Jonathan Winawer

The ability of humans to discriminate and identify spatial patterns varies across the visual field and is generally worse in the periphery than in the fovea. This decline in performance is revealed in many kinds of tasks, from detection to recognition. A parsimonious hypothesis is that the representation of any visual feature is blurred (spatially averaged) by an amount that differs for each feature, but that in all cases increases with eccentricity. Here, we examine models for two such features: local luminance and spectral energy. Each model averages the corresponding feature in pooling windows whose diameters scale linearly with eccentricity. We performed perceptual experiments with synthetic stimuli to determine the largest window scaling for which human and model discrimination abilities match (the ‘critical’ scaling). We used much larger stimuli than those of previous studies, subtending 53.6 by 42.2° of visual angle. We found that the critical scaling for the luminance model was approximately one-fourth that of the energy model and, consistent with earlier studies, that the estimated critical scaling value was smaller when discriminating a synthesized stimulus from a natural image than when discriminating two synthesized stimuli. Moreover, we found that initializing the generation of the synthesized images with natural images reduced the critical scaling value when discriminating two synthesized stimuli, but not when discriminating a synthesized from a natural image stimulus. Together, the results show that critical scaling is strongly affected by the image statistic (pooled luminance vs. spectral energy), the comparison type (synthesized vs. synthesized or synthesized vs. natural), and the initialization image for synthesis (white noise vs. natural image). We offer a coherent explanation for these results in terms of alignments and misalignments of the models with human perceptual representations.

Sensory processing is fundamentally shaped by stimulation history. For example, in the visual cortex, neural responses are reduced for repeated or sustained stimuli (adaptation). These phenomena are well characterized and effectively modeled by divisive normalization. We asked whether these same computational principles govern somatosensory processing. We used fMRI (six participants, all female) and intracranial electroencephalography (iEEG, two participants, both male) to measure responses to time-varying vibrotactile stimuli in the human somatosensory cortex. Stimuli consisted of single and paired pulses with durations and interstimulus intervals ranging from 0.05 to 1.2 s. We extracted BOLD time courses to capture neural response amplitudes and high-frequency iEEG broadband envelopes to capture fast neural dynamics. In both experiments, we observed pronounced subadditive temporal summation. Responses to longer or repeated stimuli were consistently lower than predicted by linear integration. Computational modeling revealed that divisive normalization models outperformed linear models in cross-validated accuracy across both datasets. These results demonstrate that somatosensory temporal dynamics closely mirror those in the visual system. Our findings suggest that the nervous system employs similar computational principles across modalities to encode sensory information across time.

The ability of humans to discriminate and identify spatial patterns varies across the visual field, and is generally worse in the periphery than in the fovea. This decline in performance is revealed in many kinds of tasks, from detection to recognition. A parsimonious hypothesis is that the representation of any visual feature is blurred (spatially averaged) by an amount that differs for each feature, but that in all cases increases with eccentricity. Here, we examine models for two such features: local luminance and spectral energy. Each model averages the corresponding feature in pooling windows whose diameters scale linearly with eccentricity. We performed perceptual experiments with synthetic stimuli to determine the largest window scaling for which human and model discrimination abilities match (the “critical” scaling). We used much larger stimuli than those of previous studies, subtending 53.6 by 42.2 degrees of visual angle. We found that the critical scaling for the luminance model was approximately one-fourth that of the energy model and, consistent with earlier studies, that the estimated critical scaling value was smaller when discriminating a synthesized stimulus from a natural image than when discriminating two synthesized stimuli. Moreover, we found that initializing the generation of the synthesized images with natural images reduced the critical scaling value when discriminating two synthesized stimuli, but not when discriminating a synthesized from a natural image stimulus. Together, the results show that critical scaling is strongly affected by the image statistic (pooled luminance vs. spectral energy), the comparison type (synthesized vs. synthesized or synthesized vs. natural), and the initialization image for synthesis (white noise vs natural image). We offer a coherent explanation for these results in terms of alignments and misalignments of the models with human perceptual representations.

Episodic memory retrieval is thought to rely on the reactivation of prior perceptual representations in sensory cortex, a phenomenon known as cortical reinstatement. Support for this idea in early sensory areas comes from memory studies involving repeated exposure and explicit recall instructions. In everyday life, however, people rely on details from single events without repeated practice or instruction. We used fMRI to test whether memory responses emerge in early visual cortex after a single encoding event. Twenty adults viewed objects presented once in one of four parafoveal locations, then later completed object recognition (old/new) and location recall tasks in which objects were shown foveally. Both memory tasks evoked spatially tuned, albeit substantially lower amplitude, responses compared to encoding in V1 to V3. These responses were tuned to the encoded parafoveal location, even though the recognition task did not ask the participant to remember the encoded location. These responses were more robust and precise for successfully remembered items, linking neural tuning in early visual cortex to one-shot memory performance. Our findings demonstrate that early visual cortex supports the defining property of episodic memory, the ability to retrieve sensory details from a single event.

How does the visual system recognize objects in natural environments? Here, we investigate the neural computations underlying robust object recognition along the ventral stream. We adapted psychophysical critical-band masking to fMRI, measuring BOLD responses along the ventral stream to natural images perturbed by bandpass noise. We found that, along this stream, the overall BOLD response to noise alone is sensitive to an increasingly wide range of stimulus spatial frequency, from 2 octaves in V1 to 5 octaves in ventral temporal cortex (VTC). However, when we assess the effect of the same noise on the accuracy of decoding scene images from the BOLD response, we obtain a different result: Recognition bandwidth is conserved along the ventral stream at about 2 octaves, close to the 1.5-octave behavioral channel. Though the recognition band is conserved, its noise tolerance increases steadily along the ventral stream, approaching behavioral levels in VTC. These findings suggest that V1 sets the bandwidth of the object-recognition channel, while downstream areas progressively denoise the signal, establishing the channel’s noise tolerance. This biological architecture—early channel isolation followed by successive denoising—may explain why human vision remains more robust than current machine vision.

Online vision testing enables efficient data collection from diverse participants, but often requires accurate fixation. When needed, fixation accuracy is traditionally ensured by using a camera to track gaze. That works well in the laboratory, but tracking during online testing with a built-in webcam is not yet sufficiently precise. Kurzawski, Pombo, et al. (2023) introduced a fixation task that improves fixation through hand-eye coordination, requiring participants to track a moving crosshair with a mouse-controlled cursor. This dynamic fixation task greatly reduces peeking at peripheral targets relative to a stationary fixation task, but does not eliminate it. Here, we introduce a crowded dynamic fixation task that further enhances fixation by adding clutter around the fixation mark. We assessed fixation accuracy during peripheral threshold measurement. Relative to the root mean square gaze error during the stationary fixation task, the dynamic fixation error was 55%, whereas the crowded dynamic fixation error was only 40%. With a 1.5° tolerance, peeking occurred on 7% of trials with stationary fixation, 1.5% with dynamic fixation, and 0% with crowded dynamic fixation. This improvement eliminated implausibly low peripheral thresholds, likely by preventing peeking. We conclude that crowded dynamic fixation provides accurate gaze control for online testing.

Strokes and blunt trauma can cause large changes in perception. It is rare, however, to have a sudden but persistent change to perception in the absence of trauma. Here we report a case of a 12-year-old male who reported a sudden-onset change in vision without any trauma, with akinetopsia-like symptoms: an inability to see motion. In contrast to classical cases of akinetopsia, informal testing revealed normal motion perception for simple stimuli, but difficulty in recognition of moving objects in visual clutter. Psychophysical testing confirmed normal random dot motion sensitivity and a large deficit in object recognition in clutter in moving displays, and surprisingly, in static displays. Oculomotor behavior showed both slowed saccades and difficulty in smooth pursuit. Anatomical and functional MRI showed largely intact retinotopic maps and robust responses to visual motion, including in canonical cortical motion processing areas. However, MRI imaging revealed a right lingual gyrus gray-white contrast blurring with corresponding severe focal FDG hypometabolism on PET, consistent with focal cortical dysplasia (FCD). We speculate that the abnormality in ventral cortex affects recognition in clutter, which manifests as a subjective experience of akinetopsia-like symptoms, especially in complex dynamic scenes.

Attention enables us to efficiently and flexibly interact with the environment by prioritizing specific image locations and features in preparation for responding to stimuli. Using a concurrent psychophysics–fMRI experiment, we investigate how covert spatial attention modulates responses in human visual cortex before target onset and how it affects subsequent behavioral performance. Performance improves at cued locations and worsens at uncued locations compared to distributed attention, demonstrating a selective processing tradeoff. Pre-target BOLD responses in cortical visual field maps reveal two key changes: First, a stimulus-independent baseline shift, with increases near cued locations and decreases elsewhere, paralleling behavioral results. Second, a shift in population receptive field centers toward the attended location. Both effects increase in higher visual areas. Together, these findings reveal that spatial attention has large effects on visual cortex prior to target appearance, altering neural response properties across multiple visual field maps and enhancing performance through anticipatory mechanisms.

Neuronal oscillations at about 10 Hz, called alpha oscillations, are often thought to arise from synchronous activity across the occipital cortex and are usually largest when the cortex is inactive. However, recent studies measuring visual receptive fields have reported that local alpha power increases when cortex is excited by visual stimulation. This contrasts with the expectation that alpha oscillations are associated with cortical inactivity. Here, we used intracranial electrodes in human patients to measure alpha oscillations in response to visual stimuli whose location varied systematically across the visual field. We hypothesized that stimulus-driven local increases in alpha power result from a mixture of two effects: a reduction in alpha oscillatory power and a simultaneous increase in broadband power. To test this, we implemented a model to separate these components. The two components were then independently fit by population receptive field (pRF) models. We find that the alpha pRFs have similar center locations to pRFs estimated from broadband power but are several times larger and exhibit the opposite effect: alpha oscillatory power decreases in response to stimuli within the receptive field, reinforcing the link between alpha oscillations and cortical inactivity, whereas broadband power increases. The results demonstrate that alpha suppression in the human visual cortex can be precisely tuned, but that to measure these effects, it is essential to separate the oscillatory signal from broadband power changes. Finally, we show how the large size and the negative valence of alpha pRFs can explain key features of exogenous visual attention.

This study investigates the contribution of different vascular compartments on population receptive field (pRF) size estimates within the early visual cortex (V1, V2, and V3) using BOLD-fMRI. We employed T2*-weighted gradient-echo (GE) and T2-weighted spin-echo (SE) sequences at 7 Tesla (7T) and a multi-band GE sequence at 3T to explore how different vessel sensitivities across these sequences influence pRF modeling. Our results confirm the expected pRF size increase across eccentricity and visual areas but found no significant differences in pRF size estimates across MR sequences, voxel sizes, or field strengths. BOLD signal amplitudes were influenced by MR sequence, with largest signal changes observed for 7TGE, and amplitude increases were noted across cortical depth for GE sequences but not for SE sequences. Contrary to our hypotheses, pRF size estimates were not noticeably affected by the local vascularization, suggesting that pRFs primarily reflect neuronal activity rather than vascular compartment characteristics. Our study highlights the robust nature of pRF size estimates across various fMRI conditions and points toward the decoupling of pRF properties from vascular factors.