Visual motion processing and human tracking behavior

The accurate visual tracking of a moving object is a human fundamental skill that allows to reduce the relative slip and instability of the object's image on the retina, thus granting a stable, high-quality vision. In order to optimize tracking performance across time, a quick estimate of the object's global motion properties needs to be fed to the oculomotor system and dynamically updated. Concurrently, performance can be greatly improved in terms of latency and accuracy by taking into account predictive cues, especially under variable conditions of visibility and in presence of ambiguous retinal information. Here, we review several recent studies focusing on the integration of retinal and extra-retinal information for the control of human smooth pursuit.By dynamically probing the tracking performance with well established paradigms in the visual perception and oculomotor literature we provide the basis to test theoretical hypotheses within the framework of dynamic probabilistic inference. We will in particular present the applications of these results in light of state-of-the-art computer vision algorithms

The involvement of the fronto-parietal brain network in oculomotor sequence learning using fMRI.

The basis of motor learning involves decomposing complete actions into a series of predictive individual components that form the whole. The present fMRI study investigated the areas of the human brain important for oculomotor short-term learning, by using a novel sequence learning paradigm that is equivalent in visual and temporal properties for both saccades and pursuit, enabling more direct comparisons between the oculomotor subsystems. In contrast with previous studies that have implemented a series of discrete ramps to observe predictive behaviour as evidence for learning, we presented a continuous sequence of interlinked components that better represents sequences of actions. We implemented both a classic univariate fMRI analysis, followed by a further multivariate pattern analysis (MVPA) within a priori regions of interest, to investigate oculomotor sequence learning in the brain and to determine whether these mechanisms overlap in pursuit and saccades as part of a higher order learning network. This study has uniquely identified an equivalent frontal-parietal network (dorsolateral prefrontal cortex, frontal eye fields and posterior parietal cortex) in both saccades and pursuit sequence learning. In addition, this is the first study to investigate oculomotor sequence learning during fMRI brain imaging, and makes significant contributions to understanding the role of the dorsal networks in motor learning

Seuratun kappaleen poikkeuttaminen silmänräpäysten aikana: käyttäytymis- ja neuromagneettisia havaintoja

The visual world is perceived as continuous despite frequent interruptions of sensory data due to eyeblinks and rapid eye movements. To create the perception of constancy, the brain makes use of fill-in mechanisms. This study presents an experiment in which the location of an object during smooth pursuit tracking is altered during eyeblinks. The experiment investigates the effects of blink suppression and fill-in mechanisms to cloud the discrimination of these changes. We employed a motion-tracking task, which promotes the accurate evaluation of the object’s trajectory and thus can counteract the fill-in mechanisms. Six subjects took part in the experiment, during which they were asked to report any perceived anomalies in the trajectory. Eye movements were monitored with a video-based tracking and brain responses with simultaneous MEG recordings. Discrimination success was found to depend on the direction of the displacement, and was significantly modulated by prior knowledge of the triggered effect. Eye-movement data were congruent with previous findings and revealed a smooth transition from blink recovery to object locating. MEG recordings were analysed for condition-dependent evoked and induced responses; however, intersubject variability was too large for drawing clear conclusions regarding the brain basis of the fill-in mechanisms.Visuaalinen maailma koetaan jatkuvana, vaikka silmänräpäykset ja nopeat silmänliikkeet aiheuttavat keskeytyksiä sensoriseen tiedonkeruuseen. Luodakseen käsityksen pysyvyydestä, aivot käyttävät täyttömekanismeja. Tämä tutkimus esittelee kokeen, jossa kappaleen seurantaa hitailla seurantaliikkeillä häiritään muuttamalla sen sijaintia silmänräpäysten aikana. Tämä koe tutkii, kuinka silmänräpäysten aiheuttama suppressio ja täyttömekanismit sumentavat kykyä erotella näitä muutoksia. Käytimme liikeseurantatehtävää, joka vastaavasti edistää kappaleen liikeradan tarkkaa arviointia. Kuusi koehenkilöä osallistui kokeeseen, jonka aikana heitä pyydettiin ilmoittamaan kaikki havaitut poikkeamat kappaleen liikeradassa. Silmänliikkeitä tallennettiin videopohjaisella seurannalla, ja aivovasteita yhtäaikaisella MEG:llä. Erottelykyvyn todettiin riippuvan poikkeutuksen suunnasta, sekä merkittävästi a priori tiedosta poikkeutusten esiintymistavasta. Silmänliikedata oli yhtenevää aiempien tutkimusten kanssa, ja paljasti sujuvan siirtymisen silmänräpäyksistä palautumisesta kappaleen paikallistamiseen. MEG-tallenteet analysoitiin ehdollisten heräte- ja indusoitujen vasteiden löytämiseksi, mutta yksilölliset vaste-erot koehenkilöiden välillä olivat liian suuria selkeiden johtopäätösten tekemiseksi täyttömekanismien aivoperustasta

Visual attention deficits in schizophrenia can arise from inhibitory dysfunction in thalamus or cortex

Schizophrenia is associated with diverse cognitive deficits, including disorders of attention-related oculomotor behavior. At the structural level, schizophrenia is associated with abnormal inhibitory control in the circuit linking cortex and thalamus. We developed a spiking neural network model that demonstrates how dysfunctional inhibition can degrade attentive gaze control. Our model revealed that perturbations of two functionally distinct classes of cortical inhibitory neurons, or of the inhibitory thalamic reticular nucleus, disrupted processing vital for sustained attention to a stimulus, leading to distractibility. Because perturbation at each circuit node led to comparable but qualitatively distinct disruptions in attentive tracking or fixation, our findings support the search for new eye movement metrics that may index distinct underlying neural defects. Moreover, because the cortico-thalamic circuit is a common motif across sensory, association, and motor systems, the model and extensions can be broadly applied to study normal function and the neural bases of other cognitive deficits in schizophrenia.R01 MH057414 - NIMH NIH HHS; R01 MH101209 - NIMH NIH HHS; R01 NS024760 - NINDS NIH HHSPublished versio

Differential neural mechanisms for early and late prediction error detection

Emerging evidence indicates that prediction, instantiated at different perceptual levels, facilitate visual processing and enable prompt and appropriate reactions. Until now, the mechanisms underlying the effect of predictive coding at different stages of visual processing have still remained unclear. Here, we aimed to investigate early and late processing of spatial prediction violation by performing combined recordings of saccadic eye movements and fast event-related fMRI during a continuous visual detection task. Psychophysical reverse correlation analysis revealed that the degree of mismatch between current perceptual input and prior expectations is mainly processed at late rather than early stage, which is instead responsible for fast but general prediction error detection. Furthermore, our results suggest that conscious late detection of deviant stimuli is elicited by the assessment of prediction error’s extent more than by prediction error per se. Functional MRI and functional connectivity data analyses indicated that higher-level brain systems interactions modulate conscious detection of prediction error through top-down processes for the analysis of its representational content, and possibly regulate subsequent adaptation of predictivemodels. Overall, our experimental paradigm allowed to dissect explicit from implicit behavioral and neural responses to deviant stimuli in terms of their reliance on predictive models

Eye velocity gain fields for visuo- motor coordinate transformations

’Gain-field-like’ tuning behavior is characterized by a modulation of the neuronal response depending on a certain variable, without changing the actual receptive field characteristics in relation to another variable. Eye position gain fields were first observed in area 7a of the posterior parietal cortex (PPC), where visually responsive neurons are modulated by ocular position. Analysis of artificial neural networks has shown that this type of tuning function might comprise the neuronal substrate for coordinate transformations. In this work, neuronal activity in the dorsal medial superior temporal area (MSTd) has been analyzed with an focus on it’s involvement in oculomotor control. MSTd is part of the extrastriate visual cortex and located in the PPC. Lesion studies suggested a participation of this cortical area in the control of eye movements. Inactivation of MSTd severely impairs the optokinetic response (OKR), which is an reflex-like kind of eye movement that compensates for motion of the whole visual scene. Using a novel, information-theory based approach for neuronal data analysis, we were able to identify those visual and eye movement related signals which were most correlated to the mean rate of spiking activity in MSTd neurons during optokinetic stimulation. In a majority of neurons firing rate was non-linearly related to a combination of retinal image velocity and eye velocity. The observed neuronal latency relative to these signals is in line with a system-level model of OKR, where an efference copy of the motor command signal is used to generate an internal estimate of the head-centered stimulus velocity signal. Tuning functions were obtained by using a probabilistic approach. In most MSTd neurons these functions exhibited gain-field-like shapes, with eye velocity modulating the visual response in a multiplicative manner. Population analysis revealed a large diversity of tuning forms including asymmetric and non-separable functions. The distribution of gain fields was almost identical to the predictions from a neural network model trained to perform the summation of image and eye velocity. These findings therefore strongly support the hypothesis of MSTd’s participation in the OKR control system by implementing the transformation from retinal image velocity to an estimate of stimulus velocity. In this sense, eye velocity gain fields constitute an intermediate step in transforming the eye-centered to a head-centered visual motion signal.Another aspect that was addressed in this work was the comparison of the irregularity of MSTd spiking activity during optokinetic response with the behavior during pure visual stimulation. The goal of this study was an evaluation of potential neuronal mechanisms underlying the observed gain field behavior. We found that both inter- and intra-trial variability were decreased with increasing retinal image velocity, but increased with eye velocity. This observation argues against a symmetrical integration of driving and modulating inputs. Instead, we propose an architecture where multiplicative gain modulation is achieved by simultaneous increase of excitatory and inhibitory background synaptic input. A conductance-based single-compartment model neuron was able to reproduce realistic gain modulation and the observed stimulus-dependence of neural variability, at the same time. In summary, this work leads to improved knowledge about MSTd’s role in visuomotor transformation by analyzing various functional and mechanistic aspects of eye velocity gain fields on a systems-, network-, and neuronal level