Tamas Madl

Tamas Madl
The University of Manchester · School of Computer Science

Doctor of Philosophy

About

25
Publications
9,261
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545
Citations
Citations since 2016
16 Research Items
454 Citations
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2016201720182019202020212022020406080
2016201720182019202020212022020406080
2016201720182019202020212022020406080

Publications

Publications (25)
Article
Full-text available
We propose that human cognition consists of cascading cycles of recurring brain events. Each cognitive cycle senses the current situation, interprets it with reference to ongoing goals, and then selects an internal or external action in response. While most aspects of the cognitive cycle are unconscious, each cycle also yields a momentary "ignition...
Article
Full-text available
We describe a cognitive architecture (LIDA) that affords attention, action selection and human-like learning intended for use in controlling cognitive agents that replicate human experiments as well as performing real-world tasks. LIDA combines sophisticated action selection, motivation via emotions, a centrally important attention mechanism, and m...
Article
Full-text available
Accurate spatial localization requires a mechanism that corrects for errors, which might arise from inaccurate sensory information or neuronal noise. In this paper, we propose that Hippocampal place cells might implement such an error correction mechanism by integrating different sources of information in an approximately Bayes-optimal fashion. We...
Article
Artificial intelligence (AI) deep learning protocols offer solutions to complex data processing and analysis. Increasingly these solutions are being applied in the healthcare field, most commonly in processing complex medical imaging data used for diagnosis. Current models apply AI to screening populations of patients for markers of disease and rep...
Article
Atrial fibrillation is increasingly prevalent, especially in the elderly, and challenging to detect due paroxysmal nature. Here, we propose novel computational methods based on heart beat intervals to facilitate rapid and robust discrimination between atrial fibrillation and sinus rhythm. We used low-cost Android smartphones, and recorded short, 30...
Article
Computational cognitive models of spatial memory often neglect difficulties posed by the real world, such as sensory noise, uncertainty, and high spatial complexity. On the other hand, robotics is unconcerned with understanding biological cognition. Here, we describe a computational framework for robotic architectures aiming to function in realisti...
Conference Paper
Full-text available
In several domains obtaining class annotations is expensive while at the same time unlabelled data are abundant. While most semi-supervised approaches enforce restrictive assumptions on the data distribution, recent work has managed to learn semi-supervised models in a non-restrictive regime. However, so far such approaches have only been proposed...
Conference Paper
Clinical diagnoses of age-related conditions (e.g. frailty) are based on specific signs and symptoms of the disease state. The assumption that preclinical states of these conditions display milder versions of the same clinical signs and symptoms is fundamentally flawed and lacks empirical evidence. More importantly, such assumptions preclude the de...
Article
Full-text available
Despite of the pain and limited accuracy of blood tests for early recognition of cardiovascular disease, they dominate risk screening and triage. On the other hand, heart rate variability is non-invasive and cheap, but not considered accurate enough for clinical practice. Here, we tackle heart beat interval based classification with deep learning....
Conference Paper
Heart beat interval time series contain information predictive of heart disease, but most current predictors do not provide sufficient reliability for clinical use. Using several predictors improves predictive power, but the limit is not yet known, suggesting that not all the information in interbeat interval series has been captured by previous wo...
Thesis
Existing computational cognitive models of spatial memory often neglect difficulties posed by the real world, such as sensory noise, uncertainty, and high spatial complexity. On the other hand, robotics is unconcerned with understanding biological cognition. This thesis takes an interdisciplinary approach towards developing cognitively plausible sp...
Article
Full-text available
It has been suggested that the map-like representations that support human spatial memory are fragmented into sub-maps with local reference frames, rather than being unitary and global. However, the principles underlying the structure of these 'cognitive maps' are not well understood. We propose that the structure of the representations of navigati...
Data
Methodological details. (PDF)
Article
Full-text available
Over a decade in the making and described in some seventy-five published papers, the LIDA cognitive model is comprehensive, complex, and hard to "wrap one's head around". Here we offer, in tutorial fashion, a current, relatively complete and somewhat detailed, description of the conceptual LIDA model, with pointers to more complete accounts of indi...
Article
The ability to represent and utilize spatial information relevant to their goals is vital for intelligent agents. Doing so in the real world presents significant challenges, which have so far mostly been addressed by robotics approaches neglecting cognitive plausibility; whereas existing cognitive models mostly implement spatial abilities in simpli...
Chapter
Modern tools and methods of cognitive science, such as brain imaging or computational modeling, can provide new insights for age-old philosophical questions regarding the nature of temporal experience. This chapter aims to provide an overview of functional consciousness and time perception in brains and minds (Section 8.2), and to describe a comput...
Chapter
Full-text available
Although most cognitive architectures, in general, and LIDA, in particular, are still in the early stages of development and still far from being adequate bases for implementations of human-like ethics, we think that they can contribute to the understanding, design, and implementation of constrained ethical systems for robots, and we hope that the...
Article
Full-text available
Accurate spatial localization requires a mechanism that corrects for errors, which might arise from inaccurate sensory information or neuronal noise. In this paper, we propose that Hippocampal place cells might implement such an error correction mechanism by integrating different sources of information in an approximately Bayes-optimal fashion. We...
Article
Full-text available
Spatial memory refers to the part of the memory system that encodes, stores, recognizes and recalls spatial information about the environment and the agent’s orientation within it. Such information is required to be able to navigate to goal locations, and is vitally important for any embodied agent, or model thereof, for reaching goals in a spatial...
Conference Paper
Full-text available
Human spatial representations are known to be remarkably robust and efficient, and to be structured hierarchically. In this paper, we describe a biologically inspired computational model of spatial working memory attempting to account for these properties, based on the LIDA cognitive architecture. We also present preliminary results regarding a virt...
Conference Paper
Full-text available
The attentional blink (AB) refers to the impairment in consciously perceiving the second of two targets presented in close temporal proximity (200 – 500ms) in a rapid serial visual presentation paradigm. The present paper is a preliminary report describing a conceptual and partially computational model of the AB based on the LIDA (Learning Intellig...

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Hi David et al, I'm delighted that others are interested. When I got started thinking about the scientific evidence wrt consciousness, it was (a) taboo, and (b) interpreted in very specific ways. For example, a common euphemism was "perception" _ because that was safe. But when you compare cs vs. ucs perception (as in backward masking) you get visual cortex activation with lower amplitude and spread, as shown by Dehaene and colleagues. That tell us something new, and I believe it replicates for audition. (Systematic replications should be much more common). Another problem was circular explanation. "Conscious access" was called "awareness" or "attention to" something. But that explains nothing UNLESS you have an independent source of evidence to break the circularity. Other confusions were rife. The conscious (waking) STATE was confused with consciousness OF something. Visual imagery was not fully recognized until Steve Kosslyn, and so on. Attention was used interchangeably with consciousness. All that has cleared up now, either explicitly, or implicitly, by usage. For example, my impression is that attention is used for voluntary control of access to some conscious content. As in voluntary head movements, but not for spontaneous, unconsciously directed eye movements (most fast eye movements are that). As long as these practical usages are clear, they are good enough to avoid confusion. Recent work coming from animal and human electrophysiogy is fabulous. Buszaki's book is important reading. Invasive e-physiology has 1000x the S/N ratio as scalp recording. Both deep sleep and waking look strikingly different at that resolution. Animal researchers have known that for years, but human e-phys researchers were held back by the ethical constraints of working with humans. Penfield was right. Other methodologies are reaching that kind of spatiotemporal resolution, and have their own pros and cons, of course. Our 2013 Frontiers overview still holds water, mostly. My Scholarpedia article is still mostly up to date. But the frontier is moving fast. It's very exciting. Theorists need to integrate the wealth of evidence, clarify ambiguous usages and confusions, and so on. There are still many of them. I believe our theory writing needs much improvement, with the emphasis on INDUCTIVE thinking. (Some writers seem to think this is a form of math, but that's indefensible empirically). A recent article confused the brainstem nuclei involved with the STATE of consciousness with the mostly cortical regions that support CONTENTS of consciousness, like the ventral visual stream. There is appropriate debate about the region of visual integration (MTL or PFC? or both?). I guess I'm a "corticocentrist," but that does NOT rule out other regions, especially given the long evolutionary history of csns -- at least 200 million years for neocortex. Walter Freeman, our late friend, convinced me that paleocortex (incl hippocampus) has to be involved with gustatory-olfactory consciousness. The work on the anterior insula strongly implicates interoceptive consciousness, as in feelings of nausea. Generalization between species is now much more convincing because we have the human and macaque, plus rodent genome. The avian pallium is now considered to be much like cortex in mammals. So there is a TON of work to do. Each question deserves discussion and debate, based on the best evidence available. I HOPE YOU JOIN !!!!