The deployment of eye movements to complex spatiotemporal stimuli likely involves a variety of cognitive factors. However, eye movements to movies are surprisingly reliable both within and across observers. We exploited and manipulated that reliability to characterize observers’ temporal viewing strategies. Introducing cuts and scrambling the temporal order of the resulting clips systematically changed eye movement reliability. We developed a computational model that exhibited this behavior and provided an excellent fit to the measured eye movement reliability. The model assumed that observers searched for, found, and tracked a point-of-interest, and that this process reset when there was a cut. The model did not require that eye movements depend on temporal context in any other way, and it managed to describe eye movements consistently across different observers and two movie sequences. Thus, we found no evidence for the integration of information over long time scales (greater than a second). The results are consistent with the idea that observers employ a simple tracking strategy even while viewing complex, engaging naturalistic stimuli.

Functional magnetic resonance imaging (fMRI) studies have relied on multivariate analysis methods to decode visual motion direction from measurements of cortical activity. Above-chance decoding has been commonly used to infer the motion-selective response properties of the underlying neural populations. Moreover, patterns of reliable response biases across voxels that underlie decoding have been interpreted to reflect maps of functional architecture. Using fMRI, we identified a direction-selective response bias in human visual cortex that: (1) predicted motion-decoding accuracy; (2) depended on the shape of the stimulus aperture rather than the absolute direction of motion, such that response amplitudes gradually decreased with distance from the stimulus aperture edge corresponding to motion origin; and 3) was present in V1, V2, V3, but not evident in MTϩ, explaining the higher motion-decoding accuracies reported previously in early visual cortex. These results demonstrate that fMRI-based motion decoding has little or no dependence on the underlying functional organization of motion selectivity.

Currently, non-invasive methods for studying the human brain do not routinely and reliably measure spike-rate-dependent signals, independent of responses such as hemodynamic coupling (fMRI) and subthreshold neuronal synchrony (oscillations and event-related potentials). In contrast, invasive methods—microelectrode recordings and electrocorticography (ECoG)—have recently measured broadband power elevation in field potentials (~50–200 Hz) as a proxy for locally averaged spike rates. Here, we sought to detect and quantify stimulus-related broadband responses using magnetoencephalography (MEG). Extracranial measurements like MEG and EEG have multiple global noise sources and relatively low signal-to-noise ratios; moreover high frequency artifacts from eye movements can be confounded with stimulus design and mistaken for signals originating from brain activity. For these reasons, we developed an automated denoising technique that helps reveal the broadband signal of interest. Subjects viewed 12-Hz contrast-reversing patterns in the left, right, or bilateral visual field. Sensor time series were separated into evoked (12-Hz amplitude) and broadband components (60–150 Hz). In all subjects, denoised broadband responses were reliably measured in sensors over occipital cortex, even in trials without microsaccades. The broadband pattern was stimulus-dependent, with greater power contralateral to the stimulus. Because we obtain reliable broadband estimates with short experiments (~20 minutes), and with sufficient signal-to-noise to distinguish responses to different stimuli, we conclude that MEG broadband signals, denoised with our method, offer a practical, non-invasive means for characterizing spike-rate-dependent neural activity for addressing scientific questions about human brain function.

First-order (contrast) surround suppression has been well characterized both psychophysically and physiologically, but relatively little is known as to whether the perception of second-order visual stimuli exhibits analogous center-surround interactions. Second-order surround suppression was characterized by requiring subjects to detect second-order modulation in stimuli presented alone or embedded in a surround. Both contrast-(CM) and orientation-modulated (OM) stimuli were used. For most subjects and both OM and CM stimuli, second-order surrounds caused thresholds to be higher, indicative of second-order suppression. For CM stimuli, suppression was orientation-specific, i.e., higher thresholds for parallel than for orthogonal surrounds. However, the evidence for orientation specificity of suppression for OM stimuli was weaker. These results suggest that normalization, leading to surround suppression, operates at multiple stages in cortical processing.

1Currently, non-invasive methods for studying the human brain do not reliably measure signals that 2 depend on the rate of action potentials (spikes) in a neural population, independent of other 3 responses such as hemodynamic coupling (functional magnetic resonance imaging) and 4 subthreshold neuronal synchrony (oscillations and event-related potentials). In contrast, invasive 5 methods -animal microelectrode recordings and human intracortical recordings 6 (electrocorticography, or ECoG) -have recently measured broadband power elevation spanning 7 50-200 Hz in electrical fields generated by neuronal activity as a proxy for the locally averaged 8 spike rates. Here, we sought to detect and quantify stimulus-related broadband responses using a 9 non-invasive method -magnetoencephalography (MEG) -in individual subjects. CC-BY-NC-ND 4.0 International license peer-reviewed) is the author/funder. It is made available under aThe copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/108993 doi: bioRxiv preprint first posted online Feb. 15, 2017; 2 Author Summary 24Neuronal activity causes perturbations in nearby electrical fields. These perturbations can be 25 measured non-invasively in the living human brain using electro-and magneto-encephalography 26 (EEG and MEG). These two techniques have generally emphasized two kinds of measurements: 27 oscillations and event-related responses, both of which reflect synchronous activity from large 28 populations of neurons. A third type of signal, a stimulus-related increase in power spanning a 29 wide range of frequencies ('broadband'), is routinely measured in invasive recordings in animals 30 and pre-surgical patients with implanted electrodes, but not with MEG and EEG. This broadband 31 response is of great interest because unlike oscillations and event-related responses, it is correlated 32 with neuronal spike rates. Here we report quantitative, spatially specific measurements of 33 broadband fields in individual human subjects using MEG. These results demonstrate that a spike-34 rate-dependent measure of brain activity can be obtained non-invasively from the living human 35 brain, and is suitable for investigating a wide range of questions about spiking activity in the human 36 brain.