Tiangang Zhou

Neural Activities in V1 Create a Bottom-Up Saliency Map

The bottom-up contribution to the allocation of exogenous attention is a saliency map, whose neural substrate is hard to identify because of possible contamination by top-down signals. We obviated this possibility using stimuli that observers could not perceive, but that nevertheless, through orientation contrast between foreground and background regions, attracted attention to improve a localized visual discrimination. When orientation contrast increased, so did the degree of attraction, and two physiological measures: the amplitude of the earliest (C1) component of the ERP, which is associated with primary visual cortex, and fMRI BOLD signals in areas V1-V4 (but not the intraparietal sulcus). Significantly, across observers, the degree of attraction correlated with the C1 amplitude and just the V1 BOLD signal. These findings strongly support the proposal that a bottom-up saliency map is created in V1, challenging the dominant view that the saliency map is generated in the parietal cortex.

Distinct neural substrates for the perception of real and virtual visual worlds.

Virtual environments have been frequently used for training and skill improvement. However, do real and virtual worlds engage the same brain states in human perceivers? We measured brain activity using functional magnetic resonance imaging (fMRI) while adults watched movie and cartoon clips, simulating real and virtual visual worlds, respectively. Relative to baselines using random static images, the medial prefrontal cortex (MPFC) and the cerebellum were activated only by movie clips of other humans. In contrast, cartoon clips of human and non-human agents activated the superior parietal lobes, while movie clips of animals also activated the superior parietal lobes. Our fMRI findings suggest that the perception of real-world humans is characterised by the involvement of MPFC and the cerebellum, most likely for on-line representation of the mental states of others, whereas the perception of virtual-world agents engages the parietal cortex in attention to actions.

Relationship between ventral stream for object vision and dorsal stream for spatial vision: An fMRI+ERP study

Recent imaging studies indicated the existence of two visual pathways in humans: a ventral stream for object and form vision and a dorsal stream for spatial and motion vision. The present study was motivated by a stimulating question: Supposing shape and motion are processed separately in the two pathways, how do the respective cortical areas respond to the stimuli of “forms defined by motion”? fMRI and ERP recordings were combined in order to measure the spatiotemporal activation pattern in the two pathways responding to forms defined by motion, which were produced solely by coherent movement of random dots against a background of dynamic or static random dots. The fMRI data indicated that the stimuli of forms defined by motion indeed activated both dorsal MT/V5 and ventral GTi/GF. Furthermore, the RV curves resulting from fMRI‐seeded dipole modeling indicated that each pair of dipoles located at MT/V5 or GTi/GF reached the same best‐fit point; a single pair of free dipoles located near the fMRI foci of MT/V5 and GTi/GF could be identified at the corresponding best‐fit point; and the source waveforms resulting from fixed dipole modeling also showed simultaneous activation of MT/V5 and GTi/GF dipoles in the time interval around the best‐fit point. The present results, therefore, suggest that MT/V5 and GTi/GF appear to be activated in parallel and simultaneously responding to forms defined by motion. Such findings raise interesting issues about the hierarchical organization and the functional specialization in the two pathways. Hum. Brain Mapping 8:170–181, 1999.

Connectedness affects dot numerosity judgment: Implications for configural processing

Participants judged the number of dots in visual displays with brief presentations (200 msec), such that the numerosity judgment was based on an instantaneous impression without counting. In some displays, pairs of adjacent dots were connected by line segments, whereas, in others, line segments were freely hanging without touching the dots. In Experiments 1, 2A, and 2B, connecting pairs of dots by line segments led to underestimation of dot numbers in those patterns. In Experiment 3, we controlled for the number of freely hanging line segments, whereas Experiment 4 showed that line segments that were merely attached to dots without actually connecting them did not produce a considerable underestimation effect. Experiment 5 showed that a connectedness effect existed when stimulus duration was reduced (50 msec) or extended (1,000 msec). We conclude that connectivity affects dot numerosity judgments, consistent with earlier findings of a configural effect in numerosity processing. Implications of the role of connectedness in object representation are discussed.

Global topological dominance in the left hemisphere.

A series of experiments with right-handers demonstrated that the left hemisphere (LH) is reliably and consistently superior to the right hemisphere (RH) for global topological perception. These experiments generalized the topological account of lateralization to different kinds of topological properties (including holes, inside/outside relation, and “presence vs. absence”) in comparison with a broad spectrum of geometric properties, including orientation, distance, size, mirror-symmetry, parallelism, collinearity, etc. The stimuli and paradigms used were also designed to prevent subjects from using various nontopological properties in performing the tasks of topological discrimination. Furthermore, task factors commonly considered in the study of hemispheric asymmetry, such as response latency vs. accuracy, vertical vs. horizontal presentation, detection vs. recognition, and simultaneous vs. sequential judgment, were manipulated to not be confounding factors. Moreover, left-handed subjects were tested and showed the right lateralization of topological perception, in the opposite direction of lateralization compared with right-handers. In addition, the functional magnetic resonance imaging measure revealed that only a region in the left temporal gyrus was consistently more activated across subjects in the task of topological discrimination, consistent with the behavioral results. In summary, the global topological dominance in the LH is well supported by the converging evidence from the variety of paradigms and techniques, and it suggests a unified solution to the current major controversies on visual lateralization.

Topological change disturbs object continuity in attentive tracking

The question of what is a perceptual object is one of the most central and also controversial issues in cognitive science. According to the topological approach to perceptual organization, the core intuitive notion of an object—the holistic identity preserved over shape-changing transformations—may be characterized precisely as topological invariance. Here we show that, across a series of multiple-object tracking tasks, performance was not disrupted when the moving items underwent massive featural changes. However, performance was significantly impaired when the items changed their topological properties of holes, demonstrating that topological invariance constrains what counts as an object in the first place. Consistent with previous findings, fMRI studies indicated that the anterior temporal lobe may be involved in the formation of object representation defined by topological constraints.

Perceptual learning modifies the functional specializations of visual cortical areas

Significance Using transcranial magnetic stimulation and functional magnetic resonance imaging techniques, we demonstrate here that the transfer of perceptual learning from a task involving coherent motion to a task involving noisy motion can induce a functional substitution of V3A (one of the visual areas in the extrastriate visual cortex) for MT+ (middle temporal/medial superior temporal cortex) to process noisy motion. This finding suggests that perceptual learning in visually normal adults shapes the functional architecture of the brain in a much more pronounced way than previously believed. The effects of perceptual learning extend far beyond the retuning of specific neural populations that mediate performance of the trained task. Learning could dramatically modify the inherent functional specializations of visual cortical areas and dynamically reweight their contributions to perceptual decisions based on their representational qualities. Training can improve performance of perceptual tasks. This phenomenon, known as perceptual learning, is strongest for the trained task and stimulus, leading to a widely accepted assumption that the associated neuronal plasticity is restricted to brain circuits that mediate performance of the trained task. Nevertheless, learning does transfer to other tasks and stimuli, implying the presence of more widespread plasticity. Here, we trained human subjects to discriminate the direction of coherent motion stimuli. The behavioral learning effect substantially transferred to noisy motion stimuli. We used transcranial magnetic stimulation (TMS) and functional magnetic resonance imaging (fMRI) to investigate the neural mechanisms underlying the transfer of learning. The TMS experiment revealed dissociable, causal contributions of V3A (one of the visual areas in the extrastriate visual cortex) and MT+ (middle temporal/medial superior temporal cortex) to coherent and noisy motion processing. Surprisingly, the contribution of MT+ to noisy motion processing was replaced by V3A after perceptual training. The fMRI experiment complemented and corroborated the TMS finding. Multivariate pattern analysis showed that, before training, among visual cortical areas, coherent and noisy motion was decoded most accurately in V3A and MT+, respectively. After training, both kinds of motion were decoded most accurately in V3A. Our findings demonstrate that the effects of perceptual learning extend far beyond the retuning of specific neural populations for the trained stimuli. Learning could dramatically modify the inherent functional specializations of visual cortical areas and dynamically reweight their contributions to perceptual decisions based on their representational qualities. These neural changes might serve as the neural substrate for the transfer of perceptual learning.

Topology-defined units in numerosity perception

Significance What is a number? The answer to this age-old and fundamental question of philosophy has increasingly benefited from recent scientific investigation using psychology and neuroscience. To verify the invariant nature of numerosity perception, we manipulated the numbers of items connected/enclosed in arbitrary and irregular forms while controlling for various low-level visual features in different tasks and across small and large numbers. Results were consistent with the topological account, namely that numbers were strongly influenced by topological invariants (connectivity and the inside/outside relationship): connecting/enclosing items led to robust numerosity underestimation, with the extent of underestimation increasing monotonically with the number of connected/enclosed items. Brain image results also provided evidence that numbers represented in the intraparietal sulcus were influenced by topology. What is a number? The number sense hypothesis suggests that numerosity is “a primary visual property” like color, contrast, or orientation. However, exactly what attribute of a stimulus is the primary visual property and determines numbers in the number sense? To verify the invariant nature of numerosity perception, we manipulated the numbers of items connected/enclosed in arbitrary and irregular forms while controlling for low-level features (e.g., orientation, color, and size). Subjects performed discrimination, estimation, and equality judgment tasks in a wide range of presentation durations and across small and large numbers. Results consistently show that connecting/enclosing items led to robust numerosity underestimation, with the extent of underestimation increasing monotonically with the number of connected/enclosed items. In contrast, grouping based on color similarity had no effect on numerosity judgment. We propose that numbers or the primitive units counted in numerosity perception are influenced by topological invariants, such as connectivity and the inside/outside relationship. Beyond the behavioral measures, neural tuning curves to numerosity in the intraparietal sulcus were obtained using functional MRI adaptation, and the tuning curves showed that numbers represented in the intraparietal sulcus were strongly influenced by topology.

Effects of binocular suppression on surround suppression

The responses of neurons in the primary visual cortex (V1) are generally inhibited by stimuli surrounding their classical receptive fields (CRF). This surround suppression can influence the visual perception of stimuli. For instance, the presence of a surround stimulus can decrease the apparent contrast of a central stimulus. A recent neurophysiological study in nonhuman primates suggests that two distinct mechanisms, early and late mechanisms, give rise to surround suppression. Here, we used binocular suppression to render the surround stimuli invisible and evaluated the effects of this masking on the two types of surround suppression. We found that the early mechanism was unsusceptible to, whereas the late mechanism was eliminated by, binocular suppression. The distinct effects of binocular suppression on the early and late mechanisms suggest that the two types of surround suppression arise from different neural substrates.

Cognitive gravitation model for classification on small noisy data

When performing the classification on the high dimensional, the sparse, or the noisy data, many approaches easily lead to the dramatic performance degradation. To deal with this issue from the different perspective, this paper proposes a cognitive gravitation model (CGM) based on both the law of gravitation in physics and the cognitive laws, where the self-information of each sample instead of mass is applied. Subsequently, a new classifier is designed which utilizes CGM to find k nearest neighbors from each class for the query sample and then classifies this query sample to the class whose cognitive gravitation is largest. The cognitive gravitation of the class is defined as the sum of the cognitive gravitation between its each nearest neighbor and the query sample. The advantage of our approach is that it has a firm and simple mathematical basis while it has good classification performance. The conducted experiments on challenging benchmark data sets validate the proposed model and the classification approach.