The use of current source density as electrophysiological correlates in neuropsychiatric disorders: A review of human studies.
- Authors
- Kamarajan, Chella; Pandey, Ashwini K; Chorlian, David B; Porjesz, Bernice
- Year
- 2015
- Journal
- International journal of psychophysiology : official journal of the International Organization of Psychophysiology
- PMID
- 25448264
- DOI
- 10.1016/j.ijpsycho.2014.10.013
- PMCID
- PMC4422780
The use of current source density (CSD), the Laplacian of the scalp surface voltage, to map the electrical activity of the brain is a powerful method in studies of cognitive and affective phenomena. During the last few decades, mapping of CSD has been successfully applied to characterize several neuropsychiatric conditions such as alcoholism, schizophrenia, depression, anxiety disorders, childhood/developmental disorders, and neurological conditions (i.e., epilepsy and brain lesions) using electrophysiological data from resting state and during cognitive performance. The use of CSD and Laplacian measures has proven effective in elucidating topographic and activation differences between groups: i) patients with a specific diagnosis vs. healthy controls, ii) subjects at high risk for a specific diagnosis vs. low risk or normal controls, and iii) patients with specific symptom(s) vs. patients without these symptom(s). The present review outlines and summarizes the studies that have employed CSD measures in investigating several neuropsychiatric conditions. The advantages and potential of CSD-based methods in clinical and research applications along with some of the limitations inherent in the CSD-based methods are discussed in the review, as well as future directions to expand the implementation of CSD to other potential clinical applications. As CSD methods have proved to be more advantageous than using scalp potential data to understand topographic and source activations, its clinical applications offer promising potential, not only for a better understanding of a range of psychiatric conditions, but also for a variety of focal neurological disorders, including epilepsy and other conditions involving brain lesions and surgical interventions.
Illustration of typical EEG trace (top panel), ERP waveform (middle panel), and ERO time-frequency map at Cz electrode in a visual oddball paradigm, recorded with nose tip as reference and forehead as ground electrode placements. EROs were computed using the S-transform algorithm as described in Jones et al. (2006). The horizontal axis in all panels represent time in milliseconds, and the color scale in bottom panel indicate amplitude in μV. In the middle and bottom panels, zero (0) millisecond represent the stimulus onset during a task.
Comparison of P3 response between the Alcoholic and Control group shown in ERP amplitudes (panel A) and in CSD transformed data (panel B) during a Go-NoGo task. A) Alcoholics showed lower P3 amplitude in both Go and NoGo conditions without any topographic difference; and B) alcoholics manifested differences in both intensity (‘Go’ sinks and ‘NoGo’ sources) and topography of CSD activations (mainly in ‘Go’ sources). The CSD maps provide sharper and more interpretable activation features (sources and sinks) to compare between groups and conditions. In the Go condition with a button press response, controls manifested two bilateral sources, while the alcoholics exhibited only a midline source. In the NoGo condition with inhibitory processing (and no button press), controls showed a stronger and focused source over the central region, while the alcoholics exhibited a weaker and diffused source over the central and posterior regions. The physical units for the scalp potentials and CSD data are microvolt (μV) and ampere per square centimeter (A/cm2) respectively [Adapted from: Kamarajan et al. (2005)]
Topographic patterns of ERO theta activity representing total theta power (panel A) and of CSD maps computed from theta amplitude data (panel B) as compared between alcoholic and control group. These values were extracted within the time interval of 200-500 ms during the feedback of loss and gain of 50φ in a monetary gambling task. A) Alcoholics showed lower theta power in both loss and gain conditions; and B) alcoholics manifested lower CSD activations as well as topographic differences during loss and gain conditions. The CSD maps provided more prominent and useful information regarding the activation profiles across groups and conditions [Adapted from: Kamarajan et al. (2012)]
No entities extracted from this document yet.
No uploaded files.
In this knowledge base
External
| Title | Authors | Journal | Year | Link |
|---|---|---|---|---|
| The neural correlates of grit: Frontal lobe activity in grit effort and interest. | Fleck JI et al. | — | 2026 | → |
| Audiovisual integration facilitates age-related perceptual decision making. | Yang X et al. | — | 2025 | → |
| Brain activities associated with two-handed interactive movement during different motor forms. | Jia L et al. | — | 2025 | → |
| Deep Learning Recognition of Paroxysmal Kinesigenic Dyskinesia Based on EEG Functional Connectivity. | Zhao L et al. | — | 2025 | → |
| EEG-based information transfer paths during motion discrimination: Detectable differences between normal cognition and MCI. | Renli A et al. | — | 2025 | → |
| Neuronavigation-Guided Transcranial Acoustoelectric Brain Imaging: A New Modality for High Resolution Electrical Brain Mapping. | Allard M et al. | — | 2025 | → |
| Electrophysiological responses of audiovisual integration from infancy to adulthood. | Vannasing P et al. | — | 2024 | → |
| Exploring the neural underpinnings of chord prediction uncertainty: an electroencephalography (EEG) study. | Ono K et al. | — | 2024 | → |
| Frontal alpha asymmetry during emotion regulation in adults with lifetime major depression. | Zsigo C et al. | — | 2024 | → |
| Novel methodology for detection and prediction of mild cognitive impairment using resting-state EEG. | Deng J et al. | — | 2024 | → |
| Resting-state electroencephalogram in drug-free subjects with at-risk mental states who later developed psychosis: a low-resolution electromagnetic tomography analysis. | Higuchi Y et al. | — | 2024 | → |
| Soulhacker: An artist-medical collaboration to treat depression via artistic virtual reality. | Otte G et al. | — | 2024 | — |
| Abnormal gait and motor cortical processing in drug-resistant juvenile myoclonic epilepsy. | Maidan I et al. | — | 2023 | → |
| Resting-state frontal, frontlateral, and parietal alpha asymmetry:A pilot study examining relations with depressive disorder type and severity. | Marcu GM et al. | — | 2023 | → |
| Velocity-tuning of somatosensory EEG predicts the pleasantness of gentle caress. | Schirmer A et al. | — | 2023 | → |
| Brain Functional Network and Amino Acid Metabolism Association in Females with Subclinical Depression. | Zhao S et al. | — | 2022 | → |
| Full-bandwidth electrophysiology of seizures and epileptiform activity enabled by flexible graphene microtransistor depth neural probes. | Bonaccini Calia A et al. | — | 2022 | → |
| Gentle stroking elicits somatosensory ERP that differentiates between hairy and glabrous skin. | Schirmer A et al. | — | 2022 | → |
| Using multivariate endophenotypes to identify psychophysiological mechanisms associated with polygenic scores for substance use, schizophrenia, and education attainment. | Harper J et al. | — | 2022 | → |
| Neurophysiological investigation of auditory intensity dependence in patients with Parkinson's disease. | De Keyser K et al. | — | 2021 | → |
| The influence of monetary reward on proactive and reactive control in adolescent males. | Bowers ME et al. | — | 2021 | → |
| A Bayesian approach to joint modeling of matrix-valued imaging data and treatment outcome with applications to depression studies. | Jiang B et al. | — | 2020 | → |
| Acoustoelectric imaging of deep dipoles in a human head phantom for guiding treatment of epilepsy. | Barragan A et al. | — | 2020 | → |
| Neural circuits of idiopathic Normal Pressure Hydrocephalus: A perspective review of brain connectivity and symptoms meta-analysis. | Griffa A et al. | — | 2020 | → |
| Over and over again: Changes in frontal EEG asymmetry across a boring task. | Perone S et al. | — | 2019 | → |
| The neurophysiological basis of developmental changes during sequential cognitive flexibility between adolescents and adults. | Giller F et al. | — | 2019 | → |
| Potential Role of OERP as Early Marker of Mild Cognitive Impairment. | Invitto S et al. | — | 2018 | → |
| Resting frontal EEG asymmetry in adolescents with major depression: Impact of disease state and comorbid anxiety disorder. | Feldmann L et al. | — | 2018 | → |
| Using Event-Related Potentials and Startle to Evaluate Time Course in Anxiety and Depression. | Klumpp H et al. | — | 2018 | → |
| Genetic influences on functional connectivity associated with feedback processing and prediction error: Phase coupling of theta-band oscillations in twins. | Demiral ŞB et al. | — | 2017 | → |
| Is There an Association Between Mismatch Negativity and Cortical Thickness in Schizophrenia Patients? | Seol JJ et al. | — | 2017 | → |
| LATENT CLASS MODELING USING MATRIX COVARIATES WITH APPLICATION TO IDENTIFYING EARLY PLACEBO RESPONDERS BASED ON EEG SIGNALS. | Jiang B et al. | — | 2017 | → |
| Lateralization of language function in epilepsy patients: A high-density scalp-derived event-related potentials (ERP) study. | Trimmel K et al. | — | 2017 | → |
| Advances in Electrophysiological Research. | Kamarajan C et al. | — | 2015 | → |
| Deficient Event-Related Theta Oscillations in Individuals at Risk for Alcoholism: A Study of Reward Processing and Impulsivity Features. | Kamarajan C et al. | — | 2015 | → |
| On the benefits of using surface Laplacian (current source density) methodology in electrophysiology. | Kayser J et al. | — | 2015 | → |
| Reward processing deficits and impulsivity in high-risk offspring of alcoholics: A study of event-related potentials during a monetary gambling task. | Kamarajan C et al. | — | 2015 | → |