Essential constraints for detecting deep sources in EEG - application to orthostatic tremor

The hypotheses that orthostatic tremor is generated by a central oscillator is been tested in this paper. In order to understand the mechanisms of the central network its sources need to be found. The cortical sources of both the basic and first “harmonic” frequency of orthostatic tremor are addressed in this paper. The Dynamic Imaging of Coherent Sources (DICS) was used to find the coherent sources in the brain. The three essential constraints for detecting deep sources in the brain using EEG data were tested by three model simulations. The optimal number of electrodes, length of the data and the signal to noise ratio required for error-free localization was tested. In all the orthostatic tremor patients the corticomuscular coherence was also present in the basic and the first harmonic frequency of the tremor. The basic frequency constituted a network of primary leg area, supplementary motor area, primary motor cortex, two pre-motor sources, diencephalon and cerebellum. The first harmonic frequency was in the region of primary leg area, supplementary motor area, primary motor cortex, diencephalon and cerebellum. Thus the generation of these two oscillations involves the same network structure and indicates the oscillation at double the tremor frequency is a harmonic of the basic tremor frequency. The orthostatic tremor could have the central oscillator in the brain

Neuronal networks in epileptic encephalopathies with CSWC [Abstract]

Aim: Continues spikes and waves during slow sleep (CSWS) is an agerelated epileptic encephalopathy characterized by occurrence of diffuse,continues spike and wave discharges during NREM sleep, seizures andpsychomotor impairment. The aim of our study was to investigate theneuronal networks underling background oscillations of CSWC using thesource analysis method Dynamic Imaging of Coherent Sources (DICS)and renormalized partial directed coherence (RPDC). Methods: In order to investigate underlying network and effective con-nectivity within the detected network, a DICS analyses and renormalizedpartial directed coherence (RPDC) methods were applied. The baselinesleep EEG recordings and follow up sleep EEG recordings from 12Patients with CSWS were used for the analyses. Results and Conclusions: The results revealed that independent of aeti-ology and severely of the disease CSWS EEG pattern is associated withthe complex network of coherent sources in medial prefrontal cortex,somatosensory association cortex/posterior cingulate cortex, medial pre-frontal cortex, middle temporal gyrus/parahippocampal gyrus/insularcortex, Thalamus and cerebellum. The described network underlyingCSWS was found on both group and individual levels and was no longerobserved in follow up EEGs of the patients with normalized sleep EEGs,suggesting the specificity of the network for the CSWS pattern. Furtheron, for the first time, using RPDC analyses we investigated the hierarchywithin the described network, which showed that Thalamus, togetherwith mesial temporal and parietal regions may be seen as a central hub ofthe underlying network. The involvement of this thalamocortical net-work, which was no longer observed in normalized EEGs, and a furtherpropagation towards the frontal region may interfere with restructuringof cognitive networks in the sensitive phase of development

The central oscillatory network of essential tremor

The responsible pathological mechanisms of essential tremor are not yet clear. In order to understand the mechanisms of the central network its sources need to be found. The cortical sources of both the basic and first “harmonic” frequency of essential tremor are addressed in this paper. The power and coherence were estimated using the multitaper method for EEG and EMG data from 6 essential tremor patients. The Dynamic Imaging of Coherent Sources (DICS) was used to find the coherent sources in the brain. Before hand this method was validated for the application of finding multiple sources for the same oscillation in the brain by using two model simulations which indicated the accuracy of the method. In all the essential tremor patients the corticomuscular coherence was also present in the basic and the first harmonic frequency of the tremor. The source for the basic frequency and the first harmonic frequency was in the region of primary sensory motor cortex, prefrontal and in the diencephalon on the contralateral side for all the patients. Thus the generation of these two oscillations involves the same cortical areas and indicates the oscillation at double the tremor frequency is a harmonic of the basic tremor frequency

The evolution of modular artificial neural networks.

This thesis describes a novel approach to the evolution of Modular Artificial Neural Networks. Standard Evolutionary Algorithms, used in this application include: Genetic Algorithms, Evolutionary Strategies, Evolutionary Programming and Genetic Programming; however, these often fail in the evolution of complex systems, particularly when such systems involve multi-domain sensory information which interacts in complex ways with system outputs. The aim in this work is to produce an evolutionary method that allows the structure of the network to evolve from simple to complex as it interacts with a dynamic environment. This new algorithm is therefore based on Incremental Evolution. A simulated model of a legged robot was used as a test-bed for the approach. The algorithm starts with a simple robotic body plan. This then grows incrementally in complexity along with its controlling neural network and the environment it reacts with. The network grows by adding modules to its structure - so the technique may also be termed a Growth Algorithm. Experiments are presented showing the successful evolution of multi-legged gaits and a simple vision system. These are then integrated together to form a complete robotic system. The possibility of the evolution of complex systems is one advantage of the algorithm and it is argued that it represents a possible path towards more advanced artificial intelligence. Applications in Electronics, Computer Science, Mechanical Engineering and Aerospace are also discussed

The Myth of Habituation in the Akananuru

The society of the Sangam age is an excellent cultural base. Customary practices represent the way of life of the Tamils two thousand years ago. The special customs and traditions found in society are called "cultures." All our ancient Tamil pieces of literature extol the cultural aspects of our forefathers. Akananuru is the repository that contains all the life, history, beliefs, and customs of the people of the Sangam age. Akananuru is an expression of myth. It is known that there were types of marriage where the man and the woman were married without the consent of the parents and with the consent of the parents in the marriage system. It is special that they got married on a good day. Young boys built sand houses and played ball games. They cheered and enjoyed playing Kuravai Koothu (an entertaining dance of females) and Thunangai Koothu (a religious dance of females). Tunangai Koothu was unique in that it was exclusively for women. Trades were divided based on the land. Apart from these, it can be known that there were many castes such as potters, carpenters, and paraiyars. Trading was one of our customs. It can be seen that they excelled not only in domestic trade but also in foreign trade