We rarely take the time to consider it, but our nervous systems are pretty amazing. Think about the differences among the senses of taste, smell, vision, hearing and touch. Yet, if you read the word tomato, you can easily conjure up the shape and color of a tomato. You can imagine its sweet, tart taste, the feel of the seeds in your mouth, the “splooch” sound it makes as you bite into it and its distinctive aroma.
Neuroscience explores questions such as how we are wired to perceive things in our environment, how the three-dimensional structures of our brains develop from a bunch of indistinguishable cells, the role of genes and the environment in development, what different molecules and chemical reactions are involved in the communication between nerve cells and what can go wrong with the nervous system.
Different questions require different methods and research tools to answer them, but there are some commonalities in the ways scientists go about figuring things out. Science textbooks often describe the scientific method as a series of steps that scientists follow to determine how the world works. The exact number and identity of the steps varies in different descriptions, but basically they are as follows.
- Develop a hypothesis.
- Come up with an experiment to test the hypothesis.
- Perform the experiment.
- Analyze the data.
- Draw conclusions about whether the hypothesis is valid or false.
More on the scientific method:
http://www.sciencebuddies.org/mentoring/project_scientific_method.shtml
A Simplified Scientific Method
Beyond “A” Method of Science
The list of steps in the scientific method is a useful way to think about how science progresses, but it is a simplification. Absent from the basic scientific method are the formal and informal interactions among scientists that are critical to the progress of science. It is frequently the published findings of other scientists that pique the interest of a researcher and drive him or her to generate a hypothesis. Researchers solicit the advice of their colleagues in designing experiments and analyzing data. Nearly all researchers also rely on tools and procedures that have been developed by others. This may include a specialized piece of equipment, such as those required for an MRI or a PET scan, or it could be a technique, such as the procedure that makes it possible to keep cells alive on a Petri plate so they can be studied. Alternatively, it might be the computer program that makes it practical to use advanced statistical methods to analyze the data. It is common for scientists to collaborate with colleagues from other disciplines because it often takes people with diverse expertise (mathematicians, computer programmers, engineers, biologists, psychologists, etc.) to design and conduct an experiment.
The Scientific Method and Interactions Among Scientists
The basic scientific method also gives the impression that the conclusions drawn from the data are uncontroversial and that the conclusions are simply archived and science moves on. However, in some ways, the publication of the results is more of a beginning than an end. In order to be published, the report about the experiment and results is reviewed by other scientists. If they think something is amiss, the researcher will need to address their concerns by providing clarifications or even performing additional experiments. Once the paper is published, other scientists will attempt to replicate the experiments, especially if the results are very important. This was the case when South Korean researchers published some very exciting results about embryonic stem cells. Although the experiments and results looked acceptable to the reviewers, further scrutiny of the published findings by the scientific community later revealed that the researchers had committed scientific fraud. Fortunately, scientists’ ethical standards and the fact that all findings are open to inspection make fraud uncommon.
Testimony about scientific fraud by Dr. Woo Suk Hwang:
http://www.hhs.gov/asl/testify/t060307a.html
Although scientific fraud is rare, there are still plenty of valid reasons for researchers to challenge research conclusions. The experiments students get to do in the classroom are often designed to have a “right” answer. Usually, they are meant to demonstrate a particular phenomenon that has been presented in the textbook or lecture. These experiments can be a useful learning experience, but they can also provide a misleading picture of what it means to do science.
If science really were this simple, scientists would have no reason to disagree with each other. Conclusions would follow logically from an experiment. However, in real science, there are many more caveats. For example, in an experiment in which people are receiving some type of treatment (medicine, vitamins, physical therapy, acupuncture), the placebo effect is an important concern. Placebo effect means that patients who think they are receiving a particular treatment may show improvement even if they are not receiving any treatment. To rule out this psychological effect, in trials to test a new drug, one group of people (the control group) is given fake pills, while another group (the experimental group) is given the real drug. However, it is more difficult to take care of the placebo effect when you are trying to test something other than pills. Hmmm, what exactly would fake acupuncture be?
Taking care of the placebo effect is just one example of trying to manipulate one variable while keeping all other variables the same. For example, in a drug trial you would also want your experimental and control groups to be equally healthy to begin with. Otherwise, any difference in their health at the end would not be due solely to the effects of the drug. Sometimes it is tricky to make sure the groups you are comparing are equivalent to begin with, especially if you are comparing naturally existing populations of people, plants or animals, or even (in other fields of science) stars, geological faults, glaciers, bodies of water, etc. So results may come into question if other scientists think differences in other variables could explain the results.
Junction (blue) between nerve (red) and muscle cells (green) in a frog.
Credit: Laura N. Borodinsky, UCSD
Drawing conclusions from data is not as straightforward as science textbooks often suggest. It is normal for scientists to offer possible alternative explanations. Brainstorming and discussions among scientists are essential to the healthy progress of science.
How Models Contribute to Scientific Progress
All scientists use models of one type or another. In your studies, you have probably come across various types of models: a model of the solar system, the Bohr model of the atom, climate models, molecular models, a model of a cell, etc. Models are useful for making concepts more visible and easier to understand. Some models, such as the Bohr model, are simplifications of reality. However, other models try to adhere much more closely to reality because scientists want to use them to make and test predictions. By doing this a researcher can determine whether or not all of the factors contributing to a phenomenon are adequately understood. For example, if the predictions made using a climate model turn out to be incorrect, this indicates that researchers do not adequately understand something, such as the effect of clouds on incoming heat from the sun. Alternatively, a neuroscientist’s attempt to predict behavior using a computer model might reveal a need to better understand the nerve communication between two areas of the brain.
In the life sciences, yet another kind of model is critical: model organisms. Model organisms are species used to study biological processes. Sometimes model organisms are used because it would be unethical to conduct a particular study on humans (such as to test how social deprivation affects brain development). More frequently, model organisms are used because they have particular advantages. For example, it is relatively easy to make changes to the genes of fruit flies to study the role of those genes in development. Yeast and bacteria are relatively simple and multiply quickly, and are therefore ideal for studying how organisms evolve over time. Mice and rats are mammals like us and share a similar physiology. Therefore, studies on them can help researchers understand questions such as how a medication affects the brain. Often multiple kinds of model organisms are used by different laboratories to study the same or related research questions. The findings of each laboratory may be complementary or contradictory, but either way they advance understanding.
More about Models in Science:
http://www.mcrel.org/epo/resources/sci_modeling.asp
Lesson Video
In the lesson video, Professor Spitzer discusses the process of science. He focuses on two important aspects: 1) model organisms and 2) the role that new research tools play in the advancement of science. After you watch the video, see “Explore this Topic” to check your understanding and do some critical thinking about the process of science.
