Sensory information in local field potentials and spikes from visual and auditory cortices: time scales and frequency bands.

Studies analyzing sensory cortical processing or trying to decode brain activity often rely on a combination of different electrophysiological signals, such as local field potentials (LFPs) and spiking activity. Understanding the relation between these signals and sensory stimuli and between different components of these signals is hence of great interest. We here provide an analysis of LFPs and spiking activity recorded from visual and auditory cortex during stimulation with natural stimuli. In particular, we focus on the time scales on which different components of these signals are informative about the stimulus, and on the dependencies between different components of these signals. Addressing the first question, we find that stimulus information in low frequency bands (<12 Hz) is high, regardless of whether their energy is computed at the scale of milliseconds or seconds. Stimulus information in higher bands (>50 Hz), in contrast, is scale dependent, and is larger when the energy is averaged over several hundreds of milliseconds. Indeed, combined analysis of signal reliability and information revealed that the energy of slow LFP fluctuations is well related to the stimulus even when considering individual or few cycles, while the energy of fast LFP oscillations carries information only when averaged over many cycles. Addressing the second question, we find that stimulus information in different LFP bands, and in different LFP bands and spiking activity, is largely independent regardless of time scale or sensory system. Taken together, these findings suggest that different LFP bands represent dynamic natural stimuli on distinct time scales and together provide a potentially rich source of information for sensory processing or decoding brain activity.

Low-frequency local field potentials and spikes in primary visual cortex convey independent visual information.

Local field potentials (LFPs) reflect subthreshold integrative processes that complement spike train measures. However, little is yet known about the differences between how LFPs and spikes encode rich naturalistic sensory stimuli. We addressed this question by recording LFPs and spikes from the primary visual cortex of anesthetized macaques while presenting a color movie. We then determined how the power of LFPs and spikes at different frequencies represents the visual features in the movie. We found that the most informative LFP frequency ranges were 1-8 and 60-100 Hz. LFPs in the range of 12-40 Hz carried little information about the stimulus, and may primarily reflect neuromodulatory inputs. Spike power was informative only at frequencies <12 Hz. We further quantified "signal correlations" (correlations in the trial-averaged power response to different stimuli) and "noise correlations" (trial-by-trial correlations in the fluctuations around the average) of LFPs and spikes recorded from the same electrode. We found positive signal correlation between high-gamma LFPs (60-100 Hz) and spikes, as well as strong positive signal correlation within high-gamma LFPs, suggesting that high-gamma LFPs and spikes are generated within the same network. LFPs <24 Hz shared strong positive noise correlations, indicating that they are influenced by a common source, such as a diffuse neuromodulatory input. LFPs <40 Hz showed very little signal and noise correlations with LFPs >40 Hz and with spikes, suggesting that low-frequency LFPs reflect neural processes that in natural conditions are fully decoupled from those giving rise to spikes and to high-gamma LFPs.

The effect of artifacts on dependence measurement in fMRI.

The study of effective connectivity by means of neuroimaging depends on the measurement of similarity between activity patterns at different locations in the brain, without necessarily presupposing a particular model for this dependence. When these interactions are measured using functional magnetic resonance imaging (fMRI) techniques, however, imaging and physiological artifacts create patterns of dependence that may be unrelated to cortical activity. We demonstrate some of these effects through the measurement of short-range dependencies present in fMRI scans of the primary visual cortex (V1) in the anaesthetized macaque monkey. High-field (4.7 T) fMRI scans were conducted to measure responses based on the blood oxygen level-dependent contrast mechanism, during periods of no sensory stimulation and of visual stimulation with rotating polar-transformed checkerboard gratings. Dependence between the haemodynamic activity at different spatial locations (i.e., different voxels) was measured using correlation, mutual information and functional covariance. Particular attention was paid to understanding the sources of spurious dependence that may be observed during such investigations. Two main effects were detected: (a) short-range correlations introduced by the process of image reconstruction and (b) perturbations in the haemodynamic response caused by breathing. The image reconstruction artifacts were shown to create an artificially high short-range dependence in the readout direction of the scan, and the breathing artifacts caused enhanced short-range dependence in both the readout and phase-encode directions. Additional dependence in the phase-encode direction due to image-ghosting is also possible but will not be discussed in this report, as it can be alleviated by fine adjustment of preemphasis (elimination of eddy currents). A technique is described for removing breathing artifacts, and the effect of breathing on the apparent dependence between voxels is illustrated. The correlation of haemodynamic activity with the stimulus was found to be affected by breathing, although this effect can be neutralised by averaging the haemodynamic responses over many repetitions of the stimulus. Nonetheless, patterns of dependent activity between voxels may be lost in this averaging process, which makes the removal of breathing artifacts necessary if statistical dependence and the study of effective connectivity is the primary aim of an investigation.