Mental evolution: a review of Daniel Dennett’s From Bacteria to Bach and Back

From Bacteria To Bach and Back is an ambitious book that attempts to integrate a theory about the evolution of the human mind with another theory about the evolution of human culture. It is advertised as a defense of memes, but conceptualizes memes more liberally than has been done before. It is also advertised as a defense of the proposal that natural selection operates on culture, but conceptualizes natural selection as a process in which nearly all interesting parameters are free to vary. This liberal conception of key concepts creates space for philosophical innovation, but occasionally makes the empirical content of the theory difficult to pin down. Nevertheless, the book is full of scientific insight, wit, and humor. It will undoubtedly become a cause of both controversy and inspiration for those interested in naturalistic theories of human culture

Network Representation and Complex Systems

In this article, network science is discussed from a methodological per- spective, and two central theses are defended. The first is that network science exploits the very properties that make a system complex. Rather than using idealization techniques to strip those properties away, as is standard practice in other areas of science, network science brings them to the fore, and uses them to furnish new forms of explanation. The second thesis is that network representations are particularly helpful in explaining the properties of non-decomposable systems. Where part-whole decomposition is not possible, network science provides a much-needed alternative method of compressing information about the behavior of complex systems, and does so without succumbing to problems associated with combinatorial explosion. The article concludes with a comparison between the uses of network representation analyzed in the main discussion, and an entirely distinct use of network representation that has recently been discussed in connection with mechanistic modeling

What kind of information is brain information?

Nervous systems process information. This platitude contains an in- teresting ambiguity between multiple senses of the term “information.” According to a popular thought, the ambiguity is best resolved by reserv -ing semantic concepts of information for the explication of neural activity at a high level of organization, and quantitative concepts of information for the explication of neural activity at a low level of organization. This article articulates the justification behind this view, and concludes that it is an oversimplification. An analysis of the meaning of claims about Shannon information rates in the spiking activity of neurons is then developed. On the basis of that analysis, it is shown that quantitative conceptions of information are more intertwined with semantic concepts than they seem to be, and, partially for that reason, are also more philosophically interesting

Neural Reuse and the Nature of Evolutionary Constraints

In humans, the reuse of neural structure is particularly pronounced at short, task-relevant timescales. Here, an argument is developed for the claim that facts about neural reuse at task-relevant timescales conflict with at least one characterization of neural reuse at an evolutionary timescale. It is then argued that, in order to resolve the conflict, we must conceptualize evolutionary-scale reuse more abstractly than has been generally recognized. The final section of the paper explores the relationship between neural reuse and human nature. It is argued that neural reuse is not well-described as a process that constrains our present cognitive capacities. Instead, it liberates those capacities from the ancestral tethers that might otherwise have constrained them

What kind of information is brain information?

Nervous systems process information. This platitude contains an in- teresting ambiguity between multiple senses of the term “information.” According to a popular thought, the ambiguity is best resolved by reserv -ing semantic concepts of information for the explication of neural activity at a high level of organization, and quantitative concepts of information for the explication of neural activity at a low level of organization. This article articulates the justification behind this view, and concludes that it is an oversimplification. An analysis of the meaning of claims about Shannon information rates in the spiking activity of neurons is then developed. On the basis of that analysis, it is shown that quantitative conceptions of information are more intertwined with semantic concepts than they seem to be, and, partially for that reason, are also more philosophically interesting

Neural Reuse and the Nature of Evolutionary Constraints

In humans, the reuse of neural structure is particularly pronounced at short, task-relevant timescales. Here, an argument is developed for the claim that facts about neural reuse at task-relevant timescales conflict with at least one characterization of neural reuse at an evolutionary timescale. It is then argued that, in order to resolve the conflict, we must conceptualize evolutionary-scale reuse more abstractly than has been generally recognized. The final section of the paper explores the relationship between neural reuse and human nature. It is argued that neural reuse is not well-described as a process that constrains our present cognitive capacities. Instead, it liberates those capacities from the ancestral tethers that might otherwise have constrained them

Neural Information and the Problem of Objectivity

A fascinating research program in neurophysiology attempts to quantify the amount of information transmitted by single neurons. The claims that emerge from this research raise new philosophical questions about the nature of information. What kind of information is being quantified? Do the resulting quantities describe empirical magnitudes like those found elsewhere in the natural sciences? In this article, it is argued that neural information quantities have a relativisitic character that makes them distinct from the kinds of information typically discussed in the philosophical literature. It is also argued that despite this relativistic character, there are cases in which neural information quantities can be viewed as robustly objective empirical properties

Can we read minds by imaging brains?

Will brain imaging technology soon enable neuroscientists to read minds? We cannot answer this question without some understanding of the state of the art in neuroimaging. But neither can we answer this question without some understanding of the concept invoked by the term "mind reading." This article is an attempt to develop such understanding. Our analysis proceeds in two stages. In the first stage, we provide a categorical explication of mind reading. The categorical explication articulates empirical conditions that must be satisfied if mind reading is to be achieved. In the second stage, we develop a metric for judging the proficiency of mind reading experiments. The conception of mind reading that emerges helps to reconcile folk psychological judgments about what mind reading must involve with the constraints imposed by empirical strategies for achieving it