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Brain oscillatory activity during motor preparation: effect of directional uncertainty on beta, but not alpha, frequency band.

Tzagarakis C, West S, Pellizzer G - Front Neurosci (2015)

Bottom Line: During cue presentation, the reduction of power of the alpha-band in the occipital lobe showed a brief differentiation of condition: the wider the visual cue, the more the power of the alpha-band decreased.However, during motor preparation, only the power of the beta-band was dependent on directional uncertainty: the less the directional uncertainty, the more the power of the beta-band decreased.In conclusion, the results indicate that the power in the alpha-band is associated briefly with cue size, but is otherwise an undifferentiated indication of neural activation, whereas the power of the beta-band reflects the level of motor preparation.

View Article: PubMed Central - PubMed

Affiliation: Brain Sciences Center, Veterans Affairs Health Care Service Minneapolis, MN, USA ; Department of Neuroscience, University of Minnesota Minneapolis, MN, USA.

ABSTRACT
In time-constraint activities, such as sports, it is advantageous to be prepared to act even before knowing precisely what action will be needed. Here, we studied the relation between neural oscillations during motor preparation and amount of uncertainty about the direction of the upcoming target. Ten right-handed volunteers participated in a cued center-out task. A brief visual cue identified the region of space in which the target would appear. Three cue sizes were used to vary the amount of information about the direction of the upcoming target. The target appeared at a random location within the region indicated by the cue, and the participants moved a joystick-controlled cursor toward it. Time-frequency analyses showed phasic increases of power in low (delta/theta: <7 Hz) and high (gamma: >30 Hz) frequency-bands in relation to the onset of visual stimuli and of the motor response. More importantly in regard to motor preparation, there was a tonic reduction of power in the alpha (8-12 Hz) and beta (14-30 Hz) bands during the period between cue presentation and target onset. During motor preparation, the main source of change of power of the alpha band was localized over the contralateral sensorimotor region and both parietal cortices, whereas for the beta-band the main source was the contralateral sensorimotor region. During cue presentation, the reduction of power of the alpha-band in the occipital lobe showed a brief differentiation of condition: the wider the visual cue, the more the power of the alpha-band decreased. However, during motor preparation, only the power of the beta-band was dependent on directional uncertainty: the less the directional uncertainty, the more the power of the beta-band decreased. In conclusion, the results indicate that the power in the alpha-band is associated briefly with cue size, but is otherwise an undifferentiated indication of neural activation, whereas the power of the beta-band reflects the level of motor preparation.

No MeSH data available.


Time-frequency maps of MEG gradiometers. Data were grouped to simplify the presentation in six groups of sensors (left/right × posterior/middle/anterior), as shown in the center plot of the 2D projection of the 248-MEG sensor array. One gradiometer (empty circle) in the left-posterior (cyan) group was malfunctioning and discarded from the analyses. The time-frequency maps show the change in power from baseline of target-aligned data (t = 0 s). Power was estimated with a 10 ms time resolution and 2.5 Hz frequency resolution. However, color mapping was plotted following contour levels. Average (rectangle) and range (line) of task events are shown on top of the figure (C: cue, T: target; R: response). Different power scales were used for data below and above 60 Hz to improve the visibility of changes in power. Examination of the plots reveals differences in time-course and spatial distribution of different frequency bands.
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Figure 2: Time-frequency maps of MEG gradiometers. Data were grouped to simplify the presentation in six groups of sensors (left/right × posterior/middle/anterior), as shown in the center plot of the 2D projection of the 248-MEG sensor array. One gradiometer (empty circle) in the left-posterior (cyan) group was malfunctioning and discarded from the analyses. The time-frequency maps show the change in power from baseline of target-aligned data (t = 0 s). Power was estimated with a 10 ms time resolution and 2.5 Hz frequency resolution. However, color mapping was plotted following contour levels. Average (rectangle) and range (line) of task events are shown on top of the figure (C: cue, T: target; R: response). Different power scales were used for data below and above 60 Hz to improve the visibility of changes in power. Examination of the plots reveals differences in time-course and spatial distribution of different frequency bands.

Mentions: MEG data were analyzed with custom-made MATLAB (Mathworks Inc., Natick MA) programs using the open-source Fieldtrip toolbox (Oostenveld et al., 2011). One left-posterior gradiometer was malfunctioning and discarded from all analyses (see Figure 2). Signals from reference sensors were used to subtract background noise from the neuromagnetic data using a 4-D-Neuroimaging algorithm implemented in Fieldtrip. In addition, trials contaminated by electronic artifacts (“SQUID jumps”), eye movements, eye blinks, or muscle activity were detected using a data-adaptive threshold and discarded. Cardiac artifacts were extracted using independent component analysis and removed. Finally, the data were detrended and an anti-aliasing low-pass filter was applied before resampling at 256 Hz to reduce the size of the files.


Brain oscillatory activity during motor preparation: effect of directional uncertainty on beta, but not alpha, frequency band.

Tzagarakis C, West S, Pellizzer G - Front Neurosci (2015)

Time-frequency maps of MEG gradiometers. Data were grouped to simplify the presentation in six groups of sensors (left/right × posterior/middle/anterior), as shown in the center plot of the 2D projection of the 248-MEG sensor array. One gradiometer (empty circle) in the left-posterior (cyan) group was malfunctioning and discarded from the analyses. The time-frequency maps show the change in power from baseline of target-aligned data (t = 0 s). Power was estimated with a 10 ms time resolution and 2.5 Hz frequency resolution. However, color mapping was plotted following contour levels. Average (rectangle) and range (line) of task events are shown on top of the figure (C: cue, T: target; R: response). Different power scales were used for data below and above 60 Hz to improve the visibility of changes in power. Examination of the plots reveals differences in time-course and spatial distribution of different frequency bands.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4508519&req=5

Figure 2: Time-frequency maps of MEG gradiometers. Data were grouped to simplify the presentation in six groups of sensors (left/right × posterior/middle/anterior), as shown in the center plot of the 2D projection of the 248-MEG sensor array. One gradiometer (empty circle) in the left-posterior (cyan) group was malfunctioning and discarded from the analyses. The time-frequency maps show the change in power from baseline of target-aligned data (t = 0 s). Power was estimated with a 10 ms time resolution and 2.5 Hz frequency resolution. However, color mapping was plotted following contour levels. Average (rectangle) and range (line) of task events are shown on top of the figure (C: cue, T: target; R: response). Different power scales were used for data below and above 60 Hz to improve the visibility of changes in power. Examination of the plots reveals differences in time-course and spatial distribution of different frequency bands.
Mentions: MEG data were analyzed with custom-made MATLAB (Mathworks Inc., Natick MA) programs using the open-source Fieldtrip toolbox (Oostenveld et al., 2011). One left-posterior gradiometer was malfunctioning and discarded from all analyses (see Figure 2). Signals from reference sensors were used to subtract background noise from the neuromagnetic data using a 4-D-Neuroimaging algorithm implemented in Fieldtrip. In addition, trials contaminated by electronic artifacts (“SQUID jumps”), eye movements, eye blinks, or muscle activity were detected using a data-adaptive threshold and discarded. Cardiac artifacts were extracted using independent component analysis and removed. Finally, the data were detrended and an anti-aliasing low-pass filter was applied before resampling at 256 Hz to reduce the size of the files.

Bottom Line: During cue presentation, the reduction of power of the alpha-band in the occipital lobe showed a brief differentiation of condition: the wider the visual cue, the more the power of the alpha-band decreased.However, during motor preparation, only the power of the beta-band was dependent on directional uncertainty: the less the directional uncertainty, the more the power of the beta-band decreased.In conclusion, the results indicate that the power in the alpha-band is associated briefly with cue size, but is otherwise an undifferentiated indication of neural activation, whereas the power of the beta-band reflects the level of motor preparation.

View Article: PubMed Central - PubMed

Affiliation: Brain Sciences Center, Veterans Affairs Health Care Service Minneapolis, MN, USA ; Department of Neuroscience, University of Minnesota Minneapolis, MN, USA.

ABSTRACT
In time-constraint activities, such as sports, it is advantageous to be prepared to act even before knowing precisely what action will be needed. Here, we studied the relation between neural oscillations during motor preparation and amount of uncertainty about the direction of the upcoming target. Ten right-handed volunteers participated in a cued center-out task. A brief visual cue identified the region of space in which the target would appear. Three cue sizes were used to vary the amount of information about the direction of the upcoming target. The target appeared at a random location within the region indicated by the cue, and the participants moved a joystick-controlled cursor toward it. Time-frequency analyses showed phasic increases of power in low (delta/theta: <7 Hz) and high (gamma: >30 Hz) frequency-bands in relation to the onset of visual stimuli and of the motor response. More importantly in regard to motor preparation, there was a tonic reduction of power in the alpha (8-12 Hz) and beta (14-30 Hz) bands during the period between cue presentation and target onset. During motor preparation, the main source of change of power of the alpha band was localized over the contralateral sensorimotor region and both parietal cortices, whereas for the beta-band the main source was the contralateral sensorimotor region. During cue presentation, the reduction of power of the alpha-band in the occipital lobe showed a brief differentiation of condition: the wider the visual cue, the more the power of the alpha-band decreased. However, during motor preparation, only the power of the beta-band was dependent on directional uncertainty: the less the directional uncertainty, the more the power of the beta-band decreased. In conclusion, the results indicate that the power in the alpha-band is associated briefly with cue size, but is otherwise an undifferentiated indication of neural activation, whereas the power of the beta-band reflects the level of motor preparation.

No MeSH data available.