Travel Planning Ability in Right Brain-Damaged Patients: Two Case Reports

Planning ability is fundamental for goal-directed spatial navigation. Preliminary findings from patients and healthy individuals suggest that travel planning (TP)—namely, navigational planning—can be considered a distinct process from visuospatial planning (VP) ability. To shed light on this distinction, two right brain-damaged patients without hemineglect were compared with a control group on two tasks aimed at testing VP (i.e., Tower of London-16, ToL-16) and TP (i.e., Minefield Task, MFT). The former requires planning the moves to reach the right configuration of three colored beads on three pegs, whereas the latter was opportunely developed to assess TP in the navigational environment when obstacles are present. Specifically, the MFT requires participants to plan a route on a large carpet avoiding some hidden obstacles previously observed. Patient 1 showed lesions encompassing the temporoparietal region and the insula; she performed poorer than the control group on the ToL-16 but showed no deficit on the MFT. Conversely, Patient 2 showed lesions mainly located in the occipitoparietal network of spatial navigation; she performed worse than the control group on the MFT but not on the ToL-16. In both cases performances satisfied the criteria for a classical dissociation, meeting criteria for a double dissociation. These results support the idea that TP is a distinct ability and that it is dissociated from VP skills

Face Hallucination via Deep Neural Networks.

We firstly address aligned low-resolution (LR) face images (i.e. 16X16 pixels) by designing a discriminative generative network, named URDGN. URDGN is composed of two networks: a generative model and a discriminative model. We introduce a pixel-wise L2 regularization term to the generative model and exploit the feedback of the discriminative network to make the upsampled face images more similar to real ones. We present an end-to-end transformative discriminative neural network (TDN) devised for super-resolving unaligned tiny face images. TDN embeds spatial transformation layers to enforce local receptive fields to line-up with similar spatial supports. To upsample noisy unaligned LR face images, we propose decoder-encoder-decoder networks. A transformative discriminative decoder network is employed to upsample and denoise LR inputs simultaneously. Then we project the intermediate HR faces to aligned and noise-free LR faces by a transformative encoder network. Finally, high-quality hallucinated HR images are generated by our second decoder. Furthermore, we present an end-to-end multiscale transformative discriminative neural network (MTDN) to super-resolve unaligned LR face images of different resolutions in a unified framework. We propose a method that explicitly incorporates structural information of faces into the face super-resolution process by using a multi-task convolutional neural network (CNN). Our method not only uses low-level information (i.e. intensity similarity), but also middle-level information (i.e. face structure) to further explore spatial constraints of facial components from LR inputs images. We demonstrate that supplementing residual images or feature maps with additional facial attribute information can significantly reduce the ambiguity in face super-resolution. To explore this idea, we develop an attribute-embedded upsampling network. In this manner, our method is able to super-resolve LR faces by a large upscaling factor while reducing the uncertainty of one-to-many mappings remarkably. We further push the boundaries of hallucinating a tiny, non-frontal face image to understand how much of this is possible by leveraging the availability of large datasets and deep networks. To this end, we introduce a novel Transformative Adversarial Neural Network (TANN) to jointly frontalize very LR out-of-plane rotated face images (including profile views) and aggressively super-resolve them by 8X, regardless of their original poses and without using any 3D information. Besides recovering an HR face images from an LR version, this thesis also addresses the task of restoring realistic faces from stylized portrait images, which can also be regarded as face hallucination

The Empathic Brain of Psychopaths: From Social Science to Neuroscience in Empathy

Empathy is a crucial human ability, because of its importance to prosocial behavior, and for moral development. A deficit in empathic abilities, especially affective empathy, is thought to play an important role in psychopathic personality. Empathic abilities have traditionally been studied within the social and behavioral sciences using behavioral methods, but recent work in neuroscience has begun to elucidate the neural underpinnings of empathic processing in relation to psychopathy. In this review, current knowledge in the social neuroscience of empathy is discussed and a comprehensive view of the neuronal mechanisms that underlie empathy in psychopathic personality is provided. Furthermore, it will be argued that using classification based on overt behavior, we risk failin

Brain-Computer Interface Based on Generation of Visual Images

This paper examines the task of recognizing EEG patterns that correspond to performing three mental tasks: relaxation and imagining of two types of pictures: faces and houses. The experiments were performed using two EEG headsets: BrainProducts ActiCap and Emotiv EPOC. The Emotiv headset becomes widely used in consumer BCI application allowing for conducting large-scale EEG experiments in the future. Since classification accuracy significantly exceeded the level of random classification during the first three days of the experiment with EPOC headset, a control experiment was performed on the fourth day using ActiCap. The control experiment has shown that utilization of high-quality research equipment can enhance classification accuracy (up to 68% in some subjects) and that the accuracy is independent of the presence of EEG artifacts related to blinking and eye movement. This study also shows that computationally-inexpensive Bayesian classifier based on covariance matrix analysis yields similar classification accuracy in this problem as a more sophisticated Multi-class Common Spatial Patterns (MCSP) classifier

Tracking the cognitive, social, and neuroanatomical profile in early neurodegeneration: Type III Cockayne syndrome

Cockayne syndrome (CS) is an autosomal recessive disease associated with premature aging, progressive multiorgan degeneration, and nervous system abnormalities including cerebral and cerebellar atrophy, brain calcifications, and white matter abnormalities. Although several clinical descriptions of CS patients have reported developmental delay and cognitive impairment with relative preservation of social skills, no previous studies have carried out a comprehensive neuropsychological and social cognition assessment. Furthermore, no previous research in individuals with CS has examined the relationship between brain atrophy and performance on neuropsychological and social cognition tests. This study describes the case of an atypical late-onset type III CS patient who exceeds the mean life expectancy of individuals with this pathology. The patient and a group of healthy controls underwent a comprehensive assessment that included multiple neuropsychological and social cognition (emotion recognition, theory of mind, and empathy) tasks. In addition, we compared the pattern of atrophy in the patient to controls and to its concordance with ERCC8 gene expression in a healthy brain. The results showed memory, language, and executive deficits that contrast with the relative preservation of social cognition skills. The cognitive profile of the patient was consistent with his pattern of global cerebral and cerebellar loss of gray matter volume (frontal structures, bilateral cerebellum, basal ganglia, temporal lobe, and occipito-temporal/occipito-parietal regions), which in turn was anatomically consistent with the ERCC8 gene expression level in a healthy donor's brain. The study of exceptional cases, such as the one described here, is fundamental to elucidating the processes that affect the brain in premature aging diseases, and such studies provide an important source of information for understanding the problems associated with normal and pathological aging.Fil: Báez Buitrago, Sandra Jimena. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Diego Portales; Chile. Pontificia Universidad Católica Argentina "Santa María de los Buenos Aires"; Argentina. Universidad Favaloro; Argentina. Instituto de Neurología Cognitiva; ArgentinaFil: Couto, Juan Blas Marcos. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Favaloro; Argentina. Instituto de Neurología Cognitiva; ArgentinaFil: Herrera, Eduar. Universidad Autónoma del Caribe; ColombiaFil: Bocanegra, Yamile. Universidad de Antioquia; Colombia. Universidad de San Buenaventura; ColombiaFil: Trujillo Orrego, Natalia. Universidad de Antioquia; ColombiaFil: Madriga Zapata, Lucia. Universidad de Antioquia; ColombiaFil: Cardona Londoño, Juan Felipe. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Favaloro; Argentina. Instituto de Neurología Cognitiva; ArgentinaFil: Manes, Facundo Francisco. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Australian Government, Australian Research Council; Australia. Universidad Diego Portales; Chile. Universidad Favaloro; Argentina. Instituto de Neurología Cognitiva; ArgentinaFil: Ibáñez Barassi, Agustín Mariano. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Diego Portales; Chile. Universidad Favaloro; Argentina. Instituto de Neurología Cognitiva; ArgentinaFil: Villegas, Andres. Universidad de Antioquia; Colombi

Semantic Memory for Food and Brain Correlates

Semantic memory stores knowledge about different types of objects: plants, animals, vehicles, utensils, conspecifics and food, among the others. Our ability to quickly recognize and categorize an object when we encounter it depends upon having experienced that object before and on semantic knowledge integrity. Semantic memory is one the most resilient cognitive abilities, it is less prone to interference than episodic memory and more declines slowly. The interest in how semantic memory is organized traces way back, however a great impulse was provided by the first systematic neuropsychological observations of patients with category specific recognition deficits. However, this debate is far from being resolved. In my dissertation, I will show how the study of food as a semantic category is extremely suitable to shed light on the organization of semantic knowledge. The thesis is organized as follow. In Chapter 1, I will first define semantic memory, focusing on its characteristics, such as its relationship with experience, its resilience to cognitive decline and its neural correlates, and on how it has been studied by neuropsychologists. In addition, I will review the studies on the food category, focusing on some intrinsic dimensions such as the level of transformation. Chapter 2 includes Study 1, in which I have investigated the organization of semantic memory by using food (natural and transformed) and non-food (living and on-living things) in a group of patients suffering from temporal lobe atrophy (Alzheimer\u2019s disease, PPA and FTD) and healthy controls, using Voxel Based Morphometry and DTI. Results have shown that food breaks down in natural and transformed, and that this parsing mirrors that of living and non-living things, thus strongly supporting the Sensory-functional model of semantic knowledge. Chapter 3 contains Study 2, in which I have explored the relationship between semantic memory and experience. I collected information about life-long eating habits as a proxy of long-term experience with specific foods as well as information about semantic memory of food in participants of different ages (36 \u2013 108 years old). Results support the hypothesis that semantic memory is modulated by experience. In Chapter 4, the focus of Study 3 is on episodic memory. Here I investigated whether the difference between semantic memory for natural and transformed food highlighted in Study 2 extends also to episodic memory, and whether the animacy effect - a facilitation to remember living exemplars - holds for food as well. Specifically, I administered a recognition memory task to the same participants of Study 2, to a group of young participants and to patients with Alzheimer\u2019s disease, PPA and FTD. I found that young adults had better recognition memory for transformed foods compared to natural foods. This difference disappeared in centenarians, consistently with Study 2, and in patients. The natural/transformed distinction appears susceptible to decay only in the presence of a high degree of episodic memory impairment. Finally, with Study 4, described in Chapter 5, my aim was more translational, that is, to test whether a deficit in semantic memory for food could lead to specific eating disorders. This study empirically establishes the behavioural and neural correlates of abnormal changes in eating habits in dementia and their relationship with semantic memory. In this thesis, I have shown that natural and transformed food do have different neural correlates, and that they are differently represented in semantic memory. By drawing together evidence from my studies and from studies of others I was allowed to propose a comprehensive model of semantic knowledge. Additionally, in my thesis I showed how food can be employed to study the organization of semantic knowledge, the way in which semantic knowledge is shaped by learning and experience, and its effect on behaviour

Know-how, intellectualism, and memory systems

ABSTRACTA longstanding tradition in philosophy distinguishes between knowthatand know-how. This traditional “anti-intellectualist” view is soentrenched in folk psychology that it is often invoked in supportof an allegedly equivalent distinction between explicit and implicitmemory, derived from the so-called “standard model of memory.”In the last two decades, the received philosophical view has beenchallenged by an “intellectualist” view of know-how. Surprisingly, defenders of the anti-intellectualist view have turned to the cognitivescience of memory, and to the standard model in particular, todefend their view. Here, I argue that this strategy is a mistake. As it turns out, upon closer scrutiny, the evidence from cognitivepsychology and neuroscience of memory does not support theanti-intellectualist approach, mainly because the standard modelof memory is likely wrong. However, this need not be interpretedas good news for the intellectualist, for it is not clear that theempirical evidence necessarily supp..