Visuomotor Performance in Children with Infantile Nephropathy Cystinosis

1996 ◽  
Vol 82 (1) ◽  
pp. 67-75 ◽  
Author(s):  
Kathleen M. Scarvie ◽  
Angela O. Ballantyne ◽  
Doris A. Trauner
Keyword(s):  
Visual Processing ◽  
Visual Information ◽  
Control Group ◽  
Standard Score ◽  
Developmental Test ◽  
Visual Motor ◽  
The Brain ◽  
Progressive Cognitive Impairment ◽  
Processing Of Visual Information ◽  
Qualitative Analyses

Infantile nephropathy cystinosis is a genetic metabolic disorder in which the amino acid cystine accumulates in various organs, including the kidney, cornea, thyroid, and brain. Despite normal intellect, individuals with cystinosis may have specific impairments in the processing of visual information. To examine further the specific types of deficits in visual processing found in individuals with cystinosis, we administered the Developmental Test of Visual-motor Integration to 26 children with cystinosis (4 to 16 yr. old) and 26 matched controls. The cystinosis group achieved a significantly lower standard score, raw score, and mean ceiling than did the control group. Qualitative analyses showed that in the cystinosis group, size within errors and rotation errors were more prevalent than in the control group. Correlational analyses showed that with advancing age, the cystinosis subjects tended to fall further behind their chronological age. Our data, together with the findings of previous studies, suggest that the visuospatial difficulties in children with cystinosis may be due to inadequate perception or processing of visually presented information. Furthermore, the increasing discrepancy with age may reflect a progressive cognitive impairment, possibly as a result of cystine accumulation in the brain over time.

Top-Down Predictions Determine Perceptions

2017 ◽  
Author(s):  
Martin V. Butz ◽  
Esther F. Kutter
Keyword(s):  
Graphical Models ◽  
Information Integration ◽  
Visual Processing ◽  
Visual Information ◽  
Generative Models ◽  
Sources Of Information ◽  
Multiple Sources ◽  
Top Down ◽  
Bottom Up ◽  
The Brain

While bottom-up visual processing is important, the brain integrates this information with top-down, generative expectations from very early on in the visual processing hierarchy. Indeed, our brain should not be viewed as a classification system, but rather as a generative system, which perceives something by integrating sensory evidence with the available, learned, predictive knowledge about that thing. The involved generative models continuously produce expectations over time, across space, and from abstracted encodings to more concrete encodings. Bayesian information processing is the key to understand how information integration must work computationally – at least in approximation – also in the brain. Bayesian networks in the form of graphical models allow the modularization of information and the factorization of interactions, which can strongly improve the efficiency of generative models. The resulting generative models essentially produce state estimations in the form of probability densities, which are very well-suited to integrate multiple sources of information, including top-down and bottom-up ones. A hierarchical neural visual processing architecture illustrates this point even further. Finally, some well-known visual illusions are shown and the perceptions are explained by means of generative, information integrating, perceptual processes, which in all cases combine top-down prior knowledge and expectations about objects and environments with the available, bottom-up visual information.

scholarly journals Brain state-dependent modulation of thalamic visual processing by cortico-thalamic feedback

2021 ◽  
Author(s):  
Kimberly Reinhold ◽  
Arbora Resulaj ◽  
Massimo Scanziani
Keyword(s):  
Visual Stimulus ◽  
Visual Processing ◽  
Visual Information ◽  
Early Stage ◽  
Visual Stimuli ◽  
Brain State ◽  
Spatial Features ◽  
State Dependent ◽  
Temporal And Spatial ◽  
The Brain

The behavioral state of a mammal impacts how the brain responds to visual stimuli as early as in the dorsolateral geniculate nucleus of the thalamus (dLGN), the primary relay of visual information to the cortex. A clear example of this is the markedly stronger response of dLGN neurons to higher temporal frequencies of the visual stimulus in alert as compared to quiescent animals. The dLGN receives strong feedback from the visual cortex, yet whether this feedback contributes to these state-dependent responses to visual stimuli is poorly understood. Here we show that in mice, silencing cortico-thalamic feedback abolishes state-dependent differences in the response of dLGN neurons to visual stimuli. This holds true for dLGN responses to both temporal and spatial features of the visual stimulus. These results reveal that the state-dependent shift of the response to visual stimuli in an early stage of visual processing depends on cortico-thalamic feedback.

Primary Visual Perception from the Bottom Up

2017 ◽  
Author(s):  
Martin V. Butz ◽  
Esther F. Kutter
Keyword(s):  
Visual Perception ◽  
Visual Processing ◽  
Visual Information ◽  
Information Needs ◽  
Depth Information ◽  
Top Down ◽  
Edge Detectors ◽  
Brain Extracts ◽  
Visual Properties ◽  
The Brain

This chapter addresses primary visual perception, detailing how visual information comes about and, as a consequence, which visual properties provide particularly useful information about the environment. The brain extracts this information systematically, and also separates redundant and complementary visual information aspects to improve the effectiveness of visual processing. Computationally, image smoothing, edge detectors, and motion detectors must be at work. These need to be applied in a convolutional manner over the fixated area, which are computations that are predestined to be solved by means of cortical columnar structures in the brain. On the next level, the extracted information needs to be integrated to be able to segment and detect object structures. The brain solves this highly challenging problem by incorporating top-down expectations and by integrating complementary visual information aspects, such as light reflections, texture information, line convergence information, shadows, and depth information. In conclusion, the need for integrating top-down visual expectations to form complete and stable perceptions is made explicit.

scholarly journals An evolving view of retinogeniculate transmission

2017 ◽  
Vol 34 ◽  
Author(s):  
ELIZABETH Y. LITVINA ◽  
CHINFEI CHEN
Keyword(s):  
Visual Processing ◽  
Visual Information ◽  
Dynamic Properties ◽  
Optic Tract ◽  
Retinal Ganglion ◽  
Relay Neuron ◽  
Retinogeniculate Synapse ◽  
Retinal Fibers ◽  
Processing Of Visual Information

AbstractThe thalamocortical (TC) relay neuron of the dorsoLateral Geniculate Nucleus (dLGN) has borne its imprecise label for many decades in spite of strong evidence that its role in visual processing transcends the implied simplicity of the term “relay”. The retinogeniculate synapse is the site of communication between a retinal ganglion cell and a TC neuron of the dLGN. Activation of retinal fibers in the optic tract causes reliable, rapid, and robust postsynaptic potentials that drive postsynaptics spikes in a TC neuron. Cortical and subcortical modulatory systems have been known for decades to regulate retinogeniculate transmission. The dynamic properties that the retinogeniculate synapse itself exhibits during and after developmental refinement further enrich the role of the dLGN in the transmission of the retinal signal. Here we consider the structural and functional substrates for retinogeniculate synaptic transmission and plasticity, and reflect on how the complexity of the retinogeniculate synapse imparts a novel dynamic and influential capacity to subcortical processing of visual information.

Automatic Versus Contingent Mechanisms of Sensory-Driven Neural Biasing and Reflexive Attention

2005 ◽  
Vol 17 (8) ◽  
pp. 1341-1352 ◽  
Author(s):  
Joseph B. Hopfinger ◽  
Anthony J. Ries
Keyword(s):  
Visual Processing ◽  
Visual Information ◽  
Response Times ◽  
Event Related Potentials ◽  
Top Down ◽  
Manual Response ◽  
Reflexive Attention ◽  
Manual Responses ◽  
Related Potentials ◽  
The Brain

Recent studies have generated debate regarding whether reflexive attention mechanisms are triggered in a purely automatic stimulus-driven manner. Behavioral studies have found that a nonpredictive “cue” stimulus will speed manual responses to subsequent targets at the same location, but only if that cue is congruent with actively maintained top-down settings for target detection. When a cue is incongruent with top-down settings, response times are unaffected, and this has been taken as evidence that reflexive attention mechanisms were never engaged in those conditions. However, manual response times may mask effects on earlier stages of processing. Here, we used event-related potentials to investigate the interaction of bottom-up sensory-driven mechanisms and top-down control settings at multiple stages of processing in the brain. Our results dissociate sensory-driven mechanisms that automatically bias early stages of visual processing from later mechanisms that are contingent on top-down control. An early enhancement of target processing in the extrastriate visual cortex (i.e., the P1 component) was triggered by the appearance of a unique bright cue, regardless of top-down settings. The enhancement of visual processing was prolonged, however, when the cue was congruent with top-down settings. Later processing in posterior temporal-parietal regions (i.e., the ipsilateral invalid negativity) was triggered automatically when the cue consisted of the abrupt appearance of a single new object. However, in cases where more than a single object appeared during the cue display, this stage of processing was contingent on top-down control. These findings provide evidence that visual information processing is biased at multiple levels in the brain, and the results distinguish automatically triggered sensory-driven mechanisms from those that are contingent on top-down control settings.

scholarly journals Teasing apart the extraction and the processing of visual information in the brain

2017 ◽  
Vol 17 (10) ◽  
pp. 972
Author(s):  
Laurent Caplette ◽  
Karim Jerbi ◽  
Frédéric Gosselin
Keyword(s):  
Visual Information ◽  
The Brain ◽  
Processing Of Visual Information

scholarly journals Temporal uncertainty affects the visual processing of predicted stimulus properties

2020 ◽  
Author(s):  
Sanjeev Nara ◽  
Mikel Lizarazu ◽  
Craig G Richter ◽  
Diana C Dima ◽  
Mathieu Bourguignon ◽  
...  
Keyword(s):  
Visual Processing ◽  
Visual Information ◽  
Temporal Dynamics ◽  
External Environment ◽  
Predictive Processing ◽  
External Information ◽  
Specific Information ◽  
Temporal Uncertainty ◽  
Suppression Effect ◽  
The Brain

AbstractPredictive processing has been proposed as a fundamental cognitive mechanism to account for how the brain interacts with the external environment via its sensory modalities. The brain processes external information about the content (i.e. “what”) and timing (i.e., “when”) of environmental stimuli to update an internal generative model of the world around it. However, the interaction between “what” and “when” has received very little attention when focusing on vision. In this magnetoencephalography (MEG) study we investigate how processing of feature specific information (i.e. “what”) is affected by temporal predictability (i.e. “when”). In line with previous findings, we observed a suppression of evoked neural responses in the visual cortex for predictable stimuli. Interestingly, we observed that temporal uncertainty enhances this expectation suppression effect. This suggests that in temporally uncertain scenarios the neurocognitive system relies more on internal representations and invests less resources integrating bottom-up information. Indeed, temporal decoding analysis indicated that visual features are encoded for a shorter time period by the neural system when temporal uncertainty is higher. This supports the fact that visual information is maintained active for less time for a stimulus whose time onset is unpredictable compared to when it is predictable. These findings highlight the higher reliance of the visual system on the internal expectations when the temporal dynamics of the external environment are less predictable.

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