The spatiotemporal neural dynamics underlying perceived similarity for real-world objects.

The degree to which we perceive real-world objects as similar or dissimilar structures our perception and guides categorization behavior. Here, we investigated the neural representations enabling perceived similarity using behavioral judgments, fMRI and MEG. As different object dimensions co-occur and partly correlate, to understand the relationship between perceived similarity and brain activity it is necessary to assess the unique role of multiple object dimensions. We thus behaviorally assessed perceived object similarity in relation to shape, function, color and background. We then used representational similarity analyses to relate these behavioral judgments to brain activity. We observed a link between each object dimension and representations in visual cortex. These representations emerged rapidly within 200 ms of stimulus onset. Assessing the unique role of each object dimension revealed partly overlapping and distributed representations: while color-related representations distinctly preceded shape-related representations both in the processing hierarchy of the ventral visual pathway and in time, several dimensions were linked to high-level ventral visual cortex. Further analysis singled out the shape dimension as neither fully accounted for by supra-category membership, nor a deep neural network trained on object categorization. Together our results comprehensively characterize the relationship between perceived similarity of key object dimensions and neural activity

Change blindness: eradication of gestalt strategies

Arrays of eight, texture-defined rectangles were used as stimuli in a one-shot change blindness (CB) task where there was a 50% chance that one rectangle would change orientation between two successive presentations separated by an interval. CB was eliminated by cueing the target rectangle in the first stimulus, reduced by cueing in the interval and unaffected by cueing in the second presentation. This supports the idea that a representation was formed that persisted through the interval before being 'overwritten' by the second presentation (Landman et al, 2003 Vision Research 43149–164]. Another possibility is that participants used some kind of grouping or Gestalt strategy. To test this we changed the spatial position of the rectangles in the second presentation by shifting them along imaginary spokes (by ±1 degree) emanating from the central fixation point. There was no significant difference seen in performance between this and the standard task [F(1,4)=2.565, p=0.185]. This may suggest two things: (i) Gestalt grouping is not used as a strategy in these tasks, and (ii) it gives further weight to the argument that objects may be stored and retrieved from a pre-attentional store during this task

The Spatiotemporal Neural Dynamics of Object Recognition for Natural Images and Line Drawings

Drawings offer a simple and efficient way to communicate meaning. While line drawings capture only coarsely how objects look in reality, we still perceive them as resembling real-world objects. Previous work has shown that this perceived similarity is mirrored by shared neural representations for drawings and natural images, which suggests that similar mechanisms underlie the recognition of both. However, other work has proposed that representations of drawings and natural images become similar only after substantial processing has taken place, suggesting distinct mechanisms. To arbitrate between those alternatives, we measured brain responses resolved in space and time using fMRI and MEG, respectively, while human participants (female and male) viewed images of objects depicted as photographs, line drawings, or sketch-like drawings. Using multivariate decoding, we demonstrate that object category information emerged similarly fast and across overlapping regions in occipital, ventral-temporal, and posterior parietal cortex for all types of depiction, yet with smaller effects at higher levels of visual abstraction. In addition, cross-decoding between depiction types revealed strong generalization of object category information from early processing stages on. Finally, by combining fMRI and MEG data using representational similarity analysis, we found that visual information traversed similar processing stages for all types of depiction, yet with an overall stronger representation for photographs. Together, our results demonstrate broad commonalities in the neural dynamics of object recognition across types of depiction, thus providing clear evidence for shared neural mechanisms underlying recognition of natural object images and abstract drawings

Computational Study of Multisensory Gaze-Shift Planning

In response to appearance of multimodal events in the environment, we often make a gaze-shift in order to focus the attention and gather more information. Planning such a gaze-shift involves three stages: 1) to determine the spatial location for the gaze-shift, 2) to find out the time to initiate the gaze-shift, 3) to work out a coordinated eye-head motion to execute the gaze-shift. There have been a large number of experimental investigations to inquire the nature of multisensory and oculomotor information processing in any of these three levels separately. Here in this thesis, we approach this problem as a single executive program and propose computational models for them in a unified framework. The first spatial problem is viewed as inferring the cause of cross-modal stimuli, whether or not they originate from a common source (chapter 2). We propose an evidence-accumulation decision-making framework, and introduce a spatiotemporal similarity measure as the criterion to choose to integrate the multimodal information or not. The variability of report of sameness, observed in experiments, is replicated as functions of the spatial and temporal patterns of target presentations. To solve the second temporal problem, a model is built upon the first decision-making structure (chapter 3). We introduce an accumulative measure of confidence on the chosen causal structure, as the criterion for initiation of action. We propose that gaze-shift is implemented when this confidence measure reaches a threshold. The experimentally observed variability of reaction time is simulated as functions of spatiotemporal and reliability features of the cross-modal stimuli. The third motor problem is considered to be solved downstream of the two first networks (chapter 4). We propose a kinematic strategy that coordinates eye-in-head and head-on-shoulder movements, in both spatial and temporal dimensions, in order to shift the line of sight towards the inferred position of the goal. The variabilities in contributions of eyes and head movements to gaze-shift are modeled as functions of the retinal error and the initial orientations of eyes and head. The three models should be viewed as parts of a single executive program that integrates perceptual and motor processing across time and space

The spatiotemporal neural dynamics of object recognition for natural images and line drawings

Drawings offer a simple and efficient way to communicate meaning. While line drawings capture only coarsely how objects look in reality, we still perceive them as resembling real-world objects. Previous work has shown that this perceived similarity is mirrored by shared neural representations for drawings and natural images, which suggests that similar mechanisms underlie the recognition of both. However, other work has proposed that representations of drawings and natural images become similar only after substantial processing has taken place, suggesting distinct mechanisms. To arbitrate between those alternatives, we measured brain responses resolved in space and time using fMRI and MEG, respectively, while participants viewed images of objects depicted as photographs, line drawings, or sketch-like drawings. Using multivariate decoding, we demonstrate that object category information emerged similarly fast and across overlapping regions in occipital and ventral-temporal cortex for all types of depiction, yet with smaller effects at higher levels of visual abstraction. In addition, cross-decoding between depiction types revealed strong generalization of object category information from early processing stages on. Finally, by combining fMRI and MEG data using representational similarity analysis, we found that visual information traversed similar processing stages for all types of depiction, yet with an overall stronger representation for photographs. Together our results demonstrate broad commonalities in the neural dynamics of object recognition across types of depiction, thus providing clear evidence for shared neural mechanisms underlying recognition of natural object images and abstract drawings

The very same thing: Extending the object token concept to incorporate causal constraints on individual identity

The contributions of feature recognition, object categorization, and recollection of episodic memories to the re-identification of a perceived object as the very same thing encountered in a previous perceptual episode are well understood in terms of both cognitive-behavioral phenomenology and neurofunctional implementation. Human beings do not, however, rely solely on features and context to re-identify individuals; in the presence of featural change and similarly-featured distractors, people routinely employ causal constraints to establish object identities. Based on available cognitive and neurofunctional data, the standard object-token based model of individual re-identification is extended to incorporate the construction of unobserved and hence fictive causal histories (FCHs) of observed objects by the pre-motor action planning system. Cognitive-behavioral and implementation-level predictions of this extended model and methods for testing them are outlined. It is suggested that functional deficits in the construction of FCHs are associated with clinical outcomes in both Autism Spectrum Disorders and later-stage stage Alzheimer's disease.\u

Electrophysiological correlates of motor plans and graspability via dorsal/ventral interactions

Vision has historically been subdivided into two major systems. The vision-for-perception system is thought to be responsible for generating visual representations in service of recognition and identification. Conversely, the vision-for-action system is thought to transform visual information towards the goal of guiding motor behavior. Both systems have been linked to distinct anatomical pathways - the ventral pathway, originating in early visual cortex and terminating in the temporal lobe, is thought to mediate vision-for-perception, while the dorsal pathway, originating in early visual cortex and terminating in the parietal lobe, is thought to mediate vision-for-action. While serving as a fertile and influential theoretical framework, a growing body of evidence suggests these processing streams may not be as independent as once thought. Our current investigation is predicated on the observation that many visuomotor behaviors (mediated through the dorsal pathway), such as the manipulation of man-made tools, are contingent on the successful identification of the object (mediated through the ventral pathway). Here we investigate the nature of these interactions using High-Density Electroencephalography (HD-EEG), Multivariate Pattern analysis (MVPA) & EEG source localization. In experiment 1, participants viewed images of animate objects (birds & insects) and inanimate objects (tools & graspable objects). The frequency-tagging approach and the Fast Fourier Transform was used to examine frequency domain amplitude differences between the object categories. In experiment 2, evoked potentials from the same stimuli categories were used to explore the temporal dynamics of object processing. Next, source localization was used to explore the temporal dynamics of object processing within the dorsal and ventral pathways. Experiment 3 recapitulated the analyses used in experiment 2 on a different stimulus set (a stimulus set that controlled for the shape confound that exists between tools and graspable objects). Our results do not support the main hypothesis (i.e., we do not observe a temporal difference in the classification of tools vs. graspable objects between the dorsal and ventral pathway). Nonetheless, successful classification between the aforementioned stimulus categories is observed at the sensor level (EEG time course MVPA) as well as at the source level (source localized MVPA) in both neural pathways. These results may provide interesting implications regarding the spatiotemporal dynamics of object processing as well as the involvement of the two pathways

A Neural Model of How the Brain Computes Heading from Optic Flow in Realistic Scenes

Animals avoid obstacles and approach goals in novel cluttered environments using visual information, notably optic flow, to compute heading, or direction of travel, with respect to objects in the environment. We present a neural model of how heading is computed that describes interactions among neurons in several visual areas of the primate magnocellular pathway, from retina through V1, MT+, and MSTd. The model produces outputs which are qualitatively and quantitatively similar to human heading estimation data in response to complex natural scenes. The model estimates heading to within 1.5° in random dot or photo-realistically rendered scenes and within 3° in video streams from driving in real-world environments. Simulated rotations of less than 1 degree per second do not affect model performance, but faster simulated rotation rates deteriorate performance, as in humans. The model is part of a larger navigational system that identifies and tracks objects while navigating in cluttered environments.National Science Foundation (SBE-0354378, BCS-0235398); Office of Naval Research (N00014-01-1-0624); National-Geospatial Intelligence Agency (NMA201-01-1-2016

Fractals in the Nervous System: conceptual Implications for Theoretical Neuroscience

This essay is presented with two principal objectives in mind: first, to document the prevalence of fractals at all levels of the nervous system, giving credence to the notion of their functional relevance; and second, to draw attention to the as yet still unresolved issues of the detailed relationships among power law scaling, self-similarity, and self-organized criticality. As regards criticality, I will document that it has become a pivotal reference point in Neurodynamics. Furthermore, I will emphasize the not yet fully appreciated significance of allometric control processes. For dynamic fractals, I will assemble reasons for attributing to them the capacity to adapt task execution to contextual changes across a range of scales. The final Section consists of general reflections on the implications of the reviewed data, and identifies what appear to be issues of fundamental importance for future research in the rapidly evolving topic of this review