Dorsal and Ventral Stream Function in Children With Developmental Coordination Disorder

Dorsal stream cortical networks underpin a cluster of visuomotor, visuospatial, and visual attention functions. Sensitivity to global coherence of motion and static form is considered a signature of visual cortical processing in the dorsal stream (motion) relative to the ventral stream (form). Poorer sensitivity to global motion compared to global static form has been found across a diverse range of neurodevelopmental disorders, suggesting a “dorsal stream vulnerability.” However, previous studies of global coherence sensitivity in Developmental Coordination Disorder (DCD) have shown conflicting findings. We examined two groups totalling 102 children with DCD (age 5–12 years), using the “Ball in the Grass” psychophysical test to compare sensitivity to global motion and global static form. Motor impairment was measured using the Movement-ABC (M-ABC). Global coherence sensitivity was compared with a typically developing control group (N = 69) in the same age range. Children with DCD showed impaired sensitivity to global motion (p = 0.002), but not global form (p = 0.695), compared to controls. Within the DCD group, motor impairment showed a significant linear relationship with global form sensitivity (p < 0.001). There was also a significant quadratic relationship between motor impairment and global motion sensitivity (p = 0.046), where poorer global motion sensitivity was only apparent with greater motor impairment. We suggest that two distinct visually related components, associated with global form and global motion sensitivity, contribute to DCD differentially over the range of severity of the disorder. Possible neural circuitry underlying these relationships is discussed.

Deep neural networks and visuo-semantic models explain complementary components of human ventral-stream representational dynamics

Deep neural networks (DNNs) are promising models of the cortical computations supporting human object recognition. However, despite their ability to explain a significant portion of variance in neural data, the agreement between models and brain representational dynamics is far from perfect. Here, we address this issue by asking which representational features are currently unaccounted for in neural timeseries data, estimated for multiple areas of the human ventral stream via source-reconstructed magnetoencephalography (MEG) data. In particular, we focus on the ability of visuo-semantic models, consisting of human-generated labels of higher-level object features and categories, to explain variance beyond the explanatory power of DNNs alone. We report a gradual transition in the importance of visuo-semantic features from early to higher-level areas along the ventral stream. While early visual areas are better explained by DNN features, higher-level cortical dynamics are best accounted for by visuo-semantic models. These results suggest that current DNNs fail to fully capture the visuo-semantic features represented in higher-level human visual cortex and suggest a path towards more accurate models of ventral stream computations.

Independent contributions of structural and functional connectivity: evidence from a stroke model

Altered functional connectivity is related to severity of language impairment in poststroke aphasia. However, it is not clear whether this finding specifically reflects loss of functional coherence, or more generally, is related to decreased structural connectivity due to cortical necrosis. The aim of the current study was to investigate this issue by factoring out structural connectivity from functional connectivity measures and then relating the residual data to language performance post-stroke. Ninety-seven participants with a history of stroke were assessed using language impairment measures (Auditory Verbal Comprehension and Spontaneous Speech scores from the Western Aphasia Battery-Revised) and MRI (structural, diffusion tensor imaging, and resting state functional connectivity). We analyzed the association between functional connectivity and language and controlled for multiple potential neuroanatomical confounders, namely structural connectivity. We identified functional connections within the left-hemisphere ventral stream where decreased functional connectivity, independent of structural connectivity, was associated with speech comprehension impairment. These connections exist in frontotemporal andtemporoparietal regions. Our results suggest poor speech comprehension in aphasia is at least partially caused by loss of cortical synchrony in a left hemisphere ventral stream network and is not only reflective of localized necrosis or structural connectivity.

Lessons from human vision for robotic design

The visual guidance of goal-directed movements requires transformations of incoming visual information that are different from those required for visual perception. For us to grasp an object successfully, our brain must use just-in-time computations of the object’s real-world size and shape, and its orientation and disposition with respect to our hand. These requirements have led to the emergence of dedicated visuomotor modules in the posterior parietal cortex of the human brain (the dorsal visual stream) that are functionally distinct from networks in the occipito-temporal cortex (the ventral visual stream) that mediate our conscious perception of the world. Although the identification and selection of goal objects and an appropriate course of action depends on the perceptual machinery of the ventral stream and associated cognitive modules, the execution of the subsequent goal-directed action is mediated by dedicated online control systems in the dorsal stream and associated motor areas. The dorsal stream allows an observer to reach out and grasp objects with exquisite ease, but by itself, deals only with objects that are visible at the moment the action is being programmed. The ventral stream, however, allows an observer to escape the present and bring to bear information from the past – including information about the function of objects, their intrinsic properties, and their location with reference to other objects in the world. Ultimately then, both streams contribute to the production of goal-directed actions. The principles underlying this division of labour between the dorsal and ventral streams are relevant to the design and implementation of autonomous robotic systems.

Engagement of Language and Domain General Networks during Word Monitoring in a Native and Unknown Language

Functional neuroimaging studies have highlighted the roles of three networks in processing language, all of which are typically left-lateralized: a ventral stream involved in semantics, a dorsal stream involved in phonology and speech production, and a more dorsal “multiple demand” network involved in many effortful tasks. As lateralization in all networks may be affected by life factors such as age, literacy, education, and brain pathology, we sought to develop a task paradigm with which to investigate the engagement of these networks, including manipulations to selectively emphasize semantic and phonological processing within a single task performable by almost anyone regardless of literacy status. In young healthy participants, we administered an auditory word monitoring task, in which participants had to note the occurrence of a target word within a continuous story presented in either their native language, Portuguese, or the unknown language, Japanese. Native language task performance activated ventral stream language networks, left lateralized but bilateral in the anterior temporal lobe. Unfamiliar language performance, being more difficult, activated left hemisphere dorsal stream structures and the multiple demand network bilaterally, but predominantly in the right hemisphere. These findings suggest that increased demands on phonological processing to accomplish word monitoring in the absence of semantic support may result in the bilateral recruitment of networks involved in speech perception under more challenging conditions.

Temporal stability of stimulus representation increases along rodent visual cortical hierarchies

Cortical representations of brief, static stimuli become more invariant to identity-preserving transformations along the ventral stream. Likewise, increased invariance along the visual hierarchy should imply greater temporal persistence of temporally structured dynamic stimuli, possibly complemented by temporal broadening of neuronal receptive fields. However, such stimuli could engage adaptive and predictive processes, whose impact on neural coding dynamics is unknown. By probing the rat analog 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 grew gradually along the hierarchy. A database of recordings from mouse showed similar trends, additionally revealing dependencies on the behavioral state. Overall, these findings show that visual representations become progressively more stable along rodent visual processing hierarchies, with an important contribution provided by intrinsic processing.

The role of posterior ventral stream areas for viewpoint-invariant object recognition

Object constancy is one of the most crucial mechanisms of the human visual system enabling viewpoint invariant object recognition. However, the neuronal foundations of object constancy are widely unknown. Research has shown that the ventral visual stream is involved in processing of various kinds of object stimuli and that several regions along the ventral stream are possibly sensitive to the orientation of an object in space. To systematically address the question of viewpoint sensitive object perception, we conducted a study with stroke patients as well as an fMRI experiment with healthy participants applying object stimuli in several spatial orientations, for example in typical and atypical viewing conditions. In the fMRI experiment, we found stronger BOLD signals and above-chance classification accuracies for objects presented in atypical viewing conditions in fusiform face sensitive and lateral occipito-temporal object preferring areas. In the behavioral patient study, we observed that lesions of the right fusiform gyrus were associated with lower performance in object recognition for atypical views. The complementary results from both experiments emphasize the contributions of fusiform and lateral-occipital areas to visual object constancy and indicate that visual object constancy is particularly enabled through increased neuronal activity and specific activation patterns for objects in demanding viewing conditions.

Beyond category-supervision: instance-level contrastive learning models predict human visual system responses to objects

Anterior regions of the ventral visual stream have substantial information about object categories, prompting theories that category-level forces are critical for shaping visual representation. The strong correspondence between category-supervised deep neural networks and ventral stream representation supports this view, but does not provide a viable learning model, as these deepnets rely upon millions of labeled examples. Here we present a fully self-supervised model which instead learns to represent individual images, where views of the same image are embedded nearby in a low-dimensional feature space, distinctly from other recently encountered views. We find category information implicitly emerges in the feature space, and critically that these models achieve parity with category-supervised models in predicting the hierarchical structure of brain responses across the human ventral visual stream. These results provide computational support for learning instance-level representation as a viable goal of the ventral stream, offering an alternative to the category-based framework that has been dominant in visual cognitive neuroscience.