Nonlinearity in giant depolarizing potentials

Synchronous population discharges in immature neurons, or giant depolarizing potentials (GDPs), are considered to have an important role in the development of the functional network in hippocampus and other neural tissue before or briefly after birth. Recently, theoretical models have emphasized the possible role of chaotic, nonlinear activity at circuit level in establishing functional connectivity in neural tissue. Combining these two hypotheses leads to the prediction that GDPs have chaotic characteristics. We tested nonlinearity in GDPs recorded from transverse hippocampal slices of neonatal Wistar rats. Our results provide evidence of nonlinearity in GDP activity at circuit level.

[1]  James Theiler,et al.  Testing for nonlinearity in time series: the method of surrogate data , 1992 .

[2]  Duncan J. Watts,et al.  Collective dynamics of ‘small-world’ networks , 1998, Nature.

[3]  Yasuji Sawada,et al.  Practical Methods of Measuring the Generalized Dimension and the Largest Lyapunov Exponent in High Dimensional Chaotic Systems , 1987 .

[4]  Arjen van Ooyen,et al.  Competition in the development of nerve connections: a review of models , 2001 .

[5]  P. Grassberger,et al.  Characterization of Strange Attractors , 1983 .

[6]  W. Freeman,et al.  How brains make chaos in order to make sense of the world , 1987, Behavioral and Brain Sciences.

[7]  Hatsuo Hayashi,et al.  Chaotic nature of bursting discharges in the Onchidium pacemaker neuron , 1992 .

[8]  K. Dolan,et al.  Surrogate for nonlinear time series analysis. , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.

[9]  H. Abarbanel,et al.  Determining embedding dimension for phase-space reconstruction using a geometrical construction. , 1992, Physical review. A, Atomic, molecular, and optical physics.

[10]  Hikaru Inooka,et al.  Characteristics of human fingertips in the shearing direction , 2000, Biological Cybernetics.

[11]  Albert,et al.  Emergence of scaling in random networks , 1999, Science.

[12]  S. Strogatz Exploring complex networks , 2001, Nature.

[13]  T. Wiesel Postnatal development of the visual cortex and the influence of environment , 1982, Nature.

[14]  Fraser,et al.  Independent coordinates for strange attractors from mutual information. , 1986, Physical review. A, General physics.

[15]  Schreiber,et al.  Improved Surrogate Data for Nonlinearity Tests. , 1996, Physical review letters.

[16]  Cees van Leeuwen,et al.  Emergence of scale-free network with chaotic units , 2003 .

[17]  Mark A. Changizi,et al.  Principles underlying mammalian neocortical scaling , 2001, Biological Cybernetics.

[18]  L. M. Prida,et al.  Nonlinear frequency-dependent synchronization in the developing hippocampus. , 1999, Journal of neurophysiology.

[19]  Y. Ben-Ari,et al.  Giant synaptic potentials in immature rat CA3 hippocampal neurones. , 1989, The Journal of physiology.

[20]  Farmer,et al.  Predicting chaotic time series. , 1987, Physical review letters.

[21]  Sawada,et al.  Measurement of the Lyapunov spectrum from a chaotic time series. , 1985, Physical review letters.

[22]  I Khalilov,et al.  Early Development of Neuronal Activity in the Primate HippocampusIn Utero , 2001, The Journal of Neuroscience.

[23]  I. Tsuda The form of chaos in the noisy brain can manifest function , 1996, Behavioral and Brain Sciences.

[24]  Y. Ben-Ari Developing networks play a similar melody , 2001, Trends in Neurosciences.