Thomas Schoenemann

Language has a fundamentally social function. Processes of human interaction along with domain‐general cognitive processes shape the structure and knowledge of language. Recent research in the cognitive sciences has demonstrated that patterns of use strongly affect how language is acquired, is used, and changes. These processes are not independent of one another but are facets of the same complex adaptive system (CAS). Language as a CAS involves the following key features: The system consists of multiple agents (the speakers in the speech community) interacting with one another. The system is adaptive; that is, speakers’ behavior is based on their past interactions, and current and past interactions together feed forward into future behavior. A speaker's behavior is the consequence of competing factors ranging from perceptual constraints to social motivations. The structures of language emerge …

Determining how the human brain differs from nonhuman primate brains is central to understanding human behavioral evolution. There is currently dispute over whether the prefrontal cortex, which mediates evolutionarily interesting behaviors, has increased disproportionately. Using magnetic resonance imaging brain scans from 11 primate species, we measured gray, white and total volumes for both prefrontal and the entire cerebrum on each specimen (n= 46). In relative terms, prefrontal white matter shows the largest difference between human and nonhuman, whereas gray matter shows no significant difference. This suggests that connectional elaboration (as gauged by white matter volume) played a key role in human brain evolution.

The human brain is one of the most intricate, complicated, and impressive organs ever to have evolved. Understanding its evolution requires integrating knowledge from a variety of disciplines in the natural and social sciences. Four areas of research are particularly important to this endeavor. First, we need to understand basic principles of brain evolution that appear to operate across broad classes of organisms. Second, we need to understand the ways in which human brains differ from the brains of our closest living relatives. Third, clues from the fossil record may allow us to outline the manner in which these differences evolved. Finally, studies of brain structure/function relationships are critical for us to make behavioral sense of the evolutionary changes that occurred. This review highlights important questions and work in each of these areas.

Hominid brain size increased dramatically in the face of apparently severe associated evolutionary costs. This suggests that increasing brain size must have provided some sort of counterbalancing adaptive benefit. Several recent studies using magnetic resonance imaging (MRI) have indicated that a substantial correlation (mean r = ≈0.4) exists between brain size and general cognitive performance, consistent with the hypothesis that the payoff for increasing brain size was greater general cognitive ability. However, these studies confound between-family environmental influences with direct genetic/biological influences. To address this problem, within-family (WF) sibling differences for several neuroanatomical measures were correlated to WF scores on a diverse battery of cognitive tests in a sample of 36 sibling pairs. WF correlations between neuroanatomy and general cognitive ability were essentially zero …

We develop a novel Lagrangian reference frame diffeomorphic image and landmark registration method. The algorithm uses the fixed Langrangian reference frame to define the map between coordinate systems, but also generates and stores the inverse map from the Eulerian to the Lagrangian frame. Computing both maps allows facile computation of both Eulerian and Langrangian quantities. We apply this algorithm to estimating a putative evolutionary change of coordinates between a population of chimpanzee and human cortices. Inter-species functional homologues fix the map explicitly, where they are known, while image similarities guide the alignment elsewhere. This map allows detailed study of the volumetric change between chimp and human cortex. Instead of basing the inter-species study on a single species atlas, we diffeomorphically connect the mean shape and intensity templates for each group …

It is commonly argued that the rules of language, as distinct from its semantic features, are the characteristics which most clearly distinguish language from the communication systems of other species. A number of linguists (e.g., Chomsky 1972, 1980; Pinker 1994) have suggested that the universal features of grammar (UG) are unique human adaptations showing no evolutionary continuities with any other species. However, recent summaries of the substantive features of UG are quite remarkable in the very general nature of the features proposed. While the syntax of any given language can be quite complex, the specific rules vary so much between languages that the truly universal (i.e. innate) aspects of grammar are not complex at all. In fact, these features most closely resemble a set of general descriptions of our richly complex semantic cognition, and not a list of specific rules. General principles of the …

Brain size scales with body size across large groups of animals, but exactly why this should be the case has not been resolved. It is generally assumed that body size is a general proxy for some more important or specific underlying variable, such as metabolic resources available, surface area of the body, or total muscle mass (which is more extensively innervated than is, e.g., adipose tissue). The present study tests whether brain size in mammals scales more closely with muscle mass (and other components of lean body mass) than with total fat. Felsenstein’s independent comparisons method was used to control for phylogenetic effects on body composition in organ weight data taken from a previously published comparative sample of 39 species in 8 different orders of mammals, all collected and processed by the same researchers. The analysis shows that the size of the central nervous system (CNS) is more …

The evolution of language and the evolution of the brain are tightly interlinked. Language evolution represents a special kind of adaptation, in part because language is a complex behavior (as opposed to a physical feature) but also because changes are adaptive only to the extent that they increase either one's understanding of others, or one's understanding to others. Evolutionary changes in the human brain that are thought to be relevant to language are reviewed. The extent to which these changes are a cause or consequence of language evolution is a good question, but it is argued that the process may best be viewed as a complex adaptive system, in which cultural learning interacts with biology iteratively over time to produce language.

The belief that syntax is an innate, autonomous, species-specific module is highly questionable. Syntax demonstrates the mosaic nature of evolutionary change, in that it made use of (and led to the enhancement of) numerous preexisting neurocognitive features. It is best understood as an emergent characteristic of the explosion of semantic complexity that occurred during hominid evolution.

Degree: Ph. D.DegreeYear: 1997Institute: University of California, BerkeleyHominid brain volume increased more than 3-fold in <svg aria-label="\sim " class="gs_fsvg" height="3px" style="vertical-align:2px;" width="11px"><g transform="matrix(0.01400, 0.00000, 0.00000, 0.01400, 0.00000, 5.13800)"><path d="M 143 272 Q 121 272 115 324 V 336 Q 115 494 209 623 T 455 752 Q 549 752 625 705 T 805 566 T 977 430 T 1137 387 Q 1218 387 1282 431 T 1382 548 T 1419 700 Q 1425 752 1448 752 Q 1471 752 1477 700 V 688 Q 1477 589 1435 492 T 1317 333 T 1137 272 Q 1043 272 970 316 T 794 453 T 618 591 T 455 637 Q 375 637 310 593 T 208 476 T 172 324 Q 166 272 143 272 Z " transform="scale(0.48828, -0.48828)"></path></g></svg>2.5 million years. From an evolutionary perspective, natural selection for one or more behavioral abilities is the most likely explanation. A large number of studies have demonstrated that brain volume is related to performance on standardized intelligence tests. The present study expands on this work in three important ways. First, a sibling-pair design is used, allowing for the calculation of independent within-family (WF) and between-family (BF) correlations. Second, a broader set of cognitive dimensions (specifically guided by an understanding of human evolution) is investigated. Third, neuroanatomical components are quantified from higher resolution 3D MR images (whole brain volume resolution of 1.3 mm <svg aria-label="\sp3). " class="gs_fsvg" height="15px" style="vertical-align:-4px;" width="15px"><g transform="matrix(0.01400, 0.00000, 0.00000, 0.01400, 0.00000, 11.58769)"><g><path d="M 233 160 Q 268 114 324 85 T 443 44 T 571 33 Q 658 33 715 78 T 798 198 T 825 356 Q 825 442 798 515 T 713 634 T 569 680 H 418 Q 410 680 402 687 T 395 702 V 723 Q 395 732 402 738 T 418 745 L 547 754 Q 653 754 717 858 T 782 1077 Q 782 1173 725 1232 T 571 1292 Q 487 1292 413 1267 T 291 1188 Q 334 1188 363 1154 T 393 1077 Q 393 1033 362 1001 T 285 969 Q 238 969 206 1001 T 174 1077 Q 174 1172 235 1236 T 388 1330 T 571 1360 Q 664 1360 760 1329 T 922 1234 T 989 1077 Q 989 950 905 855 T 694 717 Q 785 698 867 649 T 1001 525 T 1053 356 Q 1053 236 981 145 T 798 7 T 571 -41 Q 463 -41 358 -8 T 182 98 T 111 279 Q 111 329 145 362 T 229 395 Q 261 395 287 380 T 330 338 T 346 279 Q 346 230 313 195 T 233 160 Z " transform="matrix(0.34180, 0.00000, 0.00000, -0.34180, 0.00000, -362.89200)"></path></g><path d="M 133 -512 Q 115 -512 115 -494 Q 115 -485 119 -481 Q 469 -139 469 512 Q 469 1163 123 1501 Q 115 1506 115 1518 Q 115 1525 120 1530 T 133 1536 H 152 Q 158 1536 162 1532 Q 309 1416 407 1250 T 550 896 T 596 512 Q 596 367 571 226 T 493 -51 T 358 -303 T 162 -508 Q 158 -512 152 -512 H 133 Z " transform="matrix(0.48828, 0.00000, 0.00000, -0.48828, 398.60800, 0.00000)"></path><path d="M 172 113 Q 172 159 206 192 T 285 225 Q 313 225 340 210 T 382 168 T 397 113 Q 397 68 364 34 T 285 0 Q 240 0 206 34 T 172 113 Z " transform="matrix(0.48828, 0.00000, 0.00000, -0.48828, 787.49805, 0.00000)"></path></g></svg> The subject group consisted of 36 pairs of sisters.

The evolutionary process works by modifying pre-existing mechanisms, which makes continuity likely. A review of the evidence available to date suggests that there are many aspects of language that show evolutionary continuity, though the direct evidence for syntax and grammar is less clear. However, the universal features of grammar in modern human languages appear to be essentially descriptions of aspects of our basic conceptual universe. It is argued that the most parsimonious model of language evolution involves an increase in conceptual/semantic complexity, which in turn drove the acquisition of syntax and grammar. In this model, universal features of grammar are actually simply reflections of our internal conceptual universe, which are manifested culturally in a variety of ways that are consistent with our pre-linguistic cognitive abilities. This explains both why grammatical rules vary so much across languages, as well as the fact that the commonalities appear to be inherently semantic in nature. An understanding of the

A crucial component of research on brain evolution has been the comparison of fossil endocranial surfaces with modern human and primate endocrania. The latter have generally been obtained by creating endocasts out of rubber latex shells filled with plaster. The extent to which the method of production introduces errors in endocast replicas is unknown. We demonstrate a powerful method of comparing complex shapes in 3‐dimensions (3D) that is broadly applicable to a wide range of paleoanthropological questions. Pairs of virtual endocasts (VEs) created from high‐resolution CT scans of corresponding latex/plaster endocasts and their associated crania were rigidly registered (aligned) in 3D space for two Homo sapiens and two Pan troglodytes specimens. Distances between each cranial VE and its corresponding latex/plaster VE were then mapped on a voxel‐by‐voxel basis. The results show that between …

Understanding brain evolution involves identifying both the physical changes that occurred, as well as understanding the reasons for these changes. There are two ways in which inferences about evolutionary changes are made. By comparing a species of interest against other modern species, one can determine what exactly is different, and in what way it is different. By studying the fossil record, one assesses the time-course of evolutionary changes. Both of these approaches have strengths and weaknesses. Significantly more data are available from modern forms, both in terms of the number of species one can assess and the specific details and subtleties of the adaptations studied, parts of the brain, connectivity between regions, neurotransmitter systems, cytoarchitecture, integrated functioning, and so forth. However, one cannot unequivocally reconstruct the common ancestral states with this method because …

The existence of linked regularities in size among brain components across species is, by itself, not a strong argument against the importance of behavioral selection in brain evolution. A careful consideration of hominid brain evolution suggests that brain components can change their scaling relationships over time, and that behavioral selection was likely crucial. The best neuroanatomical index of a given behavioral ability can only be determined empirically, not through comparative analysis of brain anatomy alone.

Hominin cranial remains from the Dinaledi Chamber, South Africa, represent multiple individuals of the species Homo naledi. This species exhibits a small endocranial volume comparable to Australopithecus, combined with several aspects of external cranial anatomy similar to larger-brained species of Homo such as Homo habilis and Homo erectus. Here, we describe the endocast anatomy of this recently discovered species. Despite the small size of the H. naledi endocasts, they share several aspects of structure in common with other species of Homo, not found in other hominins or great apes, notably in the organization of the inferior frontal and lateral orbital gyri. The presence of such structural innovations in a small-brained hominin may have relevance to behavioral evolution within the genus Homo.