Measuring the speed of newborn object recognition in controlled visual worlds

Digital Twin Studies for Reverse Engineering the Origins of Visual Intelligence

What are the core learning algorithms in brains? Nativists propose that intelligence emerges from innate domain-specific knowledge systems, whereas empiricists propose that intelligence emerges from domain-general systems that learn domain-specific knowledge from experience. We address this debate by reviewing digital twin studies designed to reverse engineer the learning algorithms in newborn brains. In digital twin studies, newborn animals and artificial agents are raised in the same environments and tested with the same tasks, permitting direct comparison of their learning abilities. Supporting empiricism, digital twin studies show that domain-general algorithms learn animal-like object perception when trained on the first-person visual experiences of newborn animals. Supporting nativism, digital twin studies show that domain-general algorithms produce innate domain-specific knowledge when trained on prenatal experiences (retinal waves). We argue that learning across humans, animals, and machines can be explained by a universal principle, which we call space-time fitting. Space-time fitting explains both empiricist and nativist phenomena, providing a unified framework for understanding the origins of intelligence.

The Development of Object Recognition Requires Experience with the Surface Features of Objects

What role does visual experience play in the development of object recognition? Prior controlled-rearing studies suggest that newborn animals require slow and smooth visual experiences to develop object recognition. Here, we examined whether the development of object recognition also requires experience with the surface features of objects. We raised newborn chicks in automated controlled-rearing chambers that contained a single virtual object, then tested their ability to recognize that object from familiar and novel viewpoints. When chicks were reared with an object that had surface features, the chicks developed view-invariant object recognition. In contrast, when chicks were reared with a line drawing of an object, the chicks failed to develop object recognition. The chicks reared with line drawings performed at chance level, despite acquiring over 100 h of visual experience with the object. These results indicate that the development of object recognition requires experience with the surface features of objects.

Distorting Face Representations in Newborn Brains

What role does experience play in the development of face recognition? A growing body of evidence indicates that newborn brains need slowly changing visual experiences to develop accurate visual recognition abilities. All of the work supporting this "slowness constraint" on visual development comes from studies testing basic-level object recognition. Here, we present the results of controlled-rearing experiments that provide evidence for a slowness constraint on the development of face recognition, a prototypical subordinate-level object recognition task. We found that (1) newborn chicks can rapidly develop view-invariant face recognition and (2) the development of this ability relies on experience with slowly moving faces. When chicks were reared with quickly moving faces, they built distorted face representations that largely lacked invariance to viewpoint changes, effectively "breaking" their face recognition abilities. These results provide causal evidence that slowly changing visual experiences play a critical role in the development of face recognition, akin to basic-level object recognition. Thus, face recognition is not a hardwired property of vision but is learned rapidly as the visual system adapts to the temporal structure of the animal's visual environment.

One-shot learning of view-invariant object representations in newborn chicks

Can newborn brains perform one-shot learning? To address this question, we reared newborn chicks in strictly controlled environments containing a single view of a single object, then tested their object recognition performance across 24 uniformly-spaced viewpoints. We found that chicks can build view-invariant object representations from a single view of an object: a case of one-shot learning in newborn brains. Chicks can also build the same view-invariant object representation from different views of an object, showing that newborn brains converge on common object representations from different sets of sensory inputs. Finally, by rearing chicks with larger numbers of object views, we found that chicks develop enhanced recognition for familiar views. These results illuminate the earliest stages of object recognition, revealing (1) powerful one-shot learning that builds invariant object representations from the first views of an object and (2) view-based learning that enriches object representations, producing enhanced recognition for familiar views.

Pigeons spontaneously form three-dimensional shape categories

We explored the pigeon's representation of the shape of simple three-dimensional objects (geons) rotated in depth (four views each of four geons). Pigeons assigned to the Categorization group had to respond differentially to images of four different geons-termed arch, barrel, brick, and wedge-based on their 3D shape, regardless of the orientation of the object. Pigeons assigned to the Pseudocategorization group had to respond differentially to the same objects based on groupings that did not correspond to object identity, which required the learning of local orientation-dependent features (e.g., a concave curve on top, or the position of an illumination hotspot). The Categorization group, which could employ object-identity representations, quickly achieved highly accurate responding. The Pseudocategorization group, however, failed to achieve reliable above-chance responding. In addition, the reaction times for the Categorization group were significantly shorter than for the Pseudocategorization group. These results indicate that pigeons show a strong, spontaneous tendency to categorize the shapes of different orientations in depth of the same 3D object as similar, if not equivalent; they do so despite the vast differences in image characteristics caused by the variations in orientations, even when such categorization is contrary to the reinforcement contingencies.

Spontaneous Preference for Slowly Moving Objects in Visually Naïve Animals

To perceive the world successfully, newborns need certain types of visual experiences. The development of object recognition, for example, requires visual experience with slowly moving objects. To date, however, it is unknown whether newborns actively seek out the best visual experiences for developing object recognition. To address this question, I used an automated controlled-rearing method to examine whether visually naïve animals (newborn chicks) seek out slowly moving objects. Despite receiving equal exposure to slowly and to quickly rotating objects, the majority of the chicks developed a preference for slowly rotating objects. This preference was robust, producing large effect sizes across objects, experiments, and successive test days. These results indicate that newborn brains rapidly develop mechanisms for orienting young animals toward optimal visual experiences, thus facilitating the development of object recognition. This study also demonstrates that automation can be a valuable tool for studying the origins and development of visual preferences.