@article{wang2025study,

title = {Study on cognitive impairment evaluation based on photoelectric neural information},

author = {Zehua Wang and Ye Zhang and Ning Ma and Huiting Qiao and Meiyun Xia and Deyu Li},

doi = {https://doi.org/10.1177/25424823251325537},

year  = {2025},

date = {2025-03-21},

urldate = {2025-01-01},

journal = {Journal of Alzheimer's Disease Reports},

volume = {9},

pages = {25424823251325537},

publisher = {SAGE Publications Sage UK: London, England},

abstract = {Background

Whether there is a cognitive load-dependent brain activation pattern in the pre-Alzheimer's disease phase is unknown. Multimodal system provides a powerful technical tool.

Objective

We evaluated brain activity patterns under different cognitive loads in patients with mild cognitive impairment.

Methods

Functional near-infrared spectroscopy signals and electroencephalography signals were acquired from the mild cognitive impairment group (MCI, n = 20) and the healthy control group (HC, n = 24) under four cognitive loads. We analyzed the respective brain activity features and performed correlation analyses.

Results

(1) During the encoding phase, both the left occipital (pcond = 0.05, pgroup < 0.01) and left temporal (pcond = 0.02, pgroup = 0.03) skewness condition effects and between-group effects were significant. (2) As the cognitive load increased, the clustering coefficients and local efficiencies were significantly lower for the HC group. (3) The left occipital and left temporal activation skewness in the MCI group were significantly correlated with left occipital electrical features, whereas the left occipital activation intensity and skewness were significantly correlated with left occipital electrical features in HC group.

Conclusions

The pattern of brain activity in MCI depends on cognitive load. Left occipital and left temporal may be important brain regions for evaluating MCI and need to be focused on in the future.},

keywords = {Biomarker, DSI-7},

pubstate = {published},

tppubtype = {article}

}

@article{calvo2025deep,

title = {Deep Learning-Driven EEG Analysis for Personalized Deep Brain Stimulation Programming in Parkinson's Disease},

author = {Nicolas Calvo Peiro and Mathias Ramm Haugland and Alena Kutuzova and Cosima Graef and Aminata Bocum and Yen Foung Tai and Anastasia Borovykh and Shlomi Haar},

doi = {https://doi.org/10.1101/2025.02.11.25321886},

year  = {2025},

date = {2025-02-13},

urldate = {2025-01-01},

journal = {medRxiv},

pages = {2025–02},

publisher = {Cold Spring Harbor Laboratory Press},

abstract = {Deep Brain Stimulation (DBS) is an invasive procedure used to alleviate motor symptoms in Parkinson’s Disease (PD) patients. While brain activity can be used to optimise DBS parameters, the impact of DBS parameters on brain activity remains unclear. We aimed to identify the cortical neural response to changes in DBS parameters, which are sensitive to the effect of small changes in the stimulation parameters and could be used as neural biomarkers. We recorded in-clinic EEG data from seven hemispheres of PD patients during DBS programming sessions.



Here we developed a siamese adaptation of the EEGNet deep learning architecture and trained it to distinguish whether two short (1-sec-long) segments of brain activity were taken with the same stimulation parameters, or if either the strength or location of the stimulation had changed. 13 independent models were trained independently in each hemisphere for stimulation amplitude or contact, and all achieved high accuracy with an average of 78%. Our models are sensitive to changes in brain activity recorded at the scalp of the patients following changes as small as 0.3mA in the DBS parameters.



Next, we interpreted what our black-box AI models learned with an ablation-based explainability method, that extracts frequency bands learned by the models through a perturbation of the input’s frequency spectrum. We found that fast Narrow-Band Gamma oscillations (60-90Hz), contributed most to the models across all 7 hemispheres.



This work, using a data-driven approach, joins a recent body of evidence suggesting cortical Narrow-Band Gamma activity as the potential range for digital biomarkers for DBS optimization.},

keywords = {Biomarker, DSI-7, Neuromodulation},

pubstate = {published},

tppubtype = {article}

}

@article{al2024brain,

title = {Brain Functional Connectivity During Stroop Task and CSF Amyloid/tau in Cognitively Healthy Individuals},

author = {Abdulhakim Al-Ezzi and Natalie Astraea and J Yu and Xiaomeng Wu and Alfred N Fonteh and Yafa Minazad and Robert A Kloner and Xianghong Arakaki},

doi = {https://doi.org/10.1002/alz.090859},

year  = {2025},

date = {2025-01-09},

urldate = {2024-01-09},

journal = {Alzheimer's & Dementia},

volume = {20},

pages = {e090859},

publisher = {Wiley Online Library},

abstract = {Background

At the pre-clinical stages of Alzheimer’s disease (AD) development, the accumulation of amyloid-β (Aβ) and tau induces neural toxicity, synaptic dysfunction, and excitation/inhibition instability of neural network activity, leading to cognitive decline. However, the effects of Aβ/tau accumulation on electroencephalography (EEG) functional connectivity (FC) in cognitively healthy (CH) individuals during a cognitive challenge have not been elucidated. Therefore, the main objective of this work is to evaluate the association between Aβ/tau level and brain FC during a cognitive challenge in CH individuals.



Method

Established EEG data was recorded using a 21-EEG sensor headset (Wearable Sensing, DSI-24) during a cognitive challenge (Stroop interference test). Amyloid-β and total-tau proteins were measured from cerebrospinal fluid (CSF) using electrochemiluminescence. We assessed FC at sensor level using Partial Directed Coherence (PDC) from EEG data of CH participants including 22 normal CSF Aβ/tau ratio (CH-NAT) and 24 pathological CSF Aβ/tau (CH-PAT). For each trial type (congruent or incongruent) in the Stroop task and each of 19 sensors, linear regression was used to estimate the difference in mean FC between CH-NAT and CH-PAT, while controlling for age, gender, and years of education. The Benjamini–Hochberg procedure was used to control the false discovery rate below q = .1.



Result

Compared with CH-NATs, CH-PATs exhibit higher causal connectivity at specific sensors which each had an estimated local effect size index Cohen’s f2 >0.15, and putatively represent brain regions including medial prefrontal cortex (Fz, Fp1, and F8), central cortex (Cz and C4), and posterior cingulate cortex (Pz). For each of the same sensors, the estimated difference between CH-NAT and CH-PAT had an adjusted P value below .1.



Conclusion

These findings suggest a potential association between the CSF Aβ42/tau pathology and differences between individuals in brain connectivity during a cognitive challenge. These differences may involve compensatory mechanisms as the brain adapts to the amyloid/tau pathology. These results provide potential insights into the neurobiological implications of varying CSF amyloid/tau on brain networks. The areas with estimated medium-to-large effect sizes are favorable to doing a study with a lower significance level to confirm the findings.},

keywords = {Biomarker, DSI-24},

pubstate = {published},

tppubtype = {article}

}

@article{al2024disrupted,

title = {Disrupted brain functional connectivity as early signature in cognitively healthy individuals with pathological CSF amyloid/tau},

author = {Abdulhakim Al-Ezzi and Rebecca J Arechavala and Ryan Butler and Anne Nolty and Jimmy J Kang and Shinsuke Shimojo and Daw-An Wu and Alfred N Fonteh and Michael T Kleinman and Robert A Kloner and others},

doi = {https://doi.org/10.1038/s42003-024-06673-w},

year  = {2024},

date = {2024-08-23},

urldate = {2024-01-01},

journal = {Communications Biology},

volume = {7},

number = {1},

pages = {1037},

publisher = {Nature Publishing Group UK London},

abstract = {Alterations in functional connectivity (FC) have been observed in individuals with Alzheimer’s disease (AD) with elevated amyloid (Aβ) and tau. However, it is not yet known whether directed FC is already influenced by Aβ and tau load in cognitively healthy (CH) individuals. A 21-channel electroencephalogram (EEG) was used from 46 CHs classified based on cerebrospinal fluid (CSF) Aβ tau ratio: pathological (CH-PAT) or normal (CH-NAT). Directed FC was estimated with Partial Directed Coherence in frontal, temporal, parietal, central, and occipital regions. We also examined the correlations between directed FC and various functional metrics, including neuropsychology, cognitive reserve, MRI volumetrics, and heart rate variability between both groups. Compared to CH-NATs, the CH-PATs showed decreased FC from the temporal regions, indicating a loss of relative functional importance of the temporal regions. In addition, frontal regions showed enhanced FC in the CH-PATs compared to CH-NATs, suggesting neural compensation for the damage caused by the pathology. Moreover, CH-PATs showed greater FC in the frontal and occipital regions than CH-NATs. Our findings provide a useful and non-invasive method for EEG-based analysis to identify alterations in brain connectivity in CHs with a pathological versus normal CSF Aβ/tau.},

keywords = {Biomarker, DSI-24},

pubstate = {published},

tppubtype = {article}

}

@article{chan2023effects,

title = {Effects of multisession cathodal transcranial direct current stimulation with cognitive training on sociocognitive functioning and brain dynamics in ASD: A double-blind, sham-controlled, randomized EEG study},

author = {Melody MY Chan and Coco XT Choi and Tom CW Tsoi and Caroline KS Shea and Klaire WK Yiu and Yvonne MY Han},

doi = {https://doi.org/10.1016/j.brs.2023.10.012},

year  = {2023},

date = {2023-10-31},

urldate = {2023-01-01},

journal = {Brain Stimulation},

volume = {16},

issue = {8},

pages = {P1604-1616},

publisher = {Elsevier},

abstract = {Background

Few treatment options are available for targeting core symptoms of autism spectrum disorder (ASD). The development of treatments that target common neural circuit dysfunctions caused by known genetic defects, namely, disruption of the excitation/inhibition (E/I) balance, is promising. Transcranial direct current stimulation (tDCS) is capable of modulating the E/I balance in healthy individuals, yet its clinical and neurobiological effects in ASD remain elusive.



Objective

This double-blind, randomized, sham-controlled trial investigated the effects of multisession cathodal prefrontal tDCS coupled with online cognitive remediation on social functioning, information processing efficiency and the E/I balance in ASD patients aged 14–21 years.



Methods

Sixty individuals were randomly assigned to receive either active or sham tDCS (10 sessions in total, 20 min/session, stimulation intensity: 1.5 mA, cathode: F3, anode: Fp2, size of electrodes: 25 cm2) combined with 20 min of online cognitive remediation. Social functioning, information processing efficiency during cognitive tasks, and theta- and gamma-band E/I balance were measured one day before and after the treatment.



Results

Compared to sham tDCS, active cathodal tDCS was effective in enhancing overall social functioning [F(1, 58) = 6.79, p = .012, ηp2 = 0.105, 90% CI: (0.013, 0.234)] and information processing efficiency during cognitive tasks [F(1, 58) = 10.07, p = .002, ηp2 = 0.148, 90% CI: (0.034, 0.284)] in these individuals. Electroencephalography data showed that this cathodal tDCS protocol was effective in reducing the theta-band E/I ratio of the cortical midline structures [F(1, 58) = 4.65, p = .035, ηp2 = 0.074, 90% CI: (0.010, 0.150)] and that this reduction significantly predicted information processing efficiency enhancement (b = −2.546, 95% BCa CI: [-4.979, −0.113], p = .041).



Conclusion

Our results support the use of multisession cathodal tDCS over the left dorsolateral prefrontal cortex combined with online cognitive remediation for reducing the elevated theta-band E/I ratio in sociocognitive information processing circuits in ASD patients, resulting in more adaptive regulation of global brain dynamics that is associated with enhanced information processing efficiency after the intervention.},

keywords = {Biomarker, DSI-24, Neuromodulation},

pubstate = {published},

tppubtype = {article}

}

@article{riek2023feedback,

title = {Feedback Related Negativity Amplitude is Greatest Following Deceptive Feedback in Autistic Adolescents},

author = {Nathan T Riek and Busra T Susam and Caitlin M Hudac and Caitlin M Conner and Murat Akcakaya and Jane Yun and Susan W White and Carla A Mazefsky and Philip A Gable},

url = {https://link.springer.com/article/10.1007/s10803-023-06038-y},

year  = {2023},

date = {2023-07-01},

urldate = {2023-01-01},

journal = {Journal of Autism and Developmental Disorders},

pages = {1–11},

publisher = {Springer},

abstract = {The purpose of this study is to investigate if feedback related negativity (FRN) can capture instantaneous elevated emotional reactivity in autistic adolescents. A measurement of elevated reactivity could allow clinicians to better support autistic individuals without the need for self-reporting or verbal conveyance. The study investigated reactivity in 46 autistic adolescents (ages 12–21 years) completing the Affective Posner Task which utilizes deceptive feedback to elicit distress presented as frustration. The FRN event-related potential (ERP) served as an instantaneous quantitative neural measurement of emotional reactivity. We compared deceptive and distressing feedback to both truthful but distressing feedback and truthful and non-distressing feedback using the FRN, response times in the successive trial, and Emotion Dysregulation Inventory (EDI) reactivity scores. Results revealed that FRN values were most negative to deceptive feedback as compared to truthful non-distressing feedback. Furthermore, distressing feedback led to faster response times in the successive trial on average. Lastly, participants with higher EDI reactivity scores had more negative FRN values for non-distressing truthful feedback compared to participants with lower reactivity scores. The FRN amplitude showed changes based on both frustration and reactivity. The findings of this investigation support using the FRN to better understand emotion regulation processes for autistic adolescents in future work. Furthermore, the change in FRN based on reactivity suggests the possible need to subgroup autistic adolescents based on reactivity and adjust interventions accordingly.},

keywords = {Biomarker, DSI-24},

pubstate = {published},

tppubtype = {article}

}

@article{kim2023characteristic,

title = {Characteristic Behaviors of Elementary Students in a Low Attention State During Online Learning Identified Using Electroencephalography},

author = {Suhye Kim and Jung-Hwan Kim and Wooseok Hyung and Suhkyung Shin and Myoung Jin Choi and Dong Hwan Kim and Chang-Hwan Im},

doi = {10.1109/TLT.2023.3289498},

year  = {2023},

date = {2023-06-29},

urldate = {2023-01-01},

journal = {IEEE Transactions on Learning Technologies},

publisher = {IEEE},

abstract = {With the widespread application of online education platforms, the necessity for identifying learner's mental states from webcam videos is increasing as it can be potentially applied to artificial intelligence-based automatic identification of learner's states. However, the behaviors that elementary school students frequently exhibit during online learning particularly when they are in a low attention state have rarely been investigated. This study employed electroencephalography (EEG) to continuously track changes in the learner's attention state during online learning. A new EEG index reflecting elementary students' attention level was developed using an EEG dataset acquired from 30 fourth graders during a computerized d2 test of attention. Characteristic behaviors of 24 elementary students in a low attention state were then identified from the webcam videos showing their upper bodies captured during 40-minute online lectures, with the proposed EEG index being used as a reference to determine their attention level at the time. Various characteristic behaviors were identified regarding participant's mouth, head, arms, and torso. For example, opening mouth or leaning back was observed more frequently in a low attention state than in a high attention state. It is expected that the characteristic behaviors reflecting learner's low attention state would be utilized as a useful reference in developing more interactive and effective online education systems.},

keywords = {Biomarker, DSI-24},

pubstate = {published},

tppubtype = {article}

}

@article{chen2023classification,

title = {A Classification Framework Based on Multi-modal Features for Detection of Cognitive Impairments},

author = {Sheng Chen and Haiqun Xie and Hongjun Yang and Chenchen Fan and Zengguang Hou and Chutian Zhang},

url = {https://link.springer.com/chapter/10.1007/978-981-99-0301-6_27},

year  = {2023},

date = {2023-02-18},

urldate = {2023-01-01},

booktitle = {Intelligent Robotics: Third China Annual Conference, CCF CIRAC 2022, Xi’an, China, December 16--18, 2022, Proceedings},

journal = {Intelligent Robotics: Third China Annual Conference, CCF CIRAC 2022},

pages = {349--361},

organization = {Springer},

abstract = {Mild cognitive impairment (MCI) is the preliminary stage of dementia, and has a high risk of progression to Alzheimer’s disease (AD) in the elderly. Early detection of MCI plays a vital role in preventing progression of AD. Clinical diagnosis of MCI requires many examinations, which are highly demanding on hospital equipment and expensive for patients. Electroencephalography (EEG) offers a non-invasive and less expensive way to diagnose MCI early. In this paper, we propose a multi-modal fusion classification framework for MCI detection. We collect EEG data using a delayed match-to-sample task and analyze the differences between the two groups. Based on analysis results, we extract Power spectral density (PSD), PSD enhanced, Event-related potential (ERP) features in EEG signal along with physiological features and behavioral features of the subjects to classify MCI and healthy elderly. By comparing the effect of different features on classification performance, we find that the time-domain based ERP features are better than the frequency-domain based PSD or PSD enhanced features to overcome inter-individual differences to distinguish MCI, and these two features have good complementarity, fusing ERP and PSD enhanced features can greatly improve the classification accuracy to 84.74%. The final result shows that MCI and healthy elderly can be well classified by using this framework.},

keywords = {Biomarker, DSI-24},

pubstate = {published},

tppubtype = {article}

}

@article{ocay2022electroencephalographic,

title = {Electroencephalographic characteristics of children and adolescents with chronic musculoskeletal pain},

author = {Don Daniel Ocay and Elizabeth F Teel and Owen D Luo and Chloé Savignac and Yacine Mahdid and Stefanie Blain-Moraes and Catherine E Ferland},

url = {https://journals.lww.com/painrpts/Fulltext/2022/12000/Electroencephalographic_characteristics_of.17.aspx},

year  = {2022},

date = {2022-12-01},

urldate = {2022-12-01},

journal = {PAIN Reports},

volume = {7},

number = {6},

pages = {e1054},

publisher = {LWW},

abstract = {Introduction: 

The pathophysiology of pediatric musculoskeletal (MSK) pain is unclear, contributing to persistent challenges to its management.



Objectives: 

This study hypothesizes that children and adolescents with chronic MSK pain (CPs) will show differences in electroencephalography (EEG) features at rest and during thermal pain modalities when compared with age-matched controls.



Methods: 

One hundred forty-two CP patients and 45 age-matched healthy controls (HCs) underwent a standardized thermal tonic heat and cold stimulations, while a 21-electrode headset collected EEG data. Cohorts were compared with respect to their EEG features of spectral power, peak frequency, permutation entropy, weight phase-lag index, directed phase-lag index, and node degree at 4 frequency bands, namely, delta (1–4 Hz), theta (4–8 Hz), alpha (8–13 Hz), and beta (13–30 Hz), at rest and during the thermal conditions.



Results: 

At rest, CPs showed increased global delta (P = 0.0493) and beta (P = 0.0002) power in comparison with HCs. These findings provide further impetus for the investigation and prevention of long-lasting developmental sequalae of early life chronic pain processes. Although no cohort differences in pain intensity scores were found during the thermal pain modalities, CPs and HCs showed significant difference in changes in EEG spectral power, peak frequency, permutation entropy, and network functional connectivity at specific frequency bands (P < 0.05) during the tonic heat and cold stimulations.



Conclusion: 

This suggests that EEG can characterize subtle differences in heat and cold pain sensitivity in CPs. The complementation of EEG and evoked pain in the clinical assessment of pediatric chronic MSK pain can better detect underlying pain mechanisms and changes in pain sensitivity.},

keywords = {Biomarker, DSI-24},

pubstate = {published},

tppubtype = {article}

}

@article{rustamov2022relief,

title = {Relief of chronic pain associated with increase in midline frontal theta power},

author = {Nabi Rustamov and Elizabeth A Wilson and Alexandra E Fogarty and Lara W Crock and Eric C Leuthardt and Simon Haroutounian},

doi = {10.1097/PR9.0000000000001040},

year  = {2022},

date = {2022-10-10},

urldate = {2022-01-01},

journal = {Pain Reports},

volume = {7},

number = {6},

publisher = {Wolters Kluwer Health},

abstract = {Introduction:

There is a need to identify objective cortical electrophysiological correlates for pain relief that could potentially contribute to a better pain management. However, the field of developing brain biomarkers for pain relief is still largely underexplored.



Objectives:

The objective of this study was to investigate cortical electrophysiological correlates associated with relief from chronic pain. Those features of pain relief could serve as potential targets for novel therapeutic interventions to treat pain.



Methods:

In 12 patients with chronic pain in the upper or lower extremity undergoing a clinically indicated nerve block procedure, brain activity was recorded by means of electroencephalogram before and 30 minutes after the nerve block procedure. To determine the specific cortical electrophysiological correlates of relief from chronic pain, 12 healthy participants undergoing cold-pressor test to induce experimental acute pain were used as a control group. The data were analyzed to characterize power spectral density patterns of pain relief and identify their source generators at cortical level.



Results:

Chronic pain relief was associated with significant delta, theta, and alpha power increase at the frontal area. However, only midfrontal theta power increase showed significant positive correlation with magnitude of reduction in pain intensity. The sources of theta power rebound were located in the left dorsolateral prefrontal cortex (DLPFC) and midline frontal cortex. Furthermore, theta power increase in the midline frontal cortex was significantly higher with chronic vs acute pain relief.



Conclusion:

These findings may provide basis for targeting chronic pain relief via modulation of the midline frontal theta oscillations.},

keywords = {Biomarker, DSI-24},

pubstate = {published},

tppubtype = {article}

}

@article{schneefeld2022salient,

title = {Salient 40 Hz sounds probe affective aversion and neural excitability},

author = {F Schneefeld and K Doelling and S Marchesotti and S Schwartz and K Igloi and AL Giraud and LH Arnal},

doi = {https://doi.org/10.1101/2022.02.26.482077},

year  = {2022},

date = {2022-03-01},

urldate = {2022-01-01},

journal = {bioRxiv},

publisher = {Cold Spring Harbor Laboratory},

abstract = {The human auditory system is not equally reactive to all frequencies of the audible spectrum. Emotional and behavioral reactions to loud or aversive acoustic features can vary from one individual to another, to the point that some exhibit exaggerated or even pathological responses to certain sounds. The neural mechanisms underlying these interindividual differences remain unclear. Whether distinct aversion profiles map onto neural excitability at the individual level needs to be tested. Here, we measured behavioral and EEG responses to click trains (from 10 to 250 Hz, spanning the roughness and pitch perceptual ranges) to test the hypothesis that interindividual variability in aversion to rough sounds is reflected in neural response differences between participants. Linking subjective aversion to 40 Hz steady-state EEG responses, we demonstrate that participants experiencing enhanced aversion to roughness also show stronger neural responses to this attribute. Interestingly, this pattern also correlates with inter-individual anxiety levels, suggesting that this personality trait might interact with subjective sensitivity and neural excitability to these sounds. These results support the idea that 40 Hz sounds can probe the excitability of non-canonical auditory systems involved in exogenous salience processing and aversive responses at the individual level. By linking subjective aversion to neural excitability, 40 Hz sounds provide neuromarkers relevant to a variety of pathological conditions, such as those featuring enhanced emotional sensitivity (hyperacusis, anxiety) or aberrant neural responses at 40 Hz (autism, schizophrenia).},

keywords = {Biomarker, DSI-24},

pubstate = {published},

tppubtype = {article}

}

@article{lin2021age,

title = {Age-related differences in alpha and beta band activity in sensory association brain areas during challenging sensory tasks},

author = {Chun-Ling Lin and Ya-Wen Hsieh and Hui-Ya Chen},

doi = {https://doi.org/10.1016/j.bbr.2021.113279},

year  = {2021},

date = {2021-06-25},

journal = {Behavioural Brain Research},

volume = {408},

pages = {113279},

publisher = {Elsevier},

abstract = {Sensory challenges to postural balance are daily threats for elderly individuals. This study examined electroencephalography (EEG) in alpha and beta bands in sensory association areas during the Sensory Organization Test, involving withdrawal of visual or presenting misleading somatosensory inputs, in twelve young and twelve elderly participants. The results showed stepwise deterioration in behavioral performance in four conditions, with group effects that were amplified with combined sensory challenges. With eye closure, alpha and beta activities increased in all sensory association areas. Fast beta activity increased in the bilateral parietal-temporal-occipital areas. Misleading somatosensory information effects on EEG activity were of smaller amplitude than eye closure effects and in a different direction. Decreased alpha activity in left parietal-temporal-occipital areas and decreased beta and fast beta activities in bilateral parietal-temporal-occipital areas were significant. Elderly participants had increased fast beta activity in the left temporal-occipital and bilateral occipital areas, indicative of sustained efforts that they made in all sensory conditions. Similar to the young participants, elderly participants with eyes closed showed increased alpha activity, although to a smaller degree, in bilateral temporal-occipital and left occipital areas. This might indicate a lack of efficacy in redistributing relative sensory weights when elderly participants dealt with eye closure. In summary, EEG power changes did not match the stepwise deterioration in behavioral data, but reflected different sensory strategies adopted by young and elderly participants to cope with eye closure or misleading somatosensory information based on the efficacy of these different strategies.},

keywords = {Biomarker, DSI-24},

pubstate = {published},

tppubtype = {article}

}

@article{rustamov2021spatial,

title = {Spatial and frequency-specific electrophysiological signatures of tonic pain recovery in humans},

author = {Nabi Rustamov and Lokesh Sharma and Sarah N Chiang and Carrie Burk and Simon Haroutounian and Eric C Leuthardt},

doi = {https://doi.org/10.1016/j.neuroscience.2021.04.008},

year  = {2021},

date = {2021-04-21},

urldate = {2021-01-01},

journal = {Neuroscience},

volume = {465},

pages = {23–37},

publisher = {Elsevier},

abstract = {The objective of this study was to comprehensively investigate patterns of brain activities associated with pain recovery following experimental tonic pain in humans. Specific electrophysiological features of pain recovery may either be monitored or be modulated through neurofeedback (NF) as a novel chronic pain treatment. The cold pressor test was applied with simultaneous electroencephalogram (EEG) recording. EEG data were acquired, and analyzed to define: (1) EEG power topography patterns of pain recovery; (2) source generators of pain recovery at cortical level; (3) changes in functional connectivity associated with pain recovery; (4) features of phase-amplitude coupling (PAC) as it relates to pain recovery. The novel finding of this study is that recovery from pain was characterized by significant theta power rebound at the left fronto-central area. The sources of theta power over-recovery were located in the left dorsolateral prefrontal cortex (DLPFC), cingulate cortex, left insula and contralateral sensorimotor cortex. These effects were paralleled by theta band connectivity increase within hemispheres in a prefrontal–somatosensory network and interhemispherically between prefrontal and parietal areas. In addition, this study revealed significant reduction in PAC between theta/alpha and gamma oscillations during recovery period following tonic pain. These findings have largely been replicated across two identical sessions. Our study emphasizes the association between pain recovery and left lateral prefrontal theta power rebound, and significant over-recovery of functional connectivity in prefrontal-sensorimotor neural network synchronized at theta frequencies. These findings may provide basis for chronic pain treatment by modulating neural oscillations at theta frequencies in left prefrontal cortex.},

keywords = {Biomarker, DSI-24},

pubstate = {published},

tppubtype = {article}

}

@article{eldeeb2021trial,

title = {Trial by trial EEG based BCI for distress versus non distress classification in individuals with ASD},

author = {Safaa Eldeeb and Busra T Susam and Murat Akcakaya and Caitlin M Conner and Susan W White and Carla A Mazefsky},

url = {https://www.nature.com/articles/s41598-021-85362-8},

year  = {2021},

date = {2021-03-16},

journal = {Scientific Reports},

volume = {11},

number = {1},

pages = {1--13},

publisher = {Nature Publishing Group},

abstract = {Autism spectrum disorder (ASD) is a neurodevelopmental disorder that is often accompanied by impaired emotion regulation (ER). There has been increasing emphasis on developing evidence-based approaches to improve ER in ASD. Electroencephalography (EEG) has shown success in reducing ASD symptoms when used in neurofeedback-based interventions. Also, certain EEG components are associated with ER. Our overarching goal is to develop a technology that will use EEG to monitor real-time changes in ER and perform intervention based on these changes. As a first step, an EEG-based brain computer interface that is based on an Affective Posner task was developed to identify patterns associated with ER on a single trial basis, and EEG data collected from 21 individuals with ASD. Accordingly, our aim in this study is to investigate EEG features that could differentiate between distress and non-distress conditions. Specifically, we investigate if the EEG time-locked to the visual feedback presentation could be used to classify between WIN (non-distress) and LOSE (distress) conditions in a game with deception. Results showed that the extracted EEG features could differentiate between WIN and LOSE conditions (average accuracy of 81%), LOSE and rest-EEG conditions (average accuracy 94.8%), and WIN and rest-EEG conditions (average accuracy 94.9%).},

keywords = {BCI, Biomarker, DSI-24},

pubstate = {published},

tppubtype = {article}

}

@article{islam2020eeg,

title = {EEG mobility artifact removal for ambulatory epileptic seizure prediction applications},

author = {Md Shafiqul Islam and Ahmad M El-Hajj and Hussein Alawieh and Zaher Dawy and Nabil Abbas and Jamil El-Imad},

doi = {https://doi.org/10.1016/j.bspc.2019.101638},

issn = {1746-8094},

year  = {2020},

date = {2020-01-01},

journal = {Biomedical Signal Processing and Control},

volume = {55},

pages = {101638},

publisher = {Elsevier},

abstract = {Mobile monitoring of electroencephalogram (EEG) signals is prone to different sources of artifacts. Most importantly, motion-related artifacts present a major challenge hindering the clean acquisition of EEG data as they spread all over the scalp and across all frequency bands. This leads to additional complexity in the development of neurologically-oriented mobile health solutions. Among the top five most common neurological disorders, epilepsy has increasingly relied on EEG for diagnosis. Separate methods have been used to classify EEG segments in the context of epilepsy while reducing the existing mobility artifacts. This work specifically devises an approach to remove motion-related artifacts in the context of epilepsy. The proposed approach first includes the recording of EEG signals using a wearable EEG headset. The recorded signals are then colored by some motion artifacts generated in a lab-controlled experiment. This stage is followed by temporal and spectral characterization of the signals and artifact removal using independent component analysis (ICA). The proposed approach is tested using real clinical EEG data and results showed an average increase in accuracy of ∼9% in seizure detection and ∼24% in prediction.},

keywords = {Biomarker, DSI-24},

pubstate = {published},

tppubtype = {article}

}

@article{rice2019gender,

title = {Gender Differences in Dry-EEG Manifestations During Acute and Insidious Normobaric Hypoxia},

author = {Merrill G Rice and Dallas Snider and Sabrina Drollinger and Chris Greil and Frank Bogni and Jeffrey Phillips and Anil Raj and Katherine Marco and Steven Linnville},

doi = { https://doi.org/10.3357/AMHP.5227.2019},

year  = {2019},

date = {2019-04-01},

journal = {Aerospace Medicine and Human Performance},

volume = {90},

number = {4},

pages = {369--377},

publisher = {Aerospace Medical Association},

abstract = {INTRODUCTION: Prior research suggests there may be gender differences with regards to hypoxia resilience. Our study was designed to determine whether there were differences between genders in neuronal electrical activity at simulated altitude and whether those changes correlated with cognitive and aviation performance decrements.



METHODS: There were 60 student Naval Aviators or Flight Officers who completed this study (30 women, 30 men). Participants were exposed to increasing levels of normobaric hypoxia and monitored with dry EEG while flying a fixed-base flight simulation. Gender differences in brainwave frequency power were quantified using MATLAB. Changes in flight and cognitive performance were analyzed via simulation tasks and with a cognitive test validated under hypoxia.



RESULTS: Significant decreases in theta and gamma frequency power occurred for women compared to men with insidious hypoxic exposures to 20K, with an average frequency power decrease for women of 19.4% compared to 9.3% for men in theta, and a 42.2% decrease in gamma for women compared to 21.7% for men. Beta frequency power correlated highest between genders, with an average correlation coefficient of r = 0.95 across seven channels.



DISCUSSION: Results of this study suggest there is identifiable brain wave suppression for both men and women with hypoxic exposure and, moreover, there are significant differences in this suppression between genders. Beta frequency power was most sensitive for both genders and highly correlative compared to other brainwave frequencies. The implications of these findings are important considerations for next-generation aviation helmets, which may employ this technology as an early warning mechanism.},

keywords = {Biomarker, DSI-7},

pubstate = {published},

tppubtype = {article}

}

@article{rice2019dry,

title = {Dry-EEG Manifestations of Acute and Insidious Hypoxia During Simulated Flight},

author = {Merrill G Rice and Dallas Snider and Sabrina Drollinger and Chris Greil and Frank Bogni and Jeffrey Phillips and Anil Raj and Katherine Marco and Steven Linnville},

doi = {https://doi.org/10.3357/AMHP.5228.2019},

year  = {2019},

date = {2019-02-01},

journal = {Aerospace Medicine and Human Performance},

volume = {90},

number = {2},

pages = {92-100},

publisher = {Aerospace Medical Association},

abstract = {INTRODUCTION: Recently, portable dry electroencephalographs (dry-EEGs) have indexed cognitive workload, fatigue, and drowsiness in operational environments. Using this technology this project assessed whether significant changes in brainwave frequency power occurred in response to hypoxic exposures as experienced in military aviation.



METHODS: There were 60 (30 women, 30 men) student Naval Aviators or Flight Officers who were exposed to an intense (acute) high-altitude (25,000 ft) normobaric hypoxic exposure, and 20 min later, more gradual (insidious) normobaric hypoxic exposure up to 20,000 ft while flying a fixed-wing flight simulation and monitored with a dry-EEG system. Using MATLAB, EEG frequencies and power were quantified and analyzed. Cognitive performance was also assessed with a cognitive task validated under hypoxia. Normobaric hypoxia and O2 saturation (Spo 2) were produced and monitored using the Reduced Oxygen Breathing Device (ROBD2).



RESULTS: Significant Spo 2 decreases were recorded at acute 25K and insidious 20K simulated altitudes. Significant power decreases were recorded in all frequencies (alpha, beta, gamma, and theta) and all channels with acute 25K exposures. Gamma, beta, and theta frequency power were significantly decreased with insidious 20K exposures at most of the channels. The frequency power decreases corresponded to significant decreases in cognitive performance and flight performance. Most importantly, frequency power suppressions occurred despite 42% of the volunteers not perceiving they were hypoxic in the acute phase, nor 20% in the insidious phase.



DISCUSSION: Results suggest EEG suppression during acute/insidious hypoxia can index performance decrements. These findings have promising implications in the development of biosensors that mitigate potential in-flight hypoxic physiological episodes.},

keywords = {Biomarker, DSI-7},

pubstate = {published},

tppubtype = {article}

}

@article{arakaki2019alpha,

title = {Alpha desynchronization during simple working memory unmasks pathological aging in cognitively healthy individuals},

author = {Xianghong Arakaki and Ryan Lee and Kevin S King and Alfred N Fonteh and Michael G Harrington},

editor = {Stephen D. Ginsberg, Nathan S Kline Institute},

doi = {https://doi.org/10.1371/journal.pone.0208517},

year  = {2019},

date = {2019-01-02},

journal = {PloS one},

volume = {14},

number = {1},

pages = {e0208517},

publisher = {Public Library of Science San Francisco, CA USA},

abstract = {Our aim is to explore if cognitive challenge combined with objective physiology can reveal abnormal frontal alpha event-related desynchronization (ERD), in early Alzheimer’s disease (AD). We used quantitative electroencephalography (qEEG) to investigate brain activities during N-back working memory (WM) processing at two different load conditions (N = 0 or 2) in an aging cohort. We studied 60–100 year old participants, with normal cognition, and who fits one of two subgroups from cerebrospinal fluid (CSF) proteins: cognitively healthy (CH) with normal amyloid/tau ratio (CH-NAT, n = 10) or pathological amyloid/tau ratio (CH-PAT, n = 14). We recorded behavioral performances, and analyzed alpha power and alpha spectral entropy (SE) at three occasions: during the resting state, and at event-related desynchronization (ERD) [250 ~ 750 ms] during 0-back and 2-back. During 0-back WM testing, the behavioral performance was similar between the two groups, however, qEEG notably differentiated CH-PATs from CH-NATs on the simple, 0-back testing: Alpha ERD decreased from baseline only in the parietal region in CH-NATs, while it decreased in all brain regions in CH-PATs. Alpha SE did not change in CH-NATs, but was increased from baseline in the CH-PATs in frontal and left lateral regions (p<0.01), and was higher in the frontal region (p<0.01) of CH-PATs compared to CH-NATs. The alpha ERD and SE analyses suggest there is frontal lobe dysfunction during WM processing in the CH-PAT stage. Additional power and correlations with behavioral performance were also explored. This study provide pilot information to further evaluate whether this biomarker has clinical significance.},

keywords = {Biomarker, DSI-24, qEEG},

pubstate = {published},

tppubtype = {article}

}

@article{arakaki2018alpha,

title = {Alpha desynchronization/synchronization during working memory testing is compromised in acute mild traumatic brain injury (mTBI)},

author = {Xianghong Arakaki and Michael Shoga and Lianyang Li and George Zouridakis and Thao Tran and Alfred N Fonteh and Jessica Dawlaty and Robert Goldweber and Janice M Pogoda and Michael G Harrington},

doi = {https://doi.org/10.1371/journal.pone.0188101},

year  = {2018},

date = {2018-02-14},

journal = {PloS one},

volume = {13},

number = {2},

pages = {e0188101},

publisher = {Public Library of Science San Francisco, CA USA},

abstract = {Diagnosing and monitoring recovery of patients with mild traumatic brain injury (mTBI) is challenging because of the lack of objective, quantitative measures. Diagnosis is based on description of injuries often not witnessed, subtle neurocognitive symptoms, and neuropsychological testing. Since working memory (WM) is at the center of cognitive functions impaired in mTBI, this study was designed to define objective quantitative electroencephalographic (qEEG) measures of WM processing that may correlate with cognitive changes associated with acute mTBI. First-time mTBI patients and mild peripheral (limb) trauma controls without head injury were recruited from the emergency department. WM was assessed by a continuous performance task (N-back). EEG recordings were obtained during N-back testing on three occasions: within five days, two weeks, and one month after injury. Compared with controls, mTBI patients showed abnormal induced and evoked alpha activity including event-related desynchronization (ERD) and synchronization (ERS). For induced alpha power, TBI patients had excessive frontal ERD on their first and third visit. For evoked alpha, mTBI patients had lower parietal ERD/ERS at the second and third visits. These exploratory qEEG findings offer new and non-invasive candidate measures to characterize the evolution of injury over the first month, with potential to provide much-needed objective measures of brain dysfunction to diagnose and monitor the consequences of mTBI.},

keywords = {Biomarker, DSI-24},

pubstate = {published},

tppubtype = {article}

}

@article{hunter2018change,

title = {Change in quantitative EEG theta cordance as a potential predictor of repetitive transcranial magnetic stimulation clinical outcome in major depressive disorder},

author = {Aimee M Hunter and Thien X Nghiem and Ian A Cook and David E Krantz and Michael J Minzenberg and Andrew F Leuchter},

doi = {https://doi.org/10.1177/1550059417746212},

year  = {2017},

date = {2017-12-10},

urldate = {2017-12-10},

journal = {Clinical EEG and Neuroscience},

volume = {49},

number = {5},

pages = {306--315},

publisher = {Sage Publications Sage CA: Los Angeles, CA},

abstract = {Repetitive transcranial magnetic stimulation (rTMS) has demonstrated efficacy in major depressive disorder (MDD), although clinical outcome is variable. Change in the resting-state quantitative electroencephalogram (qEEG), particularly in theta cordance early in the course of treatment, has been linked to antidepressant medication outcomes but has not been examined extensively in clinical rTMS. This study examined change in theta cordance over the first week of clinical rTMS and sought to identify a biomarker that would predict outcome at the end of 6 weeks of treatment. Clinically stable outpatients (n = 18) received nonblinded rTMS treatment administered to the dorsolateral prefrontal cortex (DLPFC). Treatment parameters (site, intensity, number of pulses) were adjusted on an ongoing basis guided by changes in symptom severity rating scale scores. qEEGs were recorded at pretreatment baseline and after 1 week of left DLPFC (L-DLPFC) rTMS using a 21-channel dry-electrode headset. Analyses examined the association between week 1 regional changes in theta band (4-8 Hz) cordance, and week 6 patient- and physician-rated outcomes. Theta cordance change in the central brain region predicted percent change in Inventory of Depressive Symptomology–Self-Report (IDS-SR) score, and improvement versus nonimprovement on the Clinical Global Impression–Improvement Inventory (CGI-I) (R2 = .38, P = .007; and Nagelkerke R2 = .78, P = .0001, respectively). The cordance biomarker remained significant when controlling for age, gender, and baseline severity. Treatment-emergent change in EEG theta cordance in the first week of rTMS may predict acute (6-week) treatment outcome in MDD. This oscillatory synchrony biomarker merits further study in independent samples.},

keywords = {Biomarker, DSI-24, Neuromodulation, qEEG},

pubstate = {published},

tppubtype = {article}

}

@article{arakaki2016exploring,

title = {Exploring neuroplasticity in acute mild traumatic brain injury},

author = {Xianghong Arakaki and Michael Shoga and Lianyang Li and George Zouridakis and Ramona Rostami and Robert Goldweber and Michael Harrington},

url = {https://faseb.onlinelibrary.wiley.com/doi/abs/10.1096/fasebj.30.1_supplement.992.4},

year  = {2016},

date = {2016-04-01},

journal = {The FASEB Journal},

volume = {30},

pages = {992--4},

publisher = {The Federation of American Societies for Experimental Biology},

abstract = {Objectives

To explore neuroplasticity in a longitudinal study of acute mild traumatic brain injury (mTBI).



Methods

We are using quantitative electroencephalography (qEEG) and magnetoencephalography (MEG) during the resting state and during cognitive brain stress to explore neuroplasticity in an ongoing acute mild traumatic brain injury research. Acute mTBI patients are recruited from the emergency department of Huntington Memorial Hospital in Pasadena, CA, and controls are non‐head‐trauma patients. Brain stress includes the N‐back (0‐back and 2‐back) working memory test and Color‐Word Interference Test (CWIT), administered using E‐prime software. Data were collected at three time points: within 1 week of injury, 14 days, and 30 days after injury. Behavioral as well as MEG and qEEG analysis are performed to compare the two groups.



Results

Resting MEG detected low frequency activity in the mTBI group, consistent with previous publications. N‐back, in particular during 2‐back trials, and CWIT, in particular during incongruent trials, both show initial executive function impairment that improved on later visits. Time frequency analysis suggested corresponding compromised brain activity.



Conclusions

The EEG/MEG recordings during rest and brain stress are objective and sensitive to neuroplasticity in acute mTBI, and could be potential objective mTBI markers.},

keywords = {Biomarker, DSI-24},

pubstate = {published},

tppubtype = {article}

}