Complexity Of Brain Research Articles

Stress: from cells to ecosystems

If there is something that we all know about in the 21st century it is stress, whether it's the stress of work, financial stress or the stress of getting the next grant funded; we are all familiar with that heart-pounding, race-against-time feeling. But this is a very modern perspective on stress.

Stronger, faster… brainier?

Hitting the gym regularly could be the surest way to boost your IQ – whatever your age. Athleticism might even explain the evolution of our species' complex brains says Christie Aschwanden

Discourse gist: A window into the brain's complex cognitive capacity

Discourse, in general, and gist reasoning specifically, are valuable tools to explore cognitive brain health across the life span. Gist reasoning is a higher-order cognitive function that entails a...

Distribution of glutamic acid decarboxylase immunoreactivity within the brain of oval squid Sepioteuthis lessoniana

AB Aquatic Biology Contact the journal Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsTheme Sections AB 19:97-109 (2013) - DOI: https://doi.org/10.3354/ab00525 FEATURE ARTICLEDistribution of glutamic acid decarboxylase immunoreactivity within the brain of oval squid Sepioteuthis lessoniana Shiori Kobayashi1, Chitoshi Takayama2, Yuzuru Ikeda1,* 1Department of Marine and Environmental Sciences, Graduate School of Engineering and Science, and 2Department of Molecular Anatomy, Graduate School of Medicine, University of the Ryukyus, Okinawa 903-0213, Japan *Corresponding author. Email: ikeda@sci.u-ryukyu.ac.jp ABSTRACT: Coleoid cephalopods (squid, cuttlefish, and octopus) have the largest and most complex brains of all invertebrates and show behavioral abilities similar to those of vertebrates. Among the coleoids, the oval squid Sepioteuthis lessoniana forms well-structured schools that are indicative of sociality. These behaviors are reflected in aspects of the well-developed brain. In this study, we focused on the role of the cephalopod brain in complex behavior. In order to reveal the network of γ-aminobutyric acid (GABA) in coleoids, we examined the immunohistochemical localization of glutamic acid decarboxylase (GAD), which is the synthetic enzyme of GABA, in the brain of young S. lessoniana. We found that GABAergic neurons and their axons were distributed throughout the brain. GABA neurons were abundantly localized in the inferior frontal lobe, which is involved in controlling arm motions, and in the subesophageal masses, which are lower and intermediate centers of action. GABAergic fibers were abundantly localized in the tract that runs from the superior frontal lobe to the vertical lobe. These results suggested the involvement of GABA in both cognitive behaviors (such as learning and memory) and in movement. KEY WORDS: Glutamic acid decarboxylase · Neurotransmitter · Brain · Oval squid · GABA · γ‑aminobutyric acid Full text in pdf format Information about this Feature Article NextCite this article as: Kobayashi S, Takayama C, Ikeda Y (2013) Distribution of glutamic acid decarboxylase immunoreactivity within the brain of oval squid Sepioteuthis lessoniana . Aquat Biol 19:97-109. https://doi.org/10.3354/ab00525 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in AB Vol. 19, No. 2. Online publication date: September 24, 2013 Print ISSN: 1864-7782; Online ISSN: 1864-7790 Copyright © 2013 Inter-Research.

Accurate maps of visual circuitry

Such is the brain's complexity that even small neural circuits contain hundreds of neurons making thousands of connections. Connectivity and optical analyses provide close-up views of two such circuits. See Articles p.168 , p.175 & Letter p.212 Three papers in this issue of Nature use the retina as a model for mapping neuronal circuits from the level of individual synaptic contacts to the long-range scale of dendritic interactions. Helmstaedter et al. used electron microscopy to map a mammalian retinal circuit of close to a thousand neurons. The work reveals a new type of retinal bipolar neuron and suggests functional mechanisms for known visual computations. The other two groups study the detection of visual motion in the Drosophila visual system — a classic neural computation model. Takemura et al. used semi-automated electron microscopy to reconstruct the basic connectome (8,637 chemical synapses among 379 neurons) of Drosophila's optic medulla. Their results reveal a candidate motion detection circuit with a wiring plan consistent with direction selectivity. Maisak et al. used calcium imaging to show that T4 and T5 neurons are divided into specific subpopulations responding to motion in four cardinal directions, and are specific to 'ON' versus 'OFF' edges, respectively.

System-Like Consolidation of Olfactory Memories in Drosophila

System consolidation, as opposed to cellular consolidation, is defined as the relatively slow process of reorganizing the brain circuits that maintain long-term memory. This concept is founded in part on observations made in mammals that recently formed memories become progressively independent of brain regions initially involved in their acquisition and retrieval and dependent on other brain regions for their long-term storage. Here we present evidence that olfactory appetitive and aversive memories in Drosophila evolve using a system-like consolidation process. We show that all three classes of mushroom body neurons (MBNs) are involved in the retrieval of short- and intermediate-term memory. With the passage of time, memory retrieval becomes independent of α'/β' and γ MBNs, and long-term memory becomes completely dependent on α/β MBNs. This shift in neuronal dependency for behavioral performance is paralleled by shifts in the activity of the relevant neurons during the retrieval of short-term versus long-term memories. Moreover, transient neuron inactivation experiments using flies trained to have both early and remote memories showed that the α'/β' MBNs have a time-limited role in memory processing. These results argue that system consolidation is not a unique feature of the mammalian brain and memory systems, but rather a general and conserved feature of how different temporal memories are encoded from relatively simple to complex brains.

The cephalopod specialties: complex nervous system, learning, and cognition

While clearly of molluscan ancestry, the coleoid cephalopods are emergent within the phylum for complexity of brain and behaviour. The brain does not just have centralization of the molluscan ganglia but also contains lobes with “higher order” functions such as storage of learned information, and centres have been compared with the vertebrate cerebellum and frontal lobe. The flexible muscular hydrostat movement system theoretically has unlimited degrees of freedom, and octopuses are models for “soft movement” robots. The decentralized nervous system, particularly in the arms of octopuses, results in decision making at many levels. Free of the molluscan shell and with evolutionary pressure from the bony fishes, coleoids have evolved a specialty in cognition and they may have a simple form of consciousness. Cephalopods also have a skin display system of unmatched complexity and excellence of camouflage, also used for communication with predators and conspecifics. A cephalopod is first and foremost a learning animal, using the display system for deception, having spatial memory, personalities, and motor play. They represent an alternative model to the vertebrates for the evolution of complex brains and high intelligence, which has as yet been only partly explored.

The Cambrian Explosion and the Origins of Embodied Cognition

Around 540 million years ago there was a sudden, dramatic adaptive radiation known as the Cambrian Explosion. This event marked the origin of almost all of the phyla (major lineages characterized by fundamental body plans) of animals that would ever live on Earth, as well as the appearance of many notable features such as rigid skeletons and other hard parts, complex jointed appendages, eyes, and brains. This radical evolutionary event has been a major puzzle for evolutionary biologists since Darwin, and while our understanding of it has recently improved with new fossil finds, richer molecular phylogenies, and better grasp of ecological, evolutionary, and developmental processes generally, unanswered questions remain. In this article I argue that a basic cognitive toolkit for embodied, object-oriented, spatial cognition—what I call Basic Cognitive Embodiment—is a practical necessity for control of a large, mobile, complexly articulated body in space. This hypothesis allows us to relate the complexification of animal bodies to the complexification of perception, cognition, and behavior in a way that can help to fill in gaps in our emerging picture of the Cambrian Explosion, as well as shed light on the deep evolutionary origins of the mind.

Reconsidering the evolution of brain, cognition, and behavior in birds and mammals

Despite decades of research, some of the most basic issues concerning the extraordinarily complex brains and behavior of birds and mammals, such as the factors responsible for the diversity of brain size and composition, are still unclear. This is partly due to a number of conceptual and methodological issues. Determining species and group differences in brain composition requires accounting for the presence of taxon-cerebrotypes and the use of precise statistical methods. The role of allometry in determining brain variables should be revised. In particular, bird and mammalian brains appear to have evolved in response to a variety of selective pressures influencing both brain size and composition. “Brain” and “cognition” are indeed meta-variables, made up of the variables that are ecologically relevant and evolutionarily selected. External indicators of species differences in cognition and behavior are limited by the complexity of these differences. Indeed, behavioral differences between species and individuals are caused by cognitive and affective components. Although intra-species variability forms the basis of species evolution, some of the mechanisms underlying individual differences in brain and behavior appear to differ from those between species. While many issues have persisted over the years because of a lack of appropriate data or methods to test them; several fallacies, particularly those related to the human brain, reflect scientists' preconceptions. The theoretical framework on the evolution of brain, cognition, and behavior in birds and mammals should be reconsidered with these biases in mind.

The urbilaterian brain revisited: novel insights into old questions from new flatworm clades.

Flatworms are classically considered to represent the simplest organizational form of all living bilaterians with a true central nervous system. Based on their simple body plans, all flatworms have been traditionally grouped together in a single phylum at the base of the bilaterians. Current molecular phylogenomic studies now split the flatworms into two widely separated clades, the acoelomorph flatworms and the platyhelminth flatworms, such that the last common ancestor of both clades corresponds to the urbilaterian ancestor of all bilaterian animals. Remarkably, recent comparative neuroanatomical analyses of acoelomorphs and platyhelminths show that both of these flatworm groups have complex anterior brains with surprisingly similar basic neuroarchitectures. Taken together, these findings imply that fundamental neuroanatomical features of the brain in the two separate flatworm groups are likely to be primitive and derived from the urbilaterian brain.

How ants find their way

Summary Insects use a wide range of tools for orientation, including visual memory, smell, and counting steps. The tricky question is how they combine and compute different kinds of inputs, and whether their methods can help us understand more complex brains or create artificial ones. Michael Gross investigates.

Circuits drive cell diversity

Neurons of the same type can show functional differences. It turns out that this diversity is in part the result of the cells' adaptation to their specific neural networks. See Letter p.375 The brain's complexity depends largely on the variety of its neuronal cell types, but what further functional heterogeneity exists within each class of neurons is still poorly documented. Focusing on the olfactory system, Troy Margrie and colleagues now report that mitral cells belonging to the same glomerulus — and therefore receiving input from one common odorant receptor — express similar levels of the HCN2 ion channel subunit, and thus present similar neuronal excitability. Mitral cells engaged in brain circuits linked to other glomeruli express different biophysical profiles, suggesting that intrinsic diversity among neurons of a given morphological class may reflect functional adaptations of local circuits to the subtly distinct information they process.

Phylogenomics meets neuroscience: How many times might complex brains have evolved?

The origin of complex centralized brains is one of the major evolutionary transitions in the history of animals. Monophyly (i.e. presence of a centralized nervous system in urbilateria) vs polyphyly (i.e. multiple origins by parallel centralization of nervous systems within several lineages) are two historically conflicting scenarios to explain such transitions. However, recent phylogenomic and cladistic analysis suggests that complex brains may have independently evolved at least 9 times within different animal lineages. Indeed, even within the phylum Mollusca cephalization might have occurred at least 5 times. Emerging molecular data further suggest that at the genomic level such transitions might have been achieved by changes in expression of just a few transcriptional factors - not surprising since such events might happen multiple times over 700 million years of animal evolution. Both cladistic and genomic analyses also imply that neurons themselves evolved more than once. Ancestral polarized secretory cells were likely involved in coordination of ciliated locomotion in early animals, and these cells can be considered as evolutionary precursors of neurons within different lineages. Under this scenario, the origins of neurons can be linked to adaptations to stress/injury factors in the form of integrated regeneration-type cellular response with secretory signaling peptides as early neurotransmitters. To further reconstruct the parallel evolution of nervous systems genomic approaches are essential to probe enigmatic neurons of basal metazoans, selected lophotrochozoans (e.g. phoronids, brachiopods) and deuterostomes.

WHOLE BRAIN GROUP NETWORK ANALYSIS USING NETWORK BIAS AND VARIANCE PARAMETERS.

The disruption of normal function and connectivity of neural circuits is common across many diseases and disorders of the brain. This disruptive effect can be studied and analyzed using the brain's complex functional and structural connectivity network. Complex network measures from the field of graph theory have been used for this purpose in the literature. In this paper we have introduced a new approach for analyzing the brain connectivity network. In our approach the true connectivity network and each subject's bias and variance are estimated using a population of patients and healthy controls. These parameters can then be used to compare two groups of brain networks. We have used this approach for the comparison of the resting state functional MRI network of pediatric Tuberous Sclerosis Complex (TSC) patients and healthy subjects. We have shown that a significant difference between the two groups can be found. For validation, we have compared our findings with three well known complex network measures.

Serial section registration of axonal confocal microscopy datasets for long-range neural circuit reconstruction

In the context of long-range digital neural circuit reconstruction, this paper investigates an approach for registering axons across histological serial sections. Tracing distinctly labeled axons over large distances allows neuroscientists to study very explicit relationships between the brain's complex interconnects and, for example, diseases or aberrant development. Large scale histological analysis requires, however, that the tissue be cut into sections. In immunohistochemical studies thin sections are easily distorted due to the cutting, preparation, and slide mounting processes. In this work we target the registration of thin serial sections containing axons. Sections are first traced to extract axon centerlines, and these traces are used to define registration landmarks where they intersect section boundaries. The trace data also provides distinguishing information regarding an axon's size and orientation within a section. We propose the use of these features when pairing axons across sections in addition to utilizing the spatial relationships among the landmarks. The global rotation and translation of an unregistered section are accounted for using a random sample consensus (RANSAC) based technique. An iterative nonrigid refinement process using B-spline warping is then used to reconnect axons and produce the sought after connectivity information.

Stop Signals Provide Cross Inhibition in Collective Decision-Making by Honeybee Swarms

Honeybee swarms and complex brains show many parallels in how they make decisions. In both, separate populations of units (bees or neurons) integrate noisy evidence for alternatives, and, when one population exceeds a threshold, the alternative it represents is chosen. We show that a key feature of a brain--cross inhibition between the evidence-accumulating populations--also exists in a swarm as it chooses its nesting site. Nest-site scouts send inhibitory stop signals to other scouts producing waggle dances, causing them to cease dancing, and each scout targets scouts' reporting sites other than her own. An analytic model shows that cross inhibition between populations of scout bees increases the reliability of swarm decision-making by solving the problem of deadlock over equal sites.

Evolving Large and Complex Brains

X-ray studies of two Early Jurassic fossils offer insight into the evolution of mammalian brains.

2R and remodeling of vertebrate signal transduction engine

BackgroundWhole genome duplication (WGD) is a special case of gene duplication, observed rarely in animals, whereby all genes duplicate simultaneously through polyploidisation. Two rounds of WGD (2R-WGD) occurred at the base of vertebrates, giving rise to an enormous wave of genetic novelty, but a systematic analysis of functional consequences of this event has not yet been performed.ResultsWe show that 2R-WGD affected an overwhelming majority (74%) of signalling genes, in particular developmental pathways involving receptor tyrosine kinases, Wnt and transforming growth factor-β ligands, G protein-coupled receptors and the apoptosis pathway. 2R-retained genes, in contrast to tandem duplicates, were enriched in protein interaction domains and multifunctional signalling modules of Ras and mitogen-activated protein kinase cascades. 2R-WGD had a fundamental impact on the cell-cycle machinery, redefined molecular building blocks of the neuronal synapse, and was formative for vertebrate brains. We investigated 2R-associated nodes in the context of the human signalling network, as well as in an inferred ancestral pre-2R (AP2R) network, and found that hubs (particularly involving negative regulation) were preferentially retained, with high connectivity driving retention. Finally, microarrays and proteomics demonstrated a trend for gradual paralog expression divergence independent of the duplication mechanism, but inferred ancestral expression states suggested preferential subfunctionalisation among 2R-ohnologs (2ROs).ConclusionsThe 2R event left an indelible imprint on vertebrate signalling and the cell cycle. We show that 2R-WGD preferentially retained genes are associated with higher organismal complexity (for example, locomotion, nervous system, morphogenesis), while genes associated with basic cellular functions (for example, translation, replication, splicing, recombination; with the notable exception of cell cycle) tended to be excluded. 2R-WGD set the stage for the emergence of key vertebrate functional novelties (such as complex brains, circulatory system, heart, bone, cartilage, musculature and adipose tissue). A full explanation of the impact of 2R on evolution, function and the flow of information in vertebrate signalling networks is likely to have practical consequences for regenerative medicine, stem cell therapies and cancer treatment.

Epigenetics on the brain: Modifying chromatin and behaviour

Proper regulation of gene expression is essential for the development and survival of every organ ism. Epigenetic modifications provide a way for cells to regulate gene expression and to propagate expression states heritably through cell division. Given the brain's complexity, it is not surprising that epigenetic regulation is essential for both normal development and maintenance of homoeostasis of this organ. New data suggest that the role of epigenetic regulation in the brain may extend much further, influencing both the ways neurons organize their networks in response to new experiences and the resultant behaviours. Such studies highlight the relevance of epigenetic regulation for neu rodevelopmental and neuropsychiatric disease.

Quantifying Time-Varying Multiunit Neural Activity Using Entropy-Based Measures

Modern micro-electrode arrays make it possible to simultaneously record population neural activity. However, methods to analyze multiunit activity (MUA), which reflects the aggregate spiking activity of a population of neurons, have remained underdeveloped in comparison to those used for studying single unit activity (SUA). In scenarios where SUA is hard to record and maintain or is not representative of brains response, MUA is informative in deciphering the brains complex time-varying response to stimuli or to clinical insults. Here, we present two quantitative methods of analysis of the time-varying dynamics of MUA without spike detection. These methods are based on the multiresolution discrete wavelet transform (DWT) of an envelope of MUA followed by information theoretic measures: multiresolution entropy (MRE) and the multiresolution Kullback-Leibler distance (MRKLD). We test the proposed quantifiers on both simulated and experimental MUA recorded from rodent cortex in an experimental model of global hypoxic-ischemic brain injury. First, our results validate the use of the envelope of MUA as an alternative to detecting and analyzing transient and complex spike activity. Second, the MRE and MRKLD are shown to respond to dynamic changes due to the brains response to global injury and to identify the transient changes in the MUA.