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Copyright information:Taken from "Distinguishing low frequency oscillations within the 1/spectral behaviour of electromagnetic brain signals"http://www.behavioralandbrainfunctions.com/content/3/1/62Behavioral and brain functions : BBF 2007;3():62-62.Published online 10 Dec 2007PMCID:PMC2235870.nding spectrograms.
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Copyright information:Taken from "Distinguishing low frequency oscillations within the 1/spectral behaviour of electromagnetic brain signals"http://www.behavioralandbrainfunctions.com/content/3/1/62Behavioral and brain functions : BBF 2007;3():62-62.Published online 10 Dec 2007PMCID:PMC2235870.nding spectrograms.
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Copyright information:Taken from "Distinguishing low frequency oscillations within the 1/spectral behaviour of electromagnetic brain signals"http://www.behavioralandbrainfunctions.com/content/3/1/62Behavioral and brain functions : BBF 2007;3():62-62.Published online 10 Dec 2007PMCID:PMC2235870.e 4 conditions forms the normalisation curve(-).
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Copyright information:Taken from "Distinguishing low frequency oscillations within the 1/spectral behaviour of electromagnetic brain signals"http://www.behavioralandbrainfunctions.com/content/3/1/62Behavioral and brain functions : BBF 2007;3():62-62.Published online 10 Dec 2007PMCID:PMC2235870.e 4 conditions forms the normalisation curve(-).
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  • Image
Copyright information:Taken from "Distinguishing low frequency oscillations within the 1/spectral behaviour of electromagnetic brain signals"http://www.behavioralandbrainfunctions.com/content/3/1/62Behavioral and brain functions : BBF 2007;3():62-62.Published online 10 Dec 2007PMCID:PMC2235870.nding spectrograms.
Data Types:
  • Image
Copyright information:Taken from "Distinguishing low frequency oscillations within the 1/spectral behaviour of electromagnetic brain signals"http://www.behavioralandbrainfunctions.com/content/3/1/62Behavioral and brain functions : BBF 2007;3():62-62.Published online 10 Dec 2007PMCID:PMC2235870.e 4 conditions forms the normalisation curve(-).
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  • Image
Over an animal’s lifespan, neuronal circuits and systems often decline in an inherently heterogeneous fashion. To compare the age-dependent progression of changes in visual behavior with alterations in retinal physiology, we examined phototaxis and electroretinograms (ERGs) in a wild-type D. melanogaster strain (Canton-S) across their lifespan. In aged flies (beyond 50% median lifespan), we found a marked decline in phototaxis, while motor coordination was less disrupted, as indicated by relatively stronger negative geotaxis. These aged flies displayed substantially reduced ERG transient amplitudes while the receptor potentials (RP) remained largely intact. Using a repetitive light flash protocol, we serendipitously discovered two forms of activity-dependent oscillation in the ERG waveforms of young flies: ‘light-off’ and ‘light-on’ oscillations. After repeated 500 ms light flashes, light-off oscillations appeared during the ERG off-transients (frequency: 50–120 Hz, amplitude: ∼1 mV). Light-on oscillations (100–200 Hz, ∼0.3 mV) were induced by a series of 50 ms flashes, and were evident during the ERG on-transients. Both forms of oscillation were observed in other strains of D. melanogaster (Oregon-R, Berlin), additional Drosophila species (D. funerbris, D. euronotus, D. hydei, D. americana), and were evoked by a variety of light sources. Both light-off and light-on oscillations were distinct from previously described ERG oscillations in the visual mutant rosA in terms of location within the waveform and frequency. However, within rosA mutants, light-off oscillations, but not light-on oscillations could be recruited by the repetitive light flash protocol. Importantly though, we found that both forms of oscillation were rarely observed in aged flies. Although the physiological bases of these oscillations remain to be elucidated, they may provide important clues to age-related changes in neuronal excitability and synaptic transmission.
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Copyright information:Taken from "Distinguishing low frequency oscillations within the 1/spectral behaviour of electromagnetic brain signals"http://www.behavioralandbrainfunctions.com/content/3/1/62Behavioral and brain functions : BBF 2007;3():62-62.Published online 10 Dec 2007PMCID:PMC2235870. (b) The inverse filter frequency response obtained from the corresponding 6th order MA model.
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Copyright information:Taken from "Distinguishing low frequency oscillations within the 1/spectral behaviour of electromagnetic brain signals"http://www.behavioralandbrainfunctions.com/content/3/1/62Behavioral and brain functions : BBF 2007;3():62-62.Published online 10 Dec 2007PMCID:PMC2235870. (b) The inverse filter frequency response obtained from the corresponding 6th order MA model.
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We investigate the dynamics of an array of polystyrene micron-sized spheres in a dual-beam fiber-optic trap. Experimental results show non-uniform equilibrium particle spacing and spontaneous self-sustained oscillation for large particle numbers. Results are analyzed with a Maxwell-Stress Tensor method using the Generalized Multipole Technique, where hydrodynamic interactions between particles are included. The theoretical analysis matches well with the experimentally observed equilibrium particle spacing. The theory shows that an offset in the trapping beams is the underlying mechanism for the oscillations and influences both the oscillation frequency and the damping rate for oscillations. The theory presented is of general interest to other systems involving multi-particle optical interactions.
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