Population coding for figure-ground texture segregation in macaque V1 and V4.

Object recognition often involves the brain segregating objects from their surroundings. Neurophysiological studies of figure-ground texture segregation have yielded inconsistent results, particularly on whether V1 neurons can perform figure-ground texture segregation or just detect texture borders. To address this issue from a population perspective, we utilized two-photon calcium imaging to simultaneously record the responses of large samples of V1 and V4 neurons to figure-ground texture stimuli in awake, fixating macaques. The average response changes indicate that V1 neurons mainly detect texture borders, while V4 neurons are involved in figure-ground segregation. However, population analysis (SVM decoding of PCA-transformed neuronal responses) reveal that V1 neurons not only detect figure-ground borders, but also contribute to figure-ground texture segregation, although requiring substantially more principal components than V4 neurons to reach a 75 % decoding accuracy. Individually, V1/V4 neurons showing larger (negative/positive) figure-ground response differences contribute more to figure-ground segregation. But for V1 neurons, the contribution becomes significant only when many principal components are considered. We conclude that V1 neurons participate in figure-ground segregation primarily by defining the figure borders, and the poorly structured figure-ground information V1 neurons carry could be further utilized by V4 neurons to accomplish figure-ground segregation.

Ocular dominance-dependent binocular combination of monocular neuronal responses in macaque V1.

Primates rely on two eyes to perceive depth, while maintaining stable vision when either one eye or both eyes are open. Although psychophysical and modeling studies have investigated how monocular signals are combined to form binocular vision, the underlying neuronal mechanisms, particularly in V1 where most neurons exhibit binocularity with varying eye preferences, remain poorly understood. Here, we used two-photon calcium imaging to compare the monocular and binocular responses of thousands of simultaneously recorded V1 superficial-layer neurons in three awake macaques. During monocular stimulation, neurons preferring the stimulated eye exhibited significantly stronger responses compared to those preferring both eyes. However, during binocular stimulation, the responses of neurons preferring either eye were suppressed on the average, while those preferring both eyes were enhanced, resulting in similar neuronal responses irrespective of their eye preferences, and an overall response level similar to that with monocular viewing. A neuronally realistic model of binocular combination, which incorporates ocular dominance-dependent divisive interocular inhibition and binocular summation, is proposed to account for these findings.

Perceptual learning of motion direction discrimination: Location specificity and the uncertain roles of dorsal and ventral areas.

One interesting observation of perceptual learning is the asymmetric transfer between stimuli at different external noise levels: learning at zero/low noise can transfer significantly to the same stimulus at high noise, but not vice versa. The mechanisms underlying this asymmetric transfer have been investigated by psychophysical, neurophysiological, brain imaging, and computational modeling studies. One study (PNAS 113 (2016) 5724-5729) reported that rTMS stimulations of dorsal and ventral areas impair motion direction discrimination of moving dot stimuli at 40% coherent ("noisy") and 100% coherent (zero-noise) levels, respectively. However, after direction training at 100% coherence, only rTMS stimulation of the ventral cortex is effective, disturbing direction discrimination at both coherence levels. These results were interpreted as learning-induced changes of functional specializations of visual areas. We have concerns with the behavioral data of this study. First, contrary to the report of highly location-specific motion direction learning, our replicating experiment showed substantial learning transfer (e.g., transfer/learning ratio = 81.9%. vs 14.8% at 100% coherence). Second and more importantly, we found complete transfer of direction learning from 40% to 100% coherence, a critical baseline that is missing in this study. The transfer effect suggests that similar brain mechanisms underlie motion direction processing at two coherence levels. Therefore, this study's conclusions regarding the roles of dorsal and ventral areas in motion direction processing at two coherence levels, as well as the effects of perceptual learning, are not supported by proper experimental evidence. It remains unexplained why distinct impacts of dorsal and ventral rTMS stimulations on motion direction discrimination were observed.