ARTICLE Communicated by Jeffrey Elman Object Recognition and Sensitive Periods: A Computational Analysis of Visual Imprinting Randall C. OReilly Mark H. Johnson Department of Psychology, Carnegie Mellon University, Pittsburgh, PA 25213 USA Using neural and behavioral constraints from a relatively simple bio- logical visual system, we evaluate the mechanism and behavioral im- plications of a model of invariant object recognition. Evidence from a variety of methods suggests that a localized portion of the domes- tic chick brain, the intermediate and medial hyperstriatum ventrale (IMHV), is critical for object recognition. We have developed a neural network model of translation-invariant object recognition that incor- porates features of the neural circuitry of IMHV, and exhibits behav- ior qualitatively similar to a range of findings in the filial imprinting paradigm. We derive several counter-intuitive behavioral predictions that depend critically upon the biologically derived features of the model. In particular, we propose that the recurrent excitatory and lat- eral inhibitory circuitry in the model, and observed in IMHV, produces hysteresis on the activation state of the units in the model and the prin- cipal excitatory neurons in IMHV. Hysteresis, when combined with a simple Hebbian covariance learning mechanism, has been shown in this and earlier work (Foldidk 1991; O’Reilly and McClelland 1992) to produce translation-invariant visual representations. The hysteresis and learning rule are responsible for a sensitive period phenomenon in the network, and for a series of novel temporal blending phenom- ena. These effects are empirically testable. Further, physiological and anatomical features of mammalian visual cortex support a hysteresis- based mechanism, arguing for the generality of the algorithm. 1 Introduction General approaches to the computational problem of spatially invariant object recognition have come and gone over the years, but the problem remains. In both the symbolic and neural network paradigms the re- search emphasis has shifted from underlying principles to special case performance on real world tasks such as handwritten digit recognition or Neural Computation 6,357-389 (1994) @ 1994 Massachusetts Institute of Technology Downloaded from http://www.mitpressjournals.org/doi/pdf/10.1162/neco.1994.6.3.357 by guest on 28 September 2021 358 Randall C. OReilly and Mark H. Johnson assembly-line part recognition. We have adopted a different approach, which is to link the computational principles and behavior of a model to those of a biological object recognition system, wherein the research em- phasis is on the ability to use empirical data to constrain and shape the model. The biologically based approach is limited by the level of com- putational understanding about how specific neural properties produce specific behavioral phenomena. However, if it were possible to establish a mapping between a biological system and a model at both the behavioral and neural levels, then the relationship between neural computation and behavior could be understood in the simplified framework of the model. If the model makes unique and testable behavioral predictions based on its identified neural properties, then experimental research can be used to test the computational theory of object recognition embodied in the model. We have developed a model of invariant visual object recognition based on the environmental regularity of object existence: objects, though they might exhibit motion relative to the observer, have a tendency to persist in the environment. This regularity can be capitalized upon by introducing a corresponding persistence or hysteresis in the activation states of neurons responsible for object recognition. When combined with a Hebbian learning rule, these neurons become associated with the many different images of a given object, resulting in an invariant repre- sentation. This algorithm (Foldidk 1991; OReilly and McClelland 19921, as described in OReilly and McClelland (19921, relies on specific neu- ral properties that lead to hysteresis. Instead of attempting to test for evidence of the algorithm in the complex mammalian nervous system, we have taken the approach of studying the relatively well known and simpler vertebrate object recognition system of the domestic chick. Visual object recognition in the chick has been studied behaviorally for nearly 50 years under the guise of filial imprinting, which is the process whereby young precocial' birds learn to recognize the first conspicuous object that they see after hatching. The original work of Lorenz (1935, 1937) on imprinting has given rise to half a century of active research on this process by ethologists and psychologists, and more recently by neuroscientists interested in the neural basis of imprinting. Recently, the area of the chick brain that subserves this imprinting process has been identified, and some of its neurobiological properties studied. Therefore, it is now possible to assess a model of imprinting in the chick both with regard to its fidelity to these properties and the behavioral effects they produce. With a variety of neuroanatomical, neurophysiological, and biochem- ical techniques, Horn, Bateson and their collaborators have established that a particular region of the chick forebrain, referred to as the interme- diate and medial part of the hyperstriatum ventrale (IMHV), is essential 'That is, young which are capable of fending for themselves from birth. Downloaded from http://www.mitpressjournals.org/doi/pdf/10.1162/neco.1994.6.3.357 by guest on 28 September 2021 Object Recognition and Sensitive Periods 359 for imprinting (see Horn 1985; Horn and Johnson 1989; Johnson 1991 for reviews). This region receives input from the main visual projection areas of the chick, and may be analogous to mammalian association cortex on both embryological and functional grounds (Horn 1985). From a Golgi study of the histology and connectivity of the IMHV by Tombol et al. (19881, we were able to determine that the principal anatomical features necessary for hysteresis of the principal excitatory cells of this region as proposed by OReilly and McClelland (1992) are present. These features, recurrent excitatory connections and lateral inhibition, constitute an es- sential component of our object recognition model. In addition, evidence consistent with a Hebbian learning rule operating in this region has been found in morphometric studies of synaptic modification and changes in the density of postsynaptic NMDA receptors (e.g., Horn et al. 1985; Mc- Cabe and Horn 1988). Thus, both the hysteresis and the Hebbian learning properties of our model could be present in the region of the chick brain thought to be responsible for object recognition. Behavioral data are valuable to the extent that they can be accounted for by only a subset of possible models. Thus, the finding that chicks learn something about an object to which they have been exposed for a period of time is not a particularly strong constraint. However, there are several findings from the imprinting literature that appear to require more specialized mechanisms. Perhaps the best known of these is the critical or sensitive period for imprinting. A sensitive period means that a strong preference for a given object can be established only during a specific period of life, and that the animal is relatively unaffected by sub- sequent exposure to different objects. This kind of behavior is not typical of neural network models, which typically exhibit strong (even “catas- trophic”) interference effects from subsequent learning. Further, Lorenz’s original theory has been revised to reflect the fact that the termination of the sensitive period is experience-driven (Sluckin and Salzen 1961; Bate- son 19661, so that one cannot simply posit a hard-wired maturational process responsible for terminating the sensitivity of the network. Our model shows how a self-terminating sensitive period is a consequence of a system incorporating hysteresis and a covariance Hebbian learning rule. Another constraining behavioral phenomenon derives from research on temporal blending. It has been shown that chicks will blend two ob- jects if they appear in close temporal proximity to each other (Chantrey 1974; Stewart et al. 1977). This temporal dependency alone is consistent with the idea that the object recognition system uses hysteresis to develop invariant representations of objects. However, our model demonstrates a paradoxical interaction between stimulus similarity and temporal blend- ing, such that more similar stimuli experience relatively less blending. This phenomenon can be directly related to the same hysteresis and co- variance Hebbian learning rule properties as the sensitive period phe- nomenon. Downloaded from http://www.mitpressjournals.org/doi/pdf/10.1162/neco.1994.6.3.357 by guest on 28 September 2021 360 Randall C. OReilly and Mark H. Johnson In order to claim that our model of object recognition is applicable to brains other than that of the domestic chick, we would need to find ev- idence of hysteresis and Hebbian associative learning in structures such as the mammalian visual cortex. Several lines of evidence are present. First, and most relevant for our model, the intracortical connectivity of the visual system contains recurrent excitatory connections and lateral inhibition (see Douglas and Martin 1990 for a review, and Douglas et 01. 1989; Bush and Douglas 1991 for models). There are also embryological