Seminár z kognitívnej vedy a umelej inteligencie je (od zimného semestra 2015-2016) pokračovaním spoločného seminára z umelej inteligencie, ktorý organizovali Ústav aplikovanej informatiky FIIT STU (prof. Kvasnička) a Katedra aplikovanej informatiky FMFI UK (prof. Farkaš, a pred ním doc. Šefránek). V zimnom semestri je seminár určený hlavne pre študentov kognitívnej vedy, aby mali možnosť zorientovať sa v existujúcom výskume v našom okolí, v letnom semestri má rozšírený záber aj na umelú inteligenciu. Po celý rok sú však vítaní všetci záujemcovia, ktorí sú chcú vypočuť ponúkané prednášky.
Organizátorom seminára je prof. Igor Farkaš.
Čas a miesto konania seminára: utorok 16:30-17:45 v miestnosti I-9 (pavilón informatiky) na FMFI UK.
Long-term synaptic plasticity is widely accepted to be the major mechanism involved in learning and memory. It remains unclear, however, which particular activity rules are utilized by neurons to induce synaptic plasticity in behaving animals and what is the role of dendrites in this context. In the first part of my talk, I will present computer simulations which indicate that the interplay of STDP-BCM plasticity rules and ongoing neuronal activity is able to account for experimentally observed synaptic plasticity in the hippocampus of awake rats. In the second part of my talk, I will describe anatomically detailed models of hippocampal neurons which predict that changes in dendritic morphology are able to selectively modulate local synaptic plasticity.
Humans recognize themselves in the mirror, but children under 18 months do not, thinking they are looking at a person behind the mirror. In animals, the mirror self-recognition is present only in exceptional cases, for instance in chimpanzees, but not in cats. Can a robot recognize itself in the mirror? And what is the origin of the self-recognition ability? Using the simulator of the humanoid robot iCub, and a camera capturing the area in the front of the monitor, we created a control system for examining how the mirror self-recognition emerges from basic mechanisms. These mechanisms include the body model (proprioception), mirroring, i.e. the ability to create an analogical model as a result of vision, imitation and social modelling. We follow the approach of Scassellati and Hart (Yale University) who suppose that a robot should recognize itself in the mirror due to perfect correlation between the body movement and the image seen in the mirror.
Cerebrovascular diseases including stroke are the second most common cause of death and disability worldwide. One of the most devastating consequences of stroke is a cognitive impairment, which can significantly affect activities of daily living eventually leading to dementia. Dementia due to stroke or other cerebrovascular disease is the most common type of dementia after Alzheimer’s disease. However, even more patients after stroke have milder forms of vascular cognitive impairment which do not fulfill criteria for dementia but do diminish their quality of life. Cognitive syndrome in patients with cerebrovascular diseases is characterized by memory deficit consisting of impaired recall but relative preservation of recognition, dysexecutive syndrome, slowed information processing and mood changes. Our research also showed characteristic changes in the EEG alpha frequency band which correlate with cognitive impairment. Interestingly, vascular dementia and Alzheimer's disease share the same, well-known vascular risk factors: hypertension, diabetes, elevated cholesterol, smoking etc. These data suggest interaction between vascular changes and amyloid pathology and led some researchers to formulate vascular hypotheses of Alzheimer's disease. Controlling vascular risk factors a significant number of dementia cases can be prevented and the burden of this disease can be reduced.
Cognitive impairment is a common consequence of acute cerebrovascular accident (stroke). In the talk, we will more specifically focus on three particular aspects of cognition, namely: attention, working memory and motor skills. We implemented computerized versions of standard psychological tests (lateralized attention network test, digit span and fine-motor redrawing task) adjusted for our experimental group of elderly people after stroke. To assess the effect of stroke itself, we administered the tests to an age-matched control group of healthy senior volunteers. This research is a part of a larger cooperative project which aims to find a link between daily cognitive performance of stroke patients and the previous night sleep profiles (sleep quality). At the end of the talk, preliminary results of the main project will be briefly summarized.
Research in neuroscience over the past few decades has shed new light on glial cells which were always considered as purely passive supportive cells. New data provides evidence that astrocytes, a group of glial cells, possess important physiological functions that distinguishes them from passive cells. It is now known that astrocytes are actively involved in neuronal communication regulation and synaptic transmission. Similar to neurons, astrocytes form glial syncytium that enables them to communicate with one another over long distances using Ca2+ signals. Since this is a relatively new area of research in neuroscience, computational models (biophysical and connectionist) are still missing. In my talk I briefly introduce glial cells (mostly their physiology), focus on existing connectionist models and also present my preliminary results.
In computer vision, recent and rapid advances in convolutional deep neural networks (DNNs) have resulted in image-based computational models of object recognition which, for the first time, rival human performance. This talk will focus on practical use of such supervised models in our company for real-time detection and classification. We will also discuss some of the techniques how we achieve real-time performance and how we generate our datasets just as we will discuss some prevailing problems and unrealistic expectations.
In the talk, it will be explained why automatic model building for time-series has become attractive for energy industry and why they decided to develop an automatic model building engine TIM (Tangent Information Modeller). The talk will include mathematical challenges of automation in model building and some real-world deployment scenarios will be described where TIM was used to build large-scale forecasting systems. Information Criteria and Information Geometry topics will also be discussed, as advances in this field helped to enable automatic model building of high-quality models with excellent generalization capabilities.
We present our improved algorithm for finding the clique number of simple undirected graph based on Ostergaard's algorithm applied to functional brain networks. The clique number of a graph is a size of its maximum clique. Finding that clique is a NP-hard problem. Our algorithm implements several pruning techniques which greatly restricts depth-first search branching using the original method. The resulting algorithm works faster on arbitrary simple undirected graphs, but the best performance is on the graphs with a scale-free property. We have used this algorithm to find and analyse clique numbers of 40 functional brain networks for three groups of subjects: elderly patients suffering from Alzheimer disease, elderly people and young healthy individuals.
Global trend towards urbanization calls for new mobility concepts. The UP-Drive consortium is convinced that automated driving technology is the key component enabling more comfort and safety, reduction of congestion and more efficient use of resources. Yet, today's automated driving technology is not mature enough to handle the complexity of urban traffic. The main goal of UP-Drive is to push forward the perception, localization and reasoning abilities of autonomous vehicles. In the course of the project, we are building a prototype car systems capable of driverless operation in complex urban environments. Our focus is placed on residential areas and speeds up to 30 km/h.
I will introduce the paradigms of supervised, unsupervised and reinforcement learning in the context of artificial neural networks. We will look at a few examples of their use, also in the domain of cognitive robotics that represents a constructivist (synthetic) approach to mechanical understanding of cognitive functions. The ideas will be presented via selected tasks of motor learning, learning body schema and spatial cognition in a simulated humanoid robot. These examples will serve as motivation for potential research projects.
In this talk I will briefly introduce some of the computational models I have been working on for the past 15 years: (1) autonomous sense making / meaning construction and their formalization in terms of distinguishing criteria, (2) language acquisition - phonology, lexicon, morphology and syntax, (3) working memory.
Our research is focused on the role of intuition in (rational) decision-making. Intuition can be conceptualised as automatic processing of information. Its positive aspects are manifested when our automatic responses are based on extensive experience (intuition as expertise, intuition as somatic markers); on the other hand, it can be manifested in superficial processing (relying on the first thing that comes to our mind) or be expressed as belief in supernatural and it can lead to suboptimal decisions. Our research revolves around three main topics, which I will introduce together with our preliminary findings and future directions. 1. How irrational beliefs relate to cognitive abilities, thinking dispositions and cognitive biases. 2. How political/religious affiliation influences our reasoning about controversial topics. 3. How optimistic bias and overconfidence relate to irrationality.
In contemporary science and theory the nature of human mind has been considered as one of the most difficult and complex problems. In my talk I intend to point out selected experiments and research strategies which contribute significantly to a better understanding of the working mechanisms of states of mind (self-embodiment, self-deception etc.). From the number of recent theoretical approaches I will be concerned with the „phenomenal self-modeI“ (T. Metzinger) and novel methods of cognitive enhancement (J. Illes).
It is very challenging but a tricky research question to what extent polysomnographic recordings of nocturnal human sleep can provide information about sleep quality. It was already in 1958, when the standardized sleep-scoring manual was introduced and with some modest modifications has been used in clinical practice until now. While this scoring system mimics general dynamics of the sleep process, it is limited in its ability to provide objective measures of the sleep quality that would correlate with important factors of the humans’ daytime behavior and cognitive abilities. With the aim to overcome these limits we introduced and validated a new concept of sleep modeling based on the probabilistic sleep model. The model operates on an arbitrary number of different sleep microstates and high time resolution. In the talk I will briefly summarize our longer research effort in this area that includes topics such as healthy sleep modeling, searching for objective components for sleep quality indexing and their connection to daytime neurophysiological and cognitive performance. Then I will present our recent developments of the advanced functional data analysis approaches for sleep quality profiling of patients after stroke.
Stress initiates complex adaptive responses that affect multiple brain areas responsible for cognitive functioning. Recent research has indicated that this effect may be specifically deteriorative for cognitive flexibility, an attribute of human cognitive system that is related to innovation and insight. The lecture is divided into three parts. Firstly it summarizes recent findings related to changes in large-scale brain networks under acute stress that modulate distinct cognitive functions and, specifically, cognitive flexibility. Secondly, theoretical and methodological issues regarding plausible cognitive influences and new operational definitions of cognitive flexibility are discussed within the framework of complex network theory. Finally, we provide a brief review of transcranial direct current stimulation technique and propose its possible application for research in cognitive science and cognitive flexibility in particular.
Language impairment is a common clinical feature of neurodegenerative disease. Primary progressive aphasia (PPA) is a neurological syndrome in which language capabilities become slowly and progressively impaired, while other mental functions remain preserved. In PPA a language impairment interferes with the usage or comprehension of words and sentences. There are different clinical variants of PPA (agrammatic, logopenic and semantic variants), each with a characteristic pattern of atrophy. The underlying neuropathological diseases are heterogeneous and can include Alzheimer's disease as well as frontotemporal lobar degeneration. Because relatively simple tests of single-word and sentence processing can have substantial diagnostic utility, language testing should always be part of the clinical assessment of patients with suspected dementia. A comprehensive language-specific test should be used in assessment of language in Slovak speaking patients with dementia.
The talk will outline the processes of neural development of human central nervous system and its functional units during prenatal and postnatal life. The hierarchy of central regulatory systems and processing in relation to emotions and social cognition will be introduced. I will deal with the hormonal influence, particularly testosterone, on particular anatomical structures involved in cognition and its consequences on brain development and nervous functions resulting in communication deficits and disturbances in social behaviour. The results of our own research in healthy human individuals and in patients with autism will be discussed.
Cognitive enhancement of man using neurochips, chemical substances or genetic manipulations are today the topics of important discussions on ethics. In 2015 Chinese scientists published experiments, in which they, using a break-through novel method CRISPR/Cas9 for the first time in history manipulated in a controlled way the DNA of the human embryo, which evoked a vigorous reaction in the scientific community. Are we standing at an onset of the new revolution when the human takes his biological evolution in his own hands? Have we stepped out toward a creation of a new, posthuman biological species?