Collaborating Authors


Retinal waves prime visual motion detection by simulating future optic flow


As a mouse runs forward across the forest floor, the scenery that it passes flows backwards. Ge et al. show that the developing mouse retina practices in advance for what the eyes must later process as the mouse moves. Spontaneous waves of retinal activity flow in the same pattern as would be produced days later by actual movement through the environment. This patterned, spontaneous activity refines the responsiveness of cells in the brain's superior colliculus, which receives neural signals from the retina to process directional information. Science , abd0830, this issue p. [eabd0830][1] ### INTRODUCTION Fundamental circuit features of the mouse visual system emerge before the onset of vision, allowing the mouse to perceive objects and detect visual motion immediately upon eye opening. How the mouse visual system achieves self-organization by the time of eye opening without structured external sensory input is not well understood. In the absence of sensory drive, the developing retina generates spontaneous activity in the form of propagating waves. Past work has shown that spontaneous retinal waves provide the correlated activity necessary to refine the development of gross topographic maps in downstream visual areas, such as retinotopy and eye-specific segregation, but it is unclear whether waves also convey information that instructs the development of higher-order visual response properties, such as direction selectivity, at eye opening. ### RATIONALE Spontaneous retinal waves exhibit stereotyped changing spatiotemporal patterns throughout development. To characterize the spatiotemporal properties of waves during development, we used one-photon wide-field calcium imaging of retinal axons projecting to the superior colliculus in awake neonatal mice. We identified a consistent propagation bias that occurred during a transient developmental window shortly before eye opening. Using quantitative analysis, we investigated whether the directionally biased retinal waves conveyed ethological information relevant to future visual inputs. To understand the origin of directional retinal waves, we used pharmacological, optogenetic, and genetic strategies to identify the retinal circuitry underlying the propagation bias. Finally, to evaluate the role of directional retinal waves in visual system development, we used pharmacological and genetic strategies to chronically manipulate wave directionality and used two-photon calcium imaging to measure responses to visual motion in the midbrain superior colliculus immediately after eye opening. ### RESULTS We found that spontaneous retinal waves in mice exhibit a distinct propagation bias in the temporal-to-nasal direction during a transient window of development (postnatal day 8 to day 11). The spatial geometry of directional wave flow aligns strongly with the optic flow pattern generated by forward self-motion, a dominant natural optic flow pattern after eye opening. We identified an intrinsic asymmetry in the retinal circuit that enforced the wave propagation bias involving the same circuit elements necessary for motion detection in the adult retina, specifically asymmetric inhibition from starburst amacrine cells through γ-aminobutyric acid type A (GABAA) receptors. Finally, manipulation of directional retinal waves, through either the chronic delivery of gabazine to block GABAergic inhibition or the starburst amacrine cell–specific mutation of the FRMD7 gene, impaired the development of responses to visual motion in superior colliculus neurons downstream of the retina. ### CONCLUSION Our results show that spontaneous activity in the developing retina prior to vision onset is structured to convey essential information for the development of visual response properties before the onset of visual experience. Spontaneous retinal waves simulate future optic flow patterns produced by forward motion through space, due to an asymmetric retinal circuit that has an evolutionarily conserved link with motion detection circuitry in the mature retina. Furthermore, the ethologically relevant information relayed by directional retinal waves enhances the development of higher-order visual function in the downstream visual system prior to eye opening. These findings provide insight into the activity-dependent mechanisms that regulate the self-organization of brain circuits before sensory experience begins. ![Figure][2] Origin and function of directional retinal waves. ( A ) Imaging of retinal axon activity reveals a propagation bias in spontaneous retinal waves (scale bar, 500 μm). ( B ) Cartoon depiction of wave flow vectors projected onto visual space. Vectors (black arrows) align with the optic flow pattern (red arrows) generated by forward self-motion. ( C ) Asymmetric GABAergic inhibition in the retina mediates wave directionality. ( D ) Developmental manipulation of wave directionality disrupts direction-selective responses in downstream superior colliculus neurons at eye opening. The ability to perceive and respond to environmental stimuli emerges in the absence of sensory experience. Spontaneous retinal activity prior to eye opening guides the refinement of retinotopy and eye-specific segregation in mammals, but its role in the development of higher-order visual response properties remains unclear. Here, we describe a transient window in neonatal mouse development during which the spatial propagation of spontaneous retinal waves resembles the optic flow pattern generated by forward self-motion. We show that wave directionality requires the same circuit components that form the adult direction-selective retinal circuit and that chronic disruption of wave directionality alters the development of direction-selective responses of superior colliculus neurons. These data demonstrate how the developing visual system patterns spontaneous activity to simulate ethologically relevant features of the external world and thereby instruct self-organization. [1]: /lookup/doi/10.1126/science.abd0830 [2]: pending:yes

Security researchers fool Microsoft's Windows Hello authentication system


Microsoft designed Windows Hello to be compatible with webcams across multiple brands, but that feature designed for ease of adoption could also make the technology vulnerable to bad actors. As reported by Wired, researchers from the security firm CyberArk managed to fool the Hello facial recognition system using images of the computer owner's face. Windows Hello requires the use of cameras with both RGB and infrared sensors, but upon investigating the authentication system, the researchers found that it only processes infrared frames. To verify their finding, the researchers created a custom USB device, which they loaded with infrared photos of the user and RGB images of Spongebob. Hello recognized the device as a USB camera, and it was successfully unlocked with just the IR photos of the user.

Ring Video Doorbell 4 review: Great for people deep in the Ring ecosystem; just good for everyone else


Ring now offers seven video doorbell models, and as you might have guessed, the company is running out of ways to differentiate them. The Ring Video Doorbell 4 looks virtually identical to the Ring Video Doorbell 3 (and the battery-only Ring Video Doorbell 2, for that matter), and it delivers the same 1080p resolution. Like the model 3, the Ring Video Doorbell 4 can operate on either battery power or your existing doorbell wiring, and both models support dual-band Wi-Fi networks (2.4- and 5GHz). That leaves color pre-roll video previews (more on that in a bit) as the only additional feature you'll get for the extra $20 in cost. As is typical of Ring home-security products, you'll need to sign up for a subscription to unlock all the Ring Video Doorbell 4's capabilities.

How facial recognition solutions can safeguard the hybrid workplace - Help Net Security


The number of US adults teleworking due to the pandemic fell by 30% between January and May 2021 (from 23% to 16%), with the biggest drop in May. As more employees return to their offices, new and unexpected challenges hidden within the new hybrid work model threaten to severely disrupt safety and security. Another added complication is that newly relaxed CDC (Centers for Disease Control) guidelines do not apply to unvaccinated people or account for variations in local or state health guidelines that may be in place, potentially creating a need for organizations to identify and track different groups of employees and visitors. Thankfully, AI-based solutions exist to bolster the security of in-person workplaces and enhance key elements, from the sign-in process to restricted area enforcement, while also allowing for frictionless adherence to health guidelines. As the most accurate, turnkey biometric solution, facial recognition has the potential to solve many of the looming challenges offices will soon face as employees return to work.

Detection of abnormal events in videos


The rapid advancements in the technology of closed circuit television cameras and their underlying infrastructure has led to a sheer number of surveillance cameras being implemented globally, estimated to go beyond 1 billion by the end of the year 2021 . Considering the massive amounts of videos generated in real-time, manual video analysis by human operator becomes inefficient, expensive, and nearly impossible, which in turn makes a great demand for automated and intelligent methods for an efficient video surveillance system. An important task in video surveillance is anomaly detection, which refers to the identification of events that do not conform to the expected behavior. Abnormal events in the general sense have the characteristics of suddenness,in order to be able to understand the abnormal events in the first time, it usually takes a lot of manpower to stare at the monitoring screen for a long time to observe, so It will not only make people tired, but also easily overlook some inconspicuous events. Therefore, the automatic detection and recognition of abnormal events of surveillance video in complex scenes, as the core subject of intelligent video surveillance systems, is receiving more and more attention from researchers.

The All-Seeing Eyes of New York's 15,000 Surveillance Cameras


A new video from human rights organization Amnesty International maps the locations of more than 15,000 cameras used by the New York Police Department, both for routine surveillance and in facial-recognition searches. A 3D model shows the 200-meter range of a camera, part of a sweeping dragnet capturing the unwitting movements of nearly half of the city's residents, putting them at risk for misidentification. The group says it is the first to map the locations of that many cameras in the city. Amnesty International and a team of volunteer researchers mapped cameras that can feed NYPD's much criticized facial-recognition systems in three of the city's five boroughs--Manhattan, Brooklyn, and the Bronx--finding 15,280 in total. Brooklyn is the most surveilled, with over 8,000 cameras.

Banned gamblers in South Australia to be found using facial recognition tech


A large amount of South Australian gaming rooms now have facial recognition technology installed in a bid to find individuals that have been banned from gambling. The tech, installed in over 80% of venues that offer gambling, including pubs, clubs, and casinos, has been delivered by Vix Vizion, in partnership with Cradlepoint. From 3 December 2020, significant gambling reforms came into effect in South Australia. New requirements were introduced relating to the use of facial recognition technology, touted as assisting licensees to identify barred persons entering a gaming area. "Facial recognition technology will further support and assist licensed venues meet their responsibilities of identifying barred patrons by alerting gaming venue staff when a barred patron is detected entering the gaming room," South Australian Consumer and Business Services (CBS) explains.

China Testing Artificial Intelligence Emotion Detection On Uyghurs


Smith Willas is a freelance writer, blogger, and digital media journalist. Chinese authorities are testing systems that use AI and facial recognition to detect emotional states. This is reported by the BBC with reference to an unnamed developer of this technology. Experts Boosty Labs, a company that focuses on smart contract development and blockchain app development, share their thoughts of this innovative trend's implications. Beijing is accused by many countries of the genocide of the Uyghur population. The Chinese authorities have flooded the predominantly Muslim Xinjiang Uygur Autonomous Region with surveillance cameras.

Amazon's Ring is the largest civilian surveillance network the US has ever seen Lauren Bridges

The Guardian

In a 2020 letter to management, Max Eliaser, an Amazon software engineer, said Ring is "simply not compatible with a free society". We should take his claim seriously. Ring video doorbells, Amazon's signature home security product, pose a serious threat to a free and democratic society. Not only is Ring's surveillance network spreading rapidly, it is extending the reach of law enforcement into private property and expanding the surveillance of everyday life. What's more, once Ring users agree to release video content to law enforcement, there is no way to revoke access and few limitations on how that content can be used, stored, and with whom it can be shared.

China using surveillance firms to help write ethnicity-tracking specs

The Japan Times

China enlisted surveillance firms to help draw up standards for mass facial recognition systems, researchers said on Tuesday, warning that an unusually heavy emphasis on tracking characteristics such as ethnicity created wide scope for abuse. The technical standards, published by surveillance research group IPVM, specify how data captured by facial recognition cameras across China should be segmented by dozens of characteristics -- from eyebrow size to skin color and ethnicity. "It's the first time we've ever seen public security camera networks that are tracking people by these sensitive categories explicitly at this scale," said the report's author, Charles Rollet. The standards are driving the way surveillance networks are being built across the country -- from residential developments in the capital, Beijing, to police systems in the central province of Hubei, he said. In one instance, the report cites a November 2020 tender for a small "smart" housing project in Beijing, requiring suppliers for its surveillance camera system to meet a standard that allows sorting by skin tone, ethnicity and hairstyle.