Scene complexity modulates degree of feedback activity during object detection in natural scenes

Selective brain responses to objects arise within a few hundreds of milliseconds of neural processing, suggesting that visual object recognition is mediated by rapid feed-forward activations. Yet disruption of neural responses in early visual cortex beyond feed-forward processing stages affects object recognition performance. Here, we unite these discrepant findings by reporting that object recognition involves enhanced feedback activity (recurrent processing within early visual cortex) when target objects are embedded in natural scenes that are characterized by high complexity. Human participants performed an animal target detection task on natural scenes with low, medium or high complexity as determined by a computational model of low-level contrast statistics. Three converging lines of evidence indicate that feedback was selectively enhanced for high complexity scenes. First, functional magnetic resonance imaging (fMRI) activity in early visual cortex (V1) was enhanced for target objects in scenes with high, but not low or medium complexity. Second, event-related potentials (ERPs) evoked by target objects were selectively enhanced at feedback stages of visual processing (from ~220 ms onwards) for high complexity scenes only. Third, behavioral performance for high complexity scenes deteriorated when participants were pressed for time and thus less able to incorporate the feedback activity. Modeling of the reaction time distributions using drift diffusion revealed that object information accumulated more slowly for high complexity scenes, with evidence accumulation being coupled to trial-to-trial variation in the EEG feedback response. Together, these results suggest that while feed-forward activity may suffice to recognize isolated objects, the brain employs recurrent processing more adaptively in naturalistic settings, using minimal feedback for simple scenes and increasing feedback for complex scenes

The spatiotemporal profile of cortical processing leading up to visual perception

Much controversy exists around the locus of conscious visual perception in human cortex. Some authors have proposed that its neural correlates correspond with recurrent processing within visual cortex, whereas others have argued they are located in a frontoparietal network. The present experiment aims to bring together these competing viewpoints. We recorded EEG from human subjects that were engaged in detecting masked visual targets. From this, we obtained a spatiotemporal profile of neural activity selectively related to the processing of the targets, which we correlated with the subjects' ability to detect those targets. This made it possible to distinguish between those stages of visual processing that correlate with human perception and those that do not. The results show that target induced extra-striate feedforward activity peaking at 121 ms does not correlate with perception, whereas more posterior recurrent activity peaking at 160 ms does. Several subsequent stages show an alternating pattern of frontoparietal and occipital activity, all of which correlate highly with perception. This shows that perception emerges early on, but only after an initial feedforward volley, and suggests that multiple reentrant loops are involved in propagating this signal to frontoparietal areas

Quadrupole Collective States in a Large Single-J Shell

We discuss the ability of the generator coordinate method (GCM) to select collective states in microscopic calculations. The model studied is a single-$j$ shell with hamiltonian containing the quadrupole-quadrupole interaction. Quadrupole collective excitations are constructed by means of the quadrupole single-particle operator. Lowest collective bands for $j$=31/2 and particle numbers $N$=4,6,8,10,12, and $14$ are found. For lower values of $j$, exact solutions are obtained and compared with the GCM results.Comment: submitted for publication in Phys. Rev. C, revtex, 28 pages, 15 PostScript figures available on request from [email protected], preprint No. IFT/17/9

A chronometric exploration of high-resolution ‘sensitive TMS masking’ effects on subjective and objective measures of vision

Transcranial magnetic stimulation (TMS) can induce masking by interfering with ongoing neural activity in early visual cortex. Previous work has explored the chronometry of occipital involvement in vision by using single pulses of TMS with high temporal resolution. However, conventionally TMS intensities have been high and the only measure used to evaluate masking was objective in nature. Recent studies have begun to incorporate subjective measures of vision, alongside objective ones. The current study goes beyond previous work in two regards. First, we explored both objective vision (an orientation discrimination task) and subjective vision (a stimulus visibility rating on a four-point scale), across a wide range of time windows with high temporal resolution. Second, we used a very sensitive TMS-masking paradigm: stimulation was at relatively low TMS intensities, with a figure-8 coil, and the small stimulus was difficult to discriminate already at baseline level. We hypothesized that this should increase the effective temporal resolution of our paradigm. Perhaps for this reason, we are able to report a rather interesting masking curve. Within the classical-masking time window, previously reported to encompass broad SOAs anywhere between 60 and 120 ms, we report not one, but at least two dips in objective performance, with no masking in-between. The subjective measure of vision did not mirror this pattern. These preliminary data from our exploratory design suggest that, with sensitive TMS masking, we might be able to reveal visual processes in early visual cortex previously unreported

Population Receptive Field Dynamics in Human Visual Cortex

Seminal work in the early nineties revealed that the visual receptive field of neurons in cat primary visual cortex can change in location and size when artificial scotomas are applied. Recent work now suggests that these single neuron receptive field dynamics also pertain to the neuronal population receptive field (pRF) that can be measured in humans with functional magnetic resonance imaging (fMRI). To examine this further, we estimated the pRF in twelve healthy participants while masking the central portion of the visual field. We found that the pRF changes in location and size for two differently sized artificial scotomas, and that these pRF dynamics are most likely due to a combination of the neuronal receptive field position and size scatter as well as modulatory feedback signals from extrastriate visual areas

Dos and don’ts in response priming research

Response priming is a well-understood but sparsely employed paradigm in cognitive science. The method is powerful and well-suited for exploring early visuomotor processing in a wide range of tasks and research fields. Moreover, response priming can be dissociated from visual awareness, possibly because it is based on the first sweep of feedforward processing of primes and targets. This makes it a theoretically interesting device for separating conscious and unconscious vision. We discuss the major opportunities of the paradigm and give specific recommendations (e.g., tracing the time-course of priming in parametric experiments). Also, we point out typical confounds, design flaws, and data processing artifacts

Feed-Forward Segmentation of Figure-Ground and Assignment of Border-Ownership

Figure-ground is the segmentation of visual information into objects and their surrounding backgrounds. Two main processes herein are boundary assignment and surface segregation, which rely on the integration of global scene information. Recurrent processing either by intrinsic horizontal connections that connect surrounding neurons or by feedback projections from higher visual areas provide such information, and are considered to be the neural substrate for figure-ground segmentation. On the contrary, a role of feedforward projections in figure-ground segmentation is unknown. To have a better understanding of a role of feedforward connections in figure-ground organization, we constructed a feedforward spiking model using a biologically plausible neuron model. By means of surround inhibition our simple 3-layered model performs figure-ground segmentation and one-sided border-ownership coding. We propose that the visual system uses feed forward suppression for figure-ground segmentation and border-ownership assignment