The neural control of looking

نویسنده

  • R.H.S Carpenter
چکیده

Saccades are the eye movements we make to look at objects. Apart from being astonishingly fast, often lasting little more than 20 milliseconds, they also happen to be the single most frequent movement we make, much commoner than heartbeats: we make two or three saccades every second of our waking lives. Saccades determine what we see, so their importance can hardly be exaggerated. The neural system that generates saccades has a particular interest as well. Because it is relatively simple, with inputs that can easily be manipulated and outputs we can measure with precision, our knowledge about how oculomotor signals are processed by specific neural structures is more quantitative and exact than for any other comparable part of the brain. In addition, it is a system that actually does something, a system with an output as well as an input — a microcosm of the brain itself. Like the brain, this system has a natural functional hierarchy that is reflected in its structure. The hierarchy extends from local control of the forces generated by individual muscles at the lowest levels, through the mechanisms for locating objects and directing movements towards them, to the highest level, at which decisions are made to move or not to move. While the eye is in motion it is effectively blind, so saccades have to be extremely fast. Yet because of friction and internal viscosity, the eyeball and the muscles that move it are intrinsically sluggish. If an oculomotor muscle suddenly increases its tension from one steady level to another, the eye may take almost half a second to reach its new equilibrium position. This means that a saccade as brief as 20 milliseconds cannot be generated simply by a step change in the activity of a muscle or the nerve fibres that innervate it. Recordings from oculomotor nerves during saccades show that something much more sophisticated occurs (Figure 1). During the saccade, they fire in a burst of maximal frequency, throwing the eye into its new position; the firing then settles down to the new rate required to hold it there. This complex pattern of activity is created when signals from two different types of neuron in the neighbouring brainstem meet at the motor neuron. Burst units fire in a rapid burst during saccades in a particular direction, while the activity of tonic units changes from one steady level to another in a way …

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

The Extraction of Influencing Indicators for Scoring of Insurance Companies Branches Based on GMDH Neural Network

O ne of the key topics and the most important tools to determine the strengths, weaknesses, opportunities and threats of each organization and company is the evaluation the performance of organizational activities that rating and ranking follows the internal and external goals. In this regard insurance companies similarly are looking for evaluation of their branches through scoring, ...

متن کامل

Pattern Recognition in Control Chart Using Neural Network based on a New Statistical Feature

Today for the expedition of the identification and timely correction of process deviations, it is necessary to use advanced techniques to minimize the costs of production of defective products. In this way control charts as one of the important tools for the statistical process control in combination with modern tools such as artificial neural networks have been used. The artificial neural netw...

متن کامل

An artificial Neural Network approach to monitor and diagnose multi-attribute quality control processes

One of the existing problems of multi-attribute process monitoring is the occurrence of high number of false alarms (Type I error). Another problem is an increase in the probability of not detecting defects when the process is monitored by a set of independent uni-attribute control charts. In this paper, we address both of these problems and consider monitoring correlated multi-attributes proce...

متن کامل

Sliding Mode with Neural Network Regulator for DFIG Using Two-Level NPWM Strategy

This article presents a sliding mode control (SMC) with artificial neural network (ANN) regulator for the doubly fed induction generator (DFIG) using two-level neural pulse width modulation (NPWM) technique. The proposed control scheme of the DFIG-based wind turbine system (WTS) combines the advantages of SMC control and ANN regulator. The reaching conditions, robustness and stability of the sy...

متن کامل

Dynamic Sliding Mode Control of Nonlinear Systems Using Neural Networks

Dynamic sliding mode control (DSMC) of nonlinear systems using neural networks is proposed. In DSMC the chattering is removed due to the integrator which is placed before the input control signal of the plant. However, in DSMC the augmented system is one dimension bigger than the actual system i.e. the states number of augmented system is more than the actual system and then to control of such ...

متن کامل

Construction cost estimation of spherical storage tanks: artificial neural networks and hybrid regression—GA algorithms

One of the most important processes in the early stages of construction projects is to estimate the cost involved. This process involves a wide range of uncertainties, which make it a challenging task. Because of unknown issues, using the experience of the experts or looking for similar cases are the conventional methods to deal with cost estimation. The current study presents data-driven metho...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • Current Biology

دوره 10  شماره 

صفحات  -

تاریخ انتشار 2000