Variability and Correlations in Primary Visual Cortical Neurons Driven by Fixational Eye Movements

Abstract

The ability to distinguish between elements of a sensory neuron's activity that are stimulus independent versus driven by the stimulus is critical for addressing many questions in systems neuroscience. This is typically accomplished by measuring neural responses to repeated presentations of identical stimuli and identifying the trial-variable components of the response as noise. In awake primates, however, small "fixational" eye movements (FEMs) introduce uncontrolled trial-to-trial differences in the visual stimulus itself, potentially confounding this distinction. Here, we describe novel analytical methods that directly quantify the stimulus-driven and stimulusindependent components of visual neuron responses in the presence of FEMs. We apply this approach, combined with precise model-based eye tracking, to recordings from primary visual cortex (V1), finding that standard approaches that ignore FEMs typically miss more than half of the stimulus-driven neural response variance, creating substantial biases in measures of response reliability. We show that these effects are likely not isolated to the particular experimental conditions used here, such as the choice of visual stimulus or spike measurement time window, and thus will be a more general problem for V1 recordings in awake primates. We also demonstrate that measurements of the stimulus-driven and stimulus-independent correlations among pairs of V1 neurons can be greatly biased by FEMs. These results thus illustrate the potentially dramatic impact of FEMs on measures of signal and noise in visual neuron activity and also demonstrate a novel approach for controlling for these eye-movement-induced effects.

The Magnitude, But Not the Sign, of MT Single-Trial Spike-Time Correlations Predicts Motion Detection Performance

“…9G). Consistent with previous results (Martinez-Conde et al, 2000), we observed a significant modulation in firing rates around the time of these small eye movements (Fig. 9G, orange is the control MU firing rate aligned to randomly shuffled microsaccades).…”

“…Next, we examined the effects of small eye movements on our MU responses. During a trial, small eye movements such as microsaccades can modulate neural activity in area MT (Herrington et al, 2009) and areas that drive MT such as V1 (Snodderly et al, 2001;McFarland et al, 2016), which could introduce spike-time correlations between our two MT sensory pools. We extracted the occurrence of putative microsaccades as shown by the example trial in Figure 9F (asterisks indicate that three saccades in the 300 ms analysis window aligned the motion pulse; see Materials and Methods).…”

Stimulus content shapes cortical response statistics

“…Using awake and task-engaged monkeys eliminates this confound and ensures that collective fluctuations, which introduce uncontrolled factors into the measured correlations, are minimized . Eye movements have been shown to contribute to correlations in the visual cortex (McFarland et al, 2016). In our case monkeys were rewarded to fixate on a spot at the center of the screen during the presentation of off-foveal stimuli and trials in which fixation could not be maintained were removed from the analysis.…”

Attentional fluctuations induce shared variability in macaque primary visual cortex

“…Fixational eye movements, also called micro-saccades, have been reported to modulate neuronal activity in the visual system, 38,39 contribute to neuronal response variability, 40,41 and act as an index of the focus of covert spatial attention based on subtle changes in their directionality with attention condition. 42 Given these findings, we considered two means by which micro-saccades could account for our results.…”