The Lemon Illusion: Seeing curvature where there is none

Curvature is a highly informative visual cue for shape perception and object recognition. We introduce a novel illusion—the Lemon Illusion—in which subtle illusory curvature is perceived along contour regions that are devoid of physical curvature. We offer several perceptual demonstrations and observations that lead us to conclude that the Lemon Illusion is an instance of a more general illusory curvature phenomenon, one in which the presence of contour curvature discontinuities lead to the erroneous extension of perceived curvature. We propose that this erroneous extension of perceived curvature results from the interaction of neural mechanisms that operate on spatially local contour curvature signals with higher-tier mechanisms that serve to establish more global representations of object shape. Our observations suggest that the Lemon Illusion stems from discontinuous curvature transitions between rectilinear and curved contour segments. However, the presence of curvature discontinuities is not sufficient to produce the Lemon Illusion, and the minimal conditions necessary to elicit this subtle and insidious illusion are difficult to pin down

Induced and Evoked Human Electrophysiological Correlates of Visual Working Memory Set-Size Effects at Encoding

The ability to encode, store, and retrieve visually presented objects is referred to as visual working memory (VWM). Although crucial for many cognitive processes, previous research reveals that VWM strictly capacity limited. This capacity limitation is behaviorally observable in the set size effect: the ability to successfully report items in VWM asymptotes at a small number of items. Research into the neural correlates of set size effects and VWM capacity limits in general largely focus on the maintenance period of VWM. However, we previously reported that neural resources allocated to individual items during VWM encoding correspond to successful VWM performance. Here we expand on those findings by investigating neural correlates of set size during VWM encoding. We hypothesized that neural signatures of encoding-related VWM capacity limitations should be differentiable as a function of set size. We tested our hypothesis using High Density Electroencephalography (HD-EEG) to analyze frequency components evoked by flickering target items in VWM displays of set size 2 or 4. We found that set size modulated the amplitude of the 1st and 2nd harmonic frequencies evoked during successful VWM encoding across frontal and occipital-parietal electrodes. Frontal sites exhibited the most robust effects for the 2nd harmonic (set size 2 > set size 4). Additionally, we found a set-size effect on the induced power of delta-band (1-4 Hz) activity (set size 2 > set size 4). These results are consistent with a capacity limited VWM resource at encoding that is distributed across to-be-remembered items in a VWM display. This resource may work in conjunction with a task-specific selection process that determines which items are to be encoded and which are to be ignored. These neural set size effects support the view that VWM capacity limitations begin with encoding related processes

Visual working memory task and data processing sequence.

<p>(A) Participants viewed an initial fixation screen (600ms) followed by a memory array (1000ms) in which each item flicked at a distinct frequency (3 Hz, 5 Hz, 12 Hz and 20 Hz). Set size was manipulated to create 2 conditions, set size 2 or set size 4. A delay period (1000ms) followed the stimulus presentation. Finally, a single probed stimulus appeared in one of the four previously presented locations. Participants were instructed to indicate whether the probed stimulus was old (same shape in same location) or new (different shape). <i>Note</i>: <i>black squares were used in the fixation period to control for onset VEP responses that could contaminate the data</i>. (B) Epochs lasting 1000 ms time-locked to the onset of the memory array were extracted from the raw data. (C) In the evoked analysis, once epochs in each condition were averaged together, a Fourier Transform was applied to the data so that the frequency tag amplitudes could be extracted for the fundamental (red) and harmonic (green) frequencies corresponding to probed items in the stimulus array. Conversely, in the induced condition, the Fourier Transform is applied to each trial prior to averaging.</p

Index values and T-stats depicting induced power set size effects (2 vs. 4) at encoding.

<p>(A) Index values (described Materials and methods section: Induced power frequency analysis) plotted on topographic maps. Green corresponds to set size 4 > set size 2, purple corresponds to set size 2 > set size 4. (B) t-stats plotted on topographic maps. Plotted values correspond t-stats at or below a p value of 0.05. Red corresponds to set size 4 > set size 2, blue corresponds to set size 2 > set size 4. (C) t-stats at each electrode arranged by p values. Green dotted line represents a threshold of α = 0.05. Channels significant at or above the FDR threshold are represented by a thicker border. Each row depicts data from a single frequency band: delta (top), theta, alpha, beta, gamma (bottom).</p

Index values and T-stats depicting set size effects (2 vs. 4) at encoding.

<p>(A) Index values (described in Materials and methods section: Frequency-tagging (evoked) analysis) plotted on topographic maps. Green corresponds to set size 4 > set size 2, purple corresponds to set size 2 > set size 4. (B) t-stats plotted on topographic maps. Plotted values correspond to t-stats at or below a <i>p</i> value of 0.05. Red corresponds to set size 4 > set size 2, blue corresponds to set size 2 > set size 4. (C) t-stats at each electrode arranged by p values. Green dotted line represents a threshold of α = 0.05. Red line represents an FDR corrected threshold for <i>q = 0</i>.<i>1</i> (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0167022#sec012" target="_blank">results</a> section: Analysis of frequency tagging amplitude and set size effects). Channels significant at or above the FDR threshold are represented by a thicker border.</p

The psychosis human connectome project: Design and rationale for studies of visual neurophysiology

Visual perception is abnormal in psychotic disorders such as schizophrenia. In addition to hallucinations, laboratory tests show differences in fundamental visual processes including contrast sensitivity, center-surround interactions, and perceptual organization. A number of hypotheses have been proposed to explain visual dysfunction in psychotic disorders, including an imbalance between excitation and inhibition. However, the precise neural basis of abnormal visual perception in people with psychotic psychopathology (PwPP) remains unknown. Here, we describe the behavioral and 7 tesla MRI methods we used to interrogate visual neurophysiology in PwPP as part of the Psychosis Human Connectome Project (HCP). In addition to PwPP (n = 66) and healthy controls (n = 43), we also recruited first-degree biological relatives (n = 44) in order to examine the role of genetic liability for psychosis in visual perception. Our visual tasks were designed to assess fundamental visual processes in PwPP, whereas MR spectroscopy enabled us to examine neurochemistry, including excitatory and inhibitory markers. We show that it is feasible to collect high-quality data across multiple psychophysical, functional MRI, and MR spectroscopy experiments with a sizable number of participants at a single research site. These data, in addition to those from our previously described 3 tesla experiments, will be made publicly available in order to facilitate further investigations by other research groups. By combining visual neuroscience techniques and HCP brain imaging methods, our experiments offer new opportunities to investigate the neural basis of abnormal visual perception in PwPP

Induced and Evoked Human Electrophysiological Correlates of Visual Working Memory Set-Size Effects at Encoding

The ability to encode, store, and retrieve visually presented objects is referred to as visual working memory (VWM). Although crucial for many cognitive processes, previous research reveals that VWM strictly capacity limited. This capacity limitation is behaviorally observable in the set size effect: the ability to successfully report items in VWM asymptotes at a small number of items. Research into the neural correlates of set size effects and VWM capacity limits in general largely focus on the maintenance period of VWM. However, we previously reported that neural resources allocated to individual items during VWM encoding correspond to successful VWM performance. Here we expand on those findings by investigating neural correlates of set size during VWM encoding. We hypothesized that neural signatures of encoding-related VWM capacity limitations should be differentiable as a function of set size. We tested our hypothesis using High Density Electroencephalography (HD-EEG) to analyze frequency components evoked by flickering target items in VWM displays of set size 2 or 4. We found that set size modulated the amplitude of the 1st and 2nd harmonic frequencies evoked during successful VWM encoding across frontal and occipital-parietal electrodes. Frontal sites exhibited the most robust effects for the 2nd harmonic (set size 2 > set size 4). Additionally, we found a set-size effect on the induced power of delta-band (1-4 Hz) activity (set size 2 > set size 4). These results are consistent with a capacity limited VWM resource at encoding that is distributed across to-be-remembered items in a VWM display. This resource may work in conjunction with a task-specific selection process that determines which items are to be encoded and which are to be ignored. These neural set size effects support the view that VWM capacity limitations begin with encoding related processes