Biology subjects

Gandolfo, M.

Publications and source records attributed to Gandolfo, M..

8 recordsLinked to original sources

bioRxiv2026

Behavioral and causal evidence for object-based scene recognition in visual cortex

Our visual environment can be parsed into objects and scenes, a distinction that is reflected in the organization of the human visual cortex. Previous research has shown that object and scene perception nevertheless closely interact, such that scenes influence object perception and objects influence scene perception. It remains unclear, however, whether and how objects that are not inherently diagnostic of their surroundings aid the recognition of poorly visible scenes (e.g., a person standing in a dark living room). Here, in three behavioral experiments, we show that participants made more accurate indoor/outdoor judgments when degraded scene photographs were presented together with an object than when the scene or the object was shown alone, even though the same object categories appeared in indoor and outdoor scenes. This object-driven benefit vanished once scene structure was removed through phase scrambling and was reduced when objects appeared in physically inconsistent locations within the scenes. These results suggest that objects in consistent locations (e.g., a person standing on a floor) disambiguate scene layout. Finally, in a pre-registered transcranial magnetic stimulation (TMS) study (N = 48), we provide causal evidence that the object-selective lateral occipital cortex (LOC) supports scene categorization when scene layout is disambiguated by within-scene objects. Stimulation of the LOC, particularly at 260-300 ms after stimulus onset, selectively disrupted object-based scene recognition. Together, these findings demonstrate that objects facilitate the read-out of the surrounding space in service of efficient scene recognition. Significance StatementUnderstanding how scene and object processing interact for efficient recognition is a key question in natural vision. Research has long emphasized how surrounding scenes help us identify objects, yet the reverse - how objects shape the perception of scenes - has received little attention. In the dark, does a glimpse of a floating boat tell us we are looking at a lake? In this study we demonstrate that a single object helps people recognize hardly visible scenes. This benefit required intact scene structure and depended on where the object appeared in the scene. In addition, object selective visual cortex was causally related to this benefit. Together, these findings show that objects visual appearance can be used to better understand our surroundings.

neuroscience↗

bioRxiv2025

Knowledge of effort modulates visual memory biases for body postures

The visual memory of others postures has been proposed to be shaped by knowledge and expectations. For example, the visual memory of a lifted arm was recently shown to be biased downward, suggesting that observers predicted the upcoming state of the arm based on knowledge of the effort required to hold the arm up against gravity. Alternatively, the downward bias for body postures could reflect an automatic normalization towards the most frequently observed arm position, with arms more often observed in a low position. Here, in three experiments, we provide evidence that the downward bias is flexibly modulated by knowledge of effort. In Experiment 1, we found a stronger downward bias for arm postures that are relatively effortful (lifting an arm above the shoulders while standing) compared to arm postures that are less effortful (lifting an arm above the chest while lying down). In Experiment 2, we found a stronger downward bias when the actor was standing (viewed from the side) than when the actor was lying down (viewed from above), even though the arm postures were visually identical. Moreover, dividing attention during the encoding stage reduced the bias, showing that attentive processing of the stimulus was required for the bias to emerge. Finally, in Experiment 3, we found that executing the observed posture during the visual memory task did not further increase the downward bias. Together, these findings demonstrate a high-level cognitive influence on the visual memory for body postures.

neuroscience↗

bioRxiv2024

A body detection inversion effect revealed by a large-scale inattentional blindness experiment

As a social species, humans preferentially attend to the faces and bodies of other people. Previous research revealed specialized cognitive mechanisms for processing human faces and bodies. For example, upright person silhouettes are more readily found than inverted silhouettes in visual search tasks. It is unclear, however, whether these findings reflect a top-down attentional bias to social stimuli or bottom-up sensitivity to visual cues signaling the presence of other people. Here, we tested whether the upright human form is preferentially detected in the absence of attention. To rule out influences of top-down attention and expectation, we conducted a large-scale single-trial inattentional blindness experiment on a diverse sample of naive participants (N=13.539). While participants were engaged in judging the length of a cross at fixation, we briefly presented an unexpected silhouette of a person or a plant next to the cross. Subsequently, we asked whether participants noticed anything other than the cross. Results showed that silhouettes of people were more often noticed than silhouettes of plants. Crucially, upright person silhouettes were also more often detected than inverted person silhouettes, despite these stimuli being identical in their low-level visual features. These results were replicated in a second experiment involving headless person silhouettes. Finally, capitalizing on the exceptionally large and diverse sample, further analyses revealed strong detection differences across age and gender. These results indicate that the visual system is tuned to the form of the upright human body, allowing for the quick detection of other people even in the absence of attention.

neuroscience↗

bioRxiv2024

Boosting forward connectivity between primary visual and body selective cortex reduces interference of task irrelevant dimensions on body judgements

We effortlessly categorise other people along socially relevant categories such as sex, age, and emotion. A core question in social vision relates to whether we perceive these categories independently or in relation to each other. Here, we investigated categorisation of sex and emotion from the body, finding that participants generally fail to fully ignore task-irrelevant variations of sex while judging body emotional expressions. In contrast, sex categorisation was unaffected by variations in emotional expression. This asymmetric interaction between sex and emotion may arise because of bottom-up visual processing, due to partially shared visual features used for both judgments, or because of top-down, categorical associations between sex and emotion categories. To disentangle these possibilities, we used cortico-cortical paired associative stimulation (ccPAS) to modulate the connectivity between primary visual cortex and the extrastriate body area. We posited that boosting forward connectivity between these regions would increase efficiency of feature-based processing, while boosting feedback connectivity would enhance the separability of semantic categories related to sex and emotion. We found that boosting forward connectivity eliminated the interference of sex on emotion judgments, while that interference remained unaffected with modulation of feedback connectivity. These findings suggest that interactions between sex and emotion in body perception emerge during the perceptual analysis of the stimuli, and add to our understanding of person perception and social categorization.

neuroscience↗

bioRxiv2023

Converging evidence that left extrastriate body area supports visual sensitivity to social interactions

Navigating our complex social world requires processing the interactions we observe. Recent psychophysical and neuroimaging studies provide parallel evidence that the human visual system may be attuned to efficiently perceive dyadic interactions. This work implies, but has not yet demonstrated, that activity in body-selective cortical regions causally supports efficient visual perception of interactions. We adopt a multi-method approach to close this important gap. First, using a large fMRI dataset (N=92), we found that the left-hemisphere Extrastriate Body Area (EBA) responds more to face-to-face than non-facing dyads. Second, we replicated a behavioural marker of visual sensitivity to interactions: categorisation of facing dyads is more impaired by inversion than non-facing dyads. Third, in a pre-registered experiment, we used fMRI-guided transcranial magnetic stimulation to show that online stimulation of the left EBA, but not a nearby control region, abolishes this selective inversion effect. Activity in left EBA, thus, causally supports the efficient perception of social interactions.

neuroscience↗

bioRxiv2022

Prior Knowledge Biases the Perception of Body Postures

Body postures provide information about others actions, intentions, and emotional states. Little is known about how postures are represented in the brains visual system. Considering our extensive visual and motor experience with body postures, we hypothesized that priors derived from this experience may systematically bias visual body posture representations. We examined two priors: gravity and biomechanical constraints. Gravity pushes lifted body parts downwards, while biomechanical constraints limit the range of possible postures (e.g., an arm raised far behind the head cannot go down further). Across three experiments (N=246) we probed participants visual memory of briefly presented postures using change discrimination and adjustment tasks. Results showed that lifted arms were misremembered as lower and as more similar to the nearest biomechanically plausible postures. Inverting the body stimuli eliminated both biases, ruling out visual confounds. These findings show that visual memory representations of body postures are modulated by a combination of category-general and category-specific priors.

neuroscience↗

bioRxiv2022

Design, implementation, and functional validation of a new generation of microneedle 3D high-density CMOS multi-electrode array for brain tissue and spheroids

In the last decades, planar multi-electrode arrays (MEAs) have been widely used to record activity from in vitro neuronal cell cultures and tissue slices. Though successful, this technique bears some limitations, particularly relevant when applied to three-dimensional (3D) tissue, such as brain slices, spheroids or organoids. For example, planar MEAs signals are informative on just one side of a 3D-organized structure. This limits the interpretation of the results in terms of network functions in a complex structured and hyperconnected brain tissue. Moreover, the side in contact with the MEAs often shows lower oxygenation rates and related vitality issues. To overcome these problems, we empowered a CMOS high-density multi-electrode array (HD-MEA) with thousands of microneedles (needles) of 65-90 m height, able to penetrate and record in-tissue signals, providing for the first time a 3D HD-MEA chip. We propose a CMOS-compatible fabrication process to produce arrays of needles of different widths mounted on large pedestals to create microchannels underneath the tissue. By using cerebellar and cortico-hippocampal slices as a model, we show that the needles efficiently penetrate the 3D tissue while the microchannels allow the flowing of maintenance solutions to increase tissue vitality in the recording sites. These improvements are reflected by the increase in electrodes sensing capabilities, the number of sampled neuronal units (compared to matched planar technology), and the efficiency of compound effects. Importantly, each electrode can also be used to stimulate the tissue with optimal efficiency due to the 3D structure. Furthermore, we demonstrate how the 3D HD-MEA can efficiently penetrate and get outstanding signals from in vitro 3D cellular models as brain spheroids. In conclusion, we describe a new recording device characterized by the highest spatio-temporal resolution reported for a 3D MEA and significant improvements in the quality of recordings, with a high signal-to-noise ratio and improved tissue vitality. The applications of this game-changing technique are countless, opening unprecedented possibilities in the neuroscience field and beyond.

neuroscience↗

bioRxiv2021

Boundary extension is constrained by naturalistic image properties

Boundary extension (BE) is a classic memory illusion in which observers remember more of a scene than was presented. According to predictive processing accounts, BE reflects the integration of visual input and expectations of what is beyond a scenes boundaries. According to normalization accounts, BE rather reflects one end of a normalization process towards a scenes typically-experienced viewing distance, such that close-up views give BE but distant views give boundary contraction. Here across four experiments, we show that BE strongly depends on depth-of-field (DOF), as determined by the aperture settings on a camera. Photographs with naturalistic DOF led to larger BE than photographs with unnaturalistic DOF, even when showing distant views. We propose that BE reflects a predictive mechanism with adaptive value that is strongest for naturalistic views of scenes. The current findings indicate that DOF is an important variable to consider in the study of scene perception and memory. Statement of RelevanceIn daily life, we experience a rich and continuous visual world in spite of the capacity limits of the visual system. We may compensate for such limits with our memory, by filling-in the visual input with anticipatory representations of upcoming views. The boundary extension illusion (BE) provides a tool to investigate this phenomenon. For example, not all images equally lead to BE. In this set of studies, we show that memory extrapolation beyond scene boundaries is strongest for images resembling human visual experience, showing depth-of-field in the range of human vision. Based on these findings, we propose that predicting upcoming views is conditional to a scene being perceived as naturalistic. More generally, the strong reliance of a cognitive effect, such as BE, on naturalistic image properties indicates that it is imperative to use image sets that are ecologically-representative when studying the cognitive, computational, and neural mechanisms of scene processing.

neuroscience↗