Alessandro Benedetto

Numerosity perception enables us to quickly estimate the number of objects in a visual scene, a fundamental skill supporting efficient interaction with the environment. In this study, we tracked how the human brain transforms physical inputs into numerical percepts. Using EEG we measured the neural dynamics to assess whether numerosity is perceived directly or inferred from correlated non-numerical features, and how these signals are integrated with contextual cues that bias perception. We leveraged on a visual illusion in which dot arrays appear less numerous when arranged symmetrically rather than randomly. Participants viewed dot arrays of varying physical or perceived numerosity, illusorily altered by the dots’ spatial arrangement. Both univariate and multivariate analyses revealed that physical numerosity was decodable from occipitoparietal electrodes as early as ∼50 ms after stimulus onset, independently of low-level features such as dot size or convex hull. Spatial arrangement was represented later, from ∼150 ms, and perceived numerosity, biased by symmetry-induced grouping, emerged at a similar latency. These results indicate that early neural signals encode physical numerosity directly, whereas the symmetry-induced underestimation arises from later grouping processes that integrate spatial information to shape perceived numerosity.

Despite the vivid experience of homogeneous vision, our visual system is inherently endowed with highly inhomogeneous structures. Although the temporal characteristics of visual responses vary with eccentricity, the connection between this variation, the speed of visual processing, and its underlying neurophysiological mechanisms remains a topic of debate. Here, we performed simultaneous recordings of high-precision gaze positions and EEG activity to investigate how foveal and perifoveal stimulations impact reaction times (RTs) and visual evoked potentials (VEPs). Volunteers discriminated the position and orientation of a U-shaped figure with the aperture facing either upward or downward. Stimuli were presented briefly (50 ms) either in the foveola (0.33°) or perifovea (6.5°), to the right or left of the fixation point. Stimulus size in the perifovea condition was adjusted according to the cortical magnification factor (stimulus size: 0.2° and 0.75° for the foveola and perifovea conditions, respectively). When stimuli were equated for sensitivity and cortical area of stimulation, we observed faster RTs in the perifovea condition (16.8 ± 4 ms) compared to the foveola. The analysis of the VEP revealed a similar effect for the N1 response (11.0 ± 4 ms), a parieto-occipital component associated with discriminative processing and influenced by spatial attention. Overall, our findings suggest that visual discrimination speeds vary across eccentricities, with faster processing and shorter latency of early visual responses in the perifovea compared to the foveola.

The integration of numerical information with motor processes has emerged as a fascinating area of investigation in both animal and human cognition. The interest in a sensorimotor number system has recently generated neurophysiological and psychophysical evidence which combine to highlight the importance of motor functions in the encoding of numerical information. Nevertheless, several key questions remain, such as the influence of non-numerical motor parameters over numerical perception. Here we tested the role of physical effort, a parameter positively correlated with the number of actions, in modulating the link between hand-actions and visual numerosity perception. Effort was manipulated during sensorimotor adaptation as well as during a new actions-estimation paradigm. The results of Experiment 1 shows that physical effort in the absence of actions (passive effort) is not sufficient to activate the sensorimotor number system, indicating that self-produced actions are instead necessary. Further experiments demonstrated that effort is marginally integrated during motor adaptation (Experiment 2) but discarded when estimating the number of self-produced hand actions (Experiment 3). Overall, the results indicate that the sensorimotor number system is largely fed by the number of discrete actions rather than the amount of effort but also indicates that effort (under specific circumstances) might be integrated. These findings provide novel insights into the sensorimotor numerical integration, paving the way for future investigations, such as on its functional role.

Eye movements are neither necessary nor sufficient to account for the neural effects associated with covert attention.

Humans possess the ability to extract highly organized perceptual structures from sequences of temporal stimuli. For instance, we can organize specific rhythmical patterns into hierarchical, or metrical, systems. Despite the evidence of a fundamental influence of the motor system in achieving this skill, few studies have attempted to investigate the organization of our motor representation of rhythm. To this aim, we studied—in musicians and non-musicians—the ability to perceive and reproduce different rhythms. In a first experiment participants performed a temporal order-judgment task, for rhythmical sequences presented via auditory or tactile modality. In a second experiment, they were asked to reproduce the same rhythmic sequences, while their tapping force and timing were recorded. We demonstrate that tapping force encodes the metrical aspect of the rhythm, and the strength of the coding correlates with the individual’s perceptual accuracy. We suggest that the similarity between perception and tapping-force organization indicates a common representation of rhythm, shared between the perceptual and motor systems.

Pupil dynamics alterations have been found in patients affected by a variety of neuropsychiatric conditions, including autism. Studies in mouse models have used pupillometry for phenotypic assessment and as a proxy for arousal. Both in mice and humans, pupillometry is non-invasive and allows for longitudinal experiments supporting temporal specificity, however its measure requires dedicated setups. Here, we introduce a Convolutional Neural Network that performs on-line pupillometry in both mice and humans in a web app format. This solution dramatically simplifies the usage of the tool for non-specialist and non-technical operators. Because a modern web browser is the only software requirement, this choice is of great interest given its easy deployment and set-up time reduction. The tested model performances indicate that the tool is sensitive enough to detect both spontaneous and evoked pupillary changes, and its output is comparable with state-of-the-art commercial devices.

Summary: The mechanisms coordinating action and perception over time are poorly understood. The sensory cortex needs to prepare for upcoming changes contingent on action, and this requires temporally precise communication that takes into account the variable delays between sensory and motor processing. Several theorists ^1,2 have proposed synchronization of the endogenous oscillatory activity observed in most regions of the brain ³ as the basis for an efficient and flexible communication protocol between distal brain areas ^2,4 , a concept known as “communication through coherence”. Synchronization of endogenous oscillations ^5,6 occurs after a salient sensory stimulus, such as a flash or a sound ^7–11 , and after a voluntary action ^12–18 , and this impacts directly on perception, causing performance to oscillate rhythmically over time. Here we introduce a novel fMRI paradigm to probe the neural sources of oscillations, based on the concept of perturbative signals, which overcomes the low temporal resolution of BOLD signals. The assumption is that a synchronized endogenous rhythm will modulate cortical excitability rhythmically, which should be reflected in the BOLD responses to brief stimuli presented at different phases of the oscillation cycle. We record rhythmic oscillations of V1 BOLD synchronized by a simple voluntary action, in phase with behaviourally measured oscillations in visual sensitivity in the theta range. The functional connectivity between V1 and M1 also oscillates at the same rhythm. By demonstrating oscillatory temporal coupling between primary motor and sensory cortices, our results strongly implicate communication through coherence to achieve precise coordination and to encode sensory-motor timing.