A practical evaluation of measures derived from compressed sensing diffusion spectrum imaging.

Diffusion Spectrum Imaging (DSI) using dense Cartesian sampling of q-space has been shown to provide important advantages for modeling complex white matter architecture. However, its adoption has been limited by the lengthy acquisition time required. Sparser sampling of q-space combined with compressed sensing (CS) reconstruction techniques has been proposed as a way to reduce the scan time of DSI acquisitions. However prior studies have mainly evaluated CS-DSI in post-mortem or non-human data. At present, the capacity for CS-DSI to provide accurate and reliable measures of white matter anatomy and microstructure in the living human brain remains unclear. We evaluated the accuracy and inter-scan reliability of 6 different CS-DSI schemes that provided up to 80% reductions in scan time compared to a full DSI scheme. We capitalized on a dataset of 26 participants who were scanned over eight independent sessions using a full DSI scheme. From this full DSI scheme, we subsampled images to create a range of CS-DSI images. This allowed us to compare the accuracy and inter-scan reliability of derived measures of white matter structure (bundle segmentation, voxel-wise scalar maps) produced by the CS-DSI and the full DSI schemes. We found that CS-DSI estimates of both bundle segmentations and voxel-wise scalars were nearly as accurate and reliable as those generated by the full DSI scheme. Moreover, we found that the accuracy and reliability of CS-DSI was higher in white matter bundles that were more reliably segmented by the full DSI scheme. As a final step, we replicated the accuracy of CS-DSI in a prospectively acquired dataset (n = 20, scanned once). Together, these results illustrate the utility of CS-DSI for reliably delineating in vivo white matter architecture in a fraction of the scan time, underscoring its promise for both clinical and research applications.

QSIPrep: an integrative platform for preprocessing and reconstructing diffusion MRI data.

Diffusion-weighted magnetic resonance imaging (dMRI) is the primary method for noninvasively studying the organization of white matter in the human brain. Here we introduce QSIPrep, an integrative software platform for the processing of diffusion images that is compatible with nearly all dMRI sampling schemes. Drawing on a diverse set of software suites to capitalize on their complementary strengths, QSIPrep facilitates the implementation of best practices for processing of diffusion images.

Eye movements disrupt EEG alpha-band coding of behaviorally relevant and irrelevant spatial locations held in working memory.

Oscillations in the alpha frequency band (∼8-12 Hz) of the human electroencephalogram play an important role in supporting selective attention to visual items and maintaining their spatial locations in working memory (WM). Recent findings suggest that spatial information maintained in alpha is modulated by interruptions to continuous visual input, such that attention shifts, eye closure, and backward masking of the encoded item cause reconstructed representations of remembered locations to become degraded. Here, we investigated how another common visual disruption-eye movements-modulates reconstructions of behaviorally relevant and irrelevant item locations held in WM. Participants completed a delayed estimation task, where they encoded and recalled either the location or color of an object after a brief retention period. During retention, participants either fixated at the center or executed a sequence of eye movements. Electroencephalography (EEG) was recorded at the scalp and eye position was monitored with an eye tracker. Inverted encoding modeling (IEM) was applied to reconstruct location-selective responses across multiple frequency bands during encoding and retention. Location-selective responses were successfully reconstructed from alpha activity during retention where participants fixated at the center, but these reconstructions were disrupted during eye movements. Recall performance decreased during eye-movements conditions but remained largely intact, and further analyses revealed that under specific task conditions, it was possible to reconstruct retained location information from lower frequency bands (1-4 Hz) during eye movements. These results suggest that eye movements disrupt maintained spatial information in alpha in a manner consistent with other acute interruptions to continuous visual input, but this information may be represented in other frequency bands.NEW & NOTEWORTHY Neural oscillations in the alpha frequency band support selective attention to visual items and maintenance of their spatial locations in human working memory. Here, we investigate how eye movements disrupt representations of item locations held in working memory. Although it was not possible to recover item locations from alpha during eye movements, retained location information could be recovered from select lower frequency bands. This suggests that during eye movements, stored spatial information may be represented in other frequencies.

Tracking the Contents of Spatial Working Memory during an Acute Bout of Aerobic Exercise.

Recent studies have reported enhanced visual responses during acute bouts of physical exercise, suggesting that sensory systems may become more sensitive during active exploration of the environment. This raises the possibility that exercise may also modulate brain activity associated with other cognitive functions, like visual working memory, that rely on patterns of activity that persist beyond the initial sensory evoked response. Here, we investigated whether the neural coding of an object location held in memory is modulated by an acute bout of aerobic exercise. Participants performed a spatial change detection task while seated on a stationary bike at rest and during low-intensity cycling (∼50 watts/50 RPM). Brain activity was measured with EEG. An inverted encoding modeling technique was employed to estimate location-selective channel response functions from topographical patterns of alpha-band (8-12 Hz) activity. There was strong evidence of robust spatially selective responses during stimulus presentation and retention periods both at rest and during exercise. During retention, the spatial selectivity of these responses decreased in the exercise condition relative to rest. A temporal generalization analysis indicated that models trained on one time period could be used to reconstruct the remembered locations at other time periods, however, generalization was degraded during exercise. Together, these results demonstrate that it is possible to reconstruct the contents of working memory at rest and during exercise, but that exercise can result in degraded responses, which contrasts with the enhancements observed in early sensory processing.

EEG signatures of contextual influences on visual search with real scenes.

The use of scene context is a powerful way by which biological organisms guide and facilitate visual search. Although many studies have shown enhancements of target-related electroencephalographic activity (EEG) with synthetic cues, there have been fewer studies demonstrating such enhancements during search with scene context and objects in real world scenes. Here, observers covertly searched for a target in images of real scenes while we used EEG to measure the steady state visual evoked response to objects flickering at different frequencies. The target appeared in its typical contextual location or out of context while we controlled for low-level properties of the image including target saliency against the background and retinal eccentricity. A pattern classifier using EEG activity at the relevant modulated frequencies showed target detection accuracy increased when the target was in a contextually appropriate location. A control condition for which observers searched the same images for a different target orthogonal to the contextual manipulation, resulted in no effects of scene context on classifier performance, confirming that image properties cannot explain the contextual modulations of neural activity. Pattern classifier decisions for individual images were also related to the aggregated observer behavioral decisions for individual images. Together, these findings demonstrate target-related neural responses are modulated by scene context during visual search with real world scenes and can be related to behavioral search decisions.

Dual Process Coding of Recalled Locations in Human Oscillatory Brain Activity.

A mental representation of the location of an object can be constructed using sensory information selected from the environment and information stored internally. Human electrophysiological evidence indicates that behaviorally relevant locations, regardless of the source of sensory information, are represented in alpha-band oscillations suggesting a shared process. Here, we present evidence from human subjects of either sex for two distinct alpha-band-based processes that separately support the representation of location, exploiting sensory evidence sampled either externally or internally.SIGNIFICANCE STATEMENT Our sensory environment and our internal trains of thought are coded in patterns of brain activity and are used to guide coherent behavior. Oscillations in the alpha-frequency band are a predominant feature of human brain activity. This oscillation plays a central role in both selective attention and working memory, suggesting that these important cognitive functions are mediated by a unitary mechanism. We show that the alpha oscillation reflects two distinct processes, one that is supported by continuous sampling of the external sensory environment, and one that is based on sampling from internal representations coded in visual short-term memory. This represents a significant change in our understanding of the nature of alpha oscillations and their relationship to attention and memory.

Acute Exercise Modulates Feature-selective Responses in Human Cortex.

An organism's current behavioral state influences ongoing brain activity. Nonhuman mammalian and invertebrate brains exhibit large increases in the gain of feature-selective neural responses in sensory cortex during locomotion, suggesting that the visual system becomes more sensitive when actively exploring the environment. This raises the possibility that human vision is also more sensitive during active movement. To investigate this possibility, we used an inverted encoding model technique to estimate feature-selective neural response profiles from EEG data acquired from participants performing an orientation discrimination task. Participants (n = 18) fixated at the center of a flickering (15 Hz) circular grating presented at one of nine different orientations and monitored for a brief shift in orientation that occurred on every trial. Participants completed the task while seated on a stationary exercise bike at rest and during low- and high-intensity cycling. We found evidence for inverted-U effects; such that the peak of the reconstructed feature-selective tuning profiles was highest during low-intensity exercise compared with those estimated during rest and high-intensity exercise. When modeled, these effects were driven by changes in the gain of the tuning curve and in the profile bandwidth during low-intensity exercise relative to rest. Thus, despite profound differences in visual pathways across species, these data show that sensitivity in human visual cortex is also enhanced during locomotive behavior. Our results reveal the nature of exercise-induced gain on feature-selective coding in human sensory cortex and provide valuable evidence linking the neural mechanisms of behavior state across species.

Consciousness isn't all-or-none: Evidence for partial awareness during the attentional blink.

Alternative views of the nature of consciousness posit that awareness of an object is either an all-or-none phenomenon or that awareness can be partial, occurring independently for different levels of representation. The all-or-none hypothesis predicts that when one feature of an object is identified, all other features should be consciously accessible. The partial awareness hypothesis predicts that one feature may reach consciousness while others do not. These competing predictions were tested in two experiments that presented two targets within a central stream of letters. We used the attentional blink evoked by the first target to assess consciousness for two different features of the second target. The results provide evidence that there can be a severe impairment in conscious access to one feature even when another feature is accurately reported. This behavioral evidence supports the partial awareness hypothesis, showing that consciousness of different features of the same object can be dissociated.

Neural representations of contextual guidance in visual search of real-world scenes.

Exploiting scene context and object-object co-occurrence is critical in guiding eye movements and facilitating visual search, yet the mediating neural mechanisms are unknown. We used functional magnetic resonance imaging while observers searched for target objects in scenes and used multivariate pattern analyses (MVPA) to show that the lateral occipital complex (LOC) can predict the coarse spatial location of observers' expectations about the likely location of 213 different targets absent from the scenes. In addition, we found weaker but significant representations of context location in an area related to the orienting of attention (intraparietal sulcus, IPS) as well as a region related to scene processing (retrosplenial cortex, RSC). Importantly, the degree of agreement among 100 independent raters about the likely location to contain a target object in a scene correlated with LOC's ability to predict the contextual location while weaker but significant effects were found in IPS, RSC, the human motion area, and early visual areas (V1, V3v). When contextual information was made irrelevant to observers' behavioral task, the MVPA analysis of LOC and the other areas' activity ceased to predict the location of context. Thus, our findings suggest that the likely locations of targets in scenes are represented in various visual areas with LOC playing a key role in contextual guidance during visual search of objects in real scenes.

Isolating the neural mechanisms of interference during continuous multisensory dual-task performance.

The need to engage in multiple tasks simultaneously is often encountered in everyday experience, but coordinating between two or more tasks can lead to impaired performance. Typical investigations of multitasking impairments have focused on the performance of two tasks presented in close temporal proximity on discrete trials; however, such paradigms do not match well with the continuous performance situations more typically encountered outside the laboratory. As a result, the stages of information processing that are affected during multisensory continuous dual tasks and how these changes in processing relate to behavior remain unclear. To address these issues, participants were presented simultaneous rapid visual and auditory stimulus sequences under three conditions: attend visual only, attend auditory only, and dual attention (attend both visual and auditory). Performance, measured in terms of response time and perceptual sensitivity (d'), revealed dual-task impairments only in the auditory task. Neural activity, measured by the ERP technique, revealed that both early stage sensory processing and later cognitive processing of the auditory task were affected by dual-task performance, but similar stages of processing of the visual task were not. Critically, individual differences in neural activity at both early and late stages of information processing accurately rank-ordered individuals based on the observed difference in behavioral performance between the single and dual attention conditions. These results reveal relationships between behavioral performance and the neural correlates of both early and late stage information processing that provide key insights into the complex interplay between the brain and behavior when multiple tasks are performed continuously.

Stress affects navigation strategies in immersive virtual reality.

There are known individual differences in both the ability to learn the layout of novel environments and the flexibility of strategies for navigating known environments. However, it is unclear how navigational abilities are impacted by high-stress scenarios. Here we used immersive virtual reality (VR) to develop a novel behavioral paradigm to examine navigation under dynamically changing situations. We recruited 48 participants (24 female; ages 17-32) to navigate a virtual maze (7.5 m × 7.5 m). Participants learned the maze by moving along a fixed path past the maze's landmarks (paintings). Subsequently, participants experienced either a non-stress condition, or a high-stress condition tasking them with navigating the maze. In the high-stress condition, their initial path was blocked, the environment was darkened, threatening music was played, fog obstructed more distal views of the environment, and participants were given a time limit of 20 s with a countdown timer displayed at the top of their screen. On trials where the path was blocked, we found self-reported stress levels and distance traveled increased while trial completion rate decreased (as compared to non-stressed control trials). On unblocked stress trials, participants were less likely to take a shortcut and consequently navigated less efficiently compared to control trials. Participants with more trait spatial anxiety reported more stress and navigated less efficiently. Overall, our results suggest that navigational abilities change considerably under high-stress conditions.

Feature-independent neural coding of target detection during search of natural scenes.

Visual search requires humans to detect a great variety of target objects in scenes cluttered by other objects or the natural environment. It is unknown whether there is a general purpose neural detection mechanism in the brain that codes the presence of a wide variety of categories of objects embedded in natural scenes. We provide evidence for a feature-independent coding mechanism for detecting behaviorally relevant targets in natural scenes in the dorsal frontoparietal network. Pattern classifiers using single-trial fMRI responses in the dorsal frontoparietal network reliably predicted the presence of 368 different target objects and also the observer's choices. Other vision-related areas such as the primary visual cortex, lateral occipital complex, the parahippocampal, and the fusiform gyri did not predict target presence, while high-level association areas related to general purpose decision making, including the dorsolateral prefrontal cortex and anterior cingulate, did. Activity in the intraparietal sulcus, a main area in the dorsal frontoparietal network, correlated with observers' decision confidence and with the task difficulty of individual images. These results cannot be explained by physical differences across images or eye movements. Thus, the dorsal frontoparietal network detects behaviorally relevant targets in natural scenes independent of their defining visual features and may be the human analog of the priority map in monkey lateral intraparietal cortex.

Learned feature regularities enable suppression of spatially overlapping stimuli.

Contemporary theories of attentional control state that information can be prioritized based on selection history. Even though theories agree that selection history can impact representations of spatial location, which in turn helps guide attention, there remains disagreement on whether nonspatial features (e.g., color) are modulated in a similar way. While previous work has demonstrated color suppression using visual search tasks, it is possible that the location corresponding to the distractor was suppressed, consistent with a spatial mechanism of suppression. Here, we sought to rule out this possibility by testing whether similar suppression of a learned distractor color can occur for spatially overlapping visual stimuli. On a given trial, two spatially superimposed stimuli (line arrays) were tilted either left or right of vertical and presented in one of four distinct colors. Subjects performed a speeded report of the orientation of the "target" array with the most lines. Critically, the distractor array was regularly one color, and this high-probability color was never the color of the target array, which encouraged learned suppression. In two experiments, responses to the target array were fastest when the distractor array was in the high-probability color, suggesting participants suppressed the distractor color. Additionally, when regularities were removed, the high-probability distractor color continued to benefit speeded target identification for individual subjects (E1) but slowed target identification (E2) when presented in the target array. Together, these results indicate that learned suppression of feature-based regularities modulates target detection performance independent of spatial location and persists over time.

Within-subject reproducibility varies in multi-modal, longitudinal brain networks.

Network neuroscience provides important insights into brain function by analyzing complex networks constructed from diffusion Magnetic Resonance Imaging (dMRI), functional MRI (fMRI) and Electro/Magnetoencephalography (E/MEG) data. However, in order to ensure that results are reproducible, we need a better understanding of within- and between-subject variability over long periods of time. Here, we analyze a longitudinal, 8 session, multi-modal (dMRI, and simultaneous EEG-fMRI), and multiple task imaging data set. We first confirm that across all modalities, within-subject reproducibility is higher than between-subject reproducibility. We see high variability in the reproducibility of individual connections, but observe that in EEG-derived networks, during both rest and task, alpha-band connectivity is consistently more reproducible than connectivity in other frequency bands. Structural networks show a higher reliability than functional networks across network statistics, but synchronizability and eigenvector centrality are consistently less reliable than other network measures across all modalities. Finally, we find that structural dMRI networks outperform functional networks in their ability to identify individuals using a fingerprinting analysis. Our results highlight that functional networks likely reflect state-dependent variability not present in structural networks, and that the type of analysis should depend on whether or not one wants to take into account state-dependent fluctuations in connectivity.

Establishing the Validity of Compressed Sensing Diffusion Spectrum Imaging.

Diffusion Spectrum Imaging (DSI) using dense Cartesian sampling of q-space has been shown to provide important advantages for modeling complex white matter architecture. However, its adoption has been limited by the lengthy acquisition time required. Sparser sampling of q-space combined with compressed sensing (CS) reconstruction techniques has been proposed as a way to reduce the scan time of DSI acquisitions. However prior studies have mainly evaluated CS-DSI in post-mortem or non-human data. At present, the capacity for CS-DSI to provide accurate and reliable measures of white matter anatomy and microstructure in the living human brain remains unclear. We evaluated the accuracy and inter-scan reliability of 6 different CS-DSI schemes that provided up to 80% reductions in scan time compared to a full DSI scheme. We capitalized on a dataset of twenty-six participants who were scanned over eight independent sessions using a full DSI scheme. From this full DSI scheme, we subsampled images to create a range of CS-DSI images. This allowed us to compare the accuracy and inter-scan reliability of derived measures of white matter structure (bundle segmentation, voxel-wise scalar maps) produced by the CS-DSI and the full DSI schemes. We found that CS-DSI estimates of both bundle segmentations and voxel-wise scalars were nearly as accurate and reliable as those generated by the full DSI scheme. Moreover, we found that the accuracy and reliability of CS-DSI was higher in white matter bundles that were more reliably segmented by the full DSI scheme. As a final step, we replicated the accuracy of CS-DSI in a prospectively acquired dataset (n=20, scanned once). Together, these results illustrate the utility of CS-DSI for reliably delineating in vivo white matter architecture in a fraction of the scan time, underscoring its promise for both clinical and research applications.

Neural decoding of collective wisdom with multi-brain computing.

Group decisions and even aggregation of multiple opinions lead to greater decision accuracy, a phenomenon known as collective wisdom. Little is known about the neural basis of collective wisdom and whether its benefits arise in late decision stages or in early sensory coding. Here, we use electroencephalography and multi-brain computing with twenty humans making perceptual decisions to show that combining neural activity across brains increases decision accuracy paralleling the improvements shown by aggregating the observers' opinions. Although the largest gains result from an optimal linear combination of neural decision variables across brains, a simpler neural majority decision rule, ubiquitous in human behavior, results in substantial benefits. In contrast, an extreme neural response rule, akin to a group following the most extreme opinion, results in the least improvement with group size. Analyses controlling for number of electrodes and time-points while increasing number of brains demonstrate unique benefits arising from integrating neural activity across different brains. The benefits of multi-brain integration are present in neural activity as early as 200 ms after stimulus presentation in lateral occipital sites and no additional benefits arise in decision related neural activity. Sensory-related neural activity can predict collective choices reached by aggregating individual opinions, voting results, and decision confidence as accurately as neural activity related to decision components. Estimation of the potential for the collective to execute fast decisions by combining information across numerous brains, a strategy prevalent in many animals, shows large time-savings. Together, the findings suggest that for perceptual decisions the neural activity supporting collective wisdom and decisions arises in early sensory stages and that many properties of collective cognition are explainable by the neural coding of information across multiple brains. Finally, our methods highlight the potential of multi-brain computing as a technique to rapidly and in parallel gather increased information about the environment as well as to access collective perceptual/cognitive choices and mental states.

Investigating Search Among Physical and Virtual Objects Under Different Lighting Conditions.

By situating computer-generated content in the physical world, mobile augmented reality (AR) can support many tasks that involve effective search and inspection of physical environments. Currently, there is limited information regarding the viability of using AR in realistic wide-area outdoor environments and how AR experiences affect human behavior in these environments. Here, we conducted a wide-area outdoor AR user study ($n=48$) using a commercially available AR headset (Microsoft Hololens 2) to compare (1) user interactions with physical and virtual objects in the environment (2) the effects of different lighting conditions on user behavior and AR experience and (3) the impact of varying cognitive load on AR task performance. Participants engaged in a treasure hunt task where they searched for and classified virtual target items (green "gems") in an augmented outdoor courtyard scene populated with physical and virtual objects. Cognitive load was manipulated so that in half the search trials users were required to monitor an audio stream and respond to specific target sounds. Walking paths, head orientation and eye gaze information were measured, and users were queried about their memory of encountered objects and provided feedback on the experience. Key findings included (1) Participants self-reported significantly lower comfort in the ambient natural light condition, with virtual objects more visible and participants more likely to walk into physical objects at night; (2) recall for physical objects was worse than for virtual objects, (3) participants discovered more gems hidden behind virtual objects than physical objects, implying higher attention on virtual objects and (4) dual-tasking modified search behavior. These results suggest there are important technical, perceptual and cognitive factors that must be considered if the full potential of "anywhere and anytime mobile AR" is to be realized.

Habituation of the stress response multiplex to repeated cold pressor exposure.

Humans show remarkable habituation to aversive events as reflected by changes of both subjective report and objective measures of stress. Although much experimental human research focuses on the effects of stress, relatively little is known about the cascade of physiological and neural responses that contribute to stress habituation. The cold pressor test (CPT) is a common method for inducing acute stress in human participants in the laboratory; however, there are gaps in our understanding of the global state changes resulting from this stress-induction technique and how these responses change over multiple exposures. Here, we measure the stress response to repeated CPT exposures using an extensive suite of physiologic measures and state-of-the-art analysis techniques. In two separate sessions on different days, participants underwent five 90 s CPT exposures of both feet and five warm water control exposures, while electrocardiography (ECG), impedance cardiography, continuous blood pressure, pupillometry, scalp electroencephalography (EEG), salivary cortisol and self-reported pain assessments were recorded. A diverse array of adaptive responses are reported that vary in their temporal dynamics within each exposure as well as habituation across repeated exposures. During cold-water exposure there was a cascade of changes across several cardiovascular measures (elevated heart rate (HR), cardiac output (CO) and Mean Arterial Pressure (MAP) and reduced left ventricular ejection time (LVET), stroke volume (SV) and high-frequency heart rate variability (HF)). Increased pupil dilation was observed, as was increased power in low-frequency bands (delta and theta) across frontal EEG electrode sites. Several cardiovascular measures also habituated over repeated cold-water exposures (HR, MAP, CO, SV, LVET) as did pupil dilation and alpha frequency activity across the scalp. Anticipation of cold water induced stress effects in the time-period immediately prior to exposure, indexed by increased pupil size and cortical disinhibition in the alpha and beta frequency bands across central scalp sites. These results provide comprehensive insight into the evolution of a diverse array of stress responses to an acute noxious stressor, and how these responses adaptively contribute to stress habituation.

The transverse occipital sulcus and intraparietal sulcus show neural selectivity to object-scene size relationships.

To optimize visual search, humans attend to objects with the expected size of the sought target relative to its surrounding scene (object-scene scale consistency). We investigate how the human brain responds to variations in object-scene scale consistency. We use functional magnetic resonance imaging and a voxel-wise feature encoding model to estimate tuning to different object/scene properties. We find that regions involved in scene processing (transverse occipital sulcus) and spatial attention (intraparietal sulcus) have the strongest responsiveness and selectivity to object-scene scale consistency: reduced activity to mis-scaled objects (either unusually smaller or larger). The findings show how and where the brain incorporates object-scene size relationships in the processing of scenes. The response properties of these brain areas might explain why during visual search humans often miss objects that are salient but at atypical sizes relative to the surrounding scene.

Effects of changes in end-tidal PO2 and PCO2 on neural responses during rest and sustained attention.

Impairments of cognitive function during alterations in arterial blood gases (e.g., high-altitude hypoxia) may result from the disruption of neurovascular coupling; however, the link between changes in arterial blood gases, cognition, and cerebral blood flow (CBF) is poorly understood. To interrogate this link, we developed a multimodal empirical strategy capable of monitoring neural correlates of cognition and CBF simultaneously. Human participants performed a sustained attention task during hypoxia, hypercapnia, hypocapnia, and normoxia while electroencephalographic (EEG) activity and CBF (middle and posterior cerebral arteries; transcranial Doppler ultrasound) were simultaneously measured. The protocol alternated between rest and engaging in a visual target detection task that required participants to monitor a sequence of brief-duration colored circles and detect infrequent, longer duration circles (targets). The target detection task was overlaid on a large, circular checkerboard that provided robust visual stimulation. Spectral decomposition and event-related potential (ERP) analyses were applied to the EEG data to investigate spontaneous and task-specific fluctuations in neural activity. There were three main sets of findings: (1) spontaneous alpha oscillatory activity was modulated as a function of arterial CO2 (hypocapnia and hypercapnia), (2) task-related neurovascular coupling was disrupted by all arterial blood gas manipulations, and (3) changes in task-related alpha and theta band activity and attenuation of the P3 ERP component amplitude were observed during hypocapnia. Since alpha and theta are linked with suppression of visual processing and executive control and P3 amplitude with task difficulty, these data suggest that transient arterial blood gas changes can modulate multiple stages of cognitive information processing.