Current Source Density Research Articles

The use of a high-density microelectrode arrays (>4000 microelectrodes) allows the recordings of evoked and on-going field activity of the whole hippocampal formation and other tissues with high spatiotemporal resolution. From these recordings it is possible to obtain the current source density (CSD) which separates the current generators into sinks and sources; this differentiation provides the means to distinguish correlated, disjoint loci of activity and track them separately at near to cell resolution. By obtaining the vectorial average of an area regarded as sink or source, we obtain a putative center of action, or center of mass that can be traced in time. Thus, successive centers would reveal the immediate nearby correlated units that "inherit" or otherwise are affected by this activity revealing a putative route of transfer of information that can be quantitated with high spatiotemporal definition. For structured tissues, this methodology provides a means to infer effective information transmission with clear parameters that can be further analyzed in several ways. Importantly, the CSD over time reveals patterns of activity obscured by the representation of activity in the voltage domain, which can aid to uncover synaptic interactions in restricted microcircuits.

SUMMARY In mineral exploration, induced polarization and self-potential are two broadly used active and passive geophysical methods, respectively. In the case of ore bodies, both methods are associated with charge distributions associated with a secondary electrical field (induced polarization) and a source current density (self-potential). Both the chargeability and volumetric source current density distributions bring information regarding the shape of ore bodies. Therefore the joint inversion of these datasets is expected to better tomograms of ore bodies. A joint inversion approach is developed to combine both methods. The objective function to minimize includes two independent components plus a cross-gradient joint function. The use of the cross-gradient is justified from the underlying physics of the two geophysical problems at play. The structure of the cost function is tailored to overcome some problems like convergence and parameter determination in the inverse process. Two synthetic tests and a laboratory experiment are used to benchmark the proposed algorithm. We demonstrate that the joint inversion algorithm performs better than the localizations obtained from independent inversion approaches. To refine the interpretation of the shape of ores, we introduce an ore presence index using the chargeability and source current density resulting from the joint inversion algorithm. The K-Medoids clustering algorithm is used to automatically categorize the calculated ore presence index into different clusters. The cluster with larger values successfully identifies the ore bodies associated with strong chargeability and/or volumetric source current density.

EEG theta and alpha biomarkers during an avoid-avoid conflict task: Links to anxiety.

Cortical layer-specific abnormalities in auditory responses in a mouse model of Fragile X Syndrome.

This study aimed to investigate neurophysiological differences between altruistic and selfish behaviors by simultaneously measuring electroencephalography (EEG) and electrocardiography (ECG). Specifically, we hypothesized that altruistic behavior would be associated with distinct patterns of cortical activity and autonomic responses. Thirty-one healthy participants (17 females; mean age: 20.00 ± 1.18 years) completed crafting tasks in a counterbalanced order under altruistic and selfish conditions. We measured and analyzed frontal alpha asymmetry (FAA) scores, cardiac sympathetic index (CSI), and cardiac vagal index (CVI). Additionally, we used eLORETA (exact-low resolution electromagnetic tomography) to examine current source density and functional connectivity patterns across brain regions. The altruistic condition exhibited significantly higher FAA scores (p = 0.031, r = 0.45) and lower CSI (p = 0.048, Cohen's d = 0.37) compared to the selfish condition. Notably, novel correlations were observed between neurophysiological measures and specific brain regions. Specifically, FAA scores were associated with gamma activity in the anterior cingulate cortex during the altruistic condition (p = 0.071) and with precuneus activity during selfish behavior (p = 0.029). Additionally, distinct functional connectivity patterns were associated with autonomic activity in the altruistic condition. Parasympathetic activity negatively correlated with temporal-gamma connectivity (p = 0.002), and heart rate change negatively correlated with temporal-prefrontal theta connectivity (p = 0.048). Our findings reveal the intricate relationship between cortical activity, functional connectivity, and autonomic responses during altruistic versus selfish behaviors for the first time. This integrative approach sheds new light on the neural mechanisms underlying social cognition. This approach also has the potential to enhance our understanding of and ability to encourage prosocial behavior in various clinical and therapeutic settings.

FOXG1 syndrome (FS) is a rare and devastating neurodevelopmental disorder affected by FOXG1 gene mutations and reduced sound tolerance has been reported in children with FS. Effects of single missense mutation of Foxg1 gene on auditory function and behavior were studied using the G216S mouse model. G216S mice showed significantly reduced gap-induced prepulse inhibition, suggesting poor temporal processing without hearing loss. Increased running and freezing behaviors under loud sounds were also found in G216 mice, suggesting aversive sound behaviors. Electrophysiological assessment of the auditory cortex of G216 mice revealed a slightly reduced amplitude and enlarged poststimulus responses to the sound stimulus. The layer function analysis using current source density revealed reduced layer-specific response in the G216S mice. Immunocytochemistry found Foxg1 gene mutation affects cortical layer differentiations and reduced cortical neurons, which are consistent with the physiological results. Our study suggests that the Foxg1 mutation impaired cortical development. The results are consistent with other models of autism spectrum disorders (ASDs), suggesting that the G216S mouse model may represent a hyperacusis model of ASD. Our results provide direct evidence that a single-nucleotide mutation of the Foxg1 gene can affect cortical layer development and auditory processing and reduce sound tolerance.

Estimating sensor-space EEG connectivity: Identifying optimal artifact reduction techniques for functional connectivity in real data.

Estimating sensor-space EEG connectivity: Identifying best performing methods for functional connectivity in simulated data.

Summary:Our study (Mendoza-Halliday et al., 2024) made two contributions: (1) discovery of a ubiquitous cortical motif and (2) a tool derived from it—the Frequency-based Layer Identification Procedure (FLIP and vFLIP). Mackey et al. critique the tool, questioning its advantage over classic current source density (CSD) analysis, and reason backwards to challenge the motif’s ubiquity. In our rebuttal, we confirm the spectrolaminar motif in diverse cortical areas using data from multiple research groups (who joined us in this rebuttal) as well as Mackey et al.’s own dataset. Additionally, we introduce vFLIP2, an improved version of our tool that addresses their comments. It reliably identified and localized the motif in our data and Mackey et al.’s data. Our findings reaffirm the motif’s ubiquity. We value Mackey et al.’s comments, which helped refine our tool.

Spinal and corticospinal excitability changes with voluntary modulation of motor cortex oscillations.

The prefrontal cortex, well-developed in humans, plays a crucial role in various behavioural outcomes. Neuronal resources are limited, however, and must be appropriately allocated. A specific type of theta activity, known as frontal midline theta (Fmθ), is intermittently observed in the frontal midline region during intense concentration to tasks. Meanwhile, the power of Fmθ activity is stronger in individuals with excessive concentration than in those who are not engaged in such state. Fmθ activity in healthy young adults is therefore speculated to be reduced when shifting attention from one target to another. However, the neuronal mechanisms of Fmθ reduction are largely unknown. In this study, 20 healthy young male adults performed 2-back cognitive tasks including two pieces of information (colour and position). Participants initially pay attention to one of them at the start of the task, and then to shift attention to the other when the screen's background colour was changed. Transient reduction of theta activity was observed with the attentional shift, and high current source density was observed in the medial prefrontal and the anterior cingulate regions. Reduction of alpha activity in the left inferior parietal lobe was simultaneously observed during the attentional shift. Moreover, there was a significant positive correlation between the reduction of Fmθ and alpha activity in the left parietal area. The reduction of Fmθ activity and the change in activity of the inferior parietal lobe may play an essential role in disengaging from intense concentration and the appropriate attentional shift. Trial Registration: UMIN000051023.

Objective.The study objective was to characterise indices of learning and patterns of connectivity in two neurofeedback (NF) paradigms that modulate mu oscillations in opposite directions, and the relationship with change in excitability of the corticospinal tract (CST).Approach.Forty-three healthy volunteers participated in 3 NF sessions for upregulation (N = 24) or downregulation (N = 19) of individual alpha (IA) power at central location Cz. Brain signatures from multichannel electroencephalogram (EEG) were analysed, including oscillatory (power, spindles), non-oscillatory components (Hurst exponent), and effective connectivity directed transfer function (DTF) of participants who were successful at enhancing or suppressing IA power at Cz. CST excitability was studied through leg motor-evoked potential, tested before and after the last NF session. We assessed whether participants modulated widespread alpha or central mu rhythm through the use of current source density derivation (CSD), and related the change in activity in mu and upper half of mu band, to CST excitability change.Main results.In the last session, IA/mu power suppression was achieved by 79% of participants, while 63% enhanced IA. CSD-EEG revealed that mu power was upregulated through an increase in the incidence rate of bursts of alpha band activity, while downregulation involved changes in oscillation amplitude and temporal patterns. Neuromodulation also influenced frequencies adjacent to the targeted band, indicating the use of common mental strategies within groups. DTF analysis showed, for both groups, significant connectivity between structures commonly associated with motor imagery tasks, known to modulate the excitability of the motor cortex, although most connections did not remain significant after correcting for multiple comparisons. CST excitability modulation was related to the absolute amplitude of upper mu modulation, rather than the modulation direction.Significance.The upregulation and downregulation of IA/mu power during NF, with respect to baseline were achieved via distinct mechanisms involving oscillatory and non-oscillatory EEG features. Mu enhancement and suppression post-NF and during the last NF block with respect to the baseline, respectively corresponded to opposite trends in motor-evoked potential changes post-NF. The ability of NF to modulate CST excitability could be a valuable rehabilitation tool for central nervous system disorders (stroke, spinal cord injury), where increased excitability and neural plasticity are desired. This work may inform future neuromodulation protocols, and may improve NF training effectiveness by rewarding certain EEG signatures.

Chronic low back pain (CLBP) is a global health issue, and its nonspecific causes make treatment challenging. Understanding the neural mechanisms of CLBP should contribute to developing effective therapies. To compare current source density (CSD) and functional connectivity (FC) extracted from resting electroencephalography (EEG) between patients with CLBP and healthy controls and to examine the correlations between EEG indices and symptoms. Thirty-four patients with CLBP and 34 healthy controls in an open data set were analyzed. Five-minute resting-state closed-eye EEG was acquired using the international 10-20 system. Current source density across frequency bands was calculated using exact low-resolution electromagnetic tomography. Functional connectivity was assessed between 24 cortical regions using lagged linear connectivity. Correlations between pain symptoms and CSD distribution and FC were examined in patients with CLBP. Current source density analysis showed no significant differences between the groups. The CLBP group exhibited significantly reduced FC in the β3 band between the left middle temporal gyrus and the posterior cingulate cortex, and between the ventral medial prefrontal cortex and the left inferior parietal lobule. Prefrontal θ and δ activity positively correlated with pain symptoms. Increased β1 band FC between the right dorsolateral prefrontal cortex and right auditory cortex correlated with greater pain intensity. We found altered neural activity and connectivity in patients with CLBP, particularly in prefrontal and temporal regions. These results suggest potential targets for pain modulation through brain pathways and highlight the value of EEG biomarkers in understanding pain mechanisms and assessing treatment efficacy.

Progesterone and allopregnanolone facilitate excitatory synaptic transmission in the infralimbic cortex via activation of membrane progesterone receptors.

Due to the absence of objective diagnostic criteria, tinnitus diagnosis primarily relies on subjective assessments. However, its neuropathological features can be objectively quantified using electroencephalography (EEG). Despite the existing research, the pathophysiology of tinnitus remains unclear. The objective of this study was to gain a deeper comprehension of the neural mechanisms underlying tinnitus through the comparison of cognitive event-related potentials in patients with tinnitus and healthy controls (HCs). Furthermore, we explored the potential of EEG-derived features as biomarkers for tinnitus using machine learning techniques. Forty-eight participants (24 patients with tinnitus and 24 HCs) underwent comprehensive audiological assessments and EEG recordings. We extracted N2 and P3 components of the midline electrodes using an auditory oddball paradigm, to explore the relationship between tinnitus and cognitive function. In addition, the current source density for N2- and P3-related regions of interest was computed. A linear support vector machine classifier was used to distinguish patients with tinnitus from HCs. The P3 peak amplitudes were significantly diminished in patients with tinnitus at the AFz, Fz, Cz, and Pz electrodes, whereas the N2 peak latencies were significantly delayed at Cz electrode. Source analysis revealed notably reduced N2 activities in bilateral fusiform gyrus, bilateral cuneus, bilateral temporal gyrus, and bilateral insula of patients with tinnitus. Correlation analysis revealed significant associations between the Hospital Anxiety and Depression Scale-Depression scores and N2 source activities at left insula, right insula, and left inferior temporal gyrus. The best classification performance showed a validation accuracy of 85.42%, validation sensitivity of 87.50%, and validation specificity of 83.33% in distinguishing between patients with tinnitus and HCs by using a total of 18 features in both sensor- and source-level. This study demonstrated that patients with tinnitus exhibited significantly altered neural processing during the cognitive-related oddball paradigm, including lower P3 amplitudes, delayed N2 latency, and reduced source activities in specific brain regions in cognitive-related oddball paradigm. The correlations between N2 source activities and Hospital Anxiety and Depression Scale-Depression scores suggest a potential link between the physiological symptoms of tinnitus and their neural impact on patients with tinnitus. Such findings underscore the potential diagnostic relevance of N2- and P3-related features in tinnitus, while also highlighting the interplay between the temporal lobe and occipital lobe in tinnitus. Furthermore, the application of machine learning techniques has shown reliable results in distinguishing tinnitus patients from HCs, reinforcing the viability of N2 and P3 features as biomarkers for tinnitus.

Noise exposure is one of the most common causes of hearing loss and hyperacusis. Studies have shown that noise exposure can induce a cortical gain to compensate for reduced input of the cochlea, which may contribute to the increased sound sensitivity. However, many people with hyperacusis have no measurable cochlear lesion after being exposed to loud sound. In this experiment, we studied the neurological alterations in the cortical and subcortical areas following a prolonged moderate level of noise exposure (84 dB SPL, 8 h/day for 4 weeks) in the laboratory mice. The cochlear function was monitored by auditory brainstem responses (ABRs). The behavioral auditory sensitivity and temporal processing were evaluated using the acoustic startle response (ASR) and gap-induced prepulse inhibition (gap-PPI). The central auditory functions were determined by electrophysiological recordings of the inferior colliculus (IC) and the auditory cortex (AC). Our results showed that although there was no significant difference in the ABR thresholds, the noise group showed enhanced ASR and gap-PPI compared to the control group. Increased neural activity in both the IC and the AC was recorded in the noise-exposed mice compared to the control group, suggesting a central gain in both the subcortical and cortical regions. The current source density (CSD) analysis of the AC response revealed an increased columnar excitation and reduced corticocortical projection in the noise group, different from the central gain model of noise-induced hearing loss. Our results suggest that chronic “nondestructive” noise can increase the gain of the central auditory system by altering the balance of auditory thalamocortical and intracortical inputs, which may contribute to the increased sound sensitivity in people with normal hearing.

A fundamental property of the neocortex is its columnar organization in many species. Generally, neurons of the same column share stimulus preferences and have strong anatomical connections across layers. These features suggest that neurons within a column operate as one unified network. Other features, like the different patterns of input and output connections of neurons located in separate layers and systematic differences in feature tuning, hint at a more segregated and possibly flexible functional organization of neurons within a column. To distinguish between these views of columnar processing, we conducted laminar recordings in macaques' area V1 while they performed a demanding attention task. We identified three separate regions with strong gamma oscillatory activity, located in the supragranular, granular, and infragranular laminar domains, based on the current source density (CSD). Their characteristics differed significantly in their dominant gamma frequency and attention-dependent modulation of their gramma power and gamma frequency. In line, spiking activity in the supragranular, infragranular, and upper part of the granular domain exhibited strong phase coherence with the CSD signals of their domain but showed much weaker coherence with the CSD signals of other domains. These results indicate that columnar processing involves a certain degree of independence between neurons in the three laminar domains, consistent with the assumption of multiple, separate intracolumnar ensembles. Such a functional organization offers various possibilities for dynamic network configuration, indicating that neurons in a column are not restricted to operate as one unified network. Thus, the findings open interesting new possibilities for future concepts and investigations on flexible, dynamic cortical ensemble formation and selective information processing.

The local field potential (LFP), the low-frequency part of the extracellular potential, reflects transmembrane currents in the vicinity of the recording electrode. Thought mainly to stem from currents caused by synaptic input, it provides information about neural activity complementary to that of spikes, the output of neurons. However, the many neural sources contributing to the LFP, and likewise the derived current source density (CSD), can often make it challenging to interpret. Efforts to improve its interpretability have included the application of statistical decomposition tools like principal component analysis (PCA) and independent component analysis (ICA) to disentangle the contributions from different neural sources. However, their underlying assumptions of, respectively, orthogonality and statistical independence are not always valid for the various processes or pathways generating LFP. Here, we expand upon and validate a decomposition algorithm named Laminar Population Analysis (LPA), which is based on physiological rather than statistical assumptions. LPA utilizes the multiunit activity (MUA) and LFP jointly to uncover the contributions of different populations to the LFP. To perform the validation of LPA, we used data simulated with the large-scale, biophysically detailed model of mouse V1 developed by the Allen Institute. We find that LPA can identify laminar positions within V1 and the temporal profiles of laminar population firing rates from the MUA. We also find that LPA can estimate the salient current sinks and sources generated by feedforward input from the lateral geniculate nucleus (LGN), recurrent activity in V1, and feedback input from the lateromedial (LM) area of visual cortex. LPA identifies and distinguishes these contributions with a greater accuracy than the alternative statistical decomposition methods, PCA and ICA. The contributions from different cortical layers within V1 could however not be robustly separated and identified with LPA. This is likely due to substantial synchrony in population firing rates across layers, which may be reduced with other stimulus protocols in the future. Lastly, we also demonstrate the application of LPA on experimentally recorded MUA and LFP from 24 animals in the publicly available Visual Coding dataset. Our results suggest that LPA can be used both as a method to estimate positions of laminar populations and to uncover salient features in LFP/CSD contributions from different populations.

Abstract BackgroundPatients with cognitive impairment are likely to suffer from weakening of functional connectivity between certain brain regions, which may often be accompanied by increased connectivity between some other regions, the latter of which may reflect the compensatory mechanisms of the brain. In this EEG‐based study, we investigate the differences in functional connectivity between persons with normal cognition (NC) and MCI patients in motion detection tasks.MethodOur research focuses on task‐based EEG (64‐channel) acquired at Wayne State University, where participants with subjective cognitive complaints were asked to perform a motion direction discrimination task. The current dataset includes 56 consensus‐diagnosed, community‐dwelling African Americans (ages 60‐90 years, 28 Normal Cognitions (NC) and 28 MCI patients) recruited through the Wayne State Institute of Gerontology and Michigan Alzheimer’s Disease Research Center.We evaluated the functional connectivity at different time periods of the motion‐detection task across all the possible EEG region pairs using Pearson Correlation of the current source density (CSD). For each task trial, the successive time periods being examined included: (i) Pre‐Task resting‐state, (ii) Stimulus Onset to Go/NoGo indication, (iii) Go (or NoGo) indication to Motion‐Stop, (iv) Button‐Press period, (v) Post‐task resting‐state.ResultsOur analysis indicates that when the full band CSD signals were considered, MCI showed statistically significant (p‐value < 0.05) and increased functional connectivity between MP↔Occ in all the time periods during the motion task. In comparison, the Beta band, which is believed to be related to attentional deficits in the visual performance among older persons, showed similar trends with the full band, and consistent and statistically significant increased functional connectivity between MP and PCC were observed in the Button‐Press period across all frequency bands.ConclusionOur result suggests that MCI participants compensated for impaired connectivity in specific region pairs (see Figure 3) during the motion direction discrimination task by increasing the functional connectivity between MP and Occ to achieve comparable behavioral results to NC, and this may also be a particular indicator associated with MCI and AD pathology.Funding: NSF‐2032709/Li; NIH‐1R21AG046637‐01A1/Kavcic and NIH‐1R01AG054484‐01A1/Kavcic; NIH‐P30AG072931/Paulson; NIH‐P30AG024824/Yung.

Abstract BackgroundChanges in effective connectivity, which represents the directed connectivity or information flow from one brain region to the other, have been proposed to underlie mild cognitive impairment (MCI) and Alzheimer’s disease (AD) pathology. The present study explores possible differences in brain effective connectivity between persons with normal cognition (NC) and patients with MCI.MethodOur research focuses on task‐based EEG (64‐channel) acquired at Wayne State University, where participants were asked to perform a motion direction discrimination task. The current dataset includes 56 consensus‐diagnosed, community‐dwelling African Americans with subjective cognitive complaints (ages 60‐90 years, 28 NC and 28 MCI) recruited through the Wayne State Institute of Gerontology and Michigan Alzheimer’s Disease Research Center.We evaluated the effective connectivity at different time periods of the motion‐detection task across all the possible EEG region pairs using causalized convergent cross‐mapping (cCCM) of the current source density. For each task trial, the successive time periods being examined included: (I) stimulus onset to Go/No‐Go indication, (II) Go (or No‐Go) indication to motion‐stop, and (III) the button‐press period.ResultOur analysis indicated that MCI patients showed increased bidirectional effective connectivity in low‐gamma band (30‐48Hz) over MP (medial parietal)—Occ (occipital) and MP—MC (medial central) pairs in all the time periods during the motion task.ConclusionAltered effective connectivity measures in low‐gamma band may reflect compensatory brain activity among older individuals with MCI as they struggle to achieve comparable behavioral results to NC during the motion direction discrimination task. While effective connectivity may be decreased for MCI across certain region pairs (see Figures), a significant increase in effective connectivity in some other region pairs may be an indicator associated with AD and MCI pathology.Funding: NSF‐2032709/Li; NIH‐1R21AG046637‐01A1/Kavcic; NIH‐1R01AG054484‐01A1/Kavcic; NIH‐P30AG072931/Paulson and NIH‐P30AG024824/Yung.