Mukesh Dhamala | Georgia State University (original) (raw)

Papers by Mukesh Dhamala

Data in Brief, 2018

Nonparametric methods based on spectral factorization offer well validated tools for estimating s... more Nonparametric methods based on spectral factorization offer well validated tools for estimating spectral measures of causality, called Granger-Geweke Causality (GGC). In Pagnotta et al. (2018) [1] we benchmarked nonparametric GGC methods using EEG data recorded during unilateral whisker stimulations in ten rats; here, we include detailed information about the benchmark dataset. In addition, we provide codes for estimating nonparametric GGC and a simulation framework to evaluate the effects on GGC analyses of potential problems, such as the common reference problem, signal-to-noise ratio (SNR) differences between channels, and the presence of additive noise. We focus on nonparametric methods here, but these issues also affect parametric methods, which can be tested in our framework as well. Our examples allow showing that time reversal testing for GGC (tr-GGC) mitigates the detrimental effects due to SNR imbalance and presence of mixed additive noise, and illustrate that, when using a common reference, tr-GGC unambiguously detects the causal influence's dominant spectral component, irrespective of the characteristics of the common reference signal. Finally, one of our simulations provides an example that nonparametric methods can overcome a pitfall Contents lists available at ScienceDirect

Use of Granger causality analysis and artificial spike trains to examine pause coding in Purkinje... more Use of Granger causality analysis and artificial spike trains to examine pause coding in Purkinje cell spike activity related to rhythmic licking

Human cognition and behavior arise from neuronal interactions over brain structural networks. The... more Human cognition and behavior arise from neuronal interactions over brain structural networks. These neuronal interactions cause changes in structural networks over time. How a creative activity such as musical improvisation performance changes the brain structure is largely unknown. In this diffusion magnetic resonance imaging study, we examined the brain’s white matter fiber properties in previously identified functional networks and compared the findings between advanced jazz improvisers and non-musicians. We found that, for advanced improvisers compared with non-musicians, the normalized quantitative anisotropy (NQA) is elevated in the lateral prefrontal areas and supplementary motor area, and the underlying white matter fiber tracts connecting these areas. This enhancement of the diffusion anisotropy along the fiber pathway connecting the lateral prefrontal and supplementary motor is consistent with the functional networks during musical improvisation tasks performed by expert j...

Scientific Reports

One of the most complex forms of creativity is musical improvisation where new music is produced ... more One of the most complex forms of creativity is musical improvisation where new music is produced in real time. Brain behavior during music production has several dimensions depending on the conditions of the performance. The expression of creativity is suspected to be different whether novel ideas must be externalized using a musical instrument or can be imagined internally. This study explores whole brain functional network connectivity from fMRI data during jazz music improvisation compared against a baseline of prelearned score performance. Given that creativity might be affected by external execution, another dimension where musicians imagine or vocalize the music was also tested. We found improvisation was associated with a state of weak connectivity necessary for attenuated executive control network recruitment associated with a feeling of “flow” allowing unhindered musical creation. In addition, elicited connectivity for sensorimotor and executive control networks is not diff...

NeuroImage

It is shown how the brain's linear transfer function provides a means to systematically analyze b... more It is shown how the brain's linear transfer function provides a means to systematically analyze brain connectivity and dynamics, and to infer connectivity, eigenmodes, and activity measures such as spectra, evoked responses, coherence, and causality, all of which are widely used in brain monitoring. In particular, the Wilson spectral factorization algorithm is outlined and used to efficiently obtain linear transfer functions from experimental two-point correlation functions. The algorithm is tested on a series of brain-like structures of increasing complexity which include time delays, asymmetry, two-dimensionality, and complex network connectivity. These tests are used to verify the algorithm is suitable for application to brain dynamics, specify sampling requirements for experimental time series, and to verify that its runtime is short enough to obtain accurate results for systems of similar size to current experiments. The results can equally well be applied to inference of the transfer function in complex linear systems other than brains.

Physical Review E

Many real-world examples of distributed oscillators involve not only time delays but also attract... more Many real-world examples of distributed oscillators involve not only time delays but also attractive (positive) and repulsive (negative) influences in their network interactions. Here, considering such examples, we generalize the Kuramoto model of globally coupled oscillators with time-delayed positive and negative couplings to explore the effects of such couplings in collective phase synchronization. We analytically derive the exact solutions for stable incoherent and coherent states in terms of the system parameters allowing us to precisely understand the interplay of time delays and couplings in collective synchronization. Dependent on these parameters, fully coherent, incoherent states and mixed states are possible. Time-delays especially in the negative coupling seem to facilitate collective synchronization. In case of a stronger negative coupling than positive one, a stable synchronized state cannot be achieved without time delays. We discuss the implications of the model and the results for natural systems, particularly neuronal network systems in the brain.

Brain Connectivity

Musical improvisation is one of the most complex forms of creative behavior, which offers a reali... more Musical improvisation is one of the most complex forms of creative behavior, which offers a realistic task paradigm for the investigation of real-time creativity where revision is not possible. Despite some previous studies on musical improvisation and brain activity, what and how brain areas are involved during musical improvisation are not clearly understood. In this article, we designed a new functional magnetic resonance imaging (fMRI) study, in which, while being in the MRI scanner, advanced jazz improvisers performed improvisatory vocalization and imagery as main tasks and performed a prelearned melody as a control task. We incorporated a musical imagery task to avoid possible confounds of mixed motor and perceptual variables in previous studies. We found that musical improvisation compared with prelearned melody is characterized by higher node activity in the Broca's area, dorsolateral prefrontal cortex, lateral premotor cortex, supplementary motor area and cerebellum, and lower functional connectivity in number and strength among these regions. We discuss various explanations for the divergent activation and connectivity results. These results point to the notion that a human creative behavior performed under real-time constraints is an internally directed behavior controlled primarily by a smaller brain network in the frontal cortex.

The Journal of Neuroscience

Although one proposed function of both the striatum and its major dopamine inputs is related to c... more Although one proposed function of both the striatum and its major dopamine inputs is related to coding rewards and reward-related stimuli, an alternative view suggests a more general role of the striatum in processing salient events, regardless of their reward value. Here we define saliency as an event that both is unexpected and elicits an attentional-behavioral switch (i.e., arousing). In the present study, human striatal responses to nonrewarding salient stimuli were investigated. Using functional magnetic resonance imaging (fMRI), the blood oxygenation level-dependent signal was measured in response to flickering visual distractors presented in the background of an ongoing task. Distractor salience was manipulated by altering the frequency of distractor occurrence. Infrequently presented distractors were considered more salient than frequently presented distractors. We also investigated whether behavioral relevance of the distractors was a necessary component of saliency for eliciting striatal responses. In the first experiment (19 subjects), the distractors were made behaviorally relevant by defining a subset of them as targets requiring a button press. In the second experiment (17 subjects), the distractors were not behaviorally relevant (i.e., they did not require any response). The fMRI results revealed increased activation in the nucleus accumbens after infrequent (high salience) relative to frequent (low salience) presentation of distractors in both experiments. Caudate activity increased only when the distractors were behaviorally relevant. These results demonstrate a role of the striatum in coding nonrewarding salient events. In addition, a functional subdivision of the striatum according to the behavioral relevance of the stimuli is suggested.

Brain connectivity, 2018

Generating movement rhythms is known to involve a network of distributed brain regions associated... more Generating movement rhythms is known to involve a network of distributed brain regions associated with motor planning, control, execution, and perception of timing for the repertoire of motor actions. What brain areas are bound in the network and how the network activity is modulated by rhythmic complexity have not been completely explored. To contribute to answering these questions, we designed a study in which nine healthy participants performed simple to complex rhythmic finger movement tasks while undergoing simultaneous functional magnetic resonance imaging and electroencephalography (fMRI-EEG) recordings of their brain activity during the tasks and rest. From fMRI blood oxygenation-level-dependent (BOLD) measurements, we found that the complexity of rhythms was associated with brain activations in the primary motor cortex (PMC), supplementary motor area (SMA), and cerebellum (Cb), and with network interactions from these cortical regions to the cerebellum. The spectral analysi...

NeuroImage, Jan 15, 2018

In a recent PNAS article, Stokes and Purdon performed numerical simulations to argue that Granger... more In a recent PNAS article, Stokes and Purdon performed numerical simulations to argue that Granger-Geweke causality (GGC) estimation is severely biased, or of high variance, and GGC application to neuroscience is problematic because the GGC measure is independent of 'receiver' dynamics. Here, we use the same simulation examples to show that GGC measures, when properly estimated either via the spectral factorization-enabled nonparametric approach or the VAR-model based parametric approach, do not have the claimed bias and high variance problems. Further, the receiver-independence property of GGC does not present a problem for neuroscience applications. When the nature and context of experimental measurements are taken into consideration, GGC, along with other spectral quantities, yield neurophysiologically interpretable results.

Scientific reports, Jan 19, 2018

Synchronization commonly occurs in many natural and man-made systems, from neurons in the brain t... more Synchronization commonly occurs in many natural and man-made systems, from neurons in the brain to cardiac cells to power grids to Josephson junction arrays. Transitions to or out of synchrony for coupled oscillators depend on several factors, such as individual frequencies, coupling, interaction time delays and network structure-function relation. Here, using a generalized Kuramoto model of time-delay coupled phase oscillators with frequency-weighted coupling, we study the stability of incoherent and coherent states and the transitions to or out of explosive (abrupt, first-order like) phase synchronization. We analytically derive the exact formulas for the critical coupling strengths at different time delays in both directions of increasing (forward) and decreasing (backward) coupling strengths. We find that time-delay does not affect the transition for the backward direction but can shift the transition for the forward direction of increasing coupling strength. These results provi...

Frontiers in Neuroscience

In the neocortex, communication between neurons is heavily influenced by the activity of the surr... more In the neocortex, communication between neurons is heavily influenced by the activity of the surrounding network, with communication efficacy increasing when population patterns are oscillatory and coherent. Less is known about whether coherent oscillations are essential for conveyance of thalamic input to the neocortex in awake animals. Here we investigated whether visual-evoked oscillations and spikes in the primary visual cortex (V1) were aligned with those in the visual thalamus (dLGN). Using simultaneous recordings of visual-evoked activity in V1 and dLGN we demonstrate that thalamocortical communication involves synchronized local field potential oscillations in the high gamma range (50-90 Hz) which correspond uniquely to precise dLGN-V1 spike synchrony. These results provide evidence of a role for high gamma oscillations in mediating thalamocortical communication in the visual pathway of mice, analogous to beta oscillations in primates.

NeuroImage

Information processing in the human brain during cognitively demanding goal-directed tasks is tho... more Information processing in the human brain during cognitively demanding goal-directed tasks is thought to involve several large-scale brain networks, including the anterior cingulate-insula network (aCIN) and the fronto-parietal network (FPN). Recent functional MRI (fMRI) studies have provided clues that the aCIN initiates activity changes in the FPN. However, when and how often these networks interact remains largely unknown to date. Here, we systematically examined the oscillatory interactions between the aCIN and the FPN by using the spectral Granger causality analysis of reconstructed brain source signals from the scalp electroencephalography (EEG) recorded from human participants performing a face-house perceptual categorization task. We investigated how the aCIN and the FPN interact, what the temporal sequence of events in these nodes is, and what frequency bands of information flow bind these nodes in networks. We found that beta band (13-30 Hz) and gamma (30-100 Hz) bands of interactions are involved between the aCIN and the FPN during decision-making tasks. In gamma band, the aCIN initiated the Granger causal control over the FPN in 25-225 ms timeframe. In beta band, the FPN achieved a control over the aCIN in 225-425 ms timeframe. These band-specific time-dependent Granger causal controls of the aCIN and the FPN were retained for behaviorally harder decision-making tasks. These findings of times and frequencies of oscillatory interactions in the aCIN and FPN provide us new insights into the general neural mechanisms for sensory information-guided, goal-directed behaviors, including perceptual decision-making processes.

Scientific reports, Apr 3, 2017

We here study explosive synchronization transitions and network activity propagation in networks ... more We here study explosive synchronization transitions and network activity propagation in networks of coupled neurons to provide a new understanding of the relationship between network topology and explosive dynamical transitions as in epileptic seizures and their propagations in the brain. We model local network motifs and configurations of coupled neurons and analyze the activity propagations between a group of active neurons to their inactive neuron neighbors in a variety of network configurations. We find that neuronal activity propagation is limited to local regions when network is highly clustered with modular structures as in the normal brain networks. When the network cluster structure is slightly changed, the activity propagates to the entire network, which is reminiscent of epileptic seizure propagation in the brain. Finally, we analyze intracranial electroencephalography (IEEG) recordings of a seizure episode from a epilepsy patient and uncover that explosive synchronizatio...

Frontiers in human neuroscience, 2016

Balance of motor network activity between the two brain hemispheres after stroke is crucial for f... more Balance of motor network activity between the two brain hemispheres after stroke is crucial for functional recovery. Several studies have extensively studied the role of the affected brain hemisphere to better understand changes in motor network activity following stroke. Very few studies have examined the role of the unaffected brain hemisphere and confirmed the test-retest reliability of connectivity measures on unaffected hemisphere. We recorded blood oxygenation level dependent functional magnetic resonance imaging (fMRI) signals from nine stroke survivors with hemiparesis of the left or right hand. Participants performed a motor execution task with affected hand, unaffected hand, and both hands simultaneously. Participants returned for a repeat fMRI scan 1 week later. Using dynamic causal modeling (DCM), we evaluated effective connectivity among three motor areas: the primary motor area (M1), the premotor cortex (PMC) and the supplementary motor area for the affected and unaffe...

NeuroImage, 2016

Recent neuroimaging studies have demonstrated that the network consisting of the right anterior i... more Recent neuroimaging studies have demonstrated that the network consisting of the right anterior insula (rAI), left anterior insula (lAI) and dorsal anterior cingulate cortex (dACC) is activated in sensory stimulus-guided goal-directed behaviors. This network is often known as the salience network (SN). When and how a sensory signal enters and organizes within SN before reaching the central executive network including the prefrontal cortices is still a mystery. Previous electrophysiological studies focused on individual nodes of SN, either on dACC or rAI, have reports of conflicting findings of the earliest cortical activity within the network. Functional magnetic resonance imaging (fMRI) studies are not able to answer these questions in the timescales of human sensory perception and decision-making. Here, using clear and noisy face-house image categorization tasks and human scalp electroencephalography (EEG) recordings combined with source reconstruction techniques, we study when and how oscillatory activity organizes SN during a perceptual decision. We uncovered that the beta-band (13-30 Hz) oscillations bound SN, became most active around 100 ms after the stimulus onset and the rAI acted as a main outflow hub within SN for easier decision making task. The SN activities (Granger causality measures) were negatively correlated with the decision response time (decision difficulty). These findings suggest that the SN activity precedes the executive control in mediating sensory and cognitive processing to arrive at visual perceptual decisions.

Brain Connectivity, 2016

Musical improvisation offers an excellent experimental paradigm for the study of real-time human ... more Musical improvisation offers an excellent experimental paradigm for the study of real-time human creativity. It involves moment-to-moment decision-making, monitoring of one's performance, and utilizing external feedback to spontaneously create new melodies or variations on a melody. Recent neuroimaging studies have begun to study the brain activity during musical improvisation, aiming to unlock the mystery of human creativity. What brain resources come together and how these are utilized during musical improvisation are not well understood. To help answer these questions, we recorded electroencephalography (EEG) signals from 19 experienced musicians while they played or imagined short isochronous learned melodies and improvised on those learned melodies. These four conditions (Play-Prelearned, Play-Improvised, Imagine-Prelearned, Imagine-Improvised) were randomly interspersed in a total of 300 trials per participant. From the sensor-level EEG, we found that there were power differences in the alpha (8-12 Hz) and beta (13-30 Hz) bands in separate clusters of frontal, parietal, temporal, and occipital electrodes. Using EEG source localization and dipole modeling methods for task-related signals, we identified the locations and network activities of five sources: the left superior frontal gyrus (L SFG), supplementary motor area (SMA), left inferior parietal lobule (L IPL), right dorsolateral prefrontal cortex, and right superior temporal gyrus. During improvisation, the network activity between L SFG, SMA, and L IPL was significantly less than during the prelearned conditions. Our results support the general idea that attenuated cognitive control facilitates the production of creative output.

Brain Connectivity, 2016

Granger causality (GC) and dynamic causal modeling (DCM) are the two key approaches used to deter... more Granger causality (GC) and dynamic causal modeling (DCM) are the two key approaches used to determine the directed interactions among brain areas. Recent discussions have provided a constructive account of the merits and demerits. GC, on one side, considers dependencies among measured responses, whereas DCM, on the other, models how neuronal activity in one brain area causes dynamics in another. In this study, our objective was to establish construct validity between GC and DCM in the context of resting state functional magnetic resonance imaging (fMRI). We first established the face validity of both approaches using simulated fMRI time series, with endogenous fluctuations in two nodes. Crucially, we tested both unidirectional and bidirectional connections between the two nodes to ensure that both approaches give veridical and consistent results, in terms of model comparison. We then applied both techniques to empirical data and examined their consistency in terms of the (quantitative) in-degree of key nodes of the default mode. Our simulation results suggested a (qualitative) consistency between GC and DCM. Furthermore, by applying nonparametric GC and stochastic DCM to restingstate fMRI data, we confirmed that both GC and DCM infer similar (quantitative) directionality between the posterior cingulate cortex (PCC), the medial prefrontal cortex, the left middle temporal cortex, and the left angular gyrus. These findings suggest that GC and DCM can be used to estimate directed functional and effective connectivity from fMRI measurements in a consistent manner.

Granger causality (GC) and dynamic causal modeling (DCM) are the two key approaches used to deter... more Granger causality (GC) and dynamic causal modeling (DCM) are the two key approaches used to determine the directed interactions among brain areas. Recent discussions have provided a constructive account of the merits and demerits. GC, on one side, considers dependencies among measured responses, whereas DCM, on the other, models how neuronal activity in one brain area causes dynamics in another. In this study, our objective was to establish construct validity between GC and DCM in the context of resting state functional magnetic resonance imaging (fMRI). We first established the face validity of both approaches using simulated fMRI time series, with endogenous fluctuations in two nodes. Crucially, we tested both unidirectional and bidirectional connections between the two nodes to ensure that both approaches give veridical and consistent results, in terms of model comparison. We then applied both techniques to empirical data and examined their consistency in terms of the (quantitati...

Brain Connectivity, 2016

Previous functional magnetic resonance imaging studies have consistently shown that perception of... more Previous functional magnetic resonance imaging studies have consistently shown that perception of visual objects, such as faces and houses, involves distributed brain networks that include the fusiform face area (FFA), parahippocampal place area (PPA), and dorsolateral prefrontal cortex (DLPFC). These regions are commonly observed to be coactivated in BOLD measurements during perception of visual objects. In this study, we aimed to disentangle node-level and network-level activities in millisecond timescale of perception and decisionmaking in attempts to answer questions about timing and frequency of brain oscillatory activities. We used clear and noisy face-house image categorization tasks and human scalp electroencephalography recordings combined with source reconstruction techniques to study when and how oscillatory activity organizes within the FFA, PPA, and DLPFC. We uncovered the dynamics of two oscillatory networks-beta (13-30 Hz) and gamma (30-100 Hz). In beta band, the node and network activities were enhanced in time frame of 125-250 msec after stimulus onset, the FFA and PPA acted as main outflow hubs and the DLPFC as a main inflow hub, and network activities negatively correlated with behavior measures of noise levels (response times). In gamma band, node and network activities were elevated in time frame of 0-125 msec after stimulus onset, the DLPFC acted as a main outflow hub, and finally network activities were positively correlated with the noise level. These findings broaden our understanding of temporal evolution of node and network features associated with visual perceptual decision-making.

Data in Brief, 2018

Nonparametric methods based on spectral factorization offer well validated tools for estimating s... more Nonparametric methods based on spectral factorization offer well validated tools for estimating spectral measures of causality, called Granger-Geweke Causality (GGC). In Pagnotta et al. (2018) [1] we benchmarked nonparametric GGC methods using EEG data recorded during unilateral whisker stimulations in ten rats; here, we include detailed information about the benchmark dataset. In addition, we provide codes for estimating nonparametric GGC and a simulation framework to evaluate the effects on GGC analyses of potential problems, such as the common reference problem, signal-to-noise ratio (SNR) differences between channels, and the presence of additive noise. We focus on nonparametric methods here, but these issues also affect parametric methods, which can be tested in our framework as well. Our examples allow showing that time reversal testing for GGC (tr-GGC) mitigates the detrimental effects due to SNR imbalance and presence of mixed additive noise, and illustrate that, when using a common reference, tr-GGC unambiguously detects the causal influence's dominant spectral component, irrespective of the characteristics of the common reference signal. Finally, one of our simulations provides an example that nonparametric methods can overcome a pitfall Contents lists available at ScienceDirect

Use of Granger causality analysis and artificial spike trains to examine pause coding in Purkinje... more Use of Granger causality analysis and artificial spike trains to examine pause coding in Purkinje cell spike activity related to rhythmic licking

Human cognition and behavior arise from neuronal interactions over brain structural networks. The... more Human cognition and behavior arise from neuronal interactions over brain structural networks. These neuronal interactions cause changes in structural networks over time. How a creative activity such as musical improvisation performance changes the brain structure is largely unknown. In this diffusion magnetic resonance imaging study, we examined the brain’s white matter fiber properties in previously identified functional networks and compared the findings between advanced jazz improvisers and non-musicians. We found that, for advanced improvisers compared with non-musicians, the normalized quantitative anisotropy (NQA) is elevated in the lateral prefrontal areas and supplementary motor area, and the underlying white matter fiber tracts connecting these areas. This enhancement of the diffusion anisotropy along the fiber pathway connecting the lateral prefrontal and supplementary motor is consistent with the functional networks during musical improvisation tasks performed by expert j...

Scientific Reports

One of the most complex forms of creativity is musical improvisation where new music is produced ... more One of the most complex forms of creativity is musical improvisation where new music is produced in real time. Brain behavior during music production has several dimensions depending on the conditions of the performance. The expression of creativity is suspected to be different whether novel ideas must be externalized using a musical instrument or can be imagined internally. This study explores whole brain functional network connectivity from fMRI data during jazz music improvisation compared against a baseline of prelearned score performance. Given that creativity might be affected by external execution, another dimension where musicians imagine or vocalize the music was also tested. We found improvisation was associated with a state of weak connectivity necessary for attenuated executive control network recruitment associated with a feeling of “flow” allowing unhindered musical creation. In addition, elicited connectivity for sensorimotor and executive control networks is not diff...

NeuroImage

It is shown how the brain's linear transfer function provides a means to systematically analyze b... more It is shown how the brain's linear transfer function provides a means to systematically analyze brain connectivity and dynamics, and to infer connectivity, eigenmodes, and activity measures such as spectra, evoked responses, coherence, and causality, all of which are widely used in brain monitoring. In particular, the Wilson spectral factorization algorithm is outlined and used to efficiently obtain linear transfer functions from experimental two-point correlation functions. The algorithm is tested on a series of brain-like structures of increasing complexity which include time delays, asymmetry, two-dimensionality, and complex network connectivity. These tests are used to verify the algorithm is suitable for application to brain dynamics, specify sampling requirements for experimental time series, and to verify that its runtime is short enough to obtain accurate results for systems of similar size to current experiments. The results can equally well be applied to inference of the transfer function in complex linear systems other than brains.

Physical Review E

Many real-world examples of distributed oscillators involve not only time delays but also attract... more Many real-world examples of distributed oscillators involve not only time delays but also attractive (positive) and repulsive (negative) influences in their network interactions. Here, considering such examples, we generalize the Kuramoto model of globally coupled oscillators with time-delayed positive and negative couplings to explore the effects of such couplings in collective phase synchronization. We analytically derive the exact solutions for stable incoherent and coherent states in terms of the system parameters allowing us to precisely understand the interplay of time delays and couplings in collective synchronization. Dependent on these parameters, fully coherent, incoherent states and mixed states are possible. Time-delays especially in the negative coupling seem to facilitate collective synchronization. In case of a stronger negative coupling than positive one, a stable synchronized state cannot be achieved without time delays. We discuss the implications of the model and the results for natural systems, particularly neuronal network systems in the brain.

Brain Connectivity

Musical improvisation is one of the most complex forms of creative behavior, which offers a reali... more Musical improvisation is one of the most complex forms of creative behavior, which offers a realistic task paradigm for the investigation of real-time creativity where revision is not possible. Despite some previous studies on musical improvisation and brain activity, what and how brain areas are involved during musical improvisation are not clearly understood. In this article, we designed a new functional magnetic resonance imaging (fMRI) study, in which, while being in the MRI scanner, advanced jazz improvisers performed improvisatory vocalization and imagery as main tasks and performed a prelearned melody as a control task. We incorporated a musical imagery task to avoid possible confounds of mixed motor and perceptual variables in previous studies. We found that musical improvisation compared with prelearned melody is characterized by higher node activity in the Broca's area, dorsolateral prefrontal cortex, lateral premotor cortex, supplementary motor area and cerebellum, and lower functional connectivity in number and strength among these regions. We discuss various explanations for the divergent activation and connectivity results. These results point to the notion that a human creative behavior performed under real-time constraints is an internally directed behavior controlled primarily by a smaller brain network in the frontal cortex.

The Journal of Neuroscience

Although one proposed function of both the striatum and its major dopamine inputs is related to c... more Although one proposed function of both the striatum and its major dopamine inputs is related to coding rewards and reward-related stimuli, an alternative view suggests a more general role of the striatum in processing salient events, regardless of their reward value. Here we define saliency as an event that both is unexpected and elicits an attentional-behavioral switch (i.e., arousing). In the present study, human striatal responses to nonrewarding salient stimuli were investigated. Using functional magnetic resonance imaging (fMRI), the blood oxygenation level-dependent signal was measured in response to flickering visual distractors presented in the background of an ongoing task. Distractor salience was manipulated by altering the frequency of distractor occurrence. Infrequently presented distractors were considered more salient than frequently presented distractors. We also investigated whether behavioral relevance of the distractors was a necessary component of saliency for eliciting striatal responses. In the first experiment (19 subjects), the distractors were made behaviorally relevant by defining a subset of them as targets requiring a button press. In the second experiment (17 subjects), the distractors were not behaviorally relevant (i.e., they did not require any response). The fMRI results revealed increased activation in the nucleus accumbens after infrequent (high salience) relative to frequent (low salience) presentation of distractors in both experiments. Caudate activity increased only when the distractors were behaviorally relevant. These results demonstrate a role of the striatum in coding nonrewarding salient events. In addition, a functional subdivision of the striatum according to the behavioral relevance of the stimuli is suggested.

Brain connectivity, 2018

Generating movement rhythms is known to involve a network of distributed brain regions associated... more Generating movement rhythms is known to involve a network of distributed brain regions associated with motor planning, control, execution, and perception of timing for the repertoire of motor actions. What brain areas are bound in the network and how the network activity is modulated by rhythmic complexity have not been completely explored. To contribute to answering these questions, we designed a study in which nine healthy participants performed simple to complex rhythmic finger movement tasks while undergoing simultaneous functional magnetic resonance imaging and electroencephalography (fMRI-EEG) recordings of their brain activity during the tasks and rest. From fMRI blood oxygenation-level-dependent (BOLD) measurements, we found that the complexity of rhythms was associated with brain activations in the primary motor cortex (PMC), supplementary motor area (SMA), and cerebellum (Cb), and with network interactions from these cortical regions to the cerebellum. The spectral analysi...

NeuroImage, Jan 15, 2018

In a recent PNAS article, Stokes and Purdon performed numerical simulations to argue that Granger... more In a recent PNAS article, Stokes and Purdon performed numerical simulations to argue that Granger-Geweke causality (GGC) estimation is severely biased, or of high variance, and GGC application to neuroscience is problematic because the GGC measure is independent of 'receiver' dynamics. Here, we use the same simulation examples to show that GGC measures, when properly estimated either via the spectral factorization-enabled nonparametric approach or the VAR-model based parametric approach, do not have the claimed bias and high variance problems. Further, the receiver-independence property of GGC does not present a problem for neuroscience applications. When the nature and context of experimental measurements are taken into consideration, GGC, along with other spectral quantities, yield neurophysiologically interpretable results.

Scientific reports, Jan 19, 2018

Synchronization commonly occurs in many natural and man-made systems, from neurons in the brain t... more Synchronization commonly occurs in many natural and man-made systems, from neurons in the brain to cardiac cells to power grids to Josephson junction arrays. Transitions to or out of synchrony for coupled oscillators depend on several factors, such as individual frequencies, coupling, interaction time delays and network structure-function relation. Here, using a generalized Kuramoto model of time-delay coupled phase oscillators with frequency-weighted coupling, we study the stability of incoherent and coherent states and the transitions to or out of explosive (abrupt, first-order like) phase synchronization. We analytically derive the exact formulas for the critical coupling strengths at different time delays in both directions of increasing (forward) and decreasing (backward) coupling strengths. We find that time-delay does not affect the transition for the backward direction but can shift the transition for the forward direction of increasing coupling strength. These results provi...

Frontiers in Neuroscience

In the neocortex, communication between neurons is heavily influenced by the activity of the surr... more In the neocortex, communication between neurons is heavily influenced by the activity of the surrounding network, with communication efficacy increasing when population patterns are oscillatory and coherent. Less is known about whether coherent oscillations are essential for conveyance of thalamic input to the neocortex in awake animals. Here we investigated whether visual-evoked oscillations and spikes in the primary visual cortex (V1) were aligned with those in the visual thalamus (dLGN). Using simultaneous recordings of visual-evoked activity in V1 and dLGN we demonstrate that thalamocortical communication involves synchronized local field potential oscillations in the high gamma range (50-90 Hz) which correspond uniquely to precise dLGN-V1 spike synchrony. These results provide evidence of a role for high gamma oscillations in mediating thalamocortical communication in the visual pathway of mice, analogous to beta oscillations in primates.

NeuroImage

Information processing in the human brain during cognitively demanding goal-directed tasks is tho... more Information processing in the human brain during cognitively demanding goal-directed tasks is thought to involve several large-scale brain networks, including the anterior cingulate-insula network (aCIN) and the fronto-parietal network (FPN). Recent functional MRI (fMRI) studies have provided clues that the aCIN initiates activity changes in the FPN. However, when and how often these networks interact remains largely unknown to date. Here, we systematically examined the oscillatory interactions between the aCIN and the FPN by using the spectral Granger causality analysis of reconstructed brain source signals from the scalp electroencephalography (EEG) recorded from human participants performing a face-house perceptual categorization task. We investigated how the aCIN and the FPN interact, what the temporal sequence of events in these nodes is, and what frequency bands of information flow bind these nodes in networks. We found that beta band (13-30 Hz) and gamma (30-100 Hz) bands of interactions are involved between the aCIN and the FPN during decision-making tasks. In gamma band, the aCIN initiated the Granger causal control over the FPN in 25-225 ms timeframe. In beta band, the FPN achieved a control over the aCIN in 225-425 ms timeframe. These band-specific time-dependent Granger causal controls of the aCIN and the FPN were retained for behaviorally harder decision-making tasks. These findings of times and frequencies of oscillatory interactions in the aCIN and FPN provide us new insights into the general neural mechanisms for sensory information-guided, goal-directed behaviors, including perceptual decision-making processes.

Scientific reports, Apr 3, 2017

We here study explosive synchronization transitions and network activity propagation in networks ... more We here study explosive synchronization transitions and network activity propagation in networks of coupled neurons to provide a new understanding of the relationship between network topology and explosive dynamical transitions as in epileptic seizures and their propagations in the brain. We model local network motifs and configurations of coupled neurons and analyze the activity propagations between a group of active neurons to their inactive neuron neighbors in a variety of network configurations. We find that neuronal activity propagation is limited to local regions when network is highly clustered with modular structures as in the normal brain networks. When the network cluster structure is slightly changed, the activity propagates to the entire network, which is reminiscent of epileptic seizure propagation in the brain. Finally, we analyze intracranial electroencephalography (IEEG) recordings of a seizure episode from a epilepsy patient and uncover that explosive synchronizatio...

Frontiers in human neuroscience, 2016

Balance of motor network activity between the two brain hemispheres after stroke is crucial for f... more Balance of motor network activity between the two brain hemispheres after stroke is crucial for functional recovery. Several studies have extensively studied the role of the affected brain hemisphere to better understand changes in motor network activity following stroke. Very few studies have examined the role of the unaffected brain hemisphere and confirmed the test-retest reliability of connectivity measures on unaffected hemisphere. We recorded blood oxygenation level dependent functional magnetic resonance imaging (fMRI) signals from nine stroke survivors with hemiparesis of the left or right hand. Participants performed a motor execution task with affected hand, unaffected hand, and both hands simultaneously. Participants returned for a repeat fMRI scan 1 week later. Using dynamic causal modeling (DCM), we evaluated effective connectivity among three motor areas: the primary motor area (M1), the premotor cortex (PMC) and the supplementary motor area for the affected and unaffe...

NeuroImage, 2016

Recent neuroimaging studies have demonstrated that the network consisting of the right anterior i... more Recent neuroimaging studies have demonstrated that the network consisting of the right anterior insula (rAI), left anterior insula (lAI) and dorsal anterior cingulate cortex (dACC) is activated in sensory stimulus-guided goal-directed behaviors. This network is often known as the salience network (SN). When and how a sensory signal enters and organizes within SN before reaching the central executive network including the prefrontal cortices is still a mystery. Previous electrophysiological studies focused on individual nodes of SN, either on dACC or rAI, have reports of conflicting findings of the earliest cortical activity within the network. Functional magnetic resonance imaging (fMRI) studies are not able to answer these questions in the timescales of human sensory perception and decision-making. Here, using clear and noisy face-house image categorization tasks and human scalp electroencephalography (EEG) recordings combined with source reconstruction techniques, we study when and how oscillatory activity organizes SN during a perceptual decision. We uncovered that the beta-band (13-30 Hz) oscillations bound SN, became most active around 100 ms after the stimulus onset and the rAI acted as a main outflow hub within SN for easier decision making task. The SN activities (Granger causality measures) were negatively correlated with the decision response time (decision difficulty). These findings suggest that the SN activity precedes the executive control in mediating sensory and cognitive processing to arrive at visual perceptual decisions.

Brain Connectivity, 2016

Musical improvisation offers an excellent experimental paradigm for the study of real-time human ... more Musical improvisation offers an excellent experimental paradigm for the study of real-time human creativity. It involves moment-to-moment decision-making, monitoring of one's performance, and utilizing external feedback to spontaneously create new melodies or variations on a melody. Recent neuroimaging studies have begun to study the brain activity during musical improvisation, aiming to unlock the mystery of human creativity. What brain resources come together and how these are utilized during musical improvisation are not well understood. To help answer these questions, we recorded electroencephalography (EEG) signals from 19 experienced musicians while they played or imagined short isochronous learned melodies and improvised on those learned melodies. These four conditions (Play-Prelearned, Play-Improvised, Imagine-Prelearned, Imagine-Improvised) were randomly interspersed in a total of 300 trials per participant. From the sensor-level EEG, we found that there were power differences in the alpha (8-12 Hz) and beta (13-30 Hz) bands in separate clusters of frontal, parietal, temporal, and occipital electrodes. Using EEG source localization and dipole modeling methods for task-related signals, we identified the locations and network activities of five sources: the left superior frontal gyrus (L SFG), supplementary motor area (SMA), left inferior parietal lobule (L IPL), right dorsolateral prefrontal cortex, and right superior temporal gyrus. During improvisation, the network activity between L SFG, SMA, and L IPL was significantly less than during the prelearned conditions. Our results support the general idea that attenuated cognitive control facilitates the production of creative output.

Brain Connectivity, 2016

Granger causality (GC) and dynamic causal modeling (DCM) are the two key approaches used to deter... more Granger causality (GC) and dynamic causal modeling (DCM) are the two key approaches used to determine the directed interactions among brain areas. Recent discussions have provided a constructive account of the merits and demerits. GC, on one side, considers dependencies among measured responses, whereas DCM, on the other, models how neuronal activity in one brain area causes dynamics in another. In this study, our objective was to establish construct validity between GC and DCM in the context of resting state functional magnetic resonance imaging (fMRI). We first established the face validity of both approaches using simulated fMRI time series, with endogenous fluctuations in two nodes. Crucially, we tested both unidirectional and bidirectional connections between the two nodes to ensure that both approaches give veridical and consistent results, in terms of model comparison. We then applied both techniques to empirical data and examined their consistency in terms of the (quantitative) in-degree of key nodes of the default mode. Our simulation results suggested a (qualitative) consistency between GC and DCM. Furthermore, by applying nonparametric GC and stochastic DCM to restingstate fMRI data, we confirmed that both GC and DCM infer similar (quantitative) directionality between the posterior cingulate cortex (PCC), the medial prefrontal cortex, the left middle temporal cortex, and the left angular gyrus. These findings suggest that GC and DCM can be used to estimate directed functional and effective connectivity from fMRI measurements in a consistent manner.

Granger causality (GC) and dynamic causal modeling (DCM) are the two key approaches used to deter... more Granger causality (GC) and dynamic causal modeling (DCM) are the two key approaches used to determine the directed interactions among brain areas. Recent discussions have provided a constructive account of the merits and demerits. GC, on one side, considers dependencies among measured responses, whereas DCM, on the other, models how neuronal activity in one brain area causes dynamics in another. In this study, our objective was to establish construct validity between GC and DCM in the context of resting state functional magnetic resonance imaging (fMRI). We first established the face validity of both approaches using simulated fMRI time series, with endogenous fluctuations in two nodes. Crucially, we tested both unidirectional and bidirectional connections between the two nodes to ensure that both approaches give veridical and consistent results, in terms of model comparison. We then applied both techniques to empirical data and examined their consistency in terms of the (quantitati...

Brain Connectivity, 2016

Previous functional magnetic resonance imaging studies have consistently shown that perception of... more Previous functional magnetic resonance imaging studies have consistently shown that perception of visual objects, such as faces and houses, involves distributed brain networks that include the fusiform face area (FFA), parahippocampal place area (PPA), and dorsolateral prefrontal cortex (DLPFC). These regions are commonly observed to be coactivated in BOLD measurements during perception of visual objects. In this study, we aimed to disentangle node-level and network-level activities in millisecond timescale of perception and decisionmaking in attempts to answer questions about timing and frequency of brain oscillatory activities. We used clear and noisy face-house image categorization tasks and human scalp electroencephalography recordings combined with source reconstruction techniques to study when and how oscillatory activity organizes within the FFA, PPA, and DLPFC. We uncovered the dynamics of two oscillatory networks-beta (13-30 Hz) and gamma (30-100 Hz). In beta band, the node and network activities were enhanced in time frame of 125-250 msec after stimulus onset, the FFA and PPA acted as main outflow hubs and the DLPFC as a main inflow hub, and network activities negatively correlated with behavior measures of noise levels (response times). In gamma band, node and network activities were elevated in time frame of 0-125 msec after stimulus onset, the DLPFC acted as a main outflow hub, and finally network activities were positively correlated with the noise level. These findings broaden our understanding of temporal evolution of node and network features associated with visual perceptual decision-making.