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Open Access Publications from the University of California

Scholarly Works (12 results)

  • Article
  • Peer Reviewed
UC Berkeley Previously Published Works (2012)
The pulvinar nucleus of the thalamus is suspected to have an important role in visual attention, based on its widespread connectivity with the visual cortex and the fronto-parietal attention network. However, at present, there remain many hypotheses on the pulvinar's specific function, with sparse or conflicting evidence for each. Here we characterize how the human pulvinar encodes attended and ignored objects when they appear simultaneously and compete for attentional resources. Using multivoxel pattern analyses on data from two functional magnetic resonance imaging (fMRI) experiments, we show that attention gates both position and orientation information in the pulvinar: attended objects are encoded with high precision, while there is no measurable encoding of ignored objects. These data support a role of the pulvinar in distractor filtering--suppressing information from competing stimuli to isolate behaviourally relevant objects.
    Cover page: Attention gates visual coding in the human pulvinar
    • Article
    • Peer Reviewed
    UC Berkeley Previously Published Works (2014)
    Visual input often arrives in a noisy and discontinuous stream, owing to head and eye movements, occlusion, lighting changes, and many other factors. Yet the physical world is generally stable; objects and physical characteristics rarely change spontaneously. How then does the human visual system capitalize on continuity in the physical environment over time? We found that visual perception in humans is serially dependent, using both prior and present input to inform perception at the present moment. Using an orientation judgment task, we found that, even when visual input changed randomly over time, perceived orientation was strongly and systematically biased toward recently seen stimuli. Furthermore, the strength of this bias was modulated by attention and tuned to the spatial and temporal proximity of successive stimuli. These results reveal a serial dependence in perception characterized by a spatiotemporally tuned, orientation-selective operator-which we call a continuity field-that may promote visual stability over time.
      Cover page: Serial dependence in visual perception
      • Thesis
      • Peer Reviewed
      UC Berkeley Electronic Theses and Dissertations (2012)

      Perceiving objects' positions is one of the fundamental purposes of vision and is crucial to day-to-day life. Much work has been devoted to finding and characterizing spatial maps in the brain, but we still know strikingly little about how these maps support perceptual localization. The experiments in this thesis employ a combination of functional brain imaging and visual psychophysics, drawing on a body of behavioral literature on spatial perception and visual attention, to ask how position coding in the brain adapts to support the demands of the task at hand.

      The experiments in Chapter 2 ask how and where perceived object positions are represented in the brain. Perceived position depends on many factors such as attention, frame of reference, adaptation, and motion. At what stage of visual processing is this information integrated into the brain's retinotopic maps? By measuring variability in perceived position alongside variability in the multivariate pattern of neural responses in a host of visual areas, we identify a percept-centered reference frame in high-level object-, face-, scene-, and motion-selective regions.

      The experiments in Chapter 3 ask how the visual system achieves improved spatial resolution with focused attention. Attention is known to boost the amplitude of neural responses, but it might also sharpen position tuning at the neural population level, making the activations produced by adjacent objects more distinct within the cortex. Employing a combined imaging and modeling approach, we find that attention narrows the spatial spread of the fMRI BOLD response in early visual cortical areas, including V1. This narrowed population position tuning is an efficient means of achieving visual resolution improvements.

      The experiments in Chapter 4 ask how the brain suppresses distracting visual input in order to limit its negative impact on performance. During a selective attention task, we measure the BOLD response in the pulvinar nucleus of the thalamus, an area whose damage appears to lead to distractor filtering deficits. We find that while attended items are represented with high spatial and featural precision in the pulvinar, ignored items are gated out, leaving no discernable trace in the pattern of response in the pulvinar. These results suggest that the spatial maps in the pulvinar may serve as an interface in which distracting visual input is filtered out.

      Collectively, the findings presented here speak to a remarkable flexibility in the way the brain represents spatial information. The brain's visual maps adapt on a moment-by-moment basis to support the demands of the task at hand.

        Cover page: The role of attention in cortical and subcortical spatial mapping
        • Article
        • Peer Reviewed
        UC Berkeley Previously Published Works (2014)
        From moment to moment, we perceive objects in the world as continuous despite fluctuations in their image properties due to factors like occlusion, visual noise, and eye movements. The mechanism by which the visual system accomplishes this object continuity remains elusive. Recent results have demonstrated that the perception of low-level stimulus features such as orientation and numerosity is systematically biased (i.e., pulled) toward visual input from the recent past. The spatial region over which current orientations are pulled by previous orientations is known as the continuity field, which is temporally tuned for the past 10-15 s. This perceptual pull could contribute to the visual stability of low-level features over short time periods, but it does not address how visual stability occurs at the level of object identity. Here, we tested whether the visual system facilitates stable perception by biasing current perception of a face, a complex and behaviorally relevant object, toward recently seen faces. We found that perception of face identity is systematically biased toward identities seen up to several seconds prior, even across changes in viewpoint. This effect did not depend on subjects' prior responses or on the method used to measure identity perception. Although this bias in perceived identity manifests as a misperception, it is adaptive: visual processing echoes the stability of objects in the world to create perceptual continuity. The serial dependence of identity perception promotes object identity invariance over time and provides the clearest evidence for the existence of an object-selective perceptual continuity field.
          Cover page: Serial Dependence in the Perception of Faces
          • Article
          • Peer Reviewed
          UC Berkeley Previously Published Works (2014)
          Because the environment is cluttered, objects rarely appear in isolation. The visual system must therefore attentionally select behaviorally relevant objects from among many irrelevant ones. A limit on our ability to select individual objects is revealed by the phenomenon of visual crowding: an object seen in the periphery, easily recognized in isolation, can become impossible to identify when surrounded by other, similar objects. The neural basis of crowding is hotly debated: while prevailing theories hold that crowded information is irrecoverable - destroyed due to over-integration in early stage visual processing - recent evidence demonstrates otherwise. Crowding can occur between high-level, configural object representations, and crowded objects can contribute with high precision to judgments about the "gist" of a group of objects, even when they are individually unrecognizable. While existing models can account for the basic diagnostic criteria of crowding (e.g., specific critical spacing, spatial anisotropies, and temporal tuning), no present model explains how crowding can operate simultaneously at multiple levels in the visual processing hierarchy, including at the level of whole objects. Here, we present a new model of visual crowding-the hierarchical sparse selection (HSS) model, which accounts for object-level crowding, as well as a number of puzzling findings in the recent literature. Counter to existing theories, we posit that crowding occurs not due to degraded visual representations in the brain, but due to impoverished sampling of visual representations for the sake of perception. The HSS model unifies findings from a disparate array of visual crowding studies and makes testable predictions about how information in crowded scenes can be accessed.
            Cover page: The hierarchical sparse selection model of visual crowding
            • Article
            • Peer Reviewed
            UC Berkeley Previously Published Works (2011)
            We tested whether the intervening time between multiple glances influences the independence of the resulting visual percepts. Observers estimated how many dots were present in brief displays that repeated one, two, three, four, or a random number of trials later. Estimates made farther apart in time were more independent, and thus carried more information about the stimulus when combined. In addition, estimates from different visual field locations were more independent than estimates from the same location. Our results reveal a retinotopic serial dependence in visual numerosity estimates, which may be a mechanism for maintaining the continuity of visual perception in a noisy environment.
              Cover page: Facilitating Stable Representations: Serial Dependence in Vision
              • Article
              • Peer Reviewed
              UC Berkeley Previously Published Works (2011)
              Crowding is a fundamental bottleneck in object recognition. In crowding, an object in the periphery becomes unrecognizable when surrounded by clutter or distractor objects. Crowding depends on the positions of target and distractors, both their eccentricity and their relative spacing. In all previous studies, position has been expressed in terms of retinal position. However, in a number of situations retinal and perceived positions can be dissociated. Does retinal or perceived position determine the magnitude of crowding? Here observers performed an orientation judgment on a target Gabor patch surrounded by distractors that drifted toward or away from the target, causing an illusory motion-induced position shift. Distractors in identical physical positions led to worse performance when they drifted towards the target (appearing closer) versus away from the target (appearing further). This difference in crowding corresponded to the difference in perceived positions. Further, the perceptual mislocalization was necessary for the change in crowding, and both the mislocalization and crowding scaled with drift speed. The results show that crowding occurs after perceived positions have been assigned by the visual system. Crowding does not operate in a purely retinal coordinate system; perceived positions need to be taken into account.
                Cover page: Perceived Positions Determine Crowding
                • Article
                Proceedings of the Annual Meeting of the Cognitive Science Society, Volume 40 (2018)
                Humans demonstrate a remarkable ability to infer physical properties of objects and predict physical events in dynamicscenes. These abilities have been modeled as probabilistic simulations of a mental physics engine akin to 3D physicsengines used in computer simulations and video games (Battaglia, Hamrick & Tenenbaum 2013; Sanborn, Mansinghka &Griffiths 2013), but it is unknown if and how such a physics engine is implemented in the brain. Does the brain representquantities corresponding to the key latent variables of physical objects that contribute to their dynamics? To find out,we used multivariate pattern classification analyses of fMRI data from subjects viewing videos of dynamic objects. Themass of depicted objects could be decoded, across physical scenarios and object materials, from brain regions previouslyimplicated in intuitive physics. This invariant representation of mass may serve as a key variable in a generalized enginefor intuitive physics.
                  Cover page: Evidence for an Intuitive Physics Engine in the Human Brain
                  • Article
                  • Peer Reviewed
                  UC Berkeley Previously Published Works (2014)
                  Individuals can rapidly and precisely judge the average of a set of similar items, including both low-level (Ariely, 2001) and high-level objects (Haberman & Whitney, 2007). However, to date, it is unclear whether ensemble perception is based on viewpoint-invariant object representations. Here, we tested this question by presenting participants with crowds of sequentially presented faces. The number of faces in each crowd and the viewpoint of each face varied from trial to trial. This design required participants to integrate information from multiple viewpoints into one ensemble percept. Participants reported the mean identity of crowds (e.g., family resemblance) using an adjustable, forward-oriented test face. Our results showed that participants accurately perceived the mean crowd identity even when required to incorporate information across multiple face orientations. Control experiments showed that the precision of ensemble coding was not solely dependent on the length of time participants viewed the crowd. Moreover, control analyses demonstrated that observers did not simply sample a subset of faces in the crowd but rather integrated many faces into their estimates of average crowd identity. These results demonstrate that ensemble perception can operate at the highest levels of object recognition after 3-D viewpoint-invariant faces are represented.
                    Cover page: Ensemble crowd perception: A viewpoint-invariant mechanism to represent average crowd identity
                    • Article
                    • Peer Reviewed
                    UC San Francisco Previously Published Works (2016)
                    The development of a non-human primate (NHP) model of spinal cord injury (SCI) based on mechanical and computational modeling is described. We scaled up from a rodent model to a larger primate model using a highly controllable, friction-free, electronically-driven actuator to generate unilateral C6-C7 spinal cord injuries. Graded contusion lesions with varying degrees of functional recovery, depending upon pre-set impact parameters, were produced in nine NHPs. Protocols and pre-operative magnetic resonance imaging (MRI) were used to optimize the predictability of outcomes by matching impact protocols to the size of each animal's spinal canal, cord, and cerebrospinal fluid space. Post-operative MRI confirmed lesion placement and provided information on lesion volume and spread for comparison with histological measures. We evaluated the relationships between impact parameters, lesion measures, and behavioral outcomes, and confirmed that these relationships were consistent with our previous studies in the rat. In addition to providing multiple univariate outcome measures, we also developed an integrated outcome metric describing the multivariate cervical SCI syndrome. Impacts at the higher ranges of peak force produced highly lateralized and enduring deficits in multiple measures of forelimb and hand function, while lower energy impacts produced early weakness followed by substantial recovery but enduring deficits in fine digital control (e.g., pincer grasp). This model provides a clinically relevant system in which to evaluate the safety and, potentially, the efficacy of candidate translational therapies.
                      Cover page: A Unilateral Cervical Spinal Cord Contusion Injury Model in Non-Human Primates (Macaca mulatta)
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