Biology subjects

Boyaci, H.

Publications and source records attributed to Boyaci, H..

15 recordsLinked to original sources

bioRxiv2025

Perceiving Material Qualities from Moving Contours

While research on the perception of line drawings has long demonstrated the importance of contours in object recognition, recent work shows that contours can also convey material properties. For example, even simple 2D shapes with varying contours have been shown to evoke vivid impressions of different materials (Pinna & Deiana, 2015). However, such static representations capture only a single moment in time. When a material moves, its contours shift, evolve, or deform over time, creating contour motion. Does this contour motion convey diagnostic information about material properties, independent of surface appearance? Existing studies on the role of dynamic cues in material perception either use fully rendered 3D stimuli, where contour motion is confounded with rich surface information, or motion-only displays (dynamic dot stimuli or noise patches), which eliminate surface cues but also lack clearly defined contours. As a result, the relative contribution of contour motion to material perception remains unclear. To address this gap, we measured how human observers perceive materials from dynamic line drawings ("line"), compared to animations of fully textured stimuli that carry optical and motion information ("full"), as well as dynamic dot stimuli ("dot"). Stimuli were rendered versions (full, dot, line) of material animations from five material categories (jelly, liquid, smoke, fabric, and rigid-breakable). In one experiment, participants rated five material attributes (dense, flexible, wobbly, fluid, airy motion), and in a second experiment, participants were asked to choose one of the two materials that is more similar to a third material across all possible combinations. Results from both experiments consistently reveal that 1) Dynamic line drawings vividly convey mechanical material properties, and 2) the similarity in material judgments between line and full conditions was larger than that between dot and full conditions. We conclude that contour motion carries rich information about mechanical material qualities.

neuroscience↗

bioRxiv2024

hMT+ Activity Predicts the Effect Of Spatial Attention On Surround Suppression

Surround suppression refers to the decrease in behavioral sensitivity and neural response to a central stimulus due to the presence of surrounding stimuli. Several aspects of surround suppression in human motion perception have been studied in detail, including its atypicality in some clinical populations. However, how the extent of spatial attention affects the strength of surround suppression has not been systematically studied before. To address this question, we presented human participants with center and surround drifting gratings and sought to find whether attending only to the center ( narrow attention) versus both to the center and surround ( wide attention) modulates the suppression strength in motion processing. Using psychophysics and functional magnetic resonance imaging (fMRI), we measured motion direction discrimination thresholds and cortical activity in the primary visual cortex (V1) and middle temporal complex (hMT+). We found increased perceptual thresholds and, thus, stronger surround suppression under the wide attention condition. We also found that the pattern of hMT+ activity was consistent with the behavioral results. Furthermore, a mathematical model that combines spatial attention and divisive normalization was able to explain the pattern in the behavioral and fMRI results. These findings provide a deeper understanding of how attention affects center-surround interactions and suggest possible neural mechanisms with relevance to both basic and clinical vision science. Significance StatementOur sensitivity to the drift direction of a grating decreases when it is surrounded by an iso-oriented high-contrast surround. Here, we report the first systematic neuroimaging study on how the extent of spatial attention modulates the strength of this surround suppression. We found that the strength of surround suppression increases as the extent of spatial attention increases, and, pointing to its critical role, hMT+ activity predicts these results. Furthermore, a mathematical model combining spatial interactions and attention could explain the results. In addition to their relevance to basic vision science, these findings have clinical implications because they suggest that the atypical surround suppression observed in some populations could be related to abnormal spatial attention mechanisms.

neuroscience↗

bioRxiv2024

Predictive processing in biological motion perception: Evidence from human behavior

Biological motion perception plays a crucial role in understanding the actions of other animals, facilitating effective social interactions. While foundation of biological motion perception is rooted in bottom-up processes, as evidenced by point-light display studies, real-world complexities necessitate the involvement of top-down processes, such as attention and expectation. This study investigates the impact of expectations on biological motion perception using a cued individuation task with point-light display stimuli. We conducted three experiments, each providing advance information about distinct aspects of the subsequent biological motion stimuli - specifically information about action, emotion, and gender. Our results revealed a pattern in the action experiment, where participants demonstrated significantly slower response times for incongruent trials than congruent ones, but only under the 75% cue validity condition. This effect was notably absent in the emotion and gender experiments. Our exploration underscores the multi-faceted nature of biological motion perception, highlighting that while the brain adeptly harnesses prior cues to anticipate and interpret stimuli, the nature and reliability of these cues play a pivotal role on their effects. Specifically, action-related information stands out as an important modulator, possibly due to its evolutionary significance and unique neural processing pathway. These findings not only agree with the principles of predictive processing but also pave the way for future research, emphasizing the need to utilize naturalistic, complex stimuli together with neuroimaging methods to create more comprehensive models of biological motion perception.

neuroscience↗

bioRxiv2023

Neural correlates of spatiotemporal properties of lightness induction

The lightness of a surface depends not only on the amount of light reflected off it but also on the context it is embedded in. Despite a long history of research, neural correlates of context-dependent lightness perception remain a question of ongoing debate. The current study seeks to expand upon the existing literature by measuring fMRI responses to a dynamic version of a classical effect called simultaneous lightness induction (SLI), where a central disk appears lighter when embedded in a darker surround compared to when embedded in a lighter surround. During the fMRI experiment, we presented ten participants with a dynamic SLI stimulus by modulating the luminance of either the achromatic surround (surround-modulation condition) or the achromatic disk (disk-modulation condition) at four different frequencies ranging from 1 to 8 Hz. Behaviorally, when the surround luminance is modulated at low frequencies, participants perceive an illusory change in the lightness of the disk (lightness induction). In contrast, they perceive little or no induction at higher frequencies. Utilizing this temporal dependence and controlling for long-range responses to border contrast and luminance changes, we found that activity in the primary visual cortex (V1) correlates with lightness induction. However, such a correlation was not evident in extrastriate areas, V2, V3, and V4. These findings provide evidence for the involvement of V1 in the processing of context-dependent lightness.

neuroscience↗

bioRxiv2022

Unmet Expectations About Material Properties Delay Perceptual Decisions

Based on our expectations about material properties we can implicitly predict an objects future states, e.g. a wine glass falling down will break when it hits the ground. How these expectations affect relatively low level perceptual decisions, however, has not been systematically studied previously. To seek an answer to this question we conducted a behavioral experiment using animations of various familiar objects (e.g. key, wine glass etc.) freely falling and hitting the ground. During a training session participants first built expectations about the dynamic properties of those objects. Half of the participants (N=28) built expectations consistent with our daily lives (e.g. a key bounces rigidly), whereas the other half learned an anomalous behavior (e.g. a key wobbles). This was followed by experimental sessions, in which expectations were unmet in 20% of the trials. In both training and experimental sessions, participants task was to report whether the objects broke or not upon hitting the ground. Critically a specific object always remained intact or broke, only the manner with which it did so differed. For example, a key could wobble or remain rigid, but it never broke. We found that participants reaction times were longer when expectations were unmet even when those expectations were anomalous and learned during the training session. Furthermore, we found an interplay between long-term and newly learned expectations, which could be predicted by a Bayesian updating approach. Overall, our results show that expectations about material properties can have an impact on relatively low-level perceptual decision making processes.

neuroscience↗

bioRxiv2022

Tilt Aftereffect Spreads Across the Visual Field

The tilt aftereffect (TAE) is observed when adaptation to a tilted contour alters the perceived tilt of a subsequently presented contour. Thus far, the TAE has been treated as a local aftereffect observed only at the location of the adapter. Whether and how TAE spreads to other locations in the visual field has not been systematically studied. Here we sought an answer to this question by measuring TAE magnitudes at locations including but not limited to the adapter location. The adapter was a tilted grating presented at the same peripheral location throughout an experimental session. In a single trial, participants indicated the perceived tilt of a test grating presented after the adapter at one of fifteen locations in the same hemifield as the adapter. We found non-zero TAE magnitudes in all locations tested, showing that the effect spreads across the tested visual hemifield. Next, to establish a link between neuronal activity and the behavioral results, and to predict possible origins of the spread, we built a model based on known characteristics of neuronal responses in the visual cortex. Simulation results showed that the model can successfully capture the pattern of the behavioral results. Furthermore, the pattern of the optimized receptive field sizes suggests that mid-level visual areas, for example V4, could be critically involved in TAE and its spread across the visual field.

neuroscience↗

bioRxiv2022

Basis of narrow-spectrum activity of fidaxomicin on gut pathogen Clostridioides difficile

Fidaxomicin (Fdx) is widely used to treat Clostridioides difficile (Cdiff) infections (CDIs), but the molecular basis of its narrow-spectrum activity in the human gut microbiome remains enigmatic. CDIs are a leading cause of nosocomial deaths. Fdx, which inhibits RNA polymerase (RNAP), targets Cdiff with minimal effects on gut commensals, reducing CDI recurrence. Here, we present the cryo-electron microscopy structure of Cdiff RNAP in complex with Fdx, allowing us to identify a crucial Fdx-binding determinant of Cdiff RNAP that is absent in most gut microbiota like Proteobacteria and Bacteroidetes. By combining structural, biochemical, and bioinformatic analyses, we establish that a single RNAP residue is a sensitizing element for Fdx narrow-spectrum activity. Our results provide a blueprint for targeted drug design against an important human pathogen.

microbiology↗

bioRxiv2021

Increasing the Spatial Extent of Attention Strengthens Surround Suppression

Here we investigate how the extent of spatial attention affects center-surround interaction in visual motion processing. To do so, we measured motion direction discrimination thresholds in humans using drifting gratings and two attention conditions. Under the narrow attention condition, attention was limited to the central part of the visual stimulus, whereas under the wide attention condition, it was directed to both the center and surround of the stimulus. We found stronger surround suppression under the wide attention condition. The magnitude of the attention effect increased with the size of the surround when the stimulus had low contrast, but did not change when it had high contrast. Results also showed that attention had a weaker effect when the center and surround gratings drifted in opposite directions. Next, to establish a link between the behavioral results and the neuronal response characteristics, we performed computer simulations using the divisive normalization model. Our simulations showed that the model can successfully predict the observed behavioral results using parameters derived from the medial temporal (MT) area of the cortex. These findings reveal the critical role of spatial attention on surround suppression and establish a link between neuronal activity and behavior. Further, these results also suggest that the reduced surround suppression found in certain clinical disorders (e.g., schizophrenia and autism spectrum disorder) may be caused by abnormal attention mechanisms.

neuroscience↗

bioRxiv2021

A recurrent cortical model can parsimoniously explain the effect of expectations on sensory processes

The effects of prior knowledge, predictions, and expectations on sensory and decision-making processes have been extensively studied. Yet, the neural mechanisms underlying those effects are still unclear. Here, we propose a recurrent neuronal model and test its predictions on behavioral and neuroimaging data from the literature. The model implements predictive processing through recurrent interactions among feature-tuned neural populations that integrate feedback and feedforward signals within established cortical circuitry. Our results show that the model can successfully explain the behavioral effects of prediction found in a previous study in which houses and faces were used as stimuli. We then simulate fMRI data using the protocols of three different studies from the literature, and the optimized model parameters obtained from the model fit to the behavioral data. Although the studies used diverse visual stimuli, not limited to faces and houses, the model predicts their findings to a great extent, proving its generalizability. Overall, our findings demonstrate that the proposed model can provide a link between behavior and neural activity, offering a theoretical account of how prior knowledge, predictions, and expectations influence sensory processing.

neuroscience↗

bioRxiv2020

Size Aftereffect is non-local

It is well known that prolonged exposure to a certain size stimulus alters the perceived size of a subsequently presented stimulus at the same location. How the rest of the visual space is affected by this size adaptation, however, has not been systematically studied before. Here, to fill this gap in literature, we tested size adaptation at the adapter location as well as the rest of the visual space. We used peripherally presented solid discs (Experiment 1) and rings (Experiment 2) as adapter and target (test) stimuli. Observers adapted to a mid-sized stimulus and judged the size of the subsequently presented smaller or larger target stimuli. Results showed that the perceived sizes of target stimuli were repelled away from the adapter size, not only at the adapter location but also at distant locations. These findings demonstrate that size adaptation causes widespread distortion of the visual space and alters perceived size. We discuss possible computational models that may underpin the perceptual effect.

neuroscience↗

bioRxiv2020

Dynamic dot displays reveal material motion network in the human brain

There is growing research interest in the neural mechanisms underlying the recognition of material categories and properties. This research field, however, is relatively more recent and limited compared to investigations of the neural mechanisms underlying object and scene category recognition. Motion is particularly important for the perception of non-rigid materials, but the neural basis of non-rigid material motion remains unexplored. Using fMRI, we investigated which brain regions respond preferentially to material motion versus other types of motion. We introduce a new database of stimuli - dynamic dot materials - that are animations of moving dots that induce vivid percepts of various materials in motion, e.g. flapping cloth, liquid waves, wobbling jelly. Control stimuli were scrambled versions of these same animations and rigid three-dimensional rotating dots. Results showed that isolating material motion properties with dynamic dots (in contrast with other kinds of motion) activates a network of cortical regions in both ventral and dorsal visual pathways, including areas normally associated with the processing of surface properties and shape, and extending to somatosensory and premotor cortices. We suggest that such a widespread preference for material motion is due to strong associations between stimulus properties. For example viewing dots moving in a specific pattern not only elicits percepts of material motion; one perceives a flexible, non-rigid shape, identifies the object as a cloth flapping in the wind, infers the objects weight under gravity, and anticipates how it would feel to reach out and touch the material. These results are a first important step in mapping out the cortical architecture and dynamics in material-related motion processing.

neuroscience↗

bioRxiv2020

Assessing Topographic Structural Connectivity of the Human Basal Ganglia and Thalamus

The basal ganglia and thalamus play an important role in cognition, procedural learning, eye movements, control of voluntary motor movements, emotional control, habit development, and are structures that are severely impacted by neurological disorders such as Parkinsons disease, or Tourette syndrome. To understand the structural connectivity of cortical and subcortical circuits in the healthy human brain could thus be of pivotal importance for detecting changes in this circuitry and to start early intervention, to assess the progress of movement rehabilitation, or the effectiveness of therapeutic approaches in neuropsychiatry. While conventional clinical magnetic resonance imaging (MRI) is able to provide detailed information about connectivity at the macro level, the sensitivity and specificity of such structural imaging methods put limits on the amount of detail one can obtain when measuring in vivo connectivity of human basal ganglia and thalamus at routine clinical magnetic field strengths. In contrast, the multiband diffusion echo planar imaging method, which acquires multiple slices simultaneously, enables high resolution imaging of these abovementioned brain structures with only short acquisition times at 3-Tesla and higher magnetic field strengths. To unleash the greater potential of information embedded in data acquired with this technique, complementary data processing pipelines are required. Here, we use a protocol composed of multiband diffusion-, T1- and susceptibility weighted data acquisition sequences and introduce an associated pipeline based on combined manual and automated processing. The design of this data processing pipeline allows us to generate comprehensive in vivo participant-specific probabilistic patterns and visualizations of the structural connections that exist within basal ganglia and thalamic nuclei. Moreover, we are able to map specific parcellations of these nuclei into sub-territories based on their connectivity with primary motor-, and somatosensory cortex. This data processing strategy enables detailed subcortical structural connectivity mapping which could benefit early intervention and therapy methods for human movement rehabilitation and for treating neuropsychiatric disorders.

neuroscience↗

bioRxiv2019

Distinct patterns of surround modulation in V1 and hMT+

Modulation of a neurons responses by the stimuli presented outside of its classical receptive field is ubiquitous in the visual system. This \"surround modulation\" mechanism is believed to be critical for efficient processing and leads to many well-known perceptual effects. The details of surround modulation, how-ever, are still not fully understood. One of the open questions is related to the differences in surround modulation mechanisms in different cortical areas, and their interactions. Here we study patterns of surround modulation in primary visual cortex (V1) and middle temporal complex (hMT+) utilizing a well-studied effect in motion perception, where human observers ability to discriminate the drift direction of a grating improves as its size gets bigger if the grating has a low contrast, and deteriorates if it has a high contrast. We first replicated the findings in the literature with a behavioral experiment using small and large (1.06 and 8.05 degrees of visual angle) drifting gratings with either low (2%) or high (99%) contrast presented at the periphery. Next, using functional MRI, we found that in V1 with increasing size cortical responses increased at both contrast levels, but they increased more at high contrast. Whereas in hMT+ with increasing size cortical responses remained unchanged at high contrast, and increased at low contrast. These findings show that surround modulation in V1 and hMT+ are distinct. Furthermore these findings provide evidence that the size-contrast interaction in motion perception is likely to originate in hMT+.

neuroscience↗

bioRxiv2019

When expectations are not met: unraveling the computational mechanisms underlying the effect of expectation on perceptual thresholds

Expectations and prior knowledge strongly affect and even shape our visual perception. Specifically, valid expectations speed up perceptual decisions, and determine what we see in a noisy stimulus. Bayesian models have been remarkably successful to capture the behavioral effects of expectation. On the other hand several more mechanistic neural models have also been put forward, which will be referred as "predictive computation models" here. Both Bayesian and predictive computation models treat perception as a probabilistic inference process, and combine prior information and sensory input. Despite the well-established effects of expectation on recognition or decision-making, its effects on low-level visual processing, and the computational mechanisms underlying those effects remain elusive. Here we investigate how expectations affect early visual processing at the threshold level. Specifically, we measured temporal thresholds (shortest duration of presentation to achieve a certain success level) for detecting the spatial location of an intact image, which could be either a house or a face image. Task-irrelevant cues provided prior information, thus forming an expectation, about the category of the upcoming intact image. The validity of the cue was set to 100, 75 and 50% in different experimental sessions. In a separate session the cue was neutral and provided no information about the category of the upcoming intact image. Our behavioral results showed that valid expectations do not reduce temporal thresholds, rather violation of expectation increases the thresholds specifically when the expectation validity is high. Next, we implemented a recursive Bayesian model, in which the prior is first set using the validity of the specific experimental condition, but in subsequent iterations it is updated using the posterior of the previous iteration. Simulations using the model showed that the observed increase of the temporal thresholds in the unexpected trials is not due to a change in the internal parameters of the system (e.g. decision threshold or internal uncertainty). Rather, further processing is required for a successful detection when the expectation and actual input disagree. These results reveal some surprising behavioral effects of expectation at the threshold level, and show that a simple parsimonious computational model can successfully predict those effects.

neuroscience↗

bioRxiv2018

Fidaxomicin jams M. tuberculosis RNA polymerase motions needed for initiation via RbpA contacts

Fidaxomicin (Fdx) is an antimicrobial RNA polymerase (RNAP) inhibitor highly effective against Mycobacterium tuberculosis RNAP in vitro, but clinical use of Fdx is limited to treating Clostridium difficile intestinal infections due to poor absorption. To enable structure-guided optimization of Fdx to treat tuberculosis, we report the 3.4 [A] cryo-electron microscopy structure of a complete M. tuberculosis RNAP holoenzyme in complex with Fdx. We find that the actinobacteria general transcription factor RbpA contacts fidaxomycin and explains its strong effect on M. tuberculosis. We present additional structures that define conformational states of M. tuberculosis RNAP between the free apo-holenzyme and the promoter-engaged open complex ready for transcription. The results establish that Fdx acts like a doorstop to jam the enzyme in an open state, preventing the motions necessary to secure promoter DNA in the active site. Our results provide a structural platform to guide development of anti-tuberculosis antimicrobials based on Fdx.

biophysics↗