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"Visual Perception physiology."
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Coupling of functional connectivity and regional cerebral blood flow reveals a physiological basis for network hubs of the human brain
Human brain functional networks contain a few densely connected hubs that play a vital role in transferring information across regions during resting and task states. However, the relationship of these functional hubs to measures of brain physiology, such as regional cerebral blood flow (rCBF), remains incompletely understood. Here, we used functional MRI data of blood-oxygenation-level–dependent and arterial-spin–labeling perfusion contrasts to investigate the relationship between functional connectivity strength (FCS) and rCBF during resting and an N -back working-memory task. During resting state, functional brain hubs with higher FCS were identified, primarily in the default-mode, insula, and visual regions. The FCS showed a striking spatial correlation with rCBF, and the correlation was stronger in the default-mode network (DMN; including medial frontal-parietal cortices) and executive control network (ECN; including lateral frontal-parietal cortices) compared with visual and sensorimotor networks. Moreover, the relationship was connection–distance dependent; i.e., rCBF correlated stronger with long-range hubs than short-range ones. It is notable that several DMN and ECN regions exhibited higher rCBF per unit connectivity strength (rCBF/FCS ratio); whereas, this index was lower in posterior visual areas. During the working-memory experiment, both FCS–rCBF coupling and rCBF/FCS ratio were modulated by task load in the ECN and/or DMN regions. Finally, task-induced changes of FCS and rCBF in the lateral-parietal lobe positively correlated with behavioral performance. Together, our results indicate a tight coupling between blood supply and brain functional topology during rest and its modulation in response to task demands, which may shed light on the physiological basis of human brain functional connectome.
Journal Article
A neural basis of probabilistic computation in visual cortex
Bayesian models of behavior suggest that organisms represent uncertainty associated with sensory variables. However, the neural code of uncertainty remains elusive. A central hypothesis is that uncertainty is encoded in the population activity of cortical neurons in the form of likelihood functions. We tested this hypothesis by simultaneously recording population activity from primate visual cortex during a visual categorization task in which trial-to-trial uncertainty about stimulus orientation was relevant for the decision. We decoded the likelihood function from the trial-to-trial population activity and found that it predicted decisions better than a point estimate of orientation. This remained true when we conditioned on the true orientation, suggesting that internal fluctuations in neural activity drive behaviorally meaningful variations in the likelihood function. Our results establish the role of population-encoded likelihood functions in mediating behavior and provide a neural underpinning for Bayesian models of perception.
Journal Article
Distinct roles of forward and backward alpha-band waves in spatial visual attention
Previous research has associated alpha-band [8–12 Hz] oscillations with inhibitory functions: for instance, several studies showed that visual attention increases alpha-band power in the hemisphere ipsilateral to the attended location. However, other studies demonstrated that alpha oscillations positively correlate with visual perception, hinting at different processes underlying their dynamics. Here, using an approach based on traveling waves, we demonstrate that there are two functionally distinct alpha-band oscillations propagating in different directions. We analyzed EEG recordings from three datasets of human participants performing a covert visual attention task (one new dataset with N = 16, two previously published datasets with N = 16 and N = 31). Participants were instructed to detect a brief target by covertly attending to the screen’s left or right side. Our analysis reveals two distinct processes: allocating attention to one hemifield increases top-down alpha-band waves propagating from frontal to occipital regions ipsilateral to the attended location, both with and without visual stimulation. These top-down oscillatory waves correlate positively with alpha-band power in frontal and occipital regions. Yet, different alpha-band waves propagate from occipital to frontal regions and contralateral to the attended location. Crucially, these forward waves were present only during visual stimulation, suggesting a separate mechanism related to visual processing. Together, these results reveal two distinct processes reflected by different propagation directions, demonstrating the importance of considering oscillations as traveling waves when characterizing their functional role.
Journal Article
Variability in encoding precision accounts for visual short-term memory limitations
It is commonly believed that visual short-term memory (VSTM) consists of a fixed number of \"slots\" in which items can be stored. An alternative theory in which memory resource is a continuous quantity distributed over all items seems to be refuted by the appearance of guessing in human responses. Here, we introduce a model in which resource is not only continuous but also variable across items and trials, causing random fluctuations in encoding precision. We tested this model against previous models using two VSTM paradigms and two feature dimensions. Our model accurately accounts for all aspects of the data, including apparent guessing, and outperforms slot models in formal model comparison. At the neural level, variability in precision might correspond to variability in neural population gain and doubly stochastic stimulus representation. Our results suggest that VSTM resource is continuous and variable rather than discrete and fixed and might explain why subjective experience of VSTM is not all or none.
Journal Article
The Argus II epiretinal prosthesis system allows letter and word reading and long-term function in patients with profound vision loss
Background Retinal prosthesis systems (RPS) are a novel treatment for profound vision loss in outer retinal dystrophies. Ideal prostheses would offer stable, long-term retinal stimulation and reproducible spatial resolution in a portable form appropriate for daily life. Methods We report a prospective, internally controlled, multicentre trial of the Argus II system. Twenty-eight subjects with light perception vision received a retinal implant. Controlled, closed-group, forced-choice letter identification, and, open-choice two-, three- and four-letter word identification tests were carried out. Results The mean±SD percentage correct letter identification for 21 subjects tested were: letters L, T, E, J, F, H, I, U, 72.3±24.6% system on and 17.7±12.9% system off; letters A, Z, Q, V, N, W, O, C, D, M, 55.0±27.4% system on and 11.8%±10.7% system off, and letters K, R, G, X, B, Y, S, P, 51.7±28.9% system on and 15.3±7.4% system off. (p<0.001 for all groups). A subgroup of six subjects was able to consistently read letters of reduced size, the smallest measuring 0.9 cm (1.7°) at 30 cm, and four subjects correctly identify unrehearsed two-, three- and four-letter words. Average implant duration was 19.9 months. Conclusions Multiple blind subjects fitted with the Argus II system consistently identified letters and words using the device, indicating reproducible spatial resolution. This, in combination with stable, long-term function, represents significant progress in the evolution of artificial sight.
Journal Article
Simple line drawings suffice for functional MRI decoding of natural scene categories
Humans are remarkably efficient at categorizing natural scenes. In fact, scene categories can be decoded from functional MRI (fMRI) data throughout the ventral visual cortex, including the primary visual cortex, the parahippocampal place area (PPA), and the retrosplenial cortex (RSC). Here we ask whether, and where, we can still decode scene category if we reduce the scenes to mere lines. We collected fMRI data while participants viewed photographs and line drawings of beaches, city streets, forests, highways, mountains, and offices. Despite the marked difference in scene statistics, we were able to decode scene category from fMRI data for line drawings just as well as from activity for color photographs, in primary visual cortex through PPA and RSC. Even more remarkably, in PPA and RSC, error patterns for decoding from line drawings were very similar to those from color photographs. These data suggest that, in these regions, the information used to distinguish scene category is similar for line drawings and photographs. To determine the relative contributions of local and global structure to the human ability to categorize scenes, we selectively removed long or short contours from the line drawings. In a category-matching task, participants performed significantly worse when long contours were removed than when short contours were removed. We conclude that global scene structure, which is preserved in line drawings, plays an integral part in representing scene categories.
Journal Article