Search

BackgroundEmerging evidence support the view that brain stimulation might improve essential tremor (ET) by altering brain networks and facilitating plasticity. Yet, we are still missing a mechanistic explanation of the whole brain dynamics underlying these plasticity defining changes.MethodIn this study, we explored the effect of low-frequency repetitive transcranial magnetic stimulation (rTMS) over left primary motor cortex (L-M1) on functional connectivity dynamics (FCD) in patients with ET. Resting-state fMRI (RsfMRI) was acquired before and after a single session of rTMS in 30 patients with ET and compared with RsfMRI of 20 age and gender matched healthy controls (HCs). We have measured the effect of brain stimulation using network topological re-organization through whole brain integration and segregation, brain stability and capacity of neural propagation through metastability and intrinsic ignition.ResultsPatients with ET had altered FCD measures compared to controls. After a single session rTMS, the brain connectivity measures approached normality and patients with ET revealed significantly higher integration, lower segregation with higher metastability and increased intrinsic ignition.ConclusionBrain metastability and intrinsic ignition measures could be valuable tools in appreciating mechanisms of brain stimulation in ET and other neurological diseases.

Background: In transcranial direct current stimulation (tDCS), the injected current becomes distributed across the brain areas. The objective is to stimulate the target region of interest (ROI) while minimizing the current in non-target ROIs (the ‘focality’ of tDCS). For this purpose, determining the appropriate current dose for an individual is difficult. Aim: To introduce a dose–target determination index (DTDI) to quantify the focality of tDCS and examine the dose–focality relationship in three different populations. Method: Here, we extended our previous toolbox i-SATA to the MNI reference space. After a tDCS montage is simulated for a current dose, the i-SATA(MNI) computes the average (over voxels) current density for every region in the brain. DTDI is the ratio of the average current density at the target ROI to the ROI with a maximum value (the peak region). Ideally, target ROI should be the peak region, so DTDI shall range from 0 to 1. The higher the value, the better the dose. We estimated the variation of DTDI within and across individuals using T1-weighted brain images of 45 males and females distributed equally across three age groups: (a) young adults (20 ≤ x ˂ 40 years), (b) mid adults (40 ≤ x ˂ 60 years), and (c) older adults (60 ≤ x ˂ 80 years). DTDI’s were evaluated for the frontal montage with electrodes at F3 and the right supraorbital for three current doses of 1 mA, 2 mA, and 3 mA, with the target ROI at the left middle frontal gyrus. Result: As the dose is incremented, DTDI may show (a) increase, (b) decrease, and (c) no change across the individuals depending on the relationship (nonlinear or linear) between the injected tDCS current and the distribution of current density in the target ROI. The nonlinearity is predominant in older adults with a decrease in focality. The decline is stronger in males. Higher current dose at older age can enhance the focality of stimulation. Conclusion: DTDI provides information on which tDCS current dose will optimize the focality of stimulation. The recommended DTDI dose should be prioritized based on the age (&gt, 40 years) and sex (especially for males) of an individual. The toolbox i-SATA(MNI) is freely available.

There is significant interest in understanding the pathophysiology of Obsessive-Compulsive Disorder (OCD) using resting-state fMRI (rsfMRI). Previous studies acknowledge abnormalities within and beyond the fronto-striato-limbic circuit in OCD that require further clarifications. However, limited information could be inferred from the conventional way of investigating the functional connectivity differences between OCD and healthy controls. Here, we identified altered brain organization in patients with OCD by applying individual-based approaches to maximize the identification of underlying network-based features specific to the OCD group. rsfMRI of 20 patients with OCD and 22 controls were preprocessed, and individual-fMRI-subspace was derived for each subject within each group. We evaluated group differences in functional connectivity using individual-fMRI-subspace and established its advantage over conventional-fMRI methodology. We applied prediction-based approaches to highlight the group differences by evaluating the differences in functional connections that predicted the clinical scores (namely, the Obsessive-Compulsive Inventory-Revised (OCI-R) and Hamilton Anxiety Rating Scale). Then, we explored the brain network organization of both groups by estimating the subject-specific communities within each group. Lastly, we evaluated associations between the inter-individual variation of nodes in the communities to clinical measures using linear regression. Functional connectivity analysis using individual-fMRI-subspace detected 83 connections that were different between OCD and control groups, compared to none found using conventional-fMRI methodology. Connectome-based prediction analysis did not show significant overlap between the two groups in the functional connections that predicted the clinical scores. This suggests that the functional architecture in patients with OCD may be different compared to controls. Seven communities were found in both groups. Interestingly, within the OCD group but not controls, we observed functional connectivity between cerebellar and visual regions, and lack of connectivity between striato-limbic and frontal areas. Inter-individual variations in the community-size of these two communities were also associated with the OCI-R score (p

Continuous InkJet (CIJ) printing is a common 2-Dimensional printing technique that creates jets of ink that breakup into drops as they are propelled towards a substrate to create a print. Inkjet printing has been used not only to print on paper, but to manufacture a variety of devices including OLEDs, solar cells and microfluidic devices. In many cases, the ‘ink’ consists of a polymer dissolved in a volatile solvent. As this ink is sprayed on to the substrate, the solvent evaporates, leaving the polymer behind as the print. The addition of the polymer alters the physics of the problem significantly enough that it varies greatly from jetting only a fluid with nothing dissolved in it. Polymers impart viscoelasticity to the solution, creating ink jets that are long-lived and difficult to break into droplets. In order to maintain the formation of drops in a repeatable, uniform fashion, a disturbance of known magnitude is imposed upon the jet. While jetting a liquid with no additives in it, this disturbance governed jet breakup leads to the formation of satellite drops, smaller drops of fluid in-between the main jet drops. Satellite drops are an undesirable occurrence in inkjet printing because of their unpredictable behavior and potential to affect the quality of the print. However, the addition of polymers to the liquid can control and potentially suppress the formation of these satellite drops, greatly improving the print quality. The elasticity of iv the polymer and its ability to influence the jet behavior and formation of satellite drops is highly dependent on multiple factors including the backbone rigidity, molecular weight and the concentration in which it is present in the fluid. Strongly viscoelastic effects have a marked effect on the jet and their presence can be quantified quite easily. However, some polymers show weak viscoelastic behavior while present in the ink fluids and may or may not affect the jetting process. The objective of this study is to examine such a class of polymeric fluids that are weakly viscoelastic in the context of inkjet printing and satellite drop formation. Firstly, the fluids are tested in an extensional rheology setup called Capillary Breakup Extensional Rheometry – Drop-on-Substrate (CaBER-DoS) to quantify their extensional properties. Then, they are tested in an emulated inkjet printing setup. The goal is to quantify the impact of the aforementioned factors on jetting and using satellite drop behavior as a guiding metric to understanding viscoelastic behavior in inkjet printing fluids.

BackgroundTranscranial Direct Current Stimulation (tDCS) is a technique where a weak current is passed through the electrodes placed on the scalp. The distribution of the electric current induced in the brain due to tDCS is provided by simulation toolbox like Realistic-volumetric-Approach-based-Simulator-for-Transcranial-electric-stimulation (ROAST). However, the procedure to estimate the total current density induced at the target and the intermediary region of the cortex is complex. The Systematic-Approach-for-tDCS-Analysis (SATA) was developed to overcome this problem. However, SATA is limited to standardized headspace only. Here we develop individual-SATA (𝓲-SATA) to extend it to individual head.MethodT1-weighted images of 15 subjects were taken from two Magnetic Resonance Imaging (MRI) scanners of different strengths. Across the subjects, the montages were simulated in ROAST. 𝓲-SATA converts the ROAST output to Talairach space. The x, y and z coordinates of the anterior commissure (AC), posterior commissure (PC), and Mid-Sagittal (MS) points are necessary for the conversion. AC and PC are detected using the acpcdetect toolbox. We developed a method to determine the MS in the image and cross-verified its location manually using BrainSight®.ResultDetermination of points with 𝓲-SATA is fast and accurate. The 𝓲-SATA provided estimates of the current-density induced across an individual’s cortical lobes and gyri as tested on images from two different scanners.ConclusionResearchers can use 𝓲-SATA for customizing tDCS-montages. With 𝓲-SATA it is also easier to compute the inter-individual variation in current-density across the target and intermediary regions of the brain. The software is publicly available.

Introduction tDCS can modulate reading which is processed by lexical (ventral) and sub-lexical (dorsal) pathways. Previous research indicates that pathway recruitment in bilinguals depends on a script's orthographic depth and a reader's proficiency with it. The effect of tDCS on each reading pathway has not been investigated in bilinguals. We stimulated the left dorsal and ventral pathways separately in Chinese-English (C-E) bilinguals to understand whether pathway-specific modulation by tDCS is possible and, if so, how it is influenced by orthographic depth and script proficiency. Methods A double-blind, sham-controlled, within-subject experiment was designed wherein 16 balanced bilinguals received anodal tDCS in dorsal, ventral and sham sessions. Two tDCS montages of electrode sizes 5 × 5 cm2 with 1) anode at CP5 and cathode at CZ, and 2) anode at TP7 and cathode at nape of the neck, were applied for stimulating the dorsal and ventral pathways respectively. Bilinguals were asked to read word lists for each language before and after stimulation. RTs for accurate trials were analysed using linear mixed-effect modelling that included proficiency scores for reading English pseudo-words (PW) and Chinese pinyin. Results For both languages, word reading RTs were faster following dorsal pathway stimulation. The dorsal stimulation effect (change in RT) was negatively correlated with pseudoword reading and pinyin proficiency. Stimulation of the ventral pathway decreased RTs only for Chinese reading. Conclusion Dorsal and ventral reading pathways can be selectively modulated by tDCS in bilingual readers with dorsal (sub-lexical) pathway stimulation affecting reading in both scripts and ventral (lexical) pathway stimulation selectively affecting Chinese reading. Dorsal pathway tDCS effects are modulated by sub-lexical reading proficiency.

Patterns in resting-state fMRI (rs-fMRI) are widely used to characterize the trait effects of brain function. In this aspect, multiple rs-fMRI scans from single subjects can provide interesting clues about the rs-fMRI patterns, though scan-to-scan variability pose challenges. Therefore, rs-fMRI’s are either concatenated or the functional connectivity is averaged. This leads to loss of information. Here, we use an alternative way to extract the rs-fMRI features that are common across all the scans by applying Common-and-Orthogonal-Basis-Extraction (COBE) technique. To address this, we employed rs-fMRI of 788 subjects from the human connectome project and estimated the common-COBE-component of each subject from the four rs-fMRI runs. Since the common-COBE-component are specific to a subject, the pattern was used to classify the subjects based on the similarity/dissimilarity of the features. The subset of subjects (n=107) with maximal-COBE-Dissimilarity (MCD) was extracted and the remaining subjects (n = 681) formed the COBE-similarity (CS) group. The distribution of weights of the common-COBE-component for the two groups across rs-fMRI networks and subcortical regions was evaluated. We found the weights in the default mode network to be lower in the MCD compared to the CS. We compared the scores of 69 behavioral measures and found 6 behaviors related to the use of marijuana, illicit drugs, alcohol, and tobacco; and including a measure of antisocial personality to differentiate the two groups. Gender differences were also significant. Altogether findings suggested that subtypes exist even in healthy control population and comparison studies (Case vs Control) need to be mindful of it.

Modulating higher cognitive functions like reading with transcranial direct current stimulation (tDCS) can be challenging as reading involves regions in the dorsal and ventral cortical areas that lie in close proximity. If the two pathways are stimulated simultaneously, the function of dorsal pathway (predominantly used for graphophonological conversion) might interfere with the function of the ventral pathway (used for semantics), and vice-versa. To achieve functional specificity in tDCS for investigating the two pathways of reading, it is important to stimulate each pathway per session such that the spread of current across the cortical areas due to the two montages has minimal overlap. The present study intends to achieve this by introducing a systematic approach for tDCS analysis. We employed the COMETS2 software to simulate 10 montage configurations (5 for each pathway) for three electrode sizes: 5 × 5, 3 × 3, and 5 × 7 cm2. This diversity in montage configuration is chosen since previous studies found the position and the size of anode and cathode to play an important role. The values of the magnitude of current density (MCD) obtained from the configuration were used to calculate: (i) average MCD in each cortical lobe, (ii) number of overlapping coordinates, and (iii) cortical areas with high MCD. The measures (i) and (iii) ascertained the current spread by each montage within a cortical lobe, and (ii) verified the overlap of the spread of current between a pair of montages. The analyses show that a montage using the electrode size of 5 × 5 cm2 with the anode at CP5 and cathode at CZ, and another with anode at TP7 and cathode at nape of the neck are optimal choices for dorsal and ventral pathways, respectively. To verify, we cross-validated the results with ROAST. This systematic approach was helpful in reducing the ambiguity of montage selection prior to conducting a tDCS study.

Patterns in resting-state fMRI (rs-fMRI) are widely used to characterize the trait effects of brain function. In this aspect, multiple rs-fMRI scans from single subjects can provide interesting clues about the rs-fMRI patterns, though scan-to-scan variability pose challenges. Therefore, rs-fMRI's are either concatenated or the functional connectivity is averaged. This leads to loss of information. Here, we use an alternative way to extract the rs-fMRI features that are common across all the scans by applying common-and-orthogonal-basis-extraction (COBE) technique. To address this, we employed rs-fMRI of 788 subjects from the human connectome project and estimated the common-COBE-component of each subject from the four rs-fMRI runs. Since the common-COBE-component is specific to a subject, the pattern was used to classify the subjects based on the similarity/dissimilarity of the features. The subset of subjects (n = 107) with maximal-COBE-dissimilarity (MCD) was extracted and the remaining subjects (n = 681) formed the COBE-similarity (CS) group. The distribution of weights of the common-COBE-component for the two groups across rs-fMRI networks and subcortical regions was evaluated. We found the weights in the default mode network to be lower in the MCD compared to the CS. We compared the scores of 69 behavioral measures and found six behaviors related to the use of marijuana, illicit drugs, alcohol, and tobacco; and including a measure of antisocial personality to differentiate the two groups. Gender differences were also significant. Altogether the findings suggested that subtypes exist even in healthy control population, and comparison studies (case vs. control) need to be mindful of it. Nanyang Technological University National Medical Research Council (NMRC) National Research Foundation (NRF) Published version Singapore National Research Foundation (NRF)Fellowship; NUS YIA; Singapore NMRC, Grant/Award Number: CBRG/0088/20 15; NUS SOMAspiration Fund, Grant/Award Number:R185000271720; National University of SingaporeStrategic Research, Grant/Award Number:DPRT/944/09/14; Nanyang TechnologicalUniversity Start-Up Grant (NTU-SUG).

Objective. Transcranial Direct Current Stimulation (tDCS) is a technique where a weak current is passed through the electrodes placed on the scalp. The distribution of the electric current induced in the brain due to tDCS is provided by simulation toolbox like Realistic volumetric Approach based Simulator for Transcranial electric stimulation (ROAST). However, the procedure to estimate the total current density induced at the target and the intermediary region of the cortex is complex. The Systematic-Approach-for-tDCS-Analysis (SATA) was developed to overcome this problem. However, SATA is limited to standardized (MNI152) headspace only. Here we develop individual-SATA (i-SATA) to extend it to individual head. Approach. T1-weighted images of 15 subjects were taken from two Magnetic Resonance Imaging scanners of different strengths. Across the subjects, the montages were simulated in ROAST. i-SATA converts the ROAST output to Talairach space. The x, y and z coordinates of the anterior commissure (AC), posterior commissure (PC), and Mid-Sagittal (MS) points are necessary for the conversion. AC and PC are detected using the acpcdetect toolbox. We developed a method to determine the MS in the image and cross-verified its location manually using BrainSight®. Main results. Determination of points with i-SATA is fast and accurate. The i-SATA provided estimates of the current-density induced across an individual’s cortical lobes and gyri as tested on images from two different scanners. Significance. Researchers can use i-SATA for customizing tDCS-montages. With i-SATA it is also easier to compute the inter-individual variation in current-density across the target and intermediary regions of the brain. The software is publicly available.

There is significant interest in using resting-state functional connectivity (RSFC) to predict human behavior. Good behavioral prediction should in theory require RSFC to be sufficiently distinct across participants; if RSFC were the same across participants, then behavioral prediction would obviously be poor. Therefore, we hypothesize that removing common resting-state functional magnetic resonance imaging (rs-fMRI) signals that are shared across participants would improve behavioral prediction. Here, we considered 803 participants from the human connectome project (HCP) with four rs-fMRI runs. We applied the common and orthogonal basis extraction (COBE) technique to decompose each HCP run into two subspaces: a common (group-level) subspace shared across all participants and a subject-specific subspace. We found that the first common COBE component of the first HCP run was localized to the visual cortex and was unique to the run. On the other hand, the second common COBE component of the first HCP run and the first common COBE component of the remaining HCP runs were highly similar and localized to regions within the default network, including the posterior cingulate cortex and precuneus. Overall, this suggests the presence of run-specific (state-specific) effects that were shared across participants. By removing the first and second common COBE components from the first HCP run, and the first common COBE component from the remaining HCP runs, the resulting RSFC improves behavioral prediction by an average of 11.7% across 58 behavioral measures spanning cognition, emotion and personality. Ministry of Education (MOE) National Medical Research Council (NMRC) National Research Foundation (NRF) This work was supported by Singapore MOE Tier 2 (MOE2014-T2-2-016), NUS Strategic Research (DPRT/944/09/14), NUS SOM Aspiration Fund (R185000271720), Singapore NMRC (CBRG/0088/2015), NUS YIA and the Singapore National Research Foundation (NRF) Fellowship (Class of 2017). Our research also utilized resources provided by the Center for Functional Neuroimaging Technologies , P41EB015896 and instruments supported by 1S10RR023401, 1S10RR019307, and 1S10RR023043 from the Athinoula A. Martinos Center for Biomedical Imaging at the Massachusetts General Hospital. Our computational work was partially performed on resources of the National Supercomputing Center, Singapore (https://www.nscc.sg). Data were provided by the Human Connectome Project, WU-Minn Consortium (Principal Investigators: David Van Essen and Kamil Ugurbil; 1U54MH091657) funded by the 16 NIH Institutes and Centers that support the NIH Blueprint for Neuroscience Research ; and by the McDonnell Center for Systems Neuroscience at Washington University.

Repetition priming, that is, the repeated processing of a stimulus, facilitates performance. However, the neural underpinnings of repetition priming for famous faces in terms of effective connectivity are not known. Here we investigated this problem using dynamic causal modelling of latency-corrected event-related brain potentials (RERPs). Source waveforms of RERP-derived sources in the Occipital Lobe, Fusiform Gyrus, Mediotemporal Lobe, Prefrontal Cortex and Anterotemporal Lobe of each hemisphere entered into models with only forward (F) or also with backward (FB) connections. Based on the framework of predictive coding formulated for repetition suppression, modulations of F and FB connections were expected for sources that displayed priming effects in their source waveforms. Hence, neural sources in each hemisphere were fitted with either F or FB connections. Inter-hemispheric connections were considered between homologous areas and were allowed to be modulated in an incremental manner resulting in a model space that comprised of 24 models. Bayesian model averaging across models revealed effective bidirectional connectivity between the Fusiform Gyrus (face perception) and Prefrontal Cortex (decision-making) in both hemispheres to be modulated by priming. In the left hemisphere, there is also a substantial involvement from the Mediotemporal Lobe, indicating the facilitation of automatic retrieval of the famous person's name. Furthermore, there is evidence that the priming is supported by connections from the right to the left Fusiform Gyri possibly in the service of inter-hemispheric cooperation. Altogether, the study indicates that along with top-down modulations, efficient processing within and across the two hemispheres is crucial for famous face priming. Ministry of Education (MOE) National Medical Research Council (NMRC) National Research Foundation (NRF) This work was partially supported by Hong Kong Baptist University (HKBU) Strategic Development Fund, the Hong Kong PhD Fellowship Scheme, the HKBU Faculty Research Grant (FRG2/14-15/025), and GRF 12302914. This research was conducted using the resources of the High Performance Cluster Computing Centre, Hong Kong Baptist University, which receives funding from RGC, University Grant Committee of the HKSAR and HKBU. Funding support was also obtained from Singapore MOE Tier 2 (MOE2014-T2-2-016), NUS Strategic Research (DPRT/944/09/14), NUS SOM Aspiration Fund (R185000271720), Singapore NMRC (CBRG/0088/2015), NUS YIA and the Singapore National Research Foundation (NRF) Fellowship (Class of 2017).

The late components of event-related brain potentials (ERPs) pose a difficult problem in source localization. One of the reasons is the smearing of these components in conventional averaging because of trial-to-trial latency-variability. The smearing problem may be addressed by reconstructing the ERPs after latency synchronization with the Residue Iteration Decomposition (RIDE) method. Here we assessed whether the benefits of RIDE at the surface level also improve source localization of RIDE-reconstructed ERPs (RERPs) measured in a face priming paradigm. Separate source models for conventionally averaged ERPs and RERPs were derived and sources were localized for both early and late components. Jackknife averaging on the data was used to reduce the residual variance during source localization compared to conventional source model fitting on individual subject data. Distances between corresponding sources of both ERP and RERP models were measured to check consistency in both source models. Sources for activity around P100, N170, early repetition effect (ERE/N250r) and late repetition effect (LRE/N400) were reported and priming effects in these sources were evaluated for six time windows. Significant improvement in priming effect of the late sources was found from the RERP source model, especially in the Medio-Temporal Lobe, Prefrontal Cortex, and Anterior Temporal Lobe. Consistent with previous studies, we found early priming effects in the right hemisphere and late priming effects in the left hemisphere. Also, the priming effects in right hemisphere outnumbered the left hemisphere, signifying dominance of right hemisphere in face recognition. In conclusion, RIDE reconstructed ERPs promise a comprehensive understanding of the time-resolved dynamics the late sources play during face recognition.

The late components of ERPs pose difficult problem in source localization because latency jitter smears peak arising from conventional averaging. RIDE, a technique developed to solve smearing in ERP components, improves scalp topography. Our study assessed whether the benefits of RIDE at surface level could improve source localization of RIDE-transformed ERPs (RERPs) from a face priming task. Separate source models for ERP and RERP were created and sources were localized. Jackknife averaging reduced the residual variance compared to source model fitting on individual subject data. Priming effects (PE) in the sources were calculated for three early and three late time windows. Significant improvement in PE is found from RERP sources especially in the late sources. We found early PE in right hemisphere and late PE in left hemisphere, indicating earlier face processing in right. Also, the PE in right hemisphere outnumbered the left, signifying right hemispheric dominance of face recognition.