The standard nomenclature that has been used for many telencephalic and related brainstem structures in birds is based on flawed assumptions of homology to mammals. In particular, the outdated terminology implies that most of the avian telencephalon is a hypertrophied basal ganglia, when it is now clear that most of the avian telencephalon is neurochemically, hodologically, and functionally comparable to the mammalian neocortex, claustrum, and pallial amygdala (all of which derive from the pallial sector of the developing telencephalon). Recognizing that this promotes misunderstanding of the functional organization of avian brains and their evolutionary relationship to mammalian brains, avian brain specialists began discussions to rectify this problem, culminating in the Avian Brain Nomenclature Forum held at Duke University in July 2002, which approved a new terminology for avian telencephalon and some allied brainstem cell groups. Details of this new terminology are presented here, as is a rationale for each name change and evidence for any homologies implied by the new names.Revisions for the brainstem focused on vocal control, catecholaminergic, cholinergic, and basal ganglia‐related nuclei. For example, the Forum recognized that the hypoglossal nucleus had been incorrectly identified as the nucleus intermedius in the Karten and Hodos (1967) pigeon brain atlas, and what was identified as the hypoglossal nucleus in that atlas should instead be called the supraspinal nucleus. The locus ceruleus of this and other avian atlases was noted to consist of a caudal noradrenergic part homologous to the mammalian locus coeruleus and a rostral region corresponding to the mammalian A8 dopaminergic cell group. The midbrain dopaminergic cell group in birds known as the nucleus tegmenti pedunculopontinus pars compacta was recognized as homologous to the mammalian substantia nigra pars compacta and was renamed accordingly; a group of γ‐aminobutyric acid (GABA)ergic neurons at the lateral edge of this region was identified as homologous to the mammalian substantia nigra pars reticulata and was also renamed accordingly. A field of cholinergic neurons in the rostral avian hindbrain was named the nucleus pedunculopontinus tegmenti, whereas the anterior nucleus of the ansa lenticularis in the avian diencephalon was renamed the subthalamic nucleus, both for their evident mammalian homologues.For the basal (i.e., subpallial) telencephalon, the actual parts of the basal ganglia were given names reflecting their now evident homologues. For example, the lobus parolfactorius and paleostriatum augmentatum were acknowledged to make up the dorsal subdivision of the striatal part of the basal ganglia and were renamed as the medial and lateral striatum. The paleostriatum primitivum was recognized as homologous to the mammalian globus pallidus and renamed as such. Additionally, the rostroventral part of what was called the lobus parolfactorius was acknowledged as comparable to the mammalian nucleus accumbens, which, together with the olfactory tubercle, was noted to be part of the ventral striatum in birds. A ventral pallidum, a basal cholinergic cell group, and medial and lateral bed nuclei of the stria terminalis were also recognized.The dorsal (i.e., pallial) telencephalic regions that had been erroneously named to reflect presumed homology to striatal parts of mammalian basal ganglia were renamed as part of the pallium, using prefixes that retain most established abbreviations, to maintain continuity with the outdated nomenclature. We concluded, however, that one‐to‐one (i.e., discrete) homologies with mammals are still uncertain for most of the telencephalic pallium in birds and thus the new pallial terminology is largely devoid of assumptions of one‐to‐one homologies with mammals. The sectors of the hyperstriatum composing the Wulst (i.e., the hyperstriatum accessorium intermedium, and dorsale), the hyperstriatum ventrale, the neostriatum, and the archistriatum have been renamed (respectively) the hyperpallium (hypertrophied pallium), the mesopallium (middle pallium), the nidopallium (nest pallium), and the arcopallium (arched pallium). The posterior part of the archistriatum has been renamed the posterior pallial amygdala, the nucleus taeniae recognized as part of the avian amygdala, and a region inferior to the posterior paleostriatum primitivum included as a subpallial part of the avian amygdala. The names of some of the laminae and fiber tracts were also changed to reflect current understanding of the location of pallial and subpallial sectors of the avian telencephalon. Notably, the lamina medularis dorsalis has been renamed the pallial‐subpallial lamina. We urge all to use this new terminology, because we believe it will promote better communication among neuroscientists. Further information is available at http://avianbrain.org. J. Comp. Neurol. 473:377–414, 2004.

Determining how information flows along anatomical brain pathways is a fundamental requirement for understanding how animals perceive their environments, learn, and behave. Attempts to reveal such neural information flow have been made using linear computational methods, but neural interactions are known to be nonlinear. Here, we demonstrate that a dynamic Bayesian network (DBN) inference algorithm we originally developed to infer nonlinear transcriptional regulatory networks from gene expression data collected with microarrays is also successful at inferring nonlinear neural information flow networks from electrophysiology data collected with microelectrode arrays. The inferred networks we recover from the songbird auditory pathway are correctly restricted to a subset of known anatomical paths, are consistent with timing of the system, and reveal both the importance of reciprocal feedback in auditory processing and greater information flow to higher-order auditory areas when birds hear natural as opposed to synthetic sounds. A linear method applied to the same data incorrectly produces networks with information flow to non-neural tissue and over paths known not to exist. To our knowledge, this study represents the first biologically validated demonstration of an algorithm to successfully infer neural information flow networks. One of the challenges in the area of brain research is to decipher networks describing the flow of information among communicating neurons in the form of electrophysiological signals. These networks are thought to be responsible for perceiving and learning about the environment, as well as producing behavior. Monitoring these networks is limited by the number of electrodes that can be placed in the brain of an awake animal, while inferring and reasoning about these networks is limited by the availability of appropriate computational tools. Here, Smith and Yu and colleagues begin to address these issues by implanting microelectrode arrays in the auditory pathway of freely moving songbirds and by analyzing the data using new computational tools they have designed for deciphering networks. The authors find that a dynamic Bayesian network algorithm they developed to decipher gene regulatory networks from gene expression data effectively infers putative information flow networks in the brain from microelectrode array data. The networks they infer conform to known anatomy and other biological properties of the auditory system and offer new insight into how the auditory system processes natural and synthetic sound. The authors believe that their results represent the first validated study of the inference of information flow networks in the brain.