Morphology is not only a study of material things and of the forms of material things, but has its dynamical aspect, under which we deal with the interpretation, in terms of force, of the operations of energy.

(D’Arcy Wentworth Thompson—On Growth and Form 1942)

The main “object” studied by paleoneurologists in the last century was the endocranial cast. An endocast does not supply more information than the endocranium itself. Nonetheless, as primates, we base our perception largely on vision and touch, through the eye-hand circuit. A “cavity” is a non-object, and our senses are not comfortable with such empty space. That is probably why historically we relied on the positive mould of the endocranial cavity. Hence, we are used to studying a positive mould (the endocast) of the negative mould (the endocranial cavity) of an object (the brain with its vessels, meninges, and cerebrospinal fluid). It sounds a bit tricky and, in fact, it is. During this chain of biological and artificial moulding some information gets lost or altered. Furthermore, only the cortical elements of the brain and its general form can be inferred from its endocranial cast, and not every cortical trait is necessarily recorded onto the inner endocranial surface. Generally, an imprint is associated with an anatomical element, but the absence of the imprint is not necessarily associated with the absence of that element. Some specific sulci and gyri can be recognised (most of all at the surface of the frontal areas), as well as the traces of the middle meningeal artery and those of the venous sinuses of the dura mater (see Falk 1987). In smaller skulls, the traces of the cortical patterns are easy to see and recognize, with a remarkable correspondence between brain sulci and endocranial imprints (Kobayashi et al. 2014a). However, for larger brains like those of apes and humans, the traces can be smoother, and the patterns of convolution incomplete and difficult to interpret. Many cortical elements can leave faint or no traces on the endocranial wall. Most of all, it must be taken into account that most non-morphological characters cannot be studied on endocasts, and neither can most of the deeper brain structures. Therefore, a lot of caution must be taken when making brain inferences from endocasts. I recommend at least these four simple principles when dealing with paleoneurology: (1) an endocast does not add information compared to the endocranium; (2) an endocast is not the brain; (3) an endocast should not be studied without its skull; (4) an endocast is the rough geometrical result of dynamic interactions between soft and hard tissues.

Among the disciplines enhanced by digital anatomy and multivariate shape analysis, craniology is perhaps one of the fields which has been most improved by the development of these techniques. Soon after the introduction of software able to compute imaging and multivariate statistics with interfaces that are sufficiently usable for biologists, the neurocranium became object of a very large number of studies, mostly focusing on the evolution of the cranial form in our species (e.g., Lieberman et al. 2002; Zollikofer and Ponce de León 2002; Bookstein et al. 2003; Bruner et al. 2004). The same had occurred almost two centuries before, when the first biometricians found that anthropology and the cranial form represented a very effective case-study to test the first biometric approaches. The number of publications increased exponentially, moving from general heuristic surveys on the whole skull to more specific analyses aimed at evaluating the levels of integration and modularity of the anatomical systems (e.g., Rosas and Bastir 2002; Bastir et al. 2004; Hallgrissom et al. 2004). These toolkits were decisive in supporting a new renaissance in paleoneurology, through the application of geometrical models to the endocasts, using anatomical landmarks first (Bruner et al. 2003; Bruner 2004) and later by using the entire surfaces (Neubauer et al. 2009, 2010; Gunz et al. 2010). Even more importantly, these techniques make it possible to analyse the ultimate aim of these research fields, which is the study of the relationships between brain and braincase (Ribas et al. 2006; Richtsmeier et al. 2006; Bruner et al. 2014a; Kobayashi et al. 2014b).

In paleoneurology, the geometry of the brain is the key issue, being the only information available on the cerebral system of extinct species (Fig. 4.2). Traditionally, in morphometrics, the form of an object is theoretically divided into size (the dimension) and shape (the spatial organization). We can wonder whether or not these two components can be really separated in an analytical context, and if they have a real biological meaning. Nonetheless, distinguishing between these two factors may help at least to “dissect” the morphological organization of the anatomical systems. In paleoneurology, size refers to brain size, estimated by using the endocranial capacity as proxy. Of course, size is a crude measure of neural mass because it cannot separate the different volumetric components of the endocranial space: neurons, axons, vessels, glia, connectives, and cerebro-spinal fluid. When we detect brain size changes in evolution, we automatically assume that such changes increase the number of neurons, but there is no reason why this should be true and, therefore, all the alternatives should be carefully considered. Cell number, size, and density are surely relevant variables in primate encephalization (Herculano-Houzel 2012), but we should not forget that “brain” is not only about neurons.

Shape refers to the geometrical organization of the brain elements. Shape can change (in ontogeny and phylogeny) following at least two different processes: direct changes of some internal components (intrinsic changes) and indirect changes induced by external components (extrinsic changes). Intrinsic changes involve internal elements of the system, and they can be divided at least into two different types: proportional volumetric changes and spatial reorganization. In the first case, some elements change their volumes, and the geometry of the whole system is adjusted accordingly. In the second case, the volumes of the internal elements remain the same, but the elements are positioned in a different spatial relationship. Extrinsic changes are due to external factors, often through structural and biomechanical relationships: an external element changes its own shape or size and transmits the spatial change by pressures and tensions to neighbouring elements. Taking the special case of brain form into consideration, functional changes associated with form changes may be very diverse, often subtle, and probably integrated into a network of causes and consequences which may be very difficult to interpret. Volumetric changes of the brain cortex may be related to an increase or decrease in cell distribution (cell number, volume, or density) or in the number of connections. Furthermore, changes in the relative positions and proportions of the anatomical components may involve changes in geometry-dependent functions, like those influenced by the patterns of connectivity or heat dissipation (Bruner et al. 2012).

The interpretation of intrinsic and extrinsic factors depends upon the scale and the system we are observing and analyzing. The influences of the skull on brain form are extrinsic if we are analyzing the brain alone, but they may be intrinsic if we are analyzing the whole skull-brain system. Finally, we must remember that there are many changes, at very different levels, that remain silent to paleoneurological analysis because they do not affect the overall form. It is always important to take into account that in paleontology we only deal with form changes. Inferences on the underlying anatomical processes associated with those changes must be put forward integrating multiple biological data, as well as comparative studies on other primates.

Concerning brain form variation, we still have little information available because most of the research in neuroanatomy has focused only on the size component. The endocranial base angle is a major determinant of the brain’s spatial organization and packing (Lieberman et al. 2000; McCarthy 2001; Bruner and Jeffery 2007), and the neurocranial space is also strongly influenced by the facial block (Bastir and Rosas 2005; Bastir et al. 2004). In adult humans brain shape variation is not based on a few specific determinant patterns, but nonetheless the main axis of variability in the midsagittal plane is associated with bulging and flexion of the whole brain (Bruner et al. 2010). According to the same data, brain shape variation among adults has a negligible allometric component, it displays no apparent sexual differences, and there is no significant correlation between cortical and subcortical form variation. The lack of influent patterns of coviariance suggests again a scarce integration of the whole structure, probably determined by different and heterogeneous local factors. However, taking again into account the midsagittal plane, we can see that the bulging pattern, representing the most apparent shape component, is strictly associated with one single character: the relative longitudinal proportion of the medial parietal area, that is the precuneus (Bruner et al. 2014b; Fig. 4.3). In some cases the spatial relationships between brain and skull elements can be rather constant. For example, in macaques the arcuate sulcus generally approaches the coronal suture (Kobayashi et al. 2014b). Instead, in the case of the human bulging pattern it seems that skull and brain anatomical landmarks are more independent, and the geometric dilation of the precuneus changes the distance between cortical and bone references (Bruner et al. 2014a). Hence, the brain form influences the vault form, but the specific anatomical elements (sutures and circumvolutions) are more independent, and their reciprocal positions are not strictly determined. Apart from suggesting independence among these areas within the morphogenetic pathways, this information advises against excessively stringent inferences in paleoneurology on the position of the brain landmarks from the position of the sutures, at least in the case of the human vault.

Functional craniology deals mainly with anatomy and morphogenesis. Nonetheless, we must consider also the possibility to analyze indirectly those biological functions which present a correlation with morphology. Although indirect inferences may be incomplete and extrapolation/interpolation analyses need caution, they can provide essential information of functions which cannot be investigated otherwise. For example, brain morphology in modern humans displays a minor but consistent correlation with specific cognitive performances (Bruner et al. 2011a, b; Martín-Loeches et al. 2013). According to the patterns described for modern humans, values for extinct hominids can be tentatively extrapolated. More robust inferences can be put forward when the relationship between brain form and functions can be simulated through computed modelling, like in the case of endocranial heat dissipation (Bruner et al. 2012). Brain thermoregulation is one of the most relevant issues in brain biology, because of the vulnerability of the neural tissue to thermal changes, and the lack of apparent cooling systems (Brengelmann 1993; Cabanac 1993; Bertolizio et al. 2011). Brain metabolism and thermoregulation depend upon many factors, including cellular and systemic processes (Zhu et al. 2006; Karbowski 2009; Rango et al. 2012). Most of these factors cannot be considered in fossils, except one: form. In fact, heat dissipation patterns also depend upon the geometry of the object. Accordingly, using thermal models, we can simulate heat dissipation on the endocasts of extinct species, to evaluate whether brain form changes and differences may have influenced the heat distribution (Fig. 4.4). Specific regions of increased/decreased heat loading can be evidenced, and global and local values can be quantified and compared in living and extinct taxa.

The “skeleton”, as we see it in a Museum, is a poor and even a misleading picture of mechanical efficiency. From the engineer’s point of view, it is a diagram shewing all the compression-lines, but by no means all the tension-lines of the construction; it shews all the struts, but few of the ties, and perhaps we might even say none of the principal ones.

(D’Arcy Wentworth Thompson—On Growth and Form 1942)

The aim of functional craniology is to consider the skull as the result of a functional matrix, in which the final phenotype is moulded by forces exerted by the anatomical components (Moss and Young 1960). Pressures and tensions generated by muscles, connectives, bones, and organs, shape the morphology of the surrounding anatomical elements, and ultimately the organism itself. Such influences can be exerted through direct biomechanical effects, or by induction through activation/deactivation of physiological processes and molecular signalling. Bone deposition and resorption are sensitive to these kinds of mechanical stresses through the tensions and pressures exerted on the periosteal surfaces. The final phenotype is the balanced result of a network of forces, in which genes often give only general “commands” associated with cell proliferation and regulation. Such programs need to be opportunely coordinated by inner (integration) and outer (environmental) factors. Although some experimental evidence supports the functional matrix hypothesis (Moss 1968; Kyrkanides et al. 2011), the fine mechanisms regulating these processes are not known.

In paleoneurology, functional hypotheses based on structural relationships were present in the field since its beginning, as described by Veronika Kochetkova in the first chapter of her book “Paleoneurology”, a milestone in the history of this discipline (Kochetkova 1978). Providing a detailed review of the scattered (and largely ignored) literature on human brain evolution, paleontology, endocasts, and braincase anatomy, she discussed hypotheses linking brain and braincase morphogenesis with structural influences associated with sulci and gyry, cranial base flexion, cerebral pressure, meninges, vascular system, and cerebrospinsal fluid. Many of those hypotheses could not be tested at that time, and should be carefully reconsidered with the current theoretical and methodological perspectives.

In morphogenesis, we can separate at least theoretically changes in size (growth) and changes in shape (development). In the model proposed by Moss and Young (1960), changes in size of the neurocranium are mainly due to the pressure exerted by the underlying growing brain. On the other hand, changes in neurocranial shape are influenced by the redistribution and reorientation of these pressures according to the constraints of the main connective layers, which act as physical tensors. According to their perspective, the main endocranial connective tensors are the falx cerebri and the tentorium cerebelli, invagination of the meninges between the cerebral hemispheres and between the cerebrum and the cerebellum, respectively. The falx cerebri is anchored on the crista galli anteriorly, and on the internal occipital protuberance posteriorly, creating a sagittal sheet. The tentorium cerebelli is anchored on the temporal pyramids anteriorly, and on the internal occipital protuberance posteriorly, creating a transversal sheet. The major meningeal venous sinuses (namely the superior sagittal sinus and the transverse sinuses) follow the course of these two main connective sheets. Hence, the falx cerebri and the tentorium cerebelli are a structural interface between the brain cortex, the vascular network, and the endocranial bones, being the direct physical junction connecting these three systems.

Figure 4.5 provides a simple example of the possible biomechanical role of these elements. Blowing into a balloon will involve a change of size but not necessarily a change of its shape. Conversely, if a tape is fixed on its surface, at different sizes the balloon will have different shapes, because the tape will act as a tensor redistributing the growing forces. The first example represents an isometric trajectory: changes in size do not involve changes in shape. The second example represents an allometric trajectory: changes in size will involve changes in shape. In this latter case, the shape will change according to a given “model”, and hence the resulting morphologies are but different outputs of the same “program”. Despite the apparent variation, the different shapes at different sizes do not involve any structural change, being the phenotypic expression of the same underlying network. It is worth noting that exactly the same biomechanical approach can be applied at cellular levels, and neurons themselves can act as micro-tensors, shaping the cortex and the pattern of connection (Van Essen 1997; Toro and Burnod 2005; Hilgetag and Barbas 2005, 2006). Unfortunately, there is no clear evidence on how these biomechanical forces can be studied in an experimental context. Many pathological conditions involve many different components and factors, hampering a proper understanding of causes and consequences. Furthermore, although rare, many cases of partial ossification or calcification of the falx cerebri suggest that this condition is not associated with any kind of impairment or visible deformation, being generally discovered as incidental findings (Tubbs et al. 2006; Debnath et al. 2009). Melvin Moss (1959) proposed that the influence of these tensors in morphogenesis may be mediated by sutures, sensitive to mechanical induction through regulation and differentiation of cell activity. In fact, in the processes associated with neurocranial growth and development, the sutures may play an active role in coordinating the adjustments between brain and braincase, even if the actual mechanisms are poorly known (Anton et al. 1992; Henderson et al. 2004; Ogle et al. 2004; Zollikofer and Weissmann 2011). Sutures have both an active and passive role during braincase morphogenesis, acting like biomechanical components but also as an active interface between the connective tissues and the bony elements (Herring and Teng 2000; Herring 2008). The study of the sutures is a promising field in anthropology, paleontology, archaeology, and biomedicine, mostly if one considers the new toolkits associated with geometric modelling in anatomy, such as finite-element approaches or fractal analyses (Di Ieva et al. 2013).

Shape and size changes between brain and braincase during morphogenesis must be properly balanced to provide a functional phenotype. The final mechanisms behind skull morphogenesis are based on a fine regulation between bone deposition and bone reabsorption performed by osteoblasts and osteoclasts respectively. Hence, any imbalance between these two processes will lead to an excess or defect of ossification. These sub-optimal patterns of bone formation can be caused by unbalanced relationships between size changes and shape changes. If one of these two components cannot keep pace with the other, there can be the expression of non-pathological or sub-pathological morphological traits associated with an excess of bone deposition, or else with a defect of bone deposition (Manzi and Vienna 1997). In the first case (hyperostosis), osteoblasts deposit more bone than necessary, or osteoclasts do not eliminate the bone in excess, forming ridges or crests. In the second case (hypostosis), ossification cannot keep pace with the changes, leading to the formation of multiple centres of ossification (Wormian ossicle or supernumerary bones) and multiple or unfused sutures. Such characters, usually scored by their degree or prevalence of expression, are called “epigenetic traits”, and they can provide direct evidence of the morphogenetic processes underlying ontogeny and phylogeny in different cranial and endocranial areas. The dynamics and factors associated with these epigenetic traits are largely unknown, but they are generally used in archaeology, population biology, and forensic anthropology, as individual or group osteological markers (Hauser and De Stefano 1989). It must be observed that an excess of ossification is not usually interpreted as a suboptimal morphogenetic expression. In fact, many sexual characters or allometric traits are hyperostotic, being in some cases functional responses to mechanical forces (tension of muscles and tendons). In contrast, a defect in the ossification process is generally the consequence of constraints and difficulties in the normal morphogenetic pathway. In this sense, excess or defect of ossification should not be interpreted necessarily as the result of the same mechanisms in opposite directions, and further studies are necessary to investigate the factors behind these processes.

This neurocranial system is not isolated, and it must be integrated in the dynamics of the whole skull. The neurocranium has its anterior portion loaded on the facial block, and the posterior part loaded on the cranial base (Fig. 4.6). This makes the neurocranium sensitive to factors associated with many non-neural functions, like mastication, posture, or speech (Enlow 1990; Lieberman et al. 2000; McCarthy 2001; Bastir et al. 2004; Bastir 2008). Although we are used to making a distinction at least for pragmatic terminological reasons between neurocranium, face, and cranial base, the skull must be interpreted as a system with a given degree of integration, and this makes such terms rather conventional (Martínez-Abadías et al. 2012).

An example of structural association between cerebral lobes and cranial bones can be found in the spatial relationships between face and frontal lobes. In modern humans and Neanderthals, the prefrontal cortex lies almost entirely within the anterior fossa, which is at the same time the roof of the orbits. Hence, it is to be expected that the morphogenesis of the upper face and of the frontal brain areas will display a reciprocal influence, producing constraints due to this tight contact. Through the ontogenetic process, brain growth is associated with a rotation of the whole facial block under the braincase (Enlow 1990). In modern humans, this process may have reached its limit, because of the extreme reduction of the facial block and position under the orbital roof. In contrast, in most archaic human species, the frontal lobes lie behind the orbital roof, suggesting more independence between these two areas (Bruner and Manzi 2005). Another connection between face and neurocranium is represented by the ethmomaxillary complex, which is a direct biomechanical bridge between the midface and the cranial base (McCarthy 2001).

A recent hypothesis by Michael Masters supplies a relevant example of the degree of constraint possibly exerted by such structural relationships (Masters 2012). He suggested that, because of the physical relationships between orbits and frontal lobes, brain and eye can “compete” for the same space. Taking into consideration that the evolution of Homo sapiens was characterized by facial reduction and a shifting of the frontal lobes onto the orbital roof, such a relationship may have become “conflictive”. Eyeball volume is not strictly related to orbit size (Schultz 1940; Chau et al. 2004). Eye growth is, in fact, associated with brain growth through pleiotropic effects (Todd et al. 1940; Weale 1982; Mak et al. 2006), while orbit growth is associated with skull growth (Waitzman et al. 1992). That’s why in a species with reduced facial block and enlarged brain, these independent growth patterns may become conflictive, mostly when the orbits come into closer contact with upper (frontal) and posterior (temporal) brain areas. A deformation of the orbits as a consequence of these constraints may have been related to a deformation of the eyeball, involving myopia, a widespread defect of vision in our species. Current data confirm his hypothesis: the degree of myopia is correlated to orbital volume proportions, affecting to a larger degree those groups in which facial reduction and flattening are more expressed, such as women or Eastern Asian populations (Masters 2012). This example is outstanding because it provides a relationship between brain evolution, cranial evolution, and biomedical issues.

The cranial base is one of the main determinants of cranial morphogenesis and evolution, being influenced by many variables and at the same time exerting relevant constraints on face and braincase (Lieberman et al. 2000; Bastir and Rosas 2009; Bastir et al. 2010). Apart from shaping the general cranial architecture, the cranial base is in close contact with subcortical brain components like the midbrain thalamic areas. In primates, the position of many subcortical elements is influenced by the degree of flexion of the cranial base angle (Bruner and Jeffery 2007). The spatial organization of the subcortical elements can be partially influenced also by the posterior relationship with the tentorium cerebelli (Bruner et al. 2012), and it is scarcely related to the morphological variations of the cortical areas (Bruner et al. 2010).

Taking the lateral areas of the endocranial base into consideration, the temporal lobes represent an interesting example of relationships between brain and skull. Their anterior and lower areas are housed in the middle cranial fossa, which is positioned superiorly to the mandibular articulation. As a consequence, the morphology and position of the temporal poles may be partially influenced by factors involved in mastication jaw dynamics, as well as by their relationship with the anterior facial block (Bastir et al. 2004; Bastir and Rosas, 2005, 2006).