Publications by authors named "Sangkyun Lee"

20 Publications

  • Page 1 of 1

Deep-sea water displacement from a turbidity current induced by the Super Typhoon Hagibis.

PeerJ 2020 9;8:e10429. Epub 2020 Dec 9.

Research and Development Partnership for Next Generation Technology of Marine Resources Survey (J-MARES) / JGI, Inc., Tokyo, Japan.

Turbidity currents are the main drivers behind the transportation of terrestrial sediments to the deep sea, and turbidite deposits from such currents have been widely used in geological studies. Nevertheless, the contribution of turbidity currents to vertical displacement of seawater has rarely been discussed. This is partly because until recently, deep-sea turbidity currents have rarely been observed due to their unpredictable nature, being usually triggered by meteorological or geological events such as typhoons and earthquakes. Here, we report a direct observation of a deep-sea turbidity current using the recently developed Edokko Mark 1 monitoring system deployed in 2019 at a depth of 1,370 m in Suruga Bay, central Japan. A turbidity current occurred two days after its probable cause, the Super Typhoon Hagibis (2019), passed through Suruga Bay causing devastating damage. Over aperiod of 40 hours, we observed increased turbidity with turbulent conditions confirmed by a video camera. The turbidity exhibited two sharp peaks around 3:00 and 11:00 on October 14 (Japan Standard Time). The temperature and salinity characteristics during these high turbidity events agreed with independent measurements for shallow water layers in Suruga Bay at the same time, strongly suggesting that the turbidity current caused vertical displacement in the bay's water column by transporting warmer and shallower waters downslope of the canyon. Our results add to the previous few examples that show meteorological and geological events may have significant contributions in the transportation of shallower seawater to the deep sea. Recent technological developments pertaining to the Edokko Mark 1 and similar devices enable straightforward, long-term monitoring of the deep-seafloor and will contribute to the understanding of similar spontaneous events in the deep ocean.
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http://dx.doi.org/10.7717/peerj.10429DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7733332PMC
December 2020

Internal Gain Modulations, But Not Changes in Stimulus Contrast, Preserve the Neural Code.

J Neurosci 2019 02 15;39(9):1671-1687. Epub 2019 Jan 15.

Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02115, and

Neurons in primary visual cortex are strongly modulated both by stimulus contrast and by fluctuations of internal inputs. An important question is whether the population code is preserved under these conditions. Changes in stimulus contrast are thought to leave the population code invariant, whereas the effect of internal gain modulations remains unknown. To address these questions we studied how the direction-of-motion of oriented gratings is encoded in layer 2/3 primary visual cortex of mouse (with C57BL/6 background, of either sex). We found that, because contrast gain responses across cells are heterogeneous, a change in contrast alters the information distribution profile across cells leading to a violation of contrast invariance. Remarkably, internal input fluctuations that cause commensurate firing rate modulations at the single-cell level result in more homogeneous gain responses, respecting population code invariance. These observations argue that the brain strives to maintain the stability of the neural code in the face of fluctuating internal inputs. Neuronal responses are modulated both by stimulus contrast and by the spontaneous fluctuation of internal inputs. It is not well understood how these different types of input impact the population code. Specifically, it is important to understand whether the neural code stays invariant in the face of significant internal input modulations. Here, we show that changes in stimulus contrast lead to different optimal population codes, whereas spontaneous internal input fluctuations leave the population code invariant. This is because spontaneous internal input fluctuations modulate the gain of neuronal responses more homogeneously across cells compared to changes in stimulus contrast.
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http://dx.doi.org/10.1523/JNEUROSCI.2012-18.2019DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6391566PMC
February 2019

The mutational landscape of , and driven murine neuroblastoma mimics human disease.

Oncotarget 2018 Feb 22;9(9):8334-8349. Epub 2017 Dec 22.

Center for Medical Genetics, Ghent University, Ghent, Belgium.

Genetically engineered mouse models have proven to be essential tools for unraveling fundamental aspects of cancer biology and for testing novel therapeutic strategies. To optimally serve these goals, it is essential that the mouse model faithfully recapitulates the human disease. Recently, novel mouse models for neuroblastoma have been developed. Here, we report on the further genomic characterization through exome sequencing and DNA copy number analysis of four of the currently available murine neuroblastoma model systems ( Th- Dbh- and ). The murine tumors revealed a low number of genomic alterations - in keeping with human neuroblastoma - and a positive correlation of the number of genetic lesions with the time to onset of tumor formation was observed. Gene copy number alterations are the hallmark of both murine and human disease and frequently affect syntenic genomic regions. Despite low mutational load, the genes mutated in murine disease were found to be enriched for genes mutated in human disease. Taken together, our study further supports the validity of the tested mouse models for mechanistic and preclinical studies of human neuroblastoma.
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http://dx.doi.org/10.18632/oncotarget.23614DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5823580PMC
February 2018

Visually Driven Neuropil Activity and Information Encoding in Mouse Primary Visual Cortex.

Front Neural Circuits 2017 21;11:50. Epub 2017 Jul 21.

Department of Neurology, Brigham and Women's HospitalBoston, MA, United States.

Cortical neuropil modulations recorded by calcium imaging reflect the activity of large aggregates of axo-dendritic processes and synaptic compartments from a large number of neurons. The organization of this activity impacts neuronal firing but is not well understood. Here we used 2-photon imaging with Oregon Green Bapta (OGB) and GCaMP6s to study neuropil visual responses to moving gratings in layer 2/3 of mouse area V1. We found neuropil responses to be strongly modulated and more reliable than neighboring somatic activity. Furthermore, stimulus independent modulations in neuropil activity, i.e., noise correlations, were highly coherent across the cortical surface, up to distances of at least 200 μm. Pairwise neuropil-to-neuropil-patch noise correlation strength was much higher than cell-to-cell noise correlation strength and depended strongly on brain state, decreasing in quiet wakefulness relative to light anesthesia. The profile of neuropil noise correlation strength decreased gently with distance, dropping by ~11% at a distance of 200 μm. This was comparatively slower than the profile of cell-to-cell noise correlations, which dropped by ~23% at 200 μm. Interestingly, in spite of the "salt & pepper" organization of orientation and direction encoding across mouse V1 neurons, populations of neuropil patches, even of moderately large size (radius ~100 μm), showed high accuracy for discriminating perpendicularly moving gratings. This was commensurate to the accuracy of corresponding cell populations. The dynamic, stimulus dependent, nature of neuropil activity further underscores the need to carefully separate neuropil from cell soma activity in contemporary imaging studies.
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http://dx.doi.org/10.3389/fncir.2017.00050DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5519560PMC
May 2018

The Effect of Wealth Shocks on Loss Aversion: Behavior and Neural Correlates.

Front Neurosci 2017 27;11:237. Epub 2017 Apr 27.

Laboratory for Brain-Machine Interfaces and Neuromodulation, Pontificia Universidad Católica de ChileSantiago, Chile.

Kahneman and Tversky (1979) first demonstrated that when individuals decide whether or not to accept a gamble, potential losses receive more weight than possible gains in the decision. This phenomenon is referred to as loss aversion. We investigated how loss aversion in risky financial decisions is influenced by sudden changes to wealth, employing both behavioral and neurobiological measures. We implemented an fMRI experimental paradigm, based on that employed by Tom et al. (2007). There are two treatments, called RANDOM and CONTINGENT. In RANDOM, the baseline setting, the changes to wealth, referred to as wealth shocks in economics, are independent of the actual choices participants make. Under CONTINGENT, we induce the belief that the changes in income are a consequence of subjects' own decisions. The magnitudes and sequence of the shocks to wealth are identical between the CONTINGENT and RANDOM treatments. We investigated whether more loss aversion existed in one treatment than another. The behavioral results showed significantly greater loss aversion in CONTINGENT compared to RANDOM after a negative wealth shock. No differences were observed in the response to positive shocks. The fMRI results revealed a neural loss aversion network, comprising the bilateral striatum, amygdala and dorsal anterior cingulate cortex that was common to the CONTINGENT and RANDOM tasks. However, the ventral prefrontal cortex, primary somatosensory cortex and superior occipital cortex, showed greater activation in response to a negative change in wealth due to individual's own decisions than when the change was exogenous. These results indicate that striatum activation correlates with loss aversion independently of the source of the shock, and that the ventral prefrontal cortex (vPFC) codes the experimental manipulation of agency in one's actions influencing loss aversion.
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http://dx.doi.org/10.3389/fnins.2017.00237DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5406753PMC
April 2017

First Phase I human clinical trial of a killed whole-HIV-1 vaccine: demonstration of its safety and enhancement of anti-HIV antibody responses.

Retrovirology 2016 Nov 28;13(1):82. Epub 2016 Nov 28.

Department of Microbiology and Immunology, Schulich School of Medicine and Dentistry, The University of Western Ontario, 1400 Western Road, London, ON, N6G 2V4, Canada.

Background: Vaccination with inactivated (killed) whole-virus particles has been used to prevent a wide range of viral diseases. However, for an HIV vaccine this approach has been largely negated due to inherent safety concerns, despite the ability of killed whole-virus vaccines to generate a strong, predominantly antibody-mediated immune response in vivo. HIV-1 Clade B NL4-3 was genetically modified by deleting the nef and vpu genes and substituting the coding sequence for the Env signal peptide with that of honeybee melittin signal peptide to produce a less virulent and more replication efficient virus. This genetically modified virus (gmHIV-1) was inactivated and formulated as a killed whole-HIV vaccine, and then used for a Phase I human clinical trial (Trial Registration: Clinical Trials NCT01546818). The gmHIV-1 was propagated in the A3.01 human T cell line followed by virus purification and inactivation with aldrithiol-2 and γ-irradiation. Thirty-three HIV-1 positive volunteers receiving cART were recruited for this observer-blinded, placebo-controlled Phase I human clinical trial to assess the safety and immunogenicity.

Results: Genetically modified and killed whole-HIV-1 vaccine, SAV001, was well tolerated with no serious adverse events. HIV-1-specific PCR showed neither evidence of vaccine virus replication in the vaccine virus-infected human T lymphocytes in vitro nor in the participating volunteers receiving SAV001 vaccine. Furthermore, SAV001 with adjuvant significantly increased the pre-existing antibody response to HIV-1 proteins. Antibodies in the plasma of vaccinees were also found to recognize HIV-1 envelope protein on the surface of infected cells as well as showing an enhancement of broadly neutralizing antibodies inhibiting tier I and II of HIV-1 B, D, and A subtypes.

Conclusion: The killed whole-HIV vaccine, SAV001, is safe and triggers anti-HIV immune responses. It remains to be determined through an appropriate trial whether this immune response prevents HIV infection.
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http://dx.doi.org/10.1186/s12977-016-0317-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5126836PMC
November 2016

Nonlinear population receptive field changes in human area V5/MT+ of healthy subjects with simulated visual field scotomas.

Neuroimage 2015 Oct 3;120:176-90. Epub 2015 Jul 3.

Department of Neurology, Baylor College of Medicine, Houston, TX 77030, USA. Electronic address:

There is extensive controversy over whether the adult visual cortex is able to reorganize following visual field loss (scotoma) as a result of retinal or cortical lesions. Functional magnetic resonance imaging (fMRI) methods provide a useful tool to study the aggregate receptive field properties and assess the capacity of the human visual cortex to reorganize following injury. However, these methods are prone to biases near the boundaries of the scotoma. Retinotopic changes resembling reorganization have been observed in the early visual cortex of normal subjects when the visual stimulus is masked to simulate retinal or cortical scotomas. It is not known how the receptive fields of higher visual areas, like hV5/MT+, are affected by partial stimulus deprivation. We measured population receptive field (pRF) responses in human area V5/MT+ of 5 healthy participants under full stimulation and compared them with responses obtained from the same area while masking the left superior quadrant of the visual field ("artificial scotoma" or AS). We found that pRF estimations in area hV5/MT+ are nonlinearly affected by the AS. Specifically, pRF centers shift towards the AS, while the pRF amplitude increases and the pRF size decreases near the AS border. The observed pRF changes do not reflect reorganization but reveal important properties of normal visual processing under different test-stimulus conditions.
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http://dx.doi.org/10.1016/j.neuroimage.2015.06.085DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5327354PMC
October 2015

Mutational dynamics between primary and relapse neuroblastomas.

Nat Genet 2015 Aug 29;47(8):872-7. Epub 2015 Jun 29.

1] Pediatric Oncology and Hematology, University Children's Hospital Essen, University of Duisburg-Essen, Essen, Germany. [2] Pediatric Oncology and Hematology, Charité University Medicine, Berlin, Germany. [3] German Cancer Research Center (DKFZ), German Cancer Consortium (DKTK), Heidelberg, Germany.

Neuroblastoma is a malignancy of the developing sympathetic nervous system that is often lethal when relapse occurs. We here used whole-exome sequencing, mRNA expression profiling, array CGH and DNA methylation analysis to characterize 16 paired samples at diagnosis and relapse from individuals with neuroblastoma. The mutational burden significantly increased in relapsing tumors, accompanied by altered mutational signatures and reduced subclonal heterogeneity. Global allele frequencies at relapse indicated clonal mutation selection during disease progression. Promoter methylation patterns were consistent over disease course and were patient specific. Recurrent alterations at relapse included mutations in the putative CHD5 neuroblastoma tumor suppressor, chromosome 9p losses, DOCK8 mutations, inactivating mutations in PTPN14 and a relapse-specific activity pattern for the PTPN14 target YAP. Recurrent new mutations in HRAS, KRAS and genes mediating cell-cell interaction in 13 of 16 relapse tumors indicate disturbances in signaling pathways mediating mesenchymal transition. Our data shed light on genetic alteration frequency, identity and evolution in neuroblastoma.
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http://dx.doi.org/10.1038/ng.3349DOI Listing
August 2015

Sensitivity to cdk1-inhibition is modulated by p53 status in preclinical models of embryonal tumors.

Oncotarget 2015 Jun;6(17):15425-35

Department of Pediatric Oncology and Hematology, University Children's Hospital Essen, Essen, Germany.

Dysregulation of the cell cycle and cyclin-dependent kinases (cdks) is a hallmark of cancer cells. Intervention with cdk function is currently evaluated as a therapeutic option in many cancer types including neuroblastoma (NB), a common solid tumor of childhood. Re-analyses of mRNA profiling data from primary NB revealed that high level mRNA expression of both cdk1 and its corresponding cyclin, CCNB1, were significantly associated with worse patient outcome independent of MYCN amplification, a strong indicator of adverse NB prognosis. Cdk1 as well as CCNB1 expression were readily detectable in all embryonal tumor cell lines investigated. Pharmacological inhibition or siRNA-mediated knockdown of cdk1/CCNB1 induced proliferation arrest independent of MYCN status in NB cells. Sensitivity to cdk1 inhibition was modulated by TP53, which was demonstrated using isogenic cells with wild-type TP53 expressing either dominant-negative p53 or a short hairpin RNA directed against TP53. Apoptosis induced by cdk1 inhibition was dependent on caspase activation and was concomitant with upregulation of transcriptional targets of TP53. Our results confirm an essential role for the cdk1/CCNB1 complex in tumor cell survival. As relapsing embryonal tumors often present with p53 pathway alterations, these findings have potential implications for therapy approaches targeting cdks.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4558161PMC
http://dx.doi.org/10.18632/oncotarget.3908DOI Listing
June 2015

Topographical estimation of visual population receptive fields by FMRI.

J Vis Exp 2015 Feb 3(96). Epub 2015 Feb 3.

Department of Neuroscience and Neurology, Baylor College of Medicine.

Visual cortex is retinotopically organized so that neighboring populations of cells map to neighboring parts of the visual field. Functional magnetic resonance imaging allows us to estimate voxel-based population receptive fields (pRF), i.e., the part of the visual field that activates the cells within each voxel. Prior, direct, pRF estimation methods(1) suffer from certain limitations: 1) the pRF model is chosen a-priori and may not fully capture the actual pRF shape, and 2) pRF centers are prone to mislocalization near the border of the stimulus space. Here a new topographical pRF estimation method(2) is proposed that largely circumvents these limitations. A linear model is used to predict the Blood Oxygen Level-Dependent (BOLD) signal by convolving the linear response of the pRF to the visual stimulus with the canonical hemodynamic response function. PRF topography is represented as a weight vector whose components represent the strength of the aggregate response of voxel neurons to stimuli presented at different visual field locations. The resulting linear equations can be solved for the pRF weight vector using ridge regression(3), yielding the pRF topography. A pRF model that is matched to the estimated topography can then be chosen post-hoc, thereby improving the estimates of pRF parameters such as pRF-center location, pRF orientation, size, etc. Having the pRF topography available also allows the visual verification of pRF parameter estimates allowing the extraction of various pRF properties without having to make a-priori assumptions about the pRF structure. This approach promises to be particularly useful for investigating the pRF organization of patients with disorders of the visual system.
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http://dx.doi.org/10.3791/51811DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4354621PMC
February 2015

Robust selection of cancer survival signatures from high-throughput genomic data using two-fold subsampling.

PLoS One 2014 8;9(10):e108818. Epub 2014 Oct 8.

Department of Pediatric Oncology and Hematology, University Children's Hospital Essen, Essen, Germany.

Identifying relevant signatures for clinical patient outcome is a fundamental task in high-throughput studies. Signatures, composed of features such as mRNAs, miRNAs, SNPs or other molecular variables, are often non-overlapping, even though they have been identified from similar experiments considering samples with the same type of disease. The lack of a consensus is mostly due to the fact that sample sizes are far smaller than the numbers of candidate features to be considered, and therefore signature selection suffers from large variation. We propose a robust signature selection method that enhances the selection stability of penalized regression algorithms for predicting survival risk. Our method is based on an aggregation of multiple, possibly unstable, signatures obtained with the preconditioned lasso algorithm applied to random (internal) subsamples of a given cohort data, where the aggregated signature is shrunken by a simple thresholding strategy. The resulting method, RS-PL, is conceptually simple and easy to apply, relying on parameters automatically tuned by cross validation. Robust signature selection using RS-PL operates within an (external) subsampling framework to estimate the selection probabilities of features in multiple trials of RS-PL. These probabilities are used for identifying reliable features to be included in a signature. Our method was evaluated on microarray data sets from neuroblastoma, lung adenocarcinoma, and breast cancer patients, extracting robust and relevant signatures for predicting survival risk. Signatures obtained by our method achieved high prediction performance and robustness, consistently over the three data sets. Genes with high selection probability in our robust signatures have been reported as cancer-relevant. The ordering of predictor coefficients associated with signatures was well-preserved across multiple trials of RS-PL, demonstrating the capability of our method for identifying a transferable consensus signature. The software is available as an R package rsig at CRAN (http://cran.r-project.org).
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0108818PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4190101PMC
June 2015

A toolbox for real-time subject-independent and subject-dependent classification of brain states from fMRI signals.

Front Neurosci 2013 17;7:170. Epub 2013 Oct 17.

Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen Tübingen, Germany ; Graduate School of Neural & Behavioural Sciences International Max Planck Research School, University of Tübingen Tübingen, Germany ; Department of Biomedical Engineering, University of Florida Gainesville, FL, USA.

There is a recent increase in the use of multivariate analysis and pattern classification in prediction and real-time feedback of brain states from functional imaging signals and mapping of spatio-temporal patterns of brain activity. Here we present MANAS, a generalized software toolbox for performing online and offline classification of fMRI signals. MANAS has been developed using MATLAB, LIBSVM, and SVMlight packages to achieve a cross-platform environment. MANAS is targeted for neuroscience investigations and brain rehabilitation applications, based on neurofeedback and brain-computer interface (BCI) paradigms. MANAS provides two different approaches for real-time classification: subject dependent and subject independent classification. In this article, we present the methodology of real-time subject dependent and subject independent pattern classification of fMRI signals; the MANAS software architecture and subsystems; and finally demonstrate the use of the system with experimental results.
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http://dx.doi.org/10.3389/fnins.2013.00170DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3798026PMC
October 2013

A new method for estimating population receptive field topography in visual cortex.

Neuroimage 2013 Nov 16;81:144-157. Epub 2013 May 16.

Max Planck Institute for Biological Cybernetics, Spemannstr. 38, 72076 Tübingen, Germany; Bernstein Center for Computational Neuroscience, Tübingen, Germany.

We introduce a new method for measuring visual population receptive fields (pRF) with functional magnetic resonance imaging (fMRI). The pRF structure is modeled as a set of weights that can be estimated by solving a linear model that predicts the Blood Oxygen Level-Dependent (BOLD) signal using the stimulus protocol and the canonical hemodynamic response function. This method does not make a priori assumptions about the specific pRF shape and is therefore a useful tool for uncovering the underlying pRF structure at different spatial locations in an unbiased way. We show that our method is more accurate than a previously described method (Dumoulin and Wandell, 2008) which directly fits a 2-dimensional isotropic Gaussian pRF model to predict the fMRI time-series. We demonstrate that direct-fit models do not fully capture the actual pRF shape, and can be prone to pRF center mislocalization when the pRF is located near the border of the stimulus space. A quantitative comparison demonstrates that our method outperforms the direct-fit methods in the pRF center modeling by achieving higher explained variance of the BOLD signal. This was true for direct-fit isotropic Gaussian, anisotropic Gaussian, and difference of isotropic Gaussians model. Importantly, our model is also capable of exploring a variety of pRF properties such as surround suppression, receptive field center elongation, orientation, location and size. Additionally, the proposed method is particularly attractive for monitoring pRF properties in the visual areas of subjects with lesions of the visual pathways, where it is difficult to anticipate what shape the reorganized pRF might take. Finally, the method proposed here is more efficient in computation time than direct-fit methods, which need to search for a set of parameters in an extremely large searching space. Instead, this method uses the pRF topography to constrain the space that needs to be searched for the subsequent modeling.
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http://dx.doi.org/10.1016/j.neuroimage.2013.05.026DOI Listing
November 2013

The obese brain athlete: self-regulation of the anterior insula in adiposity.

PLoS One 2012 8;7(8):e42570. Epub 2012 Aug 8.

MEG Center, University of Tübingen, Tübingen, Germany.

The anterior insular cortex (AIC) is involved in emotional processes and gustatory functions which can be examined by imaging techniques. Such imaging studies showed increased activation in the insula in response to food stimuli as well as a differential activation in lean and obese people. Additionally, studies investigating lean subjects established the voluntary regulation of the insula by a real-time functional magnetic resonance imaging-brain computer interface (rtfMRI-BCI) approach. In this exploratory study, 11 lean and 10 obese healthy, male participants were investigated in a rtfMRI-BCI protocol. During the training sessions, all obese participants were able to regulate the activity of the AIC voluntarily, while four lean participants were not able to regulate at all. In successful regulators, functional connectivity during regulation vs. relaxation between the AIC and all other regions of the brain was determined by a seed voxel approach. Lean in comparison to obese regulators showed stronger connectivity in cingular and temporal cortices during regulation. We conclude, that obese people possess an improved capacity to self-regulate the anterior insula, a brain system tightly related to bodily awareness and gustatory functions.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0042570PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3414443PMC
February 2013

Species-specific response to human infant faces in the premotor cortex.

Neuroimage 2012 Apr 2;60(2):884-93. Epub 2012 Jan 2.

Institute of Medical Psychology and Behavioral Neurobiology Eberhard Karls University of Tübingen, Tübingen, Germany.

The human infant face represents an essential source of communicative signals on the basis of which adults modulate their interactions with infants. Behavioral studies demonstrate that infants' faces activate sensitive and attuned responses in adults through their gaze, face expression, voice, and gesture. In this study we aimed to identify brain responses that underlie adults' general propensity to respond to infant faces. We recorded fMRI during adults' (non-parents) processing of unfamiliar infant faces compared to carefully matched adult faces and infrahuman mammal infant and adult faces. Human infant faces activated several brain systems including the lateral premotor cortex, supplementary motor area, cingulate cortex, anterior insula and the thalamus. Activation of these brain circuits suggests adults' preparation for communicative behavior with infants as well as attachment and caregiving. The same brain regions preferentially responded to human infant faces when compared to animal infant faces, indicating species-specific adult brain responses. Moreover, results of support vector machine based classification analysis indicated that these regions allowed above chance-level prediction of brain state during perception of human infant faces. The complex of brain responses to human infant faces appears to include biological mechanisms that underlie responsiveness and a caring inclination toward young children which appear to transcend adult's biological relationship to the baby.
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http://dx.doi.org/10.1016/j.neuroimage.2011.12.068DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3557818PMC
April 2012

Acquired self-control of insula cortex modulates emotion recognition and brain network connectivity in schizophrenia.

Hum Brain Mapp 2013 Jan 22;34(1):200-12. Epub 2011 Oct 22.

Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Germany.

Real-time functional magnetic resonance imaging (rtfMRI) is a novel technique that has allowed subjects to achieve self-regulation of circumscribed brain regions. Despite its anticipated therapeutic benefits, there is no report on successful application of this technique in psychiatric populations. The objectives of the present study were to train schizophrenia patients to achieve volitional control of bilateral anterior insula cortex on multiple days, and to explore the effect of learned self-regulation on face emotion recognition (an extensively studied deficit in schizophrenia) and on brain network connectivity. Nine patients with schizophrenia were trained to regulate the hemodynamic response in bilateral anterior insula with contingent rtfMRI neurofeedback, through a 2-weeks training. At the end of the training stage, patients performed a face emotion recognition task to explore behavioral effects of learned self-regulation. A learning effect in self-regulation was found for bilateral anterior insula, which persisted through the training. Following successful self-regulation, patients recognized disgust faces more accurately and happy faces less accurately. Improvements in disgust recognition were correlated with levels of self-activation of right insula. RtfMRI training led to an increase in the number of the incoming and outgoing effective connections of the anterior insula. This study shows for the first time that patients with schizophrenia can learn volitional brain regulation by rtfMRI feedback training leading to changes in the perception of emotions and modulations of the brain network connectivity. These findings open the door for further studies of rtfMRI in severely ill psychiatric populations, and possible therapeutic applications.
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http://dx.doi.org/10.1002/hbm.21427DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6869886PMC
January 2013

Detection of cerebral reorganization induced by real-time fMRI feedback training of insula activation: a multivariate investigation.

Neurorehabil Neural Repair 2011 Mar-Apr;25(3):259-67

University of Tübingen, Tübingen, Germany.

Background: Studies with real-time functional magnetic resonance imaging (fMRI) demonstrate that humans volitionally regulate hemodynamic signals from circumscribed regions of the brain, leading to area-specific behavioral consequences. Methods to better determine the nature of dynamic functional interactions between different brain regions and plasticity due to self-regulation training are still in development.

Objective: The authors investigated changes in brain states while training 6 healthy participants to self-regulate insular cortex by real-time fMRI feedback.

Method: The authors used multivariate pattern analysis to observe spatial pattern changes and a multivariate Granger causality model to show changes in temporal interactions in multiple brain areas over the course of 5 repeated scans per subject during positive and negative emotional imagery with feedback about the level of insular activation.

Results: Feedback training leads to more spatially focused recruitment of areas relevant for learning and emotion. Effective connectivity analysis reveals that initial training is associated with an increase in network density; further training "prunes" presumably redundant connections and "strengthens" relevant connections.

Conclusions: The authors demonstrate the application of multivariate methods for assessing cerebral reorganization during the learning of volitional control of local brain activity. The findings provide insight into mechanisms of training-induced learning techniques for rehabilitation. The authors anticipate that future studies, specifically designed with this hypothesis in mind, may be able to construct a universal index of cerebral reorganization during skill learning based on multiple similar criteria across various skilled tasks. These techniques may be able to discern recovery from compensation, dose-response curves related to training, and ways to determine whether rehabilitation training is actively engaging necessary networks.
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http://dx.doi.org/10.1177/1545968310385128DOI Listing
January 2012

Real-time support vector classification and feedback of multiple emotional brain states.

Neuroimage 2011 May 6;56(2):753-65. Epub 2010 Aug 6.

Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany.

An important question that confronts current research in affective neuroscience as well as in the treatment of emotional disorders is whether it is possible to determine the emotional state of a person based on the measurement of brain activity alone. Here, we first show that an online support vector machine (SVM) can be built to recognize two discrete emotional states, such as happiness and disgust from fMRI signals, in healthy individuals instructed to recall emotionally salient episodes from their lives. We report the first application of real-time head motion correction, spatial smoothing and feature selection based on a new method called Effect mapping. The classifier also showed robust prediction rates in decoding three discrete emotional states (happiness, disgust and sadness) in an extended group of participants. Subjective reports ascertained that participants performed emotion imagery and that the online classifier decoded emotions and not arbitrary states of the brain. Offline whole brain classification as well as region-of-interest classification in 24 brain areas previously implicated in emotion processing revealed that the frontal cortex was critically involved in emotion induction by imagery. We also demonstrate an fMRI-BCI based on real-time classification of BOLD signals from multiple brain regions, for each repetition time (TR) of scanning, providing visual feedback of emotional states to the participant for potential applications in the clinical treatment of dysfunctional affect.
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http://dx.doi.org/10.1016/j.neuroimage.2010.08.007DOI Listing
May 2011

Effective functional mapping of fMRI data with support-vector machines.

Hum Brain Mapp 2010 Oct;31(10):1502-11

Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Gartenstr 29, 72074 Tübingen, Germany.

There is a growing interest in using support vector machines (SVMs) to classify and analyze fMRI signals, leading to a wide variety of applications ranging from brain state decoding to functional mapping of spatially and temporally distributed brain activations. Studies so far have generated functional maps using the vector of weight values generated by the SVM classification process, or alternatively by mapping the correlation coefficient between the fMRI signal at each voxel and the brain state determined by the SVM. However, these approaches are limited as they do not incorporate both the information involved in the SVM prediction of a brain state, namely, the BOLD activation at voxels and the degree of involvement of different voxels as indicated by their weight values. An important implication of the above point is that two different datasets of BOLD signals, presumably obtained from two different experiments, can potentially produce two identical hyperplanes irrespective of their differences in data distribution. Yet, the two sets of signal inputs could correspond to different functional maps. With this consideration, we propose a new method called Effect Mapping that is generated as a product of the weight vector and a newly computed vector of mutual information between BOLD activations at each voxel and the SVM output. By applying this method on neuroimaging data of overt motor execution in nine healthy volunteers, we demonstrate higher decoding accuracy indicating the greater efficacy of this method.
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http://dx.doi.org/10.1002/hbm.20955DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6871106PMC
October 2010

Synthesis and nonvolatile memory behavior of redox-active conjugated polymer-containing ferrocene.

J Am Chem Soc 2007 Aug 24;129(32):9842-3. Epub 2007 Jul 24.

Advanced Material Group, Electronic Chemical Materials R&D Center, Cheil Industries Inc., 332-2 Gogcheon-dong, Uiwang-si, Gyunggi-do 437-711, Korea.

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http://dx.doi.org/10.1021/ja0717459DOI Listing
August 2007