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61 Robustness of Attention Networks Across Multiple Sessions: Behavioral and ERP Findings

Published online by Cambridge University Press:  21 December 2023

Catherine Tocci*
Affiliation:
University of Florida, Gainesville, Florida, USA.
Elena Polejaeva
Affiliation:
Veterans Administration San Diego Healthcare System, San Diego, California, USA.
Andreas Keil
Affiliation:
University of Florida, Gainesville, Florida, USA.
Sarah Long
Affiliation:
University of Florida, Gainesville, Florida, USA.
Jennifer Ly
Affiliation:
University of Florida, Gainesville, Florida, USA.
Alexia Brown
Affiliation:
University of Florida, Gainesville, Florida, USA.
Christopher N Sozda
Affiliation:
Malcolm Randall Veterans Administration Medical Center, Gainesville, Florida, USA
William M Perlstein
Affiliation:
University of Florida, Gainesville, Florida, USA.
*
Correspondence: Catherine Tocci, University of Florida, Ctocci1@ufl.edu
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Abstract

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Objective:

Attention is the backbone of cognitive systems and is requisite for many cognitive processes vital to everyday functioning, including memory, problem solving, and the cognitive control of behavior. Attention is commonly impaired following traumatic brain injury and is a critical focus of rehabilitation efforts. The development of reliable methods to assess rehabilitation-related changes are paramount. The Attention Network Test (ANT) has been used previously to identify 3 independent, yet interactive attention networks—alerting, orienting, and executive control (EC). We examined the behavioral and neurophysiological robustness and temporal stability of these networks across multiple sessions to assess the ANT’s potential utility as an effective measure of change during attention rehabilitative interventions.

Participants and Methods:

15 healthy young adults completed 4 sessions of the ANT (1 session/7-day period). ANT networks were assessed within the task by contrasting opposing stimulus conditions: cued vs. non-cued trials probed alerting, valid vs. invalid spatial cues probed orienting, and congruent vs. incongruent targets probed EC. Differences in median correct-trial reaction times (RTs) and error rates (ERs) between the condition pairs were assessed to determine attention network scores; robustness of networks effects, as determined by one-sample t-tests at each session, against a mean of 0, determining the presence of significant network effects at each session. Sixty-four-channel electroencephalography (EEG) data were acquired concurrently and processed using Matlab to create condition-related event-related potentials (ERPs)—particularly the cue- and probe-related P1, N1, and P3 deflection amplitudes, measured by using signed-area calculation in regions of interest (ROIs) determined by observation of spherical-spline voltages. This enabled us to examine the robustness of cue- and probe-attention-network ERPs.

Results:

All three attention networks showed robust effects. However, only the EC RT and ER network scores remained significantly robust [t(14)s>13.9,ps<.001] across all sessions, indicating that EC is robust in the face of repeated exposure. Session 1 showed the greatest EC-RT robustness effect which became smaller during the subsequent sessions per ANOVAs on Session x Congruency [F(3,42)=10.21,p<.0001], reflecting persistence despite practice effects. RT robustness of the other networks varied across sessions. Alerting and EC ERs were similarly robust across all 4 sessions, but were more variable for the orienting network. ERP results: The cue-locked P1-orienting (valid vs. invalid) was generally larger to valid- than invalid-cues, but the robustness across sessions was variable (significant in only sessions 1 and 4 [t(14)s>2.13,ps<.04], as reflected in a significant main effect of session [p=.0042]. Next, target-locked EC P3s were generally smaller to congruent than incongruent targets [F(1,14)=9.40,p=.0084], showing robust effects only in sessions 3 and 4 [ps<.005].

Conclusions:

The EC network RT and ER scores were consistently robust across all sessions, suggesting that this network may be less vulnerable to practice effects across session than the other networks and may be the most reliable probe of attentional rehabilitation. ERP measures were more variable across attention networks with respect to robustness. Behavioral measures of EC-network may be most reliable for assessing progress related to attentional-rehabilitation efforts.

Type
Poster Session 05: Neuroimaging | Neurophysiology | Neurostimulation | Technology | Cross Cultural | Multiculturalism | Career Development
Copyright
Copyright © INS. Published by Cambridge University Press, 2023