Neural synchrony in cortical networks : history, concept and current status

Following the discovery of context-dependent synchronization of oscillatory neuronal responses in the visual system, the role of neural synchrony in cortical networks has been expanded to provide a general mechanism for the coordination of distributed neural activity patterns. In the current paper, we present an update of the status of this hypothesis through summarizing recent results from our laboratory that suggest important new insights regarding the mechanisms, function and relevance of this phenomenon. In the first part, we present recent results derived from animal experiments and mathematical simulations that provide novel explanations and mechanisms for zero and nero-zero phase lag synchronization. In the second part, we shall discuss the role of neural synchrony for expectancy during perceptual organization and its role in conscious experience. This will be followed by evidence that indicates that in addition to supporting conscious cognition, neural synchrony is abnormal in major brain disorders, such as schizophrenia and autism spectrum disorders. We conclude this paper with suggestions for further research as well as with critical issues that need to be addressed in future studies

Neural synchrony in cortical networks : history, concept and current status

Following the discovery of context-dependent synchronization of oscillatory neuronal responses in the visual system, the role of neural synchrony in cortical networks has been expanded to provide a general mechanism for the coordination of distributed neural activity patterns. In the current paper, we present an update of the status of this hypothesis through summarizing recent results from our laboratory that suggest important new insights regarding the mechanisms, function and relevance of this phenomenon. In the first part, we present recent results derived from animal experiments and mathematical simulations that provide novel explanations and mechanisms for zero and nero-zero phase lag synchronization. In the second part, we shall discuss the role of neural synchrony for expectancy during perceptual organization and its role in conscious experience. This will be followed by evidence that indicates that in addition to supporting conscious cognition, neural synchrony is abnormal in major brain disorders, such as schizophrenia and autism spectrum disorders. We conclude this paper with suggestions for further research as well as with critical issues that need to be addressed in future studies

Discovering a Domain Knowledge Representation for Image Grouping: Multimodal Data Modeling, Fusion, and Interactive Learning

In visually-oriented specialized medical domains such as dermatology and radiology, physicians explore interesting image cases from medical image repositories for comparative case studies to aid clinical diagnoses, educate medical trainees, and support medical research. However, general image classification and retrieval approaches fail in grouping medical images from the physicians\u27 viewpoint. This is because fully-automated learning techniques cannot yet bridge the gap between image features and domain-specific content for the absence of expert knowledge. Understanding how experts get information from medical images is therefore an important research topic. As a prior study, we conducted data elicitation experiments, where physicians were instructed to inspect each medical image towards a diagnosis while describing image content to a student seated nearby. Experts\u27 eye movements and their verbal descriptions of the image content were recorded to capture various aspects of expert image understanding. This dissertation aims at an intuitive approach to extracting expert knowledge, which is to find patterns in expert data elicited from image-based diagnoses. These patterns are useful to understand both the characteristics of the medical images and the experts\u27 cognitive reasoning processes. The transformation from the viewed raw image features to interpretation as domain-specific concepts requires experts\u27 domain knowledge and cognitive reasoning. This dissertation also approximates this transformation using a matrix factorization-based framework, which helps project multiple expert-derived data modalities to high-level abstractions. To combine additional expert interventions with computational processing capabilities, an interactive machine learning paradigm is developed to treat experts as an integral part of the learning process. Specifically, experts refine medical image groups presented by the learned model locally, to incrementally re-learn the model globally. This paradigm avoids the onerous expert annotations for model training, while aligning the learned model with experts\u27 sense-making

Neurocognitive Informatics Manifesto.

Informatics studies all aspects of the structure of natural and artificial information systems. Theoretical and abstract approaches to information have made great advances, but human information processing is still unmatched in many areas, including information management, representation and understanding. Neurocognitive informatics is a new, emerging field that should help to improve the matching of artificial and natural systems, and inspire better computational algorithms to solve problems that are still beyond the reach of machines. In this position paper examples of neurocognitive inspirations and promising directions in this area are given

Semantic processing with and without awareness. Insights from computational linguistics and semantic priming.

During my PhD, I’ve explored how native speakers access semantic information from lexical stimuli, and weather consciousness plays a role in the process of meaning construction. In a first study, I exploited the metaphor linking time and space to assess the specific contribution of linguistically–coded information to the emergence of priming. In fact, time is metaphorically arranged on either the horizontal or the sagittal axis in space (Clark, 1973), but only the latter comes up in language (e.g., "a bright future in front of you"). In a semantic categorization task, temporal target words (e.g., earlier, later) were primed by spatial words that were processed either consciously (unmasked) or unconsciously (masked). With visible primes, priming was observed for both lateral and sagittal words; yet, only the latter ones led to a significant effect when the primes were masked. Thus, unconscious word processing may be limited to those aspects of meaning that emerge in language use. In a second series of experiments, I tried to better characterize these aspects by taking advantage of Distributional Semantic Models (DSMs; Marelli, 2017), which represent word meaning as vectors built upon word co–occurrences in large textual database. I compared state–of–the–art DSMs with Pointwise Mutual Information (PMI; Church & Hanks, 1990), a measure of local association between words that is merely based on their surface co–occurrence. In particular, I tested how the two indexes perform on a semantic priming dataset comprising visible and masked primes, and different stimulus onset asynchronies between the two stimuli. Subliminally, none of the predictor alone elicited significant priming, although participants who showed some residual prime visibility showed larger effect. Post-hoc analyses showed that for subliminal priming to emerge, the additive contribution of both PMI and DSM was required. Supraliminally, PMI outperforms DSM in the fit to the behavioral data. According to these results, what has been traditionally thought of as unconscious semantic priming may mostly rely on local associations based on shallow word cooccurrence. Of course, masked priming is only one possible way to model unconscious perception. In an attempt to provide converging evidence, I also tested overt and covert semantic facilitation by presenting prime words in the unattended vs. attended visual hemifield of brain–injured patients suffering from neglect. In seven sub–acute cases, data show more solid PMI–based than DSM–based priming in the unattended hemifield, confirming the results obtained from healthy participants. Finally, in a fourth work package, I explored the neural underpinnings of semantic processing as revealed by EEG (Kutas & Federmeier, 2011). As the behavioral results of the previous study were much clearer when the primes were visible, I focused on this condition only. Semantic congruency was dichotomized in order to compare the ERP evoked by related and unrelated pairs. Three different types of semantic similarity were taken into account: in a first category, primes and targets were often co–occurring but far in the DSM (e.g., cheese-mouse), while in a second category the two words were closed in the DSM, but not likely to co-occur (e.g., lamp-torch). As a control condition, we added a third category with pairs that were both high in PMI and close in DSMs (e.g., lemon-orange). Mirroring the behavioral results, we observed a significant PMI effect in the N400 time window; no such effect emerged for DSM. References Church, K. W., & Hanks, P. (1990). Word association norms, mutual information, and lexicography. Computational linguistics, 16(1), 22-29. Clark, H. H. (1973). Space, time, semantics, and the child. In Cognitive development and acquisition of language (pp. 27-63). Academic Press. Kutas, M., & Federmeier, K. D. (2011). Thirty years and counting: finding meaning in the N400 component of the event-related brain potential (ERP). Annual review of psychology, 62, 621-647. Marelli, M. (2017). Word-Embeddings Italian Semantic Spaces: a semantic model for psycholinguistic research. Psihologija, 50(4), 503-520. Commentat

Neurological and Mental Disorders

Mental disorders can result from disruption of neuronal circuitry, damage to the neuronal and non-neuronal cells, altered circuitry in the different regions of the brain and any changes in the permeability of the blood brain barrier. Early identification of these impairments through investigative means could help to improve the outcome for many brain and behaviour disease states.The chapters in this book describe how these abnormalities can lead to neurological and mental diseases such as ADHD (Attention Deficit Hyperactivity Disorder), anxiety disorders, Alzheimer’s disease and personality and eating disorders. Psycho-social traumas, especially during childhood, increase the incidence of amnesia and transient global amnesia, leading to the temporary inability to create new memories.Early detection of these disorders could benefit many complex diseases such as schizophrenia and depression