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Alpha band oscillations track temporal orienting of attention

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AbstractIntroduction: Recent investigations using field-potential recordings in visual and auditory cortices have shown that oscillatory activity in neuronal ensembles become entrained to the timing of rhythmically presented stimuli according to their modality and location (Lakatos, Chen et al. 2007; Lakatos, Karmos et al. 2008; Lakatos, O'Connell et al. 2009). In spite of the evidence showing the role of brain oscillations on forming predictions about forthcoming sensory events (for a review (Engel, Fries et al. 2001), little is known about the role of such oscillations in the temporal orienting of attention (Nobre 2001; Coull and Nobre 2008). To test the effect of temporal orienting of attention on early perceptual processing, motor selection, and anticipatory low frequency oscillation (alpha waves), we analysed EEG data from healthy adults participants who were performing a visual perceptual discrimination task of targets preceded by rhythmic spatio-temporal cues. Methods: EEG was recorded continuously from 30 healthy, right-handed participants [mean age, 23.9 years (SD, 4.9 years); range, 19–32 years; 9 males], using a 34 Ag/AgCl electrodes at 1000Hz (AFZ ground, right mastoid reference) in an electrically shielded room. The task consisted of rhythmic stimuli that cued participants to the time and location that a subsequent target stimulus would occur after an occlusion (Fig. 1). At the beginning of each trial, a stimulus (ball - diameter:1.0°) appeared on the upper (50%) or lower (50%) left side of the screen and moved across the screen in a diagonal spatial trajectory of seven steps (200 ms for each step). Temporal orienting was induced by manipulating the SOA of each stimuli in three different conditions: fast (400 ms), slow (800 ms) and neutral, where the SOA within a trial was unpredictable, and varied randomly between 300-900 ms. Upon reaching an “occluder”, the ball disappeared for 600 (short occlusion) or 1400ms (long occlusion). When it reappeared on the right-hand side of the occluder, it contained an upright or tilted cross (200 ms, for which participants were required to discriminate the target, using a button-press response with either their right or left hand accordingly. The time-frequency analysis was performed in unfiltered continuous data, epoched from -700 to 1800 ms relative to the beginning of the occlusion period. Data from 12 participants had to be excluded from the analysis due to excessive artifacts in the EEG recordings or poor behavioural performance (accuracy < 60%). A multitaper time–frequency transformation was applied to all electrodes in each trial. This transformation produced an estimation of oscillatory power for each time sample and frequencies between 4 and 20 Hz. Alpha power (8 to 14 Hz) values were extracted from the epochs and submitted to a repeated-measures. All frequency analysis was done using Fieldtrip package ("http://www.ru.nl/fcdonders/fieldtrip/":http://www.ru.nl/fcdonders/fieldtrip/) for MATLAB (MatWorks). Results: To test the effect of reorienting of attention in time we analyzed alpha band oscillations during the long occlusion period. In this way we can observed the reorienting effect in the invalid (fast) trials, when participants have to shift their attention to the long occlusion given that the target did not appear after the expected cued (short) interval. This result reveals an alpha desynchronization preceding the expected target (blue dashed line). When comparing these oscillations within the same period for the slow (valid) rhythm, we observed that this desynchronization in alpha is only present when preceding by a fast, but not slow, rhythm [F(1,17) = 3.85; p = 0.029]. As can be observed in Figure 2, in the valid condition (slow rhythm) there is also a desynchronization of alpha preceding the cued late target. However, if we compare the alpha oscillations preceding the appearance of the later presented target for the valid and invalid temporal cues, no significant difference is observed [F(1,17) = 0.31; p = 0.905]. Conclusion: Our findings support the hypothesis that temporal orienting can also modulate brain oscillations, specifically in the alpha range. Importantly, we showed that in the invalid (fast) condition, in which participants were prepared for a target presentation after a short occlusion, there was also a preparation for the presentation of the later target. This indicates that participants were able to reorient their attention to the second interval given that the target fail to appear after the short (expected) occlusion. References: Coull, J. and A. Nobre (2008). "Dissociating explicit timing from temporal expectation with fMRI." Current Opinion in Neurobiology 18(2): 137-44.Engel, A. K., P. Fries, et al. (2001). "Dynamic predictions: oscillations and synchrony in top-down processing." Nature Reviews Neuroscience 2(10): 704-16.Lakatos, P., C. M. Chen, et al. (2007). "Neuronal oscillations and multisensory interaction in primary auditory cortex." Neuron 53(2): 279-92.Lakatos, P., G. Karmos, et al. (2008). "Entrainment of Neuronal Oscillations as a Mechanism of Attentional Selection." Science 320(5872): 110-113.Lakatos, P., M. N. O'Connell, et al. (2009). "The leading sense: supramodal control of neurophysiological context by attention." Neuron 64(3): 419-30.Nobre, A. C. (2001). "Orienting attention to instants in time." Neuropsychologia 39(12): 1317-28.
Springer Science and Business Media LLC
Title: Alpha band oscillations track temporal orienting of attention
Description:
AbstractIntroduction: Recent investigations using field-potential recordings in visual and auditory cortices have shown that oscillatory activity in neuronal ensembles become entrained to the timing of rhythmically presented stimuli according to their modality and location (Lakatos, Chen et al.
2007; Lakatos, Karmos et al.
2008; Lakatos, O'Connell et al.
2009).
In spite of the evidence showing the role of brain oscillations on forming predictions about forthcoming sensory events (for a review (Engel, Fries et al.
2001), little is known about the role of such oscillations in the temporal orienting of attention (Nobre 2001; Coull and Nobre 2008).
To test the effect of temporal orienting of attention on early perceptual processing, motor selection, and anticipatory low frequency oscillation (alpha waves), we analysed EEG data from healthy adults participants who were performing a visual perceptual discrimination task of targets preceded by rhythmic spatio-temporal cues.
Methods: EEG was recorded continuously from 30 healthy, right-handed participants [mean age, 23.
9 years (SD, 4.
9 years); range, 19–32 years; 9 males], using a 34 Ag/AgCl electrodes at 1000Hz (AFZ ground, right mastoid reference) in an electrically shielded room.
The task consisted of rhythmic stimuli that cued participants to the time and location that a subsequent target stimulus would occur after an occlusion (Fig.
1).
At the beginning of each trial, a stimulus (ball - diameter:1.
0°) appeared on the upper (50%) or lower (50%) left side of the screen and moved across the screen in a diagonal spatial trajectory of seven steps (200 ms for each step).
Temporal orienting was induced by manipulating the SOA of each stimuli in three different conditions: fast (400 ms), slow (800 ms) and neutral, where the SOA within a trial was unpredictable, and varied randomly between 300-900 ms.
Upon reaching an “occluder”, the ball disappeared for 600 (short occlusion) or 1400ms (long occlusion).
When it reappeared on the right-hand side of the occluder, it contained an upright or tilted cross (200 ms, for which participants were required to discriminate the target, using a button-press response with either their right or left hand accordingly.
The time-frequency analysis was performed in unfiltered continuous data, epoched from -700 to 1800 ms relative to the beginning of the occlusion period.
Data from 12 participants had to be excluded from the analysis due to excessive artifacts in the EEG recordings or poor behavioural performance (accuracy < 60%).
A multitaper time–frequency transformation was applied to all electrodes in each trial.
This transformation produced an estimation of oscillatory power for each time sample and frequencies between 4 and 20 Hz.
Alpha power (8 to 14 Hz) values were extracted from the epochs and submitted to a repeated-measures.
All frequency analysis was done using Fieldtrip package ("http://www.
ru.
nl/fcdonders/fieldtrip/":http://www.
ru.
nl/fcdonders/fieldtrip/) for MATLAB (MatWorks).
Results: To test the effect of reorienting of attention in time we analyzed alpha band oscillations during the long occlusion period.
In this way we can observed the reorienting effect in the invalid (fast) trials, when participants have to shift their attention to the long occlusion given that the target did not appear after the expected cued (short) interval.
This result reveals an alpha desynchronization preceding the expected target (blue dashed line).
When comparing these oscillations within the same period for the slow (valid) rhythm, we observed that this desynchronization in alpha is only present when preceding by a fast, but not slow, rhythm [F(1,17) = 3.
85; p = 0.
029].
As can be observed in Figure 2, in the valid condition (slow rhythm) there is also a desynchronization of alpha preceding the cued late target.
However, if we compare the alpha oscillations preceding the appearance of the later presented target for the valid and invalid temporal cues, no significant difference is observed [F(1,17) = 0.
31; p = 0.
905].
Conclusion: Our findings support the hypothesis that temporal orienting can also modulate brain oscillations, specifically in the alpha range.
Importantly, we showed that in the invalid (fast) condition, in which participants were prepared for a target presentation after a short occlusion, there was also a preparation for the presentation of the later target.
This indicates that participants were able to reorient their attention to the second interval given that the target fail to appear after the short (expected) occlusion.
References: Coull, J.
and A.
Nobre (2008).
"Dissociating explicit timing from temporal expectation with fMRI.
" Current Opinion in Neurobiology 18(2): 137-44.
Engel, A.
K.
, P.
Fries, et al.
(2001).
"Dynamic predictions: oscillations and synchrony in top-down processing.
" Nature Reviews Neuroscience 2(10): 704-16.
Lakatos, P.
, C.
M.
Chen, et al.
(2007).
"Neuronal oscillations and multisensory interaction in primary auditory cortex.
" Neuron 53(2): 279-92.
Lakatos, P.
, G.
Karmos, et al.
(2008).
"Entrainment of Neuronal Oscillations as a Mechanism of Attentional Selection.
" Science 320(5872): 110-113.
Lakatos, P.
, M.
N.
O'Connell, et al.
(2009).
"The leading sense: supramodal control of neurophysiological context by attention.
" Neuron 64(3): 419-30.
Nobre, A.
C.
(2001).
"Orienting attention to instants in time.
" Neuropsychologia 39(12): 1317-28.

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