A cortical zoom-in operation underlies covert shifts of visual spatial attention.

Shifting the focus of attention without moving the eyes poses challenges for signal coding in visual cortex in terms of spatial resolution, signal routing, and cross-talk. Little is known how these problems are solved during focus shifts. Here, we analyze the spatiotemporal dynamic of neuromagnetic activity in human visual cortex as a function of the size and number of focus shifts in visual search. We find that large shifts elicit activity modulations progressing from highest (IT) through mid-level (V4) to lowest hierarchical levels (V1). Smaller shifts cause those modulations to start at lower levels in the hierarchy. Successive shifts involve repeated backward progressions through the hierarchy. We conclude that covert focus shifts arise from a cortical coarse-to-fine process progressing from retinotopic areas with larger toward areas with smaller receptive fields. This process localizes the target and increases the spatial resolution of selection, which resolves the above issues of cortical coding.

Attention expedites target selection by prioritizing the neural processing of distractor features.

Whether doing the shopping, or driving the car - to navigate daily life, our brain has to rapidly identify relevant color signals among distracting ones. Despite a wealth of research, how color attention is dynamically adjusted is little understood. Previous studies suggest that the speed of feature attention depends on the time it takes to enhance the neural gain of cortical units tuned to the attended feature. To test this idea, we had human participants switch their attention on the fly between unpredicted target color alternatives, while recording the electromagnetic brain response to probes matching the target, a non-target, or a distracting alternative target color. Paradoxically, we observed a temporally prioritized processing of distractor colors. A larger neural modulation for the distractor followed by its stronger attenuation expedited target identification. Our results suggest that dynamic adjustments of feature attention involve the temporally prioritized processing and elimination of distracting feature representations.

Behavioral and neurophysiological effects of an intensified robot-assisted therapy in subacute stroke: a case control study.

BACKGROUND: Physical training is able to induce changes at neurophysiological and behavioral level associated with performance changes for the trained movements. The current study explores the effects of an additional intense robot-assisted upper extremity training on functional outcome and motor excitability in subacute stroke patients. METHODS: Thirty moderately to severely affected patients < 3 months after stroke received a conventional inpatient rehabilitation. Based on a case-control principle 15 patients were assigned to receive additional 45 min of robot-assisted therapy (Armeo®Spring) 5 times per week (n = 15, intervention group, IG). The Fugl-Meyer Assessment for the Upper Extremity (FMA-UE) was chosen as primary outcome parameter. Patients were tested before and after a 3-week treatment period as well as after a follow-up period of 2 weeks. Using transcranial magnetic stimulation motor evoked potentials (MEPs) and cortical silent periods were recorded from the deltoid muscle on both sides before and after the intervention period to study effects at neurophysiological level. Statistical analysis was performed with non-parametric tests. Correlation analysis was done with Spearman´s rank correlation co-efficient. RESULTS: Both groups showed a significant improvement in FMA-UE from pre to post (IG: + 10.6 points, control group (CG): + 7.3 points) and from post to follow-up (IG: + 3.9 points, CG: + 3.3 points) without a significant difference between them. However, at neurophysiological level post-intervention MEP amplitudes were significantly larger in the IG but not in the CG. The observed MEP amplitudes changes were positively correlated with FMA-UE changes and with the total amount of robot-assisted therapy. CONCLUSION: The additional robot-assisted therapy induced stronger excitability increases in the intervention group. However, this effect did not transduce to motor performance improvements at behavioral level. Trial registration The trial was registered in German Clinical Trials Register. CLINICAL TRIAL REGISTRATION NUMBER: DRKS00015083. Registration date: September 4th, 2018. https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00015083 . Registration was done retrospectively.

Lathyrus sativus diamine oxidase reduces Clostridium difficile toxin A-induced toxicity in Caco-2 cells by rescuing RhoA-GTPase and inhibiting pp38-MAPK/NF-κB/HIF-1α activation.

Clostridium difficile toxin A (TcdA) impairs the intestinal epithelial barrier, increasing the mucosa permeability and triggering a robust inflammatory response. Lathyrus sativus diamino oxidase (LSAO) is a nutraceutical compound successfully used in various gastrointestinal dysfunctions. Here, we evaluated the LSAO (0.004-0.4 µM) ability to counter TcdA-induced (30 ng/mL) toxicity and damage in Caco-2 cells, investigating its possible mechanism of action. LSAO has improved the transepithelial electrical resistance (TEER) score and increased cell viability in TcdA-treated cells, significantly rescuing the protein expression of Ras homolog family members, A-GTPase (RhoA-GTPase), occludin, and zonula occludens-1 (ZO-1). LSAO has also exhibited an anti-apoptotic effect by inhibiting the TcdA-induced expression of Bcl-2-associated X protein (Bax), p50 nuclear factor-kappa-B (p50), p65nuclear factor-kappa-B (p65), and hypoxia-inducible transcription factor-1 alpha (HIF-1α), and the release of tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), and vascular endothelial growth factor (VEGF) in the cell milieu. Our data showed that LSAO exerts a protective effect on TcdA-induced toxicity in Caco-2 cells, placing itself as an interesting nutraceutical to supplement the current treatment of the Clostridium difficile infections.

Parallel fast and slow recurrent cortical processing mediates target and distractor selection in visual search.

Visual search has been commonly used to study the neural correlates of attentional allocation in space. Recent electrophysiological research has disentangled distractor processing from target processing, showing that these mechanisms appear to operate in parallel and show electric fields of opposite polarity. Nevertheless, the localization and exact nature of this activity is unknown. Here, using MEG in humans, we provide a spatiotemporal characterization of target and distractor processing in visual cortex. We demonstrate that source activity underlying target- and distractor-processing propagates in parallel as fast and slow sweep from higher to lower hierarchical levels in visual cortex. Importantly, the fast propagating target-related source activity bypasses intermediate levels to go directly to V1, and this V1 activity correlates with behavioral performance. These findings suggest that reentrant processing is important for both selection and attenuation of stimuli, and such processing operates in parallel feedback loops.

Effects of a single mental chronometry training session in subacute stroke patients - a randomized controlled trial.

BACKGROUND: Motor imagery training might be helpful in stroke rehabilitation. This study explored if a single session of motor imagery (MI) training induces performance changes in mental chronometry (MC), motor execution, or changes of motor excitability. METHODS: Subacute stroke patients (n = 33) participated in two training sessions. The order was randomized. One training consisted of a mental chronometry task, the other training was a hand identification task, each lasting 30 min. Before and after the training session, the Box and Block Test (BBT) was fully executed and also performed as a mental version which served as a measure of MC. A subgroup analysis based on the presence of sensory deficits was performed. Patients were allocated to three groups (no sensory deficits, moderate sensory deficits, severe sensory deficits). Motor excitability was measured by transcranial magnetic stimulation (TMS) pre and post training. Amplitudes of motor evoked potentials at rest and during pre-innervation as well as the duration of cortical silent period were measured in the affected and the non-affected hand. RESULTS: Pre-post differences of MC showed an improved MC after the MI training, whereas MC was worse after the hand identification training. Motor execution of the BBT was significantly improved after mental chronometry training but not after hand identification task training. Patients with severe sensory deficits performed significantly inferior in BBT execution and MC abilities prior to the training session compared to patients without sensory deficits or with moderate sensory deficits. However, pre-post differences of MC were similar in the 3 groups. TMS results were not different between pre and post training but showed significant differences between affected and unaffected side. CONCLUSION: Even a single training session can modulate MC abilities and BBT motor execution in a task-specific way. Severe sensory deficits are associated with poorer motor performance and poorer MC ability, but do not have a negative impact on training-associated changes of mental chronometry. Studies with longer treatment periods should explore if the observed changes can further be expanded. TRIAL REGISTRATION: DRKS, DRKS00020355, registered March 9th, 2020, retrospectively registered.

TDAview: an online visualization tool for topological data analysis.

SUMMARY: TDAview is an online tool for topological data analysis (TDA) and visualization. It implements the Mapper algorithm for TDA and provides extensive graph visualization options. TDAview is a user-friendly tool that allows biologists and clinicians without programming knowledge to harness the power of TDA. TDAview supports an analysis and visualization mode in which a Mapper graph is constructed based on user-specified parameters, followed by graph visualization. It can also be used in a visualization only mode in which TDAview is used for visualizing the data properties of a Mapper graph generated using other open-source software. The graph visualization options allow data exploration by graphical display of metadata variable values for nodes and edges, as well as the generation of publishable figures. TDAview can handle large datasets, with tens of thousands of data points, and thus has a wide range of applications for high-dimensional data, including the construction of topology-based gene co-expression networks. AVAILABILITY AND IMPLEMENTATION: TDAview is a free online tool available at https://voineagulab.github.io/TDAview/. The source code, usage documentation and example data are available at TDAview GitHub repository: https://github.com/Voineagulab/TDAview.

Electroencephalography reveals a selective disruption of cognitive control processes in craving cigarette smokers.

Addiction to nicotine is extremely challenging to overcome, and the intense craving for the next cigarette often leads to relapse in smokers who wish to quit. To dampen the urges of craving and inhibit unwanted behaviour, smokers must harness cognitive control, which is itself impaired in addiction. It is likely that craving may interact with cognitive control, and the present study sought to test the specificity of such interactions. To this end, data from 24 smokers were gathered using EEG and behavioural measures in a craving session (following a three-hour nicotine abstention period) and a non-craving session (having just smoked). In both sessions, participants performed a task probing various facets of cognitive control (response inhibition, task switching and conflict processing). Results showed that craving smokers were less flexible with the implementation of cognitive control, with demands of task switching and incongruency yielding greater deficits under conditions of craving. Importantly, inhibitory control was not affected by craving, suggesting that the interactions of craving and cognitive control are selective. Together, these results provide evidence that smokers already exhibit specific control-related deficits after brief nicotine deprivation. This disruption of cognitive control while craving may help to explain why abstinence is so difficult to maintain.

Persistent homology analysis of brain transcriptome data in autism.

Persistent homology methods have found applications in the analysis of multiple types of biological data, particularly imaging data or data with a spatial and/or temporal component. However, few studies have assessed the use of persistent homology for the analysis of gene expression data. Here we apply persistent homology methods to investigate the global properties of gene expression in post-mortem brain tissue (cerebral cortex) of individuals with autism spectrum disorders (ASD) and matched controls. We observe a significant difference in the geometry of inter-sample relationships between autism and healthy controls as measured by the sum of the death times of zero-dimensional components and the Euler characteristic. This observation is replicated across two distinct datasets, and we interpret it as evidence for an increased heterogeneity of gene expression in autism. We also assessed the topology of gene-level point clouds and did not observe significant differences between ASD and control transcriptomes, suggesting that the overall transcriptome organization is similar in ASD and healthy cerebral cortex. Overall, our study provides a novel framework for persistent homology analyses of gene expression data for genetically complex disorders.

A neural hallmark of auditory implicit learning is altered in older adults.

Temporal regularities in the environment are often learned implicitly. In an auditory target-detection paradigm using EEG, Jongsma and colleagues (2006) showed that the neural response to these implicit regularities results in a reduction of the P3-N2 complex. Here, we utilized the same paradigm, this time in both young and old participants, to determine if this EEG signature of implicit learning was altered with age. Behaviorally, both groups of participants showed similar benefits for the presence of temporal regularity, with faster and more accurate responses given when the auditory targets were presented in a temporally regular vs. random pattern. In the brain, the younger adults showed the expected decrease in amplitude of this complex for regular compared to irregular trials. Older adults, in contrast, showed no difference in the amplitude of the P3-N2 complex between the irregular and regular condition. These data suggest that, although auditory implicit learning may be behaviorally spared in aging, older adults are not using the same neural substrates as younger adults to achieve this.

A Study of Background Levels of Antimony, Barium, and Lead on Vehicle Surface Samples by Graphite Furnace Atomic Absorption.

Law enforcement agencies routinely sample for gunshot residue (GSR) by bulk techniques and often submit swabs taken from other surfaces besides the hands of the suspect shooter. This study aims to establish the prevalence of antimony, barium, and lead on normally handled automobile surfaces by graphite furnace atomic absorption analysis. No positives were determined on 50 sampled automobile surfaces above cutoff (positive) from background levels. Transfers of GSR particles from shooter hands to automobile surfaces were found to potentially allow for positive GSR determinations, but such transfers seem to be dependent on the shooting conditions and length of GSR exposure. We determined that our bulk analysis method yields an overall 87.94 ± 5.52% extraction efficiency from cotton swabs, while the LOQ determinations strengthening the fact that bulk analysis methods are valid and valuable tools for GSR investigations.

Dissociating Reward- and Attention-driven Biasing of Global Feature-based Selection in Human Visual Cortex.

Objects that promise rewards are prioritized for visual selection. The way this prioritization shapes sensory processing in visual cortex, however, is debated. It has been suggested that rewards motivate stronger attentional focusing, resulting in a modulation of sensory selection in early visual cortex. An open question is whether those reward-driven modulations would be independent of similar modulations indexing the selection of attended features that are not associated with reward. Here, we use magnetoencephalography in human observers to investigate whether the modulations indexing global color-based selection in visual cortex are separable for target- and (monetary) reward-defining colors. To assess the underlying global color-based activity modulation, we compare the event-related magnetic field response elicited by a color probe in the unattended hemifield drawn either in the target color, the reward color, both colors, or a neutral task-irrelevant color. To test whether target and reward relevance trigger separable modulations, we manipulate attention demands on target selection while keeping reward-defining experimental parameters constant. Replicating previous observations, we find that reward and target relevance produce almost indistinguishable gain modulations in ventral extratriate cortex contralateral to the unattended color probe. Importantly, increasing attention demands on target discrimination increases the response to the target-defining color, whereas the response to the rewarded color remains largely unchanged. These observations indicate that, although task relevance and reward influence the very same feature-selective area in extrastriate visual cortex, the associated modulations are largely independent.

Enhanced spatial focusing increases feature-based selection in unattended locations.

Attention is a multifaceted phenomenon, which operates on features (e.g., colour or motion) and over space. A fundamental question is whether the attentional selection of features is confined to the spatially-attended location or operates independently across the entire visual field (global feature-based attention, GFBA). Studies providing evidence for GFBA often employ feature probes presented at spatially unattended locations, which elicit enhanced brain responses when they match a currently-attended target feature. However, the validity of this interpretation relies on consistent spatial focusing onto the target. If the probe were to temporarily attract spatial attention, the reported effects could reflect transient spatial selection processes, rather than GFBA. Here, using magnetoencephalographic recordings (MEG) in humans, we manipulate the strength and consistency of spatial focusing to the target by increasing the target discrimination difficulty (Experiment 1), and by demarcating the upcoming target's location with a placeholder (Experiment 2), to see if GFBA effects are preserved. We observe that motivating stronger spatial focusing to the target did not diminish the effects of GFBA. Instead, aiding spatial pre-focusing with a placeholder enhanced the feature response at unattended locations. Our findings confirm that feature selection effects measured with spatially-unattended probes reflect a true location-independent neural bias.

Detection and Quantitation of Trace Fentanyl in Heroin by Surface-Enhanced Raman Spectroscopy.

The identification of fentanyl, a main culprit in opioid overdose deaths, has become critical. Whereas Raman spectroscopy is an effective tool for detecting illicit drugs, the weak intensity of Raman scattering can make it difficult to distinguish trace materials. This shortcoming is addressed by surface-enhanced Raman spectroscopy (SERS), which produces strong signal enhancements when target compounds are near metal nanoparticles. This work examines the use of a paper-based substrate impregnated with silver nanoparticles for the detection of trace quantities of fentanyl alone and as an adulterant in heroin. In addition, intensity ratios of diagnostic peaks associated with each substance were fitted to a Langmuir isotherm calibration model and used for the quantitative analysis of fentanyl in heroin mixtures. Linearity was observed at <6% fentanyl, a significant finding that is consistent with concentrations found in drugs seized during law enforcement efforts. In addition, swabbing with these paper-based SERS substrates facilitated the recovery of fentanyl from surfaces, showing this to be applicable for crime scene investigations. However, assessment using the calibration model proved difficult for swabbed samples. Overall, this work demonstrates a potentially simple and sensitive technique for the forensic analysis and quantitation of fentanyl in trace amounts.

Cortical Mechanisms of Prioritizing Selection for Rejection in Visual Search.

In visual search, the more one knows about a target, the faster one can find it. Surprisingly, target identification is also faster with knowledge about distractor-features. The latter is paradoxical, as it implies that to avoid the selection of an item, the item must somehow be selected to some degree. This conundrum has been termed the "ignoring paradox", and, to date, little is known about how the brain resolves it. Here, in data from four experiments using neuromagnetic brain recordings in male and female humans, we provide evidence that this paradox is resolved by giving distracting information priority in cortical processing. This attentional priority to distractors manifests as an enhanced early neuromagnetic index, which occurs before target-related processing, and regardless of distractor predictability. It is most pronounced on trials for which a response rapidly occurred, and is followed by a suppression of the distracting information. These observations together suggest that in visual search items cannot be ignored without first being selected.SIGNIFICANCE STATEMENT How can we ignore distracting stimuli in our environment? To do this successfully, a logical hypothesis is that as few neural resources as possible should be devoted to distractor processing. Yet, to avoid devoting resources to a distractor, the brain must somehow mark what to avoid; this is a philosophical problem, which has been termed the "ignoring paradox" or "white bear phenomenon". Here, we use MEG recordings to determine how the human brain resolves this paradox. Our data show that distractors are not only processed, they are given temporal priority, with the brain building a robust representation of the to-be-ignored items. Thus, successful suppression of distractors can only be achieved if distractors are first strongly neurally represented.

Competitive Binding Investigations and Quantitation in Surface-Enhanced Raman Spectra of Binary Dye Mixtures.

This research presents a study in surface-enhanced Raman quantitation of dyes present in mixtures of alizarin and purpurin using standard calibration curves and Langmuir isotherm calibration models. Investigations of the nature of competitive adsorption onto silver nanoparticles by centrifugation indicates that both dyes in the mixture interact with the nanoparticles simultaneously, but only the stronger adsorbing one is seen to dominate the spectral characteristics. Calibration can be carried out by careful selection of peaks characteristic to each dye in the mixture. Comparisons of peak height and peak area calibrations reveal that peak heights, when selected by the maximum value and accounting for peak shifts, prove the better model for quantitation. It is also shown that the microwave nanoparticle synthesis method produces stable nanoparticles with a shelf-life of at least one year that give very little variation within and between uses.

Attention to Color Sharpens Neural Population Tuning via Feedback Processing in the Human Visual Cortex Hierarchy.

Attention can facilitate the selection of elementary object features such as color, orientation, or motion. This is referred to as feature-based attention and it is commonly attributed to a modulation of the gain and tuning of feature-selective units in visual cortex. Although gain mechanisms are well characterized, little is known about the cortical processes underlying the sharpening of feature selectivity. Here, we show with high-resolution magnetoencephalography in human observers (men and women) that sharpened selectivity for a particular color arises from feedback processing in the human visual cortex hierarchy. To assess color selectivity, we analyze the response to a color probe that varies in color distance from an attended color target. We find that attention causes an initial gain enhancement in anterior ventral extrastriate cortex that is coarsely selective for the target color and transitions within ∼100 ms into a sharper tuned profile in more posterior ventral occipital cortex. We conclude that attention sharpens selectivity over time by attenuating the response at lower levels of the cortical hierarchy to color values neighboring the target in color space. These observations support computational models proposing that attention tunes feature selectivity in visual cortex through backward-propagating attenuation of units less tuned to the target.SIGNIFICANCE STATEMENT Whether searching for your car, a particular item of clothing, or just obeying traffic lights, in everyday life, we must select items based on color. But how does attention allow us to select a specific color? Here, we use high spatiotemporal resolution neuromagnetic recordings to examine how color selectivity emerges in the human brain. We find that color selectivity evolves as a coarse to fine process from higher to lower levels within the visual cortex hierarchy. Our observations support computational models proposing that feature selectivity increases over time by attenuating the responses of less-selective cells in lower-level brain areas. These data emphasize that color perception involves multiple areas across a hierarchy of regions, interacting with each other in a complex, recursive manner.

Memory-Efficient Analysis of Dense Functional Connectomes.

The functioning of the human brain relies on the interplay and integration of numerous individual units within a complex network. To identify network configurations characteristic of specific cognitive tasks or mental illnesses, functional connectomes can be constructed based on the assessment of synchronous fMRI activity at separate brain sites, and then analyzed using graph-theoretical concepts. In most previous studies, relatively coarse parcellations of the brain were used to define regions as graphical nodes. Such parcellated connectomes are highly dependent on parcellation quality because regional and functional boundaries need to be relatively consistent for the results to be interpretable. In contrast, dense connectomes are not subject to this limitation, since the parcellation inherent to the data is used to define graphical nodes, also allowing for a more detailed spatial mapping of connectivity patterns. However, dense connectomes are associated with considerable computational demands in terms of both time and memory requirements. The memory required to explicitly store dense connectomes in main memory can render their analysis infeasible, especially when considering high-resolution data or analyses across multiple subjects or conditions. Here, we present an object-based matrix representation that achieves a very low memory footprint by computing matrix elements on demand instead of explicitly storing them. In doing so, memory required for a dense connectome is reduced to the amount needed to store the underlying time series data. Based on theoretical considerations and benchmarks, different matrix object implementations and additional programs (based on available Matlab functions and Matlab-based third-party software) are compared with regard to their computational efficiency. The matrix implementation based on on-demand computations has very low memory requirements, thus enabling analyses that would be otherwise infeasible to conduct due to insufficient memory. An open source software package containing the created programs is available for download.

An electrophysiological marker of the desire to quit in smokers.

For many smokers, the motivational state of craving is a central feature of their dependence on nicotine, and is often at odds with a general desire to quit. How this desire to quit may influence the craving for a cigarette, however, is unclear. In the current study, we manipulated the level of craving in 24 regular smokers, and recorded EEG measures of brain activity during a rare target detection task utilizing addiction-unrelated stimuli. In response to the non-targets, we observed that smokers wanting to quit showed an enhanced late frontal activation when they were craving vs. not craving, whereas smokers not wanting to quit showed the opposite pattern of activity. A dissociation was also present in the target-related P300 response as a function of craving and desire to quit, with smokers who did not want to quit processing targets differentially between the states of craving and non-craving. The data suggest that distinct top-down control mechanisms during craving may be implemented by people who wish to quit smoking, as compared to those who do not wish to quit. This pattern of findings establishes this ERP activity as a potential biomarker that may help to differentiate people who want to quit their addiction from those who wish to continue to use their substance of choice.

An electrophysiological dissociation of craving and stimulus-dependent attentional capture in smokers.

It has been suggested that over the course of an addiction, addiction-related stimuli become highly salient in the environment, thereby capturing an addict's attention. To assess these effects neurally in smokers, and how they interact with craving, we recorded electroencephalography (EEG) in two sessions: one in which participants had just smoked (non-craving), and one in which they had abstained from smoking for 3 h (craving). In both sessions, participants performed a visual-search task in which two colored squares were presented to the left and right of fixation, with one color being the target to which they should shift attention and discriminate the locations of two missing corners. Task-irrelevant images, both smoking-related and non-smoking-related, were embedded in both squares, enabling the shift of spatial attention to the target to be examined as a function of the addiction-related image being present or absent in the target, the distractor, or both. Behaviorally, participants were slower to respond to targets containing a smoking-related image. Furthermore, when the target contained a smoking-related image, the neural responses indicated that attention had been shifted less strongly to the target; when the distractor contained a smoking-related image, the shift of attention to the contralateral target was stronger. These effects occurred independently of craving and suggest that participants were actively avoiding the smoking-related images. Together, these results provide an electrophysiological dissociation between addiction-related visual-stimulus processing and the neural activity associated with craving.