Dynamic alpha power modulations and slow negative potentials reflect spatio-temporal attention

Poster No:

2449 

Submission Type:

Abstract Submission 

Authors:

Charline Peylo1,2,3, Carola Romberg-Taylor3, Larissa Behnke1,2,3, Paul Sauseng1,3

Institutions:

1University of Zurich, Zurich, Switzerland, 2Graduate School of Systemic Neurosciences, Planegg-Martinsried, Germany, 3Ludwig Maximilian University, Munich, Germany

First Author:

Charline Peylo  
University of Zurich|Graduate School of Systemic Neurosciences|Ludwig Maximilian University
Zurich, Switzerland|Planegg-Martinsried, Germany|Munich, Germany

Co-Author(s):

Carola Romberg-Taylor  
Ludwig Maximilian University
Munich, Germany
Larissa Behnke  
University of Zurich|Graduate School of Systemic Neurosciences|Ludwig Maximilian University
Zurich, Switzerland|Planegg-Martinsried, Germany|Munich, Germany
Paul Sauseng  
University of Zurich|Ludwig Maximilian University
Zurich, Switzerland|Munich, Germany

Introduction:

Psychophysiological processes such as spatio-temporal top-down attention and its underlying neural signatures typically do not operate in isolation and can thus easily be confounded by secondary processes. Alpha power modulations and slow negative potentials, for example, have previously been associated with anticipatory processes in spatial and temporal top-down attention (e.g., Peylo et al., 2021; Praamstra et al., 2006; Rohenkohl & Nobre, 2011; Sauseng et al., 2005; Zanto et al., 2011), but neural responses triggered by transient stimulus onsets as well as decision- and/or- motor-related processes (both of which are common to most traditional research designs) can interfere with attention-driven activity patterns and our interpretation of such (e.g., Di Russo et al., 2021; Kelly et al., 2006). Here, we investigated alpha power modulations and slow negative potentials as signatures of spatio-temporal attention in a dynamic paradigm that was designed to minimize these potential confounds.

Methods:

Twenty-nine participants performed two parallel tasks while the electroencephalogram (EEG) was recorded. The first part of each trial consisted of a dynamic target detection task, in which participants attended the cued side of a bilateral stimulus rotation and mentally counted how often one of two remembered sample orientations (i.e., the target) was displayed while ignoring the uncued side and non-target orientation. In the second part of each trial, participants performed a delayed match-to-sample task, in which they indicated if the orientation of a probe stimulus matched the orientation of the corresponding sample stimulus (previously either target or non-target). We analyzed whether changes in alpha power and/or slow negative potentials during the dynamic target detection task mirrored the expected shifts of spatio-temporal attention towards task-relevant points in space and time (i.e., onset of the target orientation in the cued hemifield) and whether these dynamics were associated with performance in either of the two tasks.

Results:

In line with our hypothesis, we observed dynamic alpha power decreases and slow negative waves around task-relevant locations and time points (i.e., onset of the target orientation on the cued side of the screen) over posterior electrodes contralateral to the locus of attention. In contrast to static alpha power lateralization, these dynamic signatures significantly correlated with performance in the subsequent delayed match-to-sample task (indicating decreased accuracy for probes of the counting-irrelevant non-target orientation with increasing alpha power reduction and slow wave negativity), suggesting a preferential allocation of attention to task-relevant points in space and time at the cost of reduced resources and impaired performance for information outside the current focus of attention.

Conclusions:

Using a dynamic paradigm to minimize potentially interfering stimulus- and motor-related activity, we were able to reveal subtle yet behaviorally relevant dynamics of alpha power and slow negative potentials that mirrored attentional shifts towards relevant moments in time at relevant locations in space, thereby providing an important contribution to our knowledge about these two signatures of spatio-temporal top-down attention.

Learning and Memory:

Working Memory

Modeling and Analysis Methods:

EEG/MEG Modeling and Analysis 2

Perception, Attention and Motor Behavior:

Attention: Visual 1
Perception: Visual

Keywords:

Cognition
Electroencephaolography (EEG)
Memory
NORMAL HUMAN
Perception
Other - Spatial Attention; Temporal Attention; Alpha Power; Slow Negative Potentials

1|2Indicates the priority used for review

Provide references using author date format

Di Russo et al. (2021), 'Sustained visuospatial attention enhances lateralized anticipatory ERP activity in sensory areas', Brain Structure and Function, vol. 226, pp. 457-470
Kelly et al. (2006), 'Increases in alpha oscillatory power reflect an active retinotopic mechanism for distracter suppression during sustained visuospatial attention', Journal of Neurophysiology, vol. 95, no. 6, pp. 3844-3851
Peylo et al. (2021), 'Cause or consequence? Alpha oscillations in visuospatial attention', Trends in Neurosciences, vol. 44, no. 9, pp. 705-713
Praamstra et al. (2006), 'Neurophysiology of implicit timing in serial choice reaction-time performance'. Journal of Neuroscience, vol. 26, no. 20, pp. 5448-5455
Rohenkohl et al. (2011), 'Alpha oscillations related to anticipatory attention follow temporal expectations', Journal of Neuroscience, vol. 31, no. 40, pp. 14076-14084
Sauseng et al. (2005), 'A shift of visual spatial attention is selectively associated with human EEG alpha activity', European Journal of Neuroscience, vol. 22, no. 11, pp. 2917-2926
Zanto et al. (2011), 'Age-related changes in orienting attention in time', Journal of Neuroscience, vol. 31, no. 35, pp. 12461-12470