Mechanisms of object recognition: what we have learned from pigeons

Jackdaws form categorical prototypes based on experience with category exemplars

Categorization represents one cognitive ability fundamental to animal behavior. Grouping of elements based on perceptual or semantic features helps to reduce processing resources and facilitates appropriate behavior. Corvids master complex categorization, yet the detailed categorization learning strategies are less well understood. We trained two jackdaws on a delayed match to category paradigm using a novel, artificial stimulus type, RUBubbles. Both birds learned to differentiate between two session-unique categories following two distinct learning protocols. Categories were either introduced via central category prototypes (low variability approach) or using a subset of diverse category exemplars from which diagnostic features had to be identified (high variability approach). In both versions, the stimulus similarity relative to a central category prototype explained categorization performance best. Jackdaws consistently used a central prototype to judge category membership, regardless of whether this prototype was used to introduce distinct categories or had to be inferred from multiple exemplars. Reliance on a category prototype occurred already after experiencing only a few trials with different category exemplars. High stimulus set variability prolonged initial learning but showed no consistent beneficial effect on later generalization performance. High numbers of stimuli, their perceptual similarity, and coherent category structure resulted in a prototype-based strategy, reflecting the most adaptive, efficient, and parsimonious way to represent RUBubble categories. Thus, our birds represent a valuable comparative animal model that permits further study of category representations throughout learning in different regions of a brain producing highly cognitive behavior.

Categorical representation of abstract spatial magnitudes in the executive telencephalon of crows

The ability to group abstract continuous magnitudes into meaningful categories is cognitively demanding but key to intelligent behavior. To explore its neuronal mechanisms, we trained carrion crows to categorize lines of variable lengths into arbitrary "short" and "long" categories. Single-neuron activity in the nidopallium caudolaterale (NCL) of behaving crows reflected the learned length categories of visual stimuli. The length categories could be reliably decoded from neuronal population activity to predict the crows' conceptual decisions. NCL activity changed with learning when a crow was retrained with the same stimuli assigned to more categories with new boundaries ("short", "medium," and "long"). Categorical neuronal representations emerged dynamically so that sensory length information at the beginning of the trial was transformed into behaviorally relevant categorical representations shortly before the crows' decision making. Our data show malleable categorization capabilities for abstract spatial magnitudes mediated by the flexible networks of the crow NCL.

Visual categories and concepts in the avian brain

Birds are excellent model organisms to study perceptual categorization and concept formation. The renewed focus on avian neuroscience has sparked an explosion of new data in the field. At the same time, our understanding of sensory and particularly visual structures in the avian brain has shifted fundamentally. These recent discoveries have revealed how categorization is mediated in the avian brain and has generated a theoretical framework that goes beyond the realm of birds. We review the contribution of avian categorization research-at the methodical, behavioral, and neurobiological levels. To this end, we first introduce avian categorization from a behavioral perspective and the common elements model of categorization. Second, we describe the functional and structural organization of the avian visual system, followed by an overview of recent anatomical discoveries and the new perspective on the avian 'visual cortex'. Third, we focus on the neurocomputational basis of perceptual categorization in the bird's visual system. Fourth, an overview of the avian prefrontal cortex and the prefrontal contribution to perceptual categorization is provided. The fifth section outlines how asymmetries of the visual system contribute to categorization. Finally, we present a mechanistic view of the neural principles of avian visual categorization and its putative extension to concept learning.

Surround Modulation Properties of Tectal Neurons in Pigeons Characterized by Moving and Flashed Stimuli

Simple Summary

Surround modulation is a basic visual attribute of sensory neurons in many species and has been extensively characterized in mammal primary visual cortex, lateral geniculate nucleus, and superior colliculus. Little attention has been paid to birds, which have a highly developed visual system. We undertook a systematic analysis on surround modulation properties of tectal neurons in pigeons (Columba livia). This study complements existing studies on surrounding modulation properties in non-mammalian species and deepens the understanding of mechanisms of figure–background segmentation performed by avians.

Abstract

Surround modulation has been abundantly studied in several mammalian brain areas, including the primary visual cortex, lateral geniculate nucleus, and superior colliculus (SC), but systematic analysis is lacking in the avian optic tectum (OT, homologous to mammal SC). Here, multi-units were recorded from pigeon (Columba livia) OT, and responses to different sizes of moving, flashed squares, and bars were compared. The statistical results showed that most tectal neurons presented suppressed responses to larger stimuli in both moving and flashed paradigms, and suppression induced by flashed squares was comparable with moving ones when the stimuli center crossed the near classical receptive field (CRF) center, which corresponded to the full surrounding condition. Correspondingly, the suppression grew weaker when the stimuli center moved across the CRF border, equivalent to partially surrounding conditions. Similarly, suppression induced by full surrounding flashed squares was more intense than by partially surrounding flashed bars. These results suggest that inhibitions performed on tectal neurons appear to be full surrounding rather than locally lateral. This study enriches the understanding of surround modulation properties of avian tectum neurons and provides possible hypotheses about the arrangement of inhibitions from other nuclei, both of which are important for clarifying the mechanism of target detection against clutter background performed by avians.

Lateralization in feeding is food type specific and impacts feeding success in wild birds

Current research suggests that hemispheric lateralization has significant fitness consequences. Foraging, as a basic survival function, is a perfect research model to test the fitness impact of lateralization. However, our understanding of lateralized feeding behavior is based predominantly on laboratory studies, while the evidence from wild animals in natural settings is limited. Here we studied visual lateralization in yellow-footed green pigeons (Treron phoenicoptera) feeding in the wild. We aimed to test whether different types of food objects requiring different searching strategies elicit different eye/hemisphere biases. When feeding on relatively large, uniformly colored food objects (mahua flowers) which can be present or absent in the viewed patch, the majority of pigeons relied mostly on the left eye-right hemisphere. In contrast, when feeding on smaller and more abundant food objects, with color cues signaling its ripeness (sacred figs), right-eye (left-hemisphere) preference prevailed. Our results demonstrate that oppositely directed visual biases previously found in different experimental tasks occur in natural feeding situations in the form of lateralized viewing strategies specific for different types of food. The results suggest that pigeons rely on the hemisphere providing more advantages for the consumption of the particular type of food objects, implying the relevance of brain lateralization as a plastic adaptation to ecological demands. We assessed the success of food discrimination and consumption to examine the link between lateralization and cognitive performance. The use of the preferred eye resulted in better discrimination of food items. Discrimination accuracy and feeding efficiency were significantly higher in lateralized individuals. The results showed that visual lateralization impacted pigeons' feeding success, implicating important fitness benefits associated with lateralization.

Recognition of natural objects in the archerfish

Recognition of individual objects and their categorization is a complex computational task. Nevertheless, visual systems can perform this task in a rapid and accurate manner. Humans and other animals can efficiently recognize objects despite countless variations in their projection on the retina due to different viewing angles, distance, illumination conditions and other parameters. To gain a better understanding of the recognition process in teleosts, we explored it in archerfish, a species that hunts by shooting a jet of water at aerial targets and thus can benefit from ecologically relevant recognition of natural objects. We found that archerfish not only can categorize objects into relevant classes but also can do so for novel objects, and additionally they can recognize an individual object presented under different conditions. To understand the mechanisms underlying this capability, we developed a computational model based on object features and a machine learning classifier. The analysis of the model revealed that a small number of features was sufficient for categorization, and the fish were more sensitive to object contours than textures. We tested these predictions in additional behavioral experiments and validated them. Our findings suggest the existence of a complex visual process in the archerfish visual system that enables object recognition and categorization.

Highlighted Article: Archerfish are capable of natural object recognition and categorization based on a small number of visual features.

Reaction to novelty as a behavioral assay of recognition memory in homing pigeons and Japanese quail

Spontaneous novelty preference is apparent in a wide array of animals, including mammals, birds, reptiles, and fish. This provides a powerful behavioral assay to assess whether an animal can recognize a diverse array of stimuli in a common paradigm. Surprisingly, no research has been conducted in birds using novelty approach under conditions comparable to the spontaneous object recognition (SOR) protocols that have become standard across other animals. To correct this, the current study adapts a number of SOR protocols commonly used in mammals to characterize novelty approach in Silver King pigeons and Japanese quail. We show that, in general, both quail and pigeons readily approach novel objects or locations when tested using SOR protocols, although pigeons show a neophilic response under some conditions in which quail do not. Neither quail nor pigeons readily approach objects in novel contexts or novel locations. These data show that SOR can be successfully adapted to birds, allowing for more direct comparison between mammals and birds in tasks of shared ecological relevance.

Five Breakthroughs: A First Approximation of Brain Evolution From Early Bilaterians to Humans

Retracing the evolutionary steps by which human brains evolved can offer insights into the underlying mechanisms of human brain function as well as the phylogenetic origin of various features of human behavior. To this end, this article presents a model for interpreting the physical and behavioral modifications throughout major milestones in human brain evolution. This model introduces the concept of a "breakthrough" as a useful tool for interpreting suites of brain modifications and the various adaptive behaviors these modifications enabled. This offers a unique view into the ordered steps by which human brains evolved and suggests several unique hypotheses on the mechanisms of human brain function.

Emergent categorization in the recognition of black and white paintings through conditional discrimination

Background

The emergent categorization involving paintings by renowned painters and their corresponding names was demonstrated by previous studies. However, the results of these studies suggest that the colors of the pictures may have played a preponderant role, obscuring other aspects of the stimuli that could be more directly related to the style of each painter. To verify this possibility, the present study used the same methodology of Ferreira et al. to investigate the establishment of emergent conditional relations between categories composed of black and white paintings and the names of their authors.

Method

The procedure consisted of the training of relations between each of the ten paintings and an abstract picture, for each of the three painters Botticelli, Monet, and Picasso. Relations between each of the three abstract figures and the printed name of one of the painters were verified in sequence. Finally, tests of relations between five trained and five untrained paintings of each artist and the printed names were conducted.

Results

The participants’ performance suggests that the outcome was properly controlled by aspects pertinent to the paintings that belonged to each painter’s category.

Conclusions

The results reinforced the data obtained previously with colored pictures, suggesting that the process of emergent categorization involving artificial categories of paintings is robust. It also indicates possibilities for future investigations, for example, using stimuli of other artistic productions, such as sculpture and music.

Comparison of pop-out responses to luminance and motion contrasting stimuli of tectal neurons in pigeons

The emergence of visual saliency has been widely studied in the primary visual cortex and the superior colliculus (SC) in mammals. There are fewer studies on the pop-out response to motion direction contrasting stimuli taken in the optic tectum (OT, homologous to mammalian SC), and these are mainly of owls and fish. To our knowledge the influence of spatial luminance has not been reported. In this study, we have recorded multi-units in pigeon OT and analyzed the tectal response to spatial luminance contrasting, motion direction contrasting, and contrasting stimuli from both feature dimensions. The comparison results showed that 1) the tectal response would pop-out in either motion direction or spatial luminance contrasting conditions. 2) The modulation from motion direction contrasting was independent of the temporal luminance variation of the visual stimuli. 3) When both spatial luminance and motion direction were salient, the response of tectal neurons was modulated more intensely by motion direction than by spatial luminance. The phenomenon was consistent with the innate instinct of avians in their natural environment. This study will help to deepen the understanding of mechanisms involved in bottom-up visual information processing and selective attention in the avian.

Measuring recognition memory in zebrafish larvae: issues and limitations

Recognition memory is the capacity to recognize previously encountered objects, events or places. This ability is crucial for many fitness-related activities, and it appears very early in the development of several species. In the laboratory, recognition memory is most often investigated using the novel object recognition test (NORt), which exploits the tendency of most vertebrates to explore novel objects over familiar ones. Despite that the use of larval zebrafish is rapidly increasing in research on brain, cognition and neuropathologies, it is unknown whether larvae possess recognition memory and whether the NORt can be used to assess it. Here, we tested a NOR procedure in zebrafish larvae of 7-, 14- and 21-days post-fertilization (dpf) to investigate when recognition memory first appears during ontogeny. Overall, we found that larvae explored a novel stimulus longer than a familiar one. This response was fully significant only for 14-dpf larvae. A control experiment evidenced that larvae become neophobic at 21-dpf, which may explain the poor performance at this age. The preference for the novel stimulus was also affected by the type of stimulus, being significant with tri-dimensional objects varying in shape and bi-dimensional geometrical figures but not with objects differing in colour. Further analyses suggest that lack of effect for objects with different colours was due to spontaneous preference for one colour. This study highlights the presence of recognition memory in zebrafish larvae but also revealed non-cognitive factors that may hinder the application of NORt paradigms in the early developmental stages of zebrafish.

Engineering a Less Artificial Intelligence

Despite enormous progress in machine learning, artificial neural networks still lag behind brains in their ability to generalize to new situations. Given identical training data, differences in generalization are caused by many defining features of a learning algorithm, such as network architecture and learning rule. Their joint effect, called "inductive bias," determines how well any learning algorithm-or brain-generalizes: robust generalization needs good inductive biases. Artificial networks use rather nonspecific biases and often latch onto patterns that are only informative about the statistics of the training data but may not generalize to different scenarios. Brains, on the other hand, generalize across comparatively drastic changes in the sensory input all the time. We highlight some shortcomings of state-of-the-art learning algorithms compared to biological brains and discuss several ideas about how neuroscience can guide the quest for better inductive biases by providing useful constraints on representations and network architecture.

Systematic Analysis of Pigeons' Discrimination of Pixelated Stimuli: A Hierarchical Pattern Recognition System Is Not Identifiable

Pigeons learned to discriminate two different patterns displayed with miniature light-emitting diode arrays. They were then tested with 84 interspersed, non-reinforced degraded pattern pairs. Choices ranged between 100% and 50% for one or other of the patterns. Stimuli consisting of few pixels yielded low choice scores whereas those consisting of many pixels yielded a broad range of scores. Those patterns with a high number of pixels coinciding with those of the rewarded training stimulus were preferred and those with a high number of pixels coinciding with the non-rewarded training pattern were avoided; a discrimination index based on this correlated 0.74 with the pattern choices. Pixels common to both training patterns had a minimal influence. A pixel-by-pixel analysis revealed that eight pixels of one pattern and six pixels of the other pattern played a prominent role in the pigeons’ choices. These pixels were disposed in four and two clusters of neighbouring locations. A summary index calculated on this basis still only yielded a weak 0.73 correlation. The individual pigeons’ data furthermore showed that these clusters were a mere averaging mirage. The pigeons’ performance depends on deep learning in a midbrain-based multimillion synapse neuronal network. Pixelated visual patterns should be helpful when simulating perception of patterns with artificial networks.

Beyond the "Conceptual Nervous System": Can computational cognitive neuroscience transform learning theory?

In the last century, learning theory has been dominated by an approach assuming that associations between hypothetical representational nodes can support the acquisition of knowledge about the environment. The similarities between this approach and connectionism did not go unnoticed to learning theorists, with many of them explicitly adopting a neural network approach in the modeling of learning phenomena. Skinner famously criticized such use of hypothetical neural structures for the explanation of behavior (the "Conceptual Nervous System"), and one aspect of his criticism has proven to be correct: theory underdetermination is a pervasive problem in cognitive modeling in general, and in associationist and connectionist models in particular. That is, models implementing two very different cognitive processes often make the exact same behavioral predictions, meaning that important theoretical questions posed by contrasting the two models remain unanswered. We show through several examples that theory underdetermination is common in the learning theory literature, affecting the solvability of some of the most important theoretical problems that have been posed in the last decades. Computational cognitive neuroscience (CCN) offers a solution to this problem, by including neurobiological constraints in computational models of behavior and cognition. Rather than simply being inspired by neural computation, CCN models are built to reflect as much as possible about the actual neural structures thought to underlie a particular behavior. They go beyond the "Conceptual Nervous System" and offer a true integration of behavioral and neural levels of analysis.

A Novel Method for Training Mice in Visuo-Tactile 3-D Object Discrimination and Recognition

Perceiving, recognizing and remembering 3-dimensional (3-D) objects encountered in the environment has a very high survival value; unsurprisingly, this ability is shared among many animal species, including humans. The psychological, psychophysical and neural basis for object perception, discrimination, recognition and memory has been extensively studied in humans, monkeys, pigeons and rodents, but is still far from understood. Nearly all 3-D object recognition studies in the rodent used the "novel object recognition" paradigm, which relies on innate rather than learned behavior; however, this procedure has several important limitations. Recently, investigators have begun to recognize the power of behavioral tasks learned through reinforcement training (operant conditioning) to reveal the sensorimotor and cognitive abilities of mice and to elucidate their underlying neural mechanisms. Here, we describe a novel method for training and testing mice in visual and tactile object discrimination, recognition and memory, and use it to begin to examine the underlying sensory basis for these cognitive capacities. A custom-designed Y maze was used to train mice to associate one of two 3-D objects with a food reward. Out of nine mice trained in two cohorts, seven reached performance criterion in about 20-35 daily sessions of 20 trials each. The learned association was retained, or rapidly re-acquired, after a 6 weeks hiatus in training. When tested under low light conditions, individual animals differed in the degree to which they used tactile or visual cues to identify the objects. Switching to total darkness resulted only in a transient dip in performance, as did subsequent trimming of all large whiskers (macrovibrissae). Additional removal of the small whiskers (microvibrissae) did not degrade performance, but transiently increased the time spent inspecting the object. This novel method can be combined in future studies with the large arsenal of genetic tools available in the mouse, to elucidate the neural basis of object perception, recognition and memory.

Cognitive flexibility and memory in pigeons, human children, and adults

This work examines cognitive flexibility using a comparative approach. Pigeons (Experiment 1), human children (Experiment 2a), and human adults (Experiment 2b) performed a task that required changing responses to the same stimuli twice across the experiment. The results indicate that all three groups demonstrated robust memory for learned information. In addition, pigeons showed comparable and substantial perseveration following both response shifts. In contrast, both children and adults exhibited some perseveration following a first response shift, while exhibiting no cost following the second response shift. These findings are discussed in relation to memory-based theories of cognitive flexibility, according to which perseveration occurs as a result of competition between long-term and working memory, revealing important differences in memory and cognitive flexibility between species.

Camouflage and Clutch Survival in Plovers and Terns

Animals achieve camouflage through a variety of mechanisms, of which background matching and disruptive coloration are likely the most common. Although many studies have investigated camouflage mechanisms using artificial stimuli and in lab experiments, less work has addressed camouflage in the wild. Here we examine egg camouflage in clutches laid by ground-nesting Snowy Plovers Charadrius nivosus and Least Terns Sternula antillarum breeding in mixed aggregations at Bahía de Ceuta, Sinaloa, Mexico. We obtained digital images of clutches laid by both species. We then calibrated the images and used custom computer software and edge detection algorithms to quantify measures related to three potential camouflage mechanisms: pattern complexity matching, disruptive effects and background color matching. Based on our image analyses, Snowy Plover clutches, in general, appeared to be more camouflaged than Least Tern clutches. Snowy Plover clutches also survived better than Least Tern clutches. Unexpectedly, variation in clutch survival was not explained by any measure of egg camouflage in either species. We conclude that measures of egg camouflage are poor predictors of clutch survival in this population. The behavior of the incubating parents may also affect clutch predation. Determining the significance of egg camouflage requires further testing using visual models and behavioral experiments.

Discrimination of human faces by archerfish (Toxotes chatareus)

Two rival theories of how humans recognize faces exist: (i) recognition is innate, relying on specialized neocortical circuitry, and (ii) recognition is a learned expertise, relying on general object recognition pathways. Here, we explore whether animals without a neocortex, can learn to recognize human faces. Human facial recognition has previously been demonstrated for birds, however they are now known to possess neocortex-like structures. Also, with much of the work done in domesticated pigeons, one cannot rule out the possibility that they have developed adaptations for human face recognition. Fish do not appear to possess neocortex-like cells, and given their lack of direct exposure to humans, are unlikely to have evolved any specialized capabilities for human facial recognition. Using a two-alternative forced-choice procedure, we show that archerfish (Toxotes chatareus) can learn to discriminate a large number of human face images (Experiment 1, 44 faces), even after controlling for colour, head-shape and brightness (Experiment 2, 18 faces). This study not only demonstrates that archerfish have impressive pattern discrimination abilities, but also provides evidence that a vertebrate lacking a neocortex and without an evolutionary prerogative to discriminate human faces, can nonetheless do so to a high degree of accuracy.

Promoting rotational-invariance in object recognition despite experience with only a single view

Different processes are assumed to underlie invariant object recognition across affine transformations, such as changes in size, and non-affine transformations, such as rotations in depth. From this perspective, promoting invariant object recognition across rotations in depth requires visual experience with the object from multiple viewpoints. One learning mechanism potentially contributing to invariant recognition is the error-driven learning of associations between relatively view-invariant visual properties and motor responses or object labels. This account uniquely predicts that experience with affine transformations of a single object view may also promote view-invariance, if view-invariant properties are also invariant across such affine transformations. We empirically confirmed this prediction in both people and pigeons, thereby suggesting that: (a) the hypothesized mechanism participates in view-invariance learning, (b) this mechanism is present across distantly-related vertebrates, and (c) the distinction between affine and non-affine transformations may not be fundamental for biological visual systems, as previously assumed.

Pigeons (Columba livia) as Trainable Observers of Pathology and Radiology Breast Cancer Images

Pathologists and radiologists spend years acquiring and refining their medically essential visual skills, so it is of considerable interest to understand how this process actually unfolds and what image features and properties are critical for accurate diagnostic performance. Key insights into human behavioral tasks can often be obtained by using appropriate animal models. We report here that pigeons (Columba livia)—which share many visual system properties with humans—can serve as promising surrogate observers of medical images, a capability not previously documented. The birds proved to have a remarkable ability to distinguish benign from malignant human breast histopathology after training with differential food reinforcement; even more importantly, the pigeons were able to generalize what they had learned when confronted with novel image sets. The birds’ histological accuracy, like that of humans, was modestly affected by the presence or absence of color as well as by degrees of image compression, but these impacts could be ameliorated with further training. Turning to radiology, the birds proved to be similarly capable of detecting cancer-relevant microcalcifications on mammogram images. However, when given a different (and for humans quite difficult) task—namely, classification of suspicious mammographic densities (masses)—the pigeons proved to be capable only of image memorization and were unable to successfully generalize when shown novel examples. The birds’ successes and difficulties suggest that pigeons are well-suited to help us better understand human medical image perception, and may also prove useful in performance assessment and development of medical imaging hardware, image processing, and image analysis tools.

Spontaneous object recognition: a promising approach to the comparative study of memory

Spontaneous recognition of a novel object is a popular measure of exploratory behavior, perception and recognition memory in rodent models. Because of its relative simplicity and speed of testing, the variety of stimuli that can be used, and its ecological validity across species, it is also an attractive task for comparative research. To date, variants of this test have been used with vertebrate and invertebrate species, but the methods have seldom been sufficiently standardized to allow cross-species comparison. Here, we review the methods necessary for the study of novel object recognition in mammalian and non-mammalian models, as well as the results of these experiments. Critical to the use of this test is an understanding of the organism's initial response to a novel object, the modulation of exploration by context, and species differences in object perception and exploratory behaviors. We argue that with appropriate consideration of species differences in perception, object affordances, and natural exploratory behaviors, the spontaneous object recognition test can be a valid and versatile tool for translational research with non-mammalian models.

Using the reassignment procedure to test object representation in pigeons and people

In four experiments, we evaluated Lea's (1984) reassignment procedure for studying object representation in pigeons (Experiments 1-3) and humans (Experiment 4). In the initial phase of Experiment 1, pigeons were taught to make discriminative button responses to five views of each of four objects. Using the same set of buttons in the second phase, one view of each object was trained to a different button. In the final phase, the four views that had been withheld in the second stage were shown. In Experiment 2, pigeons were initially trained just like the birds in Experiment 1. Then, one view of each object was reassigned to a different button, now using a new set of four response buttons. In Experiment 3, the reassignment paradigm was again tested using the number of pecks to bind together different views of the same object. Across all three experiments, pigeons showed statistically significant generalization of the new response to the non-reassigned views, but such responding was well below that to the reassigned view. In Experiment 4, human participants were studied using the same stimuli and task as the pigeons in Experiment 1. People did strongly generalize the new response to the non-reassigned views. These results indicate that humans, but not pigeons, can employ a unified object representation that they can flexibly map to different responses under the reassignment procedure.

Object similarity affects the perceptual strategy underlying invariant visual object recognition in rats

In recent years, a number of studies have explored the possible use of rats as models of high-level visual functions. One central question at the root of such an investigation is to understand whether rat object vision relies on the processing of visual shape features or, rather, on lower-order image properties (e.g., overall brightness). In a recent study, we have shown that rats are capable of extracting multiple features of an object that are diagnostic of its identity, at least when those features are, structure-wise, distinct enough to be parsed by the rat visual system. In the present study, we have assessed the impact of object structure on rat perceptual strategy. We trained rats to discriminate between two structurally similar objects, and compared their recognition strategies with those reported in our previous study. We found that, under conditions of lower stimulus discriminability, rat visual discrimination strategy becomes more view-dependent and subject-dependent. Rats were still able to recognize the target objects, in a way that was largely tolerant (i.e., invariant) to object transformation; however, the larger structural and pixel-wise similarity affected the way objects were processed. Compared to the findings of our previous study, the patterns of diagnostic features were: (i) smaller and more scattered; (ii) only partially preserved across object views; and (iii) only partially reproducible across rats. On the other hand, rats were still found to adopt a multi-featural processing strategy and to make use of part of the optimal discriminatory information afforded by the two objects. Our findings suggest that, as in humans, rat invariant recognition can flexibly rely on either view-invariant representations of distinctive object features or view-specific object representations, acquired through learning.