Aristotelian definitions versus empirical recognition criteria

An Aristotelian definition offers transparency regarding the semantic value (i.e., meaning) of its associated kind term through an ontological definition and provides an answer to the What is it? question. Whereas transparency regarding the meaning of a term is of invaluable importance for scientific communication, being able to unambiguously reference a kind term (i.e., correctly applying a term to a given real entity) is just as important. Unfortunately, Aristotelian definitions often do not provide sufficient information about the epistemologicalFootnote 2 appearance (diagnosis↑) of instances and lack specifications of the diagnostic properties that are required for scientists to successfully recognize and identify particular instances of the corresponding essentialistic class. The appearance, however, depends on the applied methods and techniques. Any knowledge about the ontological nature of a real entity is necessarily epistemological, as it always depends on empirical evidence and a chain of reasoning. Communication requires the specification of empirical recognition criteria that determine the cognitive representation of an entity’s appearance and thus provide answers to How does it look? questions.

The distinction between semantic conceptual content and reference and thus between ontological definition and empirical recognition criteria is important not only in biology, but in science in general. These two aspects are not identical, as the example of the Morning Star and the Evening Star demonstrates (or Clark Kent and Superman), which are co-referring expressions that refer to the same referent, which is the planet Venus (or a superhero character in a comic), but differ considerably in their semantic conceptual contents [61, 62].

Scientists who must identify particular structures, species, or diseases deal with this situation in their daily routines. For instance, lead (Pb) is defined as the element with the atomic number 82. This definition, however, does not provide a scientist with practically applicable criteria for empirically testing whether a given object is lead. A variety of methods and procedures has been developed to test for lead—empirical diagnostic knowledge that often has not been directly derived from the ontological definition. Therefore, for many real entities, our cognitive representations of them must be two-sided, because the ontological nature of a given real entity often does not coincide with its outward appearance.Footnote 3 The cognitive representation of a real entity should cover both its ontological nature and its empirical appearance.

This duality of cognitive representations must be reflected in two corresponding representational artifacts for their communication: 1) a textual ontological definition and 2) method- and instrument-dependent textual or perception-based recognition criteria. Both serve to order things into groups, the underlying idea being that the extension of the epistemological group coincides with that of the ontological group. And therefore, both must apply an appropriate grouping concept such as the essentialistic class concept.

The duality of cognitive representations directly relates to the distinction of inferential and referential lexical competence [64]. Inferential lexical competence↑ of a person depends on the person’s knowledge about the meaning of a term. Inferential lexical competence can be further differentiated into semantic inferential competence, which relates to natural language and formal logical Aristotelian definitions, and output inferential competence, which relates to the words and phrases (i.e., labels) used for referring to a specific concept [22]. Referential lexical competence↑ of a person, depends on the person’s knowledge about the typical appearance of instances of a kind, allowing them to recognize a portion of reality based on a given ‘factual’ description. Referential lexical competence can be further differentiated into naming referential competence, which refers to a person’s ability to select the right label (object is given → word must be found), and application referential competence, which refers to a person’s ability to select the right particular object for a given label (word is given → object must be identified) [64]. Whereas inferential lexical competence relies on a semantic system, referential lexical competence relies on a perceptual and motor system. Although these two systems are distinct, they both interact [22].

In the following, we demonstrate using anatomical examples that empirical recognition criteria cannot always be derived from ontological definitions and therefore require a separate specification.

Textual recognition criteria Recognizing a cell nucleus

According to its ontological definition (Table 1, Fig. 3), a cell nucleus is a cell organelle with a nucleolus, DNA, histones, and other proteins and a surrounding membrane, and it is located inside the cytoplasm of a eukaryotic cell. Identifying a cell nucleus inside a cell requires more information.

Without any staining techniques, if the tissue examined is unicellular or consists of only a few cell layers, bright-field, Nomarski interference, autofluorescent-based confocal laser scanning microscopy (CLSM), or phase contrast microscopy allows identifying the nucleus as a restricted compartment with a granular inner and a spherical outer shape (Fig. 5A-D; Table 2). The nucleolus can be identified as a more homogenous material with a circular outline. All four light microscopy methods are the most non-invasive methods that can be applied. In phase contrast microscopy, the nucleus appears as a restricted compartment with coarse inner material surrounded by a refracting sheath (Fig. 5D; Table 2), which makes this technique ideal for manipulating the DNA or for in-vitro fertilization.

Fig. 5

A-FAllium cepa (Amaryllidacea, Magnoliopsida), nucleus of epidermis cell visualized using bright-field (A, B), Nomarski (C), phase contrast microscopy (D), phase contrast plus fluorescence microscopy (E), and fluorescence microscopy (F). Nucleus was stained blue with Hoechst 33342 in E and F. Note prominent nucleoli in B and C. G-LRiseriellus occultus (Lineidae, Nemertea), fertilized egg cells. Due to the yolk content, the nucleus cannot be seen, neither with Nomarski contrast (G) nor with phase contrast microscopy, without being specifically stained (I). Hoechst 33342 stained chromosomes (blue, arrows) can be seen under a fluorescence microscope (H, L) that was combined with phase contrast microscopy in K. Note the fully condensed chromatin in the polar body (small arrow in H). M-RAllium cepa, root meristem, Nomarski microscopy, nuclei stained in red with Schneider carmine dye (carmine acetic acid). M differentiated nucleus. N-R mitotic stages (asterisks), a nuclear membrane is absent. N metaphase, O anaphase, P metaphase, Q late anaphase, R telophase. S-U Histological sections, Azan staining. SClymenura clypeata (Maldanidae, Annelida). Coelom with sperm cells (arrows) and adjacent gut epithelium (asterisks mark nuclei). TSalamander salamander (Amphibia, Craniota). Gut epithelium (asterisks mark nuclei, note red nucleolus). UBufo bufo (Amphibia, Craniota), tadpole. Medullary cord, ganglion cells (asterisks mark nuclei, note red nucleolus). V-Y Transmission electron microscopy, ultrathin (70 nm) sections, uranyl acetate plus lead citrate staining. VAchelia brevicauda (Pantopoda, Arthropoda), Embryo. Euchromatic (a) and heterochromatic (b) nuclei (asterisk marks nucleolus). WEpiperipatus biolleyi (Onychophora, Euarthropoda), embryo, epidermis with mitotic (a) and large heterochromatic (b) nuclei. XTetrastemma cerasinum (Nemertea). Meiotic cell (asterisk). YAmphiporus lactifloreus (Nemertea). Sperm nuclei (black)

Table 2 Diagnostic criteria of ‘cell nucleus’

Specific stains that interact with the DNA or with histones are used in fluorescent microscopy (Hoechst, Sytox) and histology (chromatin-specific stains such as carmine, hematoxilin, and others) for identifying the nucleus. Fluorescent stains that are specific for DNA and/or RNA exclusively result in a circular or ovoid coarse structure that emits light if illuminated with the wavelength specific for the chromophore used (Fig. 5; Table 2), irrespective of whether the DNA is unfolded (Fig. 5E, F) or condensed (Fig. 5H, L). Fluorescent microscopy may be combined with other non-invasive methods to localize the nucleus (Fig. 5E), especially when cell transparency is not given, as in yolky egg cells (Fig. 5K). Fixed tissue, if stained with dyes interacting with the histone proteins (Fig. 5M-U), allows identifying the nucleus as restricted compartment clustered or completely stained according to the dye used (Table 2). The nucleolus always shows homogenous staining which often is brighter than the histones.

The affinity of histones to acid staining is used in electron microscopy, where uranyl acetate is applied to visualize chromatin (Fig. 5V-Y). Using electron microscopy, the nucleus can be recognized as a compartment bound by a double layer of biomembranes that regularly line pores so that nucleoplasm and cytoplasm form a continuum (Fig. 4A). This can only be seen on the ultrastructural level. Here, the nucleus is also recognized by its chromatin that is either dispersed (euchromatin) or tightly (heterochromatin) or completely (sperm) packed, which causes irregular coarse, clustered, or complete electron-density after heavy metal staining (Fig. 5V, Y; Table 2). During mitoses, the affinity of the chromatin-specific staining allows identification of nuclear material although the nuclear membrane is absent (Fig. 5W, X). The condensed structure of metaphase chromosomes also allows their identification, even without staining, by using phase contrast or Nomarski microscopy (not shown).

Recognizing a neuron

According to its ontological definition, a neuron is defined as consisting of a soma and neurites and as having the disposition to conduct electric excitation across its outer membrane via voltage-dependent ion channels (Table 1, Fig. 3). Identifying an instance of ‘neuron’ therefore requires running experiments, which cannot be run using fixed tissue.

Alternatively, when isolated, neurons can be recognized in cell cultures by their shape using phase contrast or Nomarski microscopy, but histological techniques and electron microscopy are needed when they are clustered in a piece of tissue (Table 3). The soma of a neuron can be identified by its large size, but visualizing neurites differs tremendously between the methods used. Single neurites can be seen when using silver impregnation method (Golgi’s methods or Golgi stain). Perikarya and neurites are dark in these stainings.

Table 3 Diagnostic criteria of ‘neuron’

The perikaryon is a large globular or pear-shaped structure; the nucleus can generally not be discriminated within the perikaryal mass (Fig. 6A). Stronger portions of the neurites are stained, whereas finer branches are often not (Fig. 6B). A specific staining using fluorescent-labeled antibodies against neurotransmitters (serotonin, FMRF-amines, synapsin) or subcellular components (neurotubulin, neurofilaments) visualizes the entire neuron or specific parts within a given piece of tissue (Fig. 6C, D). This technique, however, allows identifying only neurons that contain known neurotransmitters. In AZAN or Masson-Goldner trichome stained histological sections, neuronal tracts can be identified within a brain and neurites be visualized, albeit they cannot be resolved in detail and are weakly stained (Fig. 6). Identification of bundles of neurites is easier if they are surrounded by matrix (small arrows in Fig. 6E, F). Electron microscopy allows resolving neurites in detail. Neurites can be identified by their small diameter, their dense packing, and especially by their subcellular components such as vesicles, neurofilaments, and tiny mitochondria (Fig. 6G, H). Perikarya of neurons contain a large spherical euchromatic nucleus, large mitochondria, and often numerous vesicles in the surrounding cytoplasm (Fig. 6I). In invertebrates, the nucleus may be surrounded by glial cells. In general, however, there is no unambiguous structural component that allows identifying a neuronal perikaryon in the electron microscope without 3-D reconstruction.

Fig. 6

Neurons and nervous system under various stainings. A, BLineus viridis (Nemertea), medullary cord. Silver impregnation. Note that not all neurons of a neuropile (NP) are stained (B). C, DCapitella teleta (Annelida). Anti 5HT with fluorescent secondary antibody. Note that perikaryon and neurite are stained (green). Terminal section of neurites is branched (D). E, FTetrastemma melanocephala (Nemertea), medullary cord. Azan staining (E) and Masson-Goldner-trichrome staining (F). Single neurons cannot be discriminated; perikarya of the neurons group mostly dorsal and ventral of the neuropile (NP). Neuropile and perikarya are separated by an ecm (extracellular matrix) called inner neurilemma (small arrows); groups of neurites can be seen piercing the inner neurilemma (asterisk). G-ICarinina ochracea (Nemertea), TEM. G Transverse section of several neurites. Note small spherical mitochondria (mi), neurofilaments (arrow), and dense core vesicles (v), probably containing serotonin (Trueta et al. 2012). H Sagittal section of the cephalic nerve with several neurites. Electron-density of neurites is slightly higher than in surrounding tissue. I Perikaryon with large euchromatic nucleus, peripheral neurosecretory vesicles, and large mitochondria. Perikarya are often surrounded by glial cells that are interconnected by desmosomes (arrow). gt glandular tissue, p perikaryon

Recognizing a receptor cell

A receptor cell converts a specific kind of stimulus or sensory input (external stimuli changing the conformation of membrane-bound proteins) into an active physiological event capable of initiating neuronal activity in another cell(s), usually as a change in electric potential. Receptor cells always pass neuronal activity to an effector (i.e., nerve cell, muscle cell, gland cell). The terminology is not uniform and either classifies receptors according to their structure or their function. In general, a receptor cell possesses a specific site to perceive the stimulus, called transducer herein, and a site to transmit the signal to a nerve cell. Concerning their location and anatomy, receptor cells fall into neuronal and epithelial receptor cells.

Neuronal receptor cells or receptor neurons are located in deeper tissue layers. Silver impregnation methods and 3D reconstruction of series of histological or ultrathin sections allow detecting receptor cells light- or electron-microscopically by having a free-end that lacks any connection to a synapse. In vertebrates, they can be recognized by their position (outside the central nervous system) and the absence of any myelin sheath and synapses.

Epithelial receptor cells are modified epithelial cells with an axon (primary sensory cells) or without an axon (secondary sensory cells). Epithelial receptor cells always face the exterior medium, the gut lumen, body cavities, or smaller compartments such as the optical cavity (Fig. 7B).

Fig. 7

Sensory cells under different stainings exemplified for photoreceptors. A-DLineus viridis (Nemertea), anterior end. A Bright-field microscopy. Note that shading pigment marks the photoreceptors (arrows). B Azan staining of 5 μm thick section, bright-field. Receptor cells (r) are partly surrounded by shading pigment cells (p). Asterisk marks receptive region that can easily be identified by its homogenous staining and its apical position; neither single receptor cells nor the structure of the receptive region can be identified. Arrow marks direction of incident light. C Transmission electron microscopy, sagittal section; eye outline marked by dashed line. Shading pigment cells contain numerous vesicles with electron grey to electron dark content. D Detail of the receptor cells (rc) that consists of a dendritic process with numerous apical microvilli (mv) and a single cilium (arrow). Both, cilium and microvilli are constitutive for a certain class of photoreceptor cells. Note differing electron density of the vesicle content shading pigment cells (pc). Arrow heads mark adhaerens junctions indicative for epithelial sensory cells

Modification generally enlarges the apical surface of epithelial receptors and causes branching, coiling, or ramification of the cilia, often along with altered axonemal and rootlet structures and/or elongation or branching of the microvilli (Fig. 7C). On the electron-microscopical level, they can be identified by apical adherence junctions linking them to neighboring cells (Fig. 7D). Under Nomarski contrast, they can easily be identified by their structure ([65] for olfactory cells). Silver impregnation methods that stain the axon allow detecting epithelial receptor cells if they are primary sensory cells. Certain epithelial receptor cells can be identified by antibody labelling against tubulin if the perceptive site is ciliary, or against neurotransmitters. Isolated secondary sensory cells can barely be discriminated from other epithelial cells since they lack an axon. Providing evidence for neurotransmitters is therefore decisive for identifying them. This can either be done by antibody labelling if the neurotransmitter is known [66]. Decisive identification of secondary sensory cells needs electron microscopy because 3D reconstruction allows identifying the postsynaptic processes penetrating the basal side of the secondary sensory cell and the neurotransmitter vesicles being located next to them [67].

Depending on the stimulus, receptor cells are classified as mechanoreceptors, chemoreceptors, photoreceptors, and others. Although the structure of the receptor cell is influenced by its specificity for a certain stimulus, such functional definitions pose problems on recognizing a member of a certain kind of receptor cell by its anatomy, since function and structure are not unambiguously correlated. Photoreceptors and chemoreceptors, for instance, possess enlarged surfaces such as modified microvilli [68, 69], so that this anatomical criterion cannot be used to discriminate between them. There are also receptor types that show differing anatomies, although their function is similar or identical. Mechanoreceptors are receptor neurons in the case of the muscle spindle or epithelial receptor cells in the case of the hair cells of the inner ear in vertebrates. Photoreceptors, finally, are secondary sensory cells in vertebrates, but primary sensory cells in several invertebrate taxa.

For most receptors, a combination of differential diagnosis and empirical comparative approaches are applied to unravel the potential function of a receptor if experimental approaches are not feasible. The structure of the transducer depends on its specificity for a certain stimulus, so that anatomy often allows inferring the function of receptor cells which are not experimentally accessible.

The problem of finding clearly specifiable spatio-structural recognition criteria for receptor cells reflects the general problem with specifying recognition criteria for functionally defined anatomical entities. Often, only physiological experiments can clearly identify a particular functionally defined anatomical entity. If such experiments cannot be conducted, morphologists are restricted to differential diagnostic and empirical comparative approaches coupled with conclusions based on analogy (Table 4).

Table 4 General diagnostic criteria of functional anatomical entities Perception-based recognition criteria

Iconic representational artifacts are often used in anatomy as the primary source of representation for communicating recognition criteria, as recognition criteria are often easier to convey in the form of visual examples than in the form of Aristotelian definitions and are essential for the training of diagnostic competence. Perception-based recognition criteria are also often used in taxonomic treatments through annotated images (Figs. 1, 2, 3, 4, 5, 6, 7 and 8).

Fig. 8

Lines and curves as diagnostic characters. A, B Shell outline differs between Cerastoderma edule (A) and Cerastoderma glaucum (B). Size differences refer to adult shells, arrow heads mark growth lines. C, D Truncate posterior end of the shell of Mya truncata (D) allows discriminating this species from its next relative, Mya arenaria (C). E-O Coiling of the gastropod shells causes sutures (arrows). Ridges, whorls, and outline a species-specific, despite difference in coloration. E-GLittorina littorea, dorsal view (E, F), drawing of ventral view (G). H-KNucella lapillus, dorsal view (H, I), drawing of ventral view (K). L-ONassarius reticulatus, dorsal view (L-N), drawing of ventral view (O). Note intraspecific variation in color, ridges, and curviness in the shown gastropod shells. P, Q Wing veins in Diptera (Hexapoda), d exemplifies one homologous field. PPhilonicus albiceps (Asilidae, Diptera). QMelanostoma mellinum (Syrphidae, Diptera). A, B, G, K, O modified from Hayward and Ryland [70]

By utilizing their natural relation of resemblance, perception-based recognition criteria demonstrate rather than denote the content to be communicated. In the following, we provide three examples where perception-based criteria are arguably more useful than Aristotelian definitions—in fact, Aristotelian definitions are not capable of efficiently communicating the diagnostic information.

Spatio-structural qualities

Many recognition criteria refer to specific spatio-structural qualities of anatomical entities. When having to define a term that refers to a specific spatio-structural quality, for instance, ‘mushroom-shaped’ or ‘ovoid’, we could try to textually define and describe the semantic conceptual content of the respective term, but this is often rather cumbersome and less comprehensible than simply visualizing its meaning through one or several exemplars—a picture is worth a thousand words. Anyone who has had to identify a species of a taxon that they were not familiar with using text-based keys knows how difficult it can be to make decisions based on textual criteria for shapes, colors, and relative positions, as opposed to using exemplary images.

Marine annelids, for instance, are generally identified on the species level according to the structure and arrangement of chaetae [71, 72]. These chaetae are extracellular structures that are formed by a single cell, the chaetoblast. Modification of the apical microvilli pattern of the chaetoblast during formation of the chaetae results in taxon-specific types of chaetae, which are discriminated by additional attributes like ‘hooked’, ‘falcate’, ‘falciger’, ‘winged’, ‘compound’ and others (Fig. 9). Due to the species-specificity of chaetae, these attributes are often insufficiently defined, so that pictures are used to provide an impression on what each attribute means.

Fig. 9

Chaetae in marine Annelida. A-H Schemes of falciger (A) and spiniger (E) compound chaeta and actual structure in different species. B-D Falcate compound chaetae under Nomarski contrast in Perinereis cultrifera (B), Platynereis dumerilii (C), Stenelais boa (D). F-HSpiniger compound chaetae in Platynereis dumerilii (Nomarski contrast, F), Perinereis cultrifera (bright-field plus chitin autofluorescence, G), Nereis diversicolor (SEM, H). I-P Schemes of hooked chaeta (I) and hooded hook (M) and actual structure in different species. K, L Hooked chaetae in Petaloproctus terricola at different ages (L older than K) (Nomarski contrast). N-P Hooded hooks in Dasybranchus caducus under Nomarski contrast (N) and the SEM (O), Lumbrineris tetraura (Nomarski contrast, P)

Identification, in general, becomes significantly easier if keys provide images to relate a structure, an area, or a particular pattern to a certain term. The structure, area, or pattern is not defined semantically, but only by providing one or several images, sometimes in the form of schematic drawings that abstract the structure or pattern and its position. Actually, text in identification keys and taxonomic descriptions can be understood to be limited to the purpose of serving as figure legends, only aiding the understanding and accessibility of perception-based recognition criteria. The images define the respective term based on an ostensive definition, communicating the meaning of the term by pointing to one or more exemplars, or in the case of drawings and schemas sometimes also to a somewhat abstracted type.

If a term describes a particular outward appearance of an anatomical entity, for instance its shape or form, its particular relative position, or the particular distribution pattern of a spatially scattered group of entities, its ontological definition and recognition criteria coincides. In such cases, it would make sense to define the term only ostensively through exemplary images and abandon Aristotelian definitions altogether.

Training diagnostic competence

When teaching zoology and medical science, the students have to see a lot of structures prior to being able to identify them in a new, thus far unknown organism. Typical examples are found in basic courses, when we explain the function of, for instance, a nucleus, describe its general structure, and even provide a definition including textual recognition criteria for identifying a nucleus (see 4.1.1), but then we will show different pictures of nuclei as examples. It is not easy to explain without showing examples, what ‘coarse inner material’ or ‘electron-dense clusters’ actually means. Although textual recognition criteria for ‘nucleus’ exist, we use visual exemplars to get the students familiar with variation and train their ability to identify nuclei. The competence to identify an anatomical structure will grow with the number of different exemplars shown and will establish the idea of a type in the form of a generalized cognitive representation of its outer appearance.

Diagnostic competence is of major relevance in various disciplines, including anatomy and medicine, particularly pathology. Although textual recognition criteria for diseases do exist, their individual expression in patients varies to a degree that requires visual, audio, and haptic training to gain familiarity with the possible variation-space among diagnostic characters. The reliability of diagnoses in medicine, therefore, grows with experience and thus with the number of examples seen and studied.

Terms that divide a continuum into (arbitrary) discrete classes

In anatomy, we are often dealing with a continuum of very similar forms, shapes, colors, and spatio-structural patterns. There is a continuum of degrees of concavity/invagination of a surface or a continuum of degrees of density of hair. Traditionally, such continua are partitioned into discrete classes, with each class having its own associated term. We then use these terms to indicate where in the continuum the anatomical entity we are currently looking at is located.

When, for instance, looking at a boundary line of some anatomical structure, we might want to express that this line is curved. Curviness, however, comes in degrees and with a direction (concave or convex). Any curved line is thus positioned within the corresponding continuum of variants of curviness (Fig. 1). Instead of coining various terms to specify, which degree of curviness applies to the given boundary line, and provide textual definitions for each of them, we can use exemplary images, assign to each such image a URI and refer to the respective URI when describing the curviness of a particular boundary line. The exemplary images and their corresponding URIs can be ordered into a linear sequence (see above) or positioned within an anatomical space and then positioned relative to each other within the continuum. Adding further exemplars in the future, because one realizes that the resolution is not fine-grained enough, would also be straight forward. In practice, when describing the curviness of a boundary line, a morphologist would not have to search for the correct term anymore, but instead look at the ordered sequence of exemplary images and choose the image that best matches with the given boundary line [73] or the two images in between which the boundary line can be located as ‘more curvy than’ and ‘less curvy than’. The same approach can also be used for providing perception-based recognition criteria for the identification of different states of a linear process, as for instance neurulation (see Fig. 2B).

Mental representation of semantic and perceptual knowledge

Language is an essential tool for thinking and we mentally represent knowledge in a propositional form, i.e., as statements. This points to the question of how we process and store contents in our brain, which refers to the format that our knowledge can take when we mentally represent experiences (see imagery debate [74]). We can distinguish different types of contents, for example propositional and visual contents. A given content could for example be conveyed in oral English or in written English. Similarly, visual contents could be described using words or depicted in an image. Experiments about mental imagery indicate that we store visual contents in depictive formats [74] that are useful for memory as they allow the brain to store visual information more efficiently without first having to translate it into propositional knowledge. Knowledge which is implicitly contained in an image can be recovered retrospectively, although it was not explicitly considered at the time of encoding (i.e., mentally storing the image) [74]. This is also in line with the experience that each of us has already had that we often have to visualize things as a mental image to be able to answer questions about them (e.g., What color has the door to your apartment? What shape are a cat’s ears?). These findings in cognitive science point to the importance of depictively coded cognitive representations of sensory experiences that function as low-level mental representations. Our brain can employ this knowledge and relate it to propositional language when need be.

Concepts of grouping in addition to Essentialistic classes

Our examples from anatomy and the findings in cognitive science show the importance of recognition criteria and that essentialistic classes do not cover all types of groupings morphologists are dealing with. Biological entities are the product of evolution and exhibit a considerable degree of variation and diversity. When we define an anatomical entity by a set of predicates, we must exclude many individual entities that lack one or more defining predicates. This problem relates to what Nietzsche addressed when he stated that “only something which has no history can be defined” [75]. If the Aristotelian definition is too broad, the essentialistic class includes too many variants and becomes meaningless, and if the definition is too narrow, the number of classes for completely representing biological diversity would be overwhelming. Therefore, when used as defining properties of a class, the recognition criteria themselves do not necessarily define an essentialistic class.

If we apply the different methods to visualize neurons to different representatives of a species, the artifacts caused by the method will likely vary according to the specific function of the neurons, their interaction with other neurons, and the age of the organism. In other words, although ‘neuron’ is ontologically defined as an essentialistic class, instances of ‘neuron’ cannot be consistently identified with the same methods. Therefore, the class that is defined by the set of recognition criteria of ‘neuron’ cannotbe represented as an essentialistic class. Another concept of grouping is required.

Comparative morphologists are routinely confronted with an even more complex situation if they, for instance, want to identify photoreceptor cells in representatives of different species. Although a photoreceptor cell can be ontologically defined as an essentialistic class with a specific set of essential properties,Footnote 4 no visualization method will be able to unravel all these properties at once. Each method applied will visualize certain particulars of the photoreceptors, which will likely not be identical across the different species. Depending on the life history stage of the studied organism, its species membership and the method used, each artifact will likely visualize a different subset of those properties that define the essentialistic class ‘photoreceptor’.

Among the defining properties of an essentialistic class ‘photoreceptor cell’ are functional dispositions. Functional dispositions, however, cannot be recognized without conducting physiological experiments, which are not only laborious but also invasive and may not be applicable in multi-species examinations. Instead, the presence of structural components or of special molecules in the signal transduction chain are interpreted as indices for the functional disposition. This interpretation is based on analogy and, thus, on abductive reasoning.

The type concept in biology

In addition to essentialistic classes, other concepts of grouping have been applied by morphologists that are often based on some type. Although the type concept has been controversially discussed in the past [76,77,78,79,80,81,82,83,84,85,86,87], it has always been an influential concept in biology.

The type concept in biology is heterogeneous and represents a whole family of different concepts, which should be clearly distinguished. Farber [