scholarly journals Some like it, some do not: behavioral responses and central processing of olfactory–trigeminal mixture perception

2020 ◽  
Author(s):  
Franziska S. Müschenich ◽  
Thorsten Sichtermann ◽  
Maria Elisa Di Francesco ◽  
Rea Rodriguez-Raecke ◽  
Lennart Heim ◽  
...  
Keyword(s):  
Mixture Component ◽  
Neural Activation ◽  
Imaging Data ◽  
Pain Matrix ◽  
Brain Images ◽  
Attentional Shift ◽  
Behavioral Ratings ◽  
Central Processing ◽  
Painful Sensation ◽  
Healthy Participants

AbstractExploring the potential of eucalyptol as a masking agent for aversive odors, we found that eucalyptol masks the olfactory but not the trigeminal sensation of ammonia in a previous study. Here, we further investigate the processing of a mixture consisting of eucalyptol and ammonia, two olfactory–trigeminal stimuli. We presented the two pure odors and a mixture thereof to 33 healthy participants. The nostrils were stimulated alternately (monorhinal application). We analyzed the behavioral ratings (intensity and pleasantness) and functional brain images. First, we replicated our previous finding that, within the mixture, the eucalyptol component suppressed the olfactory intensity of the ammonia component. Second, mixture pleasantness was rated differently by participants depending on which component dominated their mixture perception. Approximately half of the volunteers rated the eucalyptol component as more intense and evaluated the mixture as pleasant (pleasant group). The other half rated the ammonia component as more intense and evaluated the mixture as unpleasant (unpleasant group). Third, these individual differences were also found in functional imaging data. Contrasting the mixture either to eucalyptol or to both single odors, neural activation was found in the unpleasant group only. Activation in the anterior insula and SII was interpreted as evidence for an attentional shift towards the potentially threatening mixture component ammonia and for trigeminal enhancement. In addition to insula and SII, further regions of the pain matrix were involved when assessing all participant responses to the mixture. Both a painful sensation and an attentional shift towards the unpleasant mixture component complicates the development of an efficient mask because a pleasant perception is an important requirement for malodor coverage.

scholarly journals Methodology for tDCS integration with fMRI

2019 ◽  
Author(s):  
Zeinab Esmaeilpour ◽  
A. Duke Shereen ◽  
Peyman Ghobadi-Azbari ◽  
Abhishek Datta ◽  
Adam J. Woods ◽  
...  
Keyword(s):  
Behavioral Interventions ◽  
Computational Models ◽  
Brain Activity ◽  
State Level ◽  
Resting State Fmri ◽  
Underlying Mechanism ◽  
Cognitive State ◽  
Neural Activation ◽  
Imaging Data

AbstractIntegration of tDCS with fMRI holds promise for investigation the underlying mechanism of stimulation effect. There are 118 published tDCS studies (up to 1st Oct 2018) that used fMRI as a proxy measure of neural activation to answer mechanistic, predictive, and localization questions about how brain activity is modulated by tDCS. FMRI can potentially contribute as: a measure of cognitive state-level variance in baseline brain activation before tDCS; inform the design of stimulation montages that aim to target functional networks during specific tasks; and act as an outcome measure of functional response to tDCS. In this systematic review we explore methodological parameter space of tDCS integration with fMRI. Existing tDCS-fMRI literature shows little replication across these permutations; few studies used comparable study designs. Here, we use a case study with both task and resting state fMRI before and after tDCS in a cross-over design to discuss methodological confounds. We further outline how computational models of current flow should be combined with imaging data to understand sources of variability in responsiveness. Through the case study, we demonstrate how modeling and imaging methodology can be integrated for individualized analysis. Finally, we discuss the importance of conducting tDCS-fMRI with stimulation equipment certified as safe to use inside the MR scanner, and of correcting for image artifacts caused by tDCS. tDCS-fMRI can address important questions on the functional mechanisms of tDCS action (e.g. target engagement) and has the potential to support enhancement of behavioral interventions, provided studies are designed rationally.

A frameless stereotactic approach to neurosurgical planning based on retrospective patient-image registration

1993 ◽  
Vol 79 (2) ◽  
pp. 296-303 ◽  
Author(s):  
Kim K. Tan ◽  
Robert Grzeszczuk ◽  
David N. Levin ◽  
Charles A. Pelizzari ◽  
George T. Y. Chen ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Imaging Data ◽  
Mr Images ◽  
Cross Sectional ◽  
Brain Images ◽  
Content Type ◽  
Typical Error ◽  
Neurosurgical Planning ◽  
Computer Workstation ◽  
Stereotactic Device

✓ A frameless stereotactic device interfacing an electromagnetic three-dimensional (3-D) digitizer to a computer workstation is described. The patient-image coordinate transformation was found by retrospectively registering a digitizer-derived model of the patient's scalp with a magnetic resonance (MR) imaging-derived model of the same surface. This procedure was performed with routine imaging data, eliminating the need to obtain special-purpose MR images with fiducial markers in place. After patient-image fusion was achieved, a hand-held digitizing stylus was moved over the scalp and tracked in real time on cross-sectional and 3-D brain images on the computer screen. This device was used for presurgical localization of lesions in 10 patients with meningeal and superficial brain tumors. The results suggest that the system is accurate enough (typical error range 3 to 8 mm) to enable the surgeon to reduce the craniotomy to one-half the size advisable with conventional qualitative presurgical planning.

scholarly journals The Amsterdam Open MRI Collection, a set of multimodal MRI datasets for individual difference analyses

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Lukas Snoek ◽  
Maite M. van der Miesen ◽  
Tinka Beemsterboer ◽  
Andries van der Leij ◽  
Annemarie Eigenhuis ◽  
...  
Keyword(s):  
Cognitive Conflict ◽  
Large Set ◽  
Imaging Data ◽  
Open Mri ◽  
Bold Mri ◽  
Multimodal Mri ◽  
Brain Imaging Data ◽  
And Control ◽  
The Brain ◽  
Healthy Participants

AbstractWe present the Amsterdam Open MRI Collection (AOMIC): three datasets with multimodal (3 T) MRI data including structural (T1-weighted), diffusion-weighted, and (resting-state and task-based) functional BOLD MRI data, as well as detailed demographics and psychometric variables from a large set of healthy participants (N = 928, N = 226, and N = 216). Notably, task-based fMRI was collected during various robust paradigms (targeting naturalistic vision, emotion perception, working memory, face perception, cognitive conflict and control, and response inhibition) for which extensively annotated event-files are available. For each dataset and data modality, we provide the data in both raw and preprocessed form (both compliant with the Brain Imaging Data Structure), which were subjected to extensive (automated and manual) quality control. All data is publicly available from the OpenNeuro data sharing platform.

scholarly journals Quantitative Cellular-Resolution Map of the Oxytocin Receptor in Postnatally Developing Mouse Brains

2019 ◽  
Author(s):  
Kyra T. Newmaster ◽  
Zachary T. Nolan ◽  
Uree Chon ◽  
Daniel J. Vanselow ◽  
Abigael R. Weit ◽  
...  
Keyword(s):  
Oxytocin Receptor ◽  
Imaging Data ◽  
Brain Images ◽  
Fluorescent Reporter ◽  
Temporal Regulation ◽  
Cellular Resolution ◽  
Reporter Mice ◽  
Cell Densities ◽  
Subcortical Regions ◽  
Cortical Regions

AbstractOxytocin receptor (OTR) plays critical roles in social behavior development. Despite its significance, brain-wide quantitative understanding of OTR expression remains limited in postnatally developing brains. Here, we validated and utilized fluorescent reporter mice (OTRvenus/+) to examine OTR cells across postnatal periods. We developed postnatal 3D template brains to register whole brain images with cellular resolution to systematically quantify OTR cell densities. We found that cortical regions showed temporally and spatially heterogeneous patterns with transient postnatal OTR expression without cell death. Cortical OTR cells were largely not GABAergic neurons with the exception of cells in layer 6b. Subcortical regions showed similar temporal regulation except the hypothalamus. Moreover, our unbiased approach identified two hypothalamic nuclei with sexually dimorphic OTR expression. Lastly, we created a website to easily share our imaging data. In summary, we provide comprehensive quantitative data to understand postnatal OTR expression in the mouse brain.

scholarly journals Estimating the effect of a scanner upgrade on measures of grey matter structure for longitudinal designs

2020 ◽  
Author(s):  
Evelyn Medawar ◽  
Ronja Thieleking ◽  
Iryna Manuilova ◽  
Maria Paerisch ◽  
Arno Villringer ◽  
...  
Keyword(s):  
Grey Matter ◽  
Correction Method ◽  
Multiple Time ◽  
Imaging Data ◽  
Brain Images ◽  
The Difference ◽  
Longitudinal Imaging ◽  
Magnetic Resonance Imaging Mri ◽  
Multiple Time Points

1AbstractLongitudinal imaging studies are crucial for advancing the understanding of brain development over the lifespan. Thus, more and more studies acquire imaging data at multiple time points or with long follow-up intervals. In these studies changes to magnetic resonance imaging (MRI) scanners often become inevitable which may decrease the reliability of the MRI assessments and introduce biases.We therefore investigated the difference between MRI scanners with subsequent versions (3 Tesla Siemens Verio vs. Skyra fit) on the cortical and subcortical measures of grey matter in 116 healthy, young adults using the well-established longitudinal FreeSurfer stream for T1-weighted brain images. We found excellent between-scanner reliability for cortical and subcortical measures of grey matter structure (intra-class correlation coefficient > 0.8). Yet, paired t-tests revealed statistically significant differences in at least 75% of the regions, with percent differences up to 5%, depending on the outcome measure. Offline correction for gradient distortions only slightly reduced these biases. Further, T1-imaging based quality measures systematically differed between scanners.We conclude that scanner upgrades during a longitudinal study introduce bias in measures of cortical and subcortical grey matter structure. Therefore, before upgrading a MRI scanner during an ongoing study, researchers should prepare to implement an appropriate correction method for these effects.

scholarly journals The genetic architecture of human brainstem structures and their involvement in common brain disorders

2019 ◽  
Author(s):  
Torbjørn Elvsåshagen ◽  
Shahram Bahrami ◽  
Dennis van der Meer ◽  
Ingrid Agartz ◽  
Dag Alnæs ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Neurological Disorders ◽  
Genetic Architecture ◽  
Superior Cerebellar Peduncle ◽  
Brain Disorders ◽  
Imaging Data ◽  
Resonance Imaging ◽  
Genetic Overlap ◽  
Cerebellar Peduncle ◽  
Healthy Participants

ABSTRACTBrainstem regions support critical bodily functions, yet their genetic architectures and involvement in brain disorders remain understudied. Here, we examined volumes of brainstem structures using magnetic resonance imaging in 43,353 individuals. In 27,034 genotyped healthy participants, we identified 16 genetic loci associated with whole brainstem volume and 10, 23, 3, and 9 loci associated with volumes of the midbrain, pons, superior cerebellar peduncle, and medulla oblongata, respectively. These loci were mapped to 305 genes, including genes linked to brainstem development and common brain disorders. We detected genetic overlap between the brainstem volumes and eight psychiatric and neurological disorders. Using imaging data from 16,319 additional individuals, we observed differential volume alterations in schizophrenia, bipolar disorder, multiple sclerosis, mild cognitive impairment, dementia, and Parkinson’s disease. Together, our results provide new insights into the genetic underpinnings of brainstem structures and support their involvement in common brain disorders.

scholarly journals From BDNF to reading: Neural activation and phonological processing as multiple mediators

2020 ◽  
Author(s):  
Sara Mascheretti ◽  
Meaghan Perdue ◽  
Bei Feng ◽  
Chiara Andreola ◽  
Ginette Dionne ◽  
...  
Keyword(s):  
Phonological Processing ◽  
Neurodevelopmental Disorder ◽  
Brain Activation ◽  
Brain Regions ◽  
Brain Morphology ◽  
Neural Activation ◽  
Imaging Data ◽  
Multiple Mediation ◽  
Val66met Polymorphism ◽  
Intermediate Phenotypes

The BDNF gene is a prominent promoter of neuronal development, maturation and plasticity. Its Val66Met polymorphism affects brain morphology and function within several areas and is associated with several cognitive functions and neurodevelopmental disorder susceptibility. Recently, it has been associated with reading, reading-related traits and altered neural activation in reading–related brain regions. However, it remains unknown if the intermediate phenotypes (IPs, such as brain activation and phonological skills) mediate the pathway from gene to reading or reading disability. By conducting a serial multiple mediation model in a sample of 94 children (age 5-13), our findings revealed no direct effects of genotype on reading. Instead, we found that genotype is associated with brain activation in reading-related and more domain general regions which in turn is associated with phonological processing which is associated with reading. These findings suggest that the BDNF- Val66Met polymorphism is related to reading via phonological processing and functional activation. These results support brain imaging data and neurocognitive traits as viable IPs for complex behaviors.

The effects of sleep deprivation on vigilance and neural activation during the Sustained Attention to Response Task

2019 ◽  
Author(s):  
Johnny Soares
Keyword(s):  
Sleep Deprivation ◽  
Sustained Attention ◽  
Response Times ◽  
Neural Activation ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Normal Sleep ◽  
Response Task ◽  
Error Percentage ◽  
Healthy Participants

The effects of sleep deprivation on vigilance and neural activation during the Sustained Attention to Response TaskIntroduction: Sleep deprivation is common and can result in impaired vigilance with fatal consequences, but little is known about effects of sleep deprivation on neural activation. With functional magnetic resonance imaging (fMRI), neural activation associated with an attention-demanding task such as the Sustained Attention to Response Task (SART) can be visualized and analyzed. This is one of the first studies combining SART with fMRI to study total sleep deprivation. Aims: This study aimed to determine how sleep deprivation affects vigilance and neural activation during the SART. Primary outcomes are the number of errors committed during the SART and fMRI activity associated to the SART task. Material and Methods: This cross-over study compares sleep deprivation and full sleep. 9 healthy participants (6 males and 3 females) with normal sleep patterns were included. Participants were randomized to undergo both conditions in counterbalanced order and were planned for a total of three different MRI sessions and two SART evaluations. Results: No SART results were statistically significant, however there was a tendency of increased error percentage in the sleep deprived condition. There was no strong tendency of longer response times in sleep deprived condition. Clusters of neural activation were observed in areas associated with the executive network. However, none were statistically significant. Conclusions: This study suggests that SART performance regarding accuracy may be affected by sleep deprivation; however response times are not. No significant effect of sleep deprivation on neural activation was found, however indications of areas related to vigilance were located in expected areas.

scholarly journals Hyperactive sensorimotor cortex during voice perception in spasmodic dysphonia

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Yuji Kanazawa ◽  
Yo Kishimoto ◽  
Ichiro Tateya ◽  
Toru Ishii ◽  
Tetsuji Sanuki ◽  
...  
Keyword(s):  
Sensorimotor Cortex ◽  
Judgment Task ◽  
Neural Systems ◽  
Spasmodic Dysphonia ◽  
Neural Activation ◽  
Voice Perception ◽  
Linear Discriminant ◽  
Voice Production ◽  
Sound Discrimination ◽  
Healthy Participants

Abstract Spasmodic dysphonia (SD) is characterized by an involuntary laryngeal muscle spasm during vocalization. Previous studies measured brain activation during voice production and suggested that SD arises from abnormal sensorimotor integration involving the sensorimotor cortex. However, it remains unclear whether this abnormal sensorimotor activation merely reflects neural activation produced by abnormal vocalization. To identify the specific neural correlates of SD, we used a sound discrimination task without overt vocalization to compare neural activation between 11 patients with SD and healthy participants. Participants underwent functional MRI during a two-alternative judgment task for auditory stimuli, which could be modal or falsetto voice. Since vocalization in falsetto is intact in SD, we predicted that neural activation during speech perception would differ between the two groups only for modal voice and not for falsetto voice. Group-by-stimulus interaction was observed in the left sensorimotor cortex and thalamus, suggesting that voice perception activates different neural systems between the two groups. Moreover, the sensorimotor signals positively correlated with disease severity of SD, and classified the two groups with 73% accuracy in linear discriminant analysis. Thus, the sensorimotor cortex and thalamus play a central role in SD pathophysiology and sensorimotor signals can be a new biomarker for SD diagnosis.

Neural Representations of Abstract Concepts: Identifying Underlying Neurosemantic Dimensions

2019 ◽  
Vol 30 (4) ◽  
pp. 2157-2166
Author(s):  
Robert Vargas ◽  
Marcel Adam Just
Keyword(s):  
Imaging Data ◽  
Abstract Concepts ◽  
Neural Basis ◽  
Representation Dimension ◽  
Behavioral Ratings ◽  
Verbal Representation ◽  
Neural Representations ◽  
The Individual ◽  
Multivariate Pattern ◽  
Neural Signatures

Abstract The abstractness of concepts is sometimes defined indirectly as lacking concreteness, this view provides little insight into their cognitive or neural basis. Multivariate pattern analytic techniques applied to functional magnetic resonance imaging data were used to characterize the neural representations of 28 individual abstract concepts. A classifier trained on the concepts’ neural signatures reliably decoded their neural representations in an independent subset of data for each participant. There was considerable commonality of the neural representations across participants as indicated by the accurate classification of each participant’s concepts based on the neural signatures obtained in other participants. Group-level factor analysis revealed 3 semantic dimensions underlying the 28 concepts, suggesting a brain-based ontology for this set of abstract concepts. The 3 dimensions corresponded to 1) the degree a concept was Verbally Represented; 2) whether a concept was External (or Internal) to the individual, and 3) whether the concept contained Social Content. Further exploration of the Verbal Representation dimension suggests that the degree a concept is verbally represented can be construed as a point on a continuum between language faculties and perceptual faculties. A predictive model, based on independent behavioral ratings of the 28 concepts along the 3 factor dimensions, provided converging evidence for the interpretations.

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