NeuroImage

Effects of 3.5–23.0 T static magnetic fields on mice: A safety study Publication date: 1 October 2019 Source: NeuroImage, Volume 199 Author(s): Xiaofei Tian, Dongmei Wang, Shuang Feng, Lei Zhang, Xinmiao Ji, Ze Wang, Qingyou Lu, Chuanying Xi, Li Pi, Xin Zhang Abstract People are exposed to various magnetic fields, including the high static/steady magnetic field (SMF) of MRI, which has been increased to 9.4 T in preclinical investigations. However, relevant safety studies about high SMF are deficient. Here we examined whether 3.5–23.0 T SMF exposure for 2 h has severe long-term effects on mice using 112 C57BL/6J mice. The food/water consumption, blood glucose levels, blood routine, blood biochemistry, as well as organ weight and HE stains were all examined. The food consumption and body weight were slightly decreased for 23.0 T-exposed mice (14.6%, P < 0.01, and 1.75–5.57%, P < 0.05, respectively), but not the other groups. While total bilirubin (TBIL), white blood cells, platelet and lymphocyte numbers were affected by some magnetic conditions, most of them were still within normal reference range. Although 13.5 T magnetic fields with the highest gradient (117.2 T/m) caused spleen weight increase, the blood count and biochemistry results were still within the control reference range. Moreover, the highest field 23.0 T with no gradient did not cause organ weight or blood biochemistry abnormality, which indicates that field gradient is a key parameter. Collectively, these data suggest 3.5–23.0 T static magnetic field exposure for 2 h do not have severe long-term effects on mice. Graphical abstract

Dissociating refreshing and elaboration and their impacts on memory Publication date: 1 October 2019 Source: NeuroImage, Volume 199 Author(s): Lea M. Bartsch, Vanessa M. Loaiza, Lutz Jäncke, Klaus Oberauer, Jarrod A. Lewis-Peacock Abstract Maintenance of information in working memory (WM) is assumed to rely on refreshing and elaboration, but clear mechanistic descriptions of these cognitive processes are lacking, and it is unclear whether they are simply two labels for the same process. This fMRI study investigated the extent to which refreshing, elaboration, and repeating of items in WM are distinct neural processes with dissociable behavioral outcomes in WM and long-term memory (LTM). Multivariate pattern analyses of fMRI data revealed differentiable neural signatures for these processes, which we also replicated in an independent sample of older adults. In some cases, the degree of neural separation within an individual predicted their memory performance. Elaboration improved LTM, but not WM, and this benefit increased as its neural signature became more distinct from repetition. Refreshing had no impact on LTM, but did improve WM, although the neural discrimination of this process was not predictive of the degree of improvement. These results demonstrate that refreshing and elaboration are separate processes that differently contribute to memory performance.

The influence of brain iron on myelin water imaging Publication date: 1 October 2019 Source: NeuroImage, Volume 199 Author(s): Christoph Birkl, Anna Maria Birkl-Toeglhofer, Verena Endmayr, Romana Höftberger, Gregor Kasprian, Claudia Krebs, Johannes Haybaeck, Alexander Rauscher Abstract With myelin playing a vital role in normal brain integrity and function and thus in various neurological disorders, myelin sensitive magnetic resonance imaging (MRI) techniques are of great importance. In particular, multi-exponential T2 relaxation was shown to be highly sensitive to myelin. The myelin water imaging (MWI) technique allows to separate the T2 decay into short components, specific to myelin water, and long components reflecting the intra- and extracellular water. The myelin water fraction (MWF) is the ratio of the short components to all components. In the brain's white matter (WM), myelin and iron are closely linked via the presence of iron in the myelin generating oligodendrocytes. Iron is known to decrease T2 relaxation times and may therefore mimic myelin. In this study, we investigated if variations in WM iron content can lead to apparent MWF changes. We performed MWI in post mortem human brain tissue prior and after chemical iron extraction. Histology for iron and myelin confirmed a decrease in iron content and no change in myelin content after iron extraction. In MRI, iron extraction lead to a decrease in MWF by 26%–28% in WM. Thus, a change in MWF does not necessarily reflect a change in myelin content. This observation has important implications for the interpretation of MWI findings in previously published studies and future research.

Retrieval orientation alters neural activity during autobiographical memory recollection Publication date: 1 October 2019 Source: NeuroImage, Volume 199 Author(s): Lauri Gurguryan, Signy Sheldon Abstract When an autobiographical memory is retrieved, the underlying memory representation is constructed by flexibly activating a broad neural network. As such, the content used to reconstruct a memory can bias activity within this neural network. Here, we tested the hypothesis that focusing on the conceptual and contextual aspects of a memory to construct a memory representation will recruit distinct neural subsystems. To test this hypothesis, we measured neural activity as participants retrieved memories under retrieval orientations that biased remembering towards these elements of a past autobiographical experience. In an MRI scanner, participants first retrieved autobiographical memories and then were re-oriented towards the conceptual or contextual elements of that memory. They then used this re-oriented content (conceptual or contextual elements) to access and elaborate upon a new autobiographical memory. Confirming our hypothesis, we found a neural dissociation between these retrieval orientation conditions that aligned with established models of memory. We also found evidence that this neural dissociation was most prominent when the re-oriented mnemonic content was used to access a new memory. Altogether, the reported results provide critical insight into how and when retrieval orientations alter neural support for autobiographical memory retrieval and inform on the neural organization of autobiographical knowledge.

Neural correlates of anticipatory cardiac deceleration and its association with the speed of perceptual decision-making, in young and older adults Publication date: 1 October 2019 Source: NeuroImage, Volume 199 Author(s): Maria J. Ribeiro, Miguel Castelo-Branco Abstract Warning stimuli in sensorimotor tasks induce a state of preparedness characterized by increased alertness, focused attention and immobility. This state of attentive anticipation is associated with heart rate deceleration. Ageing affects the amplitude of the anticipatory cardiac deceleration responses; yet, the impact of this physiological change on cognitive performance is still to be elucidated. In fact, how cardiac deceleration relates to brain function and cognitive performance in the context of perceptual decision-making and different levels of decision complexity remains unknown. Here, we aimed to investigate the relationship between cardiac deceleration, brain function, and performance in perceptual decision tasks and how these associate with age-related changes. We measured simultaneously the electrocardiogram, the pupilogram, and the electroencephalogram in 36 young and 39 older adults, while they were engaged in two auditory cued reaction time tasks: a detection task and a go/no-go task requiring inhibitory control. We observed robust cardiac deceleration responses that increased with increasing task complexity. Notably, stronger modulation of the cardiac response across tasks was associated with the ability to maintain response speed as decision complexity increased suggesting a link between cardiac deceleration and facilitation of perceptual decisions. Additionally, cardiac deceleration appears to have a cortical origin as it correlated with frontocentral event-related potentials. In contrast, beta oscillations at baseline and task-related beta suppression were not predictive of cardiac deceleration suggesting a dissociation between sensorimotor oscillatory activity and this cardiac response. Importantly, we found age-related changes in anticipatory cardiac deceleration associated with deficits in perceptual decision-making.

Pre-stimulus brain state predicts auditory pattern identification accuracy Publication date: 1 October 2019 Source: NeuroImage, Volume 199 Author(s): Natalie E. Hansen, Assaf Harel, Nandini Iyer, Brian D. Simpson, Matthew G. Wisniewski Abstract Recent studies show that pre-stimulus band-specific power and phase in the electroencephalogram (EEG) can predict accuracy on tasks involving the detection of near-threshold stimuli. However, results in the auditory modality have been mixed, and few works have examined pre-stimulus features when more complex decisions are made (e.g. identifying supra-threshold sounds). Further, most auditory studies have used background sounds known to induce oscillatory EEG states, leaving it unclear whether phase predicts accuracy without such background sounds. To address this gap in knowledge, the present study examined pre-stimulus EEG as it relates to accuracy in a tone pattern identification task. On each trial, participants heard a triad of 40-ms sinusoidal tones (separated by 40-ms intervals), one of which was at a different frequency than the other two. Participants' task was to indicate the tone pattern (low-low-high, low-high-low, etc.). No background sounds were employed. Using a phase opposition measure based on inter-trial phase consistencies, pre-stimulus 7–10 Hz phase was found to differ between correct and incorrect trials ∼200 to 100 ms prior to tone-pattern onset. After sorting trials into bins based on phase, accuracy was found to be lowest at around π−+ relative to individuals' most accurate phase bin. No significant effects were found for pre-stimulus power. In the context of the literature, findings suggest an important relationship between the complexity of task demands and pre-stimulus activity within the auditory domain. Results also raise interesting questions about the role of induced oscillatory states or rhythmic processing modes in obtaining pre-stimulus effects of phase in auditory tasks.

Optimization of graph construction can significantly increase the power of structural brain network studies Publication date: 1 October 2019 Source: NeuroImage, Volume 199 Author(s): Eirini Messaritaki, Stavros I. Dimitriadis, Derek K. Jones Abstract Structural brain networks derived from diffusion magnetic resonance imaging data have been used extensively to describe the human brain, and graph theory has allowed quantification of their network properties. Schemes used to construct the graphs that represent the structural brain networks differ in the metrics they use as edge weights and the algorithms they use to define the network topologies. In this work, twenty graph construction schemes were considered. The schemes use the number of streamlines, the fractional anisotropy, the mean diffusivity or other attributes of the tracts to define the edge weights, and either an absolute threshold or a data-driven algorithm to define the graph topology. The test-retest data of the Human Connectome Project were used to compare the reproducibility of the graphs and their various attributes (edges, topologies, graph theoretical metrics) derived through those schemes, for diffusion images acquired with three different diffusion weightings. The impact of the scheme on the statistical power of the study and on the number of participants required to detect a difference between populations or an effect of an intervention was also calculated. The reproducibility of the graphs and their attributes depended heavily on the graph construction scheme. Graph reproducibility was higher for schemes that used thresholding to define the graph topology, while data-driven schemes performed better at topology reproducibility (mean similarities of 0.962 and 0.984 respectively, for graphs derived from diffusion images with b=2000 s/mm2). Additionally, schemes that used thresholding resulted in better reproducibility for local graph theoretical metrics (intra-class correlation coefficients (ICC) of the order of 0.8), compared to data-driven schemes. Thresholded and data-driven schemes resulted in high (0.86 or higher) ICCs only for schemes that use exclusively the number of streamlines to construct the graphs. Crucially, the number of participants required to detect a difference between populations or an effect of an intervention could change by a factor of two or more depending on the scheme used, affecting the power of studies to reveal the effects of interest.

From intermodulation components to visual perception and cognition-a review Publication date: 1 October 2019 Source: NeuroImage, Volume 199 Author(s): Noam Gordon, Jakob Hohwy, Matthew James Davidson, Jeroen J.A. van Boxtel, Naotsugu Tsuchiya Abstract Perception results from complex interactions among sensory and cognitive processes across hierarchical levels in the brain. Intermodulation (IM) components, used in frequency tagging neuroimaging designs, have emerged as a promising direct measure of such neural interactions. IMs have initially been used in electroencephalography (EEG) to investigate low-level visual processing. In a more recent trend, IMs in EEG and other neuroimaging methods are being used to shed light on mechanisms of mid- and high-level perceptual processes, including the involvement of cognitive functions such as attention and expectation. Here, we provide an account of various mechanisms that may give rise to IMs in neuroimaging data, and what these IMs may look like. We discuss methodologies that can be implemented for different uses of IMs and we demonstrate how IMs can provide insights into the existence, the degree and the type of neural integration mechanisms at hand. We then review a range of recent studies exploiting IMs in visual perception research, placing an emphasis on high-level vision and the influence of awareness and cognition on visual processing. We conclude by suggesting future directions that can enhance the benefits of IM-methodology in perception research.

Optimization of preprocessing strategies in Positron Emission Tomography (PET) neuroimaging: A [11C]DASB PET study Publication date: 1 October 2019 Source: NeuroImage, Volume 199 Author(s): Martin Nørgaard, Melanie Ganz, Claus Svarer, Vibe G. Frokjaer, Douglas N. Greve, Stephen C. Strother, Gitte M. Knudsen Abstract Positron Emission Tomography (PET) is an important neuroimaging tool to quantify the distribution of specific molecules in the brain. The quantification is based on a series of individually designed data preprocessing steps (pipeline) and an optimal preprocessing strategy is per definition associated with less noise and improved statistical power, potentially allowing for more valid neurobiological interpretations. In spite of this, it is currently unclear how to design the best preprocessing pipeline and to what extent the choice of each preprocessing step in the pipeline minimizes subject-specific errors. To evaluate the impact of various preprocessing strategies, we systematically examined 384 different pipeline strategies in data from 30 healthy participants scanned twice with the serotonin transporter (5-HTT) radioligand [11C]DASB. Five commonly used preprocessing steps with two to four options were investigated: (1) motion correction (MC) (2) co-registration (3) delineation of volumes of interest (VOI's) (4) partial volume correction (PVC), and (5) kinetic modeling. To quantitatively compare and evaluate the impact of various preprocessing strategies, we used the performance metrics: test-retest bias, within- and between-subject variability, the intraclass-correlation coefficient, and global signal-to-noise ratio. We also performed a power analysis to estimate the required sample size to detect either a 5% or 10% difference in 5-HTT binding as a function of preprocessing pipeline. The results showed a complex downstream dependency between the various preprocessing steps on the performance metrics. The choice of MC had the most profound effect on 5-HTT binding, prior to the effects caused by PVC and kinetic modeling, and the effects differed across VOI's. Notably, we observed a negative bias in 5-HTT binding across test and retest in 98% of pipelines, ranging from 0 to 6% depending on the pipeline. Optimization of the performance metrics revealed a trade-off in within- and between-subject variability at the group-level with opposite effects (i.e. minimization of within-subject variability increased between-subject variability and vice versa). The sample size required to detect a given effect size was also compromised by the preprocessing strategy, resulting in up to 80% increases in sample size needed to detect a 5% difference in 5-HTT binding. This is the first study to systematically investigate and demonstrate the effect of choosing different preprocessing strategies on the outcome of dynamic PET studies. We provide a framework to show how optimal and maximally powered neuroimaging results can be obtained by choosing appropriate preprocessing strategies and we provide recommendations depending on the study design. In addition, the results contribute to a better understanding of methodological uncertainty and variability in preprocessing decisions for future group- and/or longitudinal PET studies.

Brain network reconfiguration for language and domain-general cognitive control in bilinguals Publication date: 1 October 2019 Source: NeuroImage, Volume 199 Author(s): Junjie Wu, Jing Yang, Mo Chen, Shuhua Li, Zhaoqi Zhang, Chunyan Kang, Guosheng Ding, Taomei Guo Abstract For bilinguals, language control is needed for selecting the target language during language production. Numerous studies have examined the neural correlates of language control and shown a close relationship between language control and domain-general cognitive control. However, it remains unknown how these brain regions coordinate with each other when bilinguals exert cognitive control over linguistic and nonlinguistic representations. We addressed this gap using an extended unified structural equation modeling (euSEM) approach. Sixty-five Chinese-English bilinguals performed language switching and nonverbal switching tasks during functional magnetic resonance imaging (fMRI) scanning. The results showed that language control was served by a cooperative brain network, including the frontal lobe, the parietal cortex, subcortical areas, and the cerebellum. More importantly, we found that language control recruited more subcortical areas and connections from frontal to subcortical areas compared with domain-general cognitive control, demonstrating a reconfigurable brain network. In addition, the reconfiguration efficiency of the brain network was mainly determined by general cognitive ability but was also mediated by second language (L2) proficiency. These findings provide the first data-driven connectivity model that specifies the brain network for language control in bilinguals and also shed light on the relationship between language control and domain-general cognitive control.

Alexandros Sfakianakis
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alsfakia@gmail.com