Neural representations of competing stimuli along the dorsal and ventral visual pathways during binocular rivalry.

Binocular rivalry arises when two discrepant stimuli are simultaneously presented to different eyes, during which observers consciously experience vivid perceptual alternations without physical changes in visual inputs. Neural dynamics tracking such perceptual alternations have been identified at both early and late visual areas, leading to the fundamental debate concerning the primary neural substrate underlying binocular rivalry. One promising hypothesis that might reconcile these seemingly paradoxical findings is a gradual shift from interocular competition between monocular neurons to pattern competition among binocular neurons. Here, we examined this hypothesis by investigating how neural representations of rivalrous stimuli evolved along the visual pathway. We found that representations of the dominant and the suppressed stimuli initially co-existed in V1, which were enhanced and attenuated respectively in extrastriate visual areas. Notably, neural activity in V4 was dictated by the representation of the dominant stimulus, while the representation of the suppressed stimulus was only partially inhibited in dorsal areas V3A and MT+. Our findings revealed a progressive transition from the co-existing representations of the rivalrous inputs to the dictatorial representation of the dominant stimulus in the ventral pathway, and advocated different cortical evolutionary patterns of visual representations between the dorsal and the ventral pathways.

Neural mechanisms of motion perceptual learning in noise.

Practice improves our perceptual ability. However, the neural mechanisms underlying this experience-dependent plasticity in adult brain remain unclear. Here, we studied the long-term neural correlates of motion perceptual learning. Subjects' behavioral performance and BOLD signals were tracked before, immediately after, and 2 weeks after practicing a motion direction discrimination task in noise over six daily sessions. Parallel to the specificity and persistency of the behavioral learning effect, we found that training sharpened the cortical tuning in MT, and enhanced the connectivity strength from MT to the intraparietal sulcus (IPS, a motion decision-making area). In addition, the decoding accuracy for the trained motion direction was improved in IPS 2 weeks after training. The dual changes in the sensory and the high-level cortical areas suggest that learning refines the neural representation of the trained stimulus and facilitates the information transmission in the decision process. Our findings are consistent with the functional specialization in the visual cortex, and provide empirical evidence to the reweighting theory of perceptual learning at a large spatial scale. Hum Brain Mapp 38:6029-6042, 2017. © 2017 Wiley Periodicals, Inc.

Local field potentials, spiking activity, and receptive fields in human visual cortex.

The concept of receptive field (RF) is central to sensory neuroscience. Neuronal RF properties have been substantially studied in animals, while those in humans remain nearly unexplored. Here, we measured neuronal RFs with intracranial local field potentials (LFPs) and spiking activity in human visual cortex (V1/V2/V3). We recorded LFPs via macro-contacts and discovered that RF sizes estimated from low-frequency activity (LFA, 0.5-30 Hz) were larger than those estimated from low-gamma activity (LGA, 30-60 Hz) and high-gamma activity (HGA, 60-150 Hz). We then took a rare opportunity to record LFPs and spiking activity via microwires in V1 simultaneously. We found that RF sizes and temporal profiles measured from LGA and HGA closely matched those from spiking activity. In sum, this study reveals that spiking activity of neurons in human visual cortex could be well approximated by LGA and HGA in RF estimation and temporal profile measurement, implying the pivotal functions of LGA and HGA in early visual information processing.

Attention impedes neural representation of interpolated orientation during perceptual completion.

One of the most remarkable functional feats accomplished by visual system is the interpolation of missing retinal inputs based on surrounding information, a process known as perceptual completion. Perceptual completion enables the active construction of coherent, vivid percepts from spatially discontinuous visual information that is prevalent in real-life visual scenes. Despite mounting evidence linking sensory activity enhancement and perceptual completion, surprisingly little is known about whether and how attention, a fundamental modulator of sensory activities, affects perceptual completion. Using EEG-based time-resolved inverted encoding model (IEM), we reconstructed the moment-to-moment representation of the illusory grating that resulted from spatially interpolating the orientation of surrounding inducers. We found that, despite manipulation of observers' attentional focus, the illusory grating representation unfolded in time in a similar manner. Critically, attention to the surrounding inducers simultaneously attenuated the illusory grating representation and delayed its temporal development. Our findings disclosed, for the first time, the suppressive role of selective attention in perceptual completion and were suggestive of a fast, automatic neural machinery that implements the interpolation of missing visual information.

Cue-triggered activity replay in human early visual cortex.

The recall of learned temporal sequences by a visual cue is an important form of experience-based neural plasticity. Here we observed such reactivation in awake human visual cortex using intracranial recording. After repeated exposure to a moving dot, a flash of the dot was able to trigger neural reactivation in the downstream receptive field along the motion path. This effect was observed only when the cue appeared near the receptive field. The estimated traveling speed was faster compared to the activation induced by the real motion. We suggest a range-limited, time-compressed reactivation as a result of repeated visual exposure in awake human visual cortex.

Competing rhythmic neural representations of orientations during concurrent attention to multiple orientation features.

When a feature is attended, all locations containing this feature are enhanced throughout the visual field. However, how the brain concurrently attends to multiple features remains unknown and cannot be easily deduced from classical attention theories. Here, we recorded human magnetoencephalography signals when subjects concurrently attended to two spatially overlapping orientations. A time-resolved multivariate inverted encoding model was employed to track the ongoing temporal courses of the neural representations of the attended orientations. We show that the two orientation representations alternate with each other and undergo a theta-band (~4 Hz) rhythmic fluctuation over time. Similar temporal profiles are also revealed in the orientation discrimination performance. Computational modeling suggests a tuning competition process between the two neuronal populations that are selectively tuned to one of the attended orientations. Taken together, our findings reveal for the first time a rhythm-based, time-multiplexing neural machinery underlying concurrent multi-feature attention.

Detection of driver drowsiness using wearable devices: A feasibility study of the proximity sensor.

BACKGROUND: Drowsiness is one of the major factors that cause crashes in the transportation industry. Drowsiness detection systems can alert drowsy operators and potentially reduce the risk of crashes. In this study, a Google-Glass-based drowsiness detection system was developed and validated. METHODS: The proximity sensor of Google Glass was used to monitor eye blink frequency. A simulated driving study was carried out to validate the system. Driving performance and eye blinks were compared between the two states of alertness and drowsiness while driving. RESULTS: Drowsy drivers increased frequency of eye blinks, produced longer braking response time and increased lane deviation, compared to when they were alert. A threshold algorithm for proximity sensor can reliably detect eye blinks and proved the feasibility of using Google Glass to detect operator drowsiness. APPLICATIONS: This technology provides a new platform to detect operator drowsiness and has the potential to reduce drowsiness-related crashes in driving and aviation.