Biology subjects

Zoccolan, D.

Publications and source records attributed to Zoccolan, D..

13 recordsLinked to original sources

bioRxiv2025

Tactile responses in the mouse perirhinal cortex show invariance to physical features of the stimulus

Sensory processing in the cortex follows a hierarchical structure, transforming fine-grained stimulus features into abstract, invariant representations. These transformations have typically been characterised in visual pathways ranging from primary visual cortex to inferotemporal cortex. Less is known about how stimulus representations are formatted in other modalities and downstream regions such as the perirhinal cortex (PER), which receives processed sensory input from all modalities and is involved in object recognition. To address this, we investigated neural activity along the somatosensory hierarchy in awake, head-fixed mice receiving tactile whisker stimulation on either side of the face. PCA and stimulus-baseline decoding analyses revealed that PER activity was similar across stimulated sides, while this was not the case in primary somatosensory cortex (wS1). We also performed decoding analyses for the side of stimulation and the stimulus movement direction and found that wS1 and secondary somatosensory cortex could reliably decode both features. In contrast, PER was shown to be invariant to both features. We also clustered neurons based on their response dynamics, which indicated that the majority of PER neurons did not encode the basic stimulus features. These findings demonstrate that PER is a critical node in the somatosensory processing hierarchy, encoding tactile information in an invariant and abstract format. Together, these insights contribute to a more refined understanding of how perceptual processing in PER contributes to the various cognitive processes it is utilised for. Significance StatementSensory information is processed in stages that transform detailed signals into complex, stable representations. The perirhinal cortex (PER) is at the apex of these stages and is involved in recognizing objects, a cognitive process that requires both perceptual and memory-based processing. While PERs role in the latter is established, evidence for the former is conflicting. To investigate this, we recorded PER activity in mice passively experiencing simple tactile stimulation with two pairs of feature combinations. Along the cortical somatosensory hierarchy invariance of stimulus representation emerged in PER, while individual features were represented in earlier cortices with high fidelity. This suggests that PER contributes to the formation of invariant representations of sensory stimuli that is a foundation for object recognition.

neuroscience↗

bioRxiv2025

Predisposed and learned preferences for multipoint visual statistics in visually naïve newly hatched chicks

Significance statementWe show that visually naive chicks spontaneously prefer specific multipoint correlation patterns, mirroring preferences seen in humans and rats, and reflecting the most informative structures in natural scenes. This provides evidence that efficient coding mechanisms may be innately driven by evolutionary predispositions. Notably, early visual experience through imprinting can alter these preferences, highlighting a role for learning in shaping visual processing. Recent studies have revealed that human and non-human animals (rats) can detect luminance distribution and correlations between pixels in an image (ranging from 2-point to 4-point). This sensitivity is believed to stem from optimization processes in the visual system that operate through efficient coding mechanisms to extract the most informative image statistics from the environment. However, it is yet to be determined whether this optimization is evolutionarily given by inborn mechanisms or shaped by visual experience. Here we report that newly-hatched visually naive domestic chicks spontaneously prefer to approach luminance, 2-point and 4-point correlation patterns (respectively, horizontal lines and rectangular patterns), while showing no preference for 3-point correlation over white noise controls. This parallels the ranking observed in adult humans and rats, thus suggesting that evolutionarily given biological predispositions largely drive efficient coding of natural images. We also found that learning by exposure to visual stimuli, as occurs naturally during visual imprinting, induced a preference for white noise over point correlation patterns in chicks exposed to 3- and 4-point patterns. We hypothesize that this behavior could reflect chicks preference for stimuli of lower statistical complexity.

animal behavior and cognition↗

bioRxiv2025

Seeing what you hear: sound intensity alters rat visual perception in a temporal frequency classification task

The brain combines information from multiple sensory modalities to build a consistent view of the world. The principles by which multimodal stimuli are integrated in cortical hierarchies are well studied, but it is less clear whether and how unimodal inputs systematically shape the processing of signals carried by a different modality. Here we use a visual classification task in rats to investigate how task-irrelevant sounds modify the processing of visual stimuli. Our data shows that the intensity of a sound, but not its temporal modulation frequency, enacts a powerful, effective compression of the visual perceptual space. This result underscores the importance of cross-modal influences in perceptual pathways and suggests an important role for inhibition as the mediator of auditory-visual interactions at the neural representation level.

animal behavior and cognition↗

bioRxiv2024

Unraveling the complexity of rat object vision requires a full convolutional network - and beyond

Despite their prominence as model systems to dissect visual cortical circuitry, it remains unclear whether rodents are capable of truly advanced processing of visual information. Here, we considered several psychophysical studies of rat object vision, and we used a deep convolutional neural network (CNN) to measure the computational complexity required to account for the patterns of rat performances reported in these studies, as well as for the animals perceptual strategies. We found that at least half of the CNN depth was required to match the modulation of rat classification accuracy in tasks where objects underwent variations of size, position and orientation. However, the full network was needed to equal the tolerance of rat perception to more severe image manipulations, such as partial occlusion and reduction of objects to their outlines. Finally, rats displayed a perceptual strategy that was way more invariant than that of the CNN, as they more consistently relied on the same set of diagnostic features across object transformations. Overall, these results reveal an unexpected level of sophistication of rat object vision, while reinforcing the intuition that, despite their proficiency in solving challenging image classification tasks, CNNs learn solutions that only marginally match those of biological visual systems.

neuroscience↗

bioRxiv2023

Truly dorsal: nonlinear integration of motion signals is required to account for the responses of pattern cells in rat visual cortex

The defining feature of advanced motion processing in the primate dorsal stream is the existence of pattern cells - specialized cortical neurons that integrate local motion signals into pattern-invariant representations of global direction. Pattern cells have also been reported in rodent visual cortex, but it is unknown whether the tuning of these neurons results from truly integrative, nonlinear mechanisms or trivially arises from linear receptive fields (RFs) with a peculiar geometry. Here we show that pattern cells in rat visual cortical areas V1 and LM process motion direction in a way that cannot be explained by the linear spatiotemporal structure of their RFs. Instead, their tuning properties are consistent with those of units in a state-of-the-art neural network model of the dorsal stream. This suggests that similar cortical processes underly motion representation in primates and rodents. The latter could thus serve as powerful model systems to unravel the underlying circuit-level mechanisms.

neuroscience↗

bioRxiv2021

Rat sensitivity to multipoint statistics is predicted by efficient coding of natural scenes

Efficient processing of sensory data requires adapting the neuronal encoding strategy to the statistics of natural stimuli. Previously, in Hermundstad et al. 2014, we showed that local multipoint correlation patterns that are most variable in natural images are also the most perceptually salient for human observers, in a way that is compatible with the efficient coding principle. Understanding the neuronal mechanisms underlying such adaptation to image statistics will require performing invasive experiments that are impossible in humans. Therefore, it is important to understand whether a similar phenomenon can be detected in animal species that allow for powerful experimental manipulations, such as rodents. Here we selected four image statistics (from single- to four-point correlations) and trained four groups of rats to discriminate between white noise patterns and binary textures containing variable intensity levels of one of such statistics. We interpreted the resulting psychometric data with an ideal observer model, finding a sharp decrease in sensitivity from 2- to 4-point correlations and a further decrease from 4- to 3-point. This ranking fully reproduces the trend we previously observed in humans, thus extending a direct demonstration of efficient coding to a species where neuronal and developmental processes can be interrogated and causally manipulated.

neuroscience↗

bioRxiv2021

Rats spontaneously perceive global motion direction of drifting plaids

Computing global motion direction of extended visual objects is a hallmark of primate high-level vision. Although neurons selective for global motion have also been found in mouse visual cortex, it remains unknown whether rodents can combine multiple motion signals into global, integrated percepts. To address this question, we trained two groups of rats to discriminate either gratings (G group) or plaids (i.e., superpositions of gratings with different orientations; P group) drifting horizontally along opposite directions. After the animals learned the task, we applied a visual priming paradigm, where presentation of the target stimulus was preceded by the brief presentation of either a grating or a plaid. The extent to which rat responses to the targets were biased by such prime stimuli provided a measure of the spontaneous, perceived similarity between primes and targets. We found that gratings and plaids, when uses as primes, were equally effective at biasing the perception of plaid direction for the rats of the P group. Conversely, for G group, only the gratings acted as effective prime stimuli, while the plaids failed to alter the perception of grating direction. To interpret these observations, we simulated a decision neuron reading out the representations of gratings and plaids, as conveyed by populations of either component or pattern cells (i.e., local or global motion detectors). We concluded that the findings for the P group are highly consistent with the existence of a population of pattern cells, playing a functional role similar to that demonstrated in primates. We also explored different scenarios that could explain the failure of the plaid stimuli to elicit a sizable priming magnitude for the G group. These simulations yielded testable predictions about the properties of motion representations in rodent visual cortex at the single-cell and circuitry level, thus paving the way to future neurophysiology experiments.

neuroscience↗

bioRxiv2020

A general-purpose mechanism of visual feature association at the core of word learning

Writing systems are a recent cultural invention, which makes it unlikely that specific cognitive mechanisms have developed through selective pressure for reading itself. Instead, reading might capitalize on evolutionary older mechanisms that originally supported other tasks. Accordingly, animals such as baboons can be trained to perform visual word recognition. This suggests that the visual mechanisms supporting reading might be phylogenetically old and domain-general. Here we propose that if the human reading system relies on domain-general visual mechanisms, effects that are typically found within the domain of reading should also be observable with non-orthographic visual stimuli. To test this hypothesis, we systematically tested different types of visual material with the same experimental design. Subjects were passively familiarized with a set of composite visual items, and then tested in an oddball paradigm for their ability to detect novel stimuli. Some of these novel stimuli shared their statistical structure with the familiar items, and were found to be hard to detect in two experiments using strings of letter-like symbols; this replicates the well-known, and supposedly reading-specific, bigram effect. Crucially, in two further experiments we show that the same effect emerges with made-up, 3D objects and sinusoidal gratings. The effect size was equivalent across experiments, despite the use of radically different stimuli. These data suggest that a fundamental mechanism behind visual word learning also supports the learning of other visual stimuli, implying that such mechanism is general-purpose. This mechanism would enable the statistical learning of regularities in the visual environment.

neuroscience↗

bioRxiv2019

Intrinsic dynamics enhance temporal stability of stimulus representation along a visual cortical hierarchy

Along the ventral stream, cortical representations of brief, static stimuli become gradually more invariant to identity-preserving transformations. In the presence of long, temporally structured dynamic stimuli, higher invariance should imply temporally persistent representations at the top of this functional hierarchy. However, such stimuli could engage adaptive and predictive processes, whose impact on neural coding dynamics is unknown. By probing the rat analogue of the ventral stream with movies, we uncovered a hierarchy of temporal scales, with deeper areas encoding visual information more persistently. Furthermore, the impact of intrinsic dynamics on the stability of stimulus representations gradually grew along the hierarchy. Analysis of a large dataset of recordings from the mouse visual hierarchy yielded similar trends, revealing also their dependence on the behavioral state of the animal. Overall, these findings show that visual representations become progressively more stable along rodent visual processing hierarchies, with an important contribution provided by intrinsic processing.

neuroscience↗

bioRxiv2019

Causal adaptation to visual input dynamics governs the development of complex cells in V1

Visual perception relies on cortical representations of visual objects that remain relatively stable with respect to the variation in object appearance typically encountered during natural vision (e.g., because of position changes). Such stability, known as transformation tolerance, is built incrementally along the ventral stream (the cortical hierarchy devoted to shape processing), but early evidence of position tolerance is already found in primary visual cortex (V1) for complex cells1. To date, it remains unknown what mechanisms drive the development of this class of neurons, as well as the emergence of tolerance across the ventral stream. Leading theories suggest that tolerance is learned, in an unsupervised manner, either from the temporal continuity of natural visual experience2-10 or from the spatial statistics of natural scenes11,12. However, neither learning principle has been empirically proven to be at work in the postnatal developing cortex. Here we show that passive exposure to temporally continuous visual inputs during early postnatal life is essential for normal development of complex cells in rat V1. This was causally demonstrated by rearing newborn rats with frame-scrambled versions of natural movies, resulting in temporally unstructured visual input, but with unaltered, natural spatial statistics. This led to a strong reduction of the fraction of complex cells, which also displayed an abnormally fast response dynamics and a reduced ability to support stable decoding of stimulus orientation over time. Conversely, our manipulation did not prevent the development of simple cells, which showed orientation tuning and multi-lobed, Gabor-like receptive fields as sharp as those found in rats reared with temporally continuous natural movies. Overall, these findings causally implicate unsupervised temporal learning in the postnatal development of transformation tolerance but not of shape tuning, in agreement with theories that place the latter under the control of unsupervised adaptation to spatial, rather than temporal, image statistics13-16.

neuroscience↗

bioRxiv2019

A template-matching algorithm for laminar identification of cortical recording sites from evoked response potentials

In recent years, the advent of the so-called silicon probes has made it possible to homogeneously sample spikes and local field potentials (LFPs) from a regular grid of cortical recording sites. In principle, this allows inferring the laminar location of the sites based on the spatiotemporal pattern of LFPs recorded along the probe, as in the well-known current source-density (CSD) analysis. This approach, however, has several limitations, since it relies on visual identification of landmark features (i.e., current sinks and sources) by human operators - features that can be absent from the CSD pattern if the probe does not span the whole cortical thickness, thus making manual labelling harder. Furthermore, as any manual annotation procedure, the typical CSD-based workflow for laminar identification of recording sites is affected by subjective judgment undermining the consistency and reproducibility of results. To overcome these limitations, we developed an alternative approach, based on finding the optimal match between the LFPs recorded along a probe in a given experiment and a template LFP profile that was computed using 18 recording sessions, in which the depth of the recording sites had been recovered through histology. We show that this method can achieve an accuracy of 79 {micro}m in recovering the cortical depth of recording sites and a 76% accuracy in inferring their laminar location. As such, our approach provides an alternative to CSD that, being fully automated, is less prone to the idiosyncrasies of subjective judgment and works reliably also for recordings spanning a limited cortical stretch. New and noteworthyKnowing the depth and laminar location of the microelectrodes used to record neuronal activity from the cerebral cortex is crucial to properly interpret the recorded patterns of neuronal responses. Here we present an innovative approach that allows inferring such properties with high accuracy and in an automated way (i.e., without the need of visual inspection and manual annotation) from the evoked response potentials (ERPs) elicited by sensory (e.g., visual) stimuli.

neuroscience↗

bioRxiv2019

A passive, camera-based head-tracking system for real-time, 3D estimate of head position and orientation in rodents

Tracking heads position and orientation of small mammals is crucial in many behavioral neurophysiology studies. Yet, full reconstruction of the heads pose in 3D is a challenging problem that typically requires implanting custom headsets made of multiple LEDs or inertial units. These assemblies need to be powered in order to operate, thus preventing wireless experiments, and, while suitable to study navigation in large arenas, their application is unpractical in the narrow operant boxes employed in perceptual studies. Here we propose an alternative approach, based on passively imaging a 3D-printed structure, painted with a pattern of black dots over a white background. We show that this method is highly precise and accurate and we demonstrate that, given its minimal weight and encumbrance, it can be used to study how rodents sample sensory stimuli during a perceptual discrimination task and how hippocampal place cells represent head position over extremely small spatial scales.

neuroscience↗

bioRxiv2018

Evidence of ventral stream computations in rat lateral extrastriate cortex

In rodents, the progression of extrastriate areas located laterally to primary visual cortex (V1) has been assigned to a putative object-processing pathway (homologous to the primate ventral stream), based on anatomical considerations. Recently, we found functional support for such attribution (Tafazoli et al., 2017), by showing that this cortical progression is specialized for coding object identity despite view changes - the hallmark property of a ventral-like pathway. Here, we sought to clarify what computations are at the base of such specialization. To this aim, we performed multi-electrode recordings from V1 and laterolateral area LL (at the apex of the putative ventral-like hierarchy) of male adult rats, during the presentation of drifting gratings and noise movies. We found that the extent to which neuronal responses were entrained to the phase of the gratings sharply dropped from V1 to LL, along with the quality of the receptive fields inferred through reverse correlation. Concomitantly, the tendency of neurons to respond to different oriented gratings increased, while the sharpness of orientation tuning declined. Critically, these trends are consistent with the nonlinear summation of visual inputs that is expected to take place along the ventral stream, according to the predictions of hierarchical models of ventral computations and a meta-analysis of the monkey literature. This suggests an intriguing homology between the mechanisms responsible for building up shape selectivity and transformation tolerance in the visual cortex of primates and rodents, reasserting the potential of the latter as models to investigate ventral stream functions at the circuitry level.\n\nSignificance StatementDespite the growing popularity of rodents as models of visual functions, it remains unclear whether their visual cortex contains specialized modules for processing shape information. To addresses this question, we compared how neuronal tuning evolves from rat primary visual cortex (V1) to a downstream visual cortical region (area LL) that previous work has implicated in shape processing. In our experiments, LL neurons displayed a stronger tendency to respond to drifting gratings with different orientations, while maintaining a sustained response across the whole duration of the drift cycle. These trends match the increased complexity of pattern selectivity and the augmented tolerance to stimulus translation found in monkey visual temporal cortex, thus revealing a homology between shape processing in rodents and primates.

neuroscience↗