Integrated View of the Cognitive, Cerebral and Cardiac Systems

During an Inhibition Task

C. De Faria

, M. Causse

, B. Valéry

and C. T. Albinet

Laboratoire Sciences de la Cognition, Technologie, Ergonomie (SCoTE), INU Champollion, Albi, France

Institut Supérieur de l’Aéronautique et de l’Espace (ISAE-SUPAERO), Université Fédérale de Toulouse, Toulouse, France

Keywords: Flanker Task, Go/No-Go Task, Cardiac Pre-Ejection Period, Functional NIRS.

Abstract: This study examined the concomitant variations of cardiac (re)activity (pre-ejection period: PEP) and meta-

bolic brain activity (functional near infrared spectroscopy) during a cognitive task in young adults. Variants

of a flanker task involved different levels of inhibition control using a within-subject design and implied

neutral, congruent and incongruent conditions as well as conditions requiring a response (Go) or no response

(No-Go). Preliminary results showed that behavioral performance was significantly decreased when the re-

quired level of inhibitory control increased. PEP reactivity (the difference between PEP values during the task

and PEP values during the resting period) was significantly lower than 0 only during the first minute of each

experimental task condition (lasting about 4.5 minutes), going back to baseline level afterward. PEP reactivity

was most important during the most challenging Flanker Go/No-Go block. As a conclusion, PEP reactivity

was shown to be sensitive to different levels of inhibitory control requirement and to be a short lasting phe-

nomenon, demonstrating a possible rapid dynamic adaptation of the cardiac activity to task constraints.

1 INTRODUCTION

Maintaining optimal behavioral performance in

dynamic, complex and stressful situations is a

constant challenge. To better understand performance

fluctuations and prevent accidents, it is important to

have an integrated view of the cognitive, cerebral and

cardiac systems that control behavior and

physiological activity. However, these systems are

traditionally studied separately despite their strong

interdependence. Yet, a better understanding of the

fundamental mechanisms of the integrated

functioning of the central and peripheral nervous

system should ultimately allow the development of

new tools for promoting maximum cognitive

performance and safety in natural situations, such as

in civil or military aircraft.

Regarding the cognitive system, a key function

that allows adaptive behaviors and flexibility is

inhibition. It sustains the ability to stop, avoid or

ignore automatic, dominant or inappropriate

responses in certain situations and to focus attention

https://orcid.org/0000-0002-0601-2518

https://orcid.org/0000-0003-2642-0516

https://orcid.org/0000-0001-7743-4948

on relevant information (Miyake et al., 2000).

Behavioral paradigms allow to examine inhibition

ability such as in the Flanker task (Eriksen & Eriksen,

1974) or the Go/No-Go task (Heil et al., 2000).

Regarding the cerebral system, it is well known that

specific brain networks are activated in order to

support the processing of information during complex

tasks. In particular when tasks involve inhibition,

activated brain regions have notably been located in

the cingulate, prefrontal, and parietal cortices

(Collette et al. 2006). A technique for studying brain

activity is functional near infrared spectroscopy

(fNIRS). It makes it possible to noninvasively

monitor tissue oxygenation and hemodynamics of the

brain, particularly by monitoring the variations of

concentration in oxyhemoglobin and

deoxyhemoglobin. This brain imaging technique has

shown its interest in the evaluation of cerebral

metabolic activity, in particular according to

cognitive load in specific cortical regions (Fishburn

et al., 2014). Finally, regarding the cardiovascular

system, heart activity has been shown to adapt to

De Faria, C., Causse, M., Valéry, B. and Albinet, C.

Integrated View of the Cognitive, Cerebral and Cardiac Systems During an Inhibition Task.

DOI: 10.5220/0011946900003622

In Proceedings of the 1st International Conference on Cognitive Aircraft Systems (ICCAS 2022), pages 15-19

ISBN: 978-989-758-657-6

 2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

levels of complexity of a cognitive task, presumably

in order to support behavioral performance (Richter

et al., 2008). Cardiac activity is known to be

modulated by two branches of the autonomic nervous

system (ANS): the parasympathetic branch has an

inhibitory influence (decreases heart rate), while the

sympathetic branch has an excitatory influence

(increases heart rate) (Levy, 1990). Sympathetic

activity can be accurately evaluated by calculating the

cardiac pre-ejection period (PEP), which corresponds

to the time interval between the onset of ventricular

depolarization and the opening of the aortic valve

(Berntson et al., 1994). While still relatively new in

the field of cognitive neuroscience, PEP, as a marker

of the autonomic nervous system, has already been

used in studies on mental effort, where it was shown

that an increase in task difficulty resulted in a PEP

decrease (Richter et al., 2008; Silvestrini & Gendolla,

2013).

These three systems are thus essential to the

adaptive capacities of the individual to face the

demands of the environment. The link between

inhibition and the cardiovascular system (Kuipers et

al., 2016) and the link between inhibition and the

cerebral system (Herrmann et al., 2005) have been

studied in the past, but very few studies have

examined the three systems altogether. Our

understanding of their interactions or their integration

into a functional system is therefore very limited. The

aims of the present study are 1) to systematically

examine the way these three systems react to a

challenging task involving different levels of

inhibitory control and 2) to examine whether they are

functionally integrated to manage behavior

adaptation.

2 METHODS

2.1 Participants

Thirty young adults (M

age

= 20.23 ± 2.36; 15 females)

participated in the study and received a compensation

of 10€. They reported no neurological or

cardiovascular disorders. All participants had normal

or corrected vision. They all gave their written

consent at the beginning of the study, which was

approved by the local ethics committee (IRB - N°

00011835-2021-0928-418).

2.2 Measures

2.2.1 Behavioral Measures from the

Modified Flanker Task

The behavioral task is a modified version of the

Eriksen Flanker task (Eriksen & Eriksen, 1974; Heil

et al., 2000) involving neutral, congruent and

incongruent conditions as well as conditions

requiring a response (Go) or requiring no response

(No-Go). The modified Flanker task was presented on

a computer screen and the participant responded by

pressing one of the two keys on a response box. The

task consisted in responding as quickly and precisely

as possible to a central stimulus, the target, by

indicating the direction of the arrow (< or >) while

ignoring stimuli placed on either side of the target (>>

or << for the congruent and incongruent conditions,

or □□ for the neutral condition). The task was

organized around three experimental blocks

following training blocks. A first block, the “neutral

block”, involving only neutral trials (e.g., □□<□□)

corresponded to a choice reaction time task, involving

no or very little executive control. A second block,

the “flanker block”, corresponded to the classical

Flanker task with half congruent trials (e.g., <<<<<)

and half incongruent trials (e.g., <<><<). This design

allowed to assess interference management ability

(inhibition of irrelevant information) by comparing

performance on incongruent trials with that of

congruent trials. A third block, the “flanker no-go

block”, corresponded to the modified flanker task

with additional Go trials (70%) and No-Go trials

(30%) depending on the nature of a preparatory

signal. Each trial was preceded by a preparatory

signal (-----), which could be either of the same color

as the following target (Go trial) or of a different color

(No-Go trial). This allowed to evaluate the

interference management ability, but also the

response inhibition ability during No-Go trials

requiring to stop (inhibit) the response normally

expected. Thus, these three blocks differed in the

amount of inhibitory control necessary for their

successful execution. Each block lasted

approximately 4 minutes 30 seconds and was

repeated twice. The order of presentation of the

blocks was counterbalanced between the participants.

A 3-minute rest period was allowed between two

blocks to ensure a return to the baseline level of

cardiac activity (Czarnek et al., 2021). The dependent

variables were percentage of correct responses and

response time (RT) in ms for correct responses.

ICCAS 2022 - International Conference on Cognitive Aircraft Systems

2.2.2 Cardiovascular Measures

The measurement of cardiac activity was carried out

using the Biopac MP160 system at an acquisition

frequency of 2000 Hz. Once the training was finished,

the electrocardiogram (ECG) and impedance

cardiogram (ICG) electrodes were placed on neck and

torso of the participant. Blood pressure (BP)

measurements (Omron Carescape V100) were also

recorded during each rest period in order to monitor

BP evolution for the interpretation of ECG/ICG

signals (Sherwood et al., 1990). The data collected

were pre-processed on Matlab for ECG/ICG

measurements using an in-house tool. PEP was

calculated as the time interval between R-onset and

B-point (Sherwood et al., 1990). R-onset is defined as

the lowest deflection before R peak on the ECG

signal. R-peaks were found using a threshold peak

detection algorithm and visually inspected. The first

derivative of the ICG signal was computed and the

resulting dZ/dt signal was averaged over 1 minute

epochs. B-point is located based on the RZ interval

(Lozano et al., 2007). Resting PEP was calculated

over the 3 minute rest period. To examine the

dynamic of the cardiac activity during task blocks,

mean PEP in ms was calculated on 4 successive

windows of 1 minute. Dependent variables are mean

PEP in ms and PEP reactivity in ms (task PEP minus

resting PEP).

2.2.3 Cerebral Activity Measures

Cerebral hemodynamics was monitored by near

infrared spectroscopy using NIRScout system. A 16

sources and 14 detectors mapping was used, covering

the orbitofrontal cortex, the dorsolateral prefrontal

cortex, the inferior frontal gyrus, the supplementary

and pre-motor area and parts of the parietal cortex.

Eight short-channels were also used to remove

systemic physiological activity. fNIRS data was

processed using the BrainAnalyzIR toolbox (Santosa

et al., 2018). First, the raw data signal was converted

into optical density, then using the modified Beer-

Lambert Law, optical density data was converted into

oxyhemoglobin (HbO

) and deoxyhemoglobin (HHb)

concentrations. Then, a general linear model was used

to process the data, using the autoregressive

iteratively reweighted least squares (AR-IRLS)

model, and using the short-channels data as

regressors following the procedure recommended by

Santosa et al. (2020). Dependent variables were beta

values for HbO

and HHb.

Behavioral, ECG, ICG and NIRS data were

synchronously recorded throughout the experiment to

examine their concurrent evolution.

3 RESULTS

Data analysis is still ongoing at the moment of

submission of this abstract and thus not all results can

be presented here. Only PEP and behavioral results

will be presented and discussed.

3.1 Flanker Task Results

Overall, the percentage of correct responses was

significantly greater in the neutral block (M = 99.52

± 0.73) than in the flanker block (M = 98.07 ± 1.82),

which was higher than in the flanker no-go block (M

= 96.97 ± 1.83). Similarly, overall, RT significantly

differed between the three blocks. RT were lower for

the neutral block (M = 400.32 ± 58.24) comparing to

the flanker block (M = 474.16 ± 69.18) and the

flanker no-go block (M = 505.76 ± 82.82).

In the flanker block, mean RT of congruent trials

(M = 413.11 ± 45.94) was significantly lower than

mean RT of incongruent trials (M = 540.60 ± 97.36).

Also, the percentage of correct responses for

congruent trials (M = 99.65 ± 1.34) was significantly

higher than the one for incongruent trials (M = 92.63

± 7.13). Similarly, in the flanker no-go block, mean

RT of congruent trials (M = 440.95 ± 58.83) was

significantly lower than the one of incongruent trials

(M = 571.59 ± 120.96). Also, the percentage of

correct responses for congruent trials (M = 99.49 ±

1.95) was significantly higher than the one for

incongruent trials (M = 93.33 ± 8.01). Moreover, the

percentage of correct responses for Go trials, the

percentage of correctly answered trials, (M = 94.41

±6.56) was significantly higher than the one for No-

Go trials, percentage of correctly not answered trials,

(M = 88.61 ± 13.55).

3.2 PEP Results

For each task block, mean PEP of the first 1-minute

window was significantly lower than mean PEP for

the 3 other windows, which did not differ each other.

PEP was thus shorter during the first minute of the

task and then rapidly went back to baseline value and

stabilized at this level. Mean PEP during each resting

block varied from 113 ms to 115 ms and mean PEP

during each task block varied from 108 ms to 114 ms.

PEP reactivity calculated for the first 1-minute

window of each block was significantly different

from 0, indicating that task PEP was systematically

lower than resting PEP during the first minute of each

task. After that, PEP reactivity was not different from

0, except for w3 and w4 of the flanker block which

were significantly higher than 0. Comparison of the

Integrated View of the Cognitive, Cerebral and Cardiac Systems During an Inhibition Task

PEP reactivity of the first 1-minute window for each

block showed that while PEP reactivity for the flanker

No-Go block was significantly lower than the one for

the flanker block, PEP reactivity did not significantly

differ between the flanker No-Go block and the

neutral block or between the neutral block and the

flanker block.

Figure 1: PEP reactivity (in ms) for each block and each 1-

min window (w1, w2, w3 and w4) with standard error.

Larger negative PEP reactivity score reflects greater sym-

pathetic activation.

4 DISCUSSION

The preliminary results show that cognitive

performance decreased with the increase of the

amount of required inhibitory control in the task and

that PEP reactivity was significantly lower than 0 for

all block conditions, but only during the first minute.

These results partly agree with past research but may

highlight the rapid dynamic adaptation of the cardiac

activity to task constraints. The flanker no-go block,

which involves two kinds of inhibition (inhibition of

irrelevant information and response inhibition),

showed the most important PEP reactivity. This may

reflect that the increase of inhibitory control required

by the task generated an increase of sympathetic

activity to sustain effort and cognitive performance.

However, contrary to what was expected, this effect

on PEP reactivity was not linear, as the flanker block

had the lowest PEP reactivity. The next step is to

analyze the cerebral hemodynamic data as a function

of required inhibitory control and ultimately to

examine whether the variations in cardiac reactivity

and cerebral activity during the cognitive tasks are

functionally related and related to behavioral

performance. If they were actually functionally

connected, the integration of these dynamical cardiac

and cerebral markers into an online control system

could be used to detect and alert for performance and

attention fluctuations in pilot activity.

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Integrated View of the Cognitive, Cerebral and Cardiac Systems During an Inhibition Task