Steven L. Bressler - US grants

9511804 Steven Bressler The aim of this research project is to understand how different parts of the brain work together to allow us to move based on what we see. These scientists are designing sophisticated computer analysis techniques to measure properties of brain signals that occur when the brain must interpret visual patterns and use the information to make a movement. In previous research by these investigators, brain waves from the visual and motor parts of the cerebral cortex were found to briefly become aligned when the brain was deciding how to respond to a visual pattern, suggesting that the alignment od wavelike signals in the cortex is important for brain function. The objectives of this project are: (1) to observe how the normal brain processes visual input signals and transforms them into motor command signals, and (2) to advance our general understanding of similar large-scale integration problems which arise in many engineering applications.

PI: Steve Bressler Visuomotor Control by Large-Scale Distributed Cortical Networks The aim of this research project is to understand how different parts of the brain work together to allow us to move based on what we see. These scientists are designing sophisticated computer analysis techniques to measure properties of brain signals that occur when the brain must interpret visual patterns and use the information to make a movement. Previous results from this project showed that brain waves from many parts of the cerebral cortex, including but not limited to visual and motor parts, briefly become aligned when the brain is deciding how to respond to a visual pattern. This suggests that the alignment of wavelike signals from many parts of the cortex is important for brain function. The objectives of this project are: (1) to observe how the normal brain processes visual input signals and transforms them into motor command signals, and (2) to advance our general understanding of similar large- scale integration problems which arise in many engineering applications.

DESCRIPTION (Adapted from applicant's abstract): Visuomotor integration depends on a remarkable coherence among a number of interrelated subprocesses such as pattern recognition, pattern discrimination, decision to move, and guidance of movement. The brain is able to integrate these elementary cognitive processes by coordinating the activities of diverse neural structures in the face of continuously varying processing demands. The question of how this coordination operates is central to understanding the neural basis of visuomotor function. This proposal aims to develop new analytical tools to investigate the coordinated activity of distributed neuronal ensembles in the cerebral cortex of humans and non-human primates performing simple visuomotor tasks. It is motivated by recent theoretical developments (Bressler 1994, 1995, 1996, and 1997) predicting a general cortical mechanism allowing the flexible large-scale functional coordination of interacting neuronal ensembles. Hypotheses concerning this mechanism will be tested by analysis of field potential data recorded at NIMH from macaque monkeys performing a visuomotor pattern recognition task. The challenge is to develop and test new analytic approaches that characterize the multiple, complex interactions of large-scale distributed cortical networks. Earlier analysis of a small portion of this NIMH data set, reported in Nature in 1993, revealed shifting patterns of multi-site cortical synchronization during visuomotor processing, and implicated synchronization in the formation of functional relations within and between cortical areas. Standard pairwise techniques were employed to measure synchronization between field potential signals. Here, novel methods of time-series analysis are proposed that go beyond the simple detection of network interactions. Advances in signal processing technology will be utilized to also derive multi-site interaction patterns, to analyze the dependencies of functional relations on particular groups of neurons, and to measure the flow of information between cortical regions. This collaborative project will draw on the complementary strengths of Drs. Bressler and Ding. Dr. Bressler brings to the project over 15 years of experience in cognitive neuroscience, with expertise in the recording and analysis of neuroelectric data from humans to animals. He will provide theoretical oversight and the application of analytic tools to the field potential data set. Dr. Ding, although relatively new to cognitive neuroscience, has over 10 years of experience in linear and nonlinear dynamical systems analysis. He will provide the development of new analytical methods from a comprehensive dynamical systems perspective. This work is expected to (1) produce new insights into the dynamics of cortical information flow in visual perception and motor performance, (2) make available new digital signal processing tools for the investigation of large scale neural systems underlying other cognitive functions and, (3) provide a fresh perspective on the design of complex architectures for the execution of cognitive tasks by artificial neural network systems.

DESCRIPTION (Adapted from applicant's abstract): Visuomotor integration depends on a remarkable coherence among a number of interrelated subprocesses such as pattern recognition, pattern discrimination, decision to move, and guidance of movement. The brain is able to integrate these elementary cognitive processes by coordinating the activities of diverse neural structures in the face of continuously varying processing demands. The question of how this coordination operates is central to understanding the neural basis of visuomotor function. This proposal aims to develop new analytical tools to investigate the coordinated activity of distributed neuronal ensembles in the cerebral cortex of humans and non-human primates performing simple visuomotor tasks. It is motivated by recent theoretical developments (Bressler 1994, 1995, 1996, and 1997) predicting a general cortical mechanism allowing the flexible large-scale functional coordination of interacting neuronal ensembles. Hypotheses concerning this mechanism will be tested by analysis of field potential data recorded at NIMH from macaque monkeys performing a visuomotor pattern recognition task. The challenge is to develop and test new analytic approaches that characterize the multiple, complex interactions of large-scale distributed cortical networks. Earlier analysis of a small portion of this NIMH data set, reported in Nature in 1993, revealed shifting patterns of multi-site cortical synchronization during visuomotor processing, and implicated synchronization in the formation of functional relations within and between cortical areas. Standard pairwise techniques were employed to measure synchronization between field potential signals. Here, novel methods of time-series analysis are proposed that go beyond the simple detection of network interactions. Advances in signal processing technology will be utilized to also derive multi-site interaction patterns, to analyze the dependencies of functional relations on particular groups of neurons, and to measure the flow of information between cortical regions. This collaborative project will draw on the complementary strengths of Drs. Bressler and Ding. Dr. Bressler brings to the project over 15 years of experience in cognitive neuroscience, with expertise in the recording and analysis of neuroelectric data from humans to animals. He will provide theoretical oversight and the application of analytic tools to the field potential data set. Dr. Ding, although relatively new to cognitive neuroscience, has over 10 years of experience in linear and nonlinear dynamical systems analysis. He will provide the development of new analytical methods from a comprehensive dynamical systems perspective. This work is expected to (1) produce new insights into the dynamics of cortical information flow in visual perception and motor performance, (2) make available new digital signal processing tools for the investigation of large scale neural systems underlying other cognitive functions and, (3) provide a fresh perspective on the design of complex architectures for the execution of cognitive tasks by artificial neural network systems.

Visual processing in the mammalian brain is not done simply with several parallel channels leading to higher areas. We now know that visual input pathways diverge into multiple processing streams, with feedback at all levels in each stream and crosstalk between streams. The visual cortex can be seen in this view at a dynamic system of interconnected areas interacting flexibly in different combinations at different stages of processing. This renewal project builds on technological advances and analytical tools for with high spatial, temporal and frequency resolution, developed from prior support. These comprehensive advances make it possible to monitor multi-area functional interdependency patterns that arise in the cortex, and to measure and analyze how one cortical area can affect others. The novel approach in the current project is to examine the mesoscopic scale of functional brain organization, offering a complementary level between the microscopic recording of single cell activity in a local area or layer, and the macroscopic derivation of images from whole brains using scanning technologies such as PET and fMRI.
Results will have an impact by providing new insights into the dynamics of functional interdependency in the visual cortex, and going beyond visual neuroscience to make available digital signal processing tools potentially useful for a handling large-scale neural systems in a range of cognitive studies, and potentially leading to designing better complex artificial neural networks. This project also provides excellent cross-disciplinary training opportunities for students.

Visual function depends on the remarkable integration of a number of interrelated subprocesses such as anticipation, stimulus recognition, and stimulus discrimination. The brain is able to orchestrate these elementary processes by coordinating the activities of diverse neural structures in the face of continuously varying processing demands. The question of how this coordination operates is central to understanding the neural basis of visual function. This proposal aims to investigate the coordinated activity of distributed neuronal ensembles in the cerebral cortex of non-human primates performing a visual pattern discrimination task. It is motivated by theoretical considerations suggesting that the large-scale functional coordination of interacting neuronal ensembles is an essential component of visual function (Bressler 1995, 1996; Bressler & Kelso 2001). A combined approach of experimental work and methods development is proposed to investigate the operations of large-scale cortical networks underlying visual function. Specific hypotheses concerning the dynamics of large-scale cortical coordination will be tested by analysis of local field potentials recorded from indwelling electrodes in the cerebral cortex. Access to the rapidly changing dynamics of field potential interdependency will be possible through the use of the adaptive multivariate autoregressive methodology developed under our previous R03 project. This methodology consists of a number of interrelated techniques that can characterize the multiple, complex interactions of large-scale distributed cortical networks in a very short time frame (Ding et al. 2000). Included are methods to derive multi-site interaction patterns, analyze the dependencies of functional relations on particular group of neurons, and measure causal influences between cortical areas. Our methodological development will continue by constructing a comprehensive framework for the optimal utilization of existing techniques, and by developing more powerful measures of network function that deal with problems of nonlinearity and nonstationarity. This work is expected to: (1) produce new insights into the coordination dynamics of large-scale cortical networks in vision; and (2) make available new digital signal processing tools for the investigation of large-scale neural systems underlying other cognitive functions.

This proposal seeks NSF funding for an interdisciplinary conference to be held at Florida Atlantic University in 2010. The conference will focus on improving our understanding of the networks in the brain that are responsible for the generation of thought. The study of human brain function is possibly one of the most important endeavors for society. While there has been an explosive amount of research in basic neurobiology in recent years, progress has been limited in understanding the brain networks that govern the cognitive processes of thinking and intelligence. Conference participants will gain an overview of the present state of research on brain networks from various perspectives, including neurobiology, functional brain imaging, and cognitive science.

Understanding the integrated functioning of brain networks remains a significant scientific challenge with enormous implications for the diagnosis and treatment of cognitive disorders that result from impairment to the brain. These disorders include a wide array of symptoms associated with stroke, Alzheimer's disease, schizophrenia, and depression, to name a few. The overall aim of the proposed conference is to bring together an outstanding group of researchers to examine the dynamics of cooperative brain function from a multidisciplinary approach, and to educate the next generation of researchers on important topics at the frontier of studies in these disciplines. The highly interdisciplinary nature of the proposed conference is likely to promote new and existing collaborations. The funding will bring world-class experts to the meeting, and also enable undergraduate students, graduate students, and postdoctoral fellows to participate in the meeting with reduced fees and opportunities for travel support. The speakers will include women and members of underrepresented minorities. A critical outcome of the conference will be to produce an ongoing web-based resource providing essential information on the brain networks of cognition to the scientific community and the general public.

DESCRIPTION (provided by applicant): The goal of the proposed research is to advance our understanding of the storage, maintenance, and retrieval of information in visual working memory. Our guiding hypothesis is that these functions involve the synchronous, and causal, interactions of neuronal populations located in prefrontal, posterior parietal, and inferior temporal cortical regions. Our research plan, based on an extensive body of preliminary studies supported by a previous R21 award, consists of two sets of experiments addressing three specific aims. In the first experiment, we will train macaque monkeys to perform an oculomotor delayed match-to-sample task in which memory load will be manipulated by changes in task duration and the inclusion of distractors. This study will enable us to test specific hypotheses regarding the neural mechanisms mediating the storage and maintenance of information in visual working memory. In the second experiment, another set of monkeys will be trained to perform a delayed match-to-sample task in which they must actively retrieve either the shape or the color of a sample object following a rule-based cue. This experiment will enable us to test specific hypotheses regarding the neural mechanisms mediating the active retrieval of information from visual working memory. In both experiments, we will perform long-term measurements of neuronal activity (i.e. unit activity and local field potentials) from up to 32 independently movable microelectrodes in prefrontal, posterior parietal, and inferior temporal cortical areas while the monkeys perform the behavioral tasks. Once the data are collected, we will apply a comprehensive battery of statistical analyses to test specific hypotheses regarding the storage, maintenance and retrieval of information in visual working memory. These analyses will characterize the spatiotemporal statistical relations between groups of simultaneously recorded neurons, between neurons and local field potentials, and between local field potentials. The results will allow us to test hypotheses concerning the synchronous neuronal interactions that occur both within and between cortical areas in support of visual working memory function. We anticipate that the proposed studies will produce new insights into the dynamics of synchronous activity thought to underlie the representation and utilization of visual information in working memory. The knowledge gained from these studies will provide an important framework for understanding synchronous functional relations in the brain that may be important in the diagnosis of pathological conditions, such as Alzheimer's disease, autism, and schizophrenia, in which these relations have already been demonstrated to be deficient. PUBLIC HEALTH RELEVANCE: Disturbances of attention and working memory, and the changes in synchronous cortical activity that accompany them, are a hallmark of human psychiatric conditions including Alzheimer's disease, Autism, Attention Deficit Hyperactivity Disorder, and Schizophrenia. Analyses of disturbances in cortico-cortical synchronization hold the promise of providing critical diagnostic measures for a wide variety of cognitive disturbances. Hence, an improved understanding of the neural mechanisms mediating working memory and the task-dependent synchronization of cortical activity will have a significant impact on the development of treatments for a wide variety of neuropsychiatric disorders.