1,720,963 research outputs found
Consciousness as Emergent Property of the Interaction between Cognitive Levels
Full text linkThe search for possible neural correlates of consciousness is a particularly complex issue. Nonetheless it appears ascertained that consciousness is the result of the simultaneous interaction between several brain areas. At a cognitive level, consciousness can be represented as an emergent structure typical of superior animal species that manages and coordinates different cognitive levels. However, the subjective characteristic of the conscious experience does not seem to be fully explained either by neural correlates or by a cognitive interpretation. The paper presents a formal solution of the so-called “hard problem” that takes as its starting point the important works of D. Hofstadter, G. Spencer-Brown and F. Varela
Artificial Neural Network Codifies Sensory and Cognitive Events Identifying Chaotic Attractors in EEG Signals
Full text linkIn past researches our group experimented a method to analyze multiple neural signals by means of a novel self-organizing Artificial Neural Network, highlighting the attractors in which the corresponding dynamic system is evolving. If the attractors show to be chaotic, this means that the neural signals are individually self-organized and, analyzing more signals together, that there is a form of coherence between signals. The ANN can also identify different attractors with a unique code. The ANN allows to attribute the same codes to similar but not identical brain events, reaching the necessary range of flexibility. In the present work the method has been tested on signals from a 14 electrodes EEG system connected to immersive glasses that allow a realistic audiovisual experience. A software procedure synchronizes the acquired signals with various sensory experiences presented in a video. Aim of the research is to characterize sensory and emotional stimuli. The analysis lead to positive results, showing that the binary codes corresponding to similar cognitive and perceptive stimuli are similar, and well differentiated for the codes corresponding to different stimuli
Coding mental states from EEG signals and evaluating their integrated information content : a computational intelligence approach
No full textThe paper presents a method to identify and code mental states from EEG signals, performing their dynamical analysis by means of an Artificial Neural Network. The method has been tested on signals from a 14 electrodes EEG system connected to immersive glasses that allow a realistic audiovisual experience. A software procedure synchronizes the acquired signals with the sensory experiences presented in a video. A suitable Artificial Neural Network detects and codifies the chaotic attractors signals related to the sensory and cognitive events. The analysis shows that the binary codes corresponding to similar cognitive and perceptive stimuli are similar, and well differentiated from the codes corresponding to different stimuli. The dynamical attractors corresponding to each mental state are submitted to a procedure that evaluates their
Integrated Information content in the qualia space
Learning in human neural networks on microelectrode arrays
Full text linkThis paper describes experiments involving the growth of human neural networks of stem cells on a MEA (microelectrode array) support.
The microelectrode arrays (MEAs) are constituted by a glass support in which a set of tungsten electrodes are inserted.
The artificial neural network (ANN) paradigm was used by stimulating the neurons in parallel with digital patterns distributed on eight channels, then by analyzing a parallel multichannel output. In particular, the microelectrodes were connected following two different architectures, one inspired by the Kohonen's SOM, the other by the Hopfield network.
The output signals have been analyzed in order to evaluate the possibility of organized reactions by the natural neurons.f
The results show that the network of human neurons reacts selectively to the subministered digital signals, i.e., it produces similar output signals referred to identical or similar patterns, and clearly differentiates the outputs coming from different stimulations.
Analyses performed with a special artificial neural network called ITSOM show the possibility to codify the neural responses to different patterns, thus to interpret the signals coming from the network of biological neurons, assigning a code to each output. It is straightforward to verify that identical codes are generated by the neural reactions to similar patterns.
Further experiments are to be designed that improve the hybrid neural networks’ capabilities and to test the possibility of utilizing the organized answers of the neurons in several ways
The binding problem: evidence of chaotic attractors in cortical fast oscillations : tested by an artificial neural network
No full textPetri Nets as an EffectiveTool to Structure Web Multimedia Knowledge : the Case for the Giovanni Degli Antoni’s Scientific and Documentary Work
No full textThe complexity of multimedia knowledge requires new methods of representation. This work addresses the problem by proposing the use of Petri nets, a powerful knowledge representation method suitable to manage complex concurrent events. An interactive interface allows the exploration of both the knowledge structure and the multimedia content. We have developed a web application that collects and systematizes Giovanni Degli Antoni's scientific and documentary work, mainly composed of web multimedia contributions, underlining his long-life research in the field of hypermedia world and Petri nets theory and applications
Composition of feature extraction methods shows interesting performances in discriminating wakefulness and NREM sleep
No full textIntracranial electroencephalography (iEEG) is an invasive technique used to explore the cortical activity of the brain.
In this letter, we focused on features of iEEG signals recorded during wakefulness and non-rapid eye movement (NREM) sleep in order to find differences between the two states, respectively. We preliminary screened the data using standard deviation analysis (STD). Then, we compared and combined STD values with coefficients from wavelet decomposition (Daubechies mother wavelet of order 4). Resulting parameters were classified using an artificial neural network. STD analysis underlined two brain areas [superior temporal sulcus (STS) and intraparietal-sulcus and parietal transverse (IPS)] with different electrical activity in the two states.STDvalues of STS and IPS channels were highly correlated in time;therefore, only STSwas then used further in the features extraction analysis. Approximation and detail coefficients from Daubechies decomposition were used alone or in combination with the STD value. The overall accuracy of the pattern recognition was higher (98.57%), when features from different methods were used in combination. Our test was able to automatically recognize wake or NREM sleep status with very good discrimination performances using one single iEEG electrode
ICT-based Participatory Co-Creation of Urban Sustainability
Full text linkIn the last decade Information and communication technologies (ICT) have become an important tool for socialization. More and more people build and maintain relationships through various social media and increasingly this influences the way they organize their daily lives and how they use the city and its spaces. However, the quality of public open spaces remains fundamental for the development of the cultural identity of a community, as they are important gathering points in the urban fabric and offer occasion for interactions and collaborations between generations and different ethnic diversities. People of all ages still need contact with nature and with other people, in order to develop different life skills, values, attitudes to health, satisfaction with their lives and responsibility towards the environment.
ICTs allow the development of strategies and tools to increase the quality of public open spaces, positively influencing participatory co-creation and the effects of social cohesion.
New ways of cooperative co-creation must be considered, in particular by using ICT to facilitate community interaction and engagement for the integration of diversity, and identifying social needs in open public spaces, aiming at the development of vibrant and accessible urban communities.
ICT gives also the opportunity to the urban communities to improve sustainability.
This paper presents best practices and new ICT solutions for enjoyable, inclusive, participatory, sustainable urban spaces
The university of Milan contribution to the c3places project
No full textThe chapter describes the idea developed by the UNIMI team: a vibrant new way to create a community that could really communicate and help and grow not only virtually but also by means of technology.
Urban open space can easily become center of shared services and cultural events and opportunities and knowledge
Minimally Invasive and Low-Cost BCI System Interprets the Will of the Subject by means of an Artificial Neural Network
Full text linkThe advances in BCI technology are evident and continuous, but the problems of portability and invasiveness of the devices that the subject must wear still remain to be solved. The paper presents a light, low-cost and non-invasive system that allows the disabled subject unable to communicate to interact with the environment and other people. Signals are acquired from a sensor applied to the finger, then are processed by an Artificial Neural Network. This allows the tetraplegic and anarthric subject to express their will and make choices through a graphic interface. The system can be greatly improved both in the quality and quantity of different signals acquired and in their simultaneous processing to discriminate different mental states, so as to improve communication, access to computer and home automation functions
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