Deep learning-based i-EEG classification with convolutional neural networks for drug-target interaction prediction

Drug-target interaction (DTI) prediction has become a foundational task in drug repositioning, polypharmacology, drug discovery, as well as drug resistance and side-effect prediction. DTI identification using machine learning is gaining popularity in these research areas. Through the years, numerous deep learning methods have been proposed for DTI prediction. Nevertheless, prediction accuracy and efficiency remain key challenges. Pharmaco-electroencephalogram (pharmaco-EEG) is considered valuable in the development of central nervous system-active drugs. Quantitative EEG analysis demonstrates high reliability in studying the effects of drugs on the brain. Earlier preclinical pharmaco-EEG studies showed that different types of drugs can be classified according to their mechanism of action on neural activity. Here, we propose a convolutional neural network for EEG-mediated DTI prediction. This new approach can explain the mechanisms underlying complicated drug actions, as it allows the identification of similarities in the mechanisms of action and effects of psychotropic drugs

37th Rocky Mountain Conference on Analytical Chemistry

Final program, abstracts, and information about the 37th annual meeting of the Rocky Mountain Conference on Analytical Chemistry, co-sponsored by the Colorado Section of the American Chemical Society and the Rocky Mountain Section of the Society for Applied Spectroscopy. Held in Denver, Colorado, July 23-27, 1995

36th Rocky Mountain Conference on Analytical Chemistry

Program, abstracts, and information about the 36th annual meeting of the Rocky Mountain Conference on Analytical Chemistry, co-sponsored by the Colorado Section of the American Chemical Society and the Rocky Mountain Section of the Society for Applied Spectroscopy. Held in Denver, Colorado, July 31 - August 5, 1994

Magnetoencephalography

This is a practical book on MEG that covers a wide range of topics. The book begins with a series of reviews on the use of MEG for clinical applications, the study of cognitive functions in various diseases, and one chapter focusing specifically on studies of memory with MEG. There are sections with chapters that describe source localization issues, the use of beamformers and dipole source methods, as well as phase-based analyses, and a step-by-step guide to using dipoles for epilepsy spike analyses. The book ends with a section describing new innovations in MEG systems, namely an on-line real-time MEG data acquisition system, novel applications for MEG research, and a proposal for a helium re-circulation system. With such breadth of topics, there will be a chapter that is of interest to every MEG researcher or clinician

Neural correlates of auditory perceptual organization measured with direct cortical recordings in humans

Thesis (Ph. D.)--Harvard-MIT Division of Health Sciences and Technology, September 2011."August, 2011." Vita. Cataloged from PDF version of thesis.Includes bibliographical references.One of the primary functions of the human auditory system is to separate the complex mixture of sound arriving at the ears into neural representations of individual sound sources. This function is thought to be crucial for survival and communication in noisy settings, and allows listeners to selectively and dynamically attend to a sound source of interest while suppressing irrelevant information. How the brain works to perceptually organize the acoustic environment remains unclear despite the multitude of recent studies utilizing microelectrode recordings in experimental animals or non-invasive human neuroimaging. In particular, the role that brain areas outside the auditory cortex might play is, comparatively, vastly understudied. The experiments described in this thesis combined classic behavioral paradigms with electrical recordings made directly from the cortical surface of neurosurgical patients undergoing clinically-indicated invasive monitoring for localization of epileptogenic foci. By sampling from widespread brain areas with high temporal resolution while participants simultaneously engaged in streaming and jittered multi-tone masking paradigms, the present experiments sought to overcome limitations inherent in previous work, namely sampling extent, resolution in time and space, and direct knowledge of the perceptual experience of the listener. In experiment 1, participants listened to sequences of tones alternating in frequency (i.e., ABA-) and indicated whether they perceived the tones as grouped ("1 stream") or segregated ("2 streams"). As has been reported in neurologically-normal listeners since the 1950s, patients heard the sequences as grouped when the frequency separation between the A and B tones was small and segregated when it was large. Evoked potentials from widespread brain areas showed amplitude correlations with frequency separation but surprisingly did not differ based solely on perceptual organization in the absence of changes in the stimuli. In experiment 2, participants listened to sequences of jittered multi-tone masking stimuli on which a regularly-repeating target stream of tones was sometimes superimposed and indicated when they heard the target stream. Target detectability, as indexed behaviorally, increased throughout the course of each sequence. Evoked potentials and high-gamma activity differed strongly based on the listener's subjective perception of the target tones. These results extend and constrain theories of how the brain subserves auditory perceptual organization and suggests several new avenues of research for understanding the neural mechanisms underlying this critical function.by Andrew R. Dykstra.Ph.D