Postdoctoral Fellowship in Childhood Neuropsychiatric Disorders (T32) Trainee Talks

Transcript

• 00:00Good afternoon, everyone.
• 00:04Thank you for coming today
• 00:05to our T32 Grand rounds.
• 00:07We're on a tight schedule.
• 00:08We have three talks,
• 00:10so I'll be brief and concise.
• 00:12I direct the T32 Codirect
• 00:15T32 with Michael Block.
• 00:17We're in, I think our 38th or 39th year.
• 00:21It's really one of the joys of
• 00:23my professional career to be a
• 00:25part of this following in the
• 00:27big shoes of Doctor Lechman.
• 00:29Not physically big, but big.
• 00:31Metaphorically,
• 00:35we are up for a newal next year,
• 00:37so we're going to be doing a mad
• 00:39rush and reaching out to all of
• 00:41you for materials to support us.
• 00:42And we really couldn't do it and
• 00:44succeed without you all and that the
• 00:46atmosphere that you bring to the center.
• 00:51Okay. They told me I need to hit
• 00:52click first here. There we go.
• 00:54So our T32 is growing.
• 00:56We only have six slots,
• 00:57Not only but that's what we have,
• 00:58but we have many others
• 01:00who participate with us.
• 01:01And here's a picture.
• 01:02I'm not a a Photoshop ace,
• 01:03so I was able to bring everyone in here.
• 01:06I'm going to ask for some help
• 01:08down the road from you all.
• 01:11And what we're going to hear about
• 01:14today are three talks from trainees
• 01:18Francesca Penner. Dr. Penner.
• 01:20Doctor Gerber and Doctor Kistagna.
• 01:22Dr. Penner will be telling us
• 01:24about her work on understanding
• 01:26emotional regulation and pregnancy.
• 01:28Doctor Gerber will be telling
• 01:30us about emotion disruption and
• 01:32loneliness and autistic and autistic
• 01:33youth during the COVID pandemic.
• 01:35And lastly, Dr.
• 01:36Kistagna will be talking about modeling
• 01:38gaze behavior and starting point bias,
• 01:41drift rate and frontal midline
• 01:43beta EEG oscillations.
• 01:45Before we get on to the three talks,
• 01:46I just want to say a few words
• 01:48about these three trainees.
• 01:50We would love to be able to have
• 01:51everyone speak and we did make a
• 01:53call to everyone and then these are
• 01:54three individuals who reached out,
• 01:56but we'll be catching other
• 01:58people next year to present again.
• 02:00Doctor Penner has really done an
• 02:03exceptional job as a T32 trainee.
• 02:06She got her own funding, F32.
• 02:09She published 38 papers up to this point.
• 02:12Not all in the T32,
• 02:13but you know that's what she's
• 02:15been doing across her career.
• 02:17And she landed a academic position
• 02:19at Baylor University of Department
• 02:21of Psychology and Neuroscience,
• 02:23so she'll be heading there.
• 02:24Doctor Gerber is in his first
• 02:26year in the T32 and he's rocked
• 02:28it already with two grants.
• 02:30He's got a autism grant and also
• 02:35from the Organization for Autism
• 02:37Research and also a Child Study
• 02:39Center Pilot Research Award.
• 02:40So Congrats to Doctor Gerber.
• 02:42And lastly Dr.
• 02:43Stagna.
• 02:46Also was quite prolific with 33
• 02:50papers and and F32 also that's an
• 02:54independent training grant that he
• 02:56received and he's landed a tenure track
• 02:59position at University of Alabama.
• 03:02So before I hand over the
• 03:06the mic to Doctor Penner,
• 03:09I just want to make a plug
• 03:11for these these F32 grants.
• 03:13We really only have a small number of.
• 03:16Spots on the T32 compared to the need.
• 03:19And so I encourage everyone here to
• 03:22try to to pursue these F32 grants.
• 03:24We have lots of support for you.
• 03:26We read them.
• 03:27Michael and I both sat on the study second
• 03:29committee for the review of the grants.
• 03:31We have examples so we can scaffold you to
• 03:33pursue these grants if you're interested.
• 03:35Anyway, thank you.
• 03:36Here's a treat for you.
• 03:39So Doctor Penner.
• 03:48Hi everyone.
• 03:49Thank you so much, Doctor Crowley.
• 03:50I'm really thrilled to be
• 03:52presenting at Greyhounds.
• 03:53It's very exciting.
• 03:54I like Doctor Crowley said.
• 03:56My name is Francesca Penner.
• 03:58I'm a postdoc working with Helena
• 04:00Rutherford in the before and after baby lab,
• 04:02and today I'm presenting some work focused
• 04:05on emotion regulation during pregnancy.
• 04:07I was excited to present this
• 04:09work in particular because it's
• 04:11something that I started on right
• 04:13at the beginning of postdoc,
• 04:14so I thought it would be interesting
• 04:16to kind of share the progression
• 04:18of work over the past two years.
• 04:20So to start,
• 04:21I wanted to begin with talking about
• 04:23why it's interesting and important to
• 04:26study emotion regulation in pregnancy,
• 04:28beginning more broadly with the importance
• 04:30of emotion regulation in general.
• 04:31So we know emotion regulation is
• 04:34a transdiagnostic factor relevant
• 04:36to many mental health disorders
• 04:38and symptoms of psychopathology.
• 04:40We also know it's a it's targeted in
• 04:42multiple evidence based treatment.
• 04:43So we have evidence that it can it's
• 04:46modifiable that we can improve emotion
• 04:48regulation and that by improving it.
• 04:50Or by decreasing emotion to circulation,
• 04:53we can prevent and reduce
• 04:55symptoms of psychopathology.
• 04:57And we also know that emotion
• 04:58regulation is important in caregiving.
• 05:00So it helps us be more sensitive caregivers.
• 05:03And it's also important in terms of
• 05:05modeling for children as they develop
• 05:08and learn emotion regulation as well.
• 05:10When you think about emotion
• 05:12regulation during pregnancy,
• 05:13you can think about some of the unique
• 05:15factors during this period that
• 05:16might affect our emotion regulation.
• 05:18So.
• 05:18Certainly there are lots of physical
• 05:20changes for the pregnant persons
• 05:22and physiological and brain changes
• 05:23that might affect the physiological
• 05:26experience of emotions during pregnancy.
• 05:28There are also psychosocial
• 05:29stressors that might come up,
• 05:31whether it's financial relationship
• 05:33or medical stressors that might
• 05:36challenge or require emotion
• 05:38regulation strategies during this time.
• 05:40And then we also know that pregnancy
• 05:41is a time of increased vulnerability
• 05:43for mental health disorders,
• 05:45especially depression and anxiety,
• 05:47which also makes emotion regulation
• 05:50really relevant during this time.
• 05:52And then finally,
• 05:53when we think about for new parents
• 05:56of the transition to parenthood,
• 05:57whether there might be changes
• 05:59in emotion regulation as sort of
• 06:01as new skills come online as we
• 06:03become parents for the first time.
• 06:05So thinking about all those ways
• 06:07that emotion regulation might
• 06:08change during pregnancy,
• 06:10but also its relevance for stress and mental
• 06:13health and caregiving during this time,
• 06:16we were interested in kind of
• 06:18looking at what's already known
• 06:19about emotion regulation during
• 06:20pregnancy in terms of the correlates,
• 06:23both during pregnancy and
• 06:25in the postpartum period.
• 06:27So early in 2022,
• 06:28Helena and I posted a paper and
• 06:30Archives of Women's Mental Health.
• 06:32That summarizes this research area
• 06:34and it's a pretty small research
• 06:36area so far in terms of studies
• 06:38that have actually measured emotion
• 06:41regulation during pregnancy and
• 06:43association with other variables
• 06:45either in pregnancy or postpartum.
• 06:47So this figure from our paper
• 06:50kind of summarizes this
• 06:52area so far. It's definitely
• 06:53a growing area of research.
• 06:55So I expect that things have may have
• 06:56changed in the last year and a half,
• 06:58but in terms of what this
• 07:01figure represents, so the.
• 07:03Boxes in solid lines with solid arrows
• 07:06are correlates that we have evidence
• 07:09for from at least one study where the
• 07:12boxes that are grayed out with dashed
• 07:14lines are hypothesized correlates of
• 07:16emotion regulation during pregnancy.
• 07:18So some of the things you have
• 07:20evidence for so far are that emotion
• 07:23regulation measured during pregnancy
• 07:25are related to physical and mental
• 07:27health of the pregnant person
• 07:28both in pregnancy and postpartum.
• 07:30It's shown association with caregiving
• 07:33behavior measured during pregnancy as well.
• 07:35And then it's Even so shown some
• 07:39associations between motion regulation
• 07:40during pregnancy in the pregnant
• 07:43person and then with some infant
• 07:46outcomes like feeding interactions
• 07:48and infant attention and arousal.
• 07:50So we have some emerging evidence for.
• 07:54These significant links showing that
• 07:56emotion regulation in pregnancy might
• 07:58have implications for not only a mental
• 08:01health in the pregnant person but also
• 08:04caregiving and infant development.
• 08:05Which suggests that this is an
• 08:07important factor to study and also
• 08:10the potentially important factor
• 08:11for intervention because it could
• 08:14have these multi prompt impacts
• 08:16even into the postpartum period.
• 08:20So wanting to kind of build on this
• 08:22evidence base and study emotion
• 08:24regulation during pregnancy more,
• 08:25we conducted 2 studies with archival data
• 08:28focused on emotion regulation and perceived
• 08:31stress during the perinatal period.
• 08:33And in both of these studies,
• 08:35we were conceptualizing perceived stress
• 08:37in terms of appraisals of one's life
• 08:40as stressful versus objective measures
• 08:42of life of stressful life events.
• 08:45And we were thinking about emotion regulation
• 08:46in terms of James Gross's definition.
• 08:48So attempts to influence one's
• 08:51emotions and how they're expressed.
• 08:53In particular,
• 08:54thinking about the emotion regulation
• 08:56strategies of reappraisal and suppression
• 08:58with reappraisal thoughts to be a more
• 09:01adaptive emotion regulation strategy
• 09:02and suppression thoughts to be a more
• 09:05maladaptive emotion regulation strategy.
• 09:07So in the first study,
• 09:08we were focused on emotion regulation
• 09:11strategies and perceived stress
• 09:12and expectant mothers and fathers.
• 09:14During the third trimester,
• 09:17and this was a sample collected here at Yale.
• 09:20Of 83 expectant parents,
• 09:21about 50 of them were pregnant
• 09:23mothers and then about half of the
• 09:25sample were first time parents.
• 09:27They completed the Perceived Stress Scale
• 09:29and the Emotion Regulation Questionnaire.
• 09:30During the third trimester
• 09:33of pregnancy and 1st,
• 09:34we looked at associations between each
• 09:36of those emotion regulation strategies,
• 09:38reappraisal and suppression
• 09:40with perceived stress.
• 09:42And we saw associations in expected
• 09:44directions based on prior work
• 09:45with the emotion regulation
• 09:47questionnaire in other samples.
• 09:48So we saw that as parents reported greater
• 09:50levels of or greater use of suppression,
• 09:52they also reported greater stress.
• 09:55And as they reported
• 09:56greater use of reappraisal,
• 09:57they reported lower perceived stress.
• 09:59So this is really underlining that
• 10:01in a sample of expected parents,
• 10:03we're seeing associations in expected
• 10:06directions with these two emotion
• 10:08regulation strategies and perceived stress.
• 10:11We then were interested in whether
• 10:13the mothers and fathers differed in
• 10:15their levels of perceived stress
• 10:17and emotion regulation strategies.
• 10:19And we saw we were actually surprised
• 10:21to see this finding was against our
• 10:23hypothesis that perceived stress in
• 10:25mothers and fathers was not different.
• 10:28So during the third trimester,
• 10:29they're reporting similar levels of
• 10:32stress and they're also reporting
• 10:34similar levels of each emotion
• 10:35regulation strategies.
• 10:36There were not any differences
• 10:38between mothers and fathers.
• 10:41So this study, one limitation of it
• 10:43was that it was crosssectional data.
• 10:45We were interested in also trying to
• 10:48understand better the direction of effects
• 10:50between emotion regulation and perceived
• 10:52stress during the perinatal period.
• 10:53So we had some archival data
• 10:55from a collaborator at Texas
• 10:57A and M Rebecca Brooker,
• 10:58and that's what we examined and study too.
• 11:00So this study also looks at perceived
• 11:03stress and emotion regulation,
• 11:04those same 2 variables and
• 11:07measures across three time points
• 11:09in in the perinatal period.
• 11:12So because we had three time points,
• 11:14here was the 2nd trimester,
• 11:15third trimester and four months postpartum.
• 11:18We were interested in testing a cross
• 11:20like panel model to be able to look at
• 11:23both the stability of each of these
• 11:25constructs but also the cross lag and
• 11:28cross-sectional relationships between them.
• 11:31And this was a sample of 92 pregnant women.
• 11:35This these data were collected
• 11:36at Montana State University.
• 11:38And as I said,
• 11:39they completed the same 2 measures,
• 11:41the Emotion Regulation Questionnaire
• 11:42and the Perceived Stress Scale
• 11:44in the second trimester,
• 11:45third trimester and four months postpartum.
• 11:49So we looked at associations between
• 11:51suppression and perceived stress.
• 11:53We really only saw evidence for
• 11:54stability of each of these constructs.
• 11:57So there were no cross,
• 11:58lagged or cross-sectional associations
• 12:00between suppression and perceived
• 12:02stress in this sample.
• 12:05We looked at associations between
• 12:07reappraisal and perceived stress.
• 12:08We again saw evidence for the
• 12:10stability of each of these
• 12:12across the three time points.
• 12:14And then we saw cross-sectional
• 12:15associations in the same
• 12:17direction as study one. So as
• 12:21reappraisal increased, perceived stress
• 12:23decreased in the same time point.
• 12:27We also saw evidence for one cross lag
• 12:29effect, so giving us some potential
• 12:31information about the direction of
• 12:33effects where greater stress in the
• 12:36second trimester predicted lower
• 12:37reappraisal in the third trimester.
• 12:39So potentially suggesting that
• 12:41more stress in pregnancy could
• 12:44sort of get in the way of adaptive
• 12:48emotion regulation strategies.
• 12:49To summarize these two studies,
• 12:51so both studies together showed.
• 12:53Significant links between reappraisal
• 12:55and perceived stress cross sectionally in
• 13:00both mothers and fathers during during
• 13:02pregnancy Study two gave some evidence
• 13:05for the stability of emotion regulation
• 13:07strategies over the perinatal period.
• 13:09Although it's really important to know that
• 13:11this measurement of emotion regulations,
• 13:12your questionnaire measure,
• 13:13is thought to be more traitlike.
• 13:15So that's one reason why we're
• 13:18we're likely seeing stability here.
• 13:21And study two,
• 13:22we saw that higher stress or appraisals
• 13:24of stress in the second trimester
• 13:26sort of might get in the way of
• 13:28adaptive emotion regulation later on.
• 13:30So giving us information about the
• 13:32direction of effects and then study
• 13:33one suggests that there is a potential
• 13:35need to include both expected parents,
• 13:37so not just the pregnant parent in
• 13:39prenatal mental health screening
• 13:40and interventions because we saw
• 13:42these similar levels of stress
• 13:44reported by both parents.
• 13:47So I wanted to briefly go through two
• 13:50current studies that focus on emotion
• 13:52regulation during pregnancy that I
• 13:54got funding for as a postdoc and
• 13:56these are collecting data right now.
• 13:58So if we go back to our initial model,
• 14:00what is known and unknown in
• 14:02terms of correlates?
• 14:03I was interested in better understanding
• 14:06emotion regulation in during
• 14:08pregnancy at a qualitative level,
• 14:10so understanding women's subjective
• 14:12experience of emotions and emotion
• 14:14regulation during pregnancy.
• 14:15So I received funding from Yale Women
• 14:17Faculty Forum to conduct a qualitative study.
• 14:20This is data collections going on right now,
• 14:22so I've done about half of the interviews,
• 14:25and the goal is to hear directly
• 14:27from pregnant women about their
• 14:29experience of emotions, stressors,
• 14:30and emotion regulation during pregnancy.
• 14:33It's specifically first time pregnant women,
• 14:36and the plan is to code these
• 14:38interviews once they're all complete
• 14:40using thematic analysis.
• 14:42The second study that's ongoing right
• 14:43now is focused on this association
• 14:45between emotion regulation measured
• 14:47in pregnancy and whether it can tell
• 14:49us anything about future caregiving
• 14:51behavior after the baby is born.
• 14:54So this study is funded by the
• 14:56Colleen Dobbins Foundation and the
• 14:57American Psychological Foundation,
• 14:58and it is recruiting 61st time parents,
• 15:01both mothers and fathers,
• 15:03to evaluate whether emotion regulation
• 15:05measured during the third trimester.
• 15:07Can predict caregiving 2 to four
• 15:10months postpartum.
• 15:10And in terms of caregiving,
• 15:12we're specifically interested
• 15:14in responses to infant crying.
• 15:16We're measuring that in multiple ways
• 15:18that so through questionnaire measures,
• 15:20through behavior during the still
• 15:22face paradigm through behavior
• 15:23during a baby simulator task that
• 15:25Helena has used before in her studies
• 15:27that is programmed to cry for a
• 15:29certain amount of time.
• 15:31And then also through measuring EE,
• 15:33G and event related potentials during
• 15:35audio of infant crying as well.
• 15:40So as I transition to faculty, I'm excited
• 15:42to continue building this line of research.
• 15:44So some initial thoughts are to expand the
• 15:46UP study which is that last study I shared to
• 15:48have a group of parents of psychopathology.
• 15:51I'm also really interested in physiological
• 15:53measures of emotion regulation, including EE,
• 15:56G&ERP at multiple time points to understand
• 16:00other methods with other methods,
• 16:02whether there's stability or change in
• 16:04the motion regulation over this period.
• 16:05And then I'm very interested in,
• 16:08in this in the context of intervention,
• 16:11to really thinking about interventions
• 16:13that improve emotion regulation,
• 16:14whether they can really have this,
• 16:17these multipronged impacts in terms of.
• 16:20Both parental and child health and
• 16:23caregiving after the child is born.
• 16:26So I just wanted to end by thanking Helena.
• 16:29She's been the best postdoctoral mentor
• 16:31I could have imagined and as well
• 16:34as Doctor Crowley and Doctor Block,
• 16:36the T32 directors.
• 16:37It's been really great to be in the
• 16:40T32 and especially in terms of grant
• 16:43writing training and also wanted to thank
• 16:45funders and everyone in the Babel lab,
• 16:47coauthors and other post docs
• 16:49in the T32 seminar.
• 16:50Thank you.
• 17:01So we do have time for questions.
• 17:03We have 5 minutes. Make sure
• 17:06this is done. Any questions?
• 17:13That was very impressive and interesting.
• 17:15Thank you. Since you're interested
• 17:17in qualitative studies, I was just
• 17:19wondering what your thoughts are
• 17:20about measures of stress in the
• 17:22pregnant moms, if it's self-reports
• 17:25are better or some objective measures.
• 17:27What's your experience now being in there
• 17:29I think really that.
• 17:33Neither one is better.
• 17:34Like I really think it's
• 17:35important to do both.
• 17:36I mean these these studies, you know,
• 17:38were perceived stress and I do think
• 17:40there is a place for that because, you know,
• 17:43our perceptions of stress are important.
• 17:45And there's some evidence that it might
• 17:47overlap more with like mental health,
• 17:48like depression and anxiety.
• 17:50But I do think that it,
• 17:52I think it's also interesting in
• 17:54doing these interviews and kind of
• 17:56talking with women about the stressors
• 17:58they are experienced how sometimes.
• 18:01Like objective stressors are minimized
• 18:04in terms of like our reporting of
• 18:05them and so then being able to
• 18:08measure those because they might,
• 18:09they might be having some kind of
• 18:12biological effect that we're not,
• 18:14you know like acknowledging or or reporting.
• 18:18I do think there's some minimizing and.
• 18:21And I think also like I've learned
• 18:23from these interviews as well,
• 18:24I think also like pregnant women
• 18:25really get the message that they
• 18:27shouldn't be stressed during pregnancy.
• 18:29And so then they're like trying
• 18:31to minimize the stressors that
• 18:33they are experiencing.
• 18:37You have 3 minutes. Another question,
• 18:41Doctor Mcpartland.
• 18:48Having never been pregnant,
• 18:49I am surprised that the message
• 18:51received that you shouldn't be stressed
• 18:52during pregnancy As the husband
• 18:54of a woman who's been pregnant,
• 18:55we had a different experience,
• 18:56but I'm related
• 18:58to that. I'm curious when you I was surprised
• 19:00to see similar levels of stress
• 19:02between the between both partners and
• 19:04do you have a sense,
• 19:05how do you interpret that?
• 19:06And do you have a sense of
• 19:08the quality and the nature
• 19:08of the stress and whether they're
• 19:10stressed about the same things?
• 19:12Yeah, I think that's such a good question
• 19:14and I was wondering about that myself,
• 19:16like as I was doing this.
• 19:18Presentation again,
• 19:19just kind of re wondering about that result.
• 19:22I yeah, I'm not sure and some of them
• 19:24were couples and some of them were not.
• 19:26So I think there's also you know when
• 19:29we looked at whether we need to control
• 19:32for the fact that some of them were in
• 19:34couples that perceived stress like did
• 19:36have an effect at the couple level.
• 19:39So there were.
• 19:40So I think you know some of that
• 19:42is like whatever stressors are
• 19:43affecting both of them do seem
• 19:45to be a factor and then I think.
• 19:47And I think I'm definitely interested
• 19:49in kind of looking at that more.
• 19:51I'd like the partner effects in
• 19:53terms of like objective stressors
• 19:55and how stress on the mom might be
• 19:58affecting stress on the dad and
• 20:00we're on the nonpregnant parent.
• 20:02But then also understanding,
• 20:03I think,
• 20:04how the relationship can also be protective,
• 20:08like help to reduce stress or not.
• 20:15Thank you Doctor Penner. Okay,
• 20:17we'll have Dr. Gerber come up.
• 20:21All
• 20:28right.
• 20:33So that was a great talk,
• 20:35hard to follow. I am really,
• 20:38really excited to be here today and perhaps
• 20:40a little bit nervous to be speaking to
• 20:42such really great minds and people.
• 20:45Here that you know have
• 20:47inspired my work over the years,
• 20:49so I'm really excited to talk to you about
• 20:51some work that came out of my dissertation,
• 20:53which is done at Stony Brook University.
• 20:56I'm currently finishing up my first year of
• 20:59postdoc in Doctor Mcpartland's lab right now,
• 21:03and so I'll be talking about
• 21:05social disruption and loneliness
• 21:07in autistic and non autistic youth
• 21:10during the COVID-19 pandemic.
• 21:12So first of all what what do we
• 21:13mean when we talk about loneliness?
• 21:15So something we all a concept
• 21:17we're all familiar with,
• 21:18but really we're defining it as
• 21:21this mismatch between your desired
• 21:23and your actual social activity.
• 21:27So it's a really important and
• 21:29a major public health concern.
• 21:31There's a lot of data that we have
• 21:33pre pandemic even that shows that
• 21:35loneliness is associated with worse
• 21:38mental as well as physical health.
• 21:41So it's really great concern,
• 21:42but of course, as we all know,
• 21:44we all live through,
• 21:45during the pandemic this became
• 21:47almost one of the, you know,
• 21:49key or probably the key psychosocial concern.
• 21:52And even into today we're still
• 21:55experiencing a rise in social
• 21:57isolation and loneliness,
• 21:59especially in our youth or for our youth.
• 22:05So how is this affecting autistic
• 22:07individuals and autistic youth?
• 22:09Well, there were already some of
• 22:12these preexisting disparities,
• 22:13and the pandemic really exacerbated those.
• 22:16So, for example, mental health concerns,
• 22:19increases in stress, anxiety,
• 22:21depression for autistic youth who are
• 22:24already kind of at risk and importantly
• 22:26as well for their caregivers.
• 22:32So one thing we know is somebody who
• 22:35studies social isolation and loneliness is
• 22:37pre pandemic autistic youth were already
• 22:40experiencing some challenges with this.
• 22:42They were already at elevated risk
• 22:45for loneliness and social isolation.
• 22:47And so one thing to consider is that
• 22:51the pandemic could really put them
• 22:53at even greater risk for you know,
• 22:56based on its impact on social life.
• 23:00So despite the fact that you know,
• 23:02there's a clear interest in this
• 23:04and there are qualitative reports
• 23:06on this that will tell you,
• 23:07you know, autistic people will
• 23:09report missing of social contact,
• 23:11but there's actually, to my knowledge,
• 23:14has not been any qualitative or sorry
• 23:16quantitative examination of loneliness
• 23:18and autistic use during the pandemic.
• 23:23So we set out to do is really
• 23:25understand what were the trajectories
• 23:27of social disruption and loneliness
• 23:29for autistic youth during this
• 23:31early period of the pandemic.
• 23:32What was it like for them?
• 23:36I want to take you through a little bit
• 23:38of what the study recruitment looked like.
• 23:40So we began the study early June,
• 23:44so June 1st, 2020, if you can think back
• 23:46to a couple years ago what that was like.
• 23:49And we follow families and and
• 23:51youth for about six months.
• 23:53So that went from basically June until mid.
• 23:57Should I talking to the mic more?
• 23:58Can you can you guys hear me?
• 24:00Is it better with the mic?
• 24:02OK, hold on,
• 24:05it was meant for somebody taller I think.
• 24:09So in so basically the study ran
• 24:12from June until early December,
• 24:14early to mid-december 2020.
• 24:16So that over the period of six
• 24:18months we had participants in there
• 24:21and one caregiver fill out some
• 24:23questionnaires every two weeks.
• 24:24And so that total 12 total
• 24:27questionnaires over that period of time.
• 24:33All the families that came in
• 24:35and participated had already come
• 24:37into the lab and when they did.
• 24:39They completed standardized a gold
• 24:42standard diagnostic evaluation for autism.
• 24:45They also completed a
• 24:46cognitive assessment as well.
• 24:48So during this study,
• 24:50we asked participants to complete the a
• 24:54Standardized Self Report of loneliness,
• 24:56and that's the UCLA Loneliness Scale.
• 24:57So they they did that every
• 24:59other week for six months.
• 25:01We asked our caregiver to tell
• 25:02us a little bit about how the
• 25:04pandemic was impacting the family.
• 25:06And in particular,
• 25:07we're really interested in understanding
• 25:09social disruption in the family.
• 25:11And when I say that,
• 25:12what I mean is we were focused on the
• 25:14items that were related to family,
• 25:16anything that's limited or restricted
• 25:19family and social activities.
• 25:25So 76 youth participated in this study,
• 25:2851 were autistic, 25 were not.
• 25:32They range in age from 8 to 17 and what
• 25:36you can see here is as we would expect,
• 25:39there were differences.
• 25:40The autistic youth were had
• 25:43higher autism symptoms, severity.
• 25:45They also were more males,
• 25:47but other than that they were pretty
• 25:49evenly matched across the board.
• 25:50So there were no differences in
• 25:52loneliness or social disruption
• 25:53at that first time point.
• 25:59So what do we think?
• 26:00What's going to happen?
• 26:01Well, we hypothesize that social
• 26:03disruption would decrease over
• 26:05time for non autistic youth,
• 26:08but remain about the same for autistic youth,
• 26:11perhaps due to some of the stress
• 26:13and mental health challenges going
• 26:15on with parents and in youth.
• 26:18We also hypothesize that loneliness would
• 26:21decrease over time for non autistic youth,
• 26:24but remain about the same for autistic youth.
• 26:27And perhaps due to challenges
• 26:29in the change in routine that we
• 26:31all experienced in the pandemic.
• 26:33And finally,
• 26:34we hypothesize that greater social
• 26:36disruption would be associated
• 26:38with greater loneliness.
• 26:42So what did we
• 26:43find? Well, I want to walk
• 26:45you through this chart.
• 26:46So on the X axis, what you see basically
• 26:49is time since the study starts,
• 26:51so time over six months.
• 26:53And on the Y axis you can
• 26:55see their social disruption.
• 26:57So higher scores here,
• 26:59higher numbers means greater
• 27:02social disruption.
• 27:03And what you can see is
• 27:05that over time both groups,
• 27:07both the non autistic and the
• 27:09autistic groups decreased in their
• 27:12experience of social disruption.
• 27:14However, there was an interaction effect,
• 27:15so we did find that non autistic
• 27:17youth had a greater decline
• 27:19in social disruption over time
• 27:21compared to autistic youth.
• 27:26So what about loneliness?
• 27:27What happened with loneliness?
• 27:29Well, and I'll get into this later,
• 27:31this was a bit of surprise,
• 27:32but what you can see here is on the
• 27:35X axis you can see time again on the
• 27:38why you're now seeing loneliness.
• 27:39So higher scores here means
• 27:42higher self reported loneliness.
• 27:44And actually what we found here was that
• 27:46loneliness did in fact decrease over time,
• 27:48but only for the autistic youth in the study.
• 27:51So you can see in the blue.
• 27:54That's a statistically
• 27:56significant decline in the red.
• 27:59You're seeing non autistic youth
• 28:00and there's no statistically
• 28:01different change over time.
• 28:06So finally I want to show you the results
• 28:08for loneliness and social disruption.
• 28:11So you can see on the X axis now
• 28:13you're seeing social disruption.
• 28:14So again, higher numbers means
• 28:17greater social disruption.
• 28:19On the why, you're now seeing loneliness.
• 28:21So higher numbers means greater
• 28:23self reported loneliness.
• 28:25The colors are the same and what you
• 28:28can see is this interesting interaction
• 28:31effect where for autistic youth we did
• 28:33find the relationship we expected so
• 28:35we did find greater social disruption
• 28:38was associated with greater loneliness.
• 28:40But for the non autistic youth
• 28:41we did not see that,
• 28:42we didn't see that relationship.
• 28:48So what do we make of all this?
• 28:50So let's start with the
• 28:52findings on social disruption.
• 28:54But what we found was that
• 28:56social disruption declined
• 28:57over time for both groups,
• 28:59but it was a greater decline
• 29:01in the non autistic youth.
• 29:06So perhaps one way to look at this
• 29:08is that non autistic youth made a
• 29:11quicker return to social activities.
• 29:16So in thinking again.
• 29:17Into what this period
• 29:19was like for caregivers.
• 29:20There's quite a bit of research
• 29:22that suggests that, you know,
• 29:24caregivers of autistic individuals and
• 29:25autistic youth were already stressed.
• 29:27And the pandemic with challenges and
• 29:29getting services and all sorts of changes
• 29:32in routine were really quite stressful.
• 29:34And if you think about it or if
• 29:35there any parents in the room,
• 29:37parents tend to be the gatekeepers,
• 29:39the facilitators of social activity.
• 29:42And so perhaps one way to think about
• 29:44this is that it might have been hard.
• 29:46For those parents to reengage in social
• 29:49activity and to bring their kids to
• 29:52activities and things of that nature.
• 29:54And so I think it's really important
• 29:56to think about and the implications
• 29:58here for parents health particular
• 30:00or parent mental health,
• 30:01thinking about caregivers of autistic youth,
• 30:05both during the pandemic but also
• 30:07now that it can be have a really sort
• 30:10of profound impact on their kids.
• 30:16So what happened with loneliness?
• 30:18Loneliness declined over time,
• 30:20so we did find that, but actually
• 30:22it was only for the autistic youth.
• 30:24And if you think about that graph
• 30:26what it what seems to be happening
• 30:29is sort of they're coming close
• 30:31to their non autistic peers.
• 30:34This is really striking to me,
• 30:36really surprising because it runs
• 30:39counter this widely accepted idea
• 30:41that autistic youth are sort of
• 30:43universally lonely or or isolated.
• 30:46And so one one thing we thought
• 30:48about maybe this is actually
• 30:49related to the change in routine,
• 30:51but it in a positive way.
• 30:52So perhaps there was some
• 30:55flexibility or choice in who,
• 30:57how, when they were interacting,
• 30:59how frequently that led to
• 31:01reductions in loneliness.
• 31:06Another thing we really thought
• 31:07about though is if you guys remember.
• 31:10When you were in the pandemic,
• 31:11remember this appeared of of
• 31:13June 2020 and and on right?
• 31:15There was a big increase in who
• 31:17you were spending time with.
• 31:18It was whether it was your roommate,
• 31:20your your family.
• 31:21And so there was a big
• 31:23increase in family time.
• 31:24And perhaps one possibility is that
• 31:25this was actually a big positive
• 31:27for autistic youth that they enjoyed
• 31:29spending time with their family.
• 31:33So lastly, we found that increases
• 31:35in social disruption did lead to
• 31:37greater loneliness, but actually
• 31:39it was only for autistic youth.
• 31:43So this suggests to us that when they were
• 31:46actually experiencing social disruption,
• 31:48autistic youth were more vulnerable to
• 31:51feelings of loneliness than their peers.
• 31:54And so one thing we thought about was,
• 31:56you know, if you're experiencing the
• 31:58social disruption and you're sort of.
• 32:00Forced into only this
• 32:02digital social communication,
• 32:03we all remember the zoom fatigue,
• 32:05that zoom burnout of of 2020.
• 32:08This is something that might be in
• 32:10particular a challenge for autistic
• 32:12youth as they are experiencing
• 32:13more and more social disruption
• 32:15and this is for their only option.
• 32:17Although another possibility is that they
• 32:20didn't have anyone else to reach out to.
• 32:22Perhaps other teens were Facetiming all day,
• 32:24but autistic youth who are experiencing
• 32:26a lot of social disruption didn't really
• 32:29have other options and deep connections.
• 32:32So I'm thinking about what my next steps are.
• 32:34I'm really interested in continuing
• 32:36to examine loneliness and autistic
• 32:38youth and thinking about its
• 32:40relationship with suicidality.
• 32:42So I'm really grateful for funding from
• 32:44the Yale Child Study Center pilot grant,
• 32:46as well as the Organization
• 32:48for Autism Research.
• 32:49And what we plan to do is we'll
• 32:51have participants come in the lab,
• 32:53complete a naturalistic
• 32:54social reward paradigm,
• 32:56and then we'll have them fill out
• 32:58questionnaires through an app on their
• 33:00smartphone telling us about loneliness as
• 33:02they experience it outside of the lab.
• 33:04And ultimately,
• 33:05we hope to understand the
• 33:07relationship between social reward,
• 33:09loneliness,
• 33:10and and suicidality in autistic youth.
• 33:15So I just want to close
• 33:16by acknowledging the mic.
• 33:18Doctoral advisor Doctor Lerner as
• 33:20well as Doctor Mcpartlin who's in
• 33:22the room who've been really key in
• 33:25in getting all of this work done
• 33:27and for the great support of the
• 33:29Stony Brook team that was essential
• 33:31in in conducting this research.
• 33:33I also want to thank everybody in my lab,
• 33:35many of which are here and in particular.
• 33:38I did want to thank Doctor Keifer and Dr.
• 33:40Naples,
• 33:41who I know is in the room for their
• 33:43really essential and amazing work
• 33:44on this naturalistic paradigm.
• 33:46And finally,
• 33:47I'll conclude by thanking the
• 33:49funders which you can see there,
• 33:51as well as really all of the
• 33:53participating families who we really
• 33:54could not do any of this work without.
• 33:57So thank you very much for
• 33:58listening and I can take questions,
• 34:00questions
• 34:08for Doctor Gerber.
• 34:12Everything was so clear.
• 34:20Hi. I'm curious if you're defining
• 34:24loneliness as the mismatch between the
• 34:27social motivation and the and what kids
• 34:31are actually getting when when you're
• 34:33looking at the loneliness scores.
• 34:35When we know that social
• 34:36motivation might not change,
• 34:38but what they're getting might change.
• 34:40If there was a difference in.
• 34:44Initial social motivation in
• 34:46autistic and non autistic use,
• 34:48if that makes sense.
• 34:49So the loneliness scores might
• 34:51not be changing because they
• 34:53might have been lower initially.
• 34:55And the and
• 34:57yeah, if that makes sense,
• 34:59yeah. So I think this actually
• 35:01brings up kind of two questions.
• 35:02One is. The relationship between
• 35:05social motivation and loneliness and
• 35:07autism and this kind of gets to the
• 35:09heart of what I'm interested in.
• 35:11This idea that autistic people
• 35:12may not be socially motivated,
• 35:14they may not be interested in interaction,
• 35:16so how could they feel lonely pre
• 35:19pandemic though there's quite a
• 35:20bit of data at this point that
• 35:22suggests that that's not quite true,
• 35:24that they actually do feel a
• 35:26lot of loneliness.
• 35:27Now the other thing they are bringing up,
• 35:28which is kind of a challenge is and
• 35:31everybody I imagine experienced this,
• 35:32who did pre pandemic work.
• 35:34Or during pandemic work,
• 35:36right is we didn't have that
• 35:38information before the pandemic.
• 35:40So we do have some data on these kids,
• 35:42but we don't have their social
• 35:45motivation and loneliness prepandemic.
• 35:46So it would be really interesting to see if,
• 35:49you know,
• 35:50kids who are not socially
• 35:52motivated were totally fine,
• 35:53but we just don't have that.
• 35:54But it's a great question.
• 35:55More
• 35:58questions for Doctor Gerber.
• 36:04Hopefully this is a softball,
• 36:06it's going to be,
• 36:08it's not a super softball,
• 36:09but if you probably can
• 36:10answer just with yes or no.
• 36:12I was wondering if you'd done
• 36:15anything looking at the date,
• 36:17the data over time in a nonlinear fashion.
• 36:19Because I guess when I'm
• 36:21thinking about COVID,
• 36:21I kind of think about it is
• 36:23it was there was a lot of
• 36:24abs and flows of things and
• 36:26I'm wondering if you there's
• 36:27any use to parsing out
• 36:28the data looking at time or?
• 36:31Chronologically in terms of months of
• 36:33the year rather than time and and then
• 36:36also looking at when the lockdowns
• 36:38were and how that affected
• 36:40autistic versus non autistic kids.
• 36:42Yeah, this is this is a great
• 36:45question and I'm grateful to.
• 36:47I practice this in my lab and
• 36:49this question came up so.
• 36:51Always get to practice.
• 36:53It's a great question.
• 36:54We've thought about it.
• 36:56We have looked at some of these
• 36:57things in a long linear fashion,
• 36:59and I figured I'd only had 13 minutes,
• 37:01so I didn't get into it too much.
• 37:03But there is a quadratic
• 37:06relationship with social disruption.
• 37:09Where kind of dips over the
• 37:10summer and comes back up,
• 37:11which is it was just interesting.
• 37:14Loneliness didn't appear to change that much,
• 37:17which I also thought was interesting
• 37:19but wasn't shocking because
• 37:20if you look at the general,
• 37:23if you look at the data that's
• 37:25coming out now on loneliness,
• 37:26there was sort of this initial period
• 37:28where people didn't know what to do and
• 37:30people were feeling trapped and lonely,
• 37:32but people adjusted pretty quickly.
• 37:34And in the end,
• 37:35loneliness remained relatively stable.
• 37:37So we have data from June on.
• 37:40I think it would tell a different
• 37:42story if we had data in April
• 37:45and May in terms of a break,
• 37:48a breaking point when school starts.
• 37:50Also an interesting thing that
• 37:52we haven't quite looked at,
• 37:53but it's a great point.
• 37:54Sorry,
• 37:55I saved time for that last question.
• 37:57Do we have
• 37:58one more question?
• 38:04Hi, first of all great presentation.
• 38:06I wanted to ask if you saw any difference
• 38:09in habituation to the routine between
• 38:11a non autistic and autistic youth.
• 38:15Yeah so the question is
• 38:18about habituation between
• 38:20between groups to their routine.
• 38:23So the short answer here is we can only
• 38:26measure so much and we debated heavily
• 38:28what we should put in to this study.
• 38:30And so we didn't really ask about
• 38:33habituation to change in routine.
• 38:35So in a sense, I think what we're
• 38:37looking at when we look at loneliness
• 38:38and we have some data that I didn't
• 38:41present today on anxiety and
• 38:42depression is kind of a proxy for that.
• 38:45But it's a great question and that's a good
• 38:48lesson learned for designing studies if.
• 38:51The change in routine happened differently
• 38:53and was quicker and perhaps mediate
• 38:56some of of of these relationships,
• 38:58but I'm out of time.
• 39:00So thank you for that.
• 39:02Thank you Dr. Gerber. Nice job.
• 39:07Last but not least we have Doctor Kistagno.
• 39:15Wait, Mike, is it just the next?
• 39:27Perfect. All right, all set.
• 39:31So thank you for this opportunity
• 39:33to share my research Today I'll
• 39:35present research recently published
• 39:36in our image entitled Modeling
• 39:38Brain dynamics and gaze Behavior.
• 39:40Starting point bias and drift rate relate
• 39:43to frontal midline Theta EEG oscillations.
• 39:47In this study we applied.
• 39:49Computational modeling to participants
• 39:51performance on the anti saccade task
• 39:53with eye tracking while collecting
• 39:55high density EEG to investigate the
• 39:57effects of trial by trial Theta dynamics
• 40:00on contingent eye gaze behavior.
• 40:01So I know that was a lot of words
• 40:04and I promise that a lot of them
• 40:06will make sense by the end.
• 40:07Important to start is that a
• 40:09saccade is just an eye movement.
• 40:11So. If you're moving your eyes,
• 40:13what you're looking at that is a saccade.
• 40:15If I point to one side of the room,
• 40:17everyone that looked to that side of the
• 40:19room, that would have been a saccade.
• 40:21Whereas if you didn't look,
• 40:22that would have been an antisychade.
• 40:24You inhibited your natural inclination
• 40:26to look to where I pointed.
• 40:28So that's a task we're dealing with,
• 40:29which I'll get into more in depth,
• 40:32just figured need to get that
• 40:34out of the way early.
• 40:35So why visual, visual attention?
• 40:38I gaze plays a critical role
• 40:40in many human behaviors.
• 40:41What grabs our attention grabs our thoughts
• 40:44from moral judgments to purchasing decisions.
• 40:48Another is in regard to clinical
• 40:50implications.
• 40:51Tension bias is well known play
• 40:52a role in the development and
• 40:54maintenance of anxiety disorders
• 40:56and depressed depressive disorders.
• 40:58A a critical aspect of adaptive
• 41:01goal directed behaviors,
• 41:02appropriate response preparation.
• 41:04This led to our motivating research question.
• 41:08Can we model effortful eye gaze
• 41:11behavior to improve precision
• 41:13when studying intentional biases?
• 41:15Fortunately for the field,
• 41:17there's a decent grasp on a specific
• 41:19neural marker of effortful control.
• 41:22Frontal and central midline Theta
• 41:24oscillations are robust domain general
• 41:27neural marker of cognitive control
• 41:29processes and therefore promising candidate.
• 41:31So what are oscillations?
• 41:33Just really quickly there are
• 41:35two main types of eg analysis.
• 41:37Typically people are familiar
• 41:38with ERP event related potentials,
• 41:40which are an average of a bunch
• 41:43of different waves.
• 41:44One of those waves is Theta,
• 41:45which occurs between roughly 4 and 8 Hertz.
• 41:49There are other frequencies here we're
• 41:52interested in Theta oscillations,
• 41:54and really what this is indicative
• 41:56of is a population of neurons
• 41:57that are firing together.
• 41:59So this is a neural signature that
• 42:02is thought to play important role.
• 42:04It increases in the magnitude
• 42:06in response errors,
• 42:08negative feedback to unexpected
• 42:12events during inhibitory control
• 42:15when resolving different.
• 42:16Competition between different
• 42:18responses and adjusting response
• 42:20strategies to our task demands,
• 42:25as well as following events that are
• 42:28novel or ambiguous after performance.
• 42:30The signals thought to reflect
• 42:31activity in the anterior,
• 42:33at least partially in the anterior
• 42:35singlet cortex and plays a central
• 42:37role in detecting when our
• 42:39expectations are being violated.
• 42:40So what we thought was going to happen,
• 42:42did not happen, is one way to think about it.
• 42:46Depending on the circumstances
• 42:47when this occurs,
• 42:48it can work to recruit.
• 42:57Oh,
• 43:02excuse me.
• 43:30We
• 43:34got it worked that way.
• 43:34You were here. No, wait.
• 43:37Yeah, right there. Yeah, yeah,
• 43:42sure. Is that working for
• 43:46them though? On Zoom. I
• 43:51have a spy. On Zoom
• 43:57we see purpose enter for you.
• 44:01They can okay,
• 44:05so we went through that.
• 44:07So some of the limitations of past
• 44:09studies of visual attention behavior.
• 44:11A button presses one step removed from
• 44:14the true behavior of interest here,
• 44:15which is simple attention
• 44:17or eye gaze behavior.
• 44:19Therefore we apply the drift diffusion
• 44:21model to participants eye gaze behavior.
• 44:24And I will get into what
• 44:25drift diffusion model is.
• 44:26But first we need to cover what the task is.
• 44:28The anti saccade task,
• 44:30which I briefly touched on in
• 44:31the beginning in the sense of
• 44:33that is the behavior of interest
• 44:35during the anti saccade task.
• 44:36It's a fastpaced inhibitory control
• 44:38task strictly driven by participants
• 44:40eye gaze behavior and that's a really
• 44:42important thing to remember here.
• 44:43There are no button presses,
• 44:45it's strictly where the participant
• 44:47is looking on the screen is driving
• 44:50the task paradigm during pro saccade.
• 44:52Participants receive a queue on
• 44:54screen either a white or black
• 44:56fixation cross during the pro
• 44:58saccade is a white fixation cross
• 45:00and that tells them I'll need to
• 45:02look at the upcoming probe.
• 45:07Next they'll see the probe and they will
• 45:09look in that direction hopefully and
• 45:12they'll receive feedback of correct.
• 45:14Now during an anti saccade they
• 45:16will receive a probe that is a black
• 45:20fixation cross indicating to them.
• 45:21I'll need to look away when
• 45:24I see the upcoming queue.
• 45:26When the queue comes,
• 45:27if they are engaging in the task correctly,
• 45:30they should inhibit their response
• 45:31to look at the white box and look
• 45:34away in the opposite direction of
• 45:36the screen of the box and therefore
• 45:39providing a anti saccade response.
• 45:43Now the important thing also
• 45:45to remember here.
• 45:46Apart from it being strictly
• 45:47driven by participants,
• 45:48eye gaze behavior is that it
• 45:50is acute anti saccade cast,
• 45:52which some people would call
• 45:54proactive cognitive control.
• 45:55In this sense, they know what's coming.
• 45:57They know that they're going to
• 45:59have to either inhibit A prepotent
• 46:01response or they're going to have
• 46:03to just provide the response that
• 46:05is their natural inclination,
• 46:06which is which is to look at the
• 46:09white screen in this very dark
• 46:11room on this computer screen now.
• 46:14Briefly,
• 46:14Introduction to a Drift Diffusion model.
• 46:17It's a broadly defined any model
• 46:19as a dynamic system.
• 46:21When presented with a time series,
• 46:22inputs such as reaction time and
• 46:26performance can produce simulation outputs.
• 46:29And drift diffusion models were
• 46:31specifically created in order to
• 46:33relate response times to underlying
• 46:35latent cognitive processes,
• 46:36which is the really important
• 46:38part to understand here is that we
• 46:40feed in the behavior of interest,
• 46:43in this case their sequential
• 46:44behavior on the anti saccade task,
• 46:46the reaction time, their performance.
• 46:49And what is generated is individual
• 46:51estimates of certain parameters.
• 46:53These parameters are latent constructs.
• 46:54They don't actually exist,
• 46:56but they're thought to relate to
• 46:59real world underlying cognitive
• 47:01processes that are a closer step
• 47:04towards what is going on in the
• 47:06brain than simple reaction time,
• 47:08which is an amalgamation of many,
• 47:09many, many cognitive processes.
• 47:12For the drift diffusion model,
• 47:14it parses it between drift rate,
• 47:16which is thought of as information
• 47:19processing.
• 47:19You can think of a drift rate as
• 47:21being an individual's subjective
• 47:23experience of task difficulty.
• 47:25So every individual in this task,
• 47:28once we feed in their behavior,
• 47:30response time and performance,
• 47:32we get an estimate of their
• 47:34specific drift rate during the task.
• 47:36And their drift rate estimate for
• 47:38an individual would be how difficult
• 47:40say they thought the pro saccade
• 47:43or the anti saccade trials were.
• 47:46How efficient they were at processing
• 47:48that and engaging in that task.
• 47:50There's also a threshold separation,
• 47:53which is the boundaries shown on the
• 47:56right there where the red lines are
• 47:59going and meeting in the star forms.
• 48:01That is the decision boundary.
• 48:03So once that boundary is reached,
• 48:04whatever boundary that is,
• 48:06that boundary is a decision that is made.
• 48:09And here the boundary,
• 48:11the top boundary is indicative of.
• 48:14Providing a pro saccade response,
• 48:16where is the bottom boundary
• 48:17is the anti saccade response,
• 48:19so they also have a bias or a starting point.
• 48:23So where in the middle of that?
• 48:26The decision threshold or
• 48:28the threshold separation?
• 48:29Where are they starting?
• 48:30Are they starting in the middle
• 48:32or do they have a bias where
• 48:33they need more information to
• 48:34gather to make one decision,
• 48:36much less to make the alternative decision?
• 48:40And finally, there is also
• 48:41a non decision time.
• 48:43I'm not going to get too much of the
• 48:45non decision time because of the
• 48:46amalgamation of a lot of cognitive
• 48:48processes that aren't related
• 48:49to the decision making process
• 48:51like early orientate orienting,
• 48:54early perceptual encoding and
• 48:55later processes that are non
• 48:58decision related such as the
• 49:00execution of a motor response.
• 49:03But let's walk through what this actually
• 49:05is so you have a better understanding
• 49:08cuz me giving you definitions
• 49:09is probably not going to do it.
• 49:12You have the decision threshold
• 49:14here for the anti saccade task that
• 49:16if the drift rate reaches this top
• 49:19boundary then they are going to
• 49:20produce a pro saccade or decide
• 49:22to produce a pro saccade response.
• 49:24And then you have a bottom
• 49:26decision threshold.
• 49:27If the drift rate reaches this threshold,
• 49:29they provide an anti saccade response.
• 49:32And you have a bias parameter or the
• 49:35starting point is what it's also known
• 49:37as and you can have a drift rate.
• 49:39So here's a blue drift rate
• 49:40indicating a pro saccade response.
• 49:42It's viewed as a noisy process
• 49:44which is beyond the scope of this,
• 49:46but that is why that is a jagged line.
• 49:49You'll often see jagged lines.
• 49:51They might also have a.
• 49:53This is a hypothetical anti saccade
• 49:56decision deciding to provide an
• 49:58anti saccade response so you can
• 50:00have a decision threshold.
• 50:02Like I said, top is a pro psychotic response,
• 50:04bottom is an anti psychotic response.
• 50:07You can also,
• 50:08so you can think about it as someone
• 50:10who has large decision thresholds.
• 50:13This would be an individual
• 50:14where the parameter estimates is
• 50:16larger than average for a group.
• 50:18You could think of them as having a
• 50:21conservative style of decision making,
• 50:23at least on this task.
• 50:24So they need much more evidence
• 50:26to come to any decision.
• 50:27They need a lot of information they
• 50:31are favoring. Accuracy over speed.
• 50:33There could be also people with
• 50:35more of an impulsive style where
• 50:38they favor speed over accuracy.
• 50:40You can imagine now they need
• 50:42much less evidence regardless of
• 50:44what decision they're going to
• 50:45come to to come to a decision.
• 50:49And now the bias parameter as well.
• 50:52It can do a little dance on the where
• 50:55determining where that starting point is.
• 50:57It can be high, it can be low.
• 51:00And altogether, this is hypothetical,
• 51:05several trials of the pro saccade or
• 51:09the anti saccade task for both pro and
• 51:12anti saccade conditions and just for
• 51:14to show what a drift rate where bias
• 51:18is shifted downward would look like.
• 51:20And this might be something to remember
• 51:23for when I talk about the results
• 51:25very shortly you see there's much
• 51:27more information that needs to be.
• 51:29Garnered to come to a prosychod
• 51:33response and alternatively much less
• 51:35information needs to be acquired
• 51:36to come to a antisychod response.
• 51:39This would be an individual with a strong
• 51:41bias towards the antisychod boundary,
• 51:44and you can see how that's different
• 51:46from the threshold separation where
• 51:48they generally for either decision
• 51:50are either conservative or impulsive
• 51:52in their decision making style.
• 51:58Now jumping into the results here,
• 52:01interestingly we found larger
• 52:02drift rate drift rates for
• 52:04the anti psychotic condition,
• 52:06which indicates that there was actually
• 52:08more efficient processing occurring
• 52:10during these high conflict trials,
• 52:11potentially reflecting a burst
• 52:13in frontal midline Theta that's
• 52:15not as strong in the Prosecco
• 52:19condition which I'll get into very shortly.
• 52:23There's also meaningful differences in the.
• 52:27Highest parameter as well.
• 52:30So specifically when cued of an upcoming
• 52:33challenge anti saccade condition,
• 52:35there tended to be a shift downward
• 52:38towards the anti saccade boundary.
• 52:40Therefore less evidence was required
• 52:44to provide that inhibitory response,
• 52:46but much more evidence was needed to
• 52:49incorrectly provide a pro saccade response.
• 52:52I think of this potentially as
• 52:55indicating A compensatory strategy to
• 52:58facilitate fast performance but accurate
• 53:00performance the more during the more
• 53:03difficult anti saccade condition.
• 53:05During the pro saccade condition,
• 53:07on the other hand,
• 53:08there was no there was a more
• 53:09neutral approach shown with the
• 53:11bias parameter estimate where equal
• 53:14amounts of evidence was needed.
• 53:16For either decision.
• 53:17So when they were cued of
• 53:19this upcoming challenge,
• 53:20they tended to have a shift
• 53:22downward in their bias,
• 53:23which gave them a buffer such that
• 53:25they could still respond accurately
• 53:28and quickly is what we are thinking
• 53:31might be underlying these group
• 53:32differences during the task from
• 53:34a drift diffusion framework.
• 53:35Now what about those neural
• 53:38oscillations we're talking about?
• 53:40Here are the head plots.
• 53:41I'm going to Orient you to the
• 53:43grand average in the bottom here.
• 53:45On the left in red is the anti
• 53:47saccade and on the in blue on
• 53:49the right is the pro saccade.
• 53:51You can see there's a pretty routine
• 53:54and reliable neural response to
• 53:56both pro and anti saccade response,
• 53:59but the difference can be shown much.
• 54:03It becomes much more salient in the
• 54:05time series output here where I'll
• 54:07Orient you to the delay period.
• 54:08So this is the period after they're
• 54:10told they're going to need to either
• 54:12provide a pro or anti saccade response
• 54:14to Remember that white or black
• 54:16fixation cross so they know what's
• 54:18coming during that short delay period.
• 54:20Before they see the white probe,
• 54:22there is a stronger burst
• 54:23of frontal midline Theta,
• 54:25remember that is indicating that
• 54:27expectations might be violated.
• 54:29You might need to get the right,
• 54:32get the cavalry to.
• 54:34Help with this upcoming challenge since
• 54:36they were cued that this upcoming challenge,
• 54:39the anti saccade shown in orange
• 54:41there tended to be a larger
• 54:43burst of frontal midline Theta.
• 54:44So what about all that talk of trial by
• 54:47trial changes in frontal midline Theta?
• 54:50So when taking the behavioral neural
• 54:53physiological findings together,
• 54:54the drift drift diffusion model input
• 54:57includes participants trial by trial,
• 54:59reaction time, response,
• 55:01empower or strength of their event,
• 55:03locked Theta neural response
• 55:05during each task queue.
• 55:07So within the model is an estimate
• 55:09of their the specific participants
• 55:12Theta during that response queue.
• 55:16They're in that queue where I
• 55:18showed you between after the queue
• 55:20and prior to receiving the probe.
• 55:23Put differently,
• 55:24we examined the within subject
• 55:26effects of this trial by trial frontal
• 55:28midline Theta on drift rate and bias
• 55:30those two parameters that were found
• 55:32to differ in their performance.
• 55:34And allowing for different levels
• 55:35of difficulty,
• 55:36so pro and anti saccade to
• 55:38exert influence via drift
• 55:40diffusion regression model.
• 55:41This allowed us to directly examine
• 55:44eye gaze behavior and trial by trial
• 55:47changes in frontal midline Theta
• 55:49within an individual model together
• 55:52within subject in a Bayesian space.
• 55:54And this allowed us to to
• 55:57directly examine where these
• 55:59changes in frontal midline Theta.
• 56:01Over the course of tasks has a significant
• 56:04influence on the drift rate and bias.
• 56:09And finally these were the
• 56:11results of the trial by trial
• 56:13effects of frontal midline Theta.
• 56:14Here these are posterior distribution.
• 56:16So I oriented you to zero
• 56:18there with that line.
• 56:20And the important part here is
• 56:21if a posterior distribution in
• 56:22this context passes through zero,
• 56:24then is not a meaningful.
• 56:27Effect here for both pro and anti
• 56:29saccade shown in the blue and the red.
• 56:31You can see there was a positive
• 56:34effect of frontal midline Theta on
• 56:36pro during pro and anti saccade
• 56:38conditions with an individual which
• 56:40shows that which is consistent with
• 56:42those head plots you saw before
• 56:44because there were first the frontal
• 56:46midline Theta during both conditions.
• 56:47Although the time series input did
• 56:49show that they were stronger during
• 56:51the anti saccade condition however.
• 56:54Being probed that there was an upcoming task,
• 56:58a challenge,
• 56:58something to do look at the probe
• 57:01or look away elicited frontal
• 57:03midline Theta and both of those
• 57:06increased individuals processing
• 57:07efficiency during the upcoming demand.
• 57:10Now interestingly the bias parameter here.
• 57:14You can see the prosychot directly
• 57:16passes through zero,
• 57:17so there's no effect of frontal
• 57:18midline Theta within an individual
• 57:20on their prosychot response.
• 57:22So during the prosychot trials,
• 57:23there was no effect of frontal midline Theta.
• 57:26Very interestingly though,
• 57:27there was an effect, a negative effect,
• 57:30on the antisychotic condition which
• 57:32relates to that shift downward
• 57:35in that bias parameter.
• 57:37That shift downward,
• 57:38which I showed in that schematic earlier,
• 57:40is what's going on here.
• 57:42Where?
• 57:43These results indicate that that
• 57:45burst of frontal midline Theta during
• 57:47that anti psychotic condition not
• 57:49only increased processing efficiency
• 57:51via the drift rate but also shifted
• 57:54that bias parameter downward on that.
• 58:00Allowing their starting point
• 58:02bias to be shifted downward.
• 58:03Therefore, they need much more
• 58:05evidence to accumulate to erroneously
• 58:07provide a pro saccade response,
• 58:09but much less information need to
• 58:11accumulate to provide correctly
• 58:13the anti saccade response,
• 58:14if you remember,
• 58:15is that bottom threshold.
• 58:20Finally, we're also interested in
• 58:23potentially showing the utility of using.
• 58:26Computational modeling to
• 58:27decompose task based behavior.
• 58:29So we included reaction time in the
• 58:31first block which was not significant.
• 58:33In the second block we introduced
• 58:35the drift diffusion parameters.
• 58:36Bias was a significant predictor.
• 58:40Drift rate was not in this case,
• 58:41but in subsequent regressions where we
• 58:44weren't interested in showing the utility,
• 58:46but just examining whether drift
• 58:48rate and bias predicted frontal
• 58:49midline Theta during the task.
• 58:51Both of those were predictors with
• 58:54significant predictors without reaction time.
• 58:57In the in the model and the
• 59:00overall variance explained was
• 59:04fairly robust. Finally the take
• 59:08home here increased Theta power was
• 59:11associated with increased processing
• 59:12efficiency and a shift in starting
• 59:15point bias which facilitated accurate
• 59:16and fat but fast responding and finally
• 59:20modeling proactive cognitive control.
• 59:24At the level of eye gaze from a
• 59:26drift eye gaze, behavior from a
• 59:28drift diffusion framework improved
• 59:29our measurement precision,
• 59:32as shown through our regression analyses.
• 59:40And oh, there it is.
• 59:42And for acknowledgments,
• 59:43I'd like to thank Courage Lab and
• 59:45our members and Doctor Crowley,
• 59:47my mentor, as well as my other cowork
• 59:51coauthors on the on the paper,
• 59:53Stefan and Purr, as well as my
• 59:57funding the F32 as well as the T32.
• 59:59And Doctor Block who Co
• 01:00:02runs the T32 with Mike.
• 01:00:03So thank you.
• 01:00:10Thank you. Nice job, Peter.
• 01:00:11Sorry for the technical snafu.
• 01:00:12No worries. We have time
• 01:00:14for one question for Peter.
• 01:00:17Come
• 01:00:23on, there's gotta be a computational model
• 01:00:25and person in the crowd. There's Taylor.
• 01:00:33I wanted to go back to
• 01:00:34this one to show this is.
• 01:00:36I made this slide to show kind of
• 01:00:38what that effect was hypothesized
• 01:00:40for that effect of frontal midline
• 01:00:42Theta on anti sacod conditions,
• 01:00:44what that look like and that is kind of
• 01:00:47what that shift downward would look like.
• 01:00:49If anyone's interested,
• 01:00:50I wanted to go back to it.
• 01:00:51But right now I have a question, Peter.
• 01:00:54So where can we take this research
• 01:00:56studying anxiety for instance?
• 01:00:58Yeah, so I think I've thought a lot about
• 01:01:02using attentional biases to threat.
• 01:01:04And oftentimes we'll use a dot pro task or
• 01:01:08pretty much any kind of task we use really.
• 01:01:11We're inferring where their
• 01:01:13attention is via button presses.
• 01:01:15And I think it'd be it shows
• 01:01:18that we can use the Drift Drift,
• 01:01:19diffusion modeling framework to
• 01:01:22decompose gaze behavior into these
• 01:01:24late and underlying constructs which
• 01:01:27may allow us to better relate to.
• 01:01:31Neural dynamics, whether it be frontal,
• 01:01:33midline, Theta, A joint model as
• 01:01:36seen here can also be applied to FM,
• 01:01:40RI through bold response.
• 01:01:42It doesn't need to be necessarily EE,
• 01:01:45G or Austory dynamics,
• 01:01:47but what's really important with
• 01:01:49this type of modeling is having
• 01:01:52that trial by trial changes and.
• 01:01:54Obviously,
• 01:01:55the temporal specificity of veg
• 01:01:56lends itself very nicely to a
• 01:01:59computational modeling approach
• 01:02:00to something like this because
• 01:02:02of that temporal specificity as
• 01:02:03opposed to a bold response.
• 01:02:04But there are ways to kind of lag
• 01:02:06that so that it matches up with the
• 01:02:09behavior which is kind of interesting.
• 01:02:11So I think using this to study
• 01:02:13attention biases with with eye
• 01:02:15tracking is is something that's
• 01:02:17really cool and in the future.
• 01:02:20Thank you very much.
• 01:02:21Thank you for coming everyone.