Concurrent EEG Research Articles

Assessing cerebellar-cortical connectivity using concurrent TMS-EEG: a feasibility study.

Combined single-pulse transcranial magnetic stimulation (TMS) and electroencephalography (EEG) has been used to probe the features of local networks in the cerebral cortex. Here, we investigated whether we can use this approach to explore long-range connections between the cerebellum and cerebral cortex. Ten healthy adults received single-pulse suprathreshold TMS to the cerebellum and an occipital/parietal control site with double-cone and figure-of-eight coils while cerebral activity was recorded. A multisensory electrical control condition was used to simulate the sensation of the double-cone coil at the cerebellar site. Two cleaning pipelines were compared, and the spatiotemporal relationships of the EEG output between conditions were examined at sensor and source levels. Cerebellar stimulation with the double-cone coil resulted in large artifact in the EEG trace. The addition of SOUND filtering to the cleaning pipeline improved the signal such that further analyses could be undertaken. The cortical potentials evoked by the active TMS conditions showed strong relationships with the responses to the multisensory control condition after ∼50 ms. A distinct parietal component at ∼42 ms was found following cerebellar double-cone stimulation. Although evoked potentials differed across all conditions at early latencies, it is unclear as to whether these represented TMS-related network activation of the cerebellarthalamocortical tract, or whether components were dominated by sensory contamination and/or coil-driven artifact. This study highlights the need for caution when interpreting outcomes from cerebellar TMS-EEG studies.NEW & NOTEWORTHY This is the first study to systematically assess the feasibility of obtaining TMS-evoked potentials from cerebellar stimulation with concurrent EEG. An innovative control condition using electrical stimulation was modified to mimic the sensory aspects of cerebellar stimulation with a double-cone coil, and a state-of-the art cleaning pipeline was trialled. The extent of artifact contamination in signals from stimulation of a cerebellar and an occipital/parietal control site using two TMS coil types was highlighted.

An analysis framework for the integration of broadband NIRS and EEG to assess neurovascular and neurometabolic coupling

With the rapid growth of optical-based neuroimaging to explore human brain functioning, our research group has been developing broadband Near Infrared Spectroscopy (bNIRS) instruments, a technological extension to functional Near Infrared Spectroscopy (fNIRS). bNIRS has the unique capacity of monitoring brain haemodynamics/oxygenation (measuring oxygenated and deoxygenated haemoglobin), and metabolism (measuring the changes in the redox state of cytochrome-c-oxidase). When combined with electroencephalography (EEG), bNIRS provides a unique neuromonitoring platform to explore neurovascular coupling mechanisms. In this paper, we present a novel pipeline for the integrated analysis of bNIRS and EEG signals, and demonstrate its use on multi-channel bNIRS data recorded with concurrent EEG on healthy adults during a visual stimulation task. We introduce the use of the Finite Impulse Response functions within the General Linear Model for bNIRS and show its feasibility to statistically localize the haemodynamic and metabolic activity in the occipital cortex. Moreover, our results suggest that the fusion of haemodynamic and metabolic measures unveils additional information on brain functioning over haemodynamic imaging alone. The cross-correlation-based analysis of interrelationships between electrical (EEG) and haemodynamic/metabolic (bNIRS) activity revealed that the bNIRS metabolic signal offers a unique marker of brain activity, being more closely coupled to the neuronal EEG response.

A Robust Biometric Authentication System for Handheld Electronic Devices by Intelligently Combining 3D Finger Motions and Cerebral Responses

Rapid advancement in sensor technology through miniaturization of electronic components has enabled the consumer electronic (CE) research community including the manufacturers to embed various utility sensors into handheld devices. In addition to traditional sensors such as Inertial Measurement Unit (IMU), camera, fingerprint or proximity, futuristic sensors such as Electroencephalogram (EEG) or Electromyography (EMG) are also being included in the next-generation CE devices. Air or touch signature-based authentication systems are common in modern CE devices. However, cerebral activities clubbed with gestures will certainly enhance the security of such authentication systems. This can help consumers from being the victims of shoulder surfing attacks. In this article, a new method is proposed to verify air signatures by analyzing finger movements and cerebral activities together with the help of sensors in next-generation CE devices. Signatures are first spotted by analyzing 3D geometrical features of the finger movement during the signing. Concurrent EEG responses are then analyzed for the verification. Hidden Markov Model (HMM) and Random Forest (RF) classifiers have been used to train the system. Experiments reveal that EEG signals are highly correlated with the finger movements during air signatures even in the presence of motion artifacts. Therefore, false-positive rates have significantly reduced as compared to the existing tracking-based methods. Verification accuracy as high as 95.5% (HMM) and 98.5% (RF) have been recorded when tested on our dataset.

BCI Training Effects on Chronic Stroke Correlate with Functional Reorganization in Motor-Related Regions: A Concurrent EEG and fMRI Study

Brain–computer interface (BCI)-guided robot-assisted training strategy has been increasingly applied to stroke rehabilitation, while few studies have investigated the neuroplasticity change and functional reorganization after intervention from multimodality neuroimaging perspective. The present study aims to investigate the hemodynamic and electrophysical changes induced by BCI training using functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) respectively, as well as the relationship between the neurological changes and motor function improvement. Fourteen chronic stroke subjects received 20 sessions of BCI-guided robot hand training. Simultaneous EEG and fMRI data were acquired before and immediately after the intervention. Seed-based functional connectivity for resting-state fMRI data and effective connectivity analysis for EEG were processed to reveal the neuroplasticity changes and interaction between different brain regions. Moreover, the relationship among motor function improvement, hemodynamic changes, and electrophysical changes derived from the two neuroimaging modalities was also investigated. This work suggested that (a) significant motor function improvement could be obtained after BCI training therapy, (b) training effect significantly correlated with functional connectivity change between ipsilesional M1 (iM1) and contralesional Brodmann area 6 (including premotor area (cPMA) and supplementary motor area (SMA)) derived from fMRI, (c) training effect significantly correlated with information flow change from cPMA to iM1 and strongly correlated with information flow change from SMA to iM1 derived from EEG, and (d) consistency of fMRI and EEG results illustrated by the correlation between functional connectivity change and information flow change. Our study showed changes in the brain after the BCI training therapy from chronic stroke survivors and provided a better understanding of neural mechanisms, especially the interaction among motor-related brain regions during stroke recovery. Besides, our finding demonstrated the feasibility and consistency of combining multiple neuroimaging modalities to investigate the neuroplasticity change.

Methohexital – Induced lateralized periodic discharges during Wada test

ObjectiveThe Wada test is used to evaluate language lateralization and memory performance after inactivation of an isolated cerebral hemisphere. Methohexital a short-acting barbiturate has a history of use to induce interictal discharges during intraoperative corticography. We report a new finding of activation of lateralized periodic discharges (LPDs) after Methohexital injection. MethodsWe retrospectively reviewed 174 consecutive adult patients who underwent Wada testing in preparation for epilepsy surgery (N = 129, 74%) or brain tumor resection (N = 45, 26%) at the University of Michigan to determine the frequency of induced periodic discharges by methohexital. ResultsFour epilepsy patients (2.29%) had methohexital-induced LPDs within a median of 2 s (1–99 s) of the injection and lasting a median of 4 min (3–10 min) after a total of 7 injections. All LPDs occurred ipsilateral to the injection hemisphere in the known region of interictal epileptiform discharges. LPDs were not induced in brain tumor patients. In one patient, LPDs occurred during memory testing, and this patient's memory performance was below expectation based on pre-test neuropsychological testing. ConclusionsMethohexital can induce LPDs in ipsilateral hemisphere and that can potentially affect memory performance. SignificanceThis observation indicates that concurrent EEG monitoring during the Wada test is important and that induced discharges should be considered when interpreting Wada test results.

Amplitude of fNIRS Resting-State Global Signal Is Related to EEG Vigilance Measures: A Simultaneous fNIRS and EEG Study.

Recently, functional near-infrared spectroscopy (fNIRS) has been utilized to image the hemodynamic activities and connectivity in the human brain. With the advantage of economic efficiency, portability, and fewer physical constraints, fNIRS enables studying of the human brain at versatile environment and various body positions, including at bed side and during exercise, which complements the use of functional magnetic resonance imaging (fMRI). However, like fMRI, fNIRS imaging can be influenced by the presence of a strong global component. Yet, the nature of the global signal in fNIRS has not been established. In this study, we investigated the relationship between fNIRS global signal and electroencephalogram (EEG) vigilance using simultaneous recordings in resting healthy subjects in high-density and whole-head montage. In Experiment 1, data were acquired at supine, sitting, and standing positions. Results found that the factor of body positions significantly affected the amplitude of the resting-state fNIRS global signal, prominently in the frequency range of 0.05–0.1 Hz but not in the very low frequency range of less than 0.05 Hz. As a control, the task-induced fNIRS or EEG responses to auditory stimuli did not differ across body positions. However, EEG vigilance plays a modulatory role in the fNIRS signals in the frequency range of less than 0.05 Hz: resting-state sessions of low EEG vigilance measures are associated with high amplitudes of fNIRS global signals. Moreover, in Experiment 2, we further examined the epoch-to-epoch fluctuations in concurrent fNIRS and EEG data acquired from a separate group of subjects and found a negative temporal correlation between EEG vigilance measures and fNIRS global signal amplitudes. Our study for the first time revealed that vigilance as a neurophysiological factor modulates the resting-state dynamics of fNIRS, which have important implications for understanding and processing the noises in fNIRS signals.

An Active Concentric Electrode for Concurrent EEG Recording and Body-Coupled Communication (BCC) Data Transmission.

This paper presents a wearable active concentric electrode for concurrent EEG monitoring and Body-Coupled Communication (BCC) data transmission. A three-layer concentric electrode eliminates the usage of wires. A common mode averaging unit (CMAU) is proposed to cancel not only the continuous common-mode interference (CMI) but also the instantaneous CMI of up to 51Vpp. The localized potential matching technique removes the ground electrode. An open-loop programmable gain amplifier (OPPGA) with the pseudo-resistor-based RC-divider block is presented to save the silicon area. The presented work is the first reported so far to achieve the concurrent EEG signal recording and BCC-based data transmission. The proposed chip achieves 100dB CMRR and 110dB PSRR, occupies 0.044 mm2, and consumes 7.4μW with an input-referred noise density of 26nV/√Hz.

Face processing in free viewing visual search: An investigation using concurrent EEG and eye movement recordings

Face processing in free viewing visual search: An investigation using concurrent EEG and eye movement recordings

Concurrent EEG monitoring helps interpret neuropsychological testing results in patients with epilepsy

ObjectiveWe sought to determine if global cognitive function in patients with epilepsy (PWE) differs when electroencephalographic (EEG) abnormalities are present during concurrent neuropsychological (NP) evaluation. MethodsWe explored the association between subclinical epileptiform discharges (sEDs) and interictal epileptiform discharges (IEDs) and global aspects of cognition in 79 consecutive PWE who underwent continuous EEG monitoring during NP evaluation for diagnostic (15%) or presurgical (85%) purposes while on their standard antiseizure medication (ASM) regimens. As some researchers have suggested that the apparent link between IEDs and cognition represent epiphenomena of an underlying damaged neural substrate, we used functional status as a stratifying covariate to allow us to address this position. ResultsDespite being on their standard ASM regimen, EEG was abnormal in 68% of patients. Epileptiform abnormalities (IEDs, sEDs, or both) were seen in isolation or coupled with diffuse or focal slowing in 38% of patients. Individuals with IEDs occurring during their NP evaluation demonstrated poorer scores in attention/working memory (forward and backward digit span), processing speed (symbol searching and coding), and speeded components of language (semantic fluency) tests compared with those with normal EEG tracings matched by their real-world, functional status. In two high functioning patients, performance was significantly better when these individuals were tested in the absence of IEDs, with performances appearing invalid when tested during periods of IED activity. No significant association was found between NP performance and nonepileptiform EEG abnormalities. SignificanceA substantial proportion of PWE undergoing NP evaluation manifest concurrent EEG abnormalities, with epileptiform abnormalities associated with poorer global cognitive performance. As this pattern was observed regardless of functional status, this association appears to represent more than unrelated features coincidentally shared by the lowest functioning cohort. Coupled with our individual case data, our findings suggest that NP testing may be adversely affected by IEDs and sEDs going unrecognized in the absence of simultaneous EEG recordings, and set the stage for future studies to definitively establish this possible relationship.

Concurrent EEG- and fMRI-derived functional connectomes exhibit linked dynamics

Long-range connectivity has become the most studied feature of human functional Magnetic Resonance Imaging (fMRI), yet the spatial and temporal relationship between its whole-brain dynamics and electrophysiological connectivity remains largely unknown. FMRI-derived functional connectivity exhibits spatial reconfigurations or time-varying dynamics at infraslow (<0.1Hz) speeds. Conversely, electrophysiological connectivity is based on cross-region coupling of fast oscillations (~1–100Hz). It is unclear whether such fast oscillation-based coupling varies at infraslow speeds, temporally coinciding with infraslow dynamics across the fMRI-based connectome. If so, does the association of fMRI-derived and electrophysiological dynamics spatially vary over the connectome across the functionally distinct electrophysiological oscillation bands? In two concurrent electroencephalography (EEG)-fMRI resting-state datasets, oscillation-based coherence in all canonical bands (delta through gamma) indeed reconfigured at infraslow speeds in tandem with fMRI-derived connectivity changes in corresponding region-pairs. Interestingly, irrespective of EEG frequency-band the cross-modal tie of connectivity dynamics comprised a large proportion of connections distributed across the entire connectome. However, there were frequency-specific differences in the relative strength of the cross-modal association. This association was strongest in visual to somatomotor connections for slower EEG-bands, and in connections involving the Default Mode Network for faster EEG-bands. Methodologically, the findings imply that neural connectivity dynamics can be reliably measured by fMRI despite heavy susceptibility to noise, and by EEG despite shortcomings of source reconstruction. Biologically, the findings provide evidence that contrast with known territories of oscillation power, oscillation coupling in all bands slowly reconfigures in a highly distributed manner across the whole-brain connectome.

Conducting Concurrent Electroencephalography and Functional Near-Infrared Spectroscopy Recordings with a Flanker Task.

Concurrent EEG and fNIRS recordings offer an excellent opportunity to gain a full understanding of the neural mechanism of cognitive processing by inspecting the relationship between the neural and hemodynamic signals. EEG is an electrophysiological technology that can measure the rapid neuronal activity of the cortex, whereas fNIRS relies on the hemodynamic responses to infer brain activation. The combination of EEG and fNIRS neuroimaging techniques can identify more features and reveal more information associated with the functioning of the brain. In this protocol, fused EEG-fNIRS measurements were performed for concurrent recordings of evoked-electrical potentials and hemodynamic responses during a Flanker task. In addition, the critical steps for setting up the hardware and software system as well as the procedures for data acquisition and analysis were provided and discussed in detail. It is expected that the present protocol can pave a new avenue for improving the understanding of the neural mechanisms underlying various cognitive processes by using the EEG and fNIRS signals.

Concurrent electrophysiological and hemodynamic measurements of evoked neural oscillations in human visual cortex using sparsely interleaved fast fMRI and EEG

Electroencephalography (EEG) concurrently collected with functional magnetic resonance imaging (fMRI) is heavily distorted by the repetitive gradient coil switching during the fMRI acquisition. The performance of the typical template-based gradient artifact suppression method can be suboptimal because the artifact changes over time. Gradient artifact residuals also impede the subsequent suppression of ballistocardiography artifacts.Here we propose recording continuous EEG with temporally sparse fast fMRI (fast fMRI-EEG) to minimize the EEG artifacts caused by MRI gradient coil switching without significantly compromising the field-of-view and spatiotemporal resolution of fMRI. Using simultaneous multi-slice inverse imaging to achieve whole-brain fMRI with isotropic 5-mm resolution in 0.1 ​s, and performing these acquisitions once every 2 ​s, we have 95% of the duty cycle available to record EEG with substantially less gradient artifact. We found that the standard deviation of EEG signals over the entire acquisition period in fast fMRI-EEG was reduced to 54% of that in conventional concurrent echo-planar imaging (EPI) and EEG recordings (EPI-EEG) across participants. When measuring 15-Hz steady-state visual evoked potentials (SSVEPs), the baseline-normalized oscillatory neural response in fast fMRI-EEG was 2.5-fold of that in EPI-EEG. The functional MRI responses associated with the SSVEP delineated by EPI and fast fMRI were similar in the spatial distribution, the elicited waveform, and detection power. Sparsely interleaved fast fMRI-EEG provides high-quality EEG without substantially compromising the quality of fMRI in evoked response measurements, and has the potential utility for applications where the onset of the target stimulus cannot be precisely determined, such as epilepsy.

Performance Monitoring during Visual Priming.

Repetitive performance of single-feature (efficient or pop-out) visual search improves RTs and accuracy. This phenomenon, known as priming of pop-out, has been demonstrated in both humans and macaque monkeys. We investigated the relationship between performance monitoring and priming of pop-out. Neuronal activity in the supplementary eye field (SEF) contributes to performance monitoring and to the generation of performance monitoring signals in the EEG. To determine whether priming depends on performance monitoring, we investigated spiking activity in SEF as well as the concurrent EEG of two monkeys performing a priming of pop-out task. We found that SEF spiking did not modulate with priming. Surprisingly, concurrent EEG did covary with priming. Together, these results suggest that performance monitoring contributes to priming of pop-out. However, this performance monitoring seems not mediated by SEF. This dissociation suggests that EEG indices of performance monitoring arise from multiple, functionally distinct neural generators.

Selective effects of acute low-grade inflammation on human visual attention

Illness is often accompanied by perceived cognitive sluggishness, a symptom that may stem from immune system activation. The current study used electroencephalography (EEG) to assess how inflammation affected three different distinct attentional processes: alerting, orienting and executive control. In a double-blinded placebo-controlled within-subjects design (20 healthy males, mean age = 24.5, SD = 3.4), Salmonella typhoid vaccination (0.025 mg; Typhim Vi, Sanofi Pasteur) was used to induce transient mild inflammation, while a saline injection served as a placebo-control. Participants completed the Attention Network Test with concurrent EEG recorded 6 h post-injection. Analyses focused on behavioral task performance and on modulation of oscillatory EEG activity in the alpha band (9–12 Hz) for alerting as well as orienting attention and frontal theta band (4–8 Hz) for executive control. Vaccination induced mild systemic inflammation, as assessed by interleukin-6 (IL-6) levels. While no behavioral task performance differences between the inflammation and placebo condition were evident, inflammation caused significant alterations to task-related brain activity. Specifically, inflammation produced greater cue-induced suppression of alpha power in the alerting aspect of attention and individual variation in the inflammatory response was significantly correlated with the degree of alpha power suppression. Notably, inflammation did not affect orienting (i.e., alpha lateralization) or executive control (i.e., frontal theta activity). These results reveal a unique neurophysiological sensitivity to acute mild inflammation of the neural network that underpins attentional alerting functions. Observed in the absence of performance decrements, these novel findings suggest that acute inflammation requires individuals to exert greater cognitive effort when preparing for a task in order to maintain adequate behavioral performance.

Joint analysis of frontal theta synchrony and white matter following mild traumatic brain injury.

Some of the most disabling aspects of mild traumatic brain injury (mTBI) include lingering deficits in executive functioning. It is known that mTBI can damage white matter tracts, but it remains unknown how this structural brain damage translates into cognitive deficits. This experiment utilized theta band phase synchrony to identify the dysfunctional neural operations that contribute to cognitive problems following mTBI. Sub-acute stage (< 2weeks) mTBI patients (N = 52) and healthy matched controls (N = 32) completed a control-demanding task with concurrent EEG. Structural MRI was also collected. While there were no performance-specific behavioral differences between groups in the dot probe expectancy task, the degree of theta band phase synchrony immediately following injury predicted the degree of symptom recovery two months later. Although there were no differences in fractional anisotropy (FA) between groups, joint independent components analysis revealed that a smaller network of lower FA-valued voxels contributed to a diminished frontal theta phase synchrony network in the mTBI group. This finding suggests that frontal theta band markers of cognitive control are sensitive to sub-threshold structural aberrations following mTBI.

Competitive Frontoparietal Interactions Mediate Implicit Inferences.

Frequent experience with regularities in our environment allows us to use predictive information to guide our decision process. However, contingencies in our environment are not always explicitly present and sometimes need to be inferred. Heretofore, it remained unknown how predictive information guides decision-making when explicit knowledge is absent and how the brain shapes such implicit inferences. In the present experiment, 17 human participants (9 females) performed a discrimination task in which a target stimulus was preceded by a predictive cue. Critically, participants had no explicit knowledge that some of the cues signaled an upcoming target, allowing us to investigate how implicit inferences emerge and guide decision-making. Despite unawareness of the cue-target contingencies, participants were able to use implicit information to improve performance. Concurrent EEG recordings demonstrate that implicit inferences rely upon interactions between internally and externally oriented networks, whereby prefrontal regions inhibit parietal cortex under internal implicit control.SIGNIFICANCE STATEMENT Regularities in our environment can guide our behavior providing information about upcoming events. Interestingly, such predictive information does not need to be explicitly represented to effectively guide our decision process. Here, we show how the brain engages in such real-world "data mining" and how implicit inferences emerge. We used a contingency cueing task and demonstrated that implicit inferences influenced responses to subsequent targets despite a lack of awareness of cue-target contingencies. Further, we show that these implicit inferences emerge through interactions between internally and externally oriented neural networks. The current results highlight the importance of prefrontal processes in transforming external events into predictive internalized models of the world.

Aerobic exercise modulates transfer and brain signal complexity following cognitive training

Although recent evidence has demonstrated the potent effect of physical exercise to increase the efficacy of cognitive training, the neural mechanisms underlying this causal relationship remain unclear. Here, we used multiscale entropy (MSE) of electroencephalography (EEG)—a measure of brain signal complexity—to address this issue. Young males were randomly assigned to either a 20-day dual n-back training following aerobic exercise or the same training regimen following a reading. A feature binding working memory task with concurrent EEG recording was used to test for transfer effects. Although results revealed weak-to-moderate evidence for exercise-induced facilitation on cognitive training, the combination of cognitive training with exercise resulted in greater transfer gains on conditions involving greater attentional demanding, together with greater increases in cognitive modulation on MSE, compared with the reading condition. Overall, our findings suggest that the addition of antecedent physical exercise to brain training regimen could enable wider, more robust improvements.

The influence of aerobic fitness on top-down and bottom-up mechanisms of interference control.

Extensive evidence has demonstrated the relationship between aerobic fitness and cognitive function in early adulthood. Little is known, however, about whether the cognitive benefits of aerobic fitness are related to the modulation of top-down or bottom-up mechanisms in the control of executive attention. The present study aimed to shed light on this question by evaluating the phase-locking factor (PLF) of electroencephalogram (EEG) signal during cognitive control. Higher fit and lower fit young adults performed a neuropsychological test of cognitive control (i.e., Stroop color-naming task) with concurrent EEG recording. In line with previous literature, behavioral results showed that higher fit individuals performed better on the Stroop task overall. Interestingly, beta phase synchronization was larger during the incongruent condition than the congruent condition for higher fit but not for lower fit individuals, suggesting a more effective use of top-down control in the former. However, no such effect was seen for gamma activity, indicating that bottom-up mechanisms are unlikely to account for the differences in performance explained by fitness levels. Altogether, these findings suggest that the greater cognitive control observed in higher fit individuals is associated with differences in the control of top-down rather than bottom-up processing, consistent with the hypothesis of selective improvement. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Multiple Dissociations Between Comorbid Depression and Anxiety on Reward and Punishment Processing: Evidence From Computationally Informed EEG.

In this report, we provide the first evidence that mood and anxiety dimensions are associated with unique aspects of EEG responses to reward and punishment, respectively. We reanalyzed data from our prior publication of a categorical depiction of depression to address more sophisticated dimensional hypotheses. Highly symptomatic depressed individuals (N = 46) completed a probabilistic learning task with concurrent EEG. Measures of anxiety and depression symptomatology were significantly correlated with each other; however, only anxiety predicted better avoidance learning due to a tighter coupling of negative prediction error signaling with punishment-specific EEG features. In contrast, depression predicted a smaller reward-related EEG feature, but this did not affect prediction error coupling or the ability to learn from reward. We suggest that this reward-related alteration reflects motivational or hedonic aspects of reward and not a diminishment in the ability to represent the information content of reinforcements. These findings compel further research into the domain-specific neural systems underlying dimensional aspects of psychiatric disease.

Constrained temporal parallel decomposition for EEG-fMRI fusion

Objective. Multimodal neuroimaging has become a common practice in neuroscience research. Simultaneous EEG–fMRI is a popular multimodal recording approach due to the complementary spatiotemporal relationship between the two modalities. Several data fusion techniques have been proposed in the literature for EEG-fMRI fusion, including joint-ICA and parallel-ICA frameworks. Previous EEG–fMRI fusion approaches have used sensor-level EEG features. Recently, we introduced source-space ICA for EEG–MEG source reconstruction and component identification, which was shown to be a superior alternative to sensor-space ICA. Approach. Here, we extend source-space ICA to the fusion of EEG–fMRI data. Additionally, we incorporate the use of a paradigm signal (constrained) and a lag-based signal decomposition approach to accommodate recent findings demonstrating the potentially variable lag structure between electrophysiological and BOLD signals. We evaluated this method on simulated concurrent EEG–fMRI during a boxcar task design, as well as real concurrent EEG–fMRI data from three participants performing an N-Back working memory task. The block diagram of the algorithm and corresponding source codes are provided. Main results. Based on the results of the real working memory task, for all three subjects, one frontal theta component, and one right posterior alpha component had the highest contribution coefficients (~0.5) to the paradigm-related fused component. There were also two more alpha band components with contribution coefficients of 0.3. The highest contributing fMRI component (~0.8) was one known in the literature to be related to the attention network. The second fMRI component was related to the well-known default mode network, with a contribution coefficient of 0.3. Significance. The proposed EEG–fMRI fusion approach, is capable of estimating the brain maps of the EEG and fMRI for the fused components and account for the variable lag structure between electrophysiological and BOLD signals.