What do you work on?

I am inter­est­ed in how the world outside of acad­e­mia uses Psy­chol­o­gy and Neu­ro­science to address real-world prob­lems. This broadly falls under the cat­e­go­ry of “neu­ro­mar­ket­ing” or “edu­ca­tion­al neu­ro­science”, although I’m not in love with either of those terms. In a nut­shell, I am inter­est­ed in using the methods, tech­niques and insights from acad­e­mia to address real-world prob­lems in robust, sci­en­tif­i­cal­ly rig­or­ous and novel ways.

What did you do using Gorilla?

We ran an experiment in part­ner­ship with Audible, that inves­ti­gat­ed whether people respond dif­fer­ent­ly to emo­tion­al­ly engag­ing scenes when they are deliv­ered in video or audio­book format. 102 vol­un­teers (aged 18 – 55) watched clips and lis­tened to audio­book scenes from eight block­busters and best­sellers: Game of Thrones, Girl On The Train, Pride & Prej­u­dice, Silence of the Lambs, Great Expec­ta­tions, The Da Vinci Code, Hound of the Baskervilles, and Alien. Spe­cif­ic scenes from each title were select­ed based on their emo­tion­al inten­si­ty, com­par­a­tive length, and sim­i­lar­i­ty of nar­ra­tive (i.e. minimal dif­fer­ences in the sto­ry­line between audio and video adap­ta­tions). The stories were pre­sent­ed using Gorilla and after each one, par­tic­i­pants were asked about their engage­ment with the story. At the same time, we record­ed implic­it phys­i­o­log­i­cal mea­sure­ments such as heart rate and elec­tro­der­mal activ­i­ty using bio­met­ric sensors on the par­tic­i­pants because these phys­i­o­log­i­cal signals can reveal cog­ni­tive pro­cess­ing and sub-con­scious emo­tion­al arousal in the brain.

“An analy­sis of par­tic­i­pants’ bio­log­i­cal data revealed that lis­ten­ing to audio­books elicit­ed a more intense phys­i­o­log­i­cal and emo­tion­al reac­tion than watch­ing a screen.”

What was your study protocol?

Par­tic­i­pants received infor­ma­tion about the experiment and then pro­vid­ed informed consent. They then answered a few ques­tions about their current mood, media expe­ri­ence, per­son­al­i­ty, etc before watching/listening to short excerpts from 8 popular books. These were either pre­sent­ed as videos (4) or audio­book (4) and par­tic­i­pants then answered some ques­tions about their expe­ri­ence and engage­ment with each story. At the same time, par­tic­i­pants were wearing bio­met­ric sensors record­ing heart rate, gal­van­ic skin response, body tem­per­a­ture, and accel­er­a­tion (ie arm move­ment) data so that we had a com­bi­na­tion of explic­it, self-report mea­sure­ments (from Gorilla) and implic­it, phys­i­o­log­i­cal mea­sure­ments (from the bio­met­ric sensors). This allowed us to compare the two and inves­ti­gate the extent to which they pro­vid­ed com­ple­men­tary infor­ma­tion about engag­ing with the stories.

What did you find?

We found that par­tic­i­pants explic­it­ly rated the videos as more engag­ing than the audio­books but an analy­sis of par­tic­i­pants’ bio­log­i­cal data revealed that lis­ten­ing to audio­books elicit­ed a more intense phys­i­o­log­i­cal and emo­tion­al reac­tion than watch­ing a screen. For instance, our vol­un­teers had higher heart rates by an average of 2 beats per minute; their elec­tro­der­mal activ­i­ty (a measure of auto­nom­ic nervous system response due to emo­tion­al inten­si­ty) was higher and their body tem­per­a­ture was even 0.37C degrees warmer when lis­ten­ing to the audio­book clips rel­a­tive to watch­ing the videos. This is despite the fact that for both types of clips, par­tic­i­pants were sitting in a quiet, dark­ened room. They even had higher highs and lower lows in their heart rates when lis­ten­ing versus watch­ing, sug­gest­ing stronger emo­tion­al ampli­fi­ca­tion. There is an example of these find­ings based on the scene in Game of Thrones where Ned Stark scene is behead­ed avail­able below, and on YouTube here.

We inter­pret our results as evi­dence that lis­ten­ing to audio­books is a more emo­tion­al­ly engag­ing way of enjoy­ing a story than watch­ing that same story as a video. We hypoth­e­size this is a result of the more active imag­i­na­tion process­es that a lis­ten­er pro­duces rel­a­tive to the more passive viewing of a video. In other words, when lis­ten­ing, you active­ly sim­u­late the story in your mind, a process that is more demand­ing than pas­sive­ly taking in the vision of the direc­tor of a video. As a result, there are stronger phys­i­o­log­i­cal signals of this engagement.

Has this study been published?

The paper is cur­rent­ly under con­sid­er­a­tion at PLOSone but a pre-print is avail­able on bioRxiv here for anyone inter­est­ed in the full details.

What is the biggest advan­tage of online research methods?

Better sam­pling of the pop­u­la­tion. You not only get a wider demo­graph­ic spread but also get to test much larger numbers.

“The fact that the data are auto­mat­i­cal­ly coded with uni­ver­sal time stamps is helpful in linking the explic­it behav­iour­al data from Gorilla with the implic­it phys­i­o­log­i­cal data from the bio­met­ric sensors.”

How do you think online research is going to change your field?

I think it facil­i­tates col­lect­ing behav­iour­al data on a wider scale but I’m not sure that is chang­ing our field so much as evolv­ing it. To my mind, behav­iour­al data are par­tic­u­lar­ly useful when com­bined with other types of data (phys­i­o­log­i­cal, neural) – at least in answer­ing the ques­tions I am most inter­est­ed in. In this sense, the current form of Gorilla is prob­a­bly a step­ping stone towards a more inte­grat­ed data col­lec­tion scheme in the future. Goril­la’s new eye- and mouse-track­ing fea­tures are a good start!

For you, what is the stand-out feature in Gorilla?

Ability to do web-based data col­lec­tion. It also has nice teach­ing fea­tures for our under­grad­u­ates, not all of whom learn to code as well as one might hope.

Why did you choose Gorilla?

Col­leagues of mine were using it for web-based exper­i­ments as well as within the lab. For behav­iour­al exper­i­ments, it is really easy-to-use, con­ve­nient and scalable.

How did Gorilla make your life or research better, easier or faster?

For this par­tic­u­lar experiment, the fact that the data are auto­mat­i­cal­ly coded with uni­ver­sal time stamps is helpful in linking the explic­it behav­iour­al data from Gorilla with the implic­it phys­i­o­log­i­cal data from the bio­met­ric sensors (that also use UTC stamps).

What improve­ments would you like to see in Gorilla to make your research easier?

Under Task Struc­ture, I find the display editor some­what clunky to use. It would be helpful if it were much larger and allowed the ability to preview layouts, fonts, etc without having to commit a new version each time.

Response from Gorilla:

Hi Joseph,

We agree that a larger size would be helpful. We’re working on a new user inter­face for that screen and several others. It will hope­ful­ly come out later this year.

In Gorilla you can preview content without having to commit a new version every time. When you preview you’ll always see the latest set­tings, even if it hasn’t been committed.

What chal­lenges are you facing in your area of behav­iour­al science?

For me, I often want to combine large web-based samples with smaller datasets where I can collect addi­tion­al phys­i­o­log­i­cal data. At the moment, there is no way to do both of these simul­ta­ne­ous­ly. Things things like Fitbits, Apple and Samsung watches offer the poten­tial for col­lect­ing bio­met­ric data in the future. Col­lec­tion of eye­track­ing data using laptop webcams looks to be pos­si­ble now in Gorilla.

What real-world problem do you see that your research could impact?

How to choose?! My work is direct­ly related to under­stand­ing how audi­ences engage and there­fore is rel­e­vant to content providers (movies, TV, online), live per­for­mance (music, theatre, dance, comedy), mar­ket­ing and com­mu­ni­ca­tions (cor­po­rate, health, charity, polit­i­cal), edu­ca­tion, and prob­a­bly even law if you con­sid­er court­room “per­for­mances” and jurors as “audi­ence.” Real-world prob­lems are the focus of my current research program.

What do you believe to be true that you cannot prove (yet)?

I believe that human lan­guage ability is a direct result of small changes in brain wiring between us and our primate cousins, pre­sum­ably down to minor genetic changes affect­ing the action of axon growth cones.

What are the main ways people mis­un­der­stand your thesis?

Changes to brain wiring are more trans­for­ma­tive than simply linking two dif­fer­ent regions togeth­er – they fun­da­men­tal­ly alter the nature of the infor­ma­tion pro­cess­ing but this dis­tinc­tion is often missed.

What do you not believe, that the major­i­ty in your field do believe?

I think the impor­tance of lat­er­al­i­ty in the brain is vastly over stated.

What is the most excit­ing piece of research you’ve ever done?

My friend and col­league, Daniel Richard­son and I, did a fab­u­lous little experiment where we put to the test the idea that people can tell food cooked on a char­coal BBQ from food cooked on a gas BBQ. As an avid BBQer devoted to my char­coal Weber grill, I knew char­coal was better but I got a chance to prove this when we were invited by the Times news­pa­per to run London’s first BBQ experiment (July 2013). To my horror, neither myself nor the people we tested could reli­ably tell food cooked on a char­coal grill from the same food cooked on a gas grill in blind taste tests. It was, and remains, my favourite example of cog­ni­tive bias over­rid­ing ratio­nal deci­sion making – even though I con­duct­ed the experiment and eval­u­at­ed the evi­dence, I still don’t believe (at an emo­tion­al level) my own results and con­tin­ue to swear by char­coal grill. Intel­lec­tu­al­ly, I know I’m wrong as I col­lect­ed the evi­dence to prove it! Prob­a­bly the most fun experiment I’ve ever run.

What advice would you give to someone start­ing out in behav­iour­al science/research?

Work hard and do what you love. Make an effort to make every­thing you do as acces­si­ble as pos­si­ble to a wide audience.

If you could inter­view any researcher (alive or dead), who would it be and why?

Alan Turing, the father of com­put­ing. Turing saw so much further that anyone around him and his vision trans­formed our society. But even in the 1920s/30s he foresaw some of the impli­ca­tions of his work, describ­ing soft­ware engi­neers and AI as con­se­quences of his theory of com­putable numbers (which was very the­o­ret­i­cal). I’d love to under­stand more of how he thought.

Who or what orig­i­nal­ly inspired you to work in your field of research?

There is an AI called Mike in Heinlein’s The Moon is a Harsh Mis­tress that inspired me to do my PhD in AI. Sadly, the reality of AI didn’t meet the excite­ment that was Mike, and I tran­si­tioned from arti­fi­cial intel­li­gence into natural intel­li­gence. I studied the neu­ro­bi­ol­o­gy of lan­guage for about 20 years before becom­ing inter­est­ed in how psy­chol­o­gy and neu­ro­science are used by the wider com­mu­ni­ty (e.g. busi­ness, edu­ca­tion, gov­ern­ment, etc) which is how I ended up working in con­sumer neuroscience.

On a per­son­al level, what are you most proud of?

My family. I have an amazing wife and two fab­u­lous daugh­ters, who are each a force of nature. I try to keep up!

When you’re not working, what do you enjoy doing?

BBQing, reading, fight­ing (martial arts).

What science book have you read recent­ly that you’d rec­om­mend to others?

I love David Hand’s Improb­a­bil­i­ty Prin­ci­ple. David explains why unbe­liev­ably improb­a­ble events (like winning the lottery twice or getting hit by light­ning mul­ti­ple times) happen all the time. The strands of his argu­ment (selec­tion bias, law of large numbers, prob­a­bil­i­ty levers, etc) are things we rou­tine­ly deal with as data sci­en­tists but often over­look their impor­tance. Although it is not the focus of the book, this was the best expla­na­tion of the repli­ca­tion crisis in psy­chol­o­gy that I’ve read and it forced me to think care­ful­ly about so many aspects of my data han­dling life that I was taking for granted. Very acces­si­ble and easy to read and very pow­er­ful too.

What’s your favourite STEM joke?

There are 10 types of people in this world: those who know binary and those who don’t.