{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,16]],"date-time":"2026-10-16T05:22:28Z","timestamp":1792128148480,"version":"4.4.0"},"reference-count":126,"publisher":"World Scientific Pub Co Pte Ltd","issue":"09","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Bifurcation Chaos"],"published-print":{"date-parts":[[2003,9]]},"abstract":"<jats:p>The aim of this tutorial is to document a novel approach to brain function, in which the key to understanding is the capacity of brains for self-organization. The property that distinguishes animals from plants is the capacity for directed movement through the environment, which requires an organ capable of organizing information about the environment and predicting the consequences of self-initiated actions. The operations of predicting, planning acting, detecting, and learning comprise the process of intentionality by which brains construct meaning. The currency of brains is primarily meaning and only secondarily information. The information processing metaphor has dominated neurocognitive research for half a century. Brains certainly process information for input and output. They pre-process sensory stimuli before constructing meaning, and they post-process cognitive read-out to control appropriate action and express meaning. Neurobiologists have thoroughly documented sensory information processing bottom-up, and neuropsychologists have analyzed the later stages of cognition top-down, as they are expressed in behavior. However, a grasp of the intervening process of perception, in which meaning forms, requires detailed analysis and modeling of neural activity that is observed in brains during meaningful behavior of humans and other animals. Unlike computers, brains function hierarchically. Sensory and motor information is inferred from pulses of microscopic axons. Meaning is inferred from local mean fields of dendrites in mesoscopic and macroscopic populations. This tutorial is aimed to introduce engineers to an experimental basis for a theory of meaning, in terms of the nonlinear dynamics of the mass actions of large neural populations that construct meaning. The focus is on the higher frequency ranges of cortical oscillations. Part I introduces background on information, meaning and oscillatory activity (EEG). Part II details the properties of wave packets. Part III describes the covariance structure of the oscillations. Part IV addresses the amplitude modulations, and Part V deals with the phase modulations. The significance of a theory of meaning lies in applications using population neurodynamics, to open new approaches for treatment of clinical brain disorders, and to devise new machines with capacities for autonomy and intelligence that might approach those of simpler free-living animals.<\/jats:p>","DOI":"10.1142\/s0218127403008144","type":"journal-article","created":{"date-parts":[[2003,10,16]],"date-time":"2003-10-16T06:47:26Z","timestamp":1066286846000},"page":"2493-2511","source":"Crossref","is-referenced-by-count":70,"title":["A Neurobiological Theory of Meaning in Perception Part I: Information and Meaning in Nonconvergent and Nonlocal Brain Dynamics"],"prefix":"10.1142","volume":"13","author":[{"given":"Walter J.","family":"Freeman","sequence":"first","affiliation":[{"name":"Department of Molecular and Cell Biology, University of California, Berkeley, CA 94720-3200, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"219","published-online":{"date-parts":[[2011,11,20]]},"reference":[{"key":"rf1","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511574566"},{"key":"rf2","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.92.19.8616"},{"key":"rf3","doi-asserted-by":"publisher","DOI":"10.1016\/S0928-4257(97)81432-5"},{"key":"rf4","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511623257"},{"key":"rf5","doi-asserted-by":"publisher","DOI":"10.1093\/acprof:oso\/9780195102659.001.1"},{"key":"rf6","first-page":"364","volume":"59","author":"Bak P.","journal-title":"Phys. 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