Popular in Psychology

Most Cited

The adapted mind

Dalhousie University Jerome Barkow

Psychology

Consumers’ pursuit of material and experiential purchases

Cornell University Tom Gilovich

Experimental Psychology

Time to investigate human visual shape perception

University of Montreal Martin Arguin

Most Cited

James S. Jackson and the program for research on Black Americans

Harvard University David R. Williams

Psychology

Violence and Mental Illness: Rethinking Risk Factors and Enhancing Public Safety

Duke University Eric Elbogen

Cognitive Psychology

Cognitive remediation – where are we now and what should we do next?

King's College London Til Wykes

Cognitive Psychology

Harnessing Plasticity in the Atypical Developing Brain using Neurostimulation

University of Surrey Roi Cohen Kadosh

Relationship between autonomic arousal and attention orienting

View more insights in Social Sciences - Psychology - Developmental Psychology

View more figures from University of Southampton

View the page of Alessio Bellato

Read the Study

Next in Developmental Psychology

Lives and legacies of people with intellectual disability

Kenneth Keith | University of San Diego

Risk for Developmental Delay Among Infants Born During the COVID-19 Pandemic

Gerald F Giesbrecht | University of Calgary

Attention-Deficit/Hyperactivity Disorder (ADHD) and Autism Spectrum Disorder (ASD) may be characterized by different profiles of visual attention orienting. Alessio Bellato discusses the possible effect of dysregulated autonomic arousal on oculomotor mechanisms in autism and ADHD

Image courtesy of interviewee. May 28, 2024

Log-in or Sign-up to Faculti
Currently viewing this subject insight as a guest. You have insight(s) remaining for this month. Login to view 8000+ figures on the platform.

Generating Workspace...

Export as PDF

This video is a transcript of a presentation discussing a research study that is part of the speaker's PhD thesis at the University of Nottingham. This video research focuses on attention and arousal regulation in children diagnosed with ADHD (Attention-Deficit/Hyperactivity Disorder) and autism, specifically exploring the overlap and co-occurrence of these two conditions.

The study, conducted from 2017 to 2020, involved examining visual attention and the ability to shift attention between stimuli using eye-tracking technology. The research included participants aged 7 to 15, some with ADHD only, autism only, a combination of both (double diagnosis), and neurotypical children as a comparison group.

Key findings include:
- No significant differences in eye movement parameters and pupil size across different groups, suggesting similar underlying mechanisms for attention regulation despite behavioral differences.
- The study found consistent patterns in how children oriented their attention, especially showing faster responses to social stimuli (like faces) and when stimuli were presented in dynamic or multimodal formats (involving sound).
- The researchers speculate that the lack of expected differences may be related to the age of participants, suggesting future studies should investigate younger children to better understand developmental changes in ocular motor abilities.
- The speaker emphasizes the importance of engaging tasks that can hold children’s attention better during testing and the potential of conducting research in real-world settings to gain further insights into attentional mechanisms in children with these conditions.

Finally, the speaker expresses gratitude to sponsors, clinicians, and families involved in the study, highlighting the collaborative effort required for such research.

Language:

Export as PDF

X-TIMESTAMP-MAP:LOCAL=00:00:00.000,MPEGTS=900000

00:00.115 --> 00:04.165
This paper is basically my final paper of the PhD.

00:04.565 --> 00:06.725
I did my PhD at the University of Nottingham.

00:06.985 --> 00:09.565
So the study, that we reported

00:09.665 --> 00:12.005
and ascribed in this paper is actually part

00:12.005 --> 00:14.805
of a larger study that is called the Sun Study,

00:15.255 --> 00:17.205
where we basically studied attention

00:17.585 --> 00:21.405
and arousal regulation in children with A DHD and autism.

00:21.665 --> 00:24.845
So this study was conducted in between 2017

00:24.905 --> 00:27.645
and 2020 at the University of Nottingham uk.

00:28.385 --> 00:31.765
And we were specifically interested in the co recurrence

00:31.765 --> 00:33.845
between A DHD and autism.

00:34.025 --> 00:36.445
Now, I'm not sure how much familiar you are with this,

00:36.545 --> 00:40.325
but these are two very common neuro mental conditions.

00:40.915 --> 00:43.245
They're slightly different in the sense

00:43.245 --> 00:45.605
that attention deficit hyperactivity disorder

00:45.705 --> 00:49.245
or A DHD is usually characterized by inattention,

00:49.845 --> 00:53.725
difficulties in concentrating and kind of hyperactive

00:53.725 --> 00:55.205
and impulsive behaviors.

00:55.615 --> 01:00.005
While autism is mainly characterized by kind of,

01:00.375 --> 01:03.565
adorations in social functioning, some challenges,

01:03.565 --> 01:05.245
especially at the sensory level.

01:05.985 --> 01:08.765
Um, but both they, they kind of appear,

01:08.785 --> 01:10.925
and they are actually diagnosed by clinicians

01:11.685 --> 01:14.525
starting from three, four years of age.

01:14.625 --> 01:16.405
Autism, autism slightly earlier as well.

01:16.425 --> 01:19.285
But A DHD is usually between, between four years of age.

01:19.945 --> 01:22.485
Um, so our interest actually was specifically

01:23.625 --> 01:26.725
on those children and young people who showed

01:27.395 --> 01:28.845
both, conditions.

01:28.845 --> 01:30.725
So basically symptoms of both conditions.

01:31.425 --> 01:34.645
And this is, it looks actually rare,

01:34.825 --> 01:36.965
but when you look at the statistics

01:36.965 --> 01:39.605
and when you talk to clinicians, mostly with children

01:39.745 --> 01:42.885
and their families, they actually say, yes,

01:42.885 --> 01:47.445
maybe I have a diagnosis of of A DHD, but I actually feel

01:47.545 --> 01:50.125
or experience some of the characteristics of autism

01:50.385 --> 01:54.805
or s And in this specific study, again, as I said,

01:54.805 --> 01:56.205
this was part of a larger study,

01:56.345 --> 02:00.245
but in this specific study, we were interested on, kind

02:00.245 --> 02:02.725
of visual attention of enting really,

02:02.725 --> 02:05.805
because we have, done previous work that showed that,

02:06.025 --> 02:08.405
people with A DHD and with all this,

02:08.405 --> 02:10.605
and they, they experienced some difficulties with vision.

02:11.065 --> 02:13.525
And there is a lot of research, especially on kind

02:13.525 --> 02:16.205
of infants and especially in relation to all this

02:16.795 --> 02:19.405
that showed that, there may be some kind

02:19.405 --> 02:22.485
of difficulties in actually a very specific mechanism,

02:22.485 --> 02:23.885
which is attention ing.

02:23.905 --> 02:26.685
You know, think about right now you're watching at me,

02:26.945 --> 02:28.925
you're watching, you know, looking at me speaking,

02:29.025 --> 02:31.165
but maybe you'll see something on your

02:31.165 --> 02:32.365
right or on your left.

02:32.705 --> 02:34.725
And if you're really paying attention, maybe

02:34.725 --> 02:36.285
that thing you know, will not distract you.

02:36.745 --> 02:39.445
But if your attention is captured, you, you know, you,

02:39.905 --> 02:41.165
you rotate your head and,

02:41.165 --> 02:42.405
and watch towards the source

02:42.785 --> 02:44.325
of the destruction to see what's happening.

02:44.325 --> 02:48.045
Right? And there are specific mechanism, this mechanism

02:48.105 --> 02:50.805
of moving attention, from one stimulus

02:50.985 --> 02:52.325
to another is very crucial,

02:52.375 --> 02:54.685
especially very early in development.

02:55.105 --> 02:57.205
And we know that a lot of the characteristics

02:57.225 --> 02:58.765
of OTI and A DHD

02:58.825 --> 03:01.325
Are already present early in development.

03:01.785 --> 03:04.485
So again, based on, on there is a lot of literature

03:04.485 --> 03:06.765
that maybe we can talk about later if you're interested.

03:06.945 --> 03:10.205
But, that proposed, kind

03:10.205 --> 03:13.205
of these difficulties in attention orienting

03:13.205 --> 03:17.925
and switching to somehow explain, you know, some

03:17.925 --> 03:20.565
of the characteristics of TI and A DHD.

03:21.065 --> 03:24.485
But when we took a look at the overlap, so the,

03:24.505 --> 03:27.445
the basically children, so the literature on children with,

03:27.445 --> 03:30.765
with bold conditions, we didn't find much literature.

03:30.825 --> 03:32.125
So basically there weren't studies

03:32.155 --> 03:36.645
that looked specifically at visual attention ing in,

03:37.425 --> 03:40.325
you know, in these two, conditions,

03:40.555 --> 03:44.045
when they were overlapping the same, same child

03:44.105 --> 03:47.285
or the same young person, basically, few works

03:47.285 --> 03:49.205
that actually we cited in the paper as well.

03:49.585 --> 03:51.565
So first of all, actually, you know, there is support

03:51.585 --> 03:54.045
to this rational of looking at the comorbidity,

03:54.065 --> 03:56.165
the co recurrence between a DD and all this.

03:56.165 --> 03:58.805
There are a lot of very big studies conducted like,

03:58.905 --> 04:00.725
you know, internationally,

04:00.945 --> 04:02.765
and one of them is the enigma study

04:02.875 --> 04:04.925
that we actually cited in some of the papers.

04:05.705 --> 04:06.965
Um, so some of the papers

04:06.995 --> 04:08.325
that we cited actually in the paper

04:08.385 --> 04:09.565
are from the Enigma study.

04:09.565 --> 04:13.685
This is a consortium of basically different institutions

04:13.685 --> 04:15.245
and universities around Europe

04:15.635 --> 04:18.485
that looked at the genetic factors associated

04:18.555 --> 04:21.445
with different conditions, including A DHD and all.

04:22.425 --> 04:25.285
Uh, this work actually suggests that A DHD,

04:25.285 --> 04:27.445
and they arise from kind of a similar

04:27.965 --> 04:31.405
axiology factors biogenetic, environmental.

04:32.265 --> 04:34.445
So the idea of looking at A DHD

04:34.445 --> 04:37.605
and autism together is supported by this kind

04:37.605 --> 04:38.685
of, literature.

04:39.025 --> 04:43.205
And we know that both conditions actually are associated

04:43.395 --> 04:48.045
with alter trajectories in brain, development,

04:48.275 --> 04:50.765
both at the structural and the functional level.

04:51.065 --> 04:53.965
So even this kind of literature, so there are

04:53.985 --> 04:58.285
for example, studies from, Berg, so University

04:58.285 --> 05:01.445
of London, but we have a lot of, different centers

05:01.665 --> 05:04.205
and research centers and laboratories in the UK

05:04.305 --> 05:06.925
and Europe that actually are working on these.

05:08.535 --> 05:11.355
The idea, I know another idea that we actually wanted

05:11.375 --> 05:13.355
to look at, and that's actually,

05:13.575 --> 05:16.075
why we took a look at the literature in more details

05:17.095 --> 05:19.595
is about this idea of arousal

05:19.695 --> 05:22.235
or, you know, you, you talked about this very difficult

05:22.235 --> 05:23.355
work, which is autonomic.

05:23.535 --> 05:25.755
Uh, so the autonomic nervous system is actually

05:25.755 --> 05:27.155
what we were interested in.

05:27.775 --> 05:29.915
And when we talk about arou arousal,

05:29.935 --> 05:32.795
we are really looking at the ability to,

05:33.205 --> 05:35.675
especially when we look at arousal regulation,

05:36.055 --> 05:37.315
we are looking at the ability

05:37.375 --> 05:40.035
to regulate the physiological activation of the body

05:40.535 --> 05:42.915
and the evidence actually when we reviewed the evidence.

05:42.975 --> 05:47.515
So our group actually were authors on two important papers

05:47.665 --> 05:48.915
that we think are very important,

05:48.915 --> 05:52.395
where we review the literature and show that both a, d, d

05:53.015 --> 05:56.235
and, ot, they are associated with, you know,

05:56.595 --> 05:59.125
difficulties in regulating, you know, this physiological

05:59.385 --> 06:01.445
or autonom arousal levels.

06:01.985 --> 06:04.245
So these are actually, you know, another important piece

06:04.305 --> 06:06.205
of evidence that we brought into the paper

06:06.425 --> 06:09.805
to support the rationale for, for our study.

06:10.685 --> 06:14.655
Interestingly, when we reviewed the literature on visual

06:15.115 --> 06:18.815
or motor, patterns

06:18.955 --> 06:20.695
and functions in A DHD

06:20.695 --> 06:24.415
and oti, we found a, a lot of heterogeneous studies.

06:24.675 --> 06:27.135
So some studies actually, you know, they, they

06:27.575 --> 06:30.495
provided evidence in support of the idea that both A DHD

06:30.495 --> 06:33.375
and Otis are associated with challenges, you know, kind

06:33.375 --> 06:36.055
of alterations in a kilometer mechanism.

06:36.185 --> 06:38.575
Other studies actually did not find anything.

06:38.875 --> 06:40.695
So the literature was a bit confusing when

06:40.695 --> 06:41.735
we took a look at that.

06:41.795 --> 06:44.895
So that's why actually we decided to try to do another study

06:45.515 --> 06:47.055
and on a kind of an age range

06:47.055 --> 06:50.135
that was slightly different from, from what, was out.

06:50.275 --> 06:54.855
And usually they study kinda a younger, populations.

06:55.555 --> 06:58.135
And, so there is a lot of literature that we tried

06:58.135 --> 07:00.815
and summarized in the paper that supported, you know,

07:00.815 --> 07:02.815
the rational power for conducting the study.

07:03.435 --> 07:04.855
It was a larger data set,

07:04.915 --> 07:07.055
but it, it is quite, was quite a good experience.

07:07.075 --> 07:08.735
So we had a lot of support from

07:08.805 --> 07:10.295
parents and obviously children.

07:10.555 --> 07:12.615
So we, we really want thank them

07:12.675 --> 07:14.175
for participating in your research.

07:14.205 --> 07:17.375
It's very important and challenging as well for, for some

07:17.375 --> 07:19.095
of them we really appreciate their effort.

07:19.395 --> 07:22.255
But at the end, we have data from 99 children

07:22.315 --> 07:24.255
and adolescents between about seven

07:24.315 --> 07:27.695
and 15 years of age that were either diagnosed with

07:28.275 --> 07:31.015
autism only or A DHD only,

07:31.275 --> 07:33.015
or maybe they have double diagnosis.

07:33.315 --> 07:35.815
And then we have a group also of neurotypical children

07:35.845 --> 07:37.775
that we use as the comparison group.

07:37.775 --> 07:41.775
Basically, we, we try to be as much inclusive as possible.

07:41.875 --> 07:46.045
So we also included, yeah

07:46.425 --> 07:48.885
and accepted in the study children with, for example,

07:48.885 --> 07:53.365
intellectual disability or children that show A DHD and

07:53.465 --> 07:55.765
or autism and also other kind of diagnoses

07:55.765 --> 07:58.045
and conditions, which is usually the norm in clinics.

07:58.185 --> 08:00.645
So we didn't want to exclude anybody from the study.

08:01.385 --> 08:05.205
Um, the participants, you know, the mean age is 10, 10,

08:05.435 --> 08:07.525
like 11 years old, which is, you know, quite,

08:07.525 --> 08:09.485
quite common when you have this kind of age range.

08:09.595 --> 08:10.925
Most of them were males,

08:11.145 --> 08:13.925
but they were not, you know, very, there was,

08:13.935 --> 08:16.245
there were not significant differences, for example,

08:16.245 --> 08:18.405
between, males

08:18.405 --> 08:20.165
and females on the different kind of,

08:20.165 --> 08:21.325
measures that we took.

08:22.425 --> 08:25.365
So these, we had a kind of a, the majority

08:25.665 --> 08:28.685
of the children actually, not the majority,

08:28.745 --> 08:29.805
but when we took at the,

08:29.805 --> 08:31.765
when we took a look at the clinical groups,

08:31.865 --> 08:36.005
so we had about 30 children that were neurotypicals, 20

08:36.075 --> 08:39.645
that were diagnosed with a DHD, another 20 autistic,

08:39.985 --> 08:42.805
and 30 with double diagnosis.

08:42.905 --> 08:46.685
And this actually is in line with what I was telling you

08:46.685 --> 08:48.765
before, you know, the idea that those

08:48.765 --> 08:52.245
with a double diagnosis are actually not the exception,

08:52.245 --> 08:53.965
especially when we work in clinics.

08:54.785 --> 08:56.965
So the children actually part to the experiment

08:56.965 --> 09:00.765
that lasted about, I would say probably five, six hours,

09:00.825 --> 09:03.085
you know, there were breaks, obviously it was over a, a,

09:03.245 --> 09:04.925
a half day or full day.

09:04.945 --> 09:07.365
So it was again, a commitment.

09:07.365 --> 09:09.565
So again, we are really thankful to the families and,

09:09.585 --> 09:11.205
and the children that departed this.

09:11.225 --> 09:14.165
So there were different kind of a experiments.

09:14.185 --> 09:17.045
And this study focused on one specific experiment

09:17.115 --> 09:20.245
that we call the, that is called the gap overlap task.

09:20.665 --> 09:22.405
So what happened, it was the children actually,

09:22.405 --> 09:23.685
they sat in front of a computer

09:23.825 --> 09:26.045
and they just had to watch, you know,

09:26.045 --> 09:27.485
to look at, a screen.

09:27.665 --> 09:31.125
And we used a, advice that is called eye tracking,

09:31.825 --> 09:35.165
the crack, basically the children's eye case.

09:35.665 --> 09:37.845
So the, the device recorded

09:38.015 --> 09:41.285
where the child was looking on the screen basically.

09:41.465 --> 09:44.045
And we presented different kind of stimuli.

09:44.045 --> 09:47.645
There were visual stimuli, some of them were faces, some

09:47.645 --> 09:50.485
of them were non-social stimuli.

09:50.485 --> 09:52.445
There were, for example, geometrical pictures.

09:53.155 --> 09:54.525
They were static or dynamic

09:54.985 --> 09:58.645
and, sometimes they were accompanied by sounds, or,

09:58.745 --> 10:00.605
or no sounds or all because we wanted, you know,

10:00.605 --> 10:02.805
to manipulate the different conditions to,

10:02.825 --> 10:06.125
to understand a bit better, you know, basically, you know,

10:06.125 --> 10:10.005
what were the, the patterns of eye movements looking

10:10.025 --> 10:11.965
for example, from one stimulus to another

10:12.715 --> 10:13.885
between the different groups

10:14.305 --> 10:17.085
and in relation to, to other characteristics.

10:17.085 --> 10:19.485
Basically. Then the children completed some,

10:19.485 --> 10:20.885
some activities with us.

10:20.985 --> 10:23.365
The parents completed some questions to have an idea

10:23.945 --> 10:25.285
of the level of A DHD

10:25.285 --> 10:28.165
and autism symptoms, other kind of behavioral

10:28.625 --> 10:31.645
or emotional, features,

10:31.665 --> 10:35.125
and patterns like social emotional functioning, for example,

10:35.125 --> 10:36.405
intellectual functioning.

10:37.185 --> 10:39.805
And, and then, you know, they, they do, they did that,

10:39.905 --> 10:43.165
during that, that first day, the day of testing.

10:43.295 --> 10:47.885
Sorry, what happened, you know, we had like a,

10:48.245 --> 10:51.725
a specific data analysis plan that maybe I, I don't want

10:51.725 --> 10:54.365
to go into much details right now, so I suggest, you know,

10:54.365 --> 10:57.845
maybe also, people read the paper in more details

10:57.945 --> 10:59.765
and be in touch if you have any question.

10:59.865 --> 11:02.485
But basically the first set of analysis was really

11:03.335 --> 11:07.005
aimed at understanding if there were specific differences in

11:07.245 --> 11:09.885
ocular patterns between the different groups, like,

11:09.885 --> 11:13.605
you know, those with a HD only, autism only neurotypicals,

11:13.625 --> 11:15.285
or those with a double diagnosis,

11:16.785 --> 11:18.445
why we recorded eye movements.

11:18.445 --> 11:20.085
We also recorded pupil size

11:20.085 --> 11:23.405
because pupil size is a measure of what I was talking,

11:23.625 --> 11:26.965
and I was referring before with the word autonomic arousal.

11:27.305 --> 11:30.965
So the pupil, our pupil in, in the eye is actually a marker,

11:31.265 --> 11:34.725
an indirect measure of the level of activation

11:34.905 --> 11:36.125
and you know, the level of attention

11:36.155 --> 11:37.565
that you're paint or something.

11:37.825 --> 11:40.925
So we want to really to understand if changes in pupil size

11:41.635 --> 11:45.155
predicted oculomotor patterns, specifically

11:46.175 --> 11:48.835
the speed of orienting towards different kind of,

11:49.035 --> 11:50.115
stimuli on the screen.

11:50.695 --> 11:52.835
And that's actually our second part of the

11:53.125 --> 11:54.885
Analysis, which is slightly more complicated.

11:55.025 --> 11:57.685
We applied some kind of a modeling techniques

11:57.745 --> 12:00.685
to really understand if there was an association,

12:00.755 --> 12:03.685
between, changes in pupil size

12:04.185 --> 12:07.085
before actually making an eye movement.

12:07.185 --> 12:09.565
And then the speed of that, of that eye movement

12:09.565 --> 12:13.005
after that, when we looked at the task,

12:13.425 --> 12:17.125
and the, the measures that we collected, a specific measure

12:17.125 --> 12:18.925
that you collect in this task is called

12:19.075 --> 12:20.405
psychotic reaction time.

12:20.585 --> 12:24.165
And basically you, you, you present a central stimulus

12:24.305 --> 12:26.765
and then you present a separate stimulus on the periphery.

12:26.825 --> 12:29.965
So either on the right or the left side of the screen.

12:30.505 --> 12:33.805
And then you see and check how much time

12:34.415 --> 12:37.805
after presenting a central stimulus it takes to the child

12:37.905 --> 12:41.045
to make an eye movement towards the, so we took a look at

12:41.045 --> 12:42.525
that in the different kind of conditions

12:42.525 --> 12:43.685
that we had within the task.

12:44.145 --> 12:46.885
And we found, for example, that there was,

12:47.515 --> 12:49.525
when the two stimulus you were presented, one

12:49.525 --> 12:50.845
after the other, but the,

12:51.265 --> 12:54.325
the centered one was actually absent from the screen.

12:54.475 --> 12:56.045
When the peripheral was presented,

12:56.215 --> 12:58.165
there was faster ing of attention.

12:58.805 --> 13:00.725
'cause whenever you are looking at something on the screen,

13:00.865 --> 13:04.125
if something comes up, you need to spend some time

13:04.185 --> 13:07.365
to basically disengage your attention from the center

13:07.545 --> 13:09.045
and then move to the periphery.

13:09.065 --> 13:10.725
And this is one of the results that we found

13:10.985 --> 13:13.485
and that showed actually that the task was working.

13:14.355 --> 13:17.245
Another thing that we found was that, children,

13:17.335 --> 13:20.525
young people were faster to orient

13:20.785 --> 13:23.885
to the periphery when the peripheral stimulus was a

13:23.885 --> 13:25.725
phase compared to a non phase.

13:26.025 --> 13:28.005
And that shows us, you know, we are humans, you know,

13:28.005 --> 13:29.565
we are social animals.

13:29.905 --> 13:32.045
And that's actually evidence that once again,

13:32.045 --> 13:33.485
that we are really attracted

13:33.585 --> 13:36.965
and our time attention is attracted,

13:37.915 --> 13:40.525
more when actually the, the stimulus that we are,

13:40.525 --> 13:42.405
looking at is a phase.

13:42.945 --> 13:45.605
And then also when the stimulus were was multimodal.

13:45.605 --> 13:47.565
So it was dynamic, it was moving around.

13:47.565 --> 13:49.325
There was also some sound involved.

13:49.735 --> 13:51.965
Again, attention was oriented faster.

13:52.795 --> 13:55.365
What we didn't find that we expected find,

13:55.365 --> 13:57.365
based on the literature,

13:57.365 --> 14:00.085
basically we didn't find any difference in ocular motor

14:00.085 --> 14:03.205
parameters across the different groups, which is in line

14:03.205 --> 14:07.125
with more recent work that actually said, okay, maybe a DHD

14:07.125 --> 14:09.845
and autism, they are associated, yes, with behavioral

14:10.485 --> 14:13.045
outcomes, mental health challenges,

14:13.785 --> 14:17.485
but there isn't really, a specific patterns

14:17.545 --> 14:21.085
of differences in relation to ocular motor parameters.

14:21.105 --> 14:22.525
And that's actually what we found.

14:22.945 --> 14:24.685
And there was also no difference, for example,

14:24.745 --> 14:26.605
in pupil size between the groups.

14:27.305 --> 14:30.485
So we couldn't find evidence as we found, for example,

14:30.625 --> 14:35.155
for other tasks in the same battery of, of the study.

14:35.155 --> 14:38.955
Basically, no differences in arousal regulation between

14:39.525 --> 14:42.435
those with a HD, those with o autism, sorry,

14:42.755 --> 14:43.875
autistic children and those

14:43.875 --> 14:45.555
with a double diagnosis basically.

14:45.935 --> 14:48.395
And when we took a look at the second part of the analysis

14:48.395 --> 14:50.475
of the association there, between

14:50.805 --> 14:52.565
Pupil size changes and,

14:52.705 --> 14:57.645
and orienting speed, so the, the velocity basically of,

14:57.705 --> 15:01.165
of the, of the eye movements, we found something,

15:01.265 --> 15:02.725
but it was very confusing.

15:02.785 --> 15:07.685
So for example, we found that in those with a DHD, only

15:09.225 --> 15:11.235
psychotic reaction times were lowest

15:11.985 --> 15:14.995
when pupil size was either the smallest or the largest.

15:15.135 --> 15:18.715
So in some trials for this group of children in some trials,

15:18.785 --> 15:22.675
they were very slow to orient attention to the periphery.

15:22.735 --> 15:26.275
And this was the case when pupil size was very small

15:26.815 --> 15:30.595
or very large, which is not very difficult, sorry,

15:30.595 --> 15:31.835
it's not very easy to interpret.

15:32.495 --> 15:34.915
And the fact that, for example, that in neurotypicals

15:35.055 --> 15:37.795
or in those with the double diagnosis is we didn't find the

15:37.795 --> 15:41.795
same effect, actually made us think a lot about this

15:41.815 --> 15:42.995
and say, okay, what does it mean?

15:43.095 --> 15:46.155
And we really couldn't find an explanation,

15:46.355 --> 15:47.955
a clear explanation first,

15:47.955 --> 15:50.155
because this is one of the first studies of this kind

15:50.415 --> 15:52.155
to be conducted on these different groups.

15:52.855 --> 15:55.515
But it gave, it gave us some kind of a foot for toes

15:55.515 --> 15:57.955
to really understand what we need to do.

15:58.295 --> 16:00.475
And I think this is probably the next question that you want

16:00.475 --> 16:03.315
to ask me, which is, okay, where are we going next?

16:03.705 --> 16:06.715
What can we do to really understand what's going on?

16:07.135 --> 16:08.835
The first takeaway, obviously is that the task

16:08.835 --> 16:11.155
that we implemented was working, as I said,

16:11.155 --> 16:13.475
because the expected task effects were detected.

16:13.695 --> 16:16.515
We found, you know, these differences when you have just one

16:16.715 --> 16:19.515
stimulus on the screen, or two when you have phases

16:19.515 --> 16:20.595
and when you have like this kind

16:20.595 --> 16:23.315
of a multisensory dynamic stimuli showing

16:23.315 --> 16:24.475
that the task was working

16:24.615 --> 16:25.995
and it was working for all children

16:26.815 --> 16:28.675
and we didn't detect any differences.

16:29.055 --> 16:33.385
And no atypicality basically no alterations in ocular motor

16:33.385 --> 16:37.305
mechanism in a HD in the, but it's quite interesting

16:37.305 --> 16:41.105
because, one explanation that actually we gave,

16:41.285 --> 16:43.345
you know, in the paper we discussed in the papers

16:44.105 --> 16:47.785
probably the kind of age range that we chose the children,

16:48.205 --> 16:50.145
you know, in order to look at these mechanisms,

16:50.425 --> 16:54.025
probably they were a bit slightly or older than usual.

16:54.525 --> 16:58.585
And so what we tested actually was probably something

16:58.585 --> 17:00.065
that they had already developed.

17:00.845 --> 17:04.185
Uh, so focusing on infants, focusing on earlier age,

17:04.215 --> 17:07.025
when you study ocular motor mechanism would be

17:07.655 --> 17:09.905
more sensitive, you know, more and,

17:09.965 --> 17:13.345
and more effective basically to detect changes

17:13.525 --> 17:14.945
or differences between groups

17:14.975 --> 17:16.865
because you really want to look into

17:16.865 --> 17:20.865
that developmental windows where, ocular motor

17:21.415 --> 17:23.505
abilities are actually developing,

17:23.505 --> 17:25.345
which is much earlier in development.

17:25.345 --> 17:27.785
So for example, in involving infants,

17:28.735 --> 17:30.105
also newborns would be very

17:30.345 --> 17:31.465
interesting to take a look at that.

17:31.485 --> 17:33.265
And it's possible because again, this technique,

17:33.365 --> 17:35.545
eye movement is, is totally non-invasive.

17:35.685 --> 17:37.905
You don't have to even touch the child, you know,

17:38.085 --> 17:40.145
you can track the eye movements by,

17:40.315 --> 17:41.385
while looking at the screen.

17:41.485 --> 17:44.785
So that would be one, one thing to, to do.

17:45.135 --> 17:47.465
What we also observed in other tasks, it was

17:47.465 --> 17:49.485
that there were some differences in

17:49.505 --> 17:51.805
how different children actually engage with the task.

17:52.435 --> 17:54.725
Some of them were actually not engaged at all.

17:55.585 --> 17:57.045
So this was a passive task.

17:57.105 --> 18:00.485
So children didn't have to do anything, basically just had

18:00.485 --> 18:02.565
to watch the screen, you know, look at the screen,

18:02.565 --> 18:04.565
watch the stimuli, and not do much.

18:05.505 --> 18:08.245
And we noticed that for some children, this was very boring.

18:08.625 --> 18:10.325
So it could be that, for example,

18:10.475 --> 18:12.965
this task was not challenging enough for them,

18:13.505 --> 18:16.565
so it didn't actually require them to put

18:17.105 --> 18:19.605
and, you know, to concentrate, to allocate attention.

18:20.145 --> 18:23.605
It probably this task specifically was not challenging

18:23.605 --> 18:26.085
enough so that the differences

18:26.225 --> 18:27.645
and the difficulties would emerge.

18:27.645 --> 18:31.605
Basically. That's our speculation that, you know,

18:31.605 --> 18:34.205
that's why actually in the paper we propose, for example,

18:34.265 --> 18:38.085
to develop tasks that have different difficulties so

18:38.085 --> 18:41.605
that you can really see also how each child

18:42.205 --> 18:45.125
actually implement different strategies to regulate,

18:45.145 --> 18:46.445
you know, in relation to their attention,

18:46.545 --> 18:48.605
but also their arousal, their activation,

18:48.895 --> 18:50.485
their physical activity as well.

18:50.925 --> 18:53.325
Movements, but in different situations

18:53.395 --> 18:56.405
because if it is too easy, you know, too boring,

18:56.405 --> 18:58.485
sometimes it's just too easy and too boring

18:58.485 --> 19:00.325
and you're not measuring anything basically.

19:01.785 --> 19:03.005
So what we really stress

19:03.165 --> 19:06.085
and what we really recommend, future researchers

19:06.085 --> 19:10.765
to do is again, really try to work towards, you know,

19:11.215 --> 19:12.485
still collecting this data.

19:12.705 --> 19:15.085
So eye movements and pupil size, it's very important

19:15.085 --> 19:17.365
to collect this data because pupil size

19:17.365 --> 19:19.965
and eye movements, they, they, they seem

19:19.965 --> 19:21.725
to reflect the different mechanisms

19:22.545 --> 19:24.285
and they can really be helpful

19:24.425 --> 19:26.805
to understand more about attentional mechanism

19:26.865 --> 19:28.005
and arousal regulation.

19:28.705 --> 19:31.165
But this needs to be done, as I said, in in,

19:31.225 --> 19:32.365
and the data needs

19:32.385 --> 19:34.725
to be collected in different kind of situations.

19:35.515 --> 19:38.445
Ideally, you want to be in a materialistic setting as well,

19:38.445 --> 19:40.525
because obviously doing it in a laboratory

19:41.375 --> 19:43.685
where you control basically everything light,

19:43.685 --> 19:45.005
there is no distraction,

19:45.345 --> 19:47.165
is very different from the outside world.

19:47.625 --> 19:49.845
So for example, now we have a lot of very nice

19:50.225 --> 19:53.805
and beautiful devices where you can, that are portable,

19:54.055 --> 19:56.205
where you don't, I mean wire basically

19:56.205 --> 19:58.325
because they are completely in a wireless.

19:58.785 --> 20:00.485
So going out in the real world

20:00.505 --> 20:03.405
and see for example, how children with a DHD

20:03.625 --> 20:07.405
and autism actually use their visual attention, you know,

20:07.405 --> 20:09.525
what kind of stimuli are they attracted to,

20:09.835 --> 20:12.045
that would be very, very informative.

20:12.345 --> 20:14.765
I'm not saying easy, it's extremely challenging,

20:15.425 --> 20:18.205
but it would be very, very informative, I would say.

20:18.985 --> 20:22.325
So those are the things, so trying to go out into, you know,

20:22.325 --> 20:24.925
the real world, still keeping the same kind of a task,

20:25.025 --> 20:28.365
but maybe more engaging task, more challenging task so

20:28.365 --> 20:30.165
that we can have like, you know,

20:30.685 --> 20:32.805
a clearer perspective about this.

20:33.225 --> 20:37.005
And if I may, you know, spend the, the, the very last moment

20:37.105 --> 20:39.845
of this interview to really thank our founders.

20:39.985 --> 20:41.645
So the, the founders that, you know,

20:42.035 --> 20:43.205
made the study possible,

20:43.385 --> 20:46.965
but specifically, you know, all the clinicians, the families

20:47.145 --> 20:49.445
and the children that have been involved in the sun study.

20:49.445 --> 20:51.925
Because without them, we know we will not,

20:52.355 --> 20:54.165
have been able to talk about anything today.

Attention and Arousal in ADHD and Autism

00:00:00 - This paper is basically my final paper of the PhD. I did my PhD at the University of Nottingham. So the study, that we reported and ascribed in this paper is actually part of a larger study that is called the Sun Study, where we basically studied attention and arousal regulation in children with A DHD and autism. So this study was conducted in between 2017 and 2020 at the University of Nottingham uk. And we were specifically interested in the co recurrence
00:00:34 - Now, I'm not sure how much familiar you are with this, but these are two very common neuro mental conditions. They're slightly different in the sense that attention deficit hyperactivity disorder or A DHD is usually characterized by inattention, difficulties in concentrating and kind of hyperactive and impulsive behaviors. While autism is mainly characterized by kind of, adorations in social functioning, some challenges,
00:01:05 - but both they, they kind of appear, and they are actually diagnosed by clinicians starting from three, four years of age. Autism, autism slightly earlier as well. But A DHD is usually between, between four years of age. so our interest actually was specifically on those children and young people who showed both, conditions. So basically symptoms of both conditions. And this is, it looks actually rare,
00:01:36 - and when you talk to clinicians, mostly with children and their families, they actually say, yes, maybe I have a diagnosis of of A DHD, but I actually feel or experience some of the characteristics of autism or s And in this specific study, again, as I said, this was part of a larger study, but in this specific study, we were interested on, kind of visual attention of enting really, because we have, done previous work that showed that,
00:02:08 - and they, they experienced some difficulties with vision. And there is a lot of research, especially on kind of infants and especially in relation to all this that showed that, there may be some kind of difficulties in actually a very specific mechanism, which is attention ing. You know, think about right now you're watching at me, you're watching, you know, looking at me speaking, but maybe you'll see something on your right or on your left. And if you're really paying attention, maybe that thing you know, will not distract you.
00:02:39 - you rotate your head and, and watch towards the source of the destruction to see what's happening. Right? And there are specific mechanism, this mechanism of moving attention, from one stimulus to another is very crucial, especially very early in development. And we know that a lot of the characteristics of OTI and A DHD Are already present early in development. So again, based on, on there is a lot of literature that maybe we can talk about later if you're interested.

Attention and Arousal in ADHD and Autism

00:03:10 - of these difficulties in attention orienting and switching to somehow explain, you know, some of the characteristics of TI and A DHD. But when we took a look at the overlap, so the, the basically children, so the literature on children with, with bold conditions, we didn't find much literature. So basically there weren't studies that looked specifically at visual attention ing in,
00:03:40 - when they were overlapping the same, same child or the same young person, basically, few works that actually we cited in the paper as well. So first of all, actually, you know, there is support to this rational of looking at the comorbidity, the co recurrence between a DD and all this. There are a lot of very big studies conducted like, you know, internationally, and one of them is the enigma study that we actually cited in some of the papers. so some of the papers that we cited actually in the paper
00:04:09 - This is a consortium of basically different institutions and universities around Europe that looked at the genetic factors associated with different conditions, including A DHD and all. this work actually suggests that A DHD, and they arise from kind of a similar axiology factors biogenetic, environmental. So the idea of looking at A DHD and autism together is supported by this kind of, literature.
00:04:43 - with alter trajectories in brain, development, both at the structural and the functional level. So even this kind of literature, so there are for example, studies from, Berg, so University of London, but we have a lot of, different centers and research centers and laboratories in the UK and Europe that actually are working on these. The idea, I know another idea that we actually wanted
00:05:13 - why we took a look at the literature in more details is about this idea of arousal or, you know, you, you talked about this very difficult work, which is autonomic. so the autonomic nervous system is actually what we were interested in. And when we talk about arou arousal, we are really looking at the ability to, especially when we look at arousal regulation, we are looking at the ability to regulate the physiological activation of the body and the evidence actually when we reviewed the evidence.
00:05:47 - that we think are very important, where we review the literature and show that both a, d, d and, ot, they are associated with, you know, difficulties in regulating, you know, this physiological or autonom arousal levels. So these are actually, you know, another important piece of evidence that we brought into the paper to support the rationale for, for our study. Interestingly, when we reviewed the literature on visual

Examining ADHD and Autism: Diverse Study Findings

00:06:18 - and functions in A DHD and oti, we found a, a lot of heterogeneous studies. So some studies actually, you know, they, they provided evidence in support of the idea that both A DHD and Otis are associated with challenges, you know, kind of alterations in a kilometer mechanism. Other studies actually did not find anything. So the literature was a bit confusing when we took a look at that. So that's why actually we decided to try to do another study
00:06:47 - that was slightly different from, from what, was out. And usually they study kinda a younger, populations. And, so there is a lot of literature that we tried and summarized in the paper that supported, you know, the rational power for conducting the study. It was a larger data set, but it, it is quite, was quite a good experience. So we had a lot of support from parents and obviously children. So we, we really want thank them for participating in your research. It's very important and challenging as well for, for some
00:07:19 - But at the end, we have data from 99 children and adolescents between about seven and 15 years of age that were either diagnosed with autism only or A DHD only, or maybe they have double diagnosis. And then we have a group also of neurotypical children that we use as the comparison group. Basically, we, we try to be as much inclusive as possible. So we also included, yeah and accepted in the study children with, for example,
00:07:53 - or autism and also other kind of diagnoses and conditions, which is usually the norm in clinics. So we didn't want to exclude anybody from the study. the participants, you know, the mean age is 10, 10, like 11 years old, which is, you know, quite, quite common when you have this kind of age range. Most of them were males, but they were not, you know, very, there was, there were not significant differences, for example, between, males and females on the different kind of,
00:08:22 - So these, we had a kind of a, the majority of the children actually, not the majority, but when we took at the, when we took a look at the clinical groups, so we had about 30 children that were neurotypicals, 20 that were diagnosed with a DHD, another 20 autistic, and 30 with double diagnosis. And this actually is in line with what I was telling you before, you know, the idea that those with a double diagnosis are actually not the exception,
00:08:54 - So the children actually part to the experiment that lasted about, I would say probably five, six hours, you know, there were breaks, obviously it was over a, a, a half day or full day. So it was again, a commitment. So again, we are really thankful to the families and, and the children that departed this. So there were different kind of a experiments. And this study focused on one specific experiment that we call the, that is called the gap overlap task. So what happened, it was the children actually,

Eye Tracking Study in Children with Autism

00:09:23 - and they just had to watch, you know, to look at, a screen. And we used a, advice that is called eye tracking, the crack, basically the children's eye case. So the, the device recorded where the child was looking on the screen basically. And we presented different kind of stimuli. There were visual stimuli, some of them were faces, some of them were non-social stimuli. There were, for example, geometrical pictures.
00:09:54 - and, sometimes they were accompanied by sounds, or, or no sounds or all because we wanted, you know, to manipulate the different conditions to, to understand a bit better, you know, basically, you know, what were the, the patterns of eye movements looking for example, from one stimulus to another between the different groups and in relation to, to other characteristics. Basically. Then the children completed some, some activities with us. The parents completed some questions to have an idea
00:10:25 - and autism symptoms, other kind of behavioral or emotional, features, and patterns like social emotional functioning, for example, intellectual functioning. And, and then, you know, they, they do, they did that, during that, that first day, the day of testing. Sorry, what happened, you know, we had like a, a specific data analysis plan that maybe I, I don't want to go into much details right now, so I suggest, you know,
00:10:57 - and be in touch if you have any question. But basically the first set of analysis was really aimed at understanding if there were specific differences in ocular patterns between the different groups, like, you know, those with a HD only, autism only neurotypicals, or those with a double diagnosis, why we recorded eye movements. We also recorded pupil size because pupil size is a measure of what I was talking, and I was referring before with the word autonomic arousal.
00:11:31 - an indirect measure of the level of activation and you know, the level of attention that you're paint or something. So we want to really to understand if changes in pupil size predicted oculomotor patterns, specifically the speed of orienting towards different kind of, stimuli on the screen. And that's actually our second part of the Analysis, which is slightly more complicated. We applied some kind of a modeling techniques
00:12:00 - between, changes in pupil size before actually making an eye movement. And then the speed of that, of that eye movement after that, when we looked at the task, and the, the measures that we collected, a specific measure that you collect in this task is called psychotic reaction time. And basically you, you, you present a central stimulus and then you present a separate stimulus on the periphery. So either on the right or the left side of the screen.

Attention Shifts in Children with ADHD and Autism

00:12:34 - after presenting a central stimulus it takes to the child to make an eye movement towards the, so we took a look at that in the different kind of conditions that we had within the task. And we found, for example, that there was, when the two stimulus you were presented, one after the other, but the, the centered one was actually absent from the screen. When the peripheral was presented, there was faster ing of attention. 'cause whenever you are looking at something on the screen,
00:13:04 - to basically disengage your attention from the center and then move to the periphery. And this is one of the results that we found and that showed actually that the task was working. Another thing that we found was that, children, young people were faster to orient to the periphery when the peripheral stimulus was a phase compared to a non phase. And that shows us, you know, we are humans, you know, we are social animals. And that's actually evidence that once again,
00:13:33 - and our time attention is attracted, more when actually the, the stimulus that we are, looking at is a phase. And then also when the stimulus were was multimodal. So it was dynamic, it was moving around. There was also some sound involved. Again, attention was oriented faster. What we didn't find that we expected find, based on the literature, basically we didn't find any difference in ocular motor parameters across the different groups, which is in line
00:14:07 - and autism, they are associated, yes, with behavioral outcomes, mental health challenges, but there isn't really, a specific patterns of differences in relation to ocular motor parameters. And that's actually what we found. And there was also no difference, for example, in pupil size between the groups. So we couldn't find evidence as we found, for example, for other tasks in the same battery of, of the study.
00:14:39 - those with a HD, those with o autism, sorry, autistic children and those with a double diagnosis basically. And when we took a look at the second part of the analysis of the association there, between Pupil size changes and, and orienting speed, so the, the velocity basically of, of the, of the eye movements, we found something, but it was very confusing. So for example, we found that in those with a DHD, only
00:15:11 - when pupil size was either the smallest or the largest. So in some trials for this group of children in some trials, they were very slow to orient attention to the periphery. And this was the case when pupil size was very small or very large, which is not very difficult, sorry, it's not very easy to interpret. And the fact that, for example, that in neurotypicals or in those with the double diagnosis is we didn't find the same effect, actually made us think a lot about this

Understanding Challenges in Ocular Motor Mechanisms

00:15:43 - And we really couldn't find an explanation, a clear explanation first, because this is one of the first studies of this kind to be conducted on these different groups. But it gave, it gave us some kind of a foot for toes to really understand what we need to do. And I think this is probably the next question that you want to ask me, which is, okay, where are we going next? What can we do to really understand what's going on? The first takeaway, obviously is that the task that we implemented was working, as I said, because the expected task effects were detected.
00:16:16 - stimulus on the screen, or two when you have phases and when you have like this kind of a multisensory dynamic stimuli showing that the task was working and it was working for all children and we didn't detect any differences. And no atypicality basically no alterations in ocular motor mechanism in a HD in the, but it's quite interesting because, one explanation that actually we gave, you know, in the paper we discussed in the papers
00:16:48 - you know, in order to look at these mechanisms, probably they were a bit slightly or older than usual. And so what we tested actually was probably something that they had already developed. so focusing on infants, focusing on earlier age, when you study ocular motor mechanism would be more sensitive, you know, more and, and more effective basically to detect changes or differences between groups
00:17:16 - that developmental windows where, ocular motor abilities are actually developing, which is much earlier in development. So for example, in involving infants, also newborns would be very interesting to take a look at that. And it's possible because again, this technique, eye movement is, is totally non-invasive. You don't have to even touch the child, you know, you can track the eye movements by, while looking at the screen. So that would be one, one thing to, to do.
00:17:47 - that there were some differences in how different children actually engage with the task. Some of them were actually not engaged at all. So this was a passive task. So children didn't have to do anything, basically just had to watch the screen, you know, look at the screen, watch the stimuli, and not do much. And we noticed that for some children, this was very boring. So it could be that, for example, this task was not challenging enough for them, so it didn't actually require them to put
00:18:20 - It probably this task specifically was not challenging enough so that the differences and the difficulties would emerge. Basically. That's our speculation that, you know, that's why actually in the paper we propose, for example, to develop tasks that have different difficulties so that you can really see also how each child actually implement different strategies to regulate, you know, in relation to their attention, but also their arousal, their activation,

Enhancing Data Collection for Attention Studies

00:18:50 - Movements, but in different situations because if it is too easy, you know, too boring, sometimes it's just too easy and too boring and you're not measuring anything basically. So what we really stress and what we really recommend, future researchers to do is again, really try to work towards, you know, still collecting this data. So eye movements and pupil size, it's very important to collect this data because pupil size and eye movements, they, they, they seem
00:19:22 - and they can really be helpful to understand more about attentional mechanism and arousal regulation. But this needs to be done, as I said, in in, and the data needs to be collected in different kind of situations. Ideally, you want to be in a materialistic setting as well, because obviously doing it in a laboratory where you control basically everything light, there is no distraction, is very different from the outside world. So for example, now we have a lot of very nice
00:19:54 - where you don't, I mean wire basically because they are completely in a wireless. So going out in the real world and see for example, how children with a DHD and autism actually use their visual attention, you know, what kind of stimuli are they attracted to, that would be very, very informative. I'm not saying easy, it's extremely challenging, but it would be very, very informative, I would say. So those are the things, so trying to go out into, you know,
00:20:25 - but maybe more engaging task, more challenging task so that we can have like, you know, a clearer perspective about this. And if I may, you know, spend the, the, the very last moment of this interview to really thank our founders. So the, the founders that, you know, made the study possible, but specifically, you know, all the clinicians, the families and the children that have been involved in the sun study. Because without them, we know we will not,
00:20:52 -

Faculti AI can make mistakes

Faculti

Popular in Psychology

The adapted mind

Time to investigate human visual shape perception

James S. Jackson and the program for research on Black Americans

Cognitive remediation – where are we now and what should we do next?

Harnessing Plasticity in the Atypical Developing Brain using Neurostimulation

Relationship between autonomic arousal and attention orienting

Next in Developmental Psychology

Guide

Platform and Category Pages

Contact Us

FAQs

What is Faculti?

How do you select interviews?

Interview Process

Page Structure

Popular in Psychology

Guide

Platform and Category Pages

Contact Us

FAQs

What is Faculti?

How do you select interviews?

Interview Process

Accessibility Options

Contrast Adjustment

Text Size Adjustment

Text Spacing Adjustment

Line Height Adjustment

Cursor Size Adjustment

Page Structure Options

Page Structure