we have no clear knowledge about.

I have strongly come to see that the value that the non-traditional neuroscience theories, such as the quantum brain theory, brings in helping us answer our unanswered questions is enormous.

In short, I have come to realize that there is no ‘this or that’. It is both!

While there are opponents and proponents to both disciplines, I claim that we need both. On one hand, we need the mechanical way of the traditional neuroscience of bucketizing the brain. On the other hand, we need the holistic quantum way of the modern (non-traditional) neuroscience of the quantum mind theories.

This way of approaching neuroscience, in turn, will come in handy with the strives that companies such as Deep Mind are creating in the fields of, not only AI, but also in robotics, neural networks, etc.

My own work, moving forward, now that I am free to branch out to the non-traditional disciplines, will consist of such integration. We need both. Instead of fighting over who is right, who said what first, etc. my focus will be on integrating, expanding, and creating based on holistic approach because frankly we need all the help we can get to figure this thing out!

Emotional research & design

I started the ground work around neuroscience, emotions, and user experience back in 2005 at Stanford University. “Emotional design” and “pleasurable engineering” are factors that we need to take into account when developing/studying products. Below is a short excerpt from my dissertation:

“Research communities have detected how human emotions played a significant role in human-computer-interaction. Expressions such as pleasurable engineering or emotional design became driving factors in system design, and these factors were extended to information retrieval system design (Nahl & Bilal, 2007).

This trend indicates the important role of emotions in human-computer-interaction, highlighting the importance of including the affective dimension when designing information retrieval systems. However, our understanding of how emotions influence search processes, as revealed in search performance (search effectiveness and search efficiency) is limited (Nahl & Bilal, 2007).

As a result, the emotion-oriented approach has become more prominent, with researchers realizing the potential effects of user affective dimensions on information retrieval processes (Sarraf, 2015).”