Sabine Kastner studies the neural basis of visual perception, attention, and awareness using a translational approach that combines neuroimaging in humans and monkeys, monkey electrophysiology and studies in patients with brain lesions. The goal of her researches is to better understand how large-scale networks operate during cognition, using the visual attention network as a model network. Her work aims to answer the question of how large-scale networks set up efficient communication and which neural code is used in different network nodes to drive behavior. Dr. Kastner has served as the Scientific Director of Princeton’s neuroimaging facility since 2005. Her contributions to the field of cognitive neuroscience were recognized with the Young Investigator Award from the Cognitive Neuroscience Society in 2005.
In 2013, Dr. Kastner published a paper in Journal of Current Biology titled “Rhythmic Sampling within and between Objects despite Sustained Attention at a Cued Location”. This paper investigated the relationship between space- and object-based selections, attentional mechanisms that are believed to play a role in directing the brain’s limited processing resources (previous evidence has demonstrated that preferential processing resulting from a spatial cue (i.e., space-based selection) spreads to uncued locations if those locations are part of the same object (i.e., resulting in object-based selection)). Up to the date of publication of this paper, it was unclear whether a single set of neuronal processes is engaged in these two selection mechanisms, or separable neural processes are involved.
The method used in the paper to resolve this question is to look at the temporal dynamics of visual-target detection under conditions of space-based selection and object-based selection, based on the facts that the nature of attentional deployment causes specific changes in synchronization of local field potentials within and between neural ensembles, and a relationship between the pre-stimulus phase of theta oscillations (at 7 Hz) and the likelihood of visual-target detection under conditions of space-based selection was previously reported.
The experimental design of this paper is shown in Figure 1. Participants (n = 14) maintained central fixation and reported the occurrence of a near-threshold change in contrast (i.e., a visual target) at the end of one of two bar-shaped objects. A spatial cue indicated the location where the visual target was most likely to occur (with 75% cue validity). Following the cue, a valid or invalid target was presented during a randomly sampled 300–1100 ms cue-to-target interval. The spatial cue was used both to guide the deployment of space-based selection and to reset the phase of ongoing neural oscillations, causing the timing of high- and low-excitability states to align across trials.
Fig 1. The Experimental Design
Figure 2A shows the time course of visual-target detection, followed by detrending in Figure 2B to more clearly reveal the periodic nature of the dependence of detection rates on the timing of target onset (cue-target interval). Figure 2C is the power spectrum of Figure 2B computed using the fast Fourier transform (FFT) algorithm. Statistical tests revealed significant peaks at approximately 8 Hz under conditions of space- (i.e., at the cued location) and object-based selection (i.e., at the same object location). This indicates a relationship between the phase of theta-band oscillations (at 7 Hz) at the time of detection and the likelihood of visual-target detection is not limited to the cued location (previously shown) but rather spreads to uncued locations that are part of the same object (i.e., share visual boundaries with the cued location). The result also suggests that attention-dependent increases in synchronization at the cued and same-object locations seem to arise from common underlying neural processes, operating at a frequency of approximately 8 Hz. FFT results also showed a consistent phase offset of approximately 90 degrees between traces of visual-target detection at the cued and same-object locations across subjects (Figure 2D), which suggests that brain regions representing different locations within the attended object are synchronized at a common frequency but have location-specific phases.Figure 2. Visual-Target Detection under Conditions of Both Space- and Object-Based Selection Reflects Increased Theta-Band Synchronization. Color coding: cued location (black line), same-object (orange line), and different-object (blue line).
There are certainly plenty of insights that are not even alluded to in this short blog due to word limit, to learn more about the beauty of them, please join us on Tuesday 3/20/2018 at 4pm at Marilyn G. Farquhar Seminar Room at CNCB.
Huanqiu Zhang is a first-year neuroscience Ph.D. student currently rotating in Dr. Maxim Bazhenov’s laboratory.