Research Projects:

Attention modulates synchronized neuronal firing in primate somatosensory cortex
Electrophysiological correlates of synchronous neural activity and attention: a short review
The effects of input rate and synchrony on a coincidence detector: Analytical solution
Synaptic depression leads to nonmonotonic frequency dependence in the coincidence detector
Chaos control
Stimulus-induced synchronization of neurons that encode objects



Attention modulates synchronized neuronal firing in primate somatosensory cortex


A potentially powerful information processing strategy in the brain is to take advantage of the temporal structure of neuronal spike trains. An increase in synchrony within the neural representation of an object or location increases the efficacy of that neural representation at the next synaptic stage in the brain; thus, increasing synchrony is a candidate for the neural correlate of attentional selection. We investigated the synchronous firing of pairs of neurons in the secondary somatosensory cortex (SII) of three monkeys trained to switch attention between a visual task and a tactile discrimination task. We found that most neuron pairs in SII cortex fired synchronously and, furthermore, that the degree of synchrony was affected by the monkey's attentional state. In the monkey performing the most difficult task, 35% of neuron pairs that fired synchronously changed their degree of synchrony when the monkey switched attention between the tactile and visual tasks. Synchrony increased in 80% and decreased in 20% of neuron pairs affected by attention.

This reseach is described in:
Steinmetz, P. N., Roy, A., Fitzgerald, P., Hsiao, S. S., Johnson, K. O., and Niebur, E. (2000). Attention Modulates Synchronized Neuronal Firing in Primate Somatosensory Cortex. Nature, 404, 187--190.

also see:
Niebur E, Hsiao SS, Johnson KO. (2002) Synchrony: a neuronal mechanism for attentional selection? Current Opinion in Neurobiology, 12 (2), 190-194.

People Involved:
Peter Steinmetz, Arup Roy
Paul Fitzgerald, Steve Hsiao
Ken Johnson, Ernst Niebur




Electrophysiological correlates of synchronous neural activity and attention: a short review


Attentional selection implies preferential treatment of some sensory stimuli over others. This requires differential representation of attended and unattended stimuli. Most previous research has focused on pure rate codes for this representation but recent evidence indicates that a mixed code, involving both mean firing rate and temporal codes, may be employed. Of particular interest is a distinction of attended from unattended stimuli based on synchrony within neural populations. I review electrophysiological evidence at macroscopic, mesoscopic and microscopic spatial scales showing that the degree of synchronous activity varies with the attentional state of the perceiving organism.

Niebur, E. (2002). Electrophysiological correlates of synchronous neural activity and attention: a short review. Biosystems, 67 (1-3), 157-166.





The effects of input rate and synchrony on a coincidence detector: Analytical solution


We derive analytically the solution for the output rate of the ideal coincidence detector. The solution is for an arbitrary number of input spike trains with identical binomial count distributions (which includes Poisson statistics as a special case) and identical arbitrary pairwise cross-correlations, from zero correlation (independent processes) to complete correlation (identical processes).

Mikula, S. and Niebur, E. (2003). The effects of input rate and synchrony on a coincidence detector: Analytical solution. Neural Computation, 15(3), 539-47.

People involved:
Shawn Mikula
Ernst Niebur




Synaptic depression leads to nonmonotonic frequency dependence in the coincidence detector


In this report, we extend our previous analytical results (Mikula and Niebur03a) for the coincidence detector by taking into account probabilistic frequency-dependent synaptic depression. We present a solution for the steady-state output rate of an ideal coincidence detector receiving an arbitrary number of input spike trains with identical binomial count distributions (which includes Poisson statistics as a special case) and identical arbitrary pairwise cross-correlations, from zero correlation (independent processes) to perfect correlation (identical processes). Synapses vary their efficacy probabilistically according to the observed depression mechanisms. Our results show that synaptic depression, if made sufficiently strong, will result in an inverted U-shaped curve for the output rate of a coincidence detector as a function of input rate. This leads to the counterintuitive prediction that higher presynaptic (input) rates may lead to lower postsynaptic (output) rates where the output rate may fall faster than the inverse of the input rate.

Mikula, S. and Niebur, E. (in press). Synaptic depression leads to nonmonotonic frequency dependence in the coincidence detector. Neural Computation.

People involved:
Shawn Mikula
Ernst Niebur




Chaos control


Over the past 50 years, non-linear property of a single neuron has been extensively studied. These studies elucidated geometrical interpretation of neuronal action potential, its quasi-periodicity and chaotic transition. Under highly irregular input regime in cortical activities, if the deterministic characteristics have relevant significance in neuronal information processing is unknown. Yet, many researchers pointed out the deterministic (chaotic) behavior in EEG signal. Given that there is some sort of deterministic process in neuronal signal, we seek possibility to control it by external stimuli(1). Current focus is to apply the theory to stabilize higher order biologically inspired dynamical system and show the method is applicable to the large-scale biological system such as brain.

1: Schuster HG, Niebur E, Hunt ER, Johnson GA, Locher M. Parametric feedback resonance in chaotic systems. Phys Rev Lett. 1996 Jan 15;76(3):400-403.

People Involved:
Hideaki Shimazaki
Ernst Niebur



Stimulus-induced synchronization of neurons that encode objects


The neural mechanisms that allow the binding of different features in a complex visual scene to a certain object (for example, "blue" and "four-cornered" to code a blue square) is still a very much discussed question. It has been shown that cells in V1 and V2 encode feature-object relationships such as "
border ownership". Thus, the cells have to exchange information with other neurons encoding distant parts of the same figure. One theory concerning the binding problem is the so-called "Correlation Hypothesis" (von der Malsburg, 1981), which postulates a stimulus-induced synchronization of neurons that encode different aspects of the same perceived object. We test this hypothesis by analyzing the activity of simultaneously recorded pairs of neurons in the macaque visual cortex with several combined or independent static stimuli (i.e. geometric figures), and measuring the amount of excess synchronization in the evoked spike trains.

Hartmut Schuetze is PostDoc since 02/2002 in both the Niebur and the von der Heydt Labs, and evaluates spike train data from double recordings. He also is involved in psychophysical experiments on object-related visual aftereffects.




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