Evolving Brains

Given that all organisms share a common ancestry, why is it that they differ so greatly in their capacities to sense, remember, and respond to the world about them? How did we gain our ability to think and to feel? How do we differ from other organisms in these capacities? Our brain endows us with the faculties and the drive to ask these fundamental questions. The answers depend crucially on understanding how brains have evolved. This inquiry into brain evolution is interdisciplinary and multifaceted, based on converging evidence obtained from the study of the genetic regulation of development, the geological history of the earth, and the behavioral ecology of animals, as well as from direct anatomical and physiological studies of brains of animals of different species. From this investigation three themes will emerge: that the essential role of brains is to serve as a buffer against environmental variation; that every evolutionary advance in the nervous system has a cost; and that the development of the brain to the level of complexity we enjoy -- and that makes our lives so rich -- depended on the establishment of the human family as a social and reproductive unit. I will begin by considering one of the basic problems faced by all organisms: how to find food and avoid hazards in a constantly changing world. This leads to the question of how nervous systems detect and integrate the vast array of information available to them and derive from this flood of data adaptive behavioral responses. The evolution of nervous systems depended on a unique mechanism for communication, the action potential, a self-renewing electrical signal that moves along specialized neural fibers called axons that serve as the wires connecting nerve cells. By permitting the development of large nervous systems, this mechanism for neuronal communication made possible the emergence of complex and diverse forms of animal life

Religious Extremism: The Good, The Bad, and The Deadly

This paper challenges conventional views of violent religious extremism, particularly those that emphasize militant theology. We offer an alternative analysis that helps explain the persistent demand for religion, the different types of religious that naturally arise, and the special attributes of the %u201Csectarian%u201D type. Sects are adept at producing club goods both spiritual and material. Where governments and economies function poorly, sects often become major suppliers of social services, political action, and coercive force. Their success as providers is much more due to the advantages of their organizational structure than it is to their theology. Religious militancy is most effectively controlled through a combination of policies that raise the direct costs of violence, foster religious competition, improve social services, and encourage private enterprise.

The effects of technology on literacy(s)

One of the challenges when measuring the effects of technology on literacy(s) is finding a control group where technology; does not play a major role in the culture. The Amish successfully live in a Technocracy where mechanical/electronic tools are used only when absolutely necessary; the Amish are not dependent on them for survival. The crux of the Amish philosophy is humility, serving the community and serving God. Ironically, they have suffered tremendous repercussions for adopting a wholesome, selfless lifestyle which is contrary to most popular world views, regardless of religious or spiritual views --Purpose, page 40

The Evolution of Language Universals: Optimal Design and Adaptation

Inquiry into the evolution of syntactic universals is hampered by severe limitations on the available evidence. Theories of selective function nevertheless lead to predictions of local optimaliiy that can be tested scientifically. This thesis refines a diagnostic, originally proposed by Parker and Maynard Smith (1990), for identifying selective functions on this basis and applies it to the evolution of two syntactic universals: (I) the distinction between open and closed lexical classes, and (2) nested constituent structure. In the case of the former, it is argued that the selective role of the closed class items is primarily to minimise the amount of redundancy in the lexicon. In the case of the latter, the emergence of nested phrase structure is argued to have been a by-product of selection for the ability to perform insertion operations on sequences - a function that plausibly pre-dated the emergence of modem language competence. The evidence for these claims is not just that these properties perform plausibly fitness-related functions, but that they appear to perform them in a way that is improbably optimal. A number of interesting findings follow when examining the selective role of the closed classes. In particular, case, agreement and the requirement that sentences have subjects are expected consequences of an optimised lexicon, the theory thereby relating these properties to natural selection for the first time. It also motivates the view that language variation is confined to parameters associated with closed class items, in turn explaining why parameter confiicts fail to arise in bilingualism. The simplest representation of sequences that is optimised for efficient insertions can represent both nested constituent structure and long-distance dependencies in a unified way, thus suggesting that movement is intrinsic to the representation of constituency rather than an 'imperfection'. The basic structure of phrases also follows from this representation and helps to explain the interaction between case and theta assignment. These findings bring together a surprising array of phenomena, reinforcing its correctness as the representational basis of syntactic structures. The diagnostic overcomes shortcomings in the approach of Pinker and Bloom (1990), who argued that the appearance of 'adaptive complexity' in the design of a trait could be used as evidence of its selective function, but there is no reason to expect the refinements of natural selection to increase complexity in any given case. Optimality considerations are also applied in this thesis to filter theories of the nature of unobserved linguistic representations as well as theories of their functions. In this context, it is argued that, despite Chomsky's (1995) resistance to the idea, it is possible to motivate the guiding principles of the Minimalist Program in terms of evolutionary optimisation, especially if we allow the possibility that properties of language were selected for non-communicative functions and that redundancy is sometimes costly rather than beneficial

Primate social cognition: uniquely primate, uniquely social, or just unique?

Primates undoubtedly have impressive abilities in perceiving, recognising, understanding and interpreting other individuals, their ranks and relationships; they learn rapidly in social situations, employ both deceptive and cooperative tactics to manipulate companions, and distinguish others’ knowledge from ignorance. Some evidence suggests that great apes recognize the cognitive basis of manipulative tactics and have a deeper appreciation of intention and cooperation than monkeys; and only great apes among primates show any understanding of the concept of self. None of these abilities is unique to primates, however. We distinguish (1) a package of quantitative advantages in social sophistication, evident in several broad mammalian taxa, in which neocortical enlargement is associated with social group size; from (2) a qualitative difference in understanding found in several distantly related but large-brained species, including great apes, some corvids, and perhaps elephants, dolphins, and domestic dogs. Convergence of similar abilities in widely divergent taxa should enable their cognitive basis and evolutionary origins to be determined. Cortical enlargement seems to have been evolutionarily selected by social challenges, although it confers intellectual benefits in other domains also; most likely the mechanism is more efficient memory. The taxonomic distribution of qualitatively special social skills does not point to an evolutionary origin in social challenges, and may be more closely linked to a need to acquire novel ways of dealing with the physical world; but at present research on this question remains in its infancy. In the case of great apes, their ability to learn new manual routines by parsing action components may also account for their qualitatively different social skills, suggesting that any strict partition of physical and social cognition is likely to be misleading

General dynamics of the physical-chemical systems in mammals

Biodynamic regulator chain models for physical chemical systems in mammal

How research on language evolution contributes to linguistics

Since its inception in the second part of the 20th century, the science of language evolution has been exerting a growing and formative pressure on linguistics. More obviously, given its interdisciplinary character, the science of language evolution provides a platform on which linguists can meet and discuss a variety of problems pertaining to the nature of language and ways of investigating it with representatives of other disciplines and research traditions. It was largely in this way that the attention of linguists was attracted to the study of emerging sign languages and gestures, as well as to the resultant reflection on the way different modalities impact communicative systems that use them. But linguistics also benefits from the findings made by language evolution researchers in the context of their own research questions and methodologies. The most important of these findings come out of the experimental research on bootstrapping communication systems and the evolution of communicative structure, and from mass comparison studies that correlate linguists data with a wide range of environmental variables

Supporting meaningful social networks

Recent years have seen exponential growth of social network sites (SNSs) such as Friendster, MySpace and Facebook. SNSs flatten the real-world social network by making personal information and social structure visible to users outside the ego-centric networks. They provide a new basis of trust and credibility upon the Internet and Web infrastructure for users to communicate and share information. For the vast majority of social networks, it takes only a few clicks to befriend other members. People’s dynamic ever-changing real-world connections are translated to static links which, once formed, are permanent – thus entailing zero maintenance. The existence of static links as public exhibition of private connections causes the problem of friendship inflation, which refers to the online practice that users will usually acquire much more “friends” on SNSs than they can actually maintain in the real world. There is mounting evidence both in social science and statistical analysis to support the idea that there has been an inflated number of digital friendship connections on most SNSs. The theory of friendship inflation is also evidenced by our nearly 3-year observation on Facebook users in the University of Southampton. Friendship inflation can devalue the social graph and eventually lead to the decline of a social network site. From Sixdegrees.com to Facebook.com, there have been rise and fall of many social networks. We argue that friendship inflation is one of the main forces driving this move. Despite the gravity of the issue, there is surprisingly little academic research carried out to address the problems. The thesis proposes a novel algorithm, called ActiveLink, to identify meaningful online social connections. The innovation of the algorithm lies in the combination of preferential attachment and assortativity. The algorithm can identify long-range connections which may not be captured by simple reciprocity algorithms. We have tested the key ideas of the algorithms on the data set of 22,553 Facebook users in the network of University of Southampton. To better support the development of SNSs, we discuss an SNS model called RealSpace, a social network architecture based on active links. The system introduces three other algorithms: social connectivity, proximity index and community structure detection. Finally, we look at the problems relating to improving the network model and social network systems