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This study explores the neurofunctional correlates of the recognition of famous faces in patients with amnestic mild cognitive impairment (aMCI) and healthy controls depending on the genetic risk factor, Apolipoprotein E (ApoE) ε4. An event-related functional magnetic resonance imaging experiment was conducted while participants discriminated between famous and nonfamous faces. We compared the results of 32 healthy controls [17 ApoE ε4 carriers (E4+); 15 noncarriers (E4-)] with those of 30 patients with aMCI (16 E4+; 14 E4-). Despite comparable task performance, patients with aMCI, E4+ showed significantly less activation in a large cortical network including the left parahippocampal gyrus than patients with aMCI E4-. Furthermore, in the aMCI group, we found significantly reduced activation in the left parahippocampal gyrus and posterior cingulate cortex compared with the control group. Our results show that critical regions of the brain show functional decline associated with major risk factors, such as ApoE ε4 allele and neuropsychological signs of aMCI for the development of Alzheimer disease. Importantly, the ApoE genotype seems to influence cortical activation in patients with aMCI and to a lesser degree in healthy controls as well, who are without any cognitive symptoms. [ABSTRACT FROM AUTHOR]

The pervasive use of information technologies (IT) has tremendously benefited our daily lives. However, unpredicted technical breakdowns and errors can lead to the experience of stress, which has been termed technostress. It remains poorly understood how people dynamically respond to unpredicted system runtime errors occurring while interacting with the IT systems on a behavioral and neuronal level. To elucidate the mechanisms underlying such processes, we conducted a functional magnetic resonance imaging (fMRI) study in which 15 young adults solved arithmetic problems of three difficulty levels (easy, medium and hard) while two types of system runtime errors (problem errors and feedback errors) occurred in an unexpected manner. The problem error condition consisted of apparently defective displays of the arithmetic problem and the feedback error condition involved erroneous feedback. We found that the problem errors positively influenced participants' problem-solving performance at the high difficulty level (i.e., hard tasks) at the initial stage of the session, while feedback errors disturbed their performance. These dynamic behavioral changes are mainly associated with brain activation changes in the posterior cingulate and the default mode network, including the posterior cingulate cortex, the mPFC, the retrosplenial cortex and the parahippocampal gyrus. Our study illustrates the regulatory role of the posterior cingulate in coping with unpredicted errors as well as with dynamic changes in the environment., (© 2024. The Author(s).)

This study aimed to investigate the impact of eccentric-vision training on population receptive field (pRF) estimates to provide insights into brain plasticity processes driven by practice. Fifteen participants underwent functional magnetic resonance imaging (fMRI) measurements before and after behavioral training on a visual crowding task, where the relative orientation of the opening (gap position: up/down, left/right) in a Landolt C optotype had to be discriminated in the presence of flanking ring stimuli. Drifting checkerboard bar stimuli were used for pRF size estimation in multiple regions of interest (ROIs): dorsal-V1 (dV1), dorsal-V2 (dV2), ventral-V1 (vV1), and ventral-V2 (vV2), including the visual cortex region corresponding to the trained retinal location. pRF estimates in V1 and V2 were obtained along eccentricities from 0.5° to 9°. Statistical analyses revealed a significant decrease of the crowding anisotropy index (p = 0.009) after training, indicating improvement on crowding task performance following training. Notably, pRF sizes at and near the trained location decreased significantly (p = 0.005). Dorsal and ventral V2 exhibited significant pRF size reductions, especially at eccentricities where the training stimuli were presented (p < 0.001). In contrast, no significant changes in pRF estimates were found in either vV1 (p = 0.181) or dV1 (p = 0.055) voxels. These findings suggest that practice on a crowding task can lead to a reduction of pRF sizes in trained visual cortex, particularly in V2, highlighting the plasticity and adaptability of the adult visual system induced by prolonged training.

In this study, an automated 2D machine learning approach for fast and precise segmentation of MS lesions from multi-modal magnetic resonance images (mmMRI) is presented. The method is based on an U-Net like convolutional neural network (CNN) for automated 2D slice-based-segmentation of brain MRI volumes. The individual modalities are encoded in separate downsampling branches without weight sharing, to leverage the specific features. Skip connections input feature maps to multi-scale feature fusion (MSFF) blocks at every decoder stage of the network. Those are followed by multi-scale feature upsampling (MSFU) blocks which use the information about lesion shape and location. The CNN is evaluated on two publicly available datasets: The ISBI 2015 longitudinal MS lesion segmentation challenge dataset containing 19 subjects and the MICCAI 2016 MSSEG challenge dataset containing 15 subjects from various scanners. The proposed multi-input 2D architecture is among the top performing approaches in the ISBI challenge, to which open-access papers are available, is able to outperform state-of-the-art 3D approaches without additional post-processing, can be adapted to other scanners quickly, is robust against scanner variability and can be deployed for inference even on a standard laptop without a dedicated GPU., (© 2023. The Author(s).)

We present a protocol to conduct functional magnetic resonance spectroscopy (fMRS) in human participants before, during, and after training on a visual task. We describe steps for participant setup, volume-of-interest placement, fMRS measurement, and post-scan tests. We discuss the design, analysis, and interpretation of fMRS experiments. This protocol can be adapted to investigate the dynamics of chief excitatory and inhibitory neurotransmitters (glutamate and γ-aminobutyric acid, GABA, respectively) while participants perform or learn perceptual, motor, or cognitive tasks. For complete details on the use and execution of this protocol, please refer to Frank et al. (2022). 1 ., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

The perception of coherent form configurations in natural scenes relies on the activity of early visual areas that respond to local orientation cues. Subsequently, high-level visual areas pool these local signals to construct a global representation of the initial visual input. However, it is still debated whether neurons in the early visual cortex respond also to global form features. Glass patterns (GPs) are visual stimuli employed to investigate local and global form processing and consist of randomly distributed dots pairs called dipoles arranged to form specific global configurations. In the current study, we used GPs and functional magnetic resonance imaging (fMRI) adaptation to reveal the visual areas that subserve the processing of oriented GPs. Specifically, we adapted participants to vertically oriented GP, then we presented test GPs having either the same or different orientations with respect to the adapting GP. We hypothesized that if local form features are processed exclusively by early visual areas and global form by higher-order visual areas, then the effect of visual adaptation should be more pronounced in higher tier visual areas as it requires global processing of the pattern. Contrary to this expectation, our results revealed that adaptation to GPs is robust in early visual areas (V1, V2, and V3), but not in higher tier visual areas (V3AB and V4v), suggesting that form cues in oriented GPs are primarily derived from local-processing mechanisms that originate in V1. Finally, adaptation to vertically oriented GPs causes a modification in the BOLD response within early visual areas, regardless of the relative orientations of the adapting and test stimuli, indicating a lack of orientation selectivity., (© 2023. The Author(s).)

The interpretation of fMRI data in glioblastoma (GB) is challenging as these tumors exhibit specific hemodynamic processes which, together with malignancy, tumor volume and proximity to eloquent cortex areas, may lead to misinterpretations of fMRI signals. The aim of this study was to investigate if different radiologically defined GB tumor growth patterns may also influence the fMRI signal, activation pattern and functional connectivity differently. Sixty-four patients with left-hemispheric glioblastoma were included and stratified according to their radiologically defined tumor growth pattern into groups with a uniform (U-TGP) or diffuse tumor growth pattern (D-TGP). Task-based fMRI data were analyzed using SPM12 with the marsbar, LI and CONN toolboxes. The percent signal change and the laterality index were analyzed, as well as functional connectivity between 23 selected ROIs. Comparisons of both patient groups showed only minor non-significant differences, indicating that the tumor growth pattern is not a relevant influencing factor for fMRI signal. In addition to these results, signal reductions were found in areas that were not affected by the tumor underlining that a GB is not a localized but rather a systemic disease affecting the entire brain.

Self-motion perception involves an interaction between vestibular and visual brain regions. In the lateral brain, it includes the parietoinsular vestibular cortex and the posterior insular cortex. In the medial cortex, the cingulate sulcus visual (CSv) area is known to process visual-vestibular cues. Here, we show that the vestibular-visual network of the medial cortex extends beyond area CSv. We examined brain activations of 36 healthy right-handed participants by functional magnetic resonance imaging (fMRI) during stimulation with caloric vestibular, thermal, or visual motion cues. Consistent with previous research, we found that area CSv responded to both vestibular and visual cues but not to thermal cues. Moreover, the V6 complex and the precuneus motion (PcM) area responded primarily to (laminar-translational) visual motion cues. However, we also observed a region inferior to CSv within the pericallosal sulcus (vicinity of anterior retrosplenial) that primarily responded to vestibular cues. This vestibular pericallosal sulcus (vPCS) region did not respond to either visual or thermal cues. It was also distinct from a more posterior motion-sensitive region in the retrosplenial complex (mRSC) that responded to (radial) visual motion but not to vestibular and thermal cues. Together, our results suggest that the vestibular-visual network in the medial cortex not only includes areas CSv, PcM, and the V6 complex but also two additional brain regions adjacent to the callosum. These two brain regions exhibit similarities in terms of their locations and responses to vestibular and visual cues with self-motion-related brain regions recently described in nonhuman primates. NEW & NOTEWORTHY Self-motion perception involves several vestibular and visual cortical regions. Within the medial cortex, the cingulate sulcus visual (CSv) area, the precuneus motion (PcM) area, and the V6 complex respond selectively to self-motion cues. Here, we show that vestibular information is also processed in the pericallosal sulcus (vPCS), whereas (radial) visual motion information is associated with activation in the retrosplenial cortex (mRSC).

It is generally thought that children learn more efficiently than adults. One way to accomplish this is to have learning rapidly stabilized such that it is not interfered with by subsequent learning. Although γ-aminobutyric acid (GABA) plays an important role in stabilization, it has been reported that GABAergic inhibitory processing is not fully matured yet in children compared with adults. Does this finding indicate that more efficient learning in children is not due to more rapid stabilization? Here, we measured the concentration of GABA in early visual cortical areas in a time-resolved fashion before, during, and after visual perceptual learning (VPL) within subjects using functional MRS (fMRS) and then compared the concentrations between children (8 to 11 years old) and adults (18 to 35 years old). We found that children exhibited a rapid boost of GABA during visual training that persisted after training ended, whereas the concentration of GABA in adults remained unchanged. Moreover, behavioral experiments showed that children exhibited rapid development of resilience to retrograde interference, which indicates that children stabilize VPL much faster than adults. These results together suggest that inhibitory processing in children's brains is more dynamic and adapts more quickly to stabilize learning than in adults, making learning more efficient in children., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2022 Elsevier Inc. All rights reserved.)

We investigated lateral modulation effects with functional magnetic resonance imaging. We presented radial sinusoidal gratings in random sequence: a scotoma grating with two arc-shaped blank regions (scotomata) in the periphery, one in the left and one in the right visual field, a center grating containing pattern only in the scotoma regions, and a full-field grating where the pattern occupied the whole screen. On each trial, one of the three gratings flickered in counterphase for 10 s, followed by a blank period. Observers were instructed to perform a fixation task and report whether filling-in was experienced during the scotoma condition. The results showed that the blood-oxygen-level-dependent signal was reduced in areas corresponding to the scotoma regions in the full-field compared to the center condition in V1 to V3 areas, indicating a lateral inhibition effect when the surround was added to the center pattern. The univariate analysis results showed no difference between the filling-in and no-filling-in trials. However, multivariate pattern analysis results showed that classifiers trained on activation pattern in V1 to V3 could differentiate between filling-in and no-filling-in trials, suggesting that the neural activation pattern in visual cortex correlated with the subjective percept., (© 2022. The Author(s).)

Differences in the ability of students to judge images can be assessed by analyzing the individual preference order (ranking) of images. To gain insights into potential heterogeneity in judgement of visual abstraction among students, we combine Bradley-Terry preference modeling and model-based recursive partitioning. In an experiment a sample of 1,020 high-school students ranked five sets of images, three of which with respect to their level of visual abstraction. Additionally, 24 art experts and 25 novices were given the same task, while their eye movements were recorded. Results show that time spent on the task, the students' age, and self-reported interest in visual puzzles had significant influence on rankings. Fixation time of experts and novices revealed that both groups paid more attention to ambiguous images. The presented approach makes the underlying latent scale of visual judgments quantifiable., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Tallon, Greenlee, Wagner, Rakoczy, Wiedermann and Frick.)

A pioneering study by Volkmann (1858) revealed that training on a tactile discrimination task improved task performance, indicative of tactile learning, and that such tactile learning transferred from trained to untrained body parts. However, the neural mechanisms underlying tactile learning and transfer of tactile learning have remained unclear. We trained groups of human subjects (female and male) in daily sessions on a tactile discrimination task either by stimulating the palm of the right hand or the sole of the right foot. Task performance before training was similar between the palm and sole. Posttraining transfer of tactile learning was greater from the trained right sole to the untrained right palm than from the trained right palm to the untrained right sole. Functional magnetic resonance imaging (fMRI) and multivariate pattern classification analysis revealed that the somatotopic representation of the right palm in contralateral primary somatosensory cortex (SI) was coactivated during tactile stimulation of the right sole. More pronounced coactivation in the cortical representation of the right palm was associated with lower tactile performance for tactile stimulation of the right sole and more pronounced subsequent transfer of tactile learning from the trained right sole to the untrained right palm. In contrast, coactivation of the cortical sole representation during tactile stimulation of the palm was less pronounced and no association with tactile performance and subsequent transfer of tactile learning was found. These results indicate that tactile learning may transfer to untrained body parts that are coactivated to support tactile learning with the trained body part. SIGNIFICANCE STATEMENT Perceptual skills such as the discrimination of tactile cues can improve by means of training, indicative of perceptual learning and sensory plasticity. However, it has remained unclear whether and if so, how such perceptual learning can occur if the training task is very difficult. Here, we show for tactile perceptual learning that the representation of the palm of the hand in primary somatosensory cortex (SI) is coactivated to support learning of a difficult tactile discrimination task with tactile stimulation of the sole of the foot. Such cortical coactivation of an untrained body part to support tactile learning with a trained body part might be critically involved in the subsequent transfer of tactile learning between the trained and untrained body parts., (Copyright © 2022 the authors.)

Comprehending the interplay between spatial and temporal characteristics of neural dynamics can contribute to our understanding of information processing in the human brain. Graph neural networks (GNNs) provide a new possibility to interpret graph-structured signals like those observed in complex brain networks. In our study we compare different spatiotemporal GNN architectures and study their ability to model neural activity distributions obtained in functional MRI (fMRI) studies. We evaluate the performance of the GNN models on a variety of scenarios in MRI studies and also compare it to a VAR model, which is currently often used for directed functional connectivity analysis. We show that by learning localized functional interactions on the anatomical substrate, GNN-based approaches are able to robustly scale to large network studies, even when available data are scarce. By including anatomical connectivity as the physical substrate for information propagation, such GNNs also provide a multimodal perspective on directed connectivity analysis, offering a novel possibility to investigate the spatiotemporal dynamics in brain networks., (© 2022 Massachusetts Institute of Technology.)

Background: Tractography based on diffusion-weighted magnetic resonance imaging (DWI) models the structural connectivity of the human brain. Deep brain stimulation (DBS) targeting the subthalamic nucleus is an effective treatment for advanced Parkinson's disease, but may induce adverse effects. This study investigated the relationship between structural connectivity patterns of DBS electrodes and stimulation-induced side effects. Materials and Methods: Twenty-one patients with Parkinson's disease treated with bilateral subthalamic DBS were examined. Overall, 168 electrode contacts were categorized as inducing or noninducing depending on their capability for inducing side effects such as motor effects, paresthesia, dysarthria, oculomotor effects, hyperkinesia, and other complications as assessed during the initial programming session. Furthermore, the connectivity of each contact with target regions was evaluated by probabilistic tractography based on DWI. Finally, stimulation sites and structural connectivity patterns of inducing and noninducing contacts were compared. Results: Inducing contacts differed across the various side effects and from those mitigating Parkinson's symptoms. Although contacts showed a largely overlapping spatial distribution within the subthalamic region, they could be distinguished by their connectivity patterns. In particular, inducing contacts were more likely connected with supplementary motor areas (hyperkinesia, dysarthria), frontal cortex (oculomotor), fibers of the internal capsule (paresthesia), and the basal ganglia-thalamo-cortical circuitry (dysarthria). Discussion: Side effects induced by DBS seem to be associated with distinct connectivity patterns. Cerebellar connections are hardly associated with side effects, although they seem relevant for mitigating motor symptoms in Parkinson's disease. A symptom-specific, connectivity-based approach for target planning in DBS may enhance treatment outcomes and reduce adverse effects. Impact statement Tractography based on diffusion-weighted magnetic resonance imaging has become a prominent technique for investigating the connectivity of human brain networks in vivo . However, the relationship between structural connections and brain function is still hardly known. The present study examined the relationship between adverse behavioral effects induced by deep brain stimulation (DBS) and tractography patterns in individual brains. The results suggest that DBS-based side effects depend on the structural connections of electrode contacts rather than their location. Network-based target planning in DBS may improve treatment by avoiding side effects. Moreover, the adopted approach may serve as a paragon for investigating structure/function relationships.

Numerical estimation of arrays of objects is faster and more accurate when items can be clustered into groups, a phenomenon termed "groupitizing." Grouping can facilitate segregation into subitizable "chunks," each easily estimated, then summed. The current study investigates whether spatial grouping of arrays drives specific neural responses during numerical estimation, reflecting strategies such as exact calculation and fact retrieval. Fourteen adults were scanned with fMRI while estimating either the numerosity or shape of arrays of items, either randomly distributed or spatially grouped. Numerosity estimation of both classes of stimuli elicited common activation of a right lateralized frontoparietal network. Grouped stimuli additionally recruited regions in the left hemisphere and bilaterally in the angular gyrus. Multivariate pattern analysis showed that classifiers trained with the pattern of neural activations read out from parietal regions, but not from the primary visual areas, can decode different numerosities both within and across spatial arrangements. The behavioral numerical acuity correlated with the decoding performance of the parietal but not with occipital regions. Overall, this experiment suggests that the estimation of grouped stimuli relies on the approximate number system for numerosity estimation, but additionally recruits regions involved in calculation., (© 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Center-surround modulation in visual processing reflects a normalization process of contrast gain control in the responsive neurons. Prior adaptation to a clockwise (CW) tilted grating, for example, leads to the percept of counterclockwise tilt in a vertical grating, referred to as the tilt-aftereffect (TAE). We previously reported that the magnitude of the TAE is modulated by adding a same-orientation annular surround to an adapter, suggesting inhibitory lateral modulation. To further examine the property of this lateral modulation effect on the perception of a central target, we here used center-surround sinusoidal patterns as adapters and varied the adapter surround and center orientations independently. The target had the same spatial extent as the adapter center with no physical overlap with the adapter surround. Participants were asked to judge the target orientation as tilted either CW or counterclockwise from vertical after adaptation. Results showed that, when the surround orientation was held constant, the TAE magnitude was determined by the adapter center, peaking between 10° and 20° of tilt. More important, the adapter surround orientation modulated the adaptation effect such that the TAE magnitude first decreased and then increased as the surround orientation became increasingly more different from that of the center, suggesting that the surround modulation effect was indeed orientation specific. Our data can be accounted for by a divisive inhibition model, in which (1) the adaptation effect is represented by increasing the normalizing constant and (2) the surround modulation is captured by two multiplicative sensitivity parameters determined by the adapter surround orientation.

Visual crowding refers to the impairment of recognizing peripherally presented objects flanked by distractors. Crowding effects, exhibiting a certain spatial extent between target and flankers, can be reduced by perceptual learning. In this experiment, we investigated the learning-induced reduction of crowding in normally sighted participants and tested if learning on one optotype (Landolt-C) transfers to another (Tumbling-E) or vice versa. Twenty-three normally sighted participants (18-42 years) trained on a crowding task in the right-upper quadrant (target at 6.5 degrees eccentricity) over four sessions. Half of the participants had the four-alternative forced-choice task to discriminate the orientation of a Landolt-C, the other half of participants had the task to discriminate the orientation of a Tumbling-E, each flanked by distractors. In the fifth session, all participants switched to the other untrained optotype, respectively. Learning success was measured as reduction of the spatial extent of crowding. We found an overall significant and comparable learning-induced reduction of crowding in both conditions (Landolt-C and Tumbling-E). However, only in the group who trained on the Landolt-C task did learning effects transfer to the other optotype. The specific target-flanker-constellations may modulate the transfer effects found here. Perceptual learning of a crowding task with optotypes could be a promising tool in rehabilitation programs to help improve peripheral vision (e.g. in patients with central vision loss), but the dependence of possible transfer effects on the optotype and distractors used requires further clarification.

Retinal diseases like age-related macular degeneration (AMD) or hereditary juvenile macular dystrophies (JMD) lead to a loss of central vision. Many patients compensate for this loss with a pseudo fovea in the intact peripheral retina, the so-called "preferred retinal locus" (PRL). How extensive eccentric viewing associated with central vision loss (CVL) affects brain structures responsible for visual perception and visually guided eye movements remains unknown. CVL results in a reduction of cortical gray matter in the "lesion projection zone" (LPZ) in early visual cortex, but the thickness of primary visual cortex appears to be largely preserved for eccentric-field representations. Here we explore how eccentric viewing strategies are related to cortical thickness (CT) measures in early visual cortex and in brain areas involved in the control of eye movements (frontal eye fields, FEF, supplementary eye fields, SEF, and premotor eye fields, PEF). We determined the projection zones (regions of interest, ROIs) of the PRL and of an equally peripheral area in the opposite hemifield (OppPRL) in early visual cortex (V1 and V2) in 32 patients with MD and 32 age-matched controls (19-84 years) by functional magnetic resonance imaging. Subsequently, we calculated the CT in these ROIs and compared it between PRL and OppPRL as well as between groups. Additionally, we examined the CT of FEF, SEF, and PEF and correlated it with behavioral measures like reading speed and eccentric fixation stability at the PRL. We found a significant difference between PRL and OppPRL projection zones in V1 with increased CT at the PRL, that was more pronounced in the patients, but also visible in the controls. Although the mean CT of the eye fields did not differ significantly between patients and controls, we found a trend to a positive correlation between CT in the right FEF and SEF and fixation stability in the whole patient group and between CT in the right PEF and reading speed in the JMD subgroup. The results indicate a possible association between the compensatory strategies used by patients with CVL and structural brain properties in early visual cortex and cortical eye fields., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Plank, Benkowitsch, Beer, Brandl, Malania, Frank, Jägle and Greenlee.)

This short survey reviews the recent literature on the relationship between the brain structure and its functional dynamics. Imaging techniques such as diffusion tensor imaging (DTI) make it possible to reconstruct axonal fiber tracks and describe the structural connectivity (SC) between brain regions. By measuring fluctuations in neuronal activity, functional magnetic resonance imaging (fMRI) provides insights into the dynamics within this structural network. One key for a better understanding of brain mechanisms is to investigate how these fast dynamics emerge on a relatively stable structural backbone. So far, computational simulations and methods from graph theory have been mainly used for modeling this relationship. Machine learning techniques have already been established in neuroimaging for identifying functionally independent brain networks and classifying pathological brain states. This survey focuses on methods from machine learning, which contribute to our understanding of functional interactions between brain regions and their relation to the underlying anatomical substrate., Competing Interests: The authors declare that they have no conflicts of interest., (Copyright © 2021 Simon Wein et al.)

Functional magnetic resonance imaging (fMRI) is a valuable tool in the clinical routine of neurosurgery when planning surgical interventions and assessing the risk of postoperative functional deficits. Here, we examined how the presence of a brain tumor or lesion in the area of the occipital lobe affects the results of fMRI retinotopic mapping. fMRI data were evaluated on a retrospectively selected sample of 12 patients with occipital brain tumors, 7 patients with brain lesions and 19 control subjects. Analyses of the cortical activation, percent signal change, cluster size of the activated voxels and functional connectivity were carried out using Statistical Parametric Mapping (SPM12) and the CONN and Marsbar toolboxes. We found similar but reduced patterns of cortical activation and functional connectivity between the two patient groups compared to a healthy control group. Here, we found that retinotopic organization was well-preserved in the patients and was comparable to that of the age-matched controls. The results also showed that, compared to the tumor patients, the lesion patients showed higher percent signal changes but lower values in the cluster sizes of the activated voxels in the calcarine fissure region. Our results suggest that the lesion patients exhibited results that were more similar to those of the control subjects in terms of the BOLD signal, whereas the extent of the activation was comparable to that of the tumor patients.

A central question in neuroscience is how self-organizing dynamic interactions in the brain emerge on their relatively static structural backbone. Due to the complexity of spatial and temporal dependencies between different brain areas, fully comprehending the interplay between structure and function is still challenging and an area of intense research. In this paper we present a graph neural network (GNN) framework, to describe functional interactions based on the structural anatomical layout. A GNN allows us to process graph-structured spatio-temporal signals, providing a possibility to combine structural information derived from diffusion tensor imaging (DTI) with temporal neural activity profiles, like that observed in functional magnetic resonance imaging (fMRI). Moreover, dynamic interactions between different brain regions discovered by this data-driven approach can provide a multi-modal measure of causal connectivity strength. We assess the proposed model's accuracy by evaluating its capabilities to replicate empirically observed neural activation profiles, and compare the performance to those of a vector auto regression (VAR), like that typically used in Granger causality. We show that GNNs are able to capture long-term dependencies in data and also computationally scale up to the analysis of large-scale networks. Finally we confirm that features learned by a GNN can generalize across MRI scanner types and acquisition protocols, by demonstrating that the performance on small datasets can be improved by pre-training the GNN on data from an earlier study. We conclude that the proposed multi-modal GNN framework can provide a novel perspective on the structure-function relationship in the brain. Accordingly this approach appears to be promising for the characterization of the information flow in brain networks.

Attending to a stimulus enhances the neuronal responses to it, while responses to nonattended stimuli are not enhanced and may even be suppressed. Although the neural mechanisms of response enhancement for attended stimuli have been intensely studied, the neural mechanisms underlying attentional suppression remain largely unknown. It is uncertain whether attention acts to suppress the processing in sensory cortical areas that would otherwise process the nonattended stimulus or the subcortical input to these cortical areas. Moreover, the neurochemical mechanisms inducing a reduction or suppression of neuronal responses to nonattended stimuli are as yet unknown. Here, we investigated how attention directed toward visual processing cross-modally acts to suppress vestibular responses in the human brain. By using functional magnetic resonance spectroscopy in a group of female and male subjects, we find that attention to visual motion downregulates in a load-dependent manner the concentration of excitatory neurotransmitter (glutamate and its precursor glutamine, referred to together as Glx) within the parietoinsular vestibular cortex (PIVC), a core cortical area of the vestibular system, while leaving the concentration of inhibitory neurotransmitter (GABA) in PIVC unchanged. This makes PIVC less responsive to excitatory thalamic vestibular input, as corroborated by functional magnetic resonance imaging. Together, our results suggest that attention acts to suppress the processing of nonattended sensory cues cortically by neurochemically rendering the core cortical area of the nonattended sensory modality less responsive to excitatory thalamic input. SIGNIFICANCE STATEMENT Here, we address a fundamental problem that has eluded attention research for decades, namely, how the brain ignores irrelevant stimuli. To date, three classes of solutions to this problem have been proposed: (1) enhancement of GABAergic interneuron activity in cortex, (2) downregulation of glutamatergic cell activity in cortex; and (3) downregulation of neural activity in thalamic projection areas, which would then provide the cortex with less input. Here, we use magnetic resonance spectroscopy in humans and find support for the second hypothesis, implying that attention to one sensory modality involves the suppression of irrelevant stimuli of another sensory modality by downregulating glutamate in the cortex., (Copyright © 2021 the authors.)

(1) Background-Mapping language using direct cortical stimulation (DCS) during an awake craniotomy is difficult without using more than one language paradigm that particularly follows the demand of DCS by not exceeding the assessment time of 4 s to prevent intraoperative complications. We designed an intraoperative language paradigm by combining classical picture naming and verb generation, which safely engaged highly relevant language functions. (2) Methods-An evaluation study investigated whether a single trial of the language task could be performed in less than 4 s in 30 healthy subjects and whether the suggested language paradigm sufficiently pictured the cortical language network using functional magnetic resonance imaging (fMRI) in 12 healthy subjects. In a feasibility study, 24 brain tumor patients conducted the language task during an awake craniotomy. The patients' neuropsychological outcomes were monitored before and after surgery. (3) Results-The fMRI results in healthy subjects showed activations in a language-associated network around the (left) sylvian fissure. Single language trials could be performed within 4 s. Intraoperatively, all tumor patients showed DCS-induced language errors while conducting the novel language task. Postoperatively, mild neuropsychological impairments appeared compared to the presurgical assessment. (4) Conclusions-These data support the use of a novel language paradigm that safely monitors highly relevant language functions intraoperatively, which can consequently minimize negative postoperative neuropsychological outcomes.

The results of two experiments are analyzed to find out how artistic expertise influences visual search. Experiment I comprised survey data of 1,065 students on self-reported visual memory skills and their ability to find three targets in four images of artwork. Experiment II comprised eye movement data of 50 Visual Literacy (VL) experts and non-experts whose eye movements during visual search were analyzed for nine images of artwork as an external validation of the assessment tasks performed in Sample I. No time constraint was set for completion of the visual search task. A latent profile analysis revealed four typical solution patterns for the students in Sample I, including a mainstream group, a group that completes easy images fast and difficult images slowly, a fast and erroneous group, and a slow working student group, depending on task completion time and on the probability of finding all three targets. Eidetic memory, performance in art education and visual imagination as self-reported visual skills have significant impact on latent class membership probability. We present a hidden Markov model (HMM) approach to uncover underlying regions of attraction that result from visual search eye-movement behavior in Experiment II. VL experts and non-experts did not significantly differ in task time and number of targets found but they did differ in their visual search process: compared to non-experts, experts showed greater precision in fixating specific prime and target regions, assessed through hidden state fixation overlap. Exploratory analysis of HMMs revealed differences between experts and non-experts in image locations of attraction (HMM states). Experts seem to focus their attention on smaller image parts whereas non-experts used wider parts of the image during their search. Differences between experts and non-experts depend on the relative saliency of targets embedded in images. HMMs can determine the effect of expertise on exploratory eye movements executed during visual search tasks. Further research on HMMs and art expertise is required to confirm exploratory results., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Tallon, Greenlee, Wagner, Rakoczy and Frick.)

It has remained uncertain whether the mechanisms of visual perceptual learning (VPL) 1-4 remain stable across the lifespan or undergo developmental changes. This uncertainty largely originates from missing results about the mechanisms of VPL in healthy children. We here investigated the mechanisms of task-irrelevant VPL in healthy elementary school age children (7-10 years old) and compared their results to healthy young adults (18-31 years old). Subjects performed a rapid-serial-visual-presentation (RSVP) task at central fixation over the course of several daily sessions while coherent motion was merely exposed as a task-irrelevant feature in the visual periphery either at threshold or suprathreshold levels for coherent motion detection. As a result of this repeated exposure, children and adults both showed enhanced discrimination performance for the threshold task-irrelevant feature as in previous studies with adults. 5-8 However, adults demonstrated a decreased performance for the suprathreshold task-irrelevant feature whereas children increased performance. One possible explanation for this difference is that children cannot effectively suppress salient task-irrelevant features because of weaker selective attention ability compared to that of adults. 9-11 However, our results revealed to the contrary that children with stronger selective attention ability, as measured by the useful field of view (UFOV) test, showed greater increases in performance for the suprathreshold task-irrelevant feature. Together, these results suggest that the mechanisms of VPL change dramatically from childhood to adulthood due to a change in the way learners handle salient task-irrelevant features., Competing Interests: Declaration of Interests The authors declare no competing interests., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Tinnitus, the phantom perception of sound, is a frequent disorder that can lead to severe distress and stress-related comorbidity. The pathophysiological mechanisms involved in the etiology of tinnitus are still under exploration. Electrophysiological and functional neuroimaging studies provide increasing evidence for abnormal functioning in auditory but also in non-auditory, e.g., emotional, brain areas. In order to elucidate alterations of affective processing in patients with chronic tinnitus, we used functional magnetic resonance imaging (fMRI) to measure neural responses to emotionally expressive and neutral faces. Twelve patients with chronic tinnitus and a group of 11 healthy controls, matched for age, sex, hearing loss and depressive symptoms were investigated. While viewing emotionally expressive faces compared to neutral faces brain activations in the tinnitus patients differed from those of the controls in a cluster that encompasses the amygdala, the hippocampus and the parahippocampal gyrus bilaterally. Whereas in controls affective faces induced higher brain activation in these regions than neutral faces, these regions in tinnitus patients were deactivated. Our results (1) provide evidence for alterations of affective processing of facial expressions in tinnitus patients indicating general domain-unspecific dysfunctions in emotion processing and (2) indicate the involvement of medial temporal areas in the pathophysiology of tinnitus., (Copyright © 2021 Elsevier B.V. All rights reserved.)

The perception of a target stimulus may be altered by its context. Perceptual filling-in is thought to be one example of lateral modulation, in which the percept of a central blank area is replaced by that of the surround. We investigated the mechanisms in eccentric vision underlying filling-in by selectively adapting the center (pedestal adapter), surround (annulus adapter), or both (disk adapter) in a sinusoidal grating and observed how the adaptation influences the orientation percept of a subsequently presented Gabor target, located at the same position as the adapter center. In a binary choice task, observers were to judge the orientation (clockwise or counterclockwise) of the target after adaptation. The tilt aftereffect (TAE), corresponding to an illusory tilt of a physically vertical Gabor target, depended both on the adapter orientation and the adapter type. The TAE, peaked between 10 degrees and 20 degrees adapter orientation, was strongest in the pedestal, followed by the disk, and weakest in the annulus adapter conditions. The difference between the disk and pedestal conditions implies lateral inhibition from the surround. Lacking physical overlap with the target, the annulus adapter nonetheless induced a small but significant TAE in the central area. The effect of filling-in on the TAE was estimated by comparing the results from trials with and without subjectively reported filling-in during adaptation to the annulus adapter. The TAE was greater when filling-in occurred during adaptation, suggesting a stronger lateral modulation effect on trials where filling-in was induced. The data were fit by a variant of a divisive inhibition model, in which the adaptation effect is captured by the increase of an additive constant in the denominator of the response function, whereas the surround modulation in the adapter is modeled by an excitatory sensitivity in the numerator.

Purpose: One of the diagnostic features of visual crowding, radial-tangential anisotropy, has been observed both in behavioral experiments as well as in responses of the blood-oxygenation-level-dependent (BOLD) functional magnetic resonance imaging (fMRI) signal. As has been shown previously, crowding is stronger for radially arranged flankers, and this tendency is reflected in BOLD signal suppression. In the current study, we examined the effect of practice on the neural correlates of crowding. We expected that training on a crowding task would cause shrinkage of the crowding zone that would be mirrored in corresponding BOLD signal responses., Methods: Pre- and post-training fMRI images were acquired in 17 healthy volunteers using a 3-tesla MRI scanner. Participants were trained over 4 consecutive days on a crowding task., Results: Comparison of the pre- and post-training behavioral data indicates a significant shrinkage of the crowding zone as a result of training. Moreover, we observed a pronounced radial-tangential anisotropy in the BOLD signal prior to training; that is, radial flankers induced a larger reduction in the BOLD signal compared to equally spaced tangential flankers. After training, this radial-tangential anisotropy in the BOLD signal was significantly reduced. Specifically, we found significant changes in BOLD responses for the radial flanker configuration., Conclusions: Our results demonstrate that training-induced changes in the anisotropic shape of the crowding zone are reflected in the BOLD signal in the early visual cortex., Translational Relevance: Perceptual learning tasks may have the potential to improve visual performance by promoting neural plasticity. Our results could motivate the development of suitable rehabilitation protocols for patients with central vision loss., Competing Interests: Disclosure: M. Malania, None; M. Pawellek, None; T. Plank, None; M.W. Greenlee, None, (Copyright 2020 The Authors.)

Aging and central vision loss are associated with cortical atrophies, but little is known about the relationship between cortical thinning and the underlying cellular structure. We compared the macro- and micro-structure of the cortical gray and superficial white matter of 38 patients with juvenile (JMD) or age-related (AMD) macular degeneration and 38 healthy humans (19-84 years) by multimodal MRI including diffusion-tensor imaging (DTI). A factor analysis showed that cortical thickness, tissue-dependent measures, and DTI-based measures were sensitive to distinct components of brain structure. Age-related cortical thinning and increased diffusion were observed across most of the cortex, but increased T1-weighted intensities (frontal), reduced T2-weighted intensities (occipital), and reduced anisotropy (medial) were limited to confined cortical regions. Vision loss was associated with cortical thinning and enhanced diffusion in the gray matter (less in the white matter) of the occipital central visual field representation. Moreover, AMD (but not JMD) patients showed enhanced diffusion in lateral occipito-temporal cortex and cortical thinning in the posterior cingulum. These findings demonstrate that changes in brain structure are best quantified by multimodal imaging. They further suggest that age-related brain atrophies (cortical thinning) reflect diverse micro-structural etiologies. Moreover, juvenile and age-related macular degeneration are associated with distinct patterns of micro-structural alterations., Competing Interests: Declaration of competing interest Declarations of interest: none., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)

Independent component analysis (ICA), being a data-driven method, has been shown to be a powerful tool for functional magnetic resonance imaging (fMRI) data analysis. One drawback of this multivariate approach is that it is not, in general, compatible with the analysis of group data. Various techniques have been proposed to overcome this limitation of ICA. In this paper, a novel ICA-based workflow for extracting resting-state networks from fMRI group studies is proposed. An empirical mode decomposition (EMD) is used, in a data-driven manner, to generate reference signals that can be incorporated into a constrained version of ICA (cICA), thereby eliminating the inherent ambiguities of ICA. The results of the proposed workflow are then compared to those obtained by a widely used group ICA approach for fMRI analysis. In this study, we demonstrate that intrinsic modes, extracted by EMD, are suitable to serve as references for cICA. This approach yields typical resting-state patterns that are consistent over subjects. By introducing these reference signals into the ICA, our processing pipeline yields comparable activity patterns across subjects in a mathematically transparent manner. Our approach provides a user-friendly tool to adjust the trade-off between a high similarity across subjects and preserving individual subject features of the independent components., (Copyright © 2020 Wein, Tomé, Goldhacker, Greenlee and Lang.)

There is growing evidence that vestibular information is not only involved in reflexive eye movements and the control of posture but it also plays an important role in higher order cognitive processes. Previous behavioral research has shown that concomitant vestibular stimuli influence performance in tasks that involve imagined self-rotations. These results suggest that imagined and perceived body rotations share common mechanisms. However, the nature and specificity of these effects remain largely unknown. Here, we investigated the neural mechanisms underlying this vestibulocognitive interaction. Participants ( n = 20) solved an imagined self-rotation task during caloric vestibular stimulation. We found robust main effects of caloric vestibular stimulation in the core region of the vestibular network, including the rolandic operculum and insula bilaterally, and of the cognitive task in parietal and frontal regions. Interestingly, we found an interaction of stimulation and task in the left inferior parietal lobe, suggesting that this region represents the modulation of imagined body rotations by vestibular input. This result provides evidence that the inferior parietal lobe plays a crucial role in the neural integration of mental and physical body rotation.

Previous studies in human subjects reported that the parieto-insular vestibular cortex (PIVC), a core area of the vestibular cortex, is inhibited when visual processing is prioritized. However, it has remained unclear which networks in the brain modulate this inhibition of PIVC. Based on previous results showing that the inhibition of PIVC is strongly influenced by visual attention, we here examined whether attention networks in the parietooccipital cortex modulate the inhibition of PIVC. Using diffusion-weighted and resting-state fMRI in a group of female and male subjects, we found structural and functional connections between PIVC and the posterior parietal cortex (PPC), a major brain region of the cortical attention network. We then temporarily inhibited PPC by repetitive transcranial magnetic stimulation (rTMS) and hypothesized that the modulatory influence of PPC over PIVC would be reduced; and, as a result, PIVC would be less inhibited. Subjects performed a visual attentional tracking task immediately after rTMS, and the inhibition of PIVC during attentive tracking was measured with fMRI. The results showed that the inhibition of PIVC during attentive tracking was less pronounced compared with sham rTMS. We also examined the effects of inhibitory rTMS over the occipital cortex and found that the visual-vestibular posterior insular cortex area was less activated during attentive tracking compared with sham rTMS or rTMS over PPC. Together, these results suggest that attention networks in the parietooccipital cortex modulate activity in core areas of the vestibular cortex during attentive visual processing. SIGNIFICANCE STATEMENT Although multisensory integration is generally considered beneficial, it can become detrimental when cues from different senses are in conflict. The occurrence of such multisensory conflicts can be minimized by inhibiting core cortical areas of the subordinate sensory system (e.g., vestibular), thus reducing potential conflict with ongoing processing of the prevailing sensory (e.g., visual) cues. However, it has remained unclear which networks in the brain modulate the magnitude of inhibition of the subordinate sensory system. Here, by investigating the inhibition of the vestibular sensory system when visual processing is prioritized, we show that attention networks in the parietooccipital cortex modulate the magnitude of inhibition of the vestibular cortex., (Copyright © 2020 the authors.)

Background: MRI fluid-attenuated inversion recovery (FLAIR) studies reported hyperintensity in the corticospinal tract and corpus callosum of patients with amyotrophic lateral sclerosis (ALS)., Purpose: To evaluate the lesion segmentation toolbox (LST) for the objective quantification of FLAIR lesions in ALS patients., Study Type: Retrospective., Population: Twenty-eight ALS patients (eight females, mean age: 50 range: 24-73, mean ALSFRS-R sum score: 36) were compared with 31 age-matched healthy controls (12 females, mean age: 45, range: 25-67). ALS patients were treated with riluzole and additional G-CSF (granulocyte-colony stimulating factor) on a named patient basis., Field Strength/sequence: 1.5 T, FLAIR, T 1 -weighted MRI., Assessment: The lesion prediction algorithm (LPA) of the LST enabled the extraction of individual binary lesion maps, total lesion volume (TLV), and number (TLN). Location and overlap of FLAIR lesions across patients were investigated by registration to FLAIR average space and an atlas. ALS-specific functional rating scale revised (ALSFRS-R), disease progression, and survival since diagnosis served as clinical correlates., Statistical Tests: Univariate analysis of variance (ANOVA), repeated-measures ANOVA, t-test, Bravais-Pearson correlation, Chi-square test of independence, Kaplan-Meier analysis, Cox-regression analysis., Results: Both ALS patients and healthy controls exhibited FLAIR alterations. TLN significantly depended on age (F(1,54) = 24.659, P < 0.001) and sex (F(1,54) = 5.720, P = 0.020). ALS patients showed higher TLN than healthy controls depending on sex (F(1, 54) = 5.076, P = 0.028). FLAIR lesions were small and most pronounced in male ALS patients. FLAIR alterations were predominantly detected in the superior and posterior corona radiata, anterior capsula interna, and posterior thalamic radiation. Patients with pyramidal tract (PT) lesions exhibited significantly inferior survival than patients without PT lesions (P = 0.013). Covariate age exhibited strong prognostic value for survival (P = 0.015)., Data Conclusion: LST enables the objective quantification of FLAIR alterations and is a potential prognostic biomarker for ALS., Level of Evidence: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:552-559., (© 2018 The Authors. Journal of Magnetic Resonance Imaging published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.)

Independent component analysis (ICA), as a data driven method, has shown to be a powerful tool for functional magnetic resonance imaging (fMRI) data analysis. One drawback of this multivariate approach is, that it is naturally not convenient for analysis of group studies. Therefore various techniques have been proposed in order to overcome this limitation of ICA. In this paper a novel ICA based work-flow for extracting resting state networks from fMRI group studies is proposed. An empirical mode decomposition (EMD) is used to generate reference signals in a data driven manner, which can be incorporated into a constrained version of ICA (cICA), what helps to overcome the inherent ambiguities. The results of the proposed workflow are then compared to those obtained by a widely used group ICA approach. It is demonstrated that intrinsic modes, extracted by EMD, are suitable to serve as references for cICA to obtain typical resting state patterns, which are consistent over subjects. This novel processing pipeline makes it transparent for the user, how comparable activity patterns across subjects emerge, and also the trade-off between similarity across subjects and preserving individual features can be well adjusted and adapted for different requirements in the new work-flow.

In this study, we investigated visual short-term memory for coherent motion in action video game players (AVGPs), non-action video game players (NAVGPs), and non-gamers (control group: CONs). Participants performed a visual memory-masking paradigm previously used with macaque monkeys and humans. In particular, we tested whether video game players form a more robust visual short-term memory trace for coherent moving stimuli during the encoding phase, and whether such memory traces are less affected by an intervening masking stimulus presented 0.2 s after the offset of the to-be-remembered sample. The results showed that task performance of all groups was affected by the masking stimulus, but video game players were affected to a lesser extent than controls. Modelling of performance values and reaction times revealed that video game players have a lower guessing rate than CONs, and higher drift rates than CONs, indicative of more efficient perceptual decisions. These results suggest that video game players exhibit a more robust VSTM trace for moving objects and this trace is less prone to external interference.

Multiple sclerosis is a debilitating disorder resulting from scattered lesions in the central nervous system. Because of the high variability of the lesion patterns between patients, it is difficult to relate existing biomarkers to symptoms and their progression. The scattered nature of lesions in multiple sclerosis offers itself to be studied through the lens of network analyses. Recent research into multiple sclerosis has taken such a network approach by making use of functional connectivity. In this review, we briefly introduce measures of functional connectivity and how to compute them. We then identify several common observations resulting from this approach: (a) high likelihood of altered connectivity in deep-gray matter regions, (b) decrease of brain modularity, (c) hemispheric asymmetries in connectivity alterations, and (d) correspondence of behavioral symptoms with task-related and task-unrelated networks. We propose incorporating such connectivity analyses into longitudinal studies in order to improve our understanding of the underlying mechanisms affected by multiple sclerosis, which can consequently offer a promising route to individualizing imaging-related biomarkers for multiple sclerosis.

Here, we review the structure and function of a core region in the vestibular cortex of humans that is located in the midposterior Sylvian fissure and referred to as the parieto-insular vestibular cortex (PIVC). Previous studies have investigated PIVC by using vestibular or visual motion stimuli and have observed activations that were distributed across multiple anatomical structures, including the temporo-parietal junction, retroinsula, parietal operculum, and posterior insula. However, it has remained unclear whether all of these anatomical areas correspond to PIVC and whether PIVC responds to both vestibular and visual stimuli. Recent results suggest that the region that has been referred to as PIVC in previous studies consists of multiple areas with different anatomical correlates and different functional specializations. Specifically, a vestibular but not visual area is located in the parietal operculum, close to the posterior insula, and likely corresponds to the nonhuman primate PIVC, while a visual-vestibular area is located in the retroinsular cortex and is referred to, for historical reasons, as the posterior insular cortex area (PIC). In this article, we review the anatomy, connectivity, and function of PIVC and PIC and propose that the core of the human vestibular cortex consists of at least two separate areas, which we refer to together as PIVC+. We also review the organization in the nonhuman primate brain and show that there are parallels to the proposed organization in humans.

Sensory input to the human visual system often becomes accessible to cognition and overt report during processing. We investigated neural precursors of conscious vision using EEG recordings and the popular breaking continuous flash suppression (bCFS) paradigm. In this technique, a mask consisting of high-contrast dynamic patterns is presented to one eye, predominating over a target stimulus presented to the other eye. The time needed for the target stimulus to overcome the suppression is thought to reflect the transition from unconscious to conscious perception. In bCFS trials with slow responses, indicative of potent suppression, a time-frequency analysis showed reduced occipital gamma power (33-38 Hz) contralaterally to the visual hemifield where the target was presented 0.27 to 0.21 s prior to the behavioral response. This neural activity was concurrent with a local phase reset and enhanced long-range phase synchronization in the theta band (7 Hz). Such a pattern did not arise in a control condition in which suppression was not induced. Thus, the theta phase reset and synchronization in bCFS trials precede a break from suppression, likely initiating a re-routing of information such that the neural representation of the target is updated more efficiently than that of the competing mask. Overall, these findings mark the emergence of a binocularly integrated percept that can be consciously selected for a behavioral response., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Objective: Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative process affecting upper and lower motor neurons as well as non-motor systems. In this study, precentral and postcentral cortical thinning detected by structural magnetic resonance imaging (MRI) were combined with clinical (ALS-specific functional rating scale revised, ALSFRS-R) and neurophysiological (motor unit number index, MUNIX) biomarkers in both cross-sectional and longitudinal analyses. Methods: The unicenter sample included 20 limb-onset classical ALS patients compared to 30 age-related healthy controls. ALS patients were treated with standard Riluzole and additional long-term G-CSF (Filgrastim) on a named patient basis after written informed consent. Combinatory biomarker use included cortical thickness of atlas-based dorsal and ventral subdivisions of the precentral and postcentral cortex, ALSFRS-R, and MUNIX for the musculus abductor digiti minimi (ADM) bilaterally. Individual cross-sectional analysis investigated individual cortical thinning in ALS patients compared to age-related healthy controls in the context of state of disease at initial MRI scan. Beyond correlation analysis of biomarkers at cross-sectional group level ( n = 20), longitudinal monitoring in a subset of slow progressive ALS patients ( n = 4) explored within-subject temporal dynamics of repeatedly assessed biomarkers in time courses over at least 18 months. Results: Cross-sectional analysis demonstrated individually variable states of cortical thinning, which was most pronounced in the ventral section of the precentral cortex. Correlations of ALSFRS-R with cortical thickness and MUNIX were detected. Individual longitudinal biomarker monitoring in four slow progressive ALS patients revealed evident differences in individual disease courses and temporal dynamics of the biomarkers. Conclusion: A combinatory use of structural MRI, neurophysiological and clinical biomarkers allows for an appropriate and detailed assessment of clinical state and course of disease of ALS.

Competing Interests: Financial and non-financial competing interests: The authors declare no competing interests.

Investigating temporal variability of functional connectivity is an emerging field in connectomics. Entering dynamic functional connectivity by applying sliding window techniques on resting-state fMRI (rs-fMRI) time courses emerged from this topic. We introduce frequency-resolved dynamic functional connectivity (frdFC) by means of multivariate empirical mode decomposition (MEMD) followed up by filter-bank investigations. In general, we find that MEMD is capable of generating time courses to perform frdFC and we discover that the structure of connectivity-states is robust over frequency scales and even becomes more evident with decreasing frequency. This scale-stability varies with the number of extracted clusters when applying k -means. We find a scale-stability drop-off from k = 4 to k = 5 extracted connectivity-states, which is corroborated by null-models, simulations, theoretical considerations, filter-banks, and scale-adjusted windows. Our filter-bank studies show that filter design is more delicate in the rs-fMRI than in the simulated case. Besides offering a baseline for further frdFC research, we suggest and demonstrate the use of scale-stability as a possible quality criterion for connectivity-state and model selection. We present first evidence showing that connectivity-states are both a multivariate, and a multiscale phenomenon. A data repository of our frequency-resolved time-series is provided.

Grapheme-color synesthesia is a condition in which objectively achromatic graphemes induce concurrent color experiences. While it was long thought that the colors emerge during perception, there is growing support for the view that colors are integral to synesthetes' cognitive representations of graphemes. In this work, we review evidence for two opposing theories positing either a perceptual or cognitive origin of concurrent colors: the cross-activation theory and the conceptual-mediation model. The review covers results on inducer and concurrent color processing as well as findings concerning the brain structure and grapheme-color mappings in synesthetes and trained mappings in nonsynesthetes. The results support different aspects of both theories. Finally, we discuss how research on memory colors could provide a new perspective in the debate about the level of processing at which the synesthetic colors occur.