This allowed us to collect hundreds of neural population responses evoked by the exact same visual stimulus (including identical stimulus history up to several minutes). Figure 1A shows examples of ...

The encoding manifold was constructed in a two-stage procedure with no knowledge of the model’s underlying circuitry (Fig. 2 B and C and Materials and Methods): First, nonnegative tensor factorization ...

As in any good democracy, individual neurons count for little; it is population activity that matters. For example, as with control of eye 1,2 and arm 3 movements, visual discrimination in the ...

Neural encoding schemes: Poisson encoding: Encodes visual data into spike trains based on Poisson distributions. Time-To-First-Spike (TTFS): Encodes pixel intensities into spike times. Numerical ...

Neural encoding plays an important role in faithfully describing the temporally rich patterns, whose instances include human speech and environmental sounds. To classify such spatio-temporal patterns ...

These findings lead to new and interesting questions related to how the evolving neural code informs higher-level cognitive processes when people are engaged in different tasks. “We know that the code ...

Summary: Unveiling the neurological enigma of traumatic memory formation, researchers harnessed innovative optical and machine-learning methodologies to decode the brain’s neuronal networks engaged ...

We present a method for understanding the functional relationships among large populations of neurons in complex circuits such as the retina and primary visual cortex that allows a global comparison ...