The fixation-related lambda response: Effects of saccade magnitude, spatial frequency, and ocular artifact removal.

Fixation-related potentials (FRPs) enable examination of electrophysiological signatures of visual perception under naturalistic conditions, providing a neural snapshot of the fixated scene. The most prominent FRP component, commonly referred to as the lambda response, is a large deflection over occipital electrodes (O1, Oz, O2) peaking 80-100 ms post fixation, reflecting afferent input to visual cortex. The lambda response is affected by bottom-up stimulus features and the size of the preceding saccade; however, prior research has not adequately controlled for these influences in free viewing paradigms.

Isolating Discriminant Neural Activity in the Presence of Eye Movements and Concurrent Task Demands.

A growing number of studies use the combination of eye-tracking and electroencephalographic (EEG) measures to explore the neural processes that underlie visual perception. In these studies, fixation-related potentials (FRPs) are commonly used to quantify early and late stages of visual processing that follow the onset of each fixation. However, FRPs reflect a mixture of bottom-up (sensory-driven) and top-down (goal-directed) processes, in addition to eye movement artifacts and unrelated neural activity.

The Impact of Task Demands on Fixation-Related Brain Potentials during Guided Search.

Recording synchronous data from EEG and eye-tracking provides a unique methodological approach for measuring the sensory and cognitive processes of overt visual search. Using this approach we obtained fixation related potentials (FRPs) during a guided visual search task specifically focusing on the lambda and P3 components. An outstanding question is whether the lambda and P3 FRP components are influenced by concurrent task demands.

Common EEG features for behavioral estimation in disparate, real-world tasks.

In this study we explored the potential for capturing the behavioral dynamics observed in real-world tasks from concurrent measures of EEG. In doing so, we sought to develop models of behavior that would enable the identification of common cross-participant and cross-task EEG features. To accomplish this we had participants perform both simulated driving and guard duty tasks while we recorded their EEG.

Linear and non-linear properties of feature selectivity in V4 neurons.

Extrastriate area V4 is a critical component of visual form processing in both humans and non-human primates. Previous studies have shown that the tuning properties of V4 neurons demonstrate an intermediate level of complexity that lies between the narrow band orientation and spatial frequency tuning of neurons in primary visual cortex and the highly complex object selectivity seen in inferotemporal neurons. However, the nature of feature selectivity within this cortical area is not well understood, especially in the context of natural stimuli.

Estimating endogenous changes in task performance from EEG.

Brain wave activity is known to correlate with decrements in behavioral performance as individuals enter states of fatigue, boredom, or low alertness.Many BCI technologies are adversely affected by these changes in user state, limiting their application and constraining their use to relatively short temporal epochs where behavioral performance is likely to be stable. Incorporating a passive BCI that detects when the user is performing poorly at a primary task, and adapts accordingly may prove to increase overall user performance.

Isolating the neural mechanisms of interference during continuous multisensory dual-task performance.

The need to engage in multiple tasks simultaneously is often encountered in everyday experience, but coordinating between two or more tasks can lead to impaired performance. Typical investigations of multitasking impairments have focused on the performance of two tasks presented in close temporal proximity on discrete trials; however, such paradigms do not match well with the continuous performance situations more typically encountered outside the laboratory. As a result, the stages of information processing that are affected during multisensory continuous dual tasks and how these changes in processing relate to behavior remain unclear.

Real-time measurement of face recognition in rapid serial visual presentation.

Event-related potentials (ERPs) have been used extensively to study the processes involved in recognition memory. In particular, the early familiarity component of recognition has been linked to the FN400 (mid-frontal negative deflection between 300 and 500 ms), whereas the recollection component has been linked to a later positive deflection over the parietal cortex (500-800 ms). In this study, we measured the ERPs elicited by faces with varying degrees of familiarity.

ePPR: a new strategy for the characterization of sensory cells from input/output data.

A central goal of systems neuroscience is to characterize the transformation of sensory input to spiking output in single neurons. This problem is complicated by the large dimensionality of the inputs. To cope with this problem, previous methods have estimated simplified versions of a generic linear-nonlinear (LN) model and required, in most cases, stimuli with constrained statistics.

Contextual modulation of orientation tuning contributes to efficient processing of natural stimuli.

It has been proposed that sensory neurons are adapted to the statistical structure of the natural environment in order to encode natural stimuli efficiently. While spatiotemporal correlations in luminance signals may be decorrelated by neurons in early visual processing stages, higher-order correlations, such as those in the orientation domain, are likely to persist in the input representation until the cortical level. In this study, we first examine orientation correlations in natural stimuli across brief time intervals and across nearby regions of space, and find strong correlations in both domains.

Cortical sensitivity to visual features in natural scenes.

A central hypothesis concerning sensory processing is that the neuronal circuits are specifically adapted to represent natural stimuli efficiently. Here we show a novel effect in cortical coding of natural images. Using spike-triggered average or spike-triggered covariance analyses, we first identified the visual features selectively represented by each cortical neuron from its responses to natural images.

Spatial structure of complex cell receptive fields measured with natural images.

Neuronal receptive fields (RFs) play crucial roles in visual processing. While the linear RFs of early neurons have been well studied, RFs of cortical complex cells are nonlinear and therefore difficult to characterize, especially in the context of natural stimuli. In this study, we used a nonlinear technique to compute the RFs of complex cells from their responses to natural images.

Isolation of relevant visual features from random stimuli for cortical complex cells.

A crucial step in understanding the function of a neural circuit in visual processing is to know what stimulus features are represented in the spiking activity of the neurons. For neurons with complex, nonlinear response properties, characterization of feature representation requires measurement of their responses to a large ensemble of visual stimuli and an analysis technique that allows identification of relevant features in the stimuli. In the present study, we recorded the responses of complex cells in the primary visual cortex of the cat to spatiotemporal random-bar stimuli and applied spike-triggered correlation analysis of the stimulus ensemble.