Biology subjects

Vishne, G.

Publications and source records attributed to Vishne, G..

5 recordsLinked to original sources

bioRxiv2025

Computational Mechanisms of Temporal Anticipation in Perception and Action

To interact effectively with our surroundings, we rely on strategies to reduce uncertainty. One important source of information is temporal regularities, which enable us to form predictions about when events will occur, and through this, prepare for them in advance. Such preparation was shown to facilitate motor planning, yet the impact of temporal anticipation on perceptual acuity is unknown, and the cognitive computations underlying this process remain debated. To answer these questions, we administered a new difficult change discrimination task with variable anticipatory periods (N=142). We show that both perceptual sensitivity and motor responses are influenced by temporal structure. Using computational modelling, we show that the cognitive operation underlying this behavior is based on a logarithmic transformation of the event hazard rate (HR) and reveal a crucial role of temporal-estimation noise in shaping this computation, both when temporal information is encoded, and when it is decoded. Together, our results highlight the fundamental contribution of anticipation in directing behavior and advance our understanding of temporal processing in the brain.

neuroscience↗

bioRxiv2024

Universal rhythmic architecture uncovers distinct modes of neural dynamics

Understanding the organizing principles of brain activity can advance neurotechnology and medical diagnosis. Traditionally, brain activity has been viewed as consisting electrical field potentials oscillating at different frequency bands. However, emerging evidence suggests these oscillations can manifest as transient bursts rather than sustained rhythms. Here, we examine the hypothesis that rhythmicity (sustained vs. bursty) adds an additional dimension to brain organization. We segment neurophysiological spectra from 859 participants encompassing a dozen datasets across multiple species, recording techniques, ages 18-88, sexes, brain regions, and cognitive states in health and disease using a novel rhythmicity measure. Combined with simulations and brain stimulation, our results reveal a universal spectral architecture with two categories: high-rhythmicity bands exhibiting sustained oscillations and novel low-rhythmicity bands dominated by brief bursts. This universal architecture reflects stable modes of brain operation: sustained bands suitable for maintaining ongoing activity, and transient bands which can signal responses to change. Rhythmicity thus provides a powerful, replicable, and accessible feature-set for neurotechnology and diagnosis.

neuroscience↗

bioRxiv2023

Decoding object categories from EEG during free viewing reveals early information evolution compared to passive viewing

Object processing is fundamental to visual perception, and understanding its neural substrates informs many cognitive and computational visual processing models. Thus far, most human studies have used passive viewing paradigms, during which self-driven behavior, such as eye movements, is constrained, and brain activity is evoked by abrupt stimuli onsets. This artificial dissociation of perception and action ignores the natural dynamics of visual processing. Thus, conclusions based on such passive viewing paradigms may not apply to active vision. Here, we study the human neural correlates of category representations during active visual processing by time-locking EEG to self-driven fixations during visual search for natural objects. We combine the deconvolution of overlapping responses to consecutive fixations with multivariate pattern analysis (MVPA) to decode object categories from responses to single fixation. We bridge the active and passive viewing literature by comparing the temporal dynamics of multivariate object representations during free visual search (active viewing) and rapid serial visual presentation (passive viewing), leveraging the high temporal resolution of EEG. We found that categorical information, at different levels of abstraction, can be decoded from single fixations during natural visual processing, and cross-condition decoding revealed that object representations are similar between active and passive viewing conditions. However, representational dynamics emerge significantly earlier in active compared to passive conditions, likely due to the availability of predictive information in free viewing. We highlight methodological considerations for combining MVPA with deconvolution methods. Significance StatementUnderstanding the neural correlates of visual perception is crucial for advancing cognitive and computational models of human vision. This study bridges the gap between passive- and active-vision literature while shedding light on the intricate relationship between perception and action in visual processing. Although eye movements are a fundamental behavior through which visual information is naturally sampled, most neuroimaging studies probe the brain by presenting stimuli abruptly at the center of the screen while participants refrain from moving their eyes. We investigated EEG correlates of visual processing during active visual search and demonstrated that object categories of naturally fixated objects can be decoded from the EEG. We provide novel findings regarding the dynamics of active, compared to passive, visual processing, while contributing to the advancement of EEG analysis methodology.

neuroscience↗

bioRxiv2022

Representation of sustained visual experience by time-invariant distributed neural patterns

Instances of sustained stationary sensory input are ubiquitous. However, previous work focused almost exclusively on the transient onset responses. This presents a critical challenge for neural theories of consciousness, which should account for the full temporal extent of experience. Here we use intracranial recordings from human patients viewing diverse images in multiple durations. In sensory regions, we reveal that despite dramatic changes in activation magnitude, the distributed representation of categories and exemplars remains sustained and stable. In contrast, in frontoparietal regions we find transient content representation at stimulus onset. Our results highlight the connection between the anatomical and temporal correlates of experience. To the extent perception is sustained, it may rely on sensory representations, and to the extent it is discrete, centered on perceptual updating, it may rely on frontoparietal representations.

neuroscience↗

bioRxiv2020

Impaired online error-correction disrupts synchronization to external events in autism

Autism is a developmental disorder characterized by impaired social skills and accompanied by motor and perceptual atypicalities. Its etiology is an open question, partly due to the diverse range of associated difficulties. Based on recent observations that individuals with autism are slow in updating perceptual priors, we now hypothesized that motor updating is also slow. Slow motor updating is expected to hamper the ability to synchronize to external events, since asynchronies are corrected sluggishly. Since sensorimotor synchronization is important for social bonding and cooperation, its impairment is expected to impair social skills. To test this hypothesis, we measured paced finger tapping to a metronome in neurotypical, ASD, and dyslexia groups. Dyslexia was assessed as a control group with a non-social neurodevelopmental atypicality. Only the ASD group showed reduced sensorimotor synchronization. Trial-by-trial computational modelling revealed that their ability to form controlled motor responses and to maintain reliable temporal representations was adequate. Only their rate of error-correction was slow and was correlated with the severity of their social difficulties. Taken together, these findings suggest that slow updating in autism contributes to both sloppy sensorimotor performance and difficulties in forming social bonds. SignificanceThe prevalence of autism diagnosis has increased immensely is the last decades. Yet its etiology remains a challenge, partly since the functional relations between characteristic social difficulties, perceptual and motor atypicalities are not understood. Using trial-by-trial computational modelling, we show that a single deficit underlies the poor synchronization of individuals with autism in both static and changing environments. Slow updating, leading to slow online error correction of motor plans, has an immense explanatory power explaining both difficulties in sensorimotor synchronization, and social impairments.

neuroscience↗