There is increasing evidence that the brain relies on a set of canonical neural computations,
repeating them across brain regions and modalities to apply similar operations to different …

Response reliability is complementary to more conventional measurements of response
amplitudes, and can reveal phenomena that response amplitudes do not. Here we review …

Spiking neural networks (SNNs) that enables energy efficient implementation on emerging
neuromorphic hardware are gaining more attention. Yet now, SNNs have not shown …

We describe an image compression method, consisting of a nonlinear analysis
transformation, a uniform quantizer, and a nonlinear synthesis transformation. The …

Mounting evidence suggests that 'core object recognition,'the ability to rapidly recognize
objects despite substantial appearance variation, is solved in the brain via a cascade of …

Spiking neural networks (SNNs) are attracting widespread interest due to their biological
plausibility, energy efficiency, and powerful spatiotemporal information representation …

Maximum entropy models are the least structured probability distributions that exactly
reproduce a chosen set of statistics measured in an interacting network. Here we use this …

The response of neurons in sensory cortex to repeated stimulus presentations is highly
variable. To investigate the nature of this variability, we compared the spike activity of …

We present an image quality metric based on the transformations associated with the early
visual system: local luminance subtraction and local gain control. Images are decomposed …

Many sensory-driven behaviors rely on predictions about future states of the environment.
Visual input typically evolves along complex temporal trajectories that are difficult to …