Mouse Ability to Perceive Subjective Contours

Recurrent pattern completion drives the neocortical representation of sensory inference

When sensory information is incomplete or ambiguous, the brain relies on prior expectations to infer perceptual objects. Despite the centrality of this process to perception, the neural mechanism of sensory inference is not known. Illusory contours (ICs) are key tools to study sensory inference because they contain edges or objects that are implied only by their spatial context. Using cellular resolution, mesoscale two-photon calcium imaging and multi-Neuropixels recordings in the mouse visual cortex, we identified a sparse subset of neurons in the primary visual cortex (V1) and higher visual areas that respond emergently to ICs. We found that these highly selective 'IC-encoders' mediate the neural representation of IC inference. Strikingly, selective activation of these neurons using two-photon holographic optogenetics was sufficient to recreate IC representation in the rest of the V1 network, in the absence of any visual stimulus. This outlines a model in which primary sensory cortex facilitates sensory inference by selectively strengthening input patterns that match prior expectations through local, recurrent circuitry. Our data thus suggest a clear computational purpose for recurrence in the generation of holistic percepts under sensory ambiguity. More generally, selective reinforcement of top-down predictions by pattern-completing recurrent circuits in lower sensory cortices may constitute a key step in sensory inference.

Dogs (Canis lupus familiaris) are susceptible to the Kanizsa's triangle illusion

The ability to complete partially missing contours is widespread across the animal kingdom, but whether this extends to dogs is still unknown. To address this gap in knowledge, we assessed dogs' susceptibility to one of the most common contour illusions, the Kanizsa's triangle. Six dogs were trained to discriminate a triangle from other geometrical figures using a two-alternative conditioned discrimination task. Once the learning criterion was reached, dogs were presented with the Kanizsa's triangle and a control stimulus, where inducers were rotated around their centre, so as to disrupt what would be perceived as a triangle by a human observer. As a group, dogs chose the illusory triangle significantly more often than control stimuli. At the individual level, susceptibility to the illusion was shown by five out of six dogs. This is the first study where dogs as a group show susceptibility to a visual illusion in the same manner as humans. Moreover, the analyses revealed a negative effect of age on susceptibility, an effect that was also found in humans. Altogether, this suggests that the underling perceptual mechanisms are similar between dogs and humans, and in sharp contrast with other categories of visual illusions to which the susceptibility of dogs has been previously assessed.

Critical mass: The rise of a touchscreen technology community for rodent cognitive testing

The rise in the number of users and institutions utilizing the rodent touchscreen technology for cognitive testing over the past decade has prompted the need for knowledge mobilization and community building. To address the needs of the growing touchscreen community, the first international touchscreen symposium was hosted at Western University. Attendees from around the world attended talks from expert neuroscientists using touchscreens to examine a vast array of questions regarding cognition and the nervous system. In addition to the symposium, a subset of attendees was invited to partake in a hands-on training course where they received touchscreen training covering both hardware and software components. Beyond the two touchscreen events, virtual platforms have been developed to further support touchscreen users: (a) Mousebytes.ca, which includes a data repository of rodent touchscreen tasks, and (b) Touchscreencognition.org, an online community with numerous training and community resources, perhaps most notably a forum where members can ask and answer questions. The advantages of the rodent touchscreen technology for cognitive neuroscience research has allowed neuroscientists from diverse backgrounds to test specific cognitive processes using well-validated and standardized apparatus, contributing to its rise in popularity and its relevance to modern neuroscience research. The commitment of the touchscreen community to data, task development and information sharing not only ensures an expansive future of the use of rodent touchscreen technology but additionally, quality research that will increase translation from preclinical studies to clinical successes.

Top-Down Feedback Controls the Cortical Representation of Illusory Contours in Mouse Primary Visual Cortex

Visual systems have evolved to recognize and extract features from complex scenes using limited sensory information. Contour perception is essential to this process and can occur despite breaks in the continuity of neighboring features. Such robustness of the animal visual system to degraded or occluded shapes may also give rise to an interesting phenomenon of optical illusions. These illusions provide a great opportunity to decipher neural computations underlying contour integration and object detection. Kanizsa illusory contours have been shown to evoke responses in the early visual cortex despite the lack of direct receptive field activation. Recurrent processing between visual areas has been proposed to be involved in this process. However, it is unclear whether higher visual areas directly contribute to the generation of illusory responses in the early visual cortex. Using behavior, in vivo electrophysiology, and optogenetics, we first show that the primary visual cortex (V1) of male mice responds to Kanizsa illusory contours. Responses to Kanizsa illusions emerge later than the responses to the contrast-defined real contours in V1. Second, we demonstrate that illusory responses are orientation-selective. Finally, we show that top-down feedback controls the neural correlates of illusory contour perception in V1. Our results suggest that higher-order visual areas may fill in the missing information in the early visual cortex necessary for illusory contour perception.SIGNIFICANCE STATEMENT Perception of the Kanizsa illusory contours is impaired in neurodevelopmental disorders such as schizophrenia, autism, and Williams syndrome. However, the mechanism of the illusory contour perception is poorly understood. Here we describe the behavioral and neural correlates of Kanizsa illusory contours perception in mice, a genetically tractable model system. We show that top-down feedback controls the neural responses to Kanizsa illusion in V1. To our knowledge, this is the first description of the neural correlates of the Kanizsa illusion in mice and the first causal demonstration of their regulation by top-down feedback.

Indicators and Criteria of Consciousness in Animals and Intelligent Machines: An Inside-Out Approach

In today's society, it becomes increasingly important to assess which non-human and non-verbal beings possess consciousness. This review article aims to delineate criteria for consciousness especially in animals, while also taking into account intelligent artifacts. First, we circumscribe what we mean with "consciousness" and describe key features of subjective experience: qualitative richness, situatedness, intentionality and interpretation, integration and the combination of dynamic and stabilizing properties. We argue that consciousness has a biological function, which is to present the subject with a multimodal, situational survey of the surrounding world and body, subserving complex decision-making and goal-directed behavior. This survey reflects the brain's capacity for internal modeling of external events underlying changes in sensory state. Next, we follow an inside-out approach: how can the features of conscious experience, correlating to mechanisms inside the brain, be logically coupled to externally observable ("outside") properties? Instead of proposing criteria that would each define a "hard" threshold for consciousness, we outline six indicators: (i) goal-directed behavior and model-based learning; (ii) anatomic and physiological substrates for generating integrative multimodal representations; (iii) psychometrics and meta-cognition; (iv) episodic memory; (v) susceptibility to illusions and multistable perception; and (vi) specific visuospatial behaviors. Rather than emphasizing a particular indicator as being decisive, we propose that the consistency amongst these indicators can serve to assess consciousness in particular species. The integration of scores on the various indicators yields an overall, graded criterion for consciousness, somewhat comparable to the Glasgow Coma Scale for unresponsive patients. When considering theoretically derived measures of consciousness, it is argued that their validity should not be assessed on the basis of a single quantifiable measure, but requires cross-examination across multiple pieces of evidence, including the indicators proposed here. Current intelligent machines, including deep learning neural networks (DLNNs) and agile robots, are not indicated to be conscious yet. Instead of assessing machine consciousness by a brief Turing-type of test, evidence for it may gradually accumulate when we study machines ethologically and across time, considering multiple behaviors that require flexibility, improvisation, spontaneous problem-solving and the situational conspectus typically associated with conscious experience.

Neural Mechanisms of High-Level Vision

The last three decades have seen major strides in our understanding of neural mechanisms of high-level vision, or visual cognition of the world around us. Vision has also served as a model system for the study of brain function. Several broad insights, as yet incomplete, have recently emerged. First, visual perception is best understood not as an end unto itself, but as a sensory process that subserves the animal's behavioral goal at hand. Visual perception is likely to be simply a side effect that reflects the readout of visual information processing that leads to behavior. Second, the brain is essentially a probabilistic computational system that produces behaviors by collectively evaluating, not necessarily consciously or always optimally, the available information about the outside world received from the senses, the behavioral goals, prior knowledge about the world, and possible risks and benefits of a given behavior. Vision plays a prominent role in the overall functioning of the brain providing the lion's share of information about the outside world. Third, the visual system does not function in isolation, but rather interacts actively and reciprocally with other brain systems, including other sensory faculties. Finally, various regions of the visual system process information not in a strict hierarchical manner, but as parts of various dynamic brain-wide networks, collectively referred to as the "connectome." Thus, a full understanding of vision will ultimately entail understanding, in granular, quantitative detail, various aspects of dynamic brain networks that use visual sensory information to produce behavior under real-world conditions. © 2017 American Physiological Society. Compr Physiol 8:903-953, 2018.

Vision in laboratory rodents-Tools to measure it and implications for behavioral research

Mice and rats are nocturnal mammals and their vision is specialized for detection of motion and contrast in dim light conditions. These species possess a large proportion of UV-sensitive cones in their retinas and the majority of their optic nerve axons target superior colliculus rather than visual cortex. Therefore, it was a widely held belief that laboratory rodents hardly utilize vision during day-time behavior. This dogma is being questioned as accumulating evidence suggests that laboratory rodents are able to perform complex visual functions, such as perceiving subjective contours, and that declined vision may affect their performance in many behavioral tasks. For instance, genetic engineering may have unexpected consequences on vision as mouse models of Alzheimer's and Huntington's diseases have declined visual function. Rodent vision can be tested in numerous ways using operant training or reflex-based behavioral tasks, or alternatively using electrophysiological recordings. In this article, we will first provide a summary of visual system and explain its characteristics unique to rodents. Then, we present well-established techniques to test rodent vision, with an emphasis on pattern vision: visual water test, optomotor reflex test, pattern electroretinography and pattern visual evoked potentials. Finally, we highlight the importance of visual phenotyping in rodents. As the number of genetically engineered rodent models and volume of behavioral testing increase simultaneously, the possibility of visual dysfunctions needs to be addressed. Neglect in this matter potentially leads to crude biases in the field of neuroscience and beyond.