43 research outputs found

    Effects of Physical Exercise on Working Memory and Attention-Related Neural Oscillations

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    Cognitive functions, such as working memory (WM) and attention, have been shown to benefit from physical exercise. Quantifying frequency-band-specific neural oscillatory patterns during the use of such cognitive functions can provide insight into exercise-induced benefits in the brain. Specifically, we investigated whether a 4-month physical exercise training influenced theta and alpha power measured in visual WM and attention tasks. The delayed match-to-sample (DMS) task required mnemonic discrimination of similar visual stimuli, akin to pattern separation, while the visual-attention search (VAS) task required detecting the presence of a specific object (i.e., target) in an image. Behavioral and electroencephalographic data were acquired during a DMS visual WM task and VAS task both before and after the intervention. Forty-three sedentary young adults (19–34 years) were pseudorandomly assigned to a training group (indoor treadmill, n = 20) or to a control group (n = 23). Compared to the preintervention baseline, the exercise group showed increased frontal alpha power (9–12 Hz) during the VAS task after the intervention. In addition, alpha power changes correlated positively with fitness changes. Behaviorally, there were no exercise-related effects on reaction times or accuracy in either task. Our findings substantiate that aerobic training of sedentary young adults may influence neural dynamics underlying visual attention rather than visual WM and mnemonic discrimination

    Stimulus Novelty Energizes Actions in the Absence of Explicit Reward

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    Novelty seeking has been tied to impulsive choice and biased value based choice. It has been postulated that novel stimuli should trigger more vigorous approach and exploration. However, it is unclear whether stimulus novelty can enhance simple motor actions in the absence of explicit reward, a necessary condition for energizing approach and exploration in an entirely unfamiliar situation. In this study human subjects were cued to omit or perform actions in form of button presses by novel or familiar images. We found that subjects’ motor actions were faster when cued by a novel compared to a familiar image. This facilitation by novelty was strongest when the delay between cue and action was short, consistent with a link between novelty and impulsive choices. The facilitation of reaction times by novelty was correlated across subjects with trait novelty seeking as measured in the Tridimensional Personality Questionnaire. However, this li between high novelty-seeking and action facilitation was driven by trials with a long delay between cue and action. This prolonged time window of energization following novelty could hint at a mechanistic underpinning of enhanced vigour for approach and exploration frequently postulated for novelty seeking humans. In conclusion, we show that stimulus novelty enhances the speed of a cued motor action. We suggest this is likely to reflect an adaptation to changing environments but may also provide a source of maladaptive choice and impulsive behaviour

    Fully automated deep learning-based localization and segmentation of the locus coeruleus in aging and Parkinson's disease using neuromelanin-sensitive MRI

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    Purpose: Development and performance measurement of a fully automated pipeline that localizes and segments the locus coeruleus in so-called neuromelanin-sensitive magnetic resonance imaging data for the derivation of quantitative biomarkers of neurodegenerative diseases such as Alzheimer’s disease and Parkinson’s disease. Methods: We propose a pipeline composed of several 3D-Unet-based convolutional neural networks for iterative multi-scale localization and multi-rater segmentation and non-deep learning-based components for automated biomarker extraction. We trained on the healthy aging cohort and did not carry out any adaption or fine-tuning prior to the application to Parkinson’s disease subjects. Results: The localization and segmentation pipeline demonstrated sufficient performance as measured by Euclidean distance (on average around 1.3mm on healthy aging subjects and 2.2mm in Parkinson’s disease subjects) and Dice similarity coefficient (overall around 71% on healthy aging subjects and 60% for subjects with Parkinson’s disease) as well as promising agreement with respect to contrast ratios in terms of intraclass correlation coefficient of ≥0.80 for healthy aging subjects compared to a manual segmentation procedure. Lower values (≥0.48) for Parkinson’s disease subjects indicate the need for further investigation and tests before the application to clinical samples. Conclusion: These promising results suggest the usability of the proposed algorithm for data of healthy aging subjects and pave the way for further investigations using this approach on different clinical datasets to validate its practical usability more conclusively

    Longitudinal Reproducibility of Neurite Orientation Dispersion and Density Imaging (NODDI) Derived Metrics in the White Matter

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    Diffusion-weighted magnetic resonance imaging (DWI) is undergoing constant evolution with the ambitious goal of developing in-vivo histology of the brain. A recent methodological advancement is Neurite Orientation Dispersion and Density Imaging (NODDI), a histologically validated multi-compartment model to yield microstructural features of brain tissue such as geometric complexity and neurite packing density, which are especially useful in imaging the white matter. Since NODDI is increasingly popular in clinical research and fields such as developmental neuroscience and neuroplasticity, it is of vast importance to characterize its reproducibility (or reliability). We acquired multi-shell DWI data in 29 healthy young subjects twice over a rescan interval of 4 weeks to assess the within-subject coefficient of variation (CVWS), between-subject coefficient of variation (CVBS) and the intraclass correlation coefficient (ICC), respectively. Using these metrics, we compared regional and voxel-by-voxel reproducibility of the most common image analysis approaches (tract-based spatial statistics [TBSS], voxel-based analysis with different extents of smoothing [“VBM-style”], ROI-based analysis). We observed high test–retest reproducibility for the orientation dispersion index (ODI) and slightly worse results for the neurite density index (NDI). Our findings also suggest that the choice of analysis approach might have significant consequences for the results of a study. Collectively, the voxel-based approach with Gaussian smoothing kernels of ≥4 mm FWHM and ROI-averaging yielded the highest reproducibility across NDI and ODI maps (CVWS mostly ≤3%, ICC mostly ≥0.8), respectively, whilst smaller kernels and TBSS performed consistently worse. Furthermore, we demonstrate that image quality (signal-to-noise ratio [SNR]) is an important determinant of NODDI metric reproducibility. We discuss the implications of these results for longitudinal and cross-sectional research designs commonly employed in the neuroimaging field

    Big-Loop Recurrence within the Hippocampal System Supports Integration of Information across Episodes

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    Recent evidence challenges the widely held view that the hippocampus is specialized for episodic memory, by demonstrating that it also underpins the integration of information across experiences. Contemporary computational theories propose that these two contrasting functions can be accomplished by big-loop recurrence, whereby the output of the system is recirculated back into the hippocampus. We use ultra-high-resolution fMRI to provide support for this hypothesis, by showing that retrieved information is presented as a new input on the superficial entorhinal cortex—driven by functional connectivity between the deep and superficial entorhinal layers. Further, the magnitude of this laminar connectivity correlated with inferential performance, demonstrating its importance for behavior. Our findings offer a novel perspective on information processing within the hippocampus and support a unifying framework in which the hippocampus captures higher-order structure across experiences, by creating a dynamic memory space from separate episodic codes for individual experiences

    Perceived and mentally rotated contents are differentially represented in cortical depth of V1

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    Primary visual cortex (V1) in humans is known to represent both veridically perceived external input and internally-generated contents underlying imagery and mental rotation. However, it is unknown how the brain keeps these contents separate thus avoiding a mixture of the perceived and the imagined which could lead to potentially detrimental consequences. Inspired by neuroanatomical studies showing that feedforward and feedback connections in V1 terminate in different cortical layers, we hypothesized that this anatomical compartmentalization underlies functional segregation of external and internally-generated visual contents, respectively. We used high-resolution layer-specific fMRI to test this hypothesis in a mental rotation task. We found that rotated contents were predominant at outer cortical depth bins (i.e. superficial and deep). At the same time perceived contents were represented stronger at the middle cortical bin. These results identify how through cortical depth compartmentalization V1 functionally segregates rather than confuses external from internally-generated visual contents. These results indicate that feedforward and feedback manifest in distinct subdivisions of the early visual cortex, thereby reflecting a general strategy for implementing multiple cognitive functions within a single brain region

    The Role of the Striatum in Learning to Orthogonalize CD Action and Valence: A Combined PET and 7 T MRI Aging Study

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    Pavlovian biases influence instrumental learning by coupling reward seeking with action invigoration and punishment avoidance with action suppression. Using a probabilistic go/no-go task designed to orthogonalize action (go/no-go) and valence (reward/punishment), recent studies have shown that the interaction between the two is dependent on the striatum and its key neuromodulator dopamine. Using this task, we sought to identify how structural and neuromodulatory age-related differences in the striatum may influence Pavlovian biases and instrumental learning in 25 young and 31 older adults. Computational modeling revealed a significant age-related reduction in reward and punishment sensitivity and marked (albeit not significant) reduction in learning rate and lapse rate (irreducible noise). Voxel-based morphometry analysis using 7 Tesla MRI images showed that individual differences in learning rate in older adults were related to the volume of the caudate nucleus. In contrast, dopamine synthesis capacity in the dorsal striatum, assessed using [18F]-DOPA positron emission tomography in 22 of these older adults, was not associated with learning performance and did not moderate the relationship between caudate volume and learning rate. This multiparametric approach suggests that age-related differences in striatal volume may influence learning proficiency in old age

    Alzheimer's pathology targets distinct memory networks in the ageing brain

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    Alzheimer’s disease researchers have been intrigued by the selective regional vulnerability of the brain to amyloid-β plaques and tau neurofibrillary tangles. Post-mortem studies indicate that in ageing and Alzheimer’s disease tau tangles deposit early in the transentorhinal cortex, a region located in the anterior-temporal lobe that is critical for object memory. In contrast, amyloid-β pathology seems to target a posterior-medial network that subserves spatial memory. In the current study, we tested whether anterior-temporal and posterior-medial brain regions are selectively vulnerable to tau and amyloid-β deposition in the progression from ageing to Alzheimer’s disease and whether this is reflected in domain-specific behavioural deficits and neural dysfunction. 11C-PiB PET and 18F-flortaucipir uptake was quantified in a sample of 131 cognitively normal adults (age: 20–93 years; 47 amyloid-β-positive) and 20 amyloid-β-positive patients with mild cognitive impairment or Alzheimer’s disease dementia (65–95 years). Tau burden was relatively higher in anterior-temporal regions in normal ageing and this difference was further pronounced in the presence of amyloid-β and cognitive impairment, indicating exacerbation of ageing-related processes in Alzheimer’s disease. In contrast, amyloid-β deposition dominated in posterior-medial regions. A subsample of 50 cognitively normal older (26 amyloid-β-positive) and 25 young adults performed an object and scene memory task while functional MRI data were acquired. Group comparisons showed that tau-positive (n = 18) compared to tau-negative (n = 32) older adults showed lower mnemonic discrimination of object relative to scene images [t(48) = −3.2, P = 0.002]. In a multiple regression model including regional measures of both pathologies, higher anterior-temporal flortaucipir (tau) was related to relatively worse object performance (P = 0.010, r = −0.376), whereas higher posterior-medial PiB (amyloid-β) was related to worse scene performance (P = 0.037, r = 0.309). The functional MRI data revealed that tau burden (but not amyloid-β) was associated with increased task activation in both systems and a loss of functional specificity, or dedifferentiation, in posterior-medial regions. The loss of functional specificity was related to worse memory. Our study shows a regional dissociation of Alzheimer’s disease pathologies to distinct memory networks. While our data are cross-sectional, they indicate that with ageing, tau deposits mainly in the anterior-temporal system, which results in deficits in mnemonic object discrimination. As Alzheimer’s disease develops, amyloid-β deposits preferentially in posterior-medial regions additionally compromising scene discrimination and anterior-temporal tau deposition worsens further. Finally, our findings propose that the progression of tau pathology is linked to aberrant activation and dedifferentiation of specialized memory networks that is detrimental to memory function

    A protocol for manual segmentation of medial temporal lobe subregions in 7 Tesla MRI

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    Recent advances in MRI and increasing knowledge on the characterization and anatomical variability of medial temporal lobe (MTL) anatomy have paved the way for more specific subdivisions of the MTL in humans. In addition, recent studies suggest that early changes in many neurodegenerative and neuropsychiatric diseases are better detected in smaller subregions of the MTL rather than with whole structure analyses. Here, we developed a new protocol using 7 Tesla (T) MRI incorporating novel anatomical findings for the manual segmentation of entorhinal cortex (ErC), perirhinal cortex (PrC; divided into area 35 and 36), parahippocampal cortex (PhC), and hippocampus; which includes the subfields subiculum (Sub), CA1, CA2, as well as CA3 and dentate gyrus (DG) which are separated by the endfolial pathway covering most of the long axis of the hippocampus. We provide detailed instructions alongside slice-by-slice segmentations to ease learning for the untrained but also more experienced raters. Twenty-two subjects were scanned (19–32 yrs, mean age = 26 years, 12 females) with a turbo spin echo (TSE) T2-weighted MRI sequence with high-resolution oblique coronal slices oriented orthogonal to the long axis of the hippocampus (in-plane resolution 0.44 × 0.44 mm2) and 1.0 mm slice thickness. The scans were manually delineated by two experienced raters, to assess intra- and inter-rater reliability. The Dice Similarity Index (DSI) was above 0.78 for all regions and the Intraclass Correlation Coefficients (ICC) were between 0.76 to 0.99 both for intra- and inter-rater reliability. In conclusion, this study presents a fine-grained and comprehensive segmentation protocol for MTL structures at 7 T MRI that closely follows recent knowledge from anatomical studies. More specific subdivisions (e.g. area 35 and 36 in PrC, and the separation of DG and CA3) may pave the way for more precise delineations thereby enabling the detection of early volumetric changes in dementia and neuropsychiatric diseases

    Today’s older adults are cognitively fitter than older adults were 20 years ago, but when and how they decline is no different than in the past

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    History-graded increases in older adults' levels of cognitive performance are well documented, but little is known about historical shifts in within-person change: cognitive decline and onset of decline. We combined harmonized perceptual-motor speed data from independent samples recruited in 1990 and 2010 to obtain 2,008 age-matched longitudinal observations (M = 78 years, 50% women) from 228 participants in the Berlin Aging Study (BASE) and 583 participants in the Berlin Aging Study II (BASE-II). We used nonlinear growth models that orthogonalized within- and between-person age effects and controlled for retest effects. At age 78, the later-born BASE-II cohort substantially outperformed the earlier-born BASE cohort (d = 1.20; 25 years of age difference). Age trajectories, however, were parallel, and there was no evidence of cohort differences in the amount or rate of decline and the onset of decline. Cognitive functioning has shifted to higher levels, but cognitive decline in old age appears to proceed similarly as it did two decades ago
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