The integration of bottom-up and top-down signals in human perception in health and disease

To extract a meaningful visual experience from the information falling on the retina, the visual system must integrate signals from multiple levels. Bottom-up signals provide input relating to local features while top-down signals provide contextual feedback and reflect internal states of the organism. In this thesis I will explore the nature and neural basis of this integration in two key areas. I will examine perceptual filling-in of artificial scotomas to investigate the bottom-up signals causing changes in perception when filling-in takes place. I will then examine how this perceptual filling-in is modified by top-down signals reflecting attention and working memory. I will also investigate hemianopic completion, an unusual form of filling-in, which may reflect a breakdown in top-down feedback from higher visual areas. The second part of the thesis will explore a different form of top-down control of visual processing. While the effects of cognitive mechanisms such as attention on visual processing are well-characterised, other types of top-down signal such as reward outcome are less well explored. I will therefore study whether signals relating to reward can influence visual processing. To address these questions, I will employ a range of methodologies including functional MRI, magnetoencephalography and behavioural testing in healthy participants and patients with cortical damage. I will demonstrate that perceptual filling-in of artificial scotomas is largely a bottom-up process but that higher cognitive functions can modulate the phenomenon. I will also show that reward modulates activity in higher visual areas in the absence of concurrent visual stimulation and that receiving reward leads to enhanced activity in primary visual cortex on the next trial. These findings reveal that integration occurs across multiple levels even for processes rooted in early retinotopic regions, and that higher cognitive processes such as reward can influence the earliest stages of cortical visual processing

Understanding Galaxy Formation and Evolution

The old dream of integrating into one the study of micro and macrocosmos is now a reality. Cosmology, astrophysics, and particle physics intersect in a scenario (but still not a theory) of cosmic structure formation and evolution called Lambda Cold Dark Matter (LCDM) model. This scenario emerged mainly to explain the origin of galaxies. In these lecture notes, I first present a review of the main galaxy properties, highlighting the questions that any theory of galaxy formation should explain. Then, the cosmological framework and the main aspects of primordial perturbation generation and evolution are pedagogically detached. Next, I focus on the ``dark side'' of galaxy formation, presenting a review on LCDM halo assembling and properties, and on the main candidates for non-baryonic dark matter. It is shown how the nature of elemental particles can influence on the features of galaxies and their systems. Finally, the complex processes of baryon dissipation inside the non-linearly evolving CDM halos, formation of disks and spheroids, and transformation of gas into stars are briefly described, remarking on the possibility of a few driving factors and parameters able to explain the main body of galaxy properties. A summary and a discussion of some of the issues and open problems of the LCDM paradigm are given in the final part of these notes.Comment: 50 pages, 10 low-resolution figures (for normal-resolution, DOWNLOAD THE PAPER (PDF, 1.9 Mb) FROM http://www.astroscu.unam.mx/~avila/avila.pdf). Lectures given at the IV Mexican School of Astrophysics, July 18-25, 2005 (submitted to the Editors on March 15, 2006

The integration of bottom-up and top-down signals in human perception in health and disease.

To extract a meaningful visual experience from the information falling on the retina, the visual system must integrate signals from multiple levels. Bottom-up signals provide input relating to local features while top-down signals provide contextual feedback and reflect internal states of the organism. In this thesis I will explore the nature and neural basis of this integration in two key areas. I will examine perceptual filling-in of artificial scotomas to investigate the bottom-up signals causing changes in perception when filling-in takes place. I will then examine how this perceptual filling-in is modified by top-down signals reflecting attention and working memory. I will also investigate hemianopic completion, an unusual form of filling-in, which may reflect a breakdown in top-down feedback from higher visual areas. The second part of the thesis will explore a different form of top-down control of visual processing. While the effects of cognitive mechanisms such as attention on visual processing are well-characterised, other types of top-down signal such as reward outcome are less well explored. I will therefore study whether signals relating to reward can influence visual processing. To address these questions, I will employ a range of methodologies including functional MRI, magnetoencephalography and behavioural testing in healthy participants and patients with cortical damage. I will demonstrate that perceptual filling-in of artificial scotomas is largely a bottom-up process but that higher cognitive functions can modulate the phenomenon. I will also show that reward modulates activity in higher visual areas in the absence of concurrent visual stimulation and that receiving reward leads to enhanced activity in primary visual cortex on the next trial. These findings reveal that integration occurs across multiple levels even for processes rooted in early retinotopic regions, and that higher cognitive processes such as reward can influence the earliest stages of cortical visual processing.

Visual tests predict dementia risk in Parkinson disease

Objective: To assess the role of visual measures and retinal volume to predict the risk of Parkinson disease (PD) dementia. Methods: In this cohort study, we collected visual, cognitive, and motor data in people with PD. Participants underwent ophthalmic examination, retinal imaging using optical coherence tomography, and visual assessment including acuity and contrast sensitivity and high-level visuoperception measures of skew tolerance and biological motion. We assessed the risk of PD dementia using a recently described algorithm that combines age at onset, sex, depression, motor scores, and baseline cognition. Results: One hundred forty-six people were included in the study (112 with PD and 34 age-matched controls). The mean disease duration was 4.1 (±2·5) years. None of these participants had dementia. Higher risk of dementia was associated with poorer performance in visual measures (acuity: p = 0.29, p = 0.0024; contrast sensitivity: ρ = -0.37, p < 0.0001; skew tolerance: ρ = -0.25, p = 0.0073; and biological motion: p = -0.26, p = 0.0054). In addition, higher risk of PD dementia was associated with thinner retinal structure in layers containing dopaminergic cells, measured as ganglion cell layer (GCL) and inner plexiform layer (IPL) thinning (p = -0.29, p = 0.0021; p = -0.33, p = 0.00044). These relationships were not seen for the retinal nerve fiber layer that does not contain dopaminergic cells and were not seen in unaffected controls. Conclusion: Visual measures and retinal structure in dopaminergic layers were related to risk of PD dementia. Our findings suggest that visual measures and retinal GCL and IPL volumes may be useful to predict the risk of dementia in PD

Crossing to the dark side:examining antecedents and consequences of technostress

Exploring the factors that may lead to the inability of professionals to adapt or cope with emerging IS in a healthy manner