Simulating Cortical Background Activity at Rest With Filtered Noise

Freeman, Walter J.; O'nuallain, Sean; Rodríguez, José Vicente

doi:10.1142/s0219635208001885

Cited by 17 publications

(18 citation statements)

References 12 publications

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“…The implied selfsimilarity has been confirmed over the spectral ranges of clinical interest: theta, alpha, beta, and gamma (Freeman, 2007a;Freeman, O'Nuillain, & Rodriguez, 2008). The obvious inference is that a band pass filter of any center frequency and bandwidth applied to ECoG will give Rayleigh noise ( Fig.…”

Section: Power-law Psd Null Spikes Phase Cones Vorticesmentioning

confidence: 72%

Vortices in brain activity: Their mechanism and significance for perception

Freeman

2009

Neural Networks

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Brains interface with the world through perception. The process extracts information from microscopic sensory inputs and incorporates it into the mesoscopic memory store for retrieval in recognition. The process requires creation of spatiotemporal patterns of neural activity. The construction is done through phase transitions in cortical populations that condense the background activity through spontaneous symmetry breaking. Large-scale interactions create fields of synaptically driven activity that is observed by measuring brain waves (electrocorticogram, ECoG) and evaluated by constructing a mesoscopic vectorial order parameter as follows. The negative feedback among excitatory and inhibitory neurons creates spatially and spectrally distributed gamma oscillations (20-80 Hz) in the background activity. Band pass filtering reveals beats in ECoG log analytic power. In some beats that recur at theta rates (3-7 Hz), the order parameter transiently approaches zero, giving a null spike in which the microscopic activity is uniformly disordered (symmetric). A phase transition that is manifested in an analytic phase discontinuity breaks the symmetry. As the null spike terminates, the resurgent order parameter imposes mesoscopic order seen in spatial patterns of ECoG amplitude modulation (AM) that actualize and update the memory of a stimulus. Read-out is through a divergent/convergent projection that performs on cortical output an irreversible spatiotemporal integral transformation. The ECoG reveals a conic phase gradient that accompanies an AM pattern. The phase cone manifests a vortex, which is initiated by the null spike, and which is inferred to help stabilize and prolong its accompanying AM pattern that might otherwise be rapidly degraded by the turbulent neural noise from which it emerges.

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Section: Power-law Psd Null Spikes Phase Cones Vorticesmentioning

confidence: 72%

Vortices in brain activity: Their mechanism and significance for perception

Freeman

2009

Neural Networks

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“…The distribution of the magnitudes of the down spikes in the rest state was random, because it conformed to that of spikes in filtered black noise [15]. Deviations from randomness in distribution from the active state appeared as excesses and deficits from values predicted for random noise [15,20].…”

Section: A a Proposed Neural Mechanism Of The Null Spikementioning

confidence: 79%

“…Deviations from randomness in distribution from the active state appeared as excesses and deficits from values predicted for random noise [15,20]. The modal interval between bursts that had classifiable AM patterns suggested that the threshold for reduction in power in the null spikes that would incur phase transitions was ~10 -4 below the modal power [15].…”

Section: A a Proposed Neural Mechanism Of The Null Spikementioning

confidence: 90%

“…High spatial resolution was optimized by use of spatial spectral analysis to minimize the distance between electrodes (0.79 mm) in square electrode arrays with optimal aperture (6x6 mm) on the cortical surface (Chapter 4 in [2], [11]). High spectral resolution was by a FIR filter with order 1000 to 4000 to optimize a pass band of 5 Hz in the beta and gamma ranges [10,15]. High temporal resolution was optimized by sampling at 500/s over time segments lasting 6 sec, which was the duration of individual trials (3 s control period with no CS followed by 3 s with CS) and by use of the Hilbert transform [8].…”

Section: A Experimental Methodsmentioning

confidence: 99%

“…The choice of the order of the filter depended on the digitizing step of 2 ms and the pass band. Empirically order 500 gave invariance of the distribution of minimal amplitudes in null spikes over the relevant pass bands (Table 1) [15]. The pass bands were calculated in multiples of the Nyquist frequency (100 Hz and 250 Hz) in order to approximate the conventional pass bands, and in order to show the scale-invariance of the oscillations in each pass band, when the duration of display was changed inversely with the frequency range [15].…”

Section: A Experimental Methodsmentioning

confidence: 99%

See 2 more Smart Citations

Evidence for a Spatiotemporal Singularity in Percept Formation by Cerebral Cortex

Freeman

2010

Advances in Cognitive Neurodynamics (II)

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Perception proceeds by cinematic frames that are separated by an endogenous shutter, which is intrinsic to the background spontaneous activity of cerebral cortex. Cinematic displays of spatiotemporal electrocorticograms (ECoG) show turbulence, from which stable spatial patterns emerge that are correlated with perception of conditioned stimuli (CS). Extracting invariant properties of the perceptual patterns requires high-resolution measurements by high-density electrode arrays, high-order FIR filters, and the Hilbert transform giving analytic signals (instantaneous amplitudes and frequencies). Each pattern is preceded by a null spike, which is postulated to reveal a singularity in cortical dynamics that operates the shutter. A piecewise linear model is used to solve the nonlinear differential equations of mesoscopic cortical dynamics. Solutions point to the existence of a limit cycle attractor. The behavioral and physiological circumstances are described by which the trajectory of cortical dynamics may converge to the attractor and precipitate a phase transition, which destroys an existing pattern and initiates a new one.

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Phase transitions, cortical gamma, and the selection and read-out of information stored in synapses

Wright

2009

Modeling Phase Transitions in the Brain

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Simulating Cortical Background Activity at Rest With Filtered Noise

Cited by 17 publications

References 12 publications

Vortices in brain activity: Their mechanism and significance for perception

Vortices in brain activity: Their mechanism and significance for perception

Evidence for a Spatiotemporal Singularity in Percept Formation by Cerebral Cortex

Phase transitions, cortical gamma, and the selection and read-out of information stored in synapses

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