The electroencephalogram and cortical neural networks

References

• Abeles M. Local Cortical Circuits. Springer, New York 1982
   Google Scholar
• Abeles M, Vaadia E, Bergman H. Firing patterns of single units in the prefrontal cortex and neural network models. Network 1990; 1: 13–25
   Web of Science ®Google Scholar
• Ackley D H, Hinton G E, Sejnowski T J. A learning algorithm for Boltzmann machines. Cognitive Sci. 1985; 9: 147–69
   Web of Science ®Google Scholar
• Adey W R. The sensorium and the modulation of cerebral states: tonic environmental influences on limbic and related systems. Ann. NY Acad. Sci. 1977; 290: 396–420
   PubMed Web of Science ®Google Scholar
• Adey W R. Neurophysiologic effects of radio frequency and microwave radiation. Bull. NY Acad. Med. 1979; 55: 1079–93
   PubMedGoogle Scholar
• Adey W R. Tissue interactions with nonionizing electromagnetic fields. Physiol. Rev. 1981; 61: 435–514
   PubMed Web of Science ®Google Scholar
• Adey W R. Do EEG-like processes influence brain function at a physiological level?. Dynamics of Sensory and Cognitive Processing by the Brain, E Basar. Springer, Berlin 1988; 362–7
   Google Scholar
• Amari S. Learning patterns and pattern sequences by self-organising nets of threshold elements. IEEE Trans. Comput. 1972; 21: 1197–206
   Web of Science ®Google Scholar
• Amit D J. Modelling Brain Function. The World of Attractor Neural Networks. Cambridge University Press, Cambridge 1990
   Google Scholar
• Amit D J, Tsodyks M V. Attractor neural networks with biological probe records. Network 1990; 1: 381–405
   Web of Science ®Google Scholar
• Amit D J. Quantitative study of attractor neural networks retrieving at low spike rates: II. Low rate retrieval in symmetric networks. Network 1991; 2: 275–94
   Web of Science ®Google Scholar
• Blinowska K J, Malinowski M. Nonlinear and linear forecasting of the EEG times series. Biol. Cybern. 1991; 66: 159–65
   PubMed Web of Science ®Google Scholar
• Braitenberg V. Cortical architectonics: general and areal. Architectonics of the Cerebral Cortex, M A B Brazier, H Petsche. Raven, New York 1978
   Google Scholar
• Braitenberg V, Schuz A. Anatomy of the Cortex. Statistics and Geometry. Springer, New York 1991
   Google Scholar
• Broadbent D F. Perception and Communication. Pergamon, Oxford 1958
   Google Scholar
• Burns B D. The Mammalian Cortex. Williams and Wilkins, Baltimore, MD 1958
   Google Scholar
• Caianiello E R, De Luca A, Ricciardi L M. Reverberations and control of neural networks. Kybernetik 1967; 4: 10–18
   PubMedGoogle Scholar
• Clavier R M, Routtenberg A. Ascending monamine-containing fibre pathways related to intracranial self-stimulation: histochemical fluorescence study. Brain Res. 1974; 72: 25–40
   PubMed Web of Science ®Google Scholar
• Dehaene S, Changeux J P, Nadal J P. Neural networks that learn temporal sequences by selection. Proc. Natl Acad. Sci. USA 1987; 84: 2727–31
   PubMed Web of Science ®Google Scholar
• Eccles J C. The Neurophysiological Basis of Mind. Oxford University Press, Oxford 1953
   Google Scholar
• Eckhorn R, Bauer B, Jordan W, Brosch M, Kruse W, Munk M, Reitboeck H J. Coherent oscillation: a mechanism of feature linking in visual cortex?. Biol. Cybern. 1988; 60: 121–30
   PubMed Web of Science ®Google Scholar
• Eeckman F H, Freeman W J. Correlations between unit firing and EEG in the rat olfactory system. Brain Res. 1990; 528: 238–44
   PubMed Web of Science ®Google Scholar
• Elul R. The genesis of the EEG. Int. Rev. Neurobiol. 1972; 15: 227–72
   Google Scholar
• Fink M. EEG and psychopharmacology. Contemporary Clinical Neurophysiology, W A Cobb, H Van Duijin. Elsevier, Amsterdam 1978; 41–56, suppl. 4
   Google Scholar
• Franazczuk P J, Blinowska K J. Linear model of brain electrical activity-EEG as a superposition of damped oscillatory modes. Biol. Cybern. 1985; 53: 19–25
   PubMed Web of Science ®Google Scholar
• Freeman W J. A linear distributed feedback model for prepyriform cortex. Exp. Neurology 1964; 10: 525–47
   PubMed Web of Science ®Google Scholar
• Freeman W J. Measurement of open-loop responses to electrical stimulation in olfactory bulb of cat. J. Neurophysiol. 1972; 35: 745–61
   PubMed Web of Science ®Google Scholar
• Freeman W J. Mass Action in the Nervous System. Academic, New York 1975
   Google Scholar
• Freeman W J. Nonlinear gain mediation cortical stimulus response relations. Biol. Cybern. 1979; 33: 237–47
   PubMed Web of Science ®Google Scholar
• Freeman W J. A physiological hypothesis of perception. Perspectives Biol. Med. 1981; 24: 561–92
   PubMed Web of Science ®Google Scholar
• Freeman W J. The physioslogical basis of mental images. Biol. Psychiatry 1983; 18: 1107–25
   PubMed Web of Science ®Google Scholar
• Freeman W J. Techniques used in the search for the physiological basis of the EEG. Handbook of Electroencephalography and Clinical Neurophysiology, S S Gevins, A Remond. Elsevier, Amsterdam 1987a; 3A: 583–664
   Google Scholar
• Freeman W J. Simulation of chaotic EEG patterns with dynamic model of the olfactory system. Biol. Cybern. 1987b; 56: 139–50
   PubMed Web of Science ®Google Scholar
• Freeman W J. Strange attractors that govern mammalian brain dynamics shown by trajectories of electroencephalographic (EEG) potential. IEEE Trans. Circuits Systems 1988; 35: 781–3
   Google Scholar
• Freeman W J. Predictions on neocortical dynamics derived from studies in paleocortex. Induced Rhythms of the Brain, E Basar, T H Bullock. Birkhauser, Basel 1991
   Google Scholar
• Freeman W J, Skarda C A. Spatial EEG patterns, nonlinear dynamics and perception: the neo-Sherringtonian view. Brain Res. Rev. 1985; 10: 147–75
   Web of Science ®Google Scholar
• Freeman W J, van Dijk B. Spatial patterns of visual cortical fast EEG during conditioned reflex in rhesus monkey. Brain Res. 1987; 422: 267–76
   PubMed Web of Science ®Google Scholar
• Frolov A A, Medvedev A V. Substantiation of the ‘point approximation’ for describing the total electrical activity of the brain with use of a simulation model. Biophysics 1986; 31: 332–7
   Google Scholar
• Fuster J M. Behavioural electrophysiology of the prefrontal cortex. J. Neurophysiol. 1973; 36: 61–78
   PubMed Web of Science ®Google Scholar
• Gevins A S. Recent advances in neurocognitive pattern analysis. Dynamics of Sensory and Cognitive Processing by the Brain, E Basar. Springer, Berlin 1988; 88–102
   Google Scholar
• Gevins A S, Doyle J C, Cutillo B A, Schaffer R E, Tannehill R S, Bressler S L. Neurocognitive pattern analysis of a visuomotor task: rapidly shifting foci of evoked correlations between electrodes. Psychophysiology 1985; 22: 32–43
   PubMed Web of Science ®Google Scholar
• Gevins A S, Schaffer R E, Doyle J C, Cutillo B A, Tannehill R S, Bressler S L. Shadows of thought: shifting lateralisation of human brain electrical patterns during a brief visuomotor task. Science 1983; 220: 97–9
   PubMed Web of Science ®Google Scholar
• Gloor P. Hans Berger on the electroencephelogram of man: the fourteen original reports on the human encephelogram. Electroenceph. Clin. Neurophysiol, P Gloor, 1969, Suppl 28
   Google Scholar
• Gray C M, Koenig P, Engel K A, Singer W. Oscillatory responses in cat visual cortex exhibit intercolumnar synchronization which reflects global stimulus properties. Nature 1989; 338: 334–7
   PubMed Web of Science ®Google Scholar
• Griniasty M, Tsodyks M V, Amit D J. Conversion of temporal correlations between stimuli to spatial correlations between attractors. J. Phys. A: Math. Gen. 1992; 24: 715–34
   Google Scholar
• Hess W R. Hypothalamus und die zentren des autonomen nervensystems. Physiologie Archiv. fur Psychiatrie und Nervenkrankheiten (Berlin) 1936; 104: 548–57
   Google Scholar
• Hopfield J J. Neural networks and physical systems with emergent collective computational abilities. Proc. Natl Acad. Sci. USA 1982; 79: 2554–8
   PubMed Web of Science ®Google Scholar
• Hopfield J J. Neurons with graded response have collective computational properties like those of two state neurons. Proc. Natl Acad. Sci. USA 1984a; 81: 3088–92
   PubMed Web of Science ®Google Scholar
• Hopfield J J. Collective processing and neural states. Modelling and Analysis in Biomedicine, C Nicollini. World Scientific, Singapore 1984b
   Google Scholar
• Horowitz J M. Evoked activity of single units and neural populations in the hippocampus of the cat. Electroenceph. Clin. Neurophysiol. 1972; 32: 227–40
   PubMedGoogle Scholar
• Ingber L. Statistical mechanics of neocortical interactions. I. Basic formulation. Physica 1982; 5D: 83–107
   Google Scholar
• Ingber L. Statistical mechanics of neocortical interactions: a scaling paradigm applied to electroencephalography. Phys. Rev. 1991; 44: 4017–60
   Google Scholar
• Ingber L, Nunez P L. Multiple scales of statistical physics of the neocortex: application to electroencephalography. Math. Comput. Modelling 1990; 13: 83–5
   Web of Science ®Google Scholar
• Jaspers K. General Psychopathology. Manchester University Press, Manchester 1963
   Google Scholar
• John E R, et al. Neurometrics. Science 1977; 196: 1393–403
   PubMed Web of Science ®Google Scholar
• Katznelson R D. Normal modes of the bra. Electric Fields of the Brain. The Neurophysics of EEG, P L Nunez. Oxford University Press, Oxford 1981; 176–214
   Google Scholar
• Korn H, Faber D S. Electrical interactions between vertebrate neurones: field effects and electronic coupling. The Neurosciences, Fourth Study Program, F O Schmitt, F G Worden. MIT, Cambridge, MA 1979; 333–58
   Google Scholar
• Kydd R R, Wright J J. Mental phenomena as changes of state in a finite state machine. Austral. New Zealand J. Psychiatry 1986; 20: 158–65
   PubMed Web of Science ®Google Scholar
• Lagerlund T D, Sharbrough F W. Computer simulation of neuronal circuit models of rhythmic behaviour in the electroencephalogram. Comput. Biol. Med. 1988; 18: 267–304
   PubMed Web of Science ®Google Scholar
• Layne S P, Mayer-Kress G, Holzfuss J. Problems associated with dimensional analysis of electroencephalographic data. Dimensions and Entropies in Chaotic Systems, G Mayer-Kress. Springer, Berlin 1986
   Google Scholar
• Lindsley D B. Neural mechanisms of arousal, attention and information processing. Neuropsychology After Lashley, J Orbach. Erlbaum, Hillsdale, NJ 1982; 315–407
   Google Scholar
• Lindvall O, Björklund A. The organisation of the ascending catecholamine neurone systems in the rat brain as revealed by the glyoxic acid fluorescence method. Physiol. Scand. Suppl. 1974; 412: 1–48
   PubMedGoogle Scholar
• Lindvall O. Neuroanatomy of central dopamine pathways. Review of recent progress. Advances in the Biosciences, M Kohsaka, T Shomar, Y Tsukada, G N Woodruff. Pergamon, Oxford 1982; 297–311
   Google Scholar
• Little W A, Shaw G L. A statistical theory of short and long term memory. Behav. Biol. 1975; 14: 115–33
   PubMedGoogle Scholar
• Lopes da Silva F H, Hoeks A, Smits A, Zetterberg L H. Model of brain rhythmic activity. Kybernetik 1974; 15: 27–37
   PubMed Web of Science ®Google Scholar
• Lopes da Silva F H, Rotterdam A, Barts P, van Heusden E, Burr W. Models of neuronal populations: the basic mechanisms of rhythmicity. Prog. Brain Res. 1976; 45: 281–308
   PubMedGoogle Scholar
• Lopes da Silva F H, Storm van Leeuwen W. The cortical alpha rhythm in dog: the depth and surface profile of phase. Architectonics of the Cerebral Cortex, M A B Brazier, H Petsche. Raven, New York 1978; 319–33
   Google Scholar
• Marshall J F. Somatosensory inattention after dopamine depleting intracerebral 6-OHDA injections: spontaneous recovery and pharmacological control. Brain Res. 1979; 177: 311–24
   PubMed Web of Science ®Google Scholar
• Mitzdorf U. Current source-density method and application in cat cerebral cortex: investigation of evoked potentials and EEG phenomena. Physiol. Rev. 1985; 65: 37–100
   PubMed Web of Science ®Google Scholar
• Mitzdorf U. Properties of the evoked potential generators: current source-density analysis of evoked potentials in cat cortex. Int. J. Neurosci. 1987; 33: 33–59
   PubMed Web of Science ®Google Scholar
• Miyashita Y. Neuronal correlate of visual associative long-term memory in the primate temporal cortex. Nature 1988; 335: 817–20
   PubMed Web of Science ®Google Scholar
• Miyashita Y, Chang H S. Neural correlate of pictorial short-term memory in the primate temporal cortex. Nature 1988; 331: 68–70
   PubMed Web of Science ®Google Scholar
• Moruzzi G, Magoun H W. Brain stem reticular formation and activation of the EEG. Electroenceph. Clin. Neurophysiol. 1949; 1: 455–73
   PubMedGoogle Scholar
• Mountcastle V B. An organising principle for cerebral function: the unit module and the distributed system. The Neurosciences, Fourth Study Program, F O Schmitt, F G Worden. MIT Press, Cambridge, MA 1979; 21–42
   Google Scholar
• Nauta W J, Feirtag M. The organisation of the brain. Sci. Amer. 1979; 241: 78–105
   Google Scholar
• Nauta W J, Karten H J. A general profile of the vertebrate brain with sidelights on the ancestry of cerebral cortex. The Neurosciences: Second Study Program, F O Schmitt. Rockefeller University Press, New York 1970; 7–26
   Google Scholar
• Nebenzahl I. Recall of associated memories. J. Math. Biol. 1987; 25: 511–19
   PubMed Web of Science ®Google Scholar
• Niki H. Prefrontal unit activity during delayed alterntion in the monkey. Brain Res. 1974; 68: 185–197
   PubMed Web of Science ®Google Scholar
• Nunez P L. The brain wave equation. A model for the EEG. Math. Biosci. 1974; 21: 279–97
   Google Scholar
• Nunez P L. Electric Fields of the Brain. The Neurophysics of EEG. Oxford University Press, Oxford 1981
   Google Scholar
• Nunez P L. Generation of human EEG by a combination of long and short range neocortical interactions. Brain Topography 1989; 1: 199–215
   PubMedGoogle Scholar
• Nunez P L. Neocortical Dynamics and Human EEG Rhythms. Oxford University Press, Oxford 1992, to be published
   Google Scholar
• Olds J. Differential effects of drives and drugs on self-stimulation at different brain sites. Electrical Stimulation of the Brain, D E Sheer. University of Texas Press, Austin, TX 1981; 350–66
   Google Scholar
• Peretto P, Niez J J. Collective properties of neuronal networks. Disordered Systems and Biological Organisation, E Bienenstock, F Fogelman-Soulie, G Wiesbuch. Springer, Berlin 1986
   Google Scholar
• Picton T W, Hillyard S A. Endogenous event related potentials. Human Event Related Potentials EEG Handbook, T W Picton. Elsevier, Amsterdam 1988; 361–426
   Google Scholar
• Rolls E T. Theoretical and neurophysical analysis of the functions of primate hippocampus in memory. Cold Spring Harbour Symposia on Quantitative Biology. Cold Spring Harbor Laboratory Press, Cold Spring Harbor 1990; LV
   Google Scholar
• Rolls E T, Treves A. The relative advantages of sparse versus distributed encoding for associative neuronal networks in the brain. Network 1990; 1: 407–21
   Web of Science ®Google Scholar
• Rössler O E, Hudson J L. Self-similarity in hyperchaotic data. Brain Dynamics, E Basar, T H Bullock. Springer, Berlin 1989
   Google Scholar
• Sakai K, Miyashita Y. Neural organisation for the long-term memory of paired associates. Nature 1991; 354: 152
   PubMed Web of Science ®Google Scholar
• Scheibel M E, Scheibel A B. Structural organisation of nonspecific thalamic nucleii and their projection toward cortex. Brain Res. 1967; 6: 60–94
   PubMedGoogle Scholar
• Schmitt F O. The role of structural, electrical and chemical circuitry in brain function. The Neurosciences, Fourth Study Programme, F O Schmitt, F G Worden. MIT Press, Cambridge, MA 1979; 5–20
   Google Scholar
• Shaw G L, Harth E, Scheibel A B. Cooperativity in brain function: assemblies of approximately 30 neurones. Exp. Neurology 1982; 77: 324–58
   PubMed Web of Science ®Google Scholar
• Sherrington D. Magnets to Memories: from Spin Glasses to the Brain. Department of Physics, Oxford University. 1991, OUTP-91-215
   Google Scholar
• Silberstein R. in preparation. 1992
   Google Scholar
• Steriade M, Gloor P, Llinas R R, Lopes da Silva F H, Mesulam M M. Basic mechanisms of cerebral rhythmic activities. Electroenceph. Clin. Neurophysiol. 1990; 76: 481–508
   PubMedGoogle Scholar
• Szentagothai J. Specificity versus (quasi) randomness in cortical connectivity. Architectonics of the Cerebral Cortex, M A B Brazier, H Petsche. Raven, New York 1978a
   Google Scholar
• Szentagothai J. The neuron of the cerebral cortex: a functional interpretation. Proc. R. Soc. London 1978b; B 201: 219–48
   PubMed Web of Science ®Google Scholar
• Szentagothai J. Local neuron circuits of the neocortex. The Neurosciences Fourth Study Program, F O Schmitt, F G Worden. MIT Press, Cambridge, MA 1979; 399–415
   Google Scholar
• Thatcher R W, Krause P J, Hrybyk M. Corticocortical associations and EEG coherence: a two compartmental model. Electroenceph. Clin. Neurophysiol. 1986; 64: 123–43
   PubMedGoogle Scholar
• Tombol T. Comparative data on the golgi architecture of interneurons of different cortical areas in cat and rabbit. Architectonics of the Cerebral Cortex, M A B Brazier, H Petsche. Raven, New York 1978; 59–76
   Google Scholar
• van Rotterdam A, Lopes da Silva F H, van der Ende J, Viergever M A, Hermans A J. A model of the spatial-temporal characteristics of the alpha rhythm. Bull. Math. Biol. 1982; 44: 283–305
   PubMed Web of Science ®Google Scholar
• Walter D O, Kado R T, Rhodes J J, Adey W R. Electroencephalographic baselines in astronaut candidates estimated by computation and pattern-recognition techniques. Aerospace Med. 1967; 38: 371–9
   PubMedGoogle Scholar
• Wise R A. Catecholamine theories of reward: a critical review. Brain Res. 1978; 152: 215–47
   PubMed Web of Science ®Google Scholar
• Wright J J. Lateral hypothalamic regulation of electrocortical activity. Electroenceph. Clin. Neurophysiol. 1981; 51: 632–8
   PubMedGoogle Scholar
• Wright J J. Reticular activation and the dynamics of neuronal networks. Biol. Cybern. 1990; 62: 289–98
   PubMed Web of Science ®Google Scholar
• Wright J J, Craggs M D. Arousal and intracranial self-stimulation in split-brain monkeys. Exp. Neurology 1977; 55: 295–303
   PubMed Web of Science ®Google Scholar
• Wright J J, Kydd R R. A test for constant natural frequencies in electrocortical activity under lateral hypothalamic control. Biol. Cybern. 1984; 50: 83–8
   PubMed Web of Science ®Google Scholar
• Wright J J, Kydd R R, Lees G J. Amplitude and phase relation of electrocortical waves regulated by transhypothalamic dopaminergic neurones: a test for a linear theory. Biol. Cybern. 1984; 50: 273–83
   PubMed Web of Science ®Google Scholar
• Wright J J. Quantitation of a mass action of dopaminergic neurones regulating temporal damping of linear electrocortical waves. Biol. Cybern. 1985a; 52: 281–90
   PubMed Web of Science ®Google Scholar
• Wright J J. Contributions of noradrenergic neurones of the locus coeruleus to the temporal damping of linear electrocortical waves. Biol. Cybern. 1985b; 52: 351–6
   PubMed Web of Science ®Google Scholar
• Wright J J. Gross electrocortical activity as a linear wave phenomenon with variable temporal damping, regulated by ascending catecholamine neurones. Int. J. Neurosci. 1987; 33: 1–13
   PubMed Web of Science ®Google Scholar
• Wright J J, Kydd R R, Liley D T J. On integrating chaotic and linear models of electrocortical activity. Behav. Brain Sci. 1992, submitted
   Google Scholar
• Wright J J, Kydd R R, Sergejew A A. Autoregression models of EEG. Results compared with expectations for a multilinear near-equilibrium biophysical process. Biol. Cybern. 1990a; 62: 201–10
   PubMed Web of Science ®Google Scholar
• Wright J J, Sergejew A A. Radial coherence, wave velocity and damping of electrocortical waves. Electroenceph. Clin. Neurophysiol. 1991; 79: 403–12
   PubMedGoogle Scholar
• Wright J J, Sergejew A A, Stampfer H G. Inverse filter computation of the neural impulse giving rise to the auditory evoked potential. Brain Topography 1990b; 2: 293–302
   PubMedGoogle Scholar