Signatures of Higher Functions of Brain Dynamics in Electroencephalogram: A Nonlinear Analysis

The brain with its highly complex structure made up of simple units,imterconnected information pathways and specialized functions has always been an object of mystery and sceintific fascination for physiologists,neuroscientists and lately to mathematicians and physicists. The stream of biophysicists are engaged in building the bridge between the biological and physical sciences guided by a conviction that natural scenarios that appear extraordinarily complex may be tackled by application of principles from the realm of physical sciences. In a similar vein, this report aims to describe how nerve cells execute transmission of signals ,how these are put together and how out of this integration higher functions emerge and get reflected in the electrical signals that are produced in the brain.Viewing the E E G Signal through the looking glass of nonlinear theory, the dynamics of the underlying complex system-the brain ,is inferred and significant implications of the findings are explored.

Level Identification of Brain MR Images using Histogram of a LBP variant

Axial brain slices containing similar anatomical structures are retrieved using features derived from the histogram of Local binary pattern (LBP). A rotation invariant description of texture in terms of texture patterns and their strength is obtained with the incorporation of local variance to the LBP, called Modified LBP (MOD-LBP). In this paper, we compare Histogram based Features of LBP (HF/LBP), against Histogram based Features of MOD-LBP (HF/MOD-LBP) in retrieving similar axial brain images. We show that replacing local histogram with a local distance transform based similarity metric further improves the performance of MOD-LBP based image retrieval

Content Based Image Retrieval of Brain MR Images across Different Classes

Magnetic Resonance Imaging play a vital role in the decision-diagnosis process of brain MR images. For an accurate diagnosis of brain related problems, the experts mostly compares both T1 and T2 weighted images as the information presented in these two images are complementary. In this paper, rotational and translational invariant form of Local binary Pattern (LBP) with additional gray scale information is used to retrieve similar slices of T1 weighted images from T2 weighted images or vice versa. The incorporation of additional gray scale information on LBP can extract more local texture information. The accuracy of retrieval can be improved by extracting moment features of LBP and reweighting the features based on users’ feedback. Here retrieval is done in a single subject scenario where similar images of a particular subject at a particular level are retrieved, and multiple subjects scenario where relevant images at a particular level across the subjects are retrieved

Brain Glutamate Dehydrogenase Changes In Streptozotocin Diabetic Rats As A Function Of Age

Kinetic parameters of brain glutamate dehydrogenase (GDH) were compared in the brain stem, cerebellum and cerebral cortex of three weeks and one year old streptozotocin (STZ) induced four day diabetic rats with respective controls. A single intrafemoral dose of STZ (60mg/Kg body weight) was administered to induce diabetes in both age groups. After four days the blood glucose levels showed a significant increase in the diabetic animals of both age groups compared with the respective controls. The increase in blood glucose was significant in one year old compared to the three weeks old diabetic rats. The Vmm of the enzyme was decreased in all the brain regions studied, of the three weeks old diabetic rats without any significant change in the Km. In the adult the Vmax of GDH was increased in cerebellum and brain stem but was unchanged in the cerebral cortex. The K. was unchanged in cerebellum and cerebral cortex but was increased in the brain stem. These results suggest there may be an important regulatory role of the glutamate pathway in brain neural network disturbances and neuronal degeneration in diabetes as a function of age.

Enhancement of [m-methoxy 3H]MDL100907 binding to 5HT 2A receptors in cerebral cortex and brain stem of streptozotocin induced diabetic rats

5-Hydroxytryptamine2A (5-HT2A) receptor kinetics was studied in cerebral cortex and brain stem of streptozotocin (STZ) induced diabetic rats. Scatchard analysis with [3H] (±) 2,3dimethoxyphenyl-l-[2-(4-piperidine)-methanol] ([3H]MDL100907) in cerebral cortex showed no significant change in maximal binding (Bmax) in diabetic rats compared to controls. Dissociation constant (K) of diabetic rats showed a significant decrease (p < 0.05) in cerebral cortex, which was reversed to normal by insulin treatment. Competition studies of [3H]MDL100907 binding in cerebral cortex with ketanserin showed the appearance of an additional low affinity site for 5-HT2A receptors in diabetic state, which was reversed to control pattern by insulin treatment. In brain stem, scatchard analysis showed a significant increase (p < 0.05) in Bmax accompanied by a significant increase (p < 0.05) in Kd. Competition analysis in brain stem also showed a shift in affinity towards a low affinity State for 5-HT2A receptors. All these parameters were reversed to control level by insulin treatment. These results show that in cerebral cortex there is an increase in affinity of 5-HT2A receptors without any change in its number and in the case of brain stem there is an increase in number of 5HT2A receptors accompanied by a decrease in its affinity during diabetes. Thus, from the results we suggest that the increase in affinity of 5-HT2A receptors in cerebral cortex and upregulation of 5-HT2A receptors in brain stem may lead to altered neuronal function in diabetes.

“Adrenergic receptors and monoamines in the brain and pancreatic islets of streptozotoein diabetic rats: Role in insulin secretion as a function of age”

I) To study the changes in the content of brain rrrorroamirres in streptozotocirr-irrduced tliabetes as a lirnction of age and to lirrd the role oliadrenal lrornroncs in diabetic state. 2) To assess the adrenergic receptor function in the brain stem ofstreptozotocin-induced diabetic rats ofdillerent ages. 3) To study the changes in the basal levels of second messenger cAMP in the brain stenr ofstreptozotocin-induced diabetic rats as a function of age. 4) To study the changes occurring in the content ofmorroamines and their metabolites in whole pancreas and isolated pancreatic islets of streptozotocin-diabetic rats as a function ofage and the effect of adrenal hormones. 5) To study the adrenergic receptors and basal levels of cAMP in isolated pancreatic islets in young and old streptozotoein-diabetic rats. 6) The in virro study of CAMP content in pancreatic islets of young and old rats and its ellect on glucose induced insulin secretion. 7) 'lhe in vitro study on the involvement of dopamine and corticosteroids in glucose induced insulin secretion in pancreatic islets as a function of age.

Content-Based Image Retrieval of Axial Brain Slices Using a Novel LBP with a Ternary Encoding

Retrieval of similar anatomical structures of brain MR images across patients would help the expert in diagnosis of diseases. In this paper, modified local binary pattern with ternary encoding called modified local ternary pattern (MOD-LTP) is introduced, which is more discriminant and less sensitive to noise in near-uniform regions, to locate slices belonging to the same level from the brain MR image database. The ternary encoding depends on a threshold, which is a user-specified one or calculated locally, based on the variance of the pixel intensities in each window. The variancebased local threshold makes the MOD-LTP more robust to noise and global illumination changes. The retrieval performance is shown to improve by taking region-based moment features of MODLTP and iteratively reweighting the moment features of MOD-LTP based on the user’s feedback. The average rank obtained using iterated and weighted moment features of MOD-LTP with a local variance-based threshold, is one to two times better than rotational invariant LBP (Unay, D., Ekin, A. and Jasinschi, R.S. (2010) Local structure-based region-of-interest retrieval in brain MR images. IEEE Trans. Inf. Technol. Biomed., 14, 897–903.) in retrieving the first 10 relevant images

Decreased (x1-Adrenergic Receptor Binding in the Cerebral Cortex and Brain Stem during Pancreatic Regeneration in Rats

purpose of this study was to investigate the role of brain al-adrenergic receptor binding in the rat model of pancreatic regeneration using 60-70% pancre:dectorny. The a, -adrenergic receptors kinetics was studied in the cerebral cor:cx and brain stem of sham operated . 72 It pan- crea(ectoinised and 7 days pancreatectomised rats. Scar chard analysis with I `I I lprazocin in cerebral cartes and brain stein showed a significant decrease (/' < 0.01). (P < 0.05) in maximal binding ( 1),,,,,) with it significant decrease (P < 0.001 ), ( P < 0.01) in the K,,in 72 It pancreatecto- raised rats compared with sham , respectively . Competition analysis in cerebral cortex and brain stem showed it shift in affinity during pancreatic regeneration . The sympathetic activity was decreased as indicated by the significantly de- increased norepinephrine level in the plasma (P < 0.001), cerebral cortex (P < 0.01) and brain stem (P < 0.001) of 72 h pancreatectomised rats compared to sham . Thus, from our results it is suggested that the central a, -adrenergic receptors have a functional role in the pancreatic regenera- Lion mediated through the sympathetic pathway.

Significance of Time Scales in Nonlinear Dynamical Analysis of Electroencephalogram Signals

We propose to show in this paper, that the time series obtained from biological systems such as human brain are invariably nonstationary because of different time scales involved in the dynamical process. This makes the invariant parameters time dependent. We made a global analysis of the EEG data obtained from the eight locations on the skull space and studied simultaneously the dynamical characteristics from various parts of the brain. We have proved that the dynamical parameters are sensitive to the time scales and hence in the study of brain one must identify all relevant time scales involved in the process to get an insight in the working of brain.

Studies on the toxic effects of somepesticides on the fish etroplus maculatus

The present study involved investigation of the lethal and sublethal effects of three pesticides individually. The pesticides are the commercial formulations of DDT (organochlorine).Dime— cron (organophosphate) and Gramoxone (paraquat dichloride).Aspects like individual toxicity, modulations in the activities of some selected enzymes, consequent to exposure to sub lethal levels of pesticides, sub lethal effects onperipheral haematology and alterations caused on the tissue architecture of brain, gills and liver, have been documented. Attempts have been made to analyse the impact of pesticides, added at realistic Levels to the experimental media, on the life and activity of Etroplus maculatus

Spectral clustering independent component analysis for tissue classification from brain MRI

A spectral angle based feature extraction method, Spectral Clustering Independent Component Analysis (SC-ICA), is proposed in this work to improve the brain tissue classification from Magnetic Resonance Images (MRI). SC-ICA provides equal priority to global and local features; thereby it tries to resolve the inefficiency of conventional approaches in abnormal tissue extraction. First, input multispectral MRI is divided into different clusters by a spectral distance based clustering. Then, Independent Component Analysis (ICA) is applied on the clustered data, in conjunction with Support Vector Machines (SVM) for brain tissue analysis. Normal and abnormal datasets, consisting of real and synthetic T1-weighted, T2-weighted and proton density/fluid-attenuated inversion recovery images, were used to evaluate the performance of the new method. Comparative analysis with ICA based SVM and other conventional classifiers established the stability and efficiency of SC-ICA based classification, especially in reproduction of small abnormalities. Clinical abnormal case analysis demonstrated it through the highest Tanimoto Index/accuracy values, 0.75/98.8%, observed against ICA based SVM results, 0.17/96.1%, for reproduced lesions. Experimental results recommend the proposed method as a promising approach in clinical and pathological studies of brain diseases