Information-Theoretical Analysis of Sensory Information

It is clear that, in order to survive, organisms must exchange information between the body and its environment as well as between different body parts. They do so via various systems employing different means, one being the nervous system. At the nervous system’s periphery, sensory neurons transduce a physico-chemical analog signal into a train of discrete action potentials (spike trains), which can be transmitted over long distances. A similar process also occurs within the central nervous system as most neurons need to transduce their synaptic potentials, i.e., analog signals, into spike trains.

[1]  Duane T. McRuer,et al.  A Neuromuscular Actuation System Model , 1968 .

[2]  P. Milgram,et al.  Distortion Suppression in Neuromuscular Information Transmission Due to Interchannel Dispersion in Muscle Spindle Firing Thresholds , 1976, IEEE Transactions on Biomedical Engineering.

[3]  Michael A. Arbib,et al.  The handbook of brain theory and neural networks , 1995, A Bradford book.

[4]  W. Bialek,et al.  Reading Between the Spikes in the Cereal Filiform Hair Receptors of the Cricket , 1992 .

[5]  C. E. SHANNON,et al.  A mathematical theory of communication , 1948, MOCO.

[6]  Frank H. Eeckman,et al.  Analysis and Modeling of Neural Systems , 1992, Springer US.

[7]  James Charles Houk,et al.  A mathematical model of the stretch reflex in human muscle systems , 1963 .

[8]  C A Terzuolo,et al.  Frequency analysis of stretch reflex and its main subsystems in triceps surae muscles of the cat. , 1970, Journal of neurophysiology.

[9]  M. Hulliger,et al.  The mammalian muscle spindle and its central control. , 1984, Reviews of physiology, biochemistry and pharmacology.

[10]  John Hertz Sensory coding and information theory , 1998 .

[11]  Huibert Kwakernaak,et al.  Modern signals and systems , 1991 .

[12]  William Bialek,et al.  Bits and brains: Information flow in the nervous system , 1993 .

[13]  Claude E. Shannon,et al.  The mathematical theory of communication , 1950 .

[14]  William Bialek,et al.  Reading a Neural Code , 1991, NIPS.

[15]  Serap A. Savari,et al.  On the entropy of DNA: algorithms and measurements based on memory and rapid convergence , 1995, SODA '95.

[16]  Thomas M. Cover,et al.  Elements of Information Theory , 2005 .

[17]  M. Hulliger,et al.  The responses of afferent fibres from the glabrous skin of the hand during voluntary finger movements in man. , 1979, The Journal of physiology.

[18]  W. Bialek,et al.  Naturalistic stimuli increase the rate and efficiency of information transmission by primary auditory afferents , 1995, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[19]  Fred Rieke,et al.  Coding Efficiency and Information Rates in Sensory Neurons , 1993 .

[20]  P. Matthews,et al.  The sensitivity of muscle spindle afferents to small sinusoidal changes of length , 1969, The Journal of physiology.

[21]  James V Candy,et al.  Signal processing the modern approach , 1988 .

[22]  W. McCulloch,et al.  The limiting information capacity of a neuronal link , 1952 .

[23]  Gideon F. Inbar,et al.  Estimation of Intracellular Potentials from Evoked Neural Pulse Trains , 1975, IEEE Transactions on Biomedical Engineering.

[24]  R. Poppele An analysis of muscle spindle behavior using randomly applied stretches , 1981, Neuroscience.

[25]  William Bialek,et al.  Spikes: Exploring the Neural Code , 1996 .

[26]  Athanasios Papoulis,et al.  Probability, Random Variables and Stochastic Processes , 1965 .

[27]  M Hulliger,et al.  Static and dynamic fusimotor action on the response of IA fibres to low frequency sinusoidal stretching of widely ranging amplitude , 1977, The Journal of physiology.