• Publications
  • Influence
Ultrafast Population Encoding by Cortical Neurons
The processing speed of the brain depends on the ability of neurons to rapidly relay input changes. Previous theoretical and experimental studies of the timescale of population firing rate responsesExpand
  • 82
  • 9
  • PDF
Correlations and synchrony in threshold neuron models.
We study how threshold models and neocortical neurons transfer temporal and interneuronal input correlations to correlations of spikes. In both, we find that the low common input regime is governedExpand
  • 90
  • 8
  • PDF
Oscillations emerging from noise-driven steady state in networks with electrical synapses and subthreshold resonance
Oscillations play a critical role in cognitive phenomena and have been observed in many brain regions. Experimental evidence indicates that classes of neurons exhibit properties that could promoteExpand
  • 38
  • 4
  • PDF
Signatures of Synchrony in Pairwise Count Correlations
TLDR
We investigate under which conditions the correlation coefficients reflect the degree of input synchrony and when they can be used to build population models. Expand
  • 43
  • 1
  • PDF
Representation of Dynamical Stimuli in Populations of Threshold Neurons
TLDR
We provide explicit expressions for the linear and non-linear frequency response functions in the presence of correlated noise and use them to derive population rate response to step-like stimuli. Expand
  • 20
  • 1
  • PDF
Stabilized supralinear network can give rise to bistable, oscillatory, and persistent activity
TLDR
We show that the stabilized supralinear network (SSN) model, which was originally proposed for sensory integration phenomena such as contrast invariance, normalization, and surround suppression, can give rise to dynamic cortical features of working memory, persistent activity, and rhythm generation. Expand
  • 13
  • 1
Temporal pairwise spike correlations fully capture single-neuron information
TLDR
We show that temporal pairwise spike correlations fully determine the information conveyed by a single spiking neuron with finite temporal memory and stationary spike statistics. Expand
  • 20
  • PDF
Spike Correlations – What Can They Tell About Synchrony?
TLDR
We showed that many features of pairwise spike correlations can be studied analytically in a tractable threshold model based on the threshold crossings of correlated Gaussian potentials. Expand
  • 15
  • PDF
Correlated neuronal activity and its relationship to coding, dynamics and network architecture
TLDR
Correlated and synchronous activity in populations of neurons has been observed in many brain regions and has been shown to play a crucial role in cortical coding, attention, and network dynamics (Singer and Gray, 1995; Salinas and Sejnowski, 2001). Expand
  • 10
  • PDF
Energy‐efficient encoding by shifting spikes in neocortical neurons
The speed of computations in neocortical networks critically depends on the ability of populations of spiking neurons to rapidly detect subtle changes in the input and translate them into firing rateExpand
  • 10
  • PDF