Resting-state cortical connectivity predicts motor skill acquisition

“Next, EEG data underwent an Infomax ICA decomposition (EEGLAB (Delorme and Makeig, 2004)).”

“Measures of connectivity, as compared to assessments of focal brain regions, have an improved ability to represent complexity in human cortical processing and as a result have a stronger relationship with many types of behavior (Bullmore and Sporns, 2009).”

“Combined EEG and fMRI studies have reported that specific combinations of EEG rhythms correspond with low frequency activity of specific resting-state networks (Mantini et al., 2007).”

“Recent resting-state studies have provided new inroads for measuring differences in brain function in relation to behavior across individual subjects (Deco et al., 2011).”

“Of the remaining components, amplitude topography, frequency spectra, and component time series were inspected to identify eye blinks, eye movements, and heart rhythms (Delorme et al., 2007), and were removed.”

“In the present study, the N-way toolbox (Andersson and Bro, 2000) was used to generate PLS models of resting EEG coherence predicting % Improvement across practice.”

“Third, PLSmodeling is useful for defining relationships between brain function and behavior (Krishnan et al., 2011; McIntosh and Lobaugh, 2004), for example, decoding behavioral output with high accuracy using fewer variables than with other approaches (Chao et al.”

“Organization of brain networks at rest has also been correlated with subsequent behavioral performance (Hampson et al., 2006; Tambini et al., 2010).”

“Markers of brain function at rest are influenced by experience (Lewis et al., 2009) and reflect the functional organization of brain networks that are selectively engagedduring behavioral tasks.”

“In various studies of motor function using EEG coherence, changes in brain connectivity have been observed in the β (20–30 Hz) frequency range (Deeny et al., 2009; Pfurtscheller et al., 1996; Tropini et al., 2011).”

“Keywords EEG; motor learning; coherence; PLS Introduction Individuals demonstrate significant variability in motor learning (Ackerman, 1987; King et al., 2012).”

“As in previous studies of motor learning (Hardwick et al., 2013), the current results show motor skill acquisition is linked to activity in primary motor cortex, parietal cortex, and frontal-premotor areas.”

“Organization of brain networks at rest has also been correlated with subsequent behavioral performance (Hampson et al., 2006; Tambini et al., 2010).”

“2.4 Coherence and Power EEG coherence was used to estimate functional connectivity (Murias et al., 2007; Nunez and Srinivasan, 2006; Srinivasan et al., 2007).”

“Due to the central role of the contralateral primary motor cortex in movement execution and motor learning (Halsband and Lange, 2006; Hardwick et al., 2013), EEG coherence with a seed region overlying left hand motor area (M1)was used as the primarymetric of interest.”

“The ability to predict an individual’s learning skill could have utility in a number of settings, including clinical (Stinear, 2010).”

“Average absolute power at each electrode and coherence between each pair of electrodes for β (20–30 Hz) frequencies, a range associated with motor system function (Deeny et al., 2009; Roopun et al., 2006).”

“Third, PLS modeling is useful for defining relationships between brain function and behavior (Krishnan et al., 2011; McIntosh and Lobaugh, 2004), for example, decoding behavioral output with high accuracy using fewer variables than with other approaches (Chao et al., 2010).”

“PLS methods have been used to identify patterns of neural activation related to changes in task content (McIntosh et al., 2004), and have been found useful for defining relationships between measures of brain function and performance in spatial attention tasks (Krishnan et al.”

“However, there is evidence that such a transform could erroneously distort coherence across distances in the range of left M1 to left PM and Pr regions (Srinivasan et al., 1998).”

“Direct orthogonal signal correction (Westerhuis et al., 2001) was then used to remove the component of the predicting data (coherence) that was most orthogonal to the behavioral data (% Improvement).”

“The favorable comparison of a PLS approach suggestswhole-brain approaches, including graph-theoretical network analysis (Langer et al., 2011) and independent component analysis (Lin et al.”

“Alternatively, and more akin to fMRI studies (Baldassarre et al., 2012; Wang et al., 2010), regions in left M1, left PM, and left Pr were outlined across several scalp electrodes.”

“Alternatively, and more akin to fMRI studies (Baldassarre et al., 2012; Wang et al., 2010), regions in left M1, left PM, and left Pr were outlined across several scalp electrodes.”

“61, (Supekar et al., 2013)), performance on an associative memory task (R(2) = 0.”

“This may reflect basal differences in motor system efficiency, as premotor cortex activation has been associated with increased task complexity (O’Shea et al., 2007) and cognitive effort (Kantak et al., 2012).”

“It may be that increased M1-PM connectivity at rest is a marker of a inefficient motor system, similar to the aging motor system, which exhibits over-activity in premotor cortex during simple motor tasks (Ward, 2006).”

“Themotor skill task used in the current studywas a digital version of the classic pursuit rotor task motor learning paradigm (Adams, 1952; Grafton et al., 1994).”

“2.4 Coherence and Power EEG coherence was used to estimate functional connectivity (Murias et al., 2007; Nunez and Srinivasan, 2006; Srinivasan et al., 2007).”

“As with previous studies that used PLS (Esteban-Diez et al., 2004; Krishnan et al., 2013; Svensson et al., 2002; Williams et al., 2009), this step allowed for more efficient PLS models with fewer components.”

“As with previous studies that used PLS (Esteban-Diez et al., 2004; Krishnan et al., 2013; Svensson et al., 2002; Williams et al., 2009), this step allowed for more efficient PLS models with fewer components.”

“Previous studies have identified neural correlates of variability during motor learning (Tomassini et al., 2011), and both structural and functional neuroimaging methods have been evaluated as predictors of motor learning (Mathewson et al., 2012; Vo et al., 2011).”

“This may reflect greater capacity for visuomotor integration, as suggested by a recent study that reported that increased functional connectivity between sensorimotor and parietal regions during early motor learning coincidedwith significant behavioral improvement (Ma et al., 2010).”

“First, use of EEG may offer some advantages for measuring synchronized activity across neural ensembles (Ganguly et al., 2009), as EEG provides higher temporal resolution than many other functional neuroimaging techniques.”

“Opposite findings regarding M1-Pr vs. M1-PM connectivity may therefore reflect individual differences in specific processing components that contribute to variability in early motor learning (Grafton et al., 2008).”

“In various studies of motor function using EEG coherence, changes in brain connectivity have been observed in the β (20–30 Hz) frequency range (Deeny et al., 2009; Pfurtscheller et al., 1996; Tropini et al., 2011).”

“Although EEG coherence is here used as an index of cortico-cortical functional connectivity to represent communication between neural sources, it does not exclude the possibility that increased coherence may also represent increased drive from a common source (Mima et al., 2000; Saltzberg et al., 1986).”

“As with previous studies that used PLS (Esteban-Diez et al., 2004; Krishnan et al., 2013; Svensson et al., 2002; Williams et al., 2009), this step allowed for more efficient PLS models with fewer components.”

“However, 256-electrodes systems, as used in the current study, are shown to provide significantly improved spatial resolution compared to traditional 10–20 systems (Luu et al., 2001; Ryynänen et al., 2004).”

“, 2011), and both structural and functional neuroimaging methods have been evaluated as predictors of motor learning (Mathewson et al., 2012; Vo et al., 2011).”

“Themotor skill task used in the current studywas a digital version of the classic pursuit rotor task motor learning paradigm (Adams, 1952; Grafton et al., 1994).”

“A surface Laplacian could be used to further improve spatial resolution (Nunez and Westdorp, 1994).”

“As with previous studies that used PLS (Esteban-Diez et al., 2004; Krishnan et al., 2013; Svensson et al., 2002; Williams et al., 2009), this step allowed for more efficient PLS models with fewer components.”

“…patients demonstrate significant heterogeneity in motor learning, the current methods may be useful in clinical settings related to cortical plasticity, such as acute stroke or traumatic brain injury, where a high need exists for accurate methods of patient stratification (Burke and Cramer, 2013).”

“Although EEG coherence is here used as an index of cortico-cortical functional connectivity to represent communication between neural sources, it does not exclude the possibility that increased coherence may also represent increased drive from a common source (Mima et al., 2000; Saltzberg et al., 1986).”

“However, 256-electrodes systems, as used in the current study, are shown to provide significantly improved spatial resolution compared to traditional 10–20 systems (Luu et al., 2001; Ryynänen et al., 2004).”

“, 2011), and both structural and functional neuroimaging methods have been evaluated as predictors of motor learning (Mathewson et al., 2012; Vo et al., 2011).”

“Keywords EEG; motor learning; coherence; PLS Introduction Individuals demonstrate significant variability in motor learning (Ackerman, 1987; King et al., 2012).”

“The favorable comparison of a PLS approach suggests whole-brain approaches, including graph-theoretical network analysis (Langer et al., 2011) and Independent Component Analysis (Lin et al., 2012), may be more sensitive to inter-individual variations that provide insight into differences in behavior.”

“In various studies of motor function using EEG coherence, changes in brain connectivity have been observed in the β (20–30 Hz) frequency range (Deeny et al., 2009; Pfurtscheller et al., 1996; Tropini et al., 2011).”

“Furthermore, a PLS approach has been found useful for understanding behavioral correlates of EEG in populations with a range of brain-related diagnoses, such as major depression (KhodayariRostamabad et al., 2010) and Parkinson’s disease (Chiang et al., 2012).”

“Furthermore, several recent studies demonstrate that individual differences in brain function at rest are predictive of subsequent performance (Hampson et al., 2006; Tambini et al., 2010; Wu et al., 2014).”