Prospects for a Reductionist Neuroscience Term Paper

Download this Term Paper in word format (.doc)

Note: Sample below may appear distorted but all corresponding word document files contain proper formatting

Excerpt from Term Paper:

Reductionism in Cognitive Neuroscience

Cognitive science is an interdisciplinary field encompassing various aspects of the study of the mind, including perception, reasoning, language, emotion and consciousness. Departing from the strictures of behaviorism, cognitive science permitted experimental psychologists to theorize beyond the limitations of observable behavior and functional relations between stimulus and response, and to posit internal mental representations as legitimate objects for scientific inquiry. With advances in neuroimaging technology, cognitive psychology became increasingly integrated with neuroscience. The analysis of subjective psychological experience in terms of physiological activity in the brain is understood as "reductionist," because it explains a "higher" order psychological phenomena (thinking, remembering, perceiving) in terms of a more basic physiological substrate (neurons firing).

This paper explores reductionistic approaches to cognitive science. Reductionism in cognitive science has both proponents and detractors. On the one end of the spectrum, John Bickle makes a case for "ruthless reductionism" -- the project of fully explaining cognitive phenomena such as thoughts, memory, attention, and even consciousness in terms of molecular biology. On the other end of the spectrum, cognitive scientists such as Anthony Chemero and Charles Heyser contend that an adequate scientific explanation of certain aspects of cognition will never be fully reduced to genetic or neurological processes, and that to try to force an explanation of all mental activity into such a reductionistic account will lead to bad science.

What is reductionism?

In order to understand what cognitive scientists mean by psycho-neural reductionism, imagine a hierarchy of observable phenomena that function at different levels. Subjective thought processes observable through introspection -- such as remembering the past, imagining places or people, or planning for the future -- represent the highest, most complex level of phenomena that cognitive scientists wish to explain. Since cognitive science is naturalistic in its assumptions, subjective states of mind must be somehow dependent on the firing of neurons in the brain. Whereas memories, feelings and symbolic thoughts have traditionally been considered to be "nonphysical" in some sense, the brain as a physical organ of thought is amenable to dissection or clinical observation in action using an fMRI. Accounting for higher level conscious processes in terms of more basic physiological processes of the brain can be considered a reduction of complex psychological phenomena into more fundamental biological substrate.

The brain can in turn be reduced to more basic biological components. The encephalon consists of neural tissue, which is a collection of cells, which in turn consist of proteins, which in turn are produced by the activity of DNA. Following the logic of reducing a complex thing to the interactions of its constituent parts, consciousness may be reduced to the functioning of a brain, the brain to a complex of neurons, the neurons to proteins, the proteins to RNA, the RNA to molecules. A ruthlessly reductive explanation might in principle be able to show a tight connection between thought at the highest level and the activity of DNA molecules at the lowest.

A related concept to reduction is emergence (O'Connor and Wong). If strict reductionism claims that a complex system is nothing but the sum of its parts, emergence claims that at a certain level of complexity, new properties emerge making the whole greater than the mere sum of its parts.

An observed phenomenon is understood as "emergent" if it appears different in kind from anything that can be found or observed when you break the system down to simpler pieces. The concept of non-emergence can be traced back to Ancient Greek philosophy. The Roman Atomist Lucretius attributed the doctrine of homeomeria to the Greek philosopher Anaxagoras (Patzia). In Lucretius'account, Anaxagoras assumed that the infinitesimally small units which constitute an object must have the same properties as the object. So atoms of water must be wet, atoms of iron must be hard, atoms of rose petals must be red, and so on. No matter how small you break down matter into its component pieces, the observable properties of the macro-object continue to be found at the lower levels. This misconception illustrates the fallacy of division, which is the false assumption that an attribute or quality of a whole object must also be an attribute or quality of its constituent parts.

Since we now know that physical qualities such as color or wetness do not describe matter at the molecular level, we can understand emergent properties as qualities that arise from the interactions of a system's component parts. At a certain level of complexity, smaller constituents of a system interact to produce patterns or phenomena that are not an aspect of those components in isolation. The new properties only emerge through interaction at a higher level of organization.

While a reductionistic explanation of a complex phenomenon into more fundamental processes is a goal of science, emergent phenomena at higher levels of organization must also be recognized to exist.

Ruthless reductionism and the Science of Research

John Bickle is a strong advocate for reducing neuroscientific research to the most basic explanatory level -- the actions of single cells, controlled ultimately by genetic switches. Bickle surveys research into the cellular basis of working memory, a feature of conscious experience. The scope of Bickle's reductionism proceeds from mind to molecule.

Bickle is a scientific optimist. He points to recent advances in neuroimaging techniques and successful reductionistic accounts of evolutionary and developmental processes in biology to the activity of DNA molecules. He predicts that cognitive science will enjoy similar success by following similar strategies. The ultimate goal of the reductionist cognitive neuroscience is to explain all behavior, cognition, and even consciousness itself in terms of molecular biology. Bickle calls this "ruthless reductionism."

Bickle co-wrote with Alcino Silva an assessment of the current state of cognitive neuroscience. In their review, Silva and Bickle make suggestions for reforming the field along scientific lines so that more neuroscientists will pursue reductionist research agendas.

Science historian Thomas Kuhn proposed some general principles for how science advances as newer, more general paradigms with greater explanatory power displace older paradigms. Silva and Bickle find Kuhn's analysis too relativistic. They criticize the history and sociology of the science for its lack of scientific methodology. In place of the sociology of science, they propose a new scientific discipline called the "science of research" (SR).

SR entails less speculative philosophy of how science works, and more systematic hypothesis-testing. It is a results-oriented model that is itself scientific. Rather than studying general principles, Silva and Bickle propose conducting empirical investigations of particular research programs to provide practical advice for how to improve outcomes and advance the state of knowledge. For Silva and Bickle, a key goal of science is to explain natural phenomena by establishing networks of causal connections (108).

Mechanisms vs. Laws

In aiming to make the discipline of cognitive science more rigorously scientific, several authors warn against modeling cognitive research too closely on physics. As cognitive science must account for emergent phenomena of the mind and social behavior, aspects of mental phenomena may require types of explanations not used in scientific descriptions of the physical world. For example, while physics relies on causal laws, such as Newtonian mechanics, the cognitive science describes its subject matter in terms of "mechanisms." Mechanisms are conceived as computational programs and include such things as modules, networks, pathways, systems and substrates (Robins and Craver 42).

Neuroscientists structure their analysis into an ontological dualism, designating two types of mechanism: entities and activities. Computational programs of the mind thus analogize to the computer software. Neuroscience also contains an analogy to hardware -- its "entities" are the "wetware" of the brain -- the physical substrate of neural networks that enable all mental activity.

In order to illustrate how biological mechanisms can be appealed to for a scientific explanation of subjective experience and observable behavior, Sarah Robins and Carl Craver use the example of circadian rhythms, which are sleep wake cycles controlled by biological clocks. Circadian rhythms are regulated by the periodic release of hormones such as melatonin, which control sleepiness, body temperature, mood, etc. The cycles continue to function even if an organism is in an aperiodic environment, such as a cave, where external cues such as sunlight cease to influence them.

The regular release of hormones, changes in blood pressure and body temperature associated with the sleep-wake cycle can be further explained by the genes that code for the proteins that make up this elaborate system. Thus, the mechanistic explanation of the sleep-wake cycle offers an example of scientific reduction of a psychological phenomenon.

William Bechtel also agrees that cognitive neuroscience should aim for mechanistic explanations of psychological phenomena (13). Mechanistic explanations may be reductionist, since they allow for analyzing a mechanism into its component parts, and then explaining their functioning by the level of physical processes immediately below them. The mechanistic approach entails identification of brain regions responsible for particular mental phenomena. While Bechtel agrees that an account of genes and proteins completes the picture, he still distinguishes levels of explanation (38). To illustrate different levels of analysis in neuroscience,…[continue]

Cite This Term Paper:

"Prospects For A Reductionist Neuroscience" (2011, April 26) Retrieved December 8, 2016, from http://www.paperdue.com/essay/prospects-for-a-reductionist-neuroscience-119476

"Prospects For A Reductionist Neuroscience" 26 April 2011. Web.8 December. 2016. <http://www.paperdue.com/essay/prospects-for-a-reductionist-neuroscience-119476>

"Prospects For A Reductionist Neuroscience", 26 April 2011, Accessed.8 December. 2016, http://www.paperdue.com/essay/prospects-for-a-reductionist-neuroscience-119476


Read Full Term Paper
Copyright 2016 . All Rights Reserved