Ongoing Slow Fluctuations in V1 Impact on Visual Perception

Segregated Co-activation Patterns in the Emergence of Decision Confidence During Visual Perception

Visual metacognition-the introspection and evaluation of one's own visual perceptual processes-is measured through both decision confidence and "metacognitive efficiency." Metacognitive efficiency refers to an individual's ability to accurately judge incorrect and correct decisions through confidence ratings given their task performance. Previous imaging studies in humans and nonhuman primates reported widely distributed brain regions being involved in decision confidence and metacognition. However, the neural correlates of metacognition are remarkably inconsistent across studies concerning spatial outline. Therefore, this study investigates the neural correlates of visual metacognition by examining co-activation across regions that scale with visual decision confidence. We hypothesized that interacting processes of perceptual and metacognitive performance contribute to the arising decision confidence in distributed, but segregable co-activating brain regions. To test this hypothesis, we performed task-fMRI in healthy humans during a visual backward masking task with four-scale, post-decision confidence ratings. We measured blood oxygenation covariation patterns, which served as a physiological proxy for co-activation across brain regions. Decision confidence ratings and an individual's metacognitive efficiency served as behavioral measures for metacognition. We found three distinct co-activation clusters involved in decision confidence: the first included right-centered fronto-temporal-parietal regions, the second included left temporal and parietal regions, and the left basal forebrain (BF), and the third included cerebellar regions. The right fronto-temporal-parietal cluster including the supplementary eye field and the right basal forebrain showed stronger co-activation in subjects with higher metacognitive efficiency. Our results provide novel evidence for co-activation of widely distributed fronto-parieto-temporal regions involved in visual confidence. The supplementary eye field was the only region that activated for both decision confidence and metacognitive efficiency, suggesting the supplementary eye field plays a key role in visual metacognition. Our results link findings in electrophysiology studies and human fMRI studies and provide evidence that confidence estimates arise from the integration of multiple information processing pathways.

The temporal evolution of pre-stimulus slow cortical potentials is associated with an upcoming stimulus' access to visual consciousness

Slow cortical potentials (SCPs) have been proposed to be essential for the formation of conscious experience. To examine their temporal characteristics, we recorded electroencephalography during a visual backward-masking task, which required participants to localize the missing part of a target stimulus. A subsequent confidence rating was used as a proxy for the target's access to consciousness. Event-related potentials (ERPs) of all correct trials were determined relative to a brief period immediately before the target and then compared among consciousness levels. In an interval ranging from 2 s prior to target presentation up to this period, a negative relationship between slowly fluctuating ERP values and the level of consciousness became evident. After target presentation, high conscious awareness was characterized by an enhanced visual awareness negativity, an increased P3 component, and associated positive SCPs. Together, these findings add new evidence to the proposed role of SCPs in the emergence of visual consciousness.

Slow Endogenous Fluctuations in Cortical fMRI Signals Correlate with Reduced Performance in a Visual Detection Task and Are Suppressed by Spatial Attention

Spatial attention improves performance on visual tasks, increases neural responses to attended stimuli, and reduces correlated noise in visual cortical neurons. In addition to being visually responsive, many retinotopic visual cortical areas exhibit very slow (<0.1 Hz) endogenous fluctuations in functional magnetic resonance imaging signals. To test whether these fluctuations degrade stimulus representations, thereby impairing visual detection, we recorded functional magnetic resonance imaging responses while human participants performed a target detection task that required them to allocate spatial attention to either a rotating wedge stimulus or a central fixation point. We then measured the effects of spatial attention on response amplitude at the frequency of wedge rotation and on the amplitude of endogenous fluctuations at nonstimulus frequencies. We found that, in addition to enhancing stimulus-evoked responses, attending to the wedge also suppressed slow endogenous fluctuations that were unrelated to the visual stimulus in topographically defined areas in early visual cortex, posterior parietal cortex, and lateral occipital cortex, but not in a nonvisual cortical control region. Moreover, attentional enhancement of response amplitude and suppression of endogenous fluctuations were dissociable across cortical areas and across time. Finally, we found that the amplitude of the stimulus-evoked response was not correlated with a perceptual measure of visual target detection. Instead, perceptual performance was accounted for by the amount of suppression of slow endogenous fluctuations. Our results indicate that the amplitude of slow fluctuations of cortical activity is influenced by spatial attention and suggest that these endogenous fluctuations may impair perceptual processing in topographically organized visual cortical areas.

Spontaneous activity forms a foundation for odor-evoked activation maps in the rat olfactory bulb

Fluctuations in spontaneous activity have been observed by many neuroimaging techniques, but because these resting-state changes are not evoked by stimuli, it is difficult to determine how they relate to task-evoked activations. We conducted multi-modal neuroimaging scans of the rat olfactory bulb, both with and without odor, to examine interaction between spontaneous and evoked activities. Independent component analysis of spontaneous fluctuations revealed resting-state networks, and odor-evoked changes revealed activation maps. We constructed simulated activation maps using resting-state networks that were highly correlated to evoked activation maps. Simulated activation maps derived by intrinsic optical signal (IOS), which covers the dorsal portion of the glomerular sheet, significantly differentiated one odor's evoked activation map from the other two. To test the hypothesis that spontaneous activity of the entire glomerular sheet is relevant for representing odor-evoked activations, we used functional magnetic resonance imaging (fMRI) to map the entire glomerular sheet. In contrast to the IOS results, the fMRI-derived simulated activation maps significantly differentiated all three odors' evoked activation maps. Importantly, no evoked activation maps could be significantly differentiated using simulated activation maps produced using phase-randomized resting-state networks. Given that some highly organized resting-state networks did not correlate with any odors' evoked activation maps, we posit that these resting-state networks may characterize evoked activation maps associated with odors not studied. These results emphasize that fluctuations in spontaneous activity form a foundation for active processing, signifying the relevance of resting-state mapping to functional neuroimaging.

Neural and metabolic basis of dynamic resting state fMRI

Resting state fMRI (rsfMRI) as a technique showed much initial promise for use in psychiatric and neurological diseases where diagnosis and treatment were difficult. To realize this promise, many groups have moved towards examining "dynamic rsfMRI," which relies on the assumption that rsfMRI measurements on short time scales remain relevant to the underlying neural and metabolic activity. Many dynamic rsfMRI studies have demonstrated differences between clinical or behavioral groups beyond what static rsfMRI measured, suggesting a neurometabolic basis. Correlative studies combining dynamic rsfMRI and other physiological measurements have supported this. However, they also indicate multiple mechanisms and, if using correlation alone, it is difficult to separate cause and effect. Hypothesis-driven studies are needed, a few of which have begun to illuminate the underlying neurometabolic mechanisms that shape observed differences in dynamic rsfMRI. While the number of potential noise sources, potential actual neurometabolic sources, and methodological considerations can seem overwhelming, dynamic rsfMRI provides a rich opportunity in systems neuroscience. Even an incrementally better understanding of the neurometabolic basis of dynamic rsfMRI would expand rsfMRI's research and clinical utility, and the studies described herein take the first steps on that path forward.