Abstract
The brain sciences seek to discover mechanisms by which neural activity is generated, thoughts are created, and behavior is produced. What makes us see, hear, feel, and understand the world around us? How can we learn intricate movements, which require continual corrections for minor variations in path? What is the basis of memory, and how do we allocate attention to particular tasks? Answering such questions is the grand ambition of this broad enterprise and, while the workings of the nervous system are immensely complicated, several lines of now-classical research have made enormous progress: essential features of the nature of the action potential, of synaptic transmission, of sensory processing, of the biochemical basis of memory, and of motor control have been discovered.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
One source of variation across trials is that the behavior of the monkey is not identical on every trial. For instance, the eyes may move along slightly different paths and at different rates. Even in preparations in vitro, however, identical current inputs to a neuron do not necessarily produce identical spiking outputs. This is due, at least in part, to the stochastic behavior of the movements of ions and molecules that govern the spiking mechanism.
- 2.
They used a random delay followed by a separate cue to move; this helped ensure that movement and anticipatory effects would not contaminate the processing effects of interest.
- 3.
Analyses of brain activity when the subject is resting (e.g., during passive eye fixation or with eyes closed) have been reported by many groups. See, for example, Fox et al. (2005), who used fMRI to describe two distinct resting-state networks.
- 4.
For a discussion of some ways that great equations of physics remain fundamental while only approximating the real world, see Weinberg (2002). An entry into the philosophical literature on statistical inference and modeling is Mayo and Spanos (2010).
- 5.
This point was emphasized by Mosteller and Tukey (1977, Section 1F).
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2014 Springer Science+Business Media New York
About this chapter
Cite this chapter
Kass, R.E., Eden, U.T., Brown, E.N. (2014). Introduction. In: Analysis of Neural Data. Springer Series in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-9602-1_1
Download citation
DOI: https://doi.org/10.1007/978-1-4614-9602-1_1
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4614-9601-4
Online ISBN: 978-1-4614-9602-1
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)