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Neurons integrate subthreshold inputs in a frequency-dependent manner. For sinusoidal stimuli, response amplitudes thus vary with stimulus frequency. Neurons in entorhinal cortex show two types of such resonance behavior: stellate cells in layer II exhibit a prominent peak in the resonance profile at stimulus frequencies of 5-16 Hz. Pyramidal cells in layer(More)
Spike timing-dependent plasticity (STDP) is a computationally powerful form of plasticity in which synapses are strengthened or weakened according to the temporal order and precise millisecond-scale delay between presynaptic and postsynaptic spiking activity. STDP is readily observed in vitro, but evidence for STDP in vivo is scarce. Here, we studied spike(More)
In both humans and rodents, the external environment is encoded in the form of cognitive maps. Neurons in the medial entorhinal cortex (mEC) represent spatial locations in a sequence of grid-like patterns scaled along the dorsal-ventral axis. The grid spacing correlates with the intrinsic resonance frequencies of stellate cells in layer II of mEC. We(More)
In the nervous system many behaviorally relevant dynamical processes are characterized by episodes of complex oscillatory states, whose periodicity may be expressed over multiple temporal and spatial scales. In at least some of these instances the variability in oscillatory amplitude and frequency can be explained in terms of deterministic dynamics, rather(More)
This paper describes a new method for automated texture classification for glaucoma detection using high resolution retinal Optical Coherence Tomography (OCT). OCT is a non-invasive technique that produces cross-sectional imagery of ocular tissue. Here, we exploit information from OCT images , specifically the inner retinal layer thickness and speckle(More)
The temporal lobe is well known for its oscillatory activity associated with exploration, navigation, and learning. Intrinsic membrane potential oscillations (MPOs) and resonance of stellate cells (SCs) in layer II of the entorhinal cortex are thought to contribute to network oscillations and thereby to the encoding of spatial information. Generation of(More)
This paper presents novel pre-processing image enhancement algorithms for retinal optical coherence tomography (OCT). These images contain a large amount of speckle causing them to be grainy and of very low contrast. To make these images valuable for clinical interpretation, we propose a novel method to remove speckle, while preserving useful information(More)
Optical coherence tomography (OCT) has revolutionises the diagnosis of retinal disease based on the detection of microscopic rather than subcellular changes in retinal anatomy. However, currently the technique is limited to the detection of microscopic rather than subcellular changes in retinal anatomy. However, coherence based imaging is extremely(More)
This paper presents a novel, statistical model based method aimed at fusing Optical Coherence Tomography and Fundus Photographic imagery of the eye. The presented method utilises the Discrete Curvelet Transform to decompose the images into sub-band coefficients. The Meridian distribution, a specialized case of the generalized Cauchy distribution, is used to(More)
This paper presents an image enhancement method for retinal optical coherence tomography (OCT) images. Raw OCT images contain a large amount of speckle which causes images to be grainy and very low contrast. The raw OCT images are thus difficult usually processed before any clinical interpretation is made. We propose a novel method to remove speckle, while(More)
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