ChatrianGEShawCMLeffmanH.The significance of periodic lateralized epileptiform discharges in EEG: An electro-graphic, clinical and pathological study. Electroencephalogr Clin Neurophysiol1964; 17: 177–193.
CobbWAHillD.Electroencephalogram in subacute progressive encephalitis. Brain1950; 73: 392–404.
5.
Van LeeuwenStorm W.Electroencephalographical and neurophysiological aspects of subacute sclerosing encephalitis. Psychol Neurol Neurosurg1964; 67: 312–322.
6.
GloorPKalabyOGiardN.The electroencephalogram in diffuse encephalopathies: Electroencephalographs correlates of gray and white matter lesions. Brain1968; 91; 779–802.
7.
Pohlmann-EdenBCochiusJIHochBDHennericiM.Stroke and epilepsy. Cerebrovasc Dis1996 (in press).
8.
NeufeldMYVishnevskayaSTrevesTAReiderIKarepovVBornsteinNMKorczynADPeriodic lateralized epileptiform discharges (PLEDs) following stroke are associated with metabolic abnormalities. Electroencephalogr Clin Neurophysiol1997; 102: 295–299.
9.
PritchardWSDukeDWMeasuring chaos in the brain: A tutorial review of nonlinear dynamical EEG analysis. Intern J Neuroscience1992, 67: 31–80.
10.
KaplanDTGlassL.Understanding Nonlinear Dynamics. New York: Springer Verlag; 1995.
11.
GrassbergerPProcacciaI.Measuring the strangeness of strange attractors. Physica9D1983: 189–208.
12.
PackardNCrutchfieldJFarmerDShawR.Geometry from a time series. Phys Rev Lett1980; 45: 712–715.
13.
SauerTYorkeJACasdagliM.Embedology. J Stat Phys1991; 65: 579–616.
14.
TakensF.Detecting strange attractors in turbulence. Lecture Notes in Mathematics.1981; 898: 366–381.
15.
PritchardWSDukeDWKriebelKKDimensional analysis of resting human EEG. II: Surrogate data testing indicates nonlinearity but not low-dimensional chaos. Psychophysiology1995; 32:486–491.
16.
RomboutsSARBKeunenRWMStamCJInvestigation of nonlinear structure in multichannel EEG. Physics Letters A1995; 202: 352–358.
17.
SammerG.Working-memory load and dimensional complexity of the EEG. Int J Psychophysiol1996; 24: 173–182.
18.
StamCJvan WoerkomTCAMPritchardWSUse of nonlinear EEG measures to characterize EEG changes during mental activity. Electroencephalogr Clin Neurophysiol1996; 99: 214–224.
19.
RöschkeJAldenhoffJBA nonlinear approach to brain function: Deterministic chaos and sleep EEG. Sleep1992; 15: 95–101.
20.
WattRCHameroffSRPhase space electroencephalography (EEG): A new mode of intraoperative EEG analysis. Int J Clin Monit Comput1988; 5:3–13.
21.
PijnJPMvan NeervenJNoestAda SilvaLopes FH. Chaos or noise in EEG signals: Dependence on state and brain site. Electroencephalogr Clin Neurophysiol, 1991, 79: 371–381.
22.
CasdagliMCLasemidisLDSavitRSGimoreRLRoperSNSackellaresJCHNon-linearity in invasive EEG recordings from patients with temporal lobe epilepsy. Electroencephalogr Clin Neurophysiol, 1997; 102: 98–105.
23.
RöschkeJMannKFellJ.Nonlinear EEG dynamics during sleep in depression and schizophrenia. Intern J Neuroscience1994; 75: 271–284.
24.
ElbertTHLutzenbergerWRockstrohBBergPCohenR.Physical aspects of the EEG in schizophrenics. Biol Psychiatry1992; 32: 595–606.
25.
PezardLNandrinoJLRenaultBDepression as a dynamical disease. Biol Psychiatry1996; 39: 991–999.
26.
PritchardWSDukeDWCoburnKLEEG-based, neural-net predictive classification of Alzheimer's disease versus control subjects is augmented by non-linear EEG measures. Electroencephalogr Clin Neurophysiol1994; 91: 118–130.
27.
StamCJTavyDLJJellesBAchtereekteHAMSlaetsJPJKeunenRWMNon-linear dynamical analysis of multi channel EEG data: Clinical applications in dementia and Parkinson's disease. Brain Topography1994; 7: 141–150.
28.
StamCJJellesBAchtereekteHAMRomboutsSARBSlaetsJPJKeunenRWMInvestigation of EEG non-linearity in dementia and Parkinson's disease. Electroencephalogr Clin Neurophysiol1995; 95: 309–317.
29.
StamCJJellesBAchtereekteHAMvan BirgelenJHSlaetsJPJ. Diagnostic usefulness of linear and nonlinear quantitative EEG analysis in Alzheimer's disease. Clin Electroencephalogr1996; 27: 69–77.
30.
BabloyantzADestexheA.The Creutzfeldt-Jakob Disease in the hierarchy of chaotic attractors. In: MarcusMMullerSNicolisG (eds). From Chemical to Biological Organization. Berlin: Springer1988: 307–316.
31.
StamCJvan WoerkomTCAMKeunenRWM. Non-linear analysis of the electroencephalogram in Creutzfeldt-Jakob disease. Biol Cybern1997; 77: 247–256.
32.
TheilerJEubankSLongtinAGaldrikianBFarmerJDTesting for nonlinearity in time series: The method of surrogate data. Physica D1992; 58: 77–94.
33.
TheilerJBGaldrikianBLongtinAEubankSFarmerJDUsing surrogate data to detect nonlinearity in time series. In: CasdagliMCEubankS (eds). Nonlinear Modeling and Forecasting, SFI Studies in the Sciences of Complexity. Proc Vol XII Reading, MA: Addison-Wesley; 1992: 163–188.
34.
RosensteinMTCollinsJJDe LucaCJReconstruction expansion as a geometry-based framework for choosing proper delay times. Physica D1994; 73: 82–98.
35.
KennelMBrownRAbarbanelH.Determining embedding dimension for phase space reconstruction using a geometrical reconstruction. Phys Rev A1992; 45: 3403–3411.
36.
SchreiberThSchmitzAImproved surrogate data for non-linearity tests. Phys Rev Lett1996; 77: 635–638.
37.
da SilvaLopes FHHoeksASmitsAZetterbergLHModel of brain rhythmic activity. Kybernetik1974; 15: 27–37.
38.
ZetterbergLHKristianssonLMossbergK.Performance of a model for a local neuron population. Biol Cybernetics1978; 31: 15–26.
39.
WangLPichlerEERossJ.Oscillations and chaos in neural networks: An exactly solvable model. Proc Natl Acad Sci USA1990; 87: 9467–9471.
40.
DestexheA.Oscillations, complex spatiotemporal behavior, and information transport in networks of excitatory and inhibitory neurons. Physical Rev E1994; 50: 1594–1605.
41.
MenonV.Interaction of neuronal populations with delay: Effect of frequency mismatch and feedback gain. Int J Neural Systems1995; 6:3–17.
42.
NunezPLNeocortical dynamics and human EEG rhythms. New York, Oxford: Oxford University Press; 1995.
43.
VreeswijkVSompolinskyH.Chaos in neuronal networks with blananced excitatory and inhibitory activity. Science1996; 274: 1724–1726.