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J Leo van Hemmen

Publications and source records attributed to J Leo van Hemmen.

15 recordsLinked to original sources
PubMed2006

Snake's perspective on heat: reconstruction of input using an imperfect detection system.

Two groups of snakes possess an infrared detection system that is used to create a heat image of their environment. In this Letter we present an explicit reconstruction model, the "virtual lens," which explains how a snake can overcome the optical limitations of a wide aperture pinhole camera, and how ensuing properties of the receptive fields on the infrared-sensitive membrane may explain the behavioral performance of this sensory system. Our model explores the optical quality of the infrared system by detailing how a functional representation of the thermal properties of the environment can be created. The model is easy to implement neuronally and agrees well with available neuronal, physiological, and behavioral data on the snake infrared system.

Animals↗
PubMed2006

Editorial.

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Editorial Policies↗
PubMed2005

Estimating position and velocity of a submerged moving object by the clawed frog Xenopus and by fish--a cybernetic approach.

The lateral-line system is a unique facility of aquatic animals to locate predator, prey, or conspecifics. We present a detailed model of how the clawed frog Xenopus, or fish, can localize submerged moving objects in three dimensions by using their lateral-line system. In so doing we develop two models of a slightly different nature. First, we exploit the characteristic properties of the velocity field, such as zeros and maxima or minima, that a moving object generates at the lateral-line organs and that are directly accessible neuronally, in the context of a simplified geometry. In addition, we show that the associated neuronal model is robust with respect to noise. Though we focus on the superficial neuromasts of Xenopus the same arguments apply mutatis mutandis to the canal lateral-line system of fish. Second, we present a full-blown three-dimensional reconstruction of the source on the basis of a maximum likelihood argument.

Animals↗
PubMed2005

Spontaneously emerging direction selectivity maps in visual cortex through STDP.

It is still an open question as to whether, and how, direction-selective neuronal responses in primary visual cortex are generated by feedforward thalamocortical or recurrent intracortical connections, or a combination of both. Here we present an investigation that concentrates on and, only for the sake of simplicity, restricts itself to intracortical circuits, in particular, with respect to the developmental aspects of direction selectivity through spike-timing-dependent synaptic plasticity. We show that directional responses can emerge in a recurrent network model of visual cortex with spiking neurons that integrate inputs mainly from a particular direction, thus giving rise to an asymmetrically shaped receptive field. A moving stimulus that enters the receptive field from this (preferred) direction will activate a neuron most strongly because of the increased number and/or strength of inputs from this direction and since delayed isotropic inhibition will neither overlap with, nor cancel excitation, as would be the case for other stimulus directions. It is demonstrated how direction-selective responses result from spatial asymmetries in the distribution of synaptic contacts or weights of inputs delivered to a neuron by slowly conducting intracortical axonal delay lines. By means of spike-timing-dependent synaptic plasticity with an asymmetric learning window this kind of coupling asymmetry develops naturally in a recurrent network of stochastically spiking neurons in a scenario where the neurons are activated by unidirectionally moving bar stimuli and even when only intrinsic spontaneous activity drives the learning process. We also present simulation results to show the ability of this model to produce direction preference maps similar to experimental findings.

Models, Neurological↗
PubMed2005

How a frog can learn what is where in the dark.

During the night 180 lateral-line organs allow the clawed frog Xenopus to localize prey by detecting water waves emanating from insects floundering on the water surface. Not only can the frog localize prey but it can also determine its character. This suggests waveform reconstruction, and a key question is how the frog can establish the appropriate neuronal hardware. Detecting time differences arising from the input on the skin is a key to neuronal information processing, and spike-timing-dependent synaptic plasticity (STDP) therefore seems to be the natural tool. We show how supervised STDP allows a frog to learn what is where in the dark. Learning can also be derived from a minimization principle.

Animals↗
PubMed2005

Spiking neurons learning phase delays: how mammals may develop auditory time-difference sensitivity.

Time differences between the two ears are an important cue for animals to azimuthally locate a sound source. The first binaural brainstem nucleus, in mammals the medial superior olive, is generally believed to perform the necessary computations. Its cells are sensitive to variations of interaural time differences of about 10 micros. The classical explanation of such a neuronal time-difference tuning is based on the physical concept of delay lines. Recent data, however, are inconsistent with a temporal delay and rather favor a phase delay. By means of a biophysical model we show how spike-timing-dependent synaptic learning explains precise interplay of excitation and inhibition and, hence, accounts for a physical realization of a phase delay.

Action Potentials↗
PubMed2003

Auditory system.

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Animals↗
PubMed2003

Minimal model of prey localization through the lateral-line system.

The clawed frog Xenopus is an aquatic predator catching prey at night by detecting water movements caused by its prey. We present a general method, a "minimal model" based on a minimum-variance estimator, to explain prey detection through the frog's many lateral-line organs, even in case several of them are defunct. We show how waveform reconstruction allows Xenopus' neuronal system to determine both the direction and the character of the prey and even to distinguish two simultaneous wave sources. The results can be applied to many aquatic amphibians, fish, or reptiles such as crocodiles.

Animals↗
PubMed2003

Zwicker tone illusion and noise reduction in the auditory system.

The Zwicker tone is an auditory aftereffect. For instance, after switching off a broadband noise with a spectral gap, one perceives it as a lingering pure tone with the pitch in the gap. It is a unique illusion in that it cannot be explained by known properties of the auditory periphery alone. Here we introduce a neuronal model explaining the Zwicker tone. We show that a neuronal noise-reduction mechanism in conjunction with dominantly unilateral inhibition explains the effect. A pure tone's "hole burning" in noisy surroundings is given as an illustration.

Auditory Pathways↗
PubMed2002

Adaptation in the corticothalamic loop: computational prospects of tuning the senses.

The present article discusses computational hypotheses on corticothalamic feedback and modulation of cortical response properties. We have recently proposed that the two phenomena are related, hypothesizing that neuronal velocity preference in the visual cortex is altered by feedback to the lateral geniculate nucleus. We now contrast the common view that response adaptation to stimuli subserves a function of redundancy reduction with the idea that it may enhance cortical representation of objects. Our arguments lead to the concept that the corticothalamic loop is involved in reducing sensory input to behaviourally relevant aspects, a pre-attentive gating.

Adaptation, Physiological↗
PubMed2002

How spiking neurons give rise to a temporal-feature map: from synaptic plasticity to axonal selection.

A temporal-feature map is a topographic neuronal representation of temporal attributes of phenomena or objects that occur in the outside world. We explain the evolution of such maps by means of a spike-based Hebbian learning rule in conjunction with a presynaptically unspecific contribution in that, if a synapse changes, then all other synapses connected to the same axon change by a small fraction as well. The learning equation is solved for the case of an array of Poisson neurons. We discuss the evolution of a temporal-feature map and the synchronization of the single cells' synaptic structures, in dependence upon the strength of presynaptic unspecific learning. We also give an upper bound for the magnitude of the presynaptic interaction by estimating its impact on the noise level of synaptic growth. Finally, we compare the results with those obtained from a learning equation for nonlinear neurons and show that synaptic structure formation may profit from the nonlinearity.

Journal Article↗
PubMed2002

The map in your head: how does the brain represent the outside world?

In neurophysics, a "map" is a neuronal representation of the outside world. It originates from spatiotemporal activity of a sensory organ. For example, touch provides a one-to-one representation of our skin in the cortex, a somatosensory map. In a similar way, visual and auditory maps are representations of the retina and the cochlea and provide us with spatial, temporal, and, more generally, spatiotemporal maps of sensory activity. In this introduction we concentrate on temporal aspects and show how temporal maps arise in the brain. Through prey localization the sand scorpion, the barn owl, and the paddle fish provide fascinating examples of neuronal maps, which are analyzed in detail.

Animals↗
PubMed2002

How instruction and feedback can select the appropriate T helper response.

The decision of the immune system to trigger immune responses that are, respectively, induced by Th1 or Th2 effectors is a critical one, because it profoundly influences disease outcome. We have recently constructed a mathematical model of Th1-Th2-pathogen interactions that shows that the major decisional events can often be successfully determined by the intrinsic behaviour of the T helper system itself. For certain dangerous types of pathogens, however, which replicate rapidly or have developed strategies to evade the immune response, additional stimuli may be necessary. As a possible mechanism for the decision-making process innate immune recognition has been proposed. Here we present an enlarged version of our model, which incorporates signals created from the innate immune system after pathogen recognition. The model analysis suggests that there is fault-tolerance of the T helper system to incorrect Th1 signals. In the presence of incorrect Th1 stimuli an initial Th1 response is shifted to the correct Th2-dominated response owing to the intrinsic T helper dynamics. By contrast, according to our model there is no fault-tolerance for incorrect Th2 signals. In fact, if timing is unimportant then Th2 signals are superfluous since the intrinsic T helper dynamics provide an automatic switch to Th2 if Th1 effectors fail to control the pathogen. Th2 signals may, however, be required to accelerate the onset of the Th2 response. Additionally, we discuss the role of feedback where successful pathogen destruction leads to up-regulation of activation of the effective T helper type. As one possibility we examine the role of CpG motifs as indicators for successful pathogen destruction. Differences between instructive and feedback mechanisms are highlighted.

Animals↗
PubMed1999

Delayed reverberation through time windows as a key to cerebellar function.

We present a functional model of the cerebellum comprising cerebellar cortex, inferior olive, deep cerebellar nuclei, and brain stem nuclei. The discerning feature of the model being time coding, we consistently describe the system in terms of postsynaptic potentials, synchronous action potentials, and propagation delays. We show by means of detailed single-neuron modeling that (i) Golgi cells can fulfill a gating task in that they form short and well-defined time windows within which granule cells can reach firing threshold, thus organizing neuronal activity in discrete 'time slices', and that (ii) rebound firing in cerebellar nuclei cells is a robust mechanism leading to a delayed reverberation of Purkinje cell activity through cerebellar-reticular projections back to the cerebellar cortex. Computer simulations of the whole cerebellar network consisting of several thousand neurons reveal that reverberation in conjunction with long-term plasticity at the parallel fiber-Purkinje cell synapses enables the system to learn, store, and recall spatio-temporal patterns of neuronal activity. Climbing fiber spikes act both as a synchronization and as a teacher signal, not as an error signal. They are due to intrinsic oscillatory properties of inferior olivary neurons and to delayed reverberation within the network. In addition to clear experimental predictions the present theory sheds new light on a number of experimental observation such as the synchronicity of climbing fiber spikes and provides a novel explanation of how the cerebellum solves timing tasks on a time scale of several hundreds of milliseconds.

Action Potentials↗