- Timescales of multineuronal activity patterns reflect temporal structure of visual stimuli (2011)
- The investigation of distributed coding across multiple neurons in the cortex remains to this date a challenge. Our current understanding of collective encoding of information and the relevant timescales is still limited. Most results are restricted to disparate timescales, focused on either very fast, e.g., spike-synchrony, or slow timescales, e.g., firing rate. Here, we investigated systematically multineuronal activity patterns evolving on different timescales, spanning the whole range from spike-synchrony to mean firing rate. Using multi-electrode recordings from cat visual cortex, we show that cortical responses can be described as trajectories in a high-dimensional pattern space. Patterns evolve on a continuum of coexisting timescales that strongly relate to the temporal properties of stimuli. Timescales consistent with the time constants of neuronal membranes and fast synaptic transmission (5–20 ms) play a particularly salient role in encoding a large amount of stimulus-related information. Thus, to faithfully encode the properties of visual stimuli the brain engages multiple neurons into activity patterns evolving on multiple timescales.
- A matter of time : millisecond delays between action potentials convey stimulus information in the primary visual cortex (2008)
- Synchronized neural activity in the visual cortex is associated with small time delays (up to ~10 ms). The magnitude and direction of these delays depend on stimulus properties. Thus, synchronized neurons produce fast sequences of action potentials, and the order in which units tend to fire within these sequences is stimulusdependent, but not stimulus-locked. In the present thesis, I investigated whether such preferred firing sequences repeat with sufficient accuracy to serve as a neuronal code. To this end, I developed a method for extracting the preferred sequence of firing in a group of neurons from their pair-wise preferred delays, as measured by the offsets of the centre peaks in their cross-correlation histograms. This analysis method was then applied to highly parallel recordings of neuronal spiking activity made in area 17 of anaesthetized cats in response to simple visual stimuli, like drifting gratings and moving bars. Using a measure of effect size, I then analyzed the accuracy with which preferred firing sequences reflected stimulus properties, and found that in the presence of gamma oscillations, the time at which a unit fired in the firing sequence conveyed stimulus information almost as precisely as the firing rate of the same unit. Moreover, the stimulus-dependent changes in firing rates and firing times were largely unrelated, suggesting that the information they carry is not redundant. Thus, despite operating at a time scale of only a few milliseconds, firing sequences have the strong potential to provide a precise neural code that can complement firing rates in the cortical processing of stimulus information.