Polychaete community structure in the South Eastern Arabian Sea continental margin (200-1000 m)

NASA Astrophysics Data System (ADS)

Abdul Jaleel, K. U.; Anil Kumar, P. R.; Nousher Khan, K.; Correya, Neil S.; Jacob, Jini; Philip, Rosamma; Sanjeevan, V. N.; Damodaran, R.

2014-11-01

Macrofaunal polychaete communities (>500 μm) in the South Eastern Arabian Sea (SEAS) continental margin (200-1000 m) are described, based on three systematic surveys carried out in 9 transects (at ~200 m, 500 m and 1000 m) between 7°00‧and 14°30‧N latitudes. A total of 7938 polychaetes belonging to 195 species were obtained in 136 grab samples collected at 27 sites. Three distinct assemblages were identified in the northern part of the SEAS margin (10-14°30‧N), occupying the three sampled depth strata (shelf edge, upper and mid-slope) and two assemblages (shelf edge and slope) in the south (7-10°N). Highest density of polychaetes and dominance of a few species were observed in the shelf edge, where the Arabian Sea oxygen minimum zone (OMZ) impinged on the seafloor, particularly in the northern transects. The resident fauna in this region (Cossura coasta, Paraonis gracilis, Prionospio spp. and Tharyx spp.) were characteristically of smaller size, and well suited to thrive in the sandy sediments in OMZ settings. Densities were lowest along the most northerly transect (T9), where dissolved oxygen (DO) concentrations were extremely low (<0.15 ml l-1, i.e.<6.7 μmol l-1). Beyond the realm of influence of the OMZ (i.e. mid-slope, ~1000 m), the faunal density decreased while species diversity increased. The relative proportion of silt increased with depth, and the dominance of the aforementioned species decreased, giving way to forms such as Paraprionospio pinnata, Notomastus sp., Eunoe sp. and lumbrinerids. Relatively high species richness and diversity were observed in the sandy sediments of the southern sector (7-9°N), where influence of the OMZ was less intense. The area was also characterized by certain species (e.g. Aionidella cirrobranchiata, Isolda pulchella) that were nearly absent in the northern region. The gradients in DO concentration across the core and lower boundary of the OMZ, along with bathymetric and latitudinal variation in sediment texture, were responsible for differences in polychaete size and community structure on the SEAS margin. Spatial and temporal variations were observed in organic matter (OM) content of the sediment, but these were not reflected in the density, diversity or distribution pattern of the polychaetes.

Diversity, Abundance and Community Structure of Benthic Macro- and Megafauna on the Beaufort Shelf and Slope

PubMed Central

Nephin, Jessica; Juniper, S. Kim; Archambault, Philippe

2014-01-01

Diversity and community patterns of macro- and megafauna were compared on the Canadian Beaufort shelf and slope. Faunal sampling collected 247 taxa from 48 stations with box core and trawl gear over the summers of 2009–2011 between 50 and 1,000 m in depth. Of the 80 macrofaunal and 167 megafaunal taxa, 23% were uniques, present at only one station. Rare taxa were found to increase proportional to total taxa richness and differ between the shelf ( 100 m) where they tended to be sparse and the slope where they were relatively abundant. The macrofauna principally comprised polychaetes with nephtyid polychaetes dominant on the shelf and maldanid polychaetes (up to 92% in relative abundance/station) dominant on the slope. The megafauna principally comprised echinoderms with Ophiocten sp. (up to 90% in relative abundance/station) dominant on the shelf and Ophiopleura sp. dominant on the slope. Macro- and megafauna had divergent patterns of abundance, taxa richness ( diversity) and diversity. A greater degree of macrofaunal than megafaunal variation in abundance, richness and diversity was explained by confounding factors: location (east-west), sampling year and the timing of sampling with respect to sea-ice conditions. Change in megafaunal abundance, richness and diversity was greatest across the depth gradient, with total abundance and richness elevated on the shelf compared to the slope. We conclude that megafaunal slope taxa were differentiated from shelf taxa, as faunal replacement not nestedness appears to be the main driver of megafaunal diversity across the depth gradient. PMID:25007347

Diversity, abundance and community structure of benthic macro- and megafauna on the Beaufort shelf and slope.

PubMed

Nephin, Jessica; Juniper, S Kim; Archambault, Philippe

2014-01-01

Diversity and community patterns of macro- and megafauna were compared on the Canadian Beaufort shelf and slope. Faunal sampling collected 247 taxa from 48 stations with box core and trawl gear over the summers of 2009-2011 between 50 and 1,000 m in depth. Of the 80 macrofaunal and 167 megafaunal taxa, 23% were uniques, present at only one station. Rare taxa were found to increase proportional to total taxa richness and differ between the shelf (< 100 m) where they tended to be sparse and the slope where they were relatively abundant. The macrofauna principally comprised polychaetes with nephtyid polychaetes dominant on the shelf and maldanid polychaetes (up to 92% in relative abundance/station) dominant on the slope. The megafauna principally comprised echinoderms with Ophiocten sp. (up to 90% in relative abundance/station) dominant on the shelf and Ophiopleura sp. dominant on the slope. Macro- and megafauna had divergent patterns of abundance, taxa richness (α diversity) and β diversity. A greater degree of macrofaunal than megafaunal variation in abundance, richness and β diversity was explained by confounding factors: location (east-west), sampling year and the timing of sampling with respect to sea-ice conditions. Change in megafaunal abundance, richness and β diversity was greatest across the depth gradient, with total abundance and richness elevated on the shelf compared to the slope. We conclude that megafaunal slope taxa were differentiated from shelf taxa, as faunal replacement not nestedness appears to be the main driver of megafaunal β diversity across the depth gradient.

Drilling Predation on Serpulid Polychaetes (Ditrupa arietina) from the Pliocene of the Cope Basin, Murcia Region, Southeastern Spain

PubMed Central

Martinell, Jordi; Kowalewski, Michał; Domènech, Rosa

2012-01-01

We report quantitative analyses of drilling predation on the free-living, tube-dwelling serpulid polychaete Ditrupa arietina from the Cope Cabo marine succession (Pliocene, Spain). Tubes of D. arietina are abundant in the sampled units: 9 bulk samples from 5 horizons yielded ∼5925 specimens of D. arietina. Except for fragmentation, tubes were well preserved. Complete specimens ranged from 3.1 to 13.4 mm in length and displayed allometric growth patterns, with larger specimens being relatively slimmer. Drilled Ditrupa tubes were observed in all samples. Drillholes, identified as Oichnus paraboloides, were characterized by circular to elliptical outline (drillhole eccentricity increased with its diameter), parabolic vertical profile, outer diameter larger than inner diameter, penetration of one tube wall only, narrow range of drill-hole sizes, and non-random (anterior) distribution of drillholes. A total of 233 drilled specimens were identified, with drilling frequencies varying across horizons from 2.7% to 21% (3.9% for pooled data). Many tube fragments were broken across a drillhole suggesting that the reported frequencies are conservative and that biologically-facilitated (drill-hole induced) fragmentation hampers fossil preservation of complete serpulid tubes. No failed or repaired holes were observed. Multiple complete drillholes were present (3.9%). Drilled specimens were significantly smaller than undrilled specimens and tube length and drill-hole diameter were weakly correlated. The results suggest that drillholes were produced by a size-selective, site-stereotypic predatory organism of unknown affinity. The qualitative and quantitative patterns reported here are mostly consistent with previous reports on recent and fossil Ditrupa and reveal parallels with drilling patterns documented for scaphopod mollusks, a group that is ecologically and morphologically similar to Ditrupa. Consistent with previous studies, the results suggest that free-dwelling serpulid polychaetes are preyed upon by drilling predators and may provide a viable source of data on biotic interactions in the fossil record. PMID:22496828

Temporal and spatial distribution of the meiobenthic community in Daya Bay, South China Sea

NASA Astrophysics Data System (ADS)

Tang, L.; Li, H. X.; Yan, Y.

2012-04-01

Spatial and temporal biodiversity patterns of the meiobenthos were studied for the first time in Daya Bay, which is a tropical semi-enclosed basin located in the South China Sea. The abundance, biomass, and composition of the meiobenthos and the basic environmental factors in the bay were investigated. The following 19 taxonomic groups were represented in the meiofauna: Nematoda, Copepoda, Polychaeta, Oligochaeta, Kinorhyncha, Gastrotricha, Ostracoda, Bivalvia, Turbellaria, Nemertinea, Sipuncula, Hydroida, Amphipoda, Cumacea, Halacaroidea, Priapulida, Echinodermata, Tanaidacea, and Rotifera. Total abundance and biomass of the meiobenthos showed great spatial and temporal variation, with mean values of 993.57 ± 455.36 ind cm-2 and 690.51 ± 210.64 μg 10 cm-2, respectively. Nematodes constituted 95.60 % of the total abundance and thus had the greatest effect on meiofauna quantity and distribution, followed by copepods (1.55 %) and polychaetes (1.39 %). Meiobenthos abundance was significantly negatively correlated with water depth at stations (r=-0.747, P<0.05) and significantly negatively correlated with silt-clay content (r=-0.516, P<0.01) and medium diameter (r=-0.499, P<0.01) of the sediment. Similar results were found for correlations of biomass and abundance of nematodes with environmental parameters. Polychaete abundance was positively correlated with the bottom water temperature (r=0.456, P<0.01). Meiobenthos abundance differed significantly among seasons (P<0.05), although no significant difference among stations and the interaction of station × season was detected by two-way ANOVA. In terms of vertical distribution, most of the meiobenthos was found in the surface layer of sediment. This pattern was apparent for nematodes and copepods, but a vertical distribution pattern for polychaetes was not as obvious. Based on the biotic indices and analyses of their correlations and variance, the diversity of this community was likely to be influenced by environmental variations.

Polychaete richness and abundance enhanced in anthropogenically modified estuaries despite high concentrations of toxic contaminants.

PubMed

Dafforn, Katherine A; Kelaher, Brendan P; Simpson, Stuart L; Coleman, Melinda A; Hutchings, Pat A; Clark, Graeme F; Knott, Nathan A; Doblin, Martina A; Johnston, Emma L

2013-01-01

Ecological communities are increasingly exposed to multiple chemical and physical stressors, but distinguishing anthropogenic impacts from other environmental drivers remains challenging. Rarely are multiple stressors investigated in replicated studies over large spatial scales (>1000 kms) or supported with manipulations that are necessary to interpret ecological patterns. We measured the composition of sediment infaunal communities in relation to anthropogenic and natural stressors at multiple sites within seven estuaries. We observed increases in the richness and abundance of polychaete worms in heavily modified estuaries with severe metal contamination, but no changes in the diversity or abundance of other taxa. Estuaries in which toxic contaminants were elevated also showed evidence of organic enrichment. We hypothesised that the observed response of polychaetes was not a 'positive' response to toxic contamination or a reduction in biotic competition, but due to high levels of nutrients in heavily modified estuaries driving productivity in the water column and enriching the sediment over large spatial scales. We deployed defaunated field-collected sediments from the surveyed estuaries in a small scale experiment, but observed no effects of sediment characteristics (toxic or enriching). Furthermore, invertebrate recruitment instead reflected the low diversity and abundance observed during field surveys of this relatively 'pristine' estuary. This suggests that differences observed in the survey are not a direct consequence of sediment characteristics (even severe metal contamination) but are related to parameters that covary with estuary modification such as enhanced productivity from nutrient inputs and the diversity of the local species pool. This has implications for the interpretation of diversity measures in large-scale monitoring studies in which the observed patterns may be strongly influenced by many factors that covary with anthropogenic modification.

Polychaete Richness and Abundance Enhanced in Anthropogenically Modified Estuaries Despite High Concentrations of Toxic Contaminants

PubMed Central

Dafforn, Katherine A.; Kelaher, Brendan P.; Simpson, Stuart L.; Coleman, Melinda A.; Hutchings, Pat A.; Clark, Graeme F.; Knott, Nathan A.; Doblin, Martina A.; Johnston, Emma L.

2013-01-01

Ecological communities are increasingly exposed to multiple chemical and physical stressors, but distinguishing anthropogenic impacts from other environmental drivers remains challenging. Rarely are multiple stressors investigated in replicated studies over large spatial scales (>1000 kms) or supported with manipulations that are necessary to interpret ecological patterns. We measured the composition of sediment infaunal communities in relation to anthropogenic and natural stressors at multiple sites within seven estuaries. We observed increases in the richness and abundance of polychaete worms in heavily modified estuaries with severe metal contamination, but no changes in the diversity or abundance of other taxa. Estuaries in which toxic contaminants were elevated also showed evidence of organic enrichment. We hypothesised that the observed response of polychaetes was not a ‘positive’ response to toxic contamination or a reduction in biotic competition, but due to high levels of nutrients in heavily modified estuaries driving productivity in the water column and enriching the sediment over large spatial scales. We deployed defaunated field-collected sediments from the surveyed estuaries in a small scale experiment, but observed no effects of sediment characteristics (toxic or enriching). Furthermore, invertebrate recruitment instead reflected the low diversity and abundance observed during field surveys of this relatively ‘pristine’ estuary. This suggests that differences observed in the survey are not a direct consequence of sediment characteristics (even severe metal contamination) but are related to parameters that covary with estuary modification such as enhanced productivity from nutrient inputs and the diversity of the local species pool. This has implications for the interpretation of diversity measures in large-scale monitoring studies in which the observed patterns may be strongly influenced by many factors that covary with anthropogenic modification. PMID:24098816

Pearls in the ribbed mussel Aulacomya atra caused by polydorin polychaetes (Spionidae) infestation.

PubMed

Diez, M E; Vázquez, N; Cremonte, F

2016-10-01

Aulacomya atra populations of the San Jose gulf, Northern Patagonia, Southwestern Atlantic Ocean, are infested by two polydorin species, Polydora rickettsi and Dipolydora cf. giardi. The infestation by these boring polychaetes causes the formation of pearls which is evidenced by the presence of capsules containing polydorin tissue debris and the elemental composition of organic material inside the pearls. Moreover, a positive relationship between the abundance of perforations of polydorin polychaetes and abundance of pearls was found by applying generalized lineal model analysis. These results constitute the first evidence of pearls formation due to infestation by polychaete. Copyright © 2016 Elsevier Inc. All rights reserved.

Integrating a DNA barcoding project with an ecological survey: a case study on temperate intertidal polychaete communities in Qingdao, China

NASA Astrophysics Data System (ADS)

Zhou, Hong; Zhang, Zhinan; Chen, Haiyan; Sun, Renhua; Wang, Hui; Guo, Lei; Pan, Haijian

2010-07-01

In this study, we integrated a DNA barcoding project with an ecological survey on intertidal polychaete communities and investigated the utility of CO1 gene sequence as a DNA barcode for the classification of the intertidal polychaetes. Using 16S rDNA as a complementary marker and combining morphological and ecological characterization, some of dominant and common polychaete species from Chinese coasts were assessed for their taxonomic status. We obtained 22 haplotype gene sequences of 13 taxa, including 10 CO1 sequences and 12 16S rDNA sequences. Based on intra- and inter-specific distances, we built phylogenetic trees using the neighbor-joining method. Our study suggested that the mitochondrial CO1 gene was a valid DNA barcoding marker for species identification in polychaetes, but other genes, such as 16S rDNA, could be used as a complementary genetic marker. For more accurate species identification and effective testing of species hypothesis, DNA barcoding should be incorporated with morphological, ecological, biogeographical, and phylogenetic information. The application of DNA barcoding and molecular identification in the ecological survey on the intertidal polychaete communities demonstrated the feasibility of integrating DNA taxonomy and ecology.

Quantitative assessment of Hox complex expression in the indirect development of the polychaete annelid Chaetopterus sp

NASA Technical Reports Server (NTRS)

Peterson, K. J.; Irvine, S. Q.; Cameron, R. A.; Davidson, E. H.

2000-01-01

A prediction from the set-aside theory of bilaterian origins is that pattern formation processes such as those controlled by the Hox cluster genes are required specifically for adult body plan formation. This prediction can be tested in animals that use maximal indirect development, in which the embryonic formation of the larva and the postembryonic formation of the adult body plan are temporally and spatially distinct. To this end, we quantitatively measured the amount of transcripts for five Hox genes in embryos of a lophotrochozoan, the polychaete annelid Chaetopterus sp. The polychaete Hox complex is shown not to be expressed during embryogenesis, but transcripts of all measured Hox complex genes are detected at significant levels during the initial stages of adult body plan formation. Temporal colinearity in the sequence of their activation is observed, so that activation follows the 3'-5' arrangement of the genes. Moreover, Hox gene expression is spatially localized to the region of teloblastic set-aside cells of the later-stage embryos. This study shows that an indirectly developing lophotrochozoan shares with an indirectly developing deuterostome, the sea urchin, a common mode of Hox complex utilization: construction of the larva, whether a trochophore or dipleurula, does not involve Hox cluster expression, but in both forms the complex is expressed in the set-aside cells from which the adult body plan derives.

Earth’s oldest ‘Bobbit worm’ – gigantism in a Devonian eunicidan polychaete

PubMed Central

Eriksson, Mats E.; Parry, Luke A.; Rudkin, David M.

2017-01-01

Whilst the fossil record of polychaete worms extends to the early Cambrian, much data on this group derive from microfossils known as scolecodonts. These are sclerotized jaw elements, which generally range from 0.1–2 mm in size, and which, in contrast to the soft-body anatomy, have good preservation potential and a continuous fossil record. Here we describe a new eunicidan polychaete, Websteroprion armstrongi gen. et sp. nov., based primarily on monospecific bedding plane assemblages from the Lower-Middle Devonian Kwataboahegan Formation of Ontario, Canada. The specimens are preserved mainly as three-dimensional moulds in the calcareous host rock, with only parts of the original sclerotized jaw walls occasionally present. This new taxon has a unique morphology and is characterized by an unexpected combination of features seen in several different Palaeozoic polychaete families. Websteroprion armstrongi was a raptorial feeder and possessed the largest jaws recorded in polychaetes from the fossil record, with maxillae reaching over one centimetre in length. Total body length of the species is estimated to have reached over one metre, which is comparable to that of extant ‘giant eunicid’ species colloquially referred to as ‘Bobbit worms’. This demonstrates that polychaete gigantism was already a phenomenon in the Palaeozoic, some 400 million years ago. PMID:28220886

Comparative neuroanatomy suggests repeated reduction of neuroarchitectural complexity in Annelida

PubMed Central

2010-01-01

Background Paired mushroom bodies, an unpaired central complex, and bilaterally arranged clusters of olfactory glomeruli are among the most distinctive components of arthropod neuroarchitecture. Mushroom body neuropils, unpaired midline neuropils, and olfactory glomeruli also occur in the brains of some polychaete annelids, showing varying degrees of morphological similarity to their arthropod counterparts. Attempts to elucidate the evolutionary origin of these neuropils and to deduce an ancestral ground pattern of annelid cerebral complexity are impeded by the incomplete knowledge of annelid phylogeny and by a lack of comparative neuroanatomical data for this group. The present account aims to provide new morphological data for a broad range of annelid taxa in order to trace the occurrence and variability of higher brain centers in segmented worms. Results Immunohistochemically stained preparations provide comparative neuroanatomical data for representatives from 22 annelid species. The most prominent neuropil structures to be encountered in the annelid brain are the paired mushroom bodies that occur in a number of polychaete taxa. Mushroom bodies can in some cases be demonstrated to be closely associated with clusters of spheroid neuropils reminiscent of arthropod olfactory glomeruli. Less distinctive subcompartments of the annelid brain are unpaired midline neuropils that bear a remote resemblance to similar components in the arthropod brain. The occurrence of higher brain centers such as mushroom bodies, olfactory glomeruli, and unpaired midline neuropils seems to be restricted to errant polychaetes. Conclusions The implications of an assumed homology between annelid and arthropod mushroom bodies are discussed in light of the 'new animal phylogeny'. It is concluded that the apparent homology of mushroom bodies in distantly related groups has to be interpreted as a plesiomorphy, pointing towards a considerably complex neuroarchitecture inherited from the last common ancestor, Urbilateria. Within the annelid radiation, the lack of mushroom bodies in certain groups is explained by widespread secondary reductions owing to selective pressures unfavorable for the differentiation of elaborate brains. Evolutionary pathways of mushroom body neuropils in errant polychaetes remain enigmatic. PMID:20441583

Patterns of Deep-Sea Genetic Connectivity in the New Zealand Region: Implications for Management of Benthic Ecosystems

PubMed Central

Bors, Eleanor K.; Rowden, Ashley A.; Maas, Elizabeth W.; Clark, Malcolm R.; Shank, Timothy M.

2012-01-01

Patterns of genetic connectivity are increasingly considered in the design of marine protected areas (MPAs) in both shallow and deep water. In the New Zealand Exclusive Economic Zone (EEZ), deep-sea communities at upper bathyal depths (<2000 m) are vulnerable to anthropogenic disturbance from fishing and potential mining operations. Currently, patterns of genetic connectivity among deep-sea populations throughout New Zealand’s EEZ are not well understood. Using the mitochondrial Cytochrome Oxidase I and 16S rRNA genes as genetic markers, this study aimed to elucidate patterns of genetic connectivity among populations of two common benthic invertebrates with contrasting life history strategies. Populations of the squat lobster Munida gracilis and the polychaete Hyalinoecia longibranchiata were sampled from continental slope, seamount, and offshore rise habitats on the Chatham Rise, Hikurangi Margin, and Challenger Plateau. For the polychaete, significant population structure was detected among distinct populations on the Chatham Rise, the Hikurangi Margin, and the Challenger Plateau. Significant genetic differences existed between slope and seamount populations on the Hikurangi Margin, as did evidence of population differentiation between the northeast and southwest parts of the Chatham Rise. In contrast, no significant population structure was detected across the study area for the squat lobster. Patterns of genetic connectivity in Hyalinoecia longibranchiata are likely influenced by a number of factors including current regimes that operate on varying spatial and temporal scales to produce potential barriers to dispersal. The striking difference in population structure between species can be attributed to differences in life history strategies. The results of this study are discussed in the context of existing conservation areas that are intended to manage anthropogenic threats to deep-sea benthic communities in the New Zealand region. PMID:23185341

Imaging oxygen distribution in marine sediments. The importance of bioturbation and sediment heterogeneity.

PubMed

Pischedda, L; Poggiale, J C; Cuny, P; Gilbert, F

2008-06-01

The influence of sediment oxygen heterogeneity, due to bioturbation, on diffusive oxygen flux was investigated. Laboratory experiments were carried out with 3 macrobenthic species presenting different bioturbation behaviour patterns: the polychaetes Nereis diversicolor and Nereis virens, both constructing ventilated galleries in the sediment column, and the gastropod Cyclope neritea, a burrowing species which does not build any structure. Oxygen two-dimensional distribution in sediments was quantified by means of the optical planar optode technique. Diffusive oxygen fluxes (mean and integrated) and a variability index were calculated on the captured oxygen images. All species increased sediment oxygen heterogeneity compared to the controls without animals. This was particularly noticeable with the polychaetes because of the construction of more or less complex burrows. Integrated diffusive oxygen flux increased with oxygen heterogeneity due to the production of interface available for solute exchanges between overlying water and sediments. This work shows that sediment heterogeneity is an important feature of the control of oxygen exchanges at the sediment-water interface.

Ecophysiological capability of Marenzelleria populations inhabiting North Sea estuaries: an overview

NASA Astrophysics Data System (ADS)

Schiedek, Doris

1998-09-01

The metabolic responses of Marenzelleria cf. wireni, a newly established polychaete worm within North Sea estuaries, to various kinds of environmental stress are summarised. With respect to salinity, M. cf. wireni is able to deal with variations within a wide range. In the process of osmotic acclimation, free amino acids are involved. The major amino acid in terms of osmotic effector is glycine, followed by alanine. Under severe hypoxia, M. cf. wireni switches to an anaerobic metabolism, but at a very low oxygen partial pressure (<3 kPa), which indicates efficient utilisation of oxygen. Anaerobic energy production occurs predominantly via the succinate-propionate pathway. When exposed to hydrogen sulphide, M. cf. wireni is able to cope with high sulphide concentrations (up to 3 mmol l-1), but the pattern of end products of the anaerobic energy metabolism changes. In terms of sulphide tolerance, M. cf. wireni probably is even better adapted than other, indigenous polychaetes. However, in comparison with the sibling species Marenzelleria viridis, which appeared at the same time in European waters but mainly inhabits the coastal inlets of the Baltic Sea in high numbers, the metabolic capabilities of M. cf. wireni seem to be more limited at higher sulphide concentrations (>1 mmol l-1). This might have an influence on the distribution pattern of the two sibling species.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dean, T.A.; Bellis, V.J.

Epifaunal species were collected at 1-, 3-, and 12-month intervals from the Pamlico River estuary. Three epifaunal communities were recognized by characteristic species assemblages. The permanently mesohaline mouth was dominated by Garveia cerulea (hydroid), Balanus improvisus (barnacle), Victorella pavida and Membranipora tenuis (bryozoans), Diadumene leucolena (anemone), Ercolania vanellus (nudibranch), Corophium lacustre (amphipod), and Polydora websteri and Nereis succinea (polychaetes). Upriver, in oligohaline portions, dominants were Cordylophora caspia (hydroid), Balanus subalbidus and Balanus improvisus (barnacles), Victorella pavida (bryozoan), and Polydora websteri (polychaete). Between these extremes, the intermediate zone was dominated by representatives of the extremes: Balanus improvisus, Cordylophora caspia, Victorella pavida,more » Corophium lacustre (amphipod), and Polydora websteri. Demarcation of communities corresponded to salinity patterns. Within each community wide seasonal variation was demonstrated by species composition, relative abundance, and dry weight. Epifauna were most abundant in warm months (May to October) and relatively sparse the rest of the year. Seasonal expression of community structure was attributed to periodicity in larval release and settlement and was thus initiated and directed by the annual pattern of water temperature, dissolved oxygen, salinity, and interspecific competition. The sequence of epifaunal dominants began with barnacles and hydroids in the spring, a bryozoan in summer, and a smaller set of barnacles with associated tubeworms in fall. Community succession began with bacteria and protozoans followed by sessile epifauna and finally motile epifaunal associates.« less

Lepidasthenia loboi sp. n. from Puerto Madryn, Argentina (Polychaeta, Polynoidae).

PubMed

Salazar-Vallejo, Sergio I; González, Norma Emilia; Salazar-Silva, Patricia

2015-01-01

Among polychaetes, polynoids have the highest number of symbiotic species found living with a wide variety of marine invertebrates, including other polychaetes. Lepidasthenia Malmgren, 1867 and Lepidametria Webster, 1879 were regarded as synonyms but belong to different subfamilies, although both have species associated with thelepodid or terebellid polychaetes. In this contribution Lepidasthenia loboi sp. n. is described from several specimens associated with the thelepodid Thelepus antarcticus Kinberg, 1867, collected on a rocky shore near Puerto Madryn, Argentina. Lepidasthenia loboi sp. n. can be confused with Lepidasthenia esbelta Amaral & Nonato, 1982 because both live with Thelepus, are of similar sizes with similar pigmentation patterns, and have giant neurochaetae. However, in Lepidasthenia loboi sp. n. all eyes are of the same size, cephalic and parapodial cirri are tapered and mucronate, the second pair of elytra is larger than the third, the ventral cirri arise at the base of parapodia such that they do not reach chaetal lobe tips, and neuraciculae are tapered. On the contrary, in Lepidasthenia esbelta the posterior eyes are larger than anterior ones, cephalic and parapodial appendages are swollen subdistally, the second and third pairs of elytra are of the same size, the ventral cirri arise medially such that their tips reach the neurochaetal lobe tips, and the neuraciculae have falcate tips. Some comments about other genera in the Lepidastheniinae, a simplified key to its genera, and a key to Lepidasthenia species with giant neurochaetae are also included.

Lepidasthenia loboi sp. n. from Puerto Madryn, Argentina (Polychaeta, Polynoidae)

PubMed Central

Salazar-Vallejo, Sergio I.; González, Norma Emilia; Salazar-Silva, Patricia

2015-01-01

Abstract Among polychaetes, polynoids have the highest number of symbiotic species found living with a wide variety of marine invertebrates, including other polychaetes. Lepidasthenia Malmgren, 1867 and Lepidametria Webster, 1879 were regarded as synonyms but belong to different subfamilies, although both have species associated with thelepodid or terebellid polychaetes. In this contribution Lepidasthenia loboi sp. n. is described from several specimens associated with the thelepodid Thelepus antarcticus Kinberg, 1867, collected on a rocky shore near Puerto Madryn, Argentina. Lepidasthenia loboi sp. n. can be confused with Lepidasthenia esbelta Amaral & Nonato, 1982 because both live with Thelepus, are of similar sizes with similar pigmentation patterns, and have giant neurochaetae. However, in Lepidasthenia loboi sp. n. all eyes are of the same size, cephalic and parapodial cirri are tapered and mucronate, the second pair of elytra is larger than the third, the ventral cirri arise at the base of parapodia such that they do not reach chaetal lobe tips, and neuraciculae are tapered. On the contrary, in Lepidasthenia esbelta the posterior eyes are larger than anterior ones, cephalic and parapodial appendages are swollen subdistally, the second and third pairs of elytra are of the same size, the ventral cirri arise medially such that their tips reach the neurochaetal lobe tips, and the neuraciculae have falcate tips. Some comments about other genera in the Lepidastheniinae, a simplified key to its genera, and a key to Lepidasthenia species with giant neurochaetae are also included. PMID:26798303

Polychaete species (Annelida) described from the Philippine and China Seas.

PubMed

Salazar-Vallejo, Sergio I; Carrera-Parra, Luis F; Muir, Alexander I; De León-González, Jesús Angel; Piotrowski, Christina; Sato, Masanori

2014-07-30

The South China and Philippine Seas are among the most diverse regions in the Western Pacific. Although there are several local polychaete checklists available, there is none comprising the whole of this region. Presented herein is a comprehensive list of the original names of all polychaete species described from the region. The list contains 1037 species, 345 genera and 60 families; the type locality, type depository, and information regarding synonymy are presented for each species. 

Lower Cambrian polychaete from China sheds light on early annelid evolution

NASA Astrophysics Data System (ADS)

Liu, Jianni; Ou, Qiang; Han, Jian; Li, Jinshu; Wu, Yichen; Jiao, Guoxiang; He, Tongjiang

2015-06-01

We herein report a fossilized polychaete annelid, Guanshanchaeta felicia gen. et sp. nov., from the Lower Cambrian Guanshan Biota (Cambrian Series 2, stage 4). The new taxon has a generalized polychaete morphology, with biramous parapodia (most of which preserve the evidence of chaetae), an inferred prostomium bearing a pair of appendages, and a bifid pygidium. G. felicia is the first unequivocal annelid reported from the Lower Cambrian of China. It represents one of the oldest annelids among those from other early Paleozoic Lagerstätten including Sirius Passet from Greenland (Vinther et al., Nature 451: 185-188, 2008) and Emu Bay from Kangaroo island (Parry et al., Palaeontology 57: 1091-1103, 2014), and adds to our increasing roll of present-day animal phyla recognized in the early Cambrian Guanshan Biota. This finding expands the panorama of the Cambrian `explosion' exemplified by the Guanshan Biota, suggesting the presence of many more fossil annelids in the Chengjiang Lagerstätte and the Kaili Biota. In addition, this new taxon increases our knowledge of early polychaete morphology, which suggests that polychaete annelids considerably diversified in the Cambrian.

Physically disturbed deep-sea macrofauna in the Peru Basin, southeast Pacific, revisited 7 years after the experimental impact

NASA Astrophysics Data System (ADS)

Borowski, Christian

Long-term disturbance effects of a physical disturbance experiment on the benthic macrofauna (>500 μm), with particular emphasis on the dominant Polychaeta, were investigated in connection with the German ATESEPP joint programme in 4150 m depth in the Peru Basin of the tropical southeast (SE) Pacific. The study site was the 10.8 km 2 experimental field of the disturbance and re colonization experiment (DISCOL) conducted in early 1989. This programme had the objective to simulate some of the potential disturbance effects of manganese nodule mining on the bottom-dwelling biota with a towed "plough-harrow" disturber, and subsequently to investigate the resultant community responses with three post-impact samplings during a period of 3 years. Seven years after disturbance, in early 1996, the DISCOL site was revisited, and this study focuses on temporal development of the macrofauna over that extended period. Box core samples obtained during all post-impact expeditions from the disturber tracks ( disturbed treatment) were compared with unploughed sediments from the experimental field ( undisturbed treatment) and with samples from unimpacted sites of the surrounding ( reference treatment). The experiment did not cause the disastrous long-term community changes in the sediment dwelling macrofauna that previously were predicted to follow large-scale disturbances. Abundance recoveries of the macrofaunal taxa were largely terminated after 7 years. Major differences in the faunal compositions at the selected taxonomic levels of higher macrofauna taxa, polychaete families and polychaete species between disturbed and control sites were not observed, but certain disturbance effects remained present over the entire 7-year period: Within-treatment data heterogeneity for the higher macrofauna taxa and the polychaete families was greater in the disturber track samples than in undisturbed and reference treatments. Enhanced heterogeneity was expressed by significantly steeper regression slopes of variance-to-mean ratios of faunal abundances ( p<0.05) and enhanced spatial aggregation at the levels of higher macrofauna taxa and polychaete families. Hurlbert rarefaction E( Sn) and Shannon's diversity index H' calculated in non-standard ways for polychaete species revealed that patterns of diminished "diversity" in the disturbed treatments, which were observed during the later DISCOL period, were still present after 7 years, although the intensity of this signal became weaker. Recent abundance differences between treatments for the Bivalvia, Cumacea and the sigalionid polychaete species Leanira sp. A suggested that unploughed areas from the experimental field possibly were also affected by subtle long-term influences of particle plume settlement caused by the disturber action. A brief comparison with macrofauna abundance data from other ATESEPP sample locations in the Peru Basin revealed highest similarity between the sites located in the manganese nodule province, suggesting that similar disturbance effects can be expected for these areas. Nevertheless, the experimental impact by far did not reach industrial mining impact dimensions and interpretation of the results with regard to commercial mining requires caution.

Polychaete response to fresh food supply at organically enriched coastal sites: Repercussion on bioturbation potential and trophic structure

NASA Astrophysics Data System (ADS)

Venturini, N.; Pires-Vanin, A. M. S.; Salhi, M.; Bessonart, M.; Muniz, P.

2011-12-01

We investigated the vertical distribution, abundance, specific and functional structure of polychaete assemblages at four organically enriched sites. The effects of fresh organic matter input from the water column driving by upwelling were evaluated. Temperature and salinity values indicate the intrusion of South Atlantic Central Water (SACW) in spring, a nutrient-rich water mass. The dominance of the conveyor belt transport (CONV) in the station influenced by SACW, in the spring survey, is associated with fresh organic matter input as indicated by higher amounts of polyunsaturated fatty acids. Conversely, the predominance of the diffusive mixing (DIFF) bioturbation category, in the sites without SACW influence is related to the preferential accumulation of more refractive food resources as indicated by higher concentrations of short chain saturated fatty acids. At the site influenced by SACW, the changes in polychaete assemblages were not all evident during proceeding upwelling conditions, but may persist at the end of the upwelling. Polychaetes in the study area seemed to be limited by the quality but not the quantity of food. The delay in polychaete response to fresh food supply may be related to the organic enrichment and the prevalence of refractory material in the sediments.

Effects of a brine discharge over soft bottom Polychaeta assemblage.

PubMed

Del-Pilar-Ruso, Yoana; De-la-Ossa-Carretero, Jose Antonio; Giménez-Casalduero, Francisca; Sánchez-Lizaso, Jose Luis

2008-11-01

Desalination is a growing activity that has introduced a new impact, brine discharge, which may affect benthic communities. Although the role of polychaetes as indicators to assess organic pollution is well known, their tolerance to salinity changes has not been examined to such a great extent. The aim of this study was to examine the effect of brine discharge over soft bottom polychaete assemblage along the Alicante coast (Southeast Spain) over a two year period. Changes in the polychaete assemblage was analysed using univariate and multivariate techniques. We compared a transect in front of the discharge with two controls. At each transect we sampled at three depths (4, 10 and 15 m) during winter and summer. We have observed different sensitivity of polychaete families to brine discharges, Ampharetidae being the most sensitive, followed by Nephtyidae and Spionidae. Syllidae and Capitellidae showed some resistance initially, while Paraonidae proved to be a tolerant family.

Anthropogenic and natural disturbances to marine benthic communities in Antarctica

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lenihan, H.; Oliver, J.S.

1995-05-01

Sampling and field experiments were conducted from 1975 to 1990 to test how the structure of marine benthic communities around McMurdo Station, Antarctica varied with levels of anthropogenic contaminants in marine sediments. The structure of communities (e.g., infauna density, species composition, and life history characteristics) in contaminated and uncontaminated areas were compared with the structure of communities influenced by two large-scale natural disturbances, anchor ice formation and uplift or iceberg scour. Benthic communities changed radically along a steep spatial gradient of anthropogenic hydrocarbon, metal, and PCB contamination around McMurdo Station. The heavily contaminated end of the gradient, Winter Quarters Bay,more » was low in infaunal and epifaunal abundance and was dominated by a few opportunistic species of polychaete worms. The edge of the heavily contaminated bay, the transition area, contained several motile polychaete species with less opportunistic life histories. Uncontaminated sedimentary habitats harbored dense tube mats of infaunal animals numerically dominated by populations of polychaete worms, crustaceans, and a large suspension feeding bivalve. These species are generally large and relatively sessile, except for several crustacean species living among the tubes. Although the community patterns around anthropogenic and natural disturbances were similar, particularly motile and opportunistic species at heavily disturbed and marginal areas, the natural disturbances cover much greater areas of the sea floor about the entire Antarctic continent. On the other hand, recovery from chemical contamination is likely to take many more decades than recovery from natural disturbances as contaminant degradation is a slow process. 77 refs., 6 figs., 5 tabs.« less

Reducing the data-deficiency of threatened European habitats: Spatial variation of sabellariid worm reefs and associated fauna in the Sicily Channel, Mediterranean Sea.

PubMed

Bertocci, Iacopo; Badalamenti, Fabio; Lo Brutto, Sabrina; Mikac, Barbara; Pipitone, Carlo; Schimmenti, Eugenia; Vega Fernández, Tomás; Musco, Luigi

2017-09-01

Biogenic reefs, such as those produced by tube-dwelling polychaetes of the genus Sabellaria, are valuable marine habitats which are a focus of protection according to European legislation. The achievement of this goal is potentially hindered by the lack of essential empirical data, especially in the Mediterranean Sea. This study addresses some of the current knowledge gaps by quantifying and comparing multi-scale patterns of abundance and distribution of two habitat-forming species (Sabellaria alveolata and S. spinulosa) and their associated fauna along 190 km of coast on the Italian side of the Sicily Channel. While the abundance of the two sabellariids and the total number of associated taxa did not differ at any of the examined scales (from tens of centimetres to tens-100 of kilometres), the structure (composition in terms of both the identity and the relative abundance of constituting taxa) of the associated fauna and the abundance of several taxa (the polychaetes Eulalia ornata, Syllis pulvinata, S. garciai, Nereis splendida and Arabella iricolor, and the amphipods Apolochus neapolitanus, Tethylembos viguieri and Caprella acanthifera) varied among locations established ∼50-100 km apart. Syllis pulvinata also showed significant variation between sites (hundreds of metres apart), analogously to the other syllid polychaetes S. armillaris and S. gracilis, the nereidid polychaete Nereis rava, and the amphipod Gammaropsis ulrici. The largest variance of S. spinulosa, of the structure of the whole associated fauna and of 56% of taxa analysed individually occurred at the scale of replicates (metres apart), while that of the dominant bio-constructor S. alveolata and of 25% of taxa occurred at the scale of sites. The remaining 19% and the total richness of taxa showed the largest variance at the scale of locations. Present findings contribute to meet a crucial requirement of any future effective protection strategy, i.e., identifying relevant scales of variation to be included in protection schemes aiming at preserving representative samples not only of target habitats and organisms, but also of the processes driving such variability. Copyright © 2017 Elsevier Ltd. All rights reserved.

Comprehensive Assessment of Marine Coatings in the Laboratory and Field

DTIC Science & Technology

2015-03-27

basal plate morphology and minimum size requirements. Only barnacles occurring at least 5 mm from the edges of the coupon were tested. Other...Incipient Fouling Calcareous Polychaetes | Sedimentan/ Polychaetes Solitary Tunicate | Sponges |Scuzz & & & & & Figure 7. Average

Genotoxic damage in polychaetes: a study of species and cell-type sensitivities.

PubMed

Lewis, Ceri; Galloway, Tamara

2008-06-30

The marine environment is becoming increasingly contaminated by environmental pollutants with the potential to damage DNA, with marine sediments acting as a sink for many of these contaminants. Understanding genotoxic responses in sediment-dwelling marine organisms, such as polychaetes, is therefore of increasing importance. This study is an exploration of species-specific and cell-specific differences in cell sensitivities to DNA-damaging agents in polychaete worms, aimed at increasing fundamental knowledge of their responses to genotoxic damage. The sensitivities of coelomocytes from three polychaetes species of high ecological relevance, i.e. the lugworm Arenicola marina, the harbour ragworm Nereis diversicolor and the king ragworm Nereis virens to genotoxic damage are compared, and differences in sensitivities of their different coelomic cell types determined by use of the comet assay. A. marina was found to be the most sensitive to genotoxic damage induced by the direct-acting mutagen methyl methanesulfonate (MMS), and showed dose-dependent responses to MMS and the polycyclic aromatic hydrocarbon benzo(a)pyrene. Significant differences in sensitivity were also measured for the different types of coelomocyte. Eleocytes were more sensitive to induction of DNA damage than amoebocytes in both N. virens and N. diversicolor. Spermatozoa from A. marina showed significant DNA damage following in vitro exposure to MMS, but were less sensitive to DNA damage than coelomocytes. This investigation has clearly demonstrated that different cell types within the same species and different species within the polychaetes show significantly different responses to genotoxic insult. These findings are discussed in terms of the relationship between cell function and sensitivity and their implications for the use of polychaetes in environmental genotoxicity studies.

Distribution and abundance of the polychaete, Manayunkia speciosa Leidy, in western Lake Erie

USGS Publications Warehouse

Hiltunen, Jarl K.

1965-01-01

The abundance and distribution of the freshwater polychaete, Manayunkia speciosa, in 1961, are described for western Lake Erie. Previous records reveal that the species has either been generally overlooked or presently its numbers have greatly increased in the area considered.

Borehole density on the surface of living Porites corals as an indicator of sedimentation in Hong Kong.

PubMed

Xie, James Y; Wong, Jane C Y; Dumont, Clement P; Goodkin, Nathalie; Qiu, Jian-Wen

2016-07-15

Borehole density on the surface of Porites has been used as an indicator of water quality in the Great Barrier Reef. We assessed the relationship between borehole density on Porites and eight water quality parameters across 26 sites in Hong Kong. We found that total borehole densities on the surface of Porites at 16 of the studied sites were high (>1000individualsm(-2)), with polychaetes being the dominant bioeroders. Sedimentation rate was correlated positively with total borehole density and polychaete borehole density, with the latter relationship having a substantially higher correlation of determination. None of the environmental factors used were significantly correlated with bivalve borehole density. These results provide a baseline for assessing future changes in coral bioerosion in Hong Kong. This present study also indicates that polychaete boreholes can be used as a bioindicator of sedimentation in the South China Sea region where polychaetes are numerically dominant bioeroders. Copyright © 2016 Elsevier Ltd. All rights reserved.

Uptake, metabolism and sub-lethal effects of BDE-47 in two estuarine invertebrates with different trophic positions.

PubMed

Díaz-Jaramillo, M; Miglioranza, K S B; Gonzalez, M; Barón, E; Monserrat, J M; Eljarrat, E; Barceló, D

2016-06-01

Two microcosm types -sediment-biota and biota-biota- were constructed to simulate different pathways of BDE-47 uptake, metabolism and oxidative stress effects in two key estuarine invertebrates (polychaete Laeonereis acuta and crab Cyrtograpsus angulatus). In the sediment-biota experiment, both species were exposed to spiked sediments; an environmentally reported and a high concentration of BDE-47 for 2 weeks. In the biota-biota experiment, crabs were fed with polychaetes pre-exposed to BDE-47 in the sediment-biota experiment. The sediment-biota experiment first revealed that polychaetes significantly accumulated BDE-47 (biota-sediment accumulation factor >2; p < 0.05) to a much greater extent than the crab organs (muscle, hepatopancreas, gills) at both sediment concentrations. For oxidative stress responses, polychaete and crab tissues exposed to spiked sediment showed a significant increase (p < 0.05) of only glutathione S-transferase (GST) activity with respect to controls in both BDE-47 concentrations. No lipid peroxidation (TBARS) or total antioxidant capacity (ACAP) changes were evident in the species or organs exposed to either BDE-47 sediment concentration. The biota-biota experiment showed that feeding crabs with pre-exposed polychaetes caused BDE-47 accumulation in organs as well as significant amounts of BDE-47 eliminated through feces (p < 0.05). Unlike the sediment-biota exposure, crabs fed with pre-exposed BDE-47 polychaetes showed the most conspicuous oxidative stress responses. Significant changes in GST and ACAP in both hepatopancreas and gills, in addition to enhanced TBARS levels in the hepatopancreas with respect to controls (p < 0.05), revealed that BDE-47 assimilated by invertebrates represents a potential source of toxicity to their predators. No methoxylated metabolites (MeO-PBDEs) were detected during BDE-47 metabolism in the invertebrates in either of the two different exposure types. In contrast, hydroxylated metabolites (OH-PBDEs) were detected in polychaetes and crab organs/feces in both experiments. Our results demonstrate that PBDE hydroxylation is one of the main biotransformation routes of BDE-47 in estuarine animals, which could be associated with the oxidative stress responses found. Copyright © 2016 Elsevier Ltd. All rights reserved.

DIVERGENCE BETWEEN POPULATIONS OF A MONOGAMOUS POLYCHAETE WITH MALE PARENTAL CARE: PREMATING ISOLATION AND CHROMOSOME VARIATION

EPA Science Inventory

Low dispersal and sexual selection are characteristic of the coastal polychaete Nereis acuminata Ehlers 1868 [also known as Nereis arenaceodentata Moore 1903 and Nereis (Neanthes) caudata elle Chiaje 1841]. e assessed levels of premating isolation between populations of this poly...

ORGANIC CONTAMINANT DISTRIBUTION IN SEDIMENTS, POLYCHAETES (NEREIS VIRENS) AND THE AMERICAN LOBSTER, HOMARUS AMERICANUS IN A LABORATORY FOOD CHAIN EXPERIMENT

EPA Science Inventory

A laboratory experiment was conducted to investigate the transfer of organic contaminants from an environmentally contaminated marine sediment through a simple marine food chain. The infaunal polychaete, Nereis virens, was exposed to contaminated sediment collected from the Passa...

The influence of salinity on the effects of Multi-walled carbon nanotubes on polychaetes.

PubMed

De Marchi, Lucia; Neto, Victor; Pretti, Carlo; Figueira, Etelvina; Chiellini, Federica; Morelli, Andrea; Soares, Amadeu M V M; Freitas, Rosa

2018-06-05

Salinity shifts in estuarine and coastal areas are becoming a topic of concern and are one of the main factors influencing nanoparticles behaviour in the environment. For this reason, the impacts of multi-walled carbon nanotubes (MWCNTs) under different seawater salinity conditions were evaluated on the common ragworm Hediste diversicolor, a polychaete species widely used as bioindicator of estuarine environmental quality. An innovative method to assess the presence of MWCNT aggregates in the sediments was used for the first time. Biomarkers approach was used to evaluate the metabolic capacity, oxidative status and neurotoxicity of polychaetes after long-term exposure. The results revealed an alteration of energy-related responses in contaminated polychaetes under both salinity conditions, resulting in an increase of metabolism and expenditure of their energy reserves (lower glycogen and protein contents). Moreover, a concentration-dependent toxicity (higher lipid peroxidation, lower ratio between reduced and oxidized glutathione and activation of antioxidant defences and biotransformation mechanisms) was observed in H. diversicolor, especially when exposed to low salinity. Additionally, neurotoxicity was observed by inhibition of Cholinesterases activity in organisms exposed to MWCNTs at both salinities.

Polychaete functional diversity in shallow habitats: Shelter from the storm

NASA Astrophysics Data System (ADS)

Wouters, Julia M.; Gusmao, Joao B.; Mattos, Gustavo; Lana, Paulo

2018-05-01

Innovative approaches are needed to help understanding how species diversity is related to the latitudinal gradient at large or small scales. We have applied a novel approach, by combining morphological and biological traits, to assess the relative importance of the large scale latitudinal gradient and regional morphodynamic drivers in shaping the functional diversity of polychaete assemblages in shallow water habitats, from exposed to estuarine sandy beaches. We used literature data on polychaetes from beaches along the southern and southeastern Brazilian coast together with data on beach types, slope, grain size, temperature, salinity, and chlorophyll a concentration. Generalized linear models on the FDis index for functional diversity calculated for each site and a combined RLQ and fourth-corner analysis were used to investigate relationships between functional traits and environmental variables. Functional diversity was not related to the latitudinal gradient but negatively correlated with grain size and beach slope. Functional diversity was highest in flat beaches with small grain size, little wave exposure and enhanced primary production, indicating that small scale morphodynamic conditions are the primary drivers of polychaete functional diversity.

Lipid biomarkers of deep-sea hydrothermal vent polychaetes— Alvinella pompejana, A. caudata, Paralvinella grasslei and Hesiolyra bergii

NASA Astrophysics Data System (ADS)

Phleger, Charles F.; Nelson, Matthew M.; Groce, Ami K.; Craig Cary, S.; Coyne, Kathryn; Gibson, John A. E.; Nichols, Peter D.

2005-12-01

The lipid composition was determined for 5 species of polychaete annelids collected by the Deep Submergence Vehicle ALVIN from high temperature chimneys at the 2500 m depth hydrothermal vent field of the East Pacific Rise. These are the first lipid biomarker analyses reported for these hydrothermal vent polychaetes. Lipid content was low in all samples (1.6-35.9 mg g -1 wet mass) and was dominated by polar lipid (78-90% of total lipid) with 8-19% sterol (ST), and very low storage lipid (triacylglycerol and wax ester). Total polyunsaturated fatty acids (PUFA) were moderately high (22-31% of total fatty acids (FA)) with extremely low or no docosahexaenoic acid (DHA, 22:6(n-3)). Eicosapentaenoic acid (EPA, 20:5(n-3)) levels were 5-6% in Alvinella pompejana and A. caudata and 10.3-13.7% in an errantiate polychaete (likely Hesionidae) and Hesiolyra bergii. There were greater PUFA and a greater EPA/AA (AA is arachidonic acid, 20:4(n-6)) ratio in the anterior versus the posterior half of A. pompejana, which may correlate to the strong temperature gradient reported in its tube. Total nonmethylene interrupted diunsaturated fatty acids (NMID) were 4-9% of total FA for most polychaete species and included several 20:2 and 22:2 components. The principal monounsaturated fatty acids (MUFA) included 18:1(n-7)c (14-19%), 16:1(n-7)c (2.6-10%) and 20:1(n-11)c (3-7% of total FA). These polychaete species may desaturate and elongate the bacterial-derived 18:1(n-7)c to obtain the essential FA EPA and AA. The major ST in the polychaetes is cholesterol (89-98% of total ST) with less cholesterol in the gut contents of A. pompejana. Other ST included 24-ethylcholesterol (1.5-5% of total ST) with lesser amounts of 24-methylenecholesterol, desmosterol, lathosterol, 24-methylcholesterol, 24-ethylcholesterol, and the stanols dehydrocholestanol and cholestanol. The high ST levels could play a role in thermal adaptation of membranes at the hydrothermal vent environment. Differences in the FA profiles separated the closely related species A. pompejana and A. caudata from Paralvinella grasslei, H. bergii, and the errantiate polychaete (likely Hesionidae).

The spatial and temporal expression of Ch-en, the engrailed gene in the polychaete Chaetopterus, does not support a role in body axis segmentation

NASA Technical Reports Server (NTRS)

Seaver, E. C.; Paulson, D. A.; Irvine, S. Q.; Martindale, M. Q.

2001-01-01

We are interested in understanding whether the annelids and arthropods shared a common segmented ancestor and have approached this question by characterizing the expression pattern of the segment polarity gene engrailed (en) in a basal annelid, the polychaete Chaetopterus. We have isolated an en gene, Ch-en, from a Chaetopterus cDNA library. Genomic Southern blotting suggests that this is the only en class gene in this animal. The predicted protein sequence of the 1.2-kb cDNA clone contains all five domains characteristic of en proteins in other taxa, including the en class homeobox. Whole-mount in situ hybridization reveals that Ch-en is expressed throughout larval life in a complex spatial and temporal pattern. The Ch-en transcript is initially detected in a small number of neurons associated with the apical organ and in the posterior portion of the prototrochophore. At later stages, Ch-en is expressed in distinct patterns in the three segmented body regions (A, B, and C) of Chaetopterus. In all segments, Ch-en is expressed in a small set of segmentally iterated cells in the CNS. In the A region, Ch-en is also expressed in a small group of mesodermal cells at the base of the chaetal sacs. In the B region, Ch-en is initially expressed broadly in the mesoderm that then resolves into one band/segment coincident with morphological segmentation. The mesodermal expression in the B region is located in the anterior region of each segment, as defined by the position of ganglia in the ventral nerve cord, and is involved in the morphogenesis of segment-specific feeding structures late in larval life. We observe banded mesodermal and ectodermal staining in an anterior-posterior sequence in the C region. We do not observe a segment polarity pattern of expression of Ch-en in the ectoderm, as is observed in arthropods. Copyright 2001 Academic Press.

THE EFFECTS OF SALINITY CHANGE ON THE FREE AMINO ACID POOLS OF TWO NEREID POLYCHAETES, 'NEANTHES SUCCINEA' AND 'LEONEREIS CULVERI'

EPA Science Inventory

The response of the free amino acid pools of two nereid polychaetes, Neanthes succinea and Leonereis culveri to both increased and decreased salinities was examined. In both species, glycine and alanine accounted for most of the observed change in the total free amino acid (FAA) ...

Final Environmental Assessment for Test Area D-84 Waterside Redevelopment

DTIC Science & Technology

2012-09-01

typically adapted for life in saturated soil conditions (U.S. Army, 1987). Wetlands are the most productive ecosystems in the world (Mitsch and...such as amphipods, Jancelets, polychaetes, gastropods , ghost shrimp, isopods, molluscs and/or crustaceans, within estuarine and marine habitats and...lancelets, polychaetes, gastropods , ghost shrimp, isopods, mollusks, and/or crustaceans within estuarine and marine habitats and substrates for subadult

Evaluation of Venturi Oxygen Stripping (trademark) as a Ballast Water Treatment to Prevent Aquatic Invasions and Ship Corrosion

DTIC Science & Technology

2003-01-01

that can withstand low oxygen levels (e.g., resistant cysts of dinoflagellates, Hallegraeff 1998). Marine bacteria, in particular, will have...Chesapeake Bay zooplankton (copepods, barnacle larvae, polychaete larvae, cladocerans, crustacean nauplii, bivalve larvae, and nematodes ) in less than...zooplankton (copepods, barnacle larvae, polychaete larvae, cladocerans, crustacean nauplii, bivalve larvae, and nematodes ) in control and treated

Sediment Ecosystem Assessment Protocol (SEAP): An Accurate and Integrated Weight-of-Evidence Based System

DTIC Science & Technology

2011-01-01

polychaete Neanthes arenaceodentata from exposures to copper in aqueous solutions ...involved 96 h exposures in aqueous solutions , followed by a 1-2 hour (depending on size) feeding period on Artemia (brine shrimp) nauplii in clean seawater...EC50) based on post- exposure feeding of the polychaete Neanthes arenaceodentata from exposures to copper in aqueous solutions . Metric (µg/L) Worm age

Evaluation of Dredged Material Proposed for Ocean Disposal. Testing Manual

DTIC Science & Technology

1991-02-01

should include a deposit-feeding amphipod and a polychaete. Bioaccumulation tests generally should include a deposit-feeding bivalve mollusc and a...Gibson. 1987. Regulatory identification of petroleum hydrocarbons in dredged material. Proceedings of a Workshop. Misc. Pap. D-87-3, U.S. Army... Bioaccumulation from Whole-Sediment Tests. Polychaetes Molluscs Neanthes sp.* Macoma clam, Macoma sp.* Nereis sp.* Yoldia clam, Yoldia limatula Nephiy sp.* Nucula

Toxicological responses of Laeonereis acuta (Polychaeta, Nereididae) after acute, subchronic and chronic exposure to cadmium.

PubMed

Dolagaratz Carricavur, Arantxa; Chiodi Boudet, Leila; Romero, María Belén; Polizzi, Paula; Marcovecchio, Jorge Eduardo; Gerpe, Marcela

2018-03-01

The objective of this study was to analyze the toxicological responses of the estuarine polychaete Laeonereis acuta after acute (96h), subchronic (7 days) and chronic (14 days) exposure to cadmium (Cd). Concentrations of metallothioneins (MT), lipid peroxidation (LPO), total Cd and metal-rich granules (MRG) were evaluated. Seasonal variations of MT and LPO levels in the wild were also measured. Polychaetes were obtained in the Quequén estuary located southeast of Buenos Aires Province, Argentina. For the acute toxicity assay, individuals were exposed to 10; 30, 65; 310; 600; 1300; 2000; 4300; 8100; 16300µgCdL -1 , which included levels of environmental relevance and median lethal concentrations (LC 50 ) for related species of polychaete. Based on 96h LC 50 values, polychaetes were exposed to sublethal doses of Cd. The concentrations for both subchronic and chronic assays were: 10; 30; 65; 310; 600; 1300; 2000; 4300µgCdL -1 . The 96h LC 50 value was 8234.9µgL -1 , which was within the values reported for other species of polychaete, indicating a high tolerance to Cd. MT induction was not observed for any time exposure. In additoin, LPO levels showed no differences with respect to control levels, which indicated an absence of oxidative damage caused by Cd. However, the total Cd and MRG-Cd concentrations in L. acuta in all tested treatments showed significant differences with respect to control levels. L. acuta were able to accumulate Cd in their tissues in the form of granules which are the main mechanism of Cd detoxification. Copyright © 2017 Elsevier Inc. All rights reserved.

Polychaetes of Greece: an updated and annotated checklist

PubMed Central

Simboura, Nomiki; Katsiaras, Nikolaos; Chatzigeorgiou, Giorgos; Arvanitidis, Christos

2017-01-01

Abstract Background The last annotated checklist of marine polychaetes in Greece was published in 2001. Since then, global taxonomic progress, combined with many new species records for Greece, required a thorough review of the taxonomic, nomenclatural and biogeographic status of the national species list. This checklist revises the status of all extant polychaete species reported from the Greek Exclusive Economic Zone since 1832. The work was undertaken as part of the efforts on compiling a national species inventory (Greek Taxon Information System initiative) in the framework of the LifeWatchGreece Research Infrastructure. New information This checklist comprises an updated and annotated inventory of polychaete species in Greek waters, compiled from literature reports, online databases, museum collections and unpublished datasets. The list provides information on 836 species-level taxa from Greece, of which 142 are considered questionable. An additional 84 species reported in the past are currently considered absent from Greece; reasons for the exclusion of each species are given. Fourteen species are reported here for the first time from Greek waters. At least 52 species in the present list constitute in fact a complex of cryptic or pseudo-cryptic species. Forty-seven species are considered non-native to the area. In addition to the species-level taxa reported in this checklist, eleven genera have been recorded from Greece with no representatives identified to species level. One replacement name is introduced. For each species, a comprehensive bibliographic list of occurrence records in Greece and the synonyms used in these publications are provided as supplementary material. Where necessary, the taxonomic, nomenclatural or biogeographic status is discussed. Finally, the findings are discussed in the wider context of Mediterranean polychaete biogeography, taxonomic practice and worldwide research progress. PMID:29362552

Genotoxicity of two heavy metal compounds: lead nitrate and cobalt chloride in Polychaete Perinereis cultrifera.

PubMed

Singh, Nisha; Bhagat, Jacky; Ingole, Baban S

2017-07-01

The present study explores the in vivo and in vitro genotoxic effects of lead nitrate, [Pb(NO 3 ) 2 ] a recognized environmental pollutant and cobalt chloride (CoCl 2 ), an emerging environmental pollutant in polychaete Perinereis cultrifera using comet assay. Despite widespread occurrence and extensive industrial applications, no previous published reports on genotoxicity of these compounds are available in polychaete as detected by comet assay. Polychaetes were exposed in vivo to Pb(NO 3 ) 2 (0, 100, 500, and 1000 μg/l) and CoCl 2 (0, 100, 300, and 500 μg/l) for 5 days. At 100 μg/l Pb(NO 3 ) 2 concentration, tail DNA (TDNA) values in coelomocytes were increase by 1.16, 1.43, and 1.55-fold after day 1, day 3, and day 5, whereas, OTM showed 1.12, 2.33, and 2.10-fold increase in in vivo. Pb(NO 3 ) 2 showed a concentration and time-dependent genotoxicity whereas CoCl 2 showed a concentration-dependent genotoxicity in in vivo. A concentration-dependent increase in DNA damage was observed in in vitro studies for Pb(NO 3 ) 2 and CoCl 2 . DNA damage at 500 μg/L showed almost threefold increase in TDNA and approximately fourfold increase in OTM as compared to control in in vitro. Our studies suggest that Pb(NO 3 ) 2 and CoCl 2 have potential to cause genotoxic damage, with Pb(NO 3 ) 2 being more genotoxic in polychaete and should be used more carefully in industrial and other activities. Graphical abstract.

Managing the marine aquarium trade: revealing the data gaps using ornamental polychaetes.

PubMed

Murray, Joanna M; Watson, Gordon J; Giangrande, Adriana; Licciano, Margherita; Bentley, Matt G

2012-01-01

The marine aquarium industry has great potential to generate jobs in low-income coastal communities creating incentives for the maintenance of a healthy coral reef, if effectively managed. In the absence of current monitoring or legislation to govern the trade, baseline information regarding the species, number and source location of animals traded is missing despite being critical for its successful management and sustainability. An industry assessment to establish the number and provenance of species of ornamental polychaetes (sabellids and serpulids) traded was undertaken across UK wholesalers and retailers. Six geographical regions exporting fan worms were identified. Singapore contributed the highest percentage of imports, but of only one worm "type" whereas Bali, the second largest source, supplied five different worm "types". Over 50% of UK retailers were supplied by one wholesaler while the remainder were stocked by a mixture of one other wholesaler and/or direct imports from the source country. We estimate that up to 18,500 ornamental polychaetes (16,980 sabellids and 1,018 serpulids) are sold annually in the UK revealing a drastic underestimation of currently accepted trade figures. Incorrect identification (based on exporting region or visual characteristics) of traded animals exacerbates the inaccuracy in market quantification, although identification of preserved sabellids using published keys proved just as inconclusive with high within-species variability and the potential for new or cryptic species. A re-description of the polychaete groups traded using a combination of molecular and morphological techniques is necessary for effective identification and market quantification. This study provides the first assessment of ornamental polychaetes but more importantly highlights the issues surrounding the collection of baseline information necessary to manage the aquarium trade. We recommend that future management should be community based and site-specific with financial and educational support from NGOs, local governments and industry members.

Antioxidant responses in estuarine invertebrates exposed to repeated oil spills: Effects of frequency and dosage in a field manipulative experiment.

PubMed

Sandrini-Neto, Leonardo; Pereira, Letícia; Martins, César C; Silva de Assis, Helena C; Camus, Lionel; Lana, Paulo C

2016-08-01

We have experimentally investigated the effects of repeated diesel spills on the bivalve Anomalocardia brasiliana, the gastropod Neritina virginea and the polychaete Laeonereis culveri, by monitoring the responses of oxidative stress biomarkers in a subtropical estuary. Three frequencies of exposure events were compared against two dosages of oil in a factorial experiment with asymmetrical controls. Hypotheses were tested to distinguish between (i) the overall effect of oil spills, (ii) the effect of diesel dosage via different exposure regimes, and (iii) the effect of time since last spill. Antioxidant defense responses and oxidative damage in the bivalve A. brasiliana and the polychaete L. culveri were overall significantly affected by frequent oil spills compared to undisturbed controls. The main effects of diesel spills on both species were the induction of SOD and GST activities, a significant increase in LPO levels and a decrease in GSH concentration. N. virginea was particularly tolerant to oil exposure, with the exception of a significant GSH depletion. Overall, enzymatic activities and oxidative damage in A. brasiliana and L. culveri were induced by frequent low-dosage spills compared to infrequent high-dosage spills, although the opposite pattern was observed for N. virginea antioxidant responses. Antioxidant responses in A. brasiliana and L. culveri were not affected by timing of exposure events. However, our results revealed that N. virginea might have a delayed response to acute high-dosage exposure. Experimental in situ simulations of oil exposure events with varying frequencies and intensities provide a useful tool for detecting and quantifying environmental impacts. In general, antioxidant biomarkers were induced by frequent low-dosage exposures compared to infrequent high-dosage ones. The bivalve A. brasiliana and the polychaete L. culveri are more suitable sentinels due to their greater responsiveness to oil and also to their wider geographical distribution. Copyright © 2016 Elsevier B.V. All rights reserved.

Recolonization of macrofauna in unpolluted sands placed in a polluted yachting harbour: A field approach using experimental trays

NASA Astrophysics Data System (ADS)

Guerra-García, J. M.; García-Gómez, J. C.

2009-01-01

A field experiment using trays was conducted at Ceuta's yachting harbour, North Africa, to study the effect in recolonization of placing trays with unpolluted defaunate sediments (fine and gross sands with low contents of organic matter) inside an enclosed yachting harbour characterized by high percentages of silt and clay and high concentrations of organic matter. Sediment recolonization in the trays was mainly undertaken by the species living naturally at the yachting harbour, which recolonized both uncontaminated gross and fine sand trays (such as the crustaceans Corophium runcicorne, Corophium sextonae and Nebalia bipes, the mollusc Parvicardium exiguum and the polychaete Pseudomalacoceros tridentata). However, other species like the polychaetes Cirriformia tentaculata and Platynereis dumerilii, although also abundant in the yachting harbour, were unable to colonize the trays through transport of larvae and/or adults in the water column. The recolonization was very quick, and after the first month, the values of abundance, species richness, diversity and evenness were similar in the experimental trays and in the reference area (yachting harbour). Although the multivariate analysis showed that the species composition differed between the trays and the reference area, there were no significant differences in recolonization of gross and fine sands, indicating that other factors different from the granulometry are modulating the recolonization patterns.

Neural constraints on learning.

PubMed

Sadtler, Patrick T; Quick, Kristin M; Golub, Matthew D; Chase, Steven M; Ryu, Stephen I; Tyler-Kabara, Elizabeth C; Yu, Byron M; Batista, Aaron P

2014-08-28

Learning, whether motor, sensory or cognitive, requires networks of neurons to generate new activity patterns. As some behaviours are easier to learn than others, we asked if some neural activity patterns are easier to generate than others. Here we investigate whether an existing network constrains the patterns that a subset of its neurons is capable of exhibiting, and if so, what principles define this constraint. We employed a closed-loop intracortical brain-computer interface learning paradigm in which Rhesus macaques (Macaca mulatta) controlled a computer cursor by modulating neural activity patterns in the primary motor cortex. Using the brain-computer interface paradigm, we could specify and alter how neural activity mapped to cursor velocity. At the start of each session, we observed the characteristic activity patterns of the recorded neural population. The activity of a neural population can be represented in a high-dimensional space (termed the neural space), wherein each dimension corresponds to the activity of one neuron. These characteristic activity patterns comprise a low-dimensional subspace (termed the intrinsic manifold) within the neural space. The intrinsic manifold presumably reflects constraints imposed by the underlying neural circuitry. Here we show that the animals could readily learn to proficiently control the cursor using neural activity patterns that were within the intrinsic manifold. However, animals were less able to learn to proficiently control the cursor using activity patterns that were outside of the intrinsic manifold. These results suggest that the existing structure of a network can shape learning. On a timescale of hours, it seems to be difficult to learn to generate neural activity patterns that are not consistent with the existing network structure. These findings offer a network-level explanation for the observation that we are more readily able to learn new skills when they are related to the skills that we already possess.

Method and system for pattern analysis using a coarse-coded neural network

NASA Technical Reports Server (NTRS)

Spirkovska, Liljana (Inventor); Reid, Max B. (Inventor)

1994-01-01

A method and system for performing pattern analysis with a neural network coarse-coding a pattern to be analyzed so as to form a plurality of sub-patterns collectively defined by data. Each of the sub-patterns comprises sets of pattern data. The neural network includes a plurality fields, each field being associated with one of the sub-patterns so as to receive the sub-pattern data therefrom. Training and testing by the neural network then proceeds in the usual way, with one modification: the transfer function thresholds the value obtained from summing the weighted products of each field over all sub-patterns associated with each pattern being analyzed by the system.

A Reverse Taxonomic Approach to Assess Macrofaunal Distribution Patterns in Abyssal Pacific Polymetallic Nodule Fields

PubMed Central

Janssen, Annika; Kaiser, Stefanie; Meißner, Karin; Brenke, Nils; Menot, Lenaick; Martínez Arbizu, Pedro

2015-01-01

Heightened interest in the exploitation of deep seafloor minerals is raising questions on the consequences for the resident fauna. Assessing species ranges and determination of processes underlying current species distributions are prerequisites to conservation planning and predicting faunal responses to changing environmental conditions. The abyssal central Pacific nodule belt, located between the Clarion and Clipperton Fracture Zones (CCZ), is an area prospected for mining of polymetallic nodules. We examined variations in genetic diversity and broad-scale connectivity of isopods and polychaetes across the CCZ. Faunal assemblages were studied from two mining claims (the eastern German and French license areas) located 1300 km apart and influenced by different productivity regimes. Using a reverse taxonomy approach based on DNA barcoding, we tested to what extent distance and large-scale changes in environmental parameters lead to differentiation in two macrofaunal taxa exhibiting different functions and life-history patterns. A fragment of the mitochondrial gene Cytochrome Oxidase Subunit 1 (COI) was analyzed. At a 97% threshold the molecular operational taxonomic units (MOTUs) corresponded well to morphological species. Molecular analyses indicated high local and regional diversity mostly because of large numbers of singletons in the samples. Consequently, variation in composition of genotypic clusters between sites was exceedingly large partly due to paucity of deep-sea sampling and faunal patchiness. A higher proportion of wide-ranging species in polychaetes was contrasted with mostly restricted distributions in isopods. Remarkably, several cryptic lineages appeared to be sympatric and occurred in taxa with putatively good dispersal abilities, whereas some brooding lineages revealed broad distributions across the CCZ. Geographic distance could explain variation in faunal connectivity between regions and sites to some extent, while assumed dispersal capabilities were not as important. PMID:25671322

Folly Beach, South Carolina. Survey Report on Beach Erosion Control and Hurricane Protection. Appendixes.

DTIC Science & Technology

1979-08-01

horseshoe crabs, sand dollars and numerous clams and gastropod mollusks i,, the beach subtidal areas. In addition, several species of fish are conyionly...bacteria and protozoa. Most benthic animals such as crustaceans, bivalve and gastropod mollusks, and burrowing and tube-dwelling polychaete worms are...due to the continual ut :ftil tidal fJ a. . , ted sediment shifting. Inlet inhabitants onsist nos ,y 1 1.., itipods, and polychaetes which are adapted

The impact of fossil data on annelid phylogeny inferred from discrete morphological characters.

PubMed

Parry, Luke A; Edgecombe, Gregory D; Eibye-Jacobsen, Danny; Vinther, Jakob

2016-08-31

As a result of their plastic body plan, the relationships of the annelid worms and even the taxonomic makeup of the phylum have long been contentious. Morphological cladistic analyses have typically recovered a monophyletic Polychaeta, with the simple-bodied forms assigned to an early-diverging clade or grade. This is in stark contrast to molecular trees, in which polychaetes are paraphyletic and include clitellates, echiurans and sipunculans. Cambrian stem group annelid body fossils are complex-bodied polychaetes that possess well-developed parapodia and paired head appendages (palps), suggesting that the root of annelids is misplaced in morphological trees. We present a reinvestigation of the morphology of key fossil taxa and include them in a comprehensive phylogenetic analysis of annelids. Analyses using probabilistic methods and both equal- and implied-weights parsimony recover paraphyletic polychaetes and support the conclusion that echiurans and clitellates are derived polychaetes. Morphological trees including fossils depict two main clades of crown-group annelids that are similar, but not identical, to Errantia and Sedentaria, the fundamental groupings in transcriptomic analyses. Removing fossils yields trees that are often less resolved and/or root the tree in greater conflict with molecular topologies. While there are many topological similarities between the analyses herein and recent phylogenomic hypotheses, differences include the exclusion of Sipuncula from Annelida and the taxa forming the deepest crown-group divergences. © 2016 The Authors.

Mineralization of Alvinella polychaete tubes at hydrothermal vents.

PubMed

Georgieva, M N; Little, C T S; Ball, A D; Glover, A G

2015-03-01

Alvinellid polychaete worms form multilayered organic tubes in the hottest and most rapidly growing areas of deep-sea hydrothermal vent chimneys. Over short periods of time, these tubes can become entirely mineralized within this environment. Documenting the nature of this process in terms of the stages of mineralization, as well as the mineral textures and end products that result, is essential for our understanding of the fossilization of polychaetes at hydrothermal vents. Here, we report in detail the full mineralization of Alvinella spp. tubes collected from the East Pacific Rise, determined through the use of a wide range of imaging and analytical techniques. We propose a new model for tube mineralization, whereby mineralization begins as templating of tube layer and sublayer surfaces and results in fully mineralized tubes comprised of multiple concentric, colloform, pyrite bands. Silica appeared to preserve organic tube layers in some samples. Fine-scale features such as protein fibres, extracellular polymeric substances and two types of filamentous microbial colonies were also found to be well preserved within a subset of the tubes. The fully mineralized Alvinella spp. tubes do not closely resemble known ancient hydrothermal vent tube fossils, corroborating molecular evidence suggesting that the alvinellids are a relatively recent polychaete lineage. We also compare pyrite and silica preservation of organic tissues within hydrothermal vents to soft tissue preservation in sediments and hot springs. © 2014 The Authors. Geobiology Published by John Wiley & Sons Ltd.

Vibrational Analysis of Engine Components Using Neural-Net Processing and Electronic Holography

NASA Technical Reports Server (NTRS)

Decker, Arthur J.; Fite, E. Brian; Mehmed, Oral; Thorp, Scott A.

1997-01-01

The use of computational-model trained artificial neural networks to acquire damage specific information from electronic holograms is discussed. A neural network is trained to transform two time-average holograms into a pattern related to the bending-induced-strain distribution of the vibrating component. The bending distribution is very sensitive to component damage unlike the characteristic fringe pattern or the displacement amplitude distribution. The neural network processor is fast for real-time visualization of damage. The two-hologram limit makes the processor more robust to speckle pattern decorrelation. Undamaged and cracked cantilever plates serve as effective objects for testing the combination of electronic holography and neural-net processing. The requirements are discussed for using finite-element-model trained neural networks for field inspections of engine components. The paper specifically discusses neural-network fringe pattern analysis in the presence of the laser speckle effect and the performances of two limiting cases of the neural-net architecture.

Vibrational Analysis of Engine Components Using Neural-Net Processing and Electronic Holography

NASA Technical Reports Server (NTRS)

Decker, Arthur J.; Fite, E. Brian; Mehmed, Oral; Thorp, Scott A.

1998-01-01

The use of computational-model trained artificial neural networks to acquire damage specific information from electronic holograms is discussed. A neural network is trained to transform two time-average holograms into a pattern related to the bending-induced-strain distribution of the vibrating component. The bending distribution is very sensitive to component damage unlike the characteristic fringe pattern or the displacement amplitude distribution. The neural network processor is fast for real-time visualization of damage. The two-hologram limit makes the processor more robust to speckle pattern decorrelation. Undamaged and cracked cantilever plates serve as effective objects for testing the combination of electronic holography and neural-net processing. The requirements are discussed for using finite-element-model trained neural networks for field inspections of engine components. The paper specifically discusses neural-network fringe pattern analysis in the presence of the laser speckle effect and the performances of two limiting cases of the neural-net architecture.

Antioxidant capacity of polychaetes occurring at a natural CO2 vent system: Results of an in situ reciprocal transplant experiment.

PubMed

Ricevuto, E; Benedetti, M; Regoli, F; Spicer, J I; Gambi, M C

2015-12-01

Ocean acidification (OA) is occurring at a fast rate, resulting in changes of carbonate chemistry in the oceans and in lowering of the pH. Previous studies have documented significant changes in the antioxidant defenses of marine species in response to OA. Here, selected polychaete species, Platynereis dumerilii, Polyophthalmus pictus and Syllis prolifera, were sampled from a natural CO2 vent system (pH = 7.3) and from a non-venting 'control' site (pH = 8.1), and reciprocally transplanted in these areas for 30 days. Total antioxidant capacity toward different forms of oxyradicals was compared in native and transplanted polychaetes: the aim was to assess whether the environmental conditions at the vent site would act as a prooxidant stressor, and the capability of polychaetes to modulate their antioxidant capacity to counteract a varied oxyradicals formation. None of the investigated species enhanced the antioxidant potential during the experiment. A significant reduction of the capability to neutralize different forms of oxyradicals was observed in P. pictus and, partially, in S. prolifera when transplanted from control to naturally-acidified conditions. On the other hand, populations of P. dumerilii originating from the vent and of S. prolifera from both control and acidified sites, showed higher constitutive antioxidant efficiency toward peroxyl radicals and peroxynitrite, which may allow them to cope with short-term and chronic exposure to higher oxidative pressure without further enhancement of antioxidant defenses. Since low pH - high pCO2 is the greatest environmental difference between the control and the vent sites, we suggest that the pro-oxidant challenge due to such peculiarities may have different biological consequences in different polychaete species. Some appear more susceptible to oxidative effects, while others acquire a long term acclimatization to vent conditions through the enhancement of their basal antioxidant protection. Copyright © 2015 Elsevier Ltd. All rights reserved.

Neural Activity Patterns in the Human Brain Reflect Tactile Stickiness Perception.

PubMed

Kim, Junsuk; Yeon, Jiwon; Ryu, Jaekyun; Park, Jang-Yeon; Chung, Soon-Cheol; Kim, Sung-Phil

2017-01-01

Our previous human fMRI study found brain activations correlated with tactile stickiness perception using the uni-variate general linear model (GLM) (Yeon et al., 2017). Here, we conducted an in-depth investigation on neural correlates of sticky sensations by employing a multivoxel pattern analysis (MVPA) on the same dataset. In particular, we statistically compared multi-variate neural activities in response to the three groups of sticky stimuli: A supra-threshold group including a set of sticky stimuli that evoked vivid sticky perception; an infra-threshold group including another set of sticky stimuli that barely evoked sticky perception; and a sham group including acrylic stimuli with no physically sticky property. Searchlight MVPAs were performed to search for local activity patterns carrying neural information of stickiness perception. Similar to the uni-variate GLM results, significant multi-variate neural activity patterns were identified in postcentral gyrus, subcortical (basal ganglia and thalamus), and insula areas (insula and adjacent areas). Moreover, MVPAs revealed that activity patterns in posterior parietal cortex discriminated the perceptual intensities of stickiness, which was not present in the uni-variate analysis. Next, we applied a principal component analysis (PCA) to the voxel response patterns within identified clusters so as to find low-dimensional neural representations of stickiness intensities. Follow-up clustering analyses clearly showed separate neural grouping configurations between the Supra- and Infra-threshold groups. Interestingly, this neural categorization was in line with the perceptual grouping pattern obtained from the psychophysical data. Our findings thus suggest that different stickiness intensities would elicit distinct neural activity patterns in the human brain and may provide a neural basis for the perception and categorization of tactile stickiness.

Neural Activity Patterns in the Human Brain Reflect Tactile Stickiness Perception

PubMed Central

Kim, Junsuk; Yeon, Jiwon; Ryu, Jaekyun; Park, Jang-Yeon; Chung, Soon-Cheol; Kim, Sung-Phil

2017-01-01

Our previous human fMRI study found brain activations correlated with tactile stickiness perception using the uni-variate general linear model (GLM) (Yeon et al., 2017). Here, we conducted an in-depth investigation on neural correlates of sticky sensations by employing a multivoxel pattern analysis (MVPA) on the same dataset. In particular, we statistically compared multi-variate neural activities in response to the three groups of sticky stimuli: A supra-threshold group including a set of sticky stimuli that evoked vivid sticky perception; an infra-threshold group including another set of sticky stimuli that barely evoked sticky perception; and a sham group including acrylic stimuli with no physically sticky property. Searchlight MVPAs were performed to search for local activity patterns carrying neural information of stickiness perception. Similar to the uni-variate GLM results, significant multi-variate neural activity patterns were identified in postcentral gyrus, subcortical (basal ganglia and thalamus), and insula areas (insula and adjacent areas). Moreover, MVPAs revealed that activity patterns in posterior parietal cortex discriminated the perceptual intensities of stickiness, which was not present in the uni-variate analysis. Next, we applied a principal component analysis (PCA) to the voxel response patterns within identified clusters so as to find low-dimensional neural representations of stickiness intensities. Follow-up clustering analyses clearly showed separate neural grouping configurations between the Supra- and Infra-threshold groups. Interestingly, this neural categorization was in line with the perceptual grouping pattern obtained from the psychophysical data. Our findings thus suggest that different stickiness intensities would elicit distinct neural activity patterns in the human brain and may provide a neural basis for the perception and categorization of tactile stickiness. PMID:28936171

Loxosomella decorata n. sp., a new solitary entoproct from San Juan Island, WA, USA.

PubMed

Nielsen, Claus

2017-03-06

Several species of solitary entoprocts of the genera Loxosoma and Loxosomella occur on maldanid polychaetes or in their tubes (Nielsen 1964). New species turn up almost every time maldanids from new localities are studied, and the species described below has been the subject of a study of spiral cleavage (Merkel et al. 2012). This paper describes a new species of Loxosomella from tubes of the maldanid polychaete Axiothella rubrocincta (Johnson, 1901) from False Bay, San Juan Island, WA, USA.

Neural-Net Processing of Characteristic Patterns From Electronic Holograms of Vibrating Blades

NASA Technical Reports Server (NTRS)

Decker, Arthur J.

1999-01-01

Finite-element-model-trained artificial neural networks can be used to process efficiently the characteristic patterns or mode shapes from electronic holograms of vibrating blades. The models used for routine design may not yet be sufficiently accurate for this application. This document discusses the creation of characteristic patterns; compares model generated and experimental characteristic patterns; and discusses the neural networks that transform the characteristic patterns into strain or damage information. The current potential to adapt electronic holography to spin rigs, wind tunnels and engines provides an incentive to have accurate finite element models lor training neural networks.

Creative-Dynamics Approach To Neural Intelligence

NASA Technical Reports Server (NTRS)

Zak, Michail A.

1992-01-01

Paper discusses approach to mathematical modeling of artificial neural networks exhibiting complicated behaviors reminiscent of creativity and intelligence of biological neural networks. Neural network treated as non-Lipschitzian dynamical system - as described in "Non-Lipschitzian Dynamics For Modeling Neural Networks" (NPO-17814). System serves as tool for modeling of temporal-pattern memories and recognition of complicated spatial patterns.

The challenges of neural mind-reading paradigms.

PubMed

Vilarroya, Oscar

2013-01-01

Neural mind-reading studies, based on multivariate pattern analysis (MVPA) methods, are providing exciting new studies. Some of the results obtained with these paradigms have raised high expectations, such as the possibility of creating brain reading devices. However, such hopes are based on the assumptions that: (a) the BOLD signal is a marker of neural activity; (b) the BOLD pattern identified by a MVPA is a neurally sound pattern; (c) the MVPA's feature space is a good mapping of the neural representation of a stimulus, and (d) the pattern identified by a MVPA corresponds to a representation. I examine here the challenges that still have to be met before fully accepting such assumptions.

Neural Categorization of Vibrotactile Frequency in Flutter and Vibration Stimulations: An fMRI Study.

PubMed

Kim, Junsuk; Chung, Yoon Gi; Chung, Soon-Cheol; Bulthoff, Heinrich H; Kim, Sung-Phil

2016-01-01

As the use of wearable haptic devices with vibrating alert features is commonplace, an understanding of the perceptual categorization of vibrotactile frequencies has become important. This understanding can be substantially enhanced by unveiling how neural activity represents vibrotactile frequency information. Using functional magnetic resonance imaging (fMRI), this study investigated categorical clustering patterns of the frequency-dependent neural activity evoked by vibrotactile stimuli with gradually changing frequencies from 20 to 200 Hz. First, a searchlight multi-voxel pattern analysis (MVPA) was used to find brain regions exhibiting neural activities associated with frequency information. We found that the contralateral postcentral gyrus (S1) and the supramarginal gyrus (SMG) carried frequency-dependent information. Next, we applied multidimensional scaling (MDS) to find low-dimensional neural representations of different frequencies obtained from the multi-voxel activity patterns within these regions. The clustering analysis on the MDS results showed that neural activity patterns of 20-100 Hz and 120-200 Hz were divided into two distinct groups. Interestingly, this neural grouping conformed to the perceptual frequency categories found in the previous behavioral studies. Our findings therefore suggest that neural activity patterns in the somatosensory cortical regions may provide a neural basis for the perceptual categorization of vibrotactile frequency.

A temporal analysis on the dynamics of deep-sea macrofauna: Influence of environmental variability off Catalonia coasts (western Mediterranean)

NASA Astrophysics Data System (ADS)

Mamouridis, V.; Cartes, J. E.; Parra, S.; Fanelli, E.; Saiz Salinas, J. I.

2011-04-01

A seasonal analysis of deep-sea infauna (macrobenthos) based on quantitative sampling was conducted over the Catalan Sea slope, within the Besòs canyon (at ˜550-600 m) and on its adjacent slope (at 800 m). Both sites were sampled in February, April, June-July and October 2007. Environmental variables influencing faunal distribution were also recorded in the sediment and sediment/water interface. Dynamics of macrobenthos at the two stations showed differences in biomass/abundance patterns and trophic structures. Biomass was higher inside the Besòs canyon than on the adjacent slope. The community was mostly dominated by surface-deposit feeding polychaetes (Ampharetidae, Paraonidae, Flabelligeridae) and crustaceans (amphipods such as Carangoliopsis spinulosa and Harpinia spp.) inside the canyon, while subsurface deposit feeders (mainly the sipunculan Onchnesoma steenstrupii) were dominant over the adjacent slope. The taxonomic composition in the suprabenthic assemblages of polychaetes, collected on the adjacent slope by a suprabenthic sledge, was clearly different from that collected by the box-corer. The suprabenthic assemblage was dominated by carnivorous forms (mainly Harmothoe sp. and Nephthys spp.) and linked to higher near-bottom turbidity. Inside Besòs a clear temporal succession of species was related to both food availability and quality and the proliferation of opportunistic species was consistent with higher variability in food sources (TOC, C/N, δ 13C) in comparison to adjacent slope. This was likely caused by a greater influence of terrigenous inputs from river discharges. Inside the canyon, Capitellidae, Spionidae and Flabelligeridae, in general considered as deposit feeders, were more abundant in June-July coinciding with a clear signal of terrigenous carbon (depleted δ 13C, high C/N) in the sediments. By contrast, during October and under conditions of high water turbidity and increases of TOM, carnivorous polychaetes (Glyceridae, Onuphidae) increased. Total macrobenthos biomass found over Catalonian slopes were higher than that found in the neighboring Toulon canyon, probably because the two canyons are influenced by different river inputs, connected with distinct terrigenous sources.

Angle of Arrival Detection Through Artificial Neural Network Analysis of Optical Fiber Intensity Patterns

DTIC Science & Technology

1990-12-01

ARTIFICIAL NEURAL NETWORK ANALYSIS OF OPTICAL FIBER INTENSITY PATTERNS THESIS Scott Thomas Captain, USAF AFIT/GE/ENG/90D-62 DTIC...ELECTE ao • JAN08 1991 Approved for public release; distribution unlimited. AFIT/GE/ENG/90D-62 ANGLE OF ARRIVAL DETECTION THROUGH ARTIFICIAL NEURAL NETWORK ANALYSIS... ARTIFICIAL NEURAL NETWORK ANALYSIS OF OPTICAL FIBER INTENSITY PATTERNS L Introduction The optical sensors of United States Air Force reconnaissance

Acute stress evokes sexually dimorphic, stressor-specific patterns of neural activation across multiple limbic brain regions in adult rats.

PubMed

Sood, Ankit; Chaudhari, Karina; Vaidya, Vidita A

2018-03-01

Stress enhances the risk for psychiatric disorders such as anxiety and depression. Stress responses vary across sex and may underlie the heightened vulnerability to psychopathology in females. Here, we examined the influence of acute immobilization stress (AIS) and a two-day short-term forced swim stress (FS) on neural activation in multiple cortical and subcortical brain regions, implicated as targets of stress and in the regulation of neuroendocrine stress responses, in male and female rats using Fos as a neural activity marker. AIS evoked a sex-dependent pattern of neural activation within the cingulate and infralimbic subdivisions of the medial prefrontal cortex (mPFC), lateral septum (LS), habenula, and hippocampal subfields. The degree of neural activation in the mPFC, LS, and habenula was higher in males. Female rats exhibited reduced Fos positive cell numbers in the dentate gyrus hippocampal subfield, an effect not observed in males. We addressed whether the sexually dimorphic neural activation pattern noted following AIS was also observed with the short-term stress of FS. In the paraventricular nucleus of the hypothalamus and the amygdala, FS similar to AIS resulted in robust increases in neural activation in both sexes. The pattern of neural activation evoked by FS was distinct across sexes, with a heightened neural activation noted in the prelimbic mPFC subdivision and hippocampal subfields in females and differed from the pattern noted with AIS. This indicates that the sex differences in neural activation patterns observed within stress-responsive brain regions are dependent on the nature of stressor experience.

What Neural Substrates Trigger the Adept Scientific Pattern Discovery by Biologists?

ERIC Educational Resources Information Center

Lee, Jun-Ki; Kwon, Yong-Ju

2011-01-01

This study investigated the neural correlates of experts and novices during biological object pattern detection using an fMRI approach in order to reveal the neural correlates of a biologist's superior pattern discovery ability. Sixteen healthy male participants (8 biologists and 8 non-biologists) volunteered for the study. Participants were shown…

Oxygen, ecology, and the Cambrian radiation of animals

NASA Astrophysics Data System (ADS)

Sperling, Erik A.; Frieder, Christina A.; Raman, Akkur V.; Girguis, Peter R.; Levin, Lisa A.; Knoll, Andrew H.

2013-08-01

The Proterozoic-Cambrian transition records the appearance of essentially all animal body plans (phyla), yet to date no single hypothesis adequately explains both the timing of the event and the evident increase in diversity and disparity. Ecological triggers focused on escalatory predator-prey "arms races" can explain the evolutionary pattern but not its timing, whereas environmental triggers, particularly ocean/atmosphere oxygenation, do the reverse. Using modern oxygen minimum zones as an analog for Proterozoic oceans, we explore the effect of low oxygen levels on the feeding ecology of polychaetes, the dominant macrofaunal animals in deep-sea sediments. Here we show that low oxygen is clearly linked to low proportions of carnivores in a community and low diversity of carnivorous taxa, whereas higher oxygen levels support more complex food webs. The recognition of a physiological control on carnivory therefore links environmental triggers and ecological drivers, providing an integrated explanation for both the pattern and timing of Cambrian animal radiation.

Optimization of Training Sets For Neural-Net Processing of Characteristic Patterns From Vibrating Solids

NASA Technical Reports Server (NTRS)

Decker, Arthur J. (Inventor)

2006-01-01

An artificial neural network is disclosed that processes holography generated characteristic pattern of vibrating structures along with finite-element models. The present invention provides for a folding operation for conditioning training sets for optimally training forward-neural networks to process characteristic fringe pattern. The folding pattern increases the sensitivity of the feed-forward network for detecting changes in the characteristic pattern The folding routine manipulates input pixels so as to be scaled according to the location in an intensity range rather than the position in the characteristic pattern.

Dlx proteins position the neural plate border and determine adjacent cell fates.

PubMed

Woda, Juliana M; Pastagia, Julie; Mercola, Mark; Artinger, Kristin Bruk

2003-01-01

The lateral border of the neural plate is a major source of signals that induce primary neurons, neural crest cells and cranial placodes as well as provide patterning cues to mesodermal structures such as somites and heart. Whereas secreted BMP, FGF and Wnt proteins influence the differentiation of neural and non-neural ectoderm, we show here that members of the Dlx family of transcription factors position the border between neural and non-neural ectoderm and are required for the specification of adjacent cell fates. Inhibition of endogenous Dlx activity in Xenopus embryos with an EnR-Dlx homeodomain fusion protein expands the neural plate into non-neural ectoderm tissue whereas ectopic activation of Dlx target genes inhibits neural plate differentiation. Importantly, the stereotypic pattern of border cell fates in the adjacent ectoderm is re-established only under conditions where the expanded neural plate abuts Dlx-positive non-neural ectoderm. Experiments in which presumptive neural plate was grafted to ventral ectoderm reiterate induction of neural crest and placodal lineages and also demonstrate that Dlx activity is required in non-neural ectoderm for the production of signals needed for induction of these cells. We propose that Dlx proteins regulate intercellular signaling across the interface between neural and non-neural ectoderm that is critical for inducing and patterning adjacent cell fates.

Trophodynamic linkage between river runoff and coastal fishery yield elucidated by stable isotope data in the Gulf of Lions (NW Mediterranean).

PubMed

Darnaude, Audrey M; Salen-Picard, Chantal; Polunin, Nicholas V C; Harmelin-Vivien, Mireille L

2004-02-01

The link between climate-driven river runoff and sole fishery yields observed in the Gulf of Lions (NW Mediterranean) was analysed using carbon- and nitrogen stable isotopes along the flatfish food webs. Off the Rhone River, the main terrestrial (river POM) and marine (seawater POM) sources of carbon differed in delta(13)C (-26.11 per thousand and -22.36 per thousand, respectively). Surface sediment and suspended POM in plume water exhibited low delta(13)C (-24.38 per thousand and -24.70 per thousand, respectively) that differed more from the seawater POM than from river POM, demonstrating the dominance of terrestrial material in those carbon pools. Benthic invertebrates showed a wide range in delta(15)N (mean 4.30 per thousand to 9.77 per thousand ) and delta(13)C (mean -23.81 per thousand to -18.47 per thousand ), suggesting different trophic levels, diets and organic sources. Among the macroinvertebrates, the surface (mean delta(13)C -23.71 per thousand ) and subsurface (mean delta(13)C -23.81 per thousand ) deposit-feeding polychaetes were particularly (13)C depleted, indicating that their carbon was mainly derived from terrestrial material. In flatfish, delta(15)N (mean 9.42 to 10.93 per thousand ) and delta(13)C (mean -19.95 per thousand to -17.69 per thousand ) varied among species, indicating differences in food source and terrestrial POM use. A significant negative correlation was observed between the percentage by weight of polychaetes in the diet and the delta(13)C of flatfish white muscle. Solea solea (the main polychaete feeder) had the lowest mean delta(13)C, Arnoglossus laterna and Buglossidium luteum (crustacean, mollusc and polychaete feeders) had intermediate values, and Solea impar (mollusc feeder) and Citharus linguatula (crustacean and fish feeder) exhibited the highest delta(13)C. Two different benthic food webs were thus identified off the Rhone River, one based on marine planktonic carbon and the other on the terrestrial POM carried by the river. Deposit-feeding polychaetes were responsible for the main transfer of terrestrial POM to upper trophic levels, linking sole population dynamics to river runoff fluctuations.

Reconstitution of a Patterned Neural Tube from Single Mouse Embryonic Stem Cells.

PubMed

Ishihara, Keisuke; Ranga, Adrian; Lutolf, Matthias P; Tanaka, Elly M; Meinhardt, Andrea

2017-01-01

The recapitulation of tissue development and patterning in three-dimensional (3D) culture is an important dimension of stem cell research. Here, we describe a 3D culture protocol in which single mouse ES cells embedded in Matrigel under neural induction conditions clonally form a lumen containing, oval-shaped epithelial structure within 3 days. By Day 7 an apicobasally polarized neuroepithelium with uniformly dorsal cell identity forms. Treatment with retinoic acid at Day 2 results in posteriorization and self-organization of dorsal-ventral neural tube patterning. Neural tube organoid growth is also supported by pure laminin gels as well as poly(ethylene glycol) (PEG)-based artificial extracellular matrix hydrogels, which can be fine-tuned for key microenvironment characteristics. The rapid generation of a simple, patterned tissue in well-defined culture conditions makes the neural tube organoid a tractable model for studying neural stem cell self-organization.

Expression of the pair-rule gene homologs runt, Pax3/7, even-skipped-1 and even-skipped-2 during larval and juvenile development of the polychaete annelid Capitella teleta does not support a role in segmentation

PubMed Central

2012-01-01

Background Annelids and arthropods each possess a segmented body. Whether this similarity represents an evolutionary convergence or inheritance from a common segmented ancestor is the subject of ongoing investigation. Methods To investigate whether annelids and arthropods share molecular components that control segmentation, we isolated orthologs of the Drosophila melanogaster pair-rule genes, runt, paired (Pax3/7) and eve, from the polychaete annelid Capitella teleta and used whole mount in situ hybridization to characterize their expression patterns. Results When segments first appear, expression of the single C. teleta runt ortholog is only detected in the brain. Later, Ct-runt is expressed in the ventral nerve cord, foregut and hindgut. Analysis of Pax genes in the C. teleta genome reveals the presence of a single Pax3/7 ortholog. Ct-Pax3/7 is initially detected in the mid-body prior to segmentation, but is restricted to two longitudinal bands in the ventral ectoderm. Each of the two C. teleta eve orthologs has a unique and complex expression pattern, although there is partial overlap in several tissues. Prior to and during segment formation, Ct-eve1 and Ct-eve2 are both expressed in the bilaterial pair of mesoteloblasts, while Ct-eve1 is expressed in the descendant mesodermal band cells. At later stages, Ct-eve2 is expressed in the central and peripheral nervous system, and in mesoderm along the dorsal midline. In late stage larvae and adults, Ct-eve1 and Ct-eve2 are expressed in the posterior growth zone. Conclusions C. teleta eve, Pax3/7 and runt homologs all have distinct expression patterns and share expression domains with homologs from other bilaterians. None of the pair-rule orthologs examined in C. teleta exhibit segmental or pair-rule stripes of expression in the ectoderm or mesoderm, consistent with an independent origin of segmentation between annelids and arthropods. PMID:22510249

Antagonism between the transcription factors NANOG and OTX2 specifies rostral or caudal cell fate during neural patterning transition.

PubMed

Su, Zhenghui; Zhang, Yanqi; Liao, Baojian; Zhong, Xiaofen; Chen, Xin; Wang, Haitao; Guo, Yiping; Shan, Yongli; Wang, Lihui; Pan, Guangjin

2018-03-23

During neurogenesis, neural patterning is a critical step during which neural progenitor cells differentiate into neurons with distinct functions. However, the molecular determinants that regulate neural patterning remain poorly understood. Here we optimized the "dual SMAD inhibition" method to specifically promote differentiation of human pluripotent stem cells (hPSCs) into forebrain and hindbrain neural progenitor cells along the rostral-caudal axis. We report that neural patterning determination occurs at the very early stage in this differentiation. Undifferentiated hPSCs expressed basal levels of the transcription factor orthodenticle homeobox 2 (OTX2) that dominantly drove hPSCs into the "default" rostral fate at the beginning of differentiation. Inhibition of glycogen synthase kinase 3β (GSK3β) through CHIR99021 application sustained transient expression of the transcription factor NANOG at early differentiation stages through Wnt signaling. Wnt signaling and NANOG antagonized OTX2 and, in the later stages of differentiation, switched the default rostral cell fate to the caudal one. Our findings have uncovered a mutual antagonism between NANOG and OTX2 underlying cell fate decisions during neural patterning, critical for the regulation of early neural development in humans. © 2018 by The American Society for Biochemistry and Molecular Biology, Inc.

Resting-state hemodynamics are spatiotemporally coupled to synchronized and symmetric neural activity in excitatory neurons.

PubMed

Ma, Ying; Shaik, Mohammed A; Kozberg, Mariel G; Kim, Sharon H; Portes, Jacob P; Timerman, Dmitriy; Hillman, Elizabeth M C

2016-12-27

Brain hemodynamics serve as a proxy for neural activity in a range of noninvasive neuroimaging techniques including functional magnetic resonance imaging (fMRI). In resting-state fMRI, hemodynamic fluctuations have been found to exhibit patterns of bilateral synchrony, with correlated regions inferred to have functional connectivity. However, the relationship between resting-state hemodynamics and underlying neural activity has not been well established, making the neural underpinnings of functional connectivity networks unclear. In this study, neural activity and hemodynamics were recorded simultaneously over the bilateral cortex of awake and anesthetized Thy1-GCaMP mice using wide-field optical mapping. Neural activity was visualized via selective expression of the calcium-sensitive fluorophore GCaMP in layer 2/3 and 5 excitatory neurons. Characteristic patterns of resting-state hemodynamics were accompanied by more rapidly changing bilateral patterns of resting-state neural activity. Spatiotemporal hemodynamics could be modeled by convolving this neural activity with hemodynamic response functions derived through both deconvolution and gamma-variate fitting. Simultaneous imaging and electrophysiology confirmed that Thy1-GCaMP signals are well-predicted by multiunit activity. Neurovascular coupling between resting-state neural activity and hemodynamics was robust and fast in awake animals, whereas coupling in urethane-anesthetized animals was slower, and in some cases included lower-frequency (<0.04 Hz) hemodynamic fluctuations that were not well-predicted by local Thy1-GCaMP recordings. These results support that resting-state hemodynamics in the awake and anesthetized brain are coupled to underlying patterns of excitatory neural activity. The patterns of bilaterally-symmetric spontaneous neural activity revealed by wide-field Thy1-GCaMP imaging may depict the neural foundation of functional connectivity networks detected in resting-state fMRI.

Resting-state hemodynamics are spatiotemporally coupled to synchronized and symmetric neural activity in excitatory neurons

PubMed Central

Ma, Ying; Shaik, Mohammed A.; Kozberg, Mariel G.; Portes, Jacob P.; Timerman, Dmitriy

2016-01-01

Brain hemodynamics serve as a proxy for neural activity in a range of noninvasive neuroimaging techniques including functional magnetic resonance imaging (fMRI). In resting-state fMRI, hemodynamic fluctuations have been found to exhibit patterns of bilateral synchrony, with correlated regions inferred to have functional connectivity. However, the relationship between resting-state hemodynamics and underlying neural activity has not been well established, making the neural underpinnings of functional connectivity networks unclear. In this study, neural activity and hemodynamics were recorded simultaneously over the bilateral cortex of awake and anesthetized Thy1-GCaMP mice using wide-field optical mapping. Neural activity was visualized via selective expression of the calcium-sensitive fluorophore GCaMP in layer 2/3 and 5 excitatory neurons. Characteristic patterns of resting-state hemodynamics were accompanied by more rapidly changing bilateral patterns of resting-state neural activity. Spatiotemporal hemodynamics could be modeled by convolving this neural activity with hemodynamic response functions derived through both deconvolution and gamma-variate fitting. Simultaneous imaging and electrophysiology confirmed that Thy1-GCaMP signals are well-predicted by multiunit activity. Neurovascular coupling between resting-state neural activity and hemodynamics was robust and fast in awake animals, whereas coupling in urethane-anesthetized animals was slower, and in some cases included lower-frequency (<0.04 Hz) hemodynamic fluctuations that were not well-predicted by local Thy1-GCaMP recordings. These results support that resting-state hemodynamics in the awake and anesthetized brain are coupled to underlying patterns of excitatory neural activity. The patterns of bilaterally-symmetric spontaneous neural activity revealed by wide-field Thy1-GCaMP imaging may depict the neural foundation of functional connectivity networks detected in resting-state fMRI. PMID:27974609

Information Compression, Multiple Alignment, and the Representation and Processing of Knowledge in the Brain.

PubMed

Wolff, J Gerard

2016-01-01

The SP theory of intelligence , with its realization in the SP computer model , aims to simplify and integrate observations and concepts across artificial intelligence, mainstream computing, mathematics, and human perception and cognition, with information compression as a unifying theme. This paper describes how abstract structures and processes in the theory may be realized in terms of neurons, their interconnections, and the transmission of signals between neurons. This part of the SP theory- SP-neural -is a tentative and partial model for the representation and processing of knowledge in the brain. Empirical support for the SP theory-outlined in the paper-provides indirect support for SP-neural. In the abstract part of the SP theory (SP-abstract), all kinds of knowledge are represented with patterns , where a pattern is an array of atomic symbols in one or two dimensions. In SP-neural, the concept of a "pattern" is realized as an array of neurons called a pattern assembly , similar to Hebb's concept of a "cell assembly" but with important differences. Central to the processing of information in SP-abstract is information compression via the matching and unification of patterns (ICMUP) and, more specifically, information compression via the powerful concept of multiple alignment , borrowed and adapted from bioinformatics. Processes such as pattern recognition, reasoning and problem solving are achieved via the building of multiple alignments, while unsupervised learning is achieved by creating patterns from sensory information and also by creating patterns from multiple alignments in which there is a partial match between one pattern and another. It is envisaged that, in SP-neural, short-lived neural structures equivalent to multiple alignments will be created via an inter-play of excitatory and inhibitory neural signals. It is also envisaged that unsupervised learning will be achieved by the creation of pattern assemblies from sensory information and from the neural equivalents of multiple alignments, much as in the non-neural SP theory-and significantly different from the "Hebbian" kinds of learning which are widely used in the kinds of artificial neural network that are popular in computer science. The paper discusses several associated issues, with relevant empirical evidence.

Neural patterning of human induced pluripotent stem cells in 3-D cultures for studying biomolecule-directed differential cellular responses.

PubMed

Yan, Yuanwei; Bejoy, Julie; Xia, Junfei; Guan, Jingjiao; Zhou, Yi; Li, Yan

2016-09-15

Appropriate neural patterning of human induced pluripotent stem cells (hiPSCs) is critical to generate specific neural cells/tissues and even mini-brains that are physiologically relevant to model neurological diseases. However, the capacity of signaling factors that regulate 3-D neural tissue patterning in vitro and differential responses of the resulting neural populations to various biomolecules have not yet been fully understood. By tuning neural patterning of hiPSCs with small molecules targeting sonic hedgehog (SHH) signaling, this study generated different 3-D neuronal cultures that were mainly comprised of either cortical glutamatergic neurons or motor neurons. Abundant glutamatergic neurons were observed following the treatment with an antagonist of SHH signaling, cyclopamine, while Islet-1 and HB9-expressing motor neurons were enriched by an SHH agonist, purmorphamine. In neurons derived with different neural patterning factors, whole-cell patch clamp recordings showed similar voltage-gated Na(+)/K(+) currents, depolarization-evoked action potentials and spontaneous excitatory post-synaptic currents. Moreover, these different neuronal populations exhibited differential responses to three classes of biomolecules, including (1) matrix metalloproteinase inhibitors that affect extracellular matrix remodeling; (2) N-methyl-d-aspartate that induces general neurotoxicity; and (3) amyloid β (1-42) oligomers that cause neuronal subtype-specific neurotoxicity. This study should advance our understanding of hiPSC self-organization and neural tissue development and provide a transformative approach to establish 3-D models for neurological disease modeling and drug discovery. Appropriate neural patterning of human induced pluripotent stem cells (hiPSCs) is critical to generate specific neural cells, tissues and even mini-brains that are physiologically relevant to model neurological diseases. However, the capability of sonic hedgehog-related small molecules to tune different neuronal subtypes in 3-D differentiation from hiPSCs and the differential cellular responses of region-specific neuronal subtypes to various biomolecules have not been fully investigated. By tuning neural patterning of hiPSCs with small molecules targeting sonic hedgehog signaling, this study provides knowledge on the differential susceptibility of region-specific neuronal subtypes derived from hiPSCs to different biomolecules in extracellular matrix remodeling and neurotoxicity. The findings are significant for understanding 3-D neural patterning of hiPSCs for the applications in brain organoid formation, neurological disease modeling, and drug discovery. Copyright © 2016 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Automation of Some Operations of a Wind Tunnel Using Artificial Neural Networks

NASA Technical Reports Server (NTRS)

Decker, Arthur J.; Buggele, Alvin E.

1996-01-01

Artificial neural networks were used successfully to sequence operations in a small, recently modernized, supersonic wind tunnel at NASA-Lewis Research Center. The neural nets generated correct estimates of shadowgraph patterns, pressure sensor readings and mach numbers for conditions occurring shortly after startup and extending to fully developed flow. Artificial neural networks were trained and tested for estimating: sensor readings from shadowgraph patterns, shadowgraph patterns from shadowgraph patterns and sensor readings from sensor readings. The 3.81 by 10 in. (0.0968 by 0.254 m) tunnel was operated with its mach 2.0 nozzle, and shadowgraph was recorded near the nozzle exit. These results support the thesis that artificial neural networks can be combined with current workstation technology to automate wind tunnel operations.

Optimization of Training Sets for Neural-Net Processing of Characteristic Patterns from Vibrating Solids

NASA Technical Reports Server (NTRS)

Decker, Arthur J.

2001-01-01

Artificial neural networks have been used for a number of years to process holography-generated characteristic patterns of vibrating structures. This technology depends critically on the selection and the conditioning of the training sets. A scaling operation called folding is discussed for conditioning training sets optimally for training feed-forward neural networks to process characteristic fringe patterns. Folding allows feed-forward nets to be trained easily to detect damage-induced vibration-displacement-distribution changes as small as 10 nm. A specific application to aerospace of neural-net processing of characteristic patterns is presented to motivate the conditioning and optimization effort.

Dlx proteins position the neural plate border and determine adjacent cell fates

PubMed Central

Woda, Juliana M.; Pastagia, Julie; Mercola, Mark; Artinger, Kristin Bruk

2014-01-01

Summary The lateral border of the neural plate is a major source of signals that induce primary neurons, neural crest cells and cranial placodes as well as provide patterning cues to mesodermal structures such as somites and heart. Whereas secreted BMP, FGF and Wnt proteins influence the differentiation of neural and non-neural ectoderm, we show here that members of the Dlx family of transcription factors position the border between neural and non-neural ectoderm and are required for the specification of adjacent cell fates. Inhibition of endogenous Dlx activity in Xenopus embryos with an EnR-Dlx homeodomain fusion protein expands the neural plate into non-neural ectoderm tissue whereas ectopic activation of Dlx target genes inhibits neural plate differentiation. Importantly, the stereotypic pattern of border cell fates in the adjacent ectoderm is re-established only under conditions where the expanded neural plate abuts Dlx-positive non-neural ectoderm. Experiments in which presumptive neural plate was grafted to ventral ectoderm reiterate induction of neural crest and placodal lineages and also demonstrate that Dlx activity is required in non-neural ectoderm for the production of signals needed for induction of these cells. We propose that Dlx proteins regulate intercellular signaling across the interface between neural and non-neural ectoderm that is critical for inducing and patterning adjacent cell fates. PMID:12466200

Continuous monitoring of the lunar or Martian subsurface using on-board pattern recognition and neural processing of Rover geophysical data

NASA Technical Reports Server (NTRS)

Glass, Charles E.; Boyd, Richard V.; Sternberg, Ben K.

1991-01-01

The overall aim is to provide base technology for an automated vision system for on-board interpretation of geophysical data. During the first year's work, it was demonstrated that geophysical data can be treated as patterns and interpreted using single neural networks. Current research is developing an integrated vision system comprising neural networks, algorithmic preprocessing, and expert knowledge. This system is to be tested incrementally using synthetic geophysical patterns, laboratory generated geophysical patterns, and field geophysical patterns.

Patterns of synchrony for feed-forward and auto-regulation feed-forward neural networks.

PubMed

Aguiar, Manuela A D; Dias, Ana Paula S; Ferreira, Flora

2017-01-01

We consider feed-forward and auto-regulation feed-forward neural (weighted) coupled cell networks. In feed-forward neural networks, cells are arranged in layers such that the cells of the first layer have empty input set and cells of each other layer receive only inputs from cells of the previous layer. An auto-regulation feed-forward neural coupled cell network is a feed-forward neural network where additionally some cells of the first layer have auto-regulation, that is, they have a self-loop. Given a network structure, a robust pattern of synchrony is a space defined in terms of equalities of cell coordinates that is flow-invariant for any coupled cell system (with additive input structure) associated with the network. In this paper, we describe the robust patterns of synchrony for feed-forward and auto-regulation feed-forward neural networks. Regarding feed-forward neural networks, we show that only cells in the same layer can synchronize. On the other hand, in the presence of auto-regulation, we prove that cells in different layers can synchronize in a robust way and we give a characterization of the possible patterns of synchrony that can occur for auto-regulation feed-forward neural networks.

Deinterlacing using modular neural network

NASA Astrophysics Data System (ADS)

Woo, Dong H.; Eom, Il K.; Kim, Yoo S.

2004-05-01

Deinterlacing is the conversion process from the interlaced scan to progressive one. While many previous algorithms that are based on weighted-sum cause blurring in edge region, deinterlacing using neural network can reduce the blurring through recovering of high frequency component by learning process, and is found robust to noise. In proposed algorithm, input image is divided into edge and smooth region, and then, to each region, one neural network is assigned. Through this process, each neural network learns only patterns that are similar, therefore it makes learning more effective and estimation more accurate. But even within each region, there are various patterns such as long edge and texture in edge region. To solve this problem, modular neural network is proposed. In proposed modular neural network, two modules are combined in output node. One is for low frequency feature of local area of input image, and the other is for high frequency feature. With this structure, each modular neural network can learn different patterns with compensating for drawback of counterpart. Therefore it can adapt to various patterns within each region effectively. In simulation, the proposed algorithm shows better performance compared with conventional deinterlacing methods and single neural network method.

Variation in the macrofaunal community over large temporal and spatial scales in the southern Yellow Sea

NASA Astrophysics Data System (ADS)

Xu, Yong; Sui, Jixing; Yang, Mei; Sun, Yue; Li, Xinzheng; Wang, Hongfa; Zhang, Baolin

2017-09-01

To detect large, temporal- and spatial-scale variations in the macrofaunal community in the southern Yellow Sea, data collected along the western, middle and eastern regions of the southern Yellow Sea from 1958 to 2014 were organized and analyzed. Statistical methods such as cluster analysis, non-metric multidimensional scaling ordination (nMDS), permutational multivariate analysis of variance (PERMANOVA), redundancy analysis (RDA) and canonical correspondence analysis (CCA) were applied. The abundance of polychaetes increased in the western region but decreased in the eastern region from 1958 to 2014, whereas the abundance of echinoderms showed an opposite trend. For the entire macrofaunal community, Margalef's richness (d), the Shannon-Wiener index (H‧) and Pielou's evenness (J‧) were significantly lower in the eastern region when compared with the other two regions. No significant temporal differences were found for d and H‧, but there were significantly lower values of J‧ in 2014. Considerable variation in the macrofaunal community structure over the past several decades and among the geographical regions at the species, genus and family levels were observed. The species, genera and families that contributed to the temporal variation in each region were also identified. The most conspicuous pattern was the increase in the species Ophiura sarsii vadicola in the eastern region. In the western region, five polychaetes (Ninoe palmata, Notomastus latericeus, Paralacydonia paradoxa, Paraprionospio pinnata and Sternaspis scutata) increased consistently from 1958 to 2014. The dominance curves showed that both the species diversity and the dominance patterns were relatively stable in the western and middle regions. Environmental parameters such as depth, temperature and salinity could only partially explain the observed biological variation in the southern Yellow Sea. Anthropogenic activities such as demersal fishing and other unmeasured environmental variables may be more responsible for the long-term changes in the macrofaunal community.

Higher-Order Neural Networks Recognize Patterns

NASA Technical Reports Server (NTRS)

Reid, Max B.; Spirkovska, Lilly; Ochoa, Ellen

1996-01-01

Networks of higher order have enhanced capabilities to distinguish between different two-dimensional patterns and to recognize those patterns. Also enhanced capabilities to "learn" patterns to be recognized: "trained" with far fewer examples and, therefore, in less time than necessary to train comparable first-order neural networks.

Antenna analysis using neural networks

NASA Technical Reports Server (NTRS)

Smith, William T.

1992-01-01

Conventional computing schemes have long been used to analyze problems in electromagnetics (EM). The vast majority of EM applications require computationally intensive algorithms involving numerical integration and solutions to large systems of equations. The feasibility of using neural network computing algorithms for antenna analysis is investigated. The ultimate goal is to use a trained neural network algorithm to reduce the computational demands of existing reflector surface error compensation techniques. Neural networks are computational algorithms based on neurobiological systems. Neural nets consist of massively parallel interconnected nonlinear computational elements. They are often employed in pattern recognition and image processing problems. Recently, neural network analysis has been applied in the electromagnetics area for the design of frequency selective surfaces and beam forming networks. The backpropagation training algorithm was employed to simulate classical antenna array synthesis techniques. The Woodward-Lawson (W-L) and Dolph-Chebyshev (D-C) array pattern synthesis techniques were used to train the neural network. The inputs to the network were samples of the desired synthesis pattern. The outputs are the array element excitations required to synthesize the desired pattern. Once trained, the network is used to simulate the W-L or D-C techniques. Various sector patterns and cosecant-type patterns (27 total) generated using W-L synthesis were used to train the network. Desired pattern samples were then fed to the neural network. The outputs of the network were the simulated W-L excitations. A 20 element linear array was used. There were 41 input pattern samples with 40 output excitations (20 real parts, 20 imaginary). A comparison between the simulated and actual W-L techniques is shown for a triangular-shaped pattern. Dolph-Chebyshev is a different class of synthesis technique in that D-C is used for side lobe control as opposed to pattern shaping. The interesting thing about D-C synthesis is that the side lobes have the same amplitude. Five-element arrays were used. Again, 41 pattern samples were used for the input. Nine actual D-C patterns ranging from -10 dB to -30 dB side lobe levels were used to train the network. A comparison between simulated and actual D-C techniques for a pattern with -22 dB side lobe level is shown. The goal for this research was to evaluate the performance of neural network computing with antennas. Future applications will employ the backpropagation training algorithm to drastically reduce the computational complexity involved in performing EM compensation for surface errors in large space reflector antennas.

Antenna analysis using neural networks

NASA Astrophysics Data System (ADS)

Smith, William T.

1992-09-01

Conventional computing schemes have long been used to analyze problems in electromagnetics (EM). The vast majority of EM applications require computationally intensive algorithms involving numerical integration and solutions to large systems of equations. The feasibility of using neural network computing algorithms for antenna analysis is investigated. The ultimate goal is to use a trained neural network algorithm to reduce the computational demands of existing reflector surface error compensation techniques. Neural networks are computational algorithms based on neurobiological systems. Neural nets consist of massively parallel interconnected nonlinear computational elements. They are often employed in pattern recognition and image processing problems. Recently, neural network analysis has been applied in the electromagnetics area for the design of frequency selective surfaces and beam forming networks. The backpropagation training algorithm was employed to simulate classical antenna array synthesis techniques. The Woodward-Lawson (W-L) and Dolph-Chebyshev (D-C) array pattern synthesis techniques were used to train the neural network. The inputs to the network were samples of the desired synthesis pattern. The outputs are the array element excitations required to synthesize the desired pattern. Once trained, the network is used to simulate the W-L or D-C techniques. Various sector patterns and cosecant-type patterns (27 total) generated using W-L synthesis were used to train the network. Desired pattern samples were then fed to the neural network. The outputs of the network were the simulated W-L excitations. A 20 element linear array was used. There were 41 input pattern samples with 40 output excitations (20 real parts, 20 imaginary).

Orthogonal Patterns In A Binary Neural Network

NASA Technical Reports Server (NTRS)

Baram, Yoram

1991-01-01

Report presents some recent developments in theory of binary neural networks. Subject matter relevant to associate (content-addressable) memories and to recognition of patterns - both of considerable importance in advancement of robotics and artificial intelligence. When probed by any pattern, network converges to one of stored patterns.

Starting a DNA barcode reference library for shallow water polychaetes from the southern European Atlantic coast.

PubMed

Lobo, Jorge; Teixeira, Marcos A L; Borges, Luisa M S; Ferreira, Maria S G; Hollatz, Claudia; Gomes, Pedro T; Sousa, Ronaldo; Ravara, Ascensão; Costa, Maria H; Costa, Filipe O

2016-01-01

Annelid polychaetes have been seldom the focus of dedicated DNA barcoding studies, despite their ecological relevance and often dominance, particularly in soft-bottom estuarine and coastal marine ecosystems. Here, we report the first assessment of the performance of DNA barcodes in the discrimination of shallow water polychaete species from the southern European Atlantic coast, focusing on specimens collected in estuaries and coastal ecosystems of Portugal. We analysed cytochrome oxidase I DNA barcodes (COI-5P) from 164 specimens, which were assigned to 51 morphospecies. To our data set from Portugal, we added available published sequences selected from the same species, genus or family, to inspect for taxonomic congruence among studies and collection location. The final data set comprised 290 specimens and 79 morphospecies, which generated 99 Barcode Index Numbers (BINs) within Barcode of Life Data Systems (BOLD). Among these, 22 BINs were singletons, 47 other BINs were concordant, confirming the initial identification based on morphological characters, and 30 were discordant, most of which consisted on multiple BINs found for the same morphospecies. Some of the most prominent cases in the latter category include Hediste diversicolor (O.F. Müller, 1776) (7), Eulalia viridis (Linnaeus, 1767) (2) and Owenia fusiformis (delle Chiaje, 1844) (5), all of them reported from Portugal and frequently used in ecological studies as environmental quality indicators. Our results for these species showed discordance between molecular lineages and morphospecies, or added additional relatively divergent lineages. The potential inaccuracies in environmental assessments, where underpinning polychaete species diversity is poorly resolved or clarified, demand additional and extensive investigation of the DNA barcode diversity in this group, in parallel with alpha taxonomy efforts. © 2015 John Wiley & Sons Ltd.

Is polychaete family-level sufficient to assess impact on tropical estuarine gradients?

NASA Astrophysics Data System (ADS)

Nóbrega-Silva, Climélia; Patrício, Joana; Marques, João Carlos; Olímpio, Monalisa dos Santos; Farias, Jéssica Natyelle Barros; Molozzi, Joseline

2016-11-01

Regular, robust monitoring programs set up to assess the environmental conditions of aquatic systems often target different biological groups. And, of these, macroinvertebrate communities and particularly the class Polychaeta are frequently used. Identifying these organisms takes time, money and specialized expertise to ensure correct identification to the lowest possible taxonomic level. Identification errors can lead to an erroneous assessment. The concept of taxonomic sufficiency has been proposed both to minimize errors and to save time and money. This study tested the usefulness of this concept in tropical estuaries in northeast Brazil. We selected two transitional systems with different degrees of human impact due to different land uses and different conservation systems: the Mamanguape estuary, which is in an environmental conservation unit for sustainable use, and the highly impacted, urban Paraíba do Norte estuary. The results clearly showed that nutrient concentrations were markedly higher in the Paraíba do Norte estuary in the dry season and that the composition of the polychaete assemblages differed between the two estuaries as well as along the spatial gradient of each estuary. The use of either genus or family level led to equivalent representation in each system in terms of taxon richness and both the Margalef and Shannon-Wiener diversity indices. Both taxonomic levels described similar changes in the polychaete assemblage along the estuarine gradients. Based on our findings, the use of a coarser taxonomic level (i.e., family) is a good option when the aim is to implement a monitoring program in tropical estuaries with the polychaete assemblages as one of the target groups. This time-efficient taxonomic resolution can help improve sampling designs and allow long-term monitoring studies without losing much vital information.

Impaired growth in the polychaete Armandia brevis exposed to tributyltin in sediment.

PubMed

Meador, J P; Rice, C A

2001-03-01

Juveniles of the opheliid polychaete, Armandia brevis, were exposed to sediment-associated tributyltin (TBT) for 42 days to evaluate toxicity and bioaccumulation. Growth in this species was inhibited in a dose-response fashion by increasing concentrations of TBT. Even though the biota-sediment accumulation factor (BSAF) for TBT declined for the higher sediment concentrations, the total butyltins in tissue increased over all sediment concentrations. At the highest sediment concentrations, polychaetes bioaccumulated less TBT than expected, which was most likely due to reduced uptake and continued metabolism of the parent compound. The less than expected BSAF values exhibited by animals at the exposure concentrations causing severe effects are an important finding for assessing responses in the field. It appears that severe biological effects can occur in long-term experiments without the expected high tissue concentrations; an observation likely explained by altered toxicokinetics. Analysis of variance determined the lowest observed effect concentration for growth to be 191 ng/g sediment dry wt. for 21 days of exposure and 101 ng/g sediment dry wt. at day 42, indicating that 21 days was insufficient for delineating the steady-state toxicity response. When based on regression analysis, the sediment concentration causing a 25% inhibition in growth at 42 days exposure was 93 ng/g dry wt. (total organic carbon = 0.58%). A dose-response association was also determined for polychaete net weight and TBT in tissue. The tissue residue associated with a 25% reduction in growth was 2834 ng/g dry wt. at day 42. A comparison of these results with previous work indicates that juveniles are approximately three times more sensitive than adults to TBT exposure. The sediment concentrations affecting growth in this species are commonly found in urban waterways indicating potentially severe impacts for this and other sensitive species.

New species for the biomitigation of a super-intensive marine fish farm effluent: Combined use of polychaete-assisted sand filters and halophyte aquaponics.

PubMed

Marques, Bruna; Calado, Ricardo; Lillebø, Ana I

2017-12-01

The main objective of this study was to test an innovative biomitigation approach, where polychaete-assisted (Hediste diversicolor) sand filters were combined with the production of Halimione portulacoides in aquaponics, to remediate an organic-rich effluent generated by a super intensive fish farm operating a land-based RAS (Recirculating aquaculture system). The set up included four different experimental combinations that were periodically monitored for 5months. After this period, polychaete-assisted sand filters reduced in 70% the percentage of OM and the average densities increased from ≈400ind.m -2 to 7000ind.m -2 . H. portulacoides in aquaponics contributed to an average DIN (Dissolved inorganic Nitrogen) decrease of 65%, which increased to 67% when preceded by filter tanks stocked with polychaetes. From May until October (5months) halophytes biomass increased from 1.4kgm -2 ±0.7 (initial wet weight) to 18.6kgm -2 ±4.0. Bearing in mind that the uptake of carbon is mostly via photosynthesis and not though the uptake of dissolved inorganic carbon, this represents an approximate incorporation of ≈1.3kgm -2 carbon (C), ≈15gm -2 nitrogen (N) and ≈8gm -2 phosphorus (P) in the aerial part (76% of total biomass), and an approximate incorporation of ≈0.5kgm -2 carbon (C), ≈3gm -2 nitrogen (N) and ≈2gm -2 phosphorus (P) in the roots (24% of total biomass). In the present study, the potential of the two extractive species for biomitigation of a super-intensive marine fish farm effluent could be clearly demonstrated, contributing in this way to potentiate the implementation of more sustainable practices. Copyright © 2017 Elsevier B.V. All rights reserved.

Are Sediments a Source of Fukushima Radiocesium for Marine Fauna in Coastal Japan?

NASA Astrophysics Data System (ADS)

Wang, C.; Fisher, N. S.; Baumann, Z.

2016-02-01

The Fukushima nuclear power plant accident in 2011 resulted in the largest accidental release of artificial radionuclides into the world's oceans. Among the fission products released in large quantities, 137Cs has the greatest potential for long-term impacts on marine biota and human consumers of seafood. In particular, some species of bottom fish near Fukushima were very contaminated and had higher radiocesium (134Cs and 137Cs) levels than pelagic fish in the same area, sometimes exceeding Japanese safety limits >4 years after the accident. Benthic invertebrates, many being prey items for bottom fish, show the same slow decrease in radiocesium as sediments, suggesting that contaminated sediment could be a source of radiocesium for benthic fauna. We evaluated the binding of 137Cs to sediments (Kd found to be 44-60 ml g-1) and found that bioturbation by the polychaete Nereis succinea greatly increased the initial release rate of Cs to overlying seawater. We also assessed the bioavailability of dissolved and sediment-bound Cs for deposit-feeding polychaetes, and its subsequent transfer to crabs and fish, and measured the influence of water temperature on Cs accumulation in fish. Assimilation efficiency (AE) of ingested 137Cs ranged from 16% in polychaetes ingesting sediments to 79% in fish ingesting worms. Efflux rate constants ranged from 5% d-1 for killifish to 40% d-1 for polychaetes. Animal absorption and retention of dissolved 137Cs were also measured. These parameters are used to model radiocesium bioaccumulation and trophic transfer in benthic food chains. Our results are consistent with the idea that sediments can be an important source of Cs for benthic food chains and help explain why some species of bottom fish remained more contaminated than pelagic fish in Japanese coastal waters.

Pattern recognition neural-net by spatial mapping of biology visual field

NASA Astrophysics Data System (ADS)

Lin, Xin; Mori, Masahiko

2000-05-01

The method of spatial mapping in biology vision field is applied to artificial neural networks for pattern recognition. By the coordinate transform that is called the complex-logarithm mapping and Fourier transform, the input images are transformed into scale- rotation- and shift- invariant patterns, and then fed into a multilayer neural network for learning and recognition. The results of computer simulation and an optical experimental system are described.

An improved genetic algorithm for designing optimal temporal patterns of neural stimulation

NASA Astrophysics Data System (ADS)

Cassar, Isaac R.; Titus, Nathan D.; Grill, Warren M.

2017-12-01

Objective. Electrical neuromodulation therapies typically apply constant frequency stimulation, but non-regular temporal patterns of stimulation may be more effective and more efficient. However, the design space for temporal patterns is exceedingly large, and model-based optimization is required for pattern design. We designed and implemented a modified genetic algorithm (GA) intended for design optimal temporal patterns of electrical neuromodulation. Approach. We tested and modified standard GA methods for application to designing temporal patterns of neural stimulation. We evaluated each modification individually and all modifications collectively by comparing performance to the standard GA across three test functions and two biophysically-based models of neural stimulation. Main results. The proposed modifications of the GA significantly improved performance across the test functions and performed best when all were used collectively. The standard GA found patterns that outperformed fixed-frequency, clinically-standard patterns in biophysically-based models of neural stimulation, but the modified GA, in many fewer iterations, consistently converged to higher-scoring, non-regular patterns of stimulation. Significance. The proposed improvements to standard GA methodology reduced the number of iterations required for convergence and identified superior solutions.

Patterns recognition of electric brain activity using artificial neural networks

NASA Astrophysics Data System (ADS)

Musatov, V. Yu.; Pchelintseva, S. V.; Runnova, A. E.; Hramov, A. E.

2017-04-01

An approach for the recognition of various cognitive processes in the brain activity in the perception of ambiguous images. On the basis of developed theoretical background and the experimental data, we propose a new classification of oscillating patterns in the human EEG by using an artificial neural network approach. After learning of the artificial neural network reliably identified cube recognition processes, for example, left-handed or right-oriented Necker cube with different intensity of their edges, construct an artificial neural network based on Perceptron architecture and demonstrate its effectiveness in the pattern recognition of the EEG in the experimental.

Electronic system with memristive synapses for pattern recognition

PubMed Central

Park, Sangsu; Chu, Myonglae; Kim, Jongin; Noh, Jinwoo; Jeon, Moongu; Hun Lee, Byoung; Hwang, Hyunsang; Lee, Boreom; Lee, Byung-geun

2015-01-01

Memristive synapses, the most promising passive devices for synaptic interconnections in artificial neural networks, are the driving force behind recent research on hardware neural networks. Despite significant efforts to utilize memristive synapses, progress to date has only shown the possibility of building a neural network system that can classify simple image patterns. In this article, we report a high-density cross-point memristive synapse array with improved synaptic characteristics. The proposed PCMO-based memristive synapse exhibits the necessary gradual and symmetrical conductance changes, and has been successfully adapted to a neural network system. The system learns, and later recognizes, the human thought pattern corresponding to three vowels, i.e. /a /, /i /, and /u/, using electroencephalography signals generated while a subject imagines speaking vowels. Our successful demonstration of a neural network system for EEG pattern recognition is likely to intrigue many researchers and stimulate a new research direction. PMID:25941950

Wnt/Yes-Associated Protein Interactions During Neural Tissue Patterning of Human Induced Pluripotent Stem Cells.

PubMed

Bejoy, Julie; Song, Liqing; Zhou, Yi; Li, Yan

2018-04-01

Human induced pluripotent stem cells (hiPSCs) have special ability to self-assemble into neural spheroids or mini-brain-like structures. During the self-assembly process, Wnt signaling plays an important role in regional patterning and establishing positional identity of hiPSC-derived neural progenitors. Recently, the role of Wnt signaling in regulating Yes-associated protein (YAP) expression (nuclear or cytoplasmic), the pivotal regulator during organ growth and tissue generation, has attracted increasing interests. However, the interactions between Wnt and YAP expression for neural lineage commitment of hiPSCs remain poorly explored. The objective of this study is to investigate the effects of Wnt signaling and YAP expression on the cellular population in three-dimensional (3D) neural spheroids derived from hiPSCs. In this study, Wnt signaling was activated using CHIR99021 for 3D neural spheroids derived from human iPSK3 cells through embryoid body formation. Our results indicate that Wnt activation induces nuclear localization of YAP and upregulates the expression of HOXB4, the marker for hindbrain/spinal cord. By contrast, the cells exhibit more rostral forebrain neural identity (expression of TBR1) without Wnt activation. Cytochalasin D was then used to induce cytoplasmic YAP and the results showed the decreased HOXB4 expression. In addition, the incorporation of microparticles in the neural spheroids was investigated for the perturbation of neural patterning. This study may indicate the bidirectional interactions of Wnt signaling and YAP expression during neural tissue patterning, which have the significance in neurological disease modeling, drug screening, and neural tissue regeneration.

Characterization of the Trunk Neural Crest in the bamboo shark, Chiloscyllium punctatum

PubMed Central

Juarez, Marilyn; Reyes, Michelle; Coleman, Tiffany; Rotenstein, Lisa; Sao, Sothy; Martinez, Darwin; Jones, Matthew; Mackelprang, Rachel; de Bellard, Maria Elena

2013-01-01

The neural crest is a population of mesenchymal cells that after migrating from the neural tube give rise to a structures and cell-types: jaw, part of the peripheral ganglia and melanocytes. Although much is known about neural crest development in jawed vertebrates, a clear picture of trunk neural crest development for elasmobranchs is yet to be developed. Here we present a detailed study of trunk neural crest development in the bamboo shark, Chiloscyllium punctatum. Vital labeling with DiI and in situ hybridization using cloned Sox8 and Sox9 probes demonstrated that trunk neural crest cells follow a pattern similar to the migratory paths already described in zebrafish and amphibians. We found shark trunk neural crest along the rostral side of the somites, the ventromedial pathway, branchial arches, gut, sensory ganglia and nerves. Interestingly, Chiloscyllium punctatum Sox8 and Sox9 sequences aligned with vertebrate SoxE genes, but appeared to be more ancient than the corresponding vertebrate paralogs. The expression of these two SoxE genes in trunk neural crest cells, especially Sox9, matched the Sox10 migratory patterns observed in teleosts. Interestingly, we observed DiI cells and Sox9 labeling along the lateral line, suggesting that in C. punctatum, glial cells in the lateral line are likely of neural crest origin. Though this has been observed in other vertebrates, we are the first to show that the pattern is present in cartilaginous fishes. These findings demonstrate that trunk neural crest cell development in Chiloscyllium punctatum follows the same highly conserved migratory pattern observed in jawed vertebrates PMID:23640803

Introduction to Neural Networks.

DTIC Science & Technology

1992-03-01

parallel processing of information that can greatly reduce the time required to perform operations which are needed in pattern recognition. Neural network, Artificial neural network , Neural net, ANN.

Rediscovery and redescription of Leodice laurillardi (Quatrefages, 1866) comb. nov. (Annelida: Eunicidae)-a rare European polychaete or just an overlooked species?

PubMed

Arias, Andrés; Fernández-Álvarez, Fernando Á; Martins, Roberto; Anadón, Nuria

2015-06-04

The eunicid polychaete, Eunice laurillardi Quatrefages, 1866, originally described from the central Mediterranean, has been discovered on the northern Iberian Peninsula, constituting the first report of the species since its original description. The new specimens are compared with the type collection and the species is redescribed. Furthermore, the species is assigned to the genus Leodice Savigny in Lamarck, 1818, based on information provided by re-examination of type material and the newly collected specimens. A summary of the complex taxonomic history of the species and a discussion of its current status are also provided.

Individual specialization in a shorebird population with narrow foraging niche

NASA Astrophysics Data System (ADS)

Catry, Teresa; Alves, José A.; Gill, Jennifer A.; Gunnarsson, Tómas G.; Granadeiro, José P.

2014-04-01

Individual specialization in resource use is a widespread driver for intra-population trait variation, playing a crucial evolutionary role in free-living animals. We investigated the individual foraging specialization of Black-tailed Godwits (Limosa limosa islandica) during the wintering period. Godwits displayed distinct degrees of individual specialization in diet and microhabitat use, indicating the presence of both generalist and specialist birds. Females were overall more specialist than males, primarily consuming polychaetes. Specialist males consumed mainly bivalves, but some individuals also specialized on gastropods or polychaetes. Sexual dimorphism in bill length is probably important in determining the differences in specialization, as longer-billed individuals have access to deep-buried polychaetes inaccessible to most males. Different levels of specialization within the same sex, unrelated to bill length, were also found, suggesting that mechanisms other traits are involved in explaining individual specialization. Godwits specialized on bivalves achieved higher intake rates than non-specialist birds, supporting the idea that individual foraging choices or skills result in different short-term payoffs within the same population. Understanding whether short-term payoffs are good indicators of long-term fitness and how selection operates to favour the prevalence of specialist or generalist godwits is a major future challenge.

Chronic toxicity of phenanthrene to the marine polychaete worm, Nereis (Neanthes) arenaceodentata

DOE Office of Scientific and Technical Information (OSTI.GOV)

Emery, V.L. Jr.; Dillon, T.M.

1996-02-01

Polycyclic aromatic hydrocarbons (PAHs) are widely distributed in the environment. While environmental concentrations are generally below acutely, lethal levels, chronic, low level exposures may result in subtle sublethal effects. PAHs accumulate in bottom sediments and may represent a hazard to the benthos. Polychaetes are important members of this community. The objective of this study is to evaluate the chronic sublethal effects of one PAH, phenanthrene (PHN), on the polychaete worm, Nereis arenaceodentata. PHN was selected because of its high toxicity to marine invertebrates relative to other PAHs. The response of bivalves to heavy metals and other toxins has usually beenmore » determined by observing valve position. Since mussels close their valves to avoid noxious stimuli, experimental delivery of chemicals is uncertain. To obtain constant results. Preston employed plastic spacers to hold the valves apart. This obviates the observation of valve position as an index of response, and some other method is required. Electromyography of intact mussels is one such index, and is shown to be a simple, effective and quantitative measurement of activity. Experiments are reported on the effects of added mercury on salt water and fresh water species. Parts of this Nvork have appeared in brief form.« less

Functional biodiversity of marine soft-sediment polychaetes from two Mediterranean coastal areas in relation to environmental stress.

PubMed

Nasi, F; Nordström, M C; Bonsdorff, E; Auriemma, R; Cibic, T; Del Negro, P

2018-06-01

Biological Traits Analysis (BTA) was used to identify functional features of infaunal polychaete assemblages associated with contamination in two Italian coastal areas: the harbour of Trieste (Adriatic Sea) and the Mar Piccolo of Taranto (Ionian Sea). The analysis was performed on 103 taxa, collected at four stations in each area. The two areas differed in species composition. The low diversity and the presence of stress-tolerant species in more polluted sites were not reflected in functional diversity, due to species contributing little to community functions or being functionally redundant. Sand and clay fractions were significant drivers of trait category expressions, however other environmental parameters (depth, total organic carbon and nitrogen, and Hg in sediments) influenced traits composition. Motile was the prevalent trait in environments with coarse sediments, and tube-builder were related to fine-grained ones. Motile, endobenthic and burrower were essential traits for living in contaminated sediments. Epibenthic and sessile polychaetes dominated at stations subjected to high organic loads. BTA offers an integrative approach to detect functional adaptations to contaminated sediments and multiple anthropogenic stressors. Copyright © 2018 Elsevier Ltd. All rights reserved.

Polychaetes of an artificial reef in the central mediterranean sea

NASA Astrophysics Data System (ADS)

Gravina, M. F.; Ardizzone, G. D.; Belluscio, A.

1989-02-01

The development of a polychaete community over five years on a man-made reef was analyzed. The reef was composed of 280 concrete blocks (2 × 2 × 2 m) and located in the Tyrrhenian Sea (Italy) 1.5 miles offshore and 12-14 m deep. Sixty-three species were collected—serpulids, nereids and cirratulids being the most abundant families. Ordination by Principal Components Analysis (PCA) technique showed three main stages in the colonization process: a pioneer phase, when mainly serpulids ( Pomatoceros triqueter, P. lamarckii, Hydroides pseuduncinata) occurred; a second phase, characterized by mussel ( Mytilus galloprovincialis) dominance and a more differentiated community structure with a lot of new species especially recurring on hard bottom ( Serpula concharum, H. dianthus, Ceratonereis costae); and a third phase, with an alteration of the substratum through soft deposits and the polychaete community characterized by also the occurrence of soft bottom species ( Heteromastus filiformis, Polydora ciliata, Dorvillea rubrovittata). From the trophic point of view, the structure of the community changed from dominance by filter feeders (97%) to a more differentiated situation with abundant detritic feeders ( c. 20%). The rates of immigration and extinction and the colonization curve showed that an actual stable steady-state was not reached.

Uptake and loss of dissolved 109Cd and 75Se in estuarine macroinvertebrates.

PubMed

Alquezar, Ralph; Markich, Scott J; Twining, John R

2007-04-01

Semaphore crabs (Heloecius cordiformis), soldier crabs (Mictyris platycheles), ghost shrimps (Trypaea australiensis), pygmy mussels (Xenostrobus securis), and polychaetes (Eunice sp.), key benthic prey items of predatory fish commonly found in estuaries throughout southeastern Australia, were exposed to dissolved (109)Cd and (75)Se for 385 h at 30 k Bq/l (uptake phase), followed by exposure to radionuclide-free water for 189 h (loss phase). The whole body uptake rates of (75)Se by pygmy mussels, semaphore crabs and soldier crabs were 1.9, 2.4 and 4.1 times higher than (109)Cd, respectively. There were no significant (P>0.05) differences between the uptake rates of (75)Se and (109)Cd for ghost shrimps and polychaetes. The uptake rates of (109)Cd and (75)Se were highest in pygmy mussels; about six times higher than in soldier crabs for (109)Cd and in polychaetes for (75)Se - the organisms with the lowest uptake rates. The loss rates of (109)Cd and (75)Se were highest in semaphore crabs; about four times higher than in polychaetes for (109)Cd and nine times higher than in ghost shrimps for (75)Se - the organisms with the lowest loss rates. The loss of (109)Cd and (75)Se in all organisms was best described by a two (i.e. short and a longer-lived) compartment model. In the short-lived, or rapidly exchanging, compartment, the biological half-lives of (75)Se (16-39 h) were about three times greater than those of (109)Cd (5-12h). In contrast, the biological half-lives of (109)Cd in the longer-lived, or slowly exchanging compartment(s), were typically greater (1370-5950 h) than those of (75)Se (161-1500 h). Semaphore crabs had the shortest biological half-lives of both radionuclides in the long-lived compartment, whereas polychaetes had the greatest biological half-life for (109)Cd (5950 h), and ghost shrimps had the greatest biological half-life for (75)Se (1500 h). This study provides the first reported data for the biological half-lives of Se in estuarine decapod crustaceans. Moreover, it emphasises the importance of determining metal(loid) accumulation and loss kinetics in keystone prey items, which consequently influences their trophic transfer potential to higher-order predators.

Physical habitat predictors of Manayunkia speciosa distribution in the Klamath River and implications for management of Ceratomyxa shasta, a parasite with a complex life cycle

NASA Astrophysics Data System (ADS)

Jordan, M. S.; Alexander, J. D.; Grant, G. E.; Bartholomew, J. L.

2011-12-01

Management strategies for parasites with complex life cycles may target not the parasite itself, but one of the alternate hosts. One approach is to decrease habitat for the alternate host, and in river systems flow manipulations may be employed. Two-dimensional hydraulic models can be powerful tools for predicting the relationship between flow alterations and changes in physical habit, however they require a rigorous definition of physical habitat for the organism of interest. We present habitat characterization data for the case of the alternate host of a salmonid parasite and introduce how it will be used in conjunction with a 2-dimensional hydraulic model. Ceratomyxa shasta is a myxozoan parasite of salmonids that requires a freshwater polychaete Manayunkia speciosa to complete its life cycle. Manayunkia speciosa is a small (3mm) benthic filter-feeding worm that attaches itself perpendicularly to substrate through construction of a flexible tube. In the Klamath River, CA/OR, C. shasta causes significant juvenile salmon mortality, imposing social and economic losses on commercial, sport and tribal fisheries. An interest in manipulating habitat for the polychaete host to decrease the abundance of C. shasta has therefore developed. Unfortunately, there are limited data on the habitat requirements of M. speciosa or the influence of streamflow regime and hydraulics on population dynamics and infection prevalence. This work aims to address these data needs by identifying physical habitat variables that influence the distribution of M. speciosa and determining the relationship between those variables, M. speciosa population density, and C. shasta infection prevalence. Biological samples were collected from nine sites representing three river features (runs, pools, and eddies) within the Klamath River during the summer and fall of 2010 and 2011. Environmental data including depth, velocity, and substrate, were collected at each polychaete sampling location. We tested for differences in environmental variables and polychaete densities among months and river features. Preliminary data suggest differences in density among months and river features as well as relationships among density and water velocity and substrate type. Polychaetes are currently being assayed for C. shasta infection, which will ultimately be included in our analyses. The data will subsequently be used in conjunction with a 2-dimensional hydraulic model to evaluate habitat stability and the influence of varied streamflow senarios.

Information Compression, Multiple Alignment, and the Representation and Processing of Knowledge in the Brain

PubMed Central

Wolff, J. Gerard

2016-01-01

The SP theory of intelligence, with its realization in the SP computer model, aims to simplify and integrate observations and concepts across artificial intelligence, mainstream computing, mathematics, and human perception and cognition, with information compression as a unifying theme. This paper describes how abstract structures and processes in the theory may be realized in terms of neurons, their interconnections, and the transmission of signals between neurons. This part of the SP theory—SP-neural—is a tentative and partial model for the representation and processing of knowledge in the brain. Empirical support for the SP theory—outlined in the paper—provides indirect support for SP-neural. In the abstract part of the SP theory (SP-abstract), all kinds of knowledge are represented with patterns, where a pattern is an array of atomic symbols in one or two dimensions. In SP-neural, the concept of a “pattern” is realized as an array of neurons called a pattern assembly, similar to Hebb's concept of a “cell assembly” but with important differences. Central to the processing of information in SP-abstract is information compression via the matching and unification of patterns (ICMUP) and, more specifically, information compression via the powerful concept of multiple alignment, borrowed and adapted from bioinformatics. Processes such as pattern recognition, reasoning and problem solving are achieved via the building of multiple alignments, while unsupervised learning is achieved by creating patterns from sensory information and also by creating patterns from multiple alignments in which there is a partial match between one pattern and another. It is envisaged that, in SP-neural, short-lived neural structures equivalent to multiple alignments will be created via an inter-play of excitatory and inhibitory neural signals. It is also envisaged that unsupervised learning will be achieved by the creation of pattern assemblies from sensory information and from the neural equivalents of multiple alignments, much as in the non-neural SP theory—and significantly different from the “Hebbian” kinds of learning which are widely used in the kinds of artificial neural network that are popular in computer science. The paper discusses several associated issues, with relevant empirical evidence. PMID:27857695

Fractal Patterns of Neural Activity Exist within the Suprachiasmatic Nucleus and Require Extrinsic Network Interactions

PubMed Central

Hu, Kun; Meijer, Johanna H.; Shea, Steven A.; vanderLeest, Henk Tjebbe; Pittman-Polletta, Benjamin; Houben, Thijs; van Oosterhout, Floor; Deboer, Tom; Scheer, Frank A. J. L.

2012-01-01

The mammalian central circadian pacemaker (the suprachiasmatic nucleus, SCN) contains thousands of neurons that are coupled through a complex network of interactions. In addition to the established role of the SCN in generating rhythms of ∼24 hours in many physiological functions, the SCN was recently shown to be necessary for normal self-similar/fractal organization of motor activity and heart rate over a wide range of time scales—from minutes to 24 hours. To test whether the neural network within the SCN is sufficient to generate such fractal patterns, we studied multi-unit neural activity of in vivo and in vitro SCNs in rodents. In vivo SCN-neural activity exhibited fractal patterns that are virtually identical in mice and rats and are similar to those in motor activity at time scales from minutes up to 10 hours. In addition, these patterns remained unchanged when the main afferent signal to the SCN, namely light, was removed. However, the fractal patterns of SCN-neural activity are not autonomous within the SCN as these patterns completely broke down in the isolated in vitro SCN despite persistence of circadian rhythmicity. Thus, SCN-neural activity is fractal in the intact organism and these fractal patterns require network interactions between the SCN and extra-SCN nodes. Such a fractal control network could underlie the fractal regulation observed in many physiological functions that involve the SCN, including motor control and heart rate regulation. PMID:23185285

Improvement of the Hopfield Neural Network by MC-Adaptation Rule

NASA Astrophysics Data System (ADS)

Zhou, Zhen; Zhao, Hong

2006-06-01

We show that the performance of the Hopfield neural networks, especially the quality of the recall and the capacity of the effective storing, can be greatly improved by making use of a recently presented neural network designing method without altering the whole structure of the network. In the improved neural network, a memory pattern is recalled exactly from initial states having a given degree of similarity with the memory pattern, and thus one can avoids to apply the overlap criterion as carried out in the Hopfield neural networks.

Two-year temporal response of benthic macrofauna and sediments to hypoxia in a tropical semi-enclosed bay (Cienfuegos, Cuba).

PubMed

Díaz Asencio, Lisbet; Helguera, Yusmila; Fernández-Garcés, Raúl; Gómez-Batista, Miguel; Rosell, Guillermo; Hernández, Yurisbey; Pulido, Anabell; Armenteros, Maickel

2016-03-01

Hypoxia is the depletion of dissolved oxygen below 2 mg O(2)/L. Relatively few studies on hypoxia and its effects on benthic macrofauna have been done in tropical marine ecosystems. This study describes the temporal response of the water column, sediments and macrofauna to seasonal hypoxia in a semi-enclosed bay (Cienfuegos, Caribbean Sea). The Calisito site was sampled monthly from June 2010 until February 2012, yielding 21 sampling times. At each sampling event water and sediment samples were collected for measuring the abiotic variables (temperature, salinity, dissolved oxygen, nutrients, redox potential discontinuity, silt/clay and organic matter content) and macrofauna (abundance and species richness). Temperature and surface salinity followed a typical temporal pattern during the summer/rainy and the winter/dry periods. Salinity stratification occurred in the rainy period, lasting three months in 2010 and six months in 2011. The bottom water dissolved oxygen indicated hypoxic and anoxic events during the wet periods of 2010 and 2011 associated with salinity stratification, low hydrodynamics and oxidation of the accumulated organic matter. Over the study period, 817 individuals were collected and identified. Polychaetes were the dominant group in terms of abundance (57 % of total) followed by mollusks (41%). Hypoxia (and occasionally anoxia) caused strong deleterious effects on the abundance and species richness of macrofaunal communities in the study site. The most abundant polychaetes were opportunistic species with high tolerance to hypoxic conditions: Prionospio steenstrupi, Polydora sp.and Paraprionospio pinnata. Most of them colonized relatively fast once hypoxia ended. Persistent species such as Caecum pulchellum and Parvanachis obesa were present during hypoxia with fluctuating densities and apparently recover to higher abundances when normoxic conditions are re-established. Macoma tenta and Tellina consobrina colonized approximately 1-2 months later than the first polychaete peak during normoxia. Probably, the deleterious effects of hypoxia on the macrofauna were intensified by negative interspecific relationships such as competition by suitable space and predation. The recolonization of macrofauna depended possibly on local transport by currents within the bay because the connection with the Caribbean Sea is relatively limited. In summary, seasonal hypoxia in Cienfuegos Bay influences the water and sediment geochemistry and reduces both the abundance and diversity of macrofauna.

Neural Networks for the Beginner.

ERIC Educational Resources Information Center

Snyder, Robin M.

Motivated by the brain, neural networks are a right-brained approach to artificial intelligence that is used to recognize patterns based on previous training. In practice, one would not program an expert system to recognize a pattern and one would not train a neural network to make decisions from rules; but one could combine the best features of…

Development of a computational model on the neural activity patterns of a visual working memory in a hierarchical feedforward Network

NASA Astrophysics Data System (ADS)

An, Soyoung; Choi, Woochul; Paik, Se-Bum

2015-11-01

Understanding the mechanism of information processing in the human brain remains a unique challenge because the nonlinear interactions between the neurons in the network are extremely complex and because controlling every relevant parameter during an experiment is difficult. Therefore, a simulation using simplified computational models may be an effective approach. In the present study, we developed a general model of neural networks that can simulate nonlinear activity patterns in the hierarchical structure of a neural network system. To test our model, we first examined whether our simulation could match the previously-observed nonlinear features of neural activity patterns. Next, we performed a psychophysics experiment for a simple visual working memory task to evaluate whether the model could predict the performance of human subjects. Our studies show that the model is capable of reproducing the relationship between memory load and performance and may contribute, in part, to our understanding of how the structure of neural circuits can determine the nonlinear neural activity patterns in the human brain.

The Neural Border: Induction, Specification and Maturation of the territory that generates Neural Crest cells.

PubMed

Pla, Patrick; Monsoro-Burq, Anne H

2018-05-28

The neural crest is induced at the edge between the neural plate and the nonneural ectoderm, in an area called the neural (plate) border, during gastrulation and neurulation. In recent years, many studies have explored how this domain is patterned, and how the neural crest is induced within this territory, that also participates to the prospective dorsal neural tube, the dorsalmost nonneural ectoderm, as well as placode derivatives in the anterior area. This review highlights the tissue interactions, the cell-cell signaling and the molecular mechanisms involved in this dynamic spatiotemporal patterning, resulting in the induction of the premigratory neural crest. Collectively, these studies allow building a complex neural border and early neural crest gene regulatory network, mostly composed by transcriptional regulations but also, more recently, including novel signaling interactions. Copyright © 2018. Published by Elsevier Inc.

Oxygen, ecology, and the Cambrian radiation of animals

PubMed Central

Sperling, Erik A.; Frieder, Christina A.; Raman, Akkur V.; Girguis, Peter R.; Levin, Lisa A.; Knoll, Andrew H.

2013-01-01

The Proterozoic-Cambrian transition records the appearance of essentially all animal body plans (phyla), yet to date no single hypothesis adequately explains both the timing of the event and the evident increase in diversity and disparity. Ecological triggers focused on escalatory predator–prey “arms races” can explain the evolutionary pattern but not its timing, whereas environmental triggers, particularly ocean/atmosphere oxygenation, do the reverse. Using modern oxygen minimum zones as an analog for Proterozoic oceans, we explore the effect of low oxygen levels on the feeding ecology of polychaetes, the dominant macrofaunal animals in deep-sea sediments. Here we show that low oxygen is clearly linked to low proportions of carnivores in a community and low diversity of carnivorous taxa, whereas higher oxygen levels support more complex food webs. The recognition of a physiological control on carnivory therefore links environmental triggers and ecological drivers, providing an integrated explanation for both the pattern and timing of Cambrian animal radiation. PMID:23898193

Digital micromirror based near-infrared illumination system for plasmonic photothermal neuromodulation.

PubMed

Jung, Hyunjun; Kang, Hongki; Nam, Yoonkey

2017-06-01

Light-mediated neuromodulation techniques provide great advantages to investigate neuroscience due to its high spatial and temporal resolution. To generate a spatial pattern of neural activity, it is necessary to develop a system for patterned-light illumination to a specific area. Digital micromirror device (DMD) based patterned illumination system have been used for neuromodulation due to its simple configuration and design flexibility. In this paper, we developed a patterned near-infrared (NIR) illumination system for region specific photothermal manipulation of neural activity using NIR-sensitive plasmonic gold nanorods (GNRs). The proposed system had high power transmission efficiency for delivering power density up to 19 W/mm 2 . We used a GNR-coated microelectrode array (MEA) to perform biological experiments using E18 rat hippocampal neurons and showed that it was possible to inhibit neural spiking activity of specific area in neural circuits with the patterned NIR illumination. This patterned NIR illumination system can serve as a promising neuromodulation tool to investigate neuroscience in a wide range of physiological and clinical applications.

Optical computing and neural networks; Proceedings of the Meeting, National Chiao Tung Univ., Hsinchu, Taiwan, Dec. 16, 17, 1992

NASA Technical Reports Server (NTRS)

Hsu, Ken-Yuh (Editor); Liu, Hua-Kuang (Editor)

1992-01-01

The present conference discusses optical neural networks, photorefractive nonlinear optics, optical pattern recognition, digital and analog processors, and holography and its applications. Attention is given to bifurcating optical information processing, neural structures in digital halftoning, an exemplar-based optical neural net classifier for color pattern recognition, volume storage in photorefractive disks, and microlaser-based compact optical neuroprocessors. Also treated are the optical implementation of a feature-enhanced optical interpattern-associative neural network model and its optical implementation, an optical pattern binary dual-rail logic gate module, a theoretical analysis for holographic associative memories, joint transform correlators, image addition and subtraction via the Talbot effect, and optical wavelet-matched filters. (No individual items are abstracted in this volume)

Optical computing and neural networks; Proceedings of the Meeting, National Chiao Tung Univ., Hsinchu, Taiwan, Dec. 16, 17, 1992

NASA Astrophysics Data System (ADS)

Hsu, Ken-Yuh; Liu, Hua-Kuang

The present conference discusses optical neural networks, photorefractive nonlinear optics, optical pattern recognition, digital and analog processors, and holography and its applications. Attention is given to bifurcating optical information processing, neural structures in digital halftoning, an exemplar-based optical neural net classifier for color pattern recognition, volume storage in photorefractive disks, and microlaser-based compact optical neuroprocessors. Also treated are the optical implementation of a feature-enhanced optical interpattern-associative neural network model and its optical implementation, an optical pattern binary dual-rail logic gate module, a theoretical analysis for holographic associative memories, joint transform correlators, image addition and subtraction via the Talbot effect, and optical wavelet-matched filters. (No individual items are abstracted in this volume)

Temporal pattern processing in songbirds.

PubMed

Comins, Jordan A; Gentner, Timothy Q

2014-10-01

Understanding how the brain perceives, organizes and uses patterned information is directly related to the neurobiology of language. Given the present limitations, such knowledge at the scale of neurons, neural circuits and neural populations can only come from non-human models, focusing on shared capacities that are relevant to language processing. Here we review recent advances in the behavioral and neural basis of temporal pattern processing of natural auditory communication signals in songbirds, focusing on European starlings. We suggest a general inhibitory circuit for contextual modulation that can act to control sensory representations based on patterning rules. Copyright © 2014. Published by Elsevier Ltd.

Bioprinting for Neural Tissue Engineering.

PubMed

Knowlton, Stephanie; Anand, Shivesh; Shah, Twisha; Tasoglu, Savas

2018-01-01

Bioprinting is a method by which a cell-encapsulating bioink is patterned to create complex tissue architectures. Given the potential impact of this technology on neural research, we review the current state-of-the-art approaches for bioprinting neural tissues. While 2D neural cultures are ubiquitous for studying neural cells, 3D cultures can more accurately replicate the microenvironment of neural tissues. By bioprinting neuronal constructs, one can precisely control the microenvironment by specifically formulating the bioink for neural tissues, and by spatially patterning cell types and scaffold properties in three dimensions. We review a range of bioprinted neural tissue models and discuss how they can be used to observe how neurons behave, understand disease processes, develop new therapies and, ultimately, design replacement tissues. Copyright © 2017 Elsevier Ltd. All rights reserved.

Resting-state brain activity in the motor cortex reflects task-induced activity: A multi-voxel pattern analysis.

PubMed

Kusano, Toshiki; Kurashige, Hiroki; Nambu, Isao; Moriguchi, Yoshiya; Hanakawa, Takashi; Wada, Yasuhiro; Osu, Rieko

2015-08-01

It has been suggested that resting-state brain activity reflects task-induced brain activity patterns. In this study, we examined whether neural representations of specific movements can be observed in the resting-state brain activity patterns of motor areas. First, we defined two regions of interest (ROIs) to examine brain activity associated with two different behavioral tasks. Using multi-voxel pattern analysis with regularized logistic regression, we designed a decoder to detect voxel-level neural representations corresponding to the tasks in each ROI. Next, we applied the decoder to resting-state brain activity. We found that the decoder discriminated resting-state neural activity with accuracy comparable to that associated with task-induced neural activity. The distribution of learned weighted parameters for each ROI was similar for resting-state and task-induced activities. Large weighted parameters were mainly located on conjunctive areas. Moreover, the accuracy of detection was higher than that for a decoder whose weights were randomly shuffled, indicating that the resting-state brain activity includes multi-voxel patterns similar to the neural representation for the tasks. Therefore, these results suggest that the neural representation of resting-state brain activity is more finely organized and more complex than conventionally considered.

Cross-Modal Decoding of Neural Patterns Associated with Working Memory: Evidence for Attention-Based Accounts of Working Memory

PubMed Central

Majerus, Steve; Cowan, Nelson; Péters, Frédéric; Van Calster, Laurens; Phillips, Christophe; Schrouff, Jessica

2016-01-01

Recent studies suggest common neural substrates involved in verbal and visual working memory (WM), interpreted as reflecting shared attention-based, short-term retention mechanisms. We used a machine-learning approach to determine more directly the extent to which common neural patterns characterize retention in verbal WM and visual WM. Verbal WM was assessed via a standard delayed probe recognition task for letter sequences of variable length. Visual WM was assessed via a visual array WM task involving the maintenance of variable amounts of visual information in the focus of attention. We trained a classifier to distinguish neural activation patterns associated with high- and low-visual WM load and tested the ability of this classifier to predict verbal WM load (high–low) from their associated neural activation patterns, and vice versa. We observed significant between-task prediction of load effects during WM maintenance, in posterior parietal and superior frontal regions of the dorsal attention network; in contrast, between-task prediction in sensory processing cortices was restricted to the encoding stage. Furthermore, between-task prediction of load effects was strongest in those participants presenting the highest capacity for the visual WM task. This study provides novel evidence for common, attention-based neural patterns supporting verbal and visual WM. PMID:25146374

Pattern classification and recognition of invertebrate functional groups using self-organizing neural networks.

PubMed

Zhang, WenJun

2007-07-01

Self-organizing neural networks can be used to mimic non-linear systems. The main objective of this study is to make pattern classification and recognition on sampling information using two self-organizing neural network models. Invertebrate functional groups sampled in the irrigated rice field were classified and recognized using one-dimensional self-organizing map and self-organizing competitive learning neural networks. Comparisons between neural network models, distance (similarity) measures, and number of neurons were conducted. The results showed that self-organizing map and self-organizing competitive learning neural network models were effective in pattern classification and recognition of sampling information. Overall the performance of one-dimensional self-organizing map neural network was better than self-organizing competitive learning neural network. The number of neurons could determine the number of classes in the classification. Different neural network models with various distance (similarity) measures yielded similar classifications. Some differences, dependent upon the specific network structure, would be found. The pattern of an unrecognized functional group was recognized with the self-organizing neural network. A relative consistent classification indicated that the following invertebrate functional groups, terrestrial blood sucker; terrestrial flyer; tourist (nonpredatory species with no known functional role other than as prey in ecosystem); gall former; collector (gather, deposit feeder); predator and parasitoid; leaf miner; idiobiont (acarine ectoparasitoid), were classified into the same group, and the following invertebrate functional groups, external plant feeder; terrestrial crawler, walker, jumper or hunter; neustonic (water surface) swimmer (semi-aquatic), were classified into another group. It was concluded that reliable conclusions could be drawn from comparisons of different neural network models that use different distance (similarity) measures. Results with the larger consistency will be more reliable.

Weaving and neural complexity in symmetric quantum states

NASA Astrophysics Data System (ADS)

Susa, Cristian E.; Girolami, Davide

2018-04-01

We study the behaviour of two different measures of the complexity of multipartite correlation patterns, weaving and neural complexity, for symmetric quantum states. Weaving is the weighted sum of genuine multipartite correlations of any order, where the weights are proportional to the correlation order. The neural complexity, originally introduced to characterize correlation patterns in classical neural networks, is here extended to the quantum scenario. We derive closed formulas of the two quantities for GHZ states mixed with white noise.

Spatio-Temporal Neural Networks for Vision, Reasoning and Rapid Decision Making

DTIC Science & Technology

1994-08-31

something that is obviously not pattern for long-term knowledge base (LTKB) facts. As a matter possiblc in common neural networks (as units in a...Conferences on Neural Davis, P. (19W0) Application of op~tical chaos to temporal pattern search in a Networks . Piscataway, NJ. [SC] nonlinear optical...Science Institute PROJECT TITLE: Spatio-temporal Neural Networks for Vision, Reasoning and Rapid Decision Making (N00014-93-1-1149) Number of ONR

Reproductive toxicity of the water accommodated fraction (WAF) of crude oil in the polychaetes Arenicola marina (L.) and Nereis virens (Sars).

PubMed

Lewis, Ceri; Pook, Chris; Galloway, Tamara

2008-10-20

Accidental pollution incidents are common in the marine environment and are often caused by oil-related activities. Here the potential of such an incident to disrupt reproduction in two polychaete species is investigated, using an environmentally relevant preparation of weathered Forties crude oil, i.e. the water accommodated fraction (WAF). Oocytes were collected and exposed to three concentrations of WAF for 1h prior to the addition of sperm, so that fertilization took place under exposure conditions. Fertilization success was significantly reduced in both species by an exposure to WAF concentrations equivalent to 0.38 mgL(-1) PAHs, to just 26.8% in Arenicola marina compared to 76% in Nereis virens. The effects of WAF exposure on fertilization were greatly enhanced at lower sperm concentrations in N. virens, with a complete lack of fertilization reactions observed at sperm concentrations of 10(3)sperm per mL. We therefore suggest a mechanism of toxicity related to sperm swimming behaviour, resulting in reduced sperm:egg collision rates. WAF was found to reduce post-fertilization development rates and have teratogenic effects on early embryonic stages in both species, which exhibited abnormal cleavage patterns and high levels of fluctuating asymmetry. These results illustrate how the presence of crude oil in its soluble form in seawater at the time of a spawning event for either A. marina or N. virens could impact on fertilization success with implications for the fertilization ecology of these free spawning marine invertebrates.

The effect of bio-irrigation by the polychaete Lanice conchilega on active denitrifiers: Distribution, diversity and composition of nosZ gene

PubMed Central

Yazdani Foshtomi, Maryam; Leliaert, Frederik; Derycke, Sofie; Willems, Anne; Vincx, Magda

2018-01-01

The presence of large densities of the piston-pumping polychaete Lanice conchilega can have important consequences for the functioning of marine sediments. It is considered both an allogenic and an autogenic ecosystem engineer, affecting spatial and temporal biogeochemical gradients (oxygen concentrations, oxygen penetration depth and nutrient concentrations) and physical properties (grain size) of marine sediments, which could affect functional properties of sediment-inhabiting microbial communities. Here we investigated whether density-dependent effects of L. conchilega affected horizontal (m-scale) and vertical (cm-scale) patterns in the distribution, diversity and composition of the typical nosZ gene in the active denitrifying organisms. This gene plays a major role in N2O reduction in coastal ecosystems as the last step completing the denitrification pathway. We showed that both vertical and horizontal composition and richness of nosZ gene were indeed significantly affected when large densities of the bio-irrigator were present. This could be directly related to allogenic ecosystem engineering effects on the environment, reflected in increased oxygen penetration depth and oxygen concentrations in the upper cm of the sediment in high densities of L. conchilega. A higher diversity (Shannon diversity and inverse Simpson) of nosZ observed in patches with high L. conchilega densities (3,185–3,440 ind. m-2) at deeper sediment layers could suggest a downward transport of NO3− to deeper layers resulting from bio-irrigation as well. Hence, our results show the effect of L. conchilega bio-irrigation activity on denitrifying organisms in L. conchilega reefs. PMID:29408934

Pattern learning with deep neural networks in EMG-based speech recognition.

PubMed

Wand, Michael; Schultz, Tanja

2014-01-01

We report on classification of phones and phonetic features from facial electromyographic (EMG) data, within the context of our EMG-based Silent Speech interface. In this paper we show that a Deep Neural Network can be used to perform this classification task, yielding a significant improvement over conventional Gaussian Mixture models. Our central contribution is the visualization of patterns which are learned by the neural network. With increasing network depth, these patterns represent more and more intricate electromyographic activity.

Nested neural networks

NASA Technical Reports Server (NTRS)

Baram, Yoram

1988-01-01

Nested neural networks, consisting of small interconnected subnetworks, allow for the storage and retrieval of neural state patterns of different sizes. The subnetworks are naturally categorized by layers of corresponding to spatial frequencies in the pattern field. The storage capacity and the error correction capability of the subnetworks generally increase with the degree of connectivity between layers (the nesting degree). Storage of only few subpatterns in each subnetworks results in a vast storage capacity of patterns and subpatterns in the nested network, maintaining high stability and error correction capability.

Distinct Mechanisms for Synchronization and Temporal Patterning of Odor-Encoding Neural Assemblies

NASA Astrophysics Data System (ADS)

MacLeod, Katrina; Laurent, Gilles

1996-11-01

Stimulus-evoked oscillatory synchronization of neural assemblies and temporal patterns of neuronal activity have been observed in many sensory systems, such as the visual and auditory cortices of mammals or the olfactory system of insects. In the locust olfactory system, single odor puffs cause the immediate formation of odor-specific neural assemblies, defined both by their transient synchronized firing and their progressive transformation over the course of a response. The application of an antagonist of ionotropic γ-aminobutyric acid (GABA) receptors to the first olfactory relay neuropil selectively blocked the fast inhibitory synapse between local and projection neurons. This manipulation abolished the synchronization of the odor-coding neural ensembles but did not affect each neuron's temporal response patterns to odors, even when these patterns contained periods of inhibition. Fast GABA-mediated inhibition, therefore, appears to underlie neuronal synchronization but not response tuning in this olfactory system. The selective desynchronization of stimulus-evoked oscillating neural assemblies in vivo is now possible, enabling direct functional tests of their significance for sensation and perception.

Optical-Correlator Neural Network Based On Neocognitron

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin; Stoner, William W.

1994-01-01

Multichannel optical correlator implements shift-invariant, high-discrimination pattern-recognizing neural network based on paradigm of neocognitron. Selected as basic building block of this neural network because invariance under shifts is inherent advantage of Fourier optics included in optical correlators in general. Neocognitron is conceptual electronic neural-network model for recognition of visual patterns. Multilayer processing achieved by iteratively feeding back output of feature correlator to input spatial light modulator and updating Fourier filters. Neural network trained by use of characteristic features extracted from target images. Multichannel implementation enables parallel processing of large number of selected features.

Neural-Network Simulator

NASA Technical Reports Server (NTRS)

Mitchell, Paul H.

1991-01-01

F77NNS (FORTRAN 77 Neural Network Simulator) computer program simulates popular back-error-propagation neural network. Designed to take advantage of vectorization when used on computers having this capability, also used on any computer equipped with ANSI-77 FORTRAN Compiler. Problems involving matching of patterns or mathematical modeling of systems fit class of problems F77NNS designed to solve. Program has restart capability so neural network solved in stages suitable to user's resources and desires. Enables user to customize patterns of connections between layers of network. Size of neural network F77NNS applied to limited only by amount of random-access memory available to user.

Weaving and neural complexity in symmetric quantum states

DOE PAGES

Susa, Cristian E.; Girolami, Davide

2017-12-27

Here, we study the behaviour of two different measures of the complexity of multipartite correlation patterns, weaving and neural complexity, for symmetric quantum states. Weaving is the weighted sum of genuine multipartite correlations of any order, where the weights are proportional to the correlation order. The neural complexity, originally introduced to characterize correlation patterns in classical neural networks, is here extended to the quantum scenario. We derive closed formulas of the two quantities for GHZ states mixed with white noise.

Weaving and neural complexity in symmetric quantum states

DOE Office of Scientific and Technical Information (OSTI.GOV)

Susa, Cristian E.; Girolami, Davide

Here, we study the behaviour of two different measures of the complexity of multipartite correlation patterns, weaving and neural complexity, for symmetric quantum states. Weaving is the weighted sum of genuine multipartite correlations of any order, where the weights are proportional to the correlation order. The neural complexity, originally introduced to characterize correlation patterns in classical neural networks, is here extended to the quantum scenario. We derive closed formulas of the two quantities for GHZ states mixed with white noise.

Macrofaunal colonization across the Indian margin oxygen minimum zone

NASA Astrophysics Data System (ADS)

Levin, L. A.; McGregor, A. L.; Mendoza, G. F.; Woulds, C.; Cross, P.; Witte, U.; Gooday, A. J.; Cowie, G.; Kitazato, H.

2013-11-01

There is a growing need to understand the ability of bathyal assemblages to recover from disturbance and oxygen stress, as human activities and expanding oxygen minimum zones increasingly affect deep continental margins. The effects of a pronounced oxygen minimum zone (OMZ) on slope benthic community structure have been studied on every major upwelling margin; however, little is known about the dynamics or resilience of these benthic populations. To examine the influence of oxygen and phytodetritus on short-term settlement patterns, we conducted colonization experiments at 3 depths on the West Indian continental margin. Four colonization trays were deployed at each depth for 4 days at 542 and 802 m (transect 1-16°58' N) and for 9 days at 817 and 1147 m (transect 2-17°31' N). Oxygen concentrations ranged from 0.9 μM (0.02 mL L-1) at 542 m to 22 μM (0.5 mL L-1) at 1147 m. All trays contained local defaunated sediments; half of the trays at each depth also contained 13C/15N-labeled phytodetritus mixed into the sediments. Sediment cores were collected between 535 m and 1140 m from 2 cross-margin transects for analysis of ambient (source) macrofaunal (>300 μm) densities and composition. Ambient macrofaunal densities ranged from 0 ind m-2 (at 535-542 m) to 7400 ind m-2, with maximum values on both transects at 700-800 m. Macrofaunal colonizer densities ranged from 0 ind m-2 at 542 m, where oxygen was lowest, to average values of 142 ind m-2 at 800 m, and 3074 ind m-2 at 1147 m, where oxygen concentration was highest. These were equal to 4.3 and 151% of the ambient community at 800 m and 1147 m, respectively. Community structure of settlers showed no response to the presence of phytodetritus. Increasing depth and oxygen concentration, however, significantly influenced the community composition and abundance of colonizing macrofauna. Polychaetes constituted 92.4% of the total colonizers, followed by crustaceans (4.2%), mollusks (2.5%), and echinoderms (0.8%). The majority of colonizers were found at 1147 m; 88.5% of these were Capitella sp., although they were rare in the ambient community. Colonists at 800 and 1147 m also included ampharetid, spionid, syllid, lumbrinerid, cirratulid, cossurid and sabellid polychaetes. Consumption of 13C/15N-labeled phytodetritus was observed for macrofaunal foraminifera (too large to be colonizers) at the 542 and 802/817 m sites, and by metazoan macrofauna mainly at the deepest, better oxygenated sites. Calcareous foraminifera (Uvigerina, Hoeglundina sp.), capitellid polychaetes and cumaceans were among the major phytodetritus consumers. These preliminary experiments suggest that bottom-water oxygen concentrations may strongly influence ecosystem services on continental margins, as reflected in rates of colonization by benthos and colonizer processing of carbon following disturbance. They may also provide a window into future patterns of settlement on the continental slope as the world's oxygen minimum zones expand.

The Cluster Variation Method: A Primer for Neuroscientists.

PubMed

Maren, Alianna J

2016-09-30

Effective Brain-Computer Interfaces (BCIs) require that the time-varying activation patterns of 2-D neural ensembles be modelled. The cluster variation method (CVM) offers a means for the characterization of 2-D local pattern distributions. This paper provides neuroscientists and BCI researchers with a CVM tutorial that will help them to understand how the CVM statistical thermodynamics formulation can model 2-D pattern distributions expressing structural and functional dynamics in the brain. The premise is that local-in-time free energy minimization works alongside neural connectivity adaptation, supporting the development and stabilization of consistent stimulus-specific responsive activation patterns. The equilibrium distribution of local patterns, or configuration variables , is defined in terms of a single interaction enthalpy parameter ( h ) for the case of an equiprobable distribution of bistate (neural/neural ensemble) units. Thus, either one enthalpy parameter (or two, for the case of non-equiprobable distribution) yields equilibrium configuration variable values. Modeling 2-D neural activation distribution patterns with the representational layer of a computational engine, we can thus correlate variational free energy minimization with specific configuration variable distributions. The CVM triplet configuration variables also map well to the notion of a M = 3 functional motif. This paper addresses the special case of an equiprobable unit distribution, for which an analytic solution can be found.

The Cluster Variation Method: A Primer for Neuroscientists

PubMed Central

Maren, Alianna J.

2016-01-01

Effective Brain–Computer Interfaces (BCIs) require that the time-varying activation patterns of 2-D neural ensembles be modelled. The cluster variation method (CVM) offers a means for the characterization of 2-D local pattern distributions. This paper provides neuroscientists and BCI researchers with a CVM tutorial that will help them to understand how the CVM statistical thermodynamics formulation can model 2-D pattern distributions expressing structural and functional dynamics in the brain. The premise is that local-in-time free energy minimization works alongside neural connectivity adaptation, supporting the development and stabilization of consistent stimulus-specific responsive activation patterns. The equilibrium distribution of local patterns, or configuration variables, is defined in terms of a single interaction enthalpy parameter (h) for the case of an equiprobable distribution of bistate (neural/neural ensemble) units. Thus, either one enthalpy parameter (or two, for the case of non-equiprobable distribution) yields equilibrium configuration variable values. Modeling 2-D neural activation distribution patterns with the representational layer of a computational engine, we can thus correlate variational free energy minimization with specific configuration variable distributions. The CVM triplet configuration variables also map well to the notion of a M = 3 functional motif. This paper addresses the special case of an equiprobable unit distribution, for which an analytic solution can be found. PMID:27706022

Retinoic acid regulates size, pattern and alignment of tissues at the head-trunk transition.

PubMed

Lee, Keun; Skromne, Isaac

2014-11-01

At the head-trunk transition, hindbrain and spinal cord alignment to occipital and vertebral bones is crucial for coherent neural and skeletal system organization. Changes in neural or mesodermal tissue configuration arising from defects in the specification, patterning or relative axial placement of territories can severely compromise their integration and function. Here, we show that coordination of neural and mesodermal tissue at the zebrafish head-trunk transition crucially depends on two novel activities of the signaling factor retinoic acid (RA): one specifying the size and the other specifying the axial position relative to mesodermal structures of the hindbrain territory. These activities are each independent but coordinated with the well-established function of RA in hindbrain patterning. Using neural and mesodermal landmarks we demonstrate that the functions of RA in aligning neural and mesodermal tissues temporally precede the specification of hindbrain and spinal cord territories and the activation of hox transcription. Using cell transplantation assays we show that RA activity in the neuroepithelium regulates hindbrain patterning directly and territory size specification indirectly. This indirect function is partially dependent on Wnts but independent of FGFs. Importantly, RA specifies and patterns the hindbrain territory by antagonizing the activity of the spinal cord specification gene cdx4; loss of Cdx4 rescues the defects associated with the loss of RA, including the reduction in hindbrain size and the loss of posterior rhombomeres. We propose that at the head-trunk transition, RA coordinates specification, patterning and alignment of neural and mesodermal tissues that are essential for the organization and function of the neural and skeletal systems. © 2014. Published by The Company of Biologists Ltd.

Neural feedback for instantaneous spatiotemporal modulation of afferent pathways in bi-directional brain-machine interfaces.

PubMed

Liu, Jianbo; Khalil, Hassan K; Oweiss, Karim G

2011-10-01

In bi-directional brain-machine interfaces (BMIs), precisely controlling the delivery of microstimulation, both in space and in time, is critical to continuously modulate the neural activity patterns that carry information about the state of the brain-actuated device to sensory areas in the brain. In this paper, we investigate the use of neural feedback to control the spatiotemporal firing patterns of neural ensembles in a model of the thalamocortical pathway. Control of pyramidal (PY) cells in the primary somatosensory cortex (S1) is achieved based on microstimulation of thalamic relay cells through multiple-input multiple-output (MIMO) feedback controllers. This closed loop feedback control mechanism is achieved by simultaneously varying the stimulation parameters across multiple stimulation electrodes in the thalamic circuit based on continuous monitoring of the difference between reference patterns and the evoked responses of the cortical PY cells. We demonstrate that it is feasible to achieve a desired level of performance by controlling the firing activity pattern of a few "key" neural elements in the network. Our results suggest that neural feedback could be an effective method to facilitate the delivery of information to the cortex to substitute lost sensory inputs in cortically controlled BMIs.

Evolution of central pattern generators and rhythmic behaviours

PubMed Central

Katz, Paul S.

2016-01-01

Comparisons of rhythmic movements and the central pattern generators (CPGs) that control them uncover principles about the evolution of behaviour and neural circuits. Over the course of evolutionary history, gradual evolution of behaviours and their neural circuitry within any lineage of animals has been a predominant occurrence. Small changes in gene regulation can lead to divergence of circuit organization and corresponding changes in behaviour. However, some behavioural divergence has resulted from large-scale rewiring of the neural network. Divergence of CPG circuits has also occurred without a corresponding change in behaviour. When analogous rhythmic behaviours have evolved independently, it has generally been with different neural mechanisms. Repeated evolution of particular rhythmic behaviours has occurred within some lineages due to parallel evolution or latent CPGs. Particular motor pattern generating mechanisms have also evolved independently in separate lineages. The evolution of CPGs and rhythmic behaviours shows that although most behaviours and neural circuits are highly conserved, the nature of the behaviour does not dictate the neural mechanism and that the presence of homologous neural components does not determine the behaviour. This suggests that although behaviour is generated by neural circuits, natural selection can act separately on these two levels of biological organization. PMID:26598733

Evolution of central pattern generators and rhythmic behaviours.

PubMed

Katz, Paul S

2016-01-05

Comparisons of rhythmic movements and the central pattern generators (CPGs) that control them uncover principles about the evolution of behaviour and neural circuits. Over the course of evolutionary history, gradual evolution of behaviours and their neural circuitry within any lineage of animals has been a predominant occurrence. Small changes in gene regulation can lead to divergence of circuit organization and corresponding changes in behaviour. However, some behavioural divergence has resulted from large-scale rewiring of the neural network. Divergence of CPG circuits has also occurred without a corresponding change in behaviour. When analogous rhythmic behaviours have evolved independently, it has generally been with different neural mechanisms. Repeated evolution of particular rhythmic behaviours has occurred within some lineages due to parallel evolution or latent CPGs. Particular motor pattern generating mechanisms have also evolved independently in separate lineages. The evolution of CPGs and rhythmic behaviours shows that although most behaviours and neural circuits are highly conserved, the nature of the behaviour does not dictate the neural mechanism and that the presence of homologous neural components does not determine the behaviour. This suggests that although behaviour is generated by neural circuits, natural selection can act separately on these two levels of biological organization. © 2015 The Author(s).

Neural net target-tracking system using structured laser patterns

NASA Astrophysics Data System (ADS)

Cho, Jae-Wan; Lee, Yong-Bum; Lee, Nam-Ho; Park, Soon-Yong; Lee, Jongmin; Choi, Gapchu; Baek, Sunghyun; Park, Dong-Sun

1996-06-01

In this paper, we describe a robot endeffector tracking system using sensory information from recently-announced structured pattern laser diodes, which can generate images with several different types of structured pattern. The neural network approach is employed to recognize the robot endeffector covering the situation of three types of motion: translation, scaling and rotation. Features for the neural network to detect the position of the endeffector are extracted from the preprocessed images. Artificial neural networks are used to store models and to match with unknown input features recognizing the position of the robot endeffector. Since a minimal number of samples are used for different directions of the robot endeffector in the system, an artificial neural network with the generalization capability can be utilized for unknown input features. A feedforward neural network with the generalization capability can be utilized for unknown input features. A feedforward neural network trained with the back propagation learning is used to detect the position of the robot endeffector. Another feedforward neural network module is used to estimate the motion from a sequence of images and to control movements of the robot endeffector. COmbining the tow neural networks for recognizing the robot endeffector and estimating the motion with the preprocessing stage, the whole system keeps tracking of the robot endeffector effectively.

Encoding sensory and motor patterns as time-invariant trajectories in recurrent neural networks

PubMed Central

2018-01-01

Much of the information the brain processes and stores is temporal in nature—a spoken word or a handwritten signature, for example, is defined by how it unfolds in time. However, it remains unclear how neural circuits encode complex time-varying patterns. We show that by tuning the weights of a recurrent neural network (RNN), it can recognize and then transcribe spoken digits. The model elucidates how neural dynamics in cortical networks may resolve three fundamental challenges: first, encode multiple time-varying sensory and motor patterns as stable neural trajectories; second, generalize across relevant spatial features; third, identify the same stimuli played at different speeds—we show that this temporal invariance emerges because the recurrent dynamics generate neural trajectories with appropriately modulated angular velocities. Together our results generate testable predictions as to how recurrent networks may use different mechanisms to generalize across the relevant spatial and temporal features of complex time-varying stimuli. PMID:29537963

Neural networks: Alternatives to conventional techniques for automatic docking

NASA Technical Reports Server (NTRS)

Vinz, Bradley L.

1994-01-01

Automatic docking of orbiting spacecraft is a crucial operation involving the identification of vehicle orientation as well as complex approach dynamics. The chaser spacecraft must be able to recognize the target spacecraft within a scene and achieve accurate closing maneuvers. In a video-based system, a target scene must be captured and transformed into a pattern of pixels. Successful recognition lies in the interpretation of this pattern. Due to their powerful pattern recognition capabilities, artificial neural networks offer a potential role in interpretation and automatic docking processes. Neural networks can reduce the computational time required by existing image processing and control software. In addition, neural networks are capable of recognizing and adapting to changes in their dynamic environment, enabling enhanced performance, redundancy, and fault tolerance. Most neural networks are robust to failure, capable of continued operation with a slight degradation in performance after minor failures. This paper discusses the particular automatic docking tasks neural networks can perform as viable alternatives to conventional techniques.

Encoding sensory and motor patterns as time-invariant trajectories in recurrent neural networks.

PubMed

Goudar, Vishwa; Buonomano, Dean V

2018-03-14

Much of the information the brain processes and stores is temporal in nature-a spoken word or a handwritten signature, for example, is defined by how it unfolds in time. However, it remains unclear how neural circuits encode complex time-varying patterns. We show that by tuning the weights of a recurrent neural network (RNN), it can recognize and then transcribe spoken digits. The model elucidates how neural dynamics in cortical networks may resolve three fundamental challenges: first, encode multiple time-varying sensory and motor patterns as stable neural trajectories; second, generalize across relevant spatial features; third, identify the same stimuli played at different speeds-we show that this temporal invariance emerges because the recurrent dynamics generate neural trajectories with appropriately modulated angular velocities. Together our results generate testable predictions as to how recurrent networks may use different mechanisms to generalize across the relevant spatial and temporal features of complex time-varying stimuli. © 2018, Goudar et al.

Classification of 2-dimensional array patterns: assembling many small neural networks is better than using a large one.

PubMed

Chen, Liang; Xue, Wei; Tokuda, Naoyuki

2010-08-01

In many pattern classification/recognition applications of artificial neural networks, an object to be classified is represented by a fixed sized 2-dimensional array of uniform type, which corresponds to the cells of a 2-dimensional grid of the same size. A general neural network structure, called an undistricted neural network, which takes all the elements in the array as inputs could be used for problems such as these. However, a districted neural network can be used to reduce the training complexity. A districted neural network usually consists of two levels of sub-neural networks. Each of the lower level neural networks, called a regional sub-neural network, takes the elements in a region of the array as its inputs and is expected to output a temporary class label, called an individual opinion, based on the partial information of the entire array. The higher level neural network, called an assembling sub-neural network, uses the outputs (opinions) of regional sub-neural networks as inputs, and by consensus derives the label decision for the object. Each of the sub-neural networks can be trained separately and thus the training is less expensive. The regional sub-neural networks can be trained and performed in parallel and independently, therefore a high speed can be achieved. We prove theoretically in this paper, using a simple model, that a districted neural network is actually more stable than an undistricted neural network in noisy environments. We conjecture that the result is valid for all neural networks. This theory is verified by experiments involving gender classification and human face recognition. We conclude that a districted neural network is highly recommended for neural network applications in recognition or classification of 2-dimensional array patterns in highly noisy environments. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Developmental stages of fish blood flukes, Cardicola forsteri and Cardicola opisthorchis (Trematoda: Aporocotylidae), in their polychaete intermediate hosts collected at Pacific bluefin tuna culture sites in Japan.

PubMed

Ogawa, Kazuo; Shirakashi, Sho; Tani, Kazuki; Shin, Sang Phil; Ishimaru, Katsuya; Honryo, Tomoki; Sugihara, Yukitaka; Uchida, Hiro'omi

2017-02-01

Farming of Pacific bluefin tuna (PBT), Thunnus orientalis, is a rapidly growing industry in Japan. Aporocotylid blood flukes of the genus Cardicola comprising C. orientalis, C. opisthorchis and C. forsteri are parasites of economic importance for PBT farming. Recently, terebellid polychaetes have been identified as the intermediate hosts for all these parasites. We collected infected polychaetes, Terebella sp., the intermediate host of C. opisthorchis, from ropes and floats attached to tuna cages in Tsushima, Nagasaki Prefecture, Japan. Also, Neoamphitrite vigintipes (formerly as Amphitrite sp. sensu Shirakashi et al., 2016), the intermediate host of C. forsteri, were collected from culture cages in Kushimoto, Wakayama Prefecture, Japan. The terebellid intermediate hosts harbored the sporocysts and cercariae in their body cavity. Developmental stages of these blood flukes were molecularly identified using species specific PCR primers. In this paper, we describe the cercaria and sporocyst stages of C. opisthorchis and C. forsteri and compare their morphological characteristics among three Cardicola blood flukes infecting PBT. We also discuss phylogenetic relations of the six genera of the terebellid intermediate hosts (Artacama, Lanassa, Longicarpus, Terebella, Nicolea and Neoamphitrite) of blood flukes infecting marine fishes, based on their morphological characters. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

In situ effects of simulated overfishing and eutrophication on settlement of benthic coral reef invertebrates in the Central Red Sea

PubMed Central

Voolstra, Christian R.; Wild, Christian

2014-01-01

In the Central Red Sea, healthy coral reefs meet intense coastal development, but data on the effects of related stressors for reef functioning are lacking. This in situ study therefore investigated the independent and combined effects of simulated overfishing through predator/grazer exclusion and simulated eutrophication through fertilizer addition on settlement of reef associated invertebrates on light-exposed and -shaded tiles over 4 months. At the end of the study period invertebrates had almost exclusively colonized shaded tiles. Algae were superior settling competitors on light-exposed tiles. On the shaded tiles, simulated overfishing prevented settlement of hard corals, but significantly increased settlement of polychaetes, while simulated eutrophication only significantly decreased hard coral settlement relative to controls. The combined treatment significantly increased settlement of bryozoans and bivalves compared to controls and individual manipulations, but significantly decreased polychaetes compared to simulated overfishing. These results suggest settlement of polychaetes and hard corals as potential bioindicators for overfishing and eutrophication, respectively, and settlement of bivalves and bryozoans for a combination of both. Therefore, if the investigated stressors are not controlled, phase shifts from dominance by hard corals to that by other invertebrates may occur at shaded reef locations in the Central Red Sea. PMID:24765573

Measurement and modeling of polychlorinated biphenyl bioaccumulation from sediment for the marine polychaete neanthes arenaceodentata and response to sorbent amendment

USGS Publications Warehouse

Janssen, E.M.-L.; Croteau, M.-N.; Luoma, S.N.; Luthy, R.G.

2010-01-01

Bioaccumulation rates of polychlorinated biphenyls (PCBs) for the marine polychaete Neanthes arenaceodentata were characterized, including PCB uptake rates from water and sediment, and the effect of sorbent amendment to the sediment on PCB bioavailability, organism growth, and lipid content. Physiological parameters were incorporated into a biodynamic model to predict contaminant uptake. The results indicate rapid PCB uptake from contaminated sediment and significant organism growth dilution during time-series exposure studies. PCB uptake from the aqueous phase accounted for less than 3% of the total uptake for this deposit-feeder. Proportional increase of gut residence time and assimilation efficiency as a consequence of the organism's growth was assessed by PCB uptake and a reactor theory model of gut architecture. Pulse-chase feeding and multilabeled stable isotope tracing techniques proved high sediment ingestion rates (i.e., 6?10 times of dry body weight per day) indicating that such deposit-feeders are promising biological indicators for sediment risk assessment. Activated carbon amendment reduced PCB uptake by 95% in laboratory experiments with no observed adverse growth effects on the marine polychaete. Biodynamic modeling explained the observed PCB body burdens for N. arenaceodentata, with and without sorbent amendment. ?? 2009 American Chemical Society.

In situ effects of simulated overfishing and eutrophication on settlement of benthic coral reef invertebrates in the Central Red Sea.

PubMed

Jessen, Christian; Voolstra, Christian R; Wild, Christian

2014-01-01

In the Central Red Sea, healthy coral reefs meet intense coastal development, but data on the effects of related stressors for reef functioning are lacking. This in situ study therefore investigated the independent and combined effects of simulated overfishing through predator/grazer exclusion and simulated eutrophication through fertilizer addition on settlement of reef associated invertebrates on light-exposed and -shaded tiles over 4 months. At the end of the study period invertebrates had almost exclusively colonized shaded tiles. Algae were superior settling competitors on light-exposed tiles. On the shaded tiles, simulated overfishing prevented settlement of hard corals, but significantly increased settlement of polychaetes, while simulated eutrophication only significantly decreased hard coral settlement relative to controls. The combined treatment significantly increased settlement of bryozoans and bivalves compared to controls and individual manipulations, but significantly decreased polychaetes compared to simulated overfishing. These results suggest settlement of polychaetes and hard corals as potential bioindicators for overfishing and eutrophication, respectively, and settlement of bivalves and bryozoans for a combination of both. Therefore, if the investigated stressors are not controlled, phase shifts from dominance by hard corals to that by other invertebrates may occur at shaded reef locations in the Central Red Sea.

Polychaeta (Annelida) associated with Thalassia testudinum in the northeastern coastal waters of Venezuela.

PubMed

Liñero Arana, Ildefonso; Díaz Díaz, Oscar

2006-09-01

Seasonal variations of polychaetes in a Thalassia testudinum bed were studied from June 2000 to April 2001 in Chacopata, northeastern Venezuela. Eight replicate samples were taken monthly with a 15 cm diameter core and the sediment was passed through a 0.5 mm mesh sieve. A total of 1,013 specimens, belonging to 35 species, was collected. The monthly density ranged from 387 ind/m2 (September) to 1,735 ind/m2 in May (x = 989+/-449 ind/m2). Species richness was lowest in August and September (8) and highest (25) in April (x = 18.00+/-5.29). The shoot density of Thalassia showed an average of 284+/-77.60 shoots/m2, with extreme values in February (164) and May (422). Species diversity ranged from 1.25 in August and 3.33 bits/ind in December (x = 2.47+/-0.64). Significant positive correlations were detected among the number of Thalassia shoots, polychaete abundance and species richness, as well as among species richness, polychaete abundance and species diversity. Species number and average density were found within the intervals of mean values reported in similar studies. The higher number of species and organisms obtained in March-April and June-July can be attributed to the recruitment correlated with the regional up-welling.

Neural breathing patterns in preterm newborns supported with non-invasive neurally adjusted ventilatory assist.

PubMed

García-Muñoz Rodrigo, Fermín; Urquía Martí, Lourdes; Galán Henríquez, Gloria; Rivero Rodríguez, Sonia; Hernández Gómez, Alberto

2018-06-18

To characterize the neural breathing pattern in preterm infants supported with non-invasive neurally adjusted ventilatory assist (NIV-NAVA). Single-center prospective observational study. The electrical activity of the diaphragm (EAdi) was periodically recorded in 30-second series with the Edi catheter and the Servo-n software (Maquet, Solna, Sweden) in preterm infants supported with NIV-NAVA. The EAdi Peak , EAdi Min , EAdi Tonic , EAdi Phasic , neural inspiratory, and expiratory times (nTi and nTe) and the neural respiratory rate (nRR) were calculated. EAdi curves were generated by Excel for visual examination and classified according to the predominant pattern. 291 observations were analyzed in 19 patients with a mean GA of 27.3 weeks (range 24-36 weeks), birth weight 1028 g (510-2945 g), and a median (IQR) postnatal age of 18 days (4-27 days). The distribution of respiratory patterns was phasic without tonic activity 61.9%, phasic with basal tonic activity 18.6, tonic burst 3.8%, central apnea 7.9%, and mixed pattern 7.9%. In addition, 12% of the records showed apneas of >10 seconds, and 50.2% one or more "sighs", defined as breaths with an EAdi Peak and/or nTi greater than twice the average EAdi Peak and/or nTi of the recording. Neural times were measurable in 252 observations. The nTi was, median (IQR): 279 ms (253-285 ms), the nTe 764 ms (642-925 ms), and the nRR 63 bpm (51-70), with a great intra and inter-subjects variability. The neural breathing patterns in preterm infants supported with NIV-NAVA are quite variable and are characterized by the presence of significant tonic activity. Central apneas and sighs are common in this group of patients. The nTi seems to be shorter than the mechanical Ti commonly used in assisted ventilation.

Beyond mind-reading: multi-voxel pattern analysis of fMRI data.

PubMed

Norman, Kenneth A; Polyn, Sean M; Detre, Greg J; Haxby, James V

2006-09-01

A key challenge for cognitive neuroscience is determining how mental representations map onto patterns of neural activity. Recently, researchers have started to address this question by applying sophisticated pattern-classification algorithms to distributed (multi-voxel) patterns of functional MRI data, with the goal of decoding the information that is represented in the subject's brain at a particular point in time. This multi-voxel pattern analysis (MVPA) approach has led to several impressive feats of mind reading. More importantly, MVPA methods constitute a useful new tool for advancing our understanding of neural information processing. We review how researchers are using MVPA methods to characterize neural coding and information processing in domains ranging from visual perception to memory search.

Cross-Modal Decoding of Neural Patterns Associated with Working Memory: Evidence for Attention-Based Accounts of Working Memory.

PubMed

Majerus, Steve; Cowan, Nelson; Péters, Frédéric; Van Calster, Laurens; Phillips, Christophe; Schrouff, Jessica

2016-01-01

Recent studies suggest common neural substrates involved in verbal and visual working memory (WM), interpreted as reflecting shared attention-based, short-term retention mechanisms. We used a machine-learning approach to determine more directly the extent to which common neural patterns characterize retention in verbal WM and visual WM. Verbal WM was assessed via a standard delayed probe recognition task for letter sequences of variable length. Visual WM was assessed via a visual array WM task involving the maintenance of variable amounts of visual information in the focus of attention. We trained a classifier to distinguish neural activation patterns associated with high- and low-visual WM load and tested the ability of this classifier to predict verbal WM load (high-low) from their associated neural activation patterns, and vice versa. We observed significant between-task prediction of load effects during WM maintenance, in posterior parietal and superior frontal regions of the dorsal attention network; in contrast, between-task prediction in sensory processing cortices was restricted to the encoding stage. Furthermore, between-task prediction of load effects was strongest in those participants presenting the highest capacity for the visual WM task. This study provides novel evidence for common, attention-based neural patterns supporting verbal and visual WM. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Neural Pattern Similarity in the Left IFG and Fusiform Is Associated with Novel Word Learning

PubMed Central

Qu, Jing; Qian, Liu; Chen, Chuansheng; Xue, Gui; Li, Huiling; Xie, Peng; Mei, Leilei

2017-01-01

Previous studies have revealed that greater neural pattern similarity across repetitions is associated with better subsequent memory. In this study, we used an artificial language training paradigm and representational similarity analysis to examine whether neural pattern similarity across repetitions before training was associated with post-training behavioral performance. Twenty-four native Chinese speakers were trained to learn a logographic artificial language for 12 days and behavioral performance was recorded using the word naming and picture naming tasks. Participants were scanned while performing a passive viewing task before training, after 4-day training and after 12-day training. Results showed that pattern similarity in the left pars opercularis (PO) and fusiform gyrus (FG) before training was negatively associated with reaction time (RT) in both word naming and picture naming tasks after training. These results suggest that neural pattern similarity is an effective neurofunctional predictor of novel word learning in addition to word memory. PMID:28878640

Modality-independent representations of small quantities based on brain activation patterns.

PubMed

Damarla, Saudamini Roy; Cherkassky, Vladimir L; Just, Marcel Adam

2016-04-01

Machine learning or MVPA (Multi Voxel Pattern Analysis) studies have shown that the neural representation of quantities of objects can be decoded from fMRI patterns, in cases where the quantities were visually displayed. Here we apply these techniques to investigate whether neural representations of quantities depicted in one modality (say, visual) can be decoded from brain activation patterns evoked by quantities depicted in the other modality (say, auditory). The main finding demonstrated, for the first time, that quantities of dots were decodable by a classifier that was trained on the neural patterns evoked by quantities of auditory tones, and vice-versa. The representations that were common across modalities were mainly right-lateralized in frontal and parietal regions. A second finding was that the neural patterns in parietal cortex that represent quantities were common across participants. These findings demonstrate a common neuronal foundation for the representation of quantities across sensory modalities and participants and provide insight into the role of parietal cortex in the representation of quantity information. © 2016 Wiley Periodicals, Inc.

Digital micromirror based near-infrared illumination system for plasmonic photothermal neuromodulation

PubMed Central

Jung, Hyunjun; Kang, Hongki; Nam, Yoonkey

2017-01-01

Light-mediated neuromodulation techniques provide great advantages to investigate neuroscience due to its high spatial and temporal resolution. To generate a spatial pattern of neural activity, it is necessary to develop a system for patterned-light illumination to a specific area. Digital micromirror device (DMD) based patterned illumination system have been used for neuromodulation due to its simple configuration and design flexibility. In this paper, we developed a patterned near-infrared (NIR) illumination system for region specific photothermal manipulation of neural activity using NIR-sensitive plasmonic gold nanorods (GNRs). The proposed system had high power transmission efficiency for delivering power density up to 19 W/mm2. We used a GNR-coated microelectrode array (MEA) to perform biological experiments using E18 rat hippocampal neurons and showed that it was possible to inhibit neural spiking activity of specific area in neural circuits with the patterned NIR illumination. This patterned NIR illumination system can serve as a promising neuromodulation tool to investigate neuroscience in a wide range of physiological and clinical applications. PMID:28663912

Diversity of the benthic macrofauna off northern Namibia from the shelf to the deep sea

NASA Astrophysics Data System (ADS)

Eisenbarth, Simone; Zettler, Michael L.

2016-03-01

In late summer 2011, shortly after an upwelling event, 17 stations ranging from 30 to 2513 m water depth have been sampled at 20° south in the northern part of the Benguela Current Large Marine Ecosystem (BCLME) for the investigation of the benthic macrofauna. Sediments of this area are dominated by silt. At the time of sampling, oxygen conditions on the shelf were poor (between 0.42 and 0.68 ml l- 1) but not hypoxic. Below 400 m, however, concentrations rose steadily up to 5.28 ml l- 1. Macrozoobenthic communities along this depth gradient are described, revealing among others the community structure for the continental margin area and the deep sea off northern Namibia for the first time. Cluster analysis revealed 5 different communities along the depth gradient with three shelf communities, one continental margin community and one deep-sea community. All in all, 314 different taxa were found with polychaetes being the most abundant group. Diversity index (Shannon) was lowest for the shallow water community with 2.21 and highest for the deep-sea community with 4.79, showing a clear trend with increasing water depth. Species richness, however, reached its maximum with 187 taxa along the continental margin between 400 and 1300 m water depth. Dominant species for each community are named with the two Cumacea, Iphinoeafricana and Upselaspis caparti, being characteristic for the shallow water community. On the shelf, we found surprisingly high biomass values (23-123 g m- 2), mainly caused by polychaetes, the bivalve Sinupharus galatheae and the gastropod Nassarius vinctus. In terms of composition, the remaining communities were dominated by polychaetes with members of the Paraonidae dominating along the continental margin where we also found surprisingly high abundances of the bivalves Pecten sp. and Dosinia sp. Spionid polychaetes and some representatives of the genus Paraonis were the most common organisms for the deep-sea community.

Neural networks for calibration tomography

NASA Technical Reports Server (NTRS)

Decker, Arthur

1993-01-01

Artificial neural networks are suitable for performing pattern-to-pattern calibrations. These calibrations are potentially useful for facilities operations in aeronautics, the control of optical alignment, and the like. Computed tomography is compared with neural net calibration tomography for estimating density from its x-ray transform. X-ray transforms are measured, for example, in diffuse-illumination, holographic interferometry of fluids. Computed tomography and neural net calibration tomography are shown to have comparable performance for a 10 degree viewing cone and 29 interferograms within that cone. The system of tomography discussed is proposed as a relevant test of neural networks and other parallel processors intended for using flow visualization data.

Empirical modeling for intelligent, real-time manufacture control

NASA Technical Reports Server (NTRS)

Xu, Xiaoshu

1994-01-01

Artificial neural systems (ANS), also known as neural networks, are an attempt to develop computer systems that emulate the neural reasoning behavior of biological neural systems (e.g. the human brain). As such, they are loosely based on biological neural networks. The ANS consists of a series of nodes (neurons) and weighted connections (axons) that, when presented with a specific input pattern, can associate specific output patterns. It is essentially a highly complex, nonlinear, mathematical relationship or transform. These constructs have two significant properties that have proven useful to the authors in signal processing and process modeling: noise tolerance and complex pattern recognition. Specifically, the authors have developed a new network learning algorithm that has resulted in the successful application of ANS's to high speed signal processing and to developing models of highly complex processes. Two of the applications, the Weld Bead Geometry Control System and the Welding Penetration Monitoring System, are discussed in the body of this paper.

An FPGA Implementation of a Polychronous Spiking Neural Network with Delay Adaptation.

PubMed

Wang, Runchun; Cohen, Gregory; Stiefel, Klaus M; Hamilton, Tara Julia; Tapson, Jonathan; van Schaik, André

2013-01-01

We present an FPGA implementation of a re-configurable, polychronous spiking neural network with a large capacity for spatial-temporal patterns. The proposed neural network generates delay paths de novo, so that only connections that actually appear in the training patterns will be created. This allows the proposed network to use all the axons (variables) to store information. Spike Timing Dependent Delay Plasticity is used to fine-tune and add dynamics to the network. We use a time multiplexing approach allowing us to achieve 4096 (4k) neurons and up to 1.15 million programmable delay axons on a Virtex 6 FPGA. Test results show that the proposed neural network is capable of successfully recalling more than 95% of all spikes for 96% of the stored patterns. The tests also show that the neural network is robust to noise from random input spikes.

Heuristic pattern correction scheme using adaptively trained generalized regression neural networks.

PubMed

Hoya, T; Chambers, J A

2001-01-01

In many pattern classification problems, an intelligent neural system is required which can learn the newly encountered but misclassified patterns incrementally, while keeping a good classification performance over the past patterns stored in the network. In the paper, an heuristic pattern correction scheme is proposed using adaptively trained generalized regression neural networks (GRNNs). The scheme is based upon both network growing and dual-stage shrinking mechanisms. In the network growing phase, a subset of the misclassified patterns in each incoming data set is iteratively added into the network until all the patterns in the incoming data set are classified correctly. Then, the redundancy in the growing phase is removed in the dual-stage network shrinking. Both long- and short-term memory models are considered in the network shrinking, which are motivated from biological study of the brain. The learning capability of the proposed scheme is investigated through extensive simulation studies.

Long-Term Memory Stabilized by Noise-Induced Rehearsal

PubMed Central

Wei, Yi

2014-01-01

Cortical networks can maintain memories for decades despite the short lifetime of synaptic strengths. Can a neural network store long-lasting memories in unstable synapses? Here, we study the effects of ongoing spike-timing-dependent plasticity (STDP) on the stability of memory patterns stored in synapses of an attractor neural network. We show that certain classes of STDP rules can stabilize all stored memory patterns despite a short lifetime of synapses. In our model, unstructured neural noise, after passing through the recurrent network connections, carries the imprint of all memory patterns in temporal correlations. STDP, combined with these correlations, leads to reinforcement of all stored patterns, even those that are never explicitly visited. Our findings may provide the functional reason for irregular spiking displayed by cortical neurons and justify models of system memory consolidation. Therefore, we propose that irregular neural activity is the feature that helps cortical networks maintain stable connections. PMID:25411507

Increasing Spontaneous Retinal Activity before Eye Opening Accelerates the Development of Geniculate Receptive Fields

PubMed Central

Davis, Zachary W.; Chapman, Barbara

2015-01-01

Visually evoked activity is necessary for the normal development of the visual system. However, little is known about the capacity for patterned spontaneous activity to drive the maturation of receptive fields before visual experience. Retinal waves provide instructive retinotopic information for the anatomical organization of the visual thalamus. To determine whether retinal waves also drive the maturation of functional responses, we increased the frequency of retinal waves pharmacologically in the ferret (Mustela putorius furo) during a period of retinogeniculate development before eye opening. The development of geniculate receptive fields after receiving these increased neural activities was measured using single-unit electrophysiology. We found that increased retinal waves accelerate the developmental reduction of geniculate receptive field sizes. This reduction is due to a decrease in receptive field center size rather than an increase in inhibitory surround strength. This work reveals an instructive role for patterned spontaneous activity in guiding the functional development of neural circuits. SIGNIFICANCE STATEMENT Patterned spontaneous neural activity that occurs during development is known to be necessary for the proper formation of neural circuits. However, it is unknown whether the spontaneous activity alone is sufficient to drive the maturation of the functional properties of neurons. Our work demonstrates for the first time an acceleration in the maturation of neural function as a consequence of driving patterned spontaneous activity during development. This work has implications for our understanding of how neural circuits can be modified actively to improve function prematurely or to recover from injury with guided interventions of patterned neural activity. PMID:26511250

Neural correlates of own- and other-race face perception: spatial and temporal response differences.

PubMed

Natu, Vaidehi; Raboy, David; O'Toole, Alice J

2011-02-01

Humans show an "other-race effect" for face recognition, with more accurate recognition of own- versus other-race faces. We compared the neural representations of own- and other-race faces using functional magnetic resonance imaging (fMRI) data in combination with a multi-voxel pattern classifier. Neural activity was recorded while Asians and Caucasians viewed Asian and Caucasian faces. A pattern classifier, applied to voxels across a broad range of ventral temporal areas, discriminated the brain activity maps elicited in response to Asian versus Caucasian faces in the brains of both Asians and Caucasians. Classification was most accurate in the first few time points of the block and required the use of own-race faces in the localizer scan to select voxels for classifier input. Next, we examined differences in the time-course of neural responses to own- and other-race faces and found evidence for a temporal "other-race effect." Own-race faces elicited a larger neural response initially that attenuated rapidly. The response to other-race faces was weaker at first, but increased over time, ultimately surpassing the magnitude of the own-race response in the fusiform "face" area (FFA). A similar temporal response pattern held across a broad range of ventral temporal areas. The pattern-classification results indicate the early availability of categorical information about own- versus other-race face status in the spatial pattern of neural activity. The slower, more sustained, brain response to other-race faces may indicate the need to recruit additional neural resources to process other-race faces for identification. Copyright © 2010 Elsevier Inc. All rights reserved.

Neuromorphic Hardware Architecture Using the Neural Engineering Framework for Pattern Recognition.

PubMed

Wang, Runchun; Thakur, Chetan Singh; Cohen, Gregory; Hamilton, Tara Julia; Tapson, Jonathan; van Schaik, Andre

2017-06-01

We present a hardware architecture that uses the neural engineering framework (NEF) to implement large-scale neural networks on field programmable gate arrays (FPGAs) for performing massively parallel real-time pattern recognition. NEF is a framework that is capable of synthesising large-scale cognitive systems from subnetworks and we have previously presented an FPGA implementation of the NEF that successfully performs nonlinear mathematical computations. That work was developed based on a compact digital neural core, which consists of 64 neurons that are instantiated by a single physical neuron using a time-multiplexing approach. We have now scaled this approach up to build a pattern recognition system by combining identical neural cores together. As a proof of concept, we have developed a handwritten digit recognition system using the MNIST database and achieved a recognition rate of 96.55%. The system is implemented on a state-of-the-art FPGA and can process 5.12 million digits per second. The architecture and hardware optimisations presented offer high-speed and resource-efficient means for performing high-speed, neuromorphic, and massively parallel pattern recognition and classification tasks.

A New Local Bipolar Autoassociative Memory Based on External Inputs of Discrete Recurrent Neural Networks With Time Delay.

PubMed

Zhou, Caigen; Zeng, Xiaoqin; Luo, Chaomin; Zhang, Huaguang

In this paper, local bipolar auto-associative memories are presented based on discrete recurrent neural networks with a class of gain type activation function. The weight parameters of neural networks are acquired by a set of inequalities without the learning procedure. The global exponential stability criteria are established to ensure the accuracy of the restored patterns by considering time delays and external inputs. The proposed methodology is capable of effectively overcoming spurious memory patterns and achieving memory capacity. The effectiveness, robustness, and fault-tolerant capability are validated by simulated experiments.In this paper, local bipolar auto-associative memories are presented based on discrete recurrent neural networks with a class of gain type activation function. The weight parameters of neural networks are acquired by a set of inequalities without the learning procedure. The global exponential stability criteria are established to ensure the accuracy of the restored patterns by considering time delays and external inputs. The proposed methodology is capable of effectively overcoming spurious memory patterns and achieving memory capacity. The effectiveness, robustness, and fault-tolerant capability are validated by simulated experiments.

Towards multifocal ultrasonic neural stimulation: pattern generation algorithms

NASA Astrophysics Data System (ADS)

Hertzberg, Yoni; Naor, Omer; Volovick, Alexander; Shoham, Shy

2010-10-01

Focused ultrasound (FUS) waves directed onto neural structures have been shown to dynamically modulate neural activity and excitability, opening up a range of possible systems and applications where the non-invasiveness, safety, mm-range resolution and other characteristics of FUS are advantageous. As in other neuro-stimulation and modulation modalities, the highly distributed and parallel nature of neural systems and neural information processing call for the development of appropriately patterned stimulation strategies which could simultaneously address multiple sites in flexible patterns. Here, we study the generation of sparse multi-focal ultrasonic distributions using phase-only modulation in ultrasonic phased arrays. We analyse the relative performance of an existing algorithm for generating multifocal ultrasonic distributions and new algorithms that we adapt from the field of optical digital holography, and find that generally the weighted Gerchberg-Saxton algorithm leads to overall superior efficiency and uniformity in the focal spots, without significantly increasing the computational burden. By combining phased-array FUS and magnetic-resonance thermometry we experimentally demonstrate the simultaneous generation of tightly focused multifocal distributions in a tissue phantom, a first step towards patterned FUS neuro-modulation systems and devices.

Fear and the Defense Cascade: Clinical Implications and Management.

PubMed

Kozlowska, Kasia; Walker, Peter; McLean, Loyola; Carrive, Pascal

2015-01-01

Evolution has endowed all humans with a continuum of innate, hard-wired, automatically activated defense behaviors, termed the defense cascade. Arousal is the first step in activating the defense cascade; flight or fight is an active defense response for dealing with threat; freezing is a flight-or-fight response put on hold; tonic immobility and collapsed immobility are responses of last resort to inescapable threat, when active defense responses have failed; and quiescent immobility is a state of quiescence that promotes rest and healing. Each of these defense reactions has a distinctive neural pattern mediated by a common neural pathway: activation and inhibition of particular functional components in the amygdala, hypothalamus, periaqueductal gray, and sympathetic and vagal nuclei. Unlike animals, which generally are able to restore their standard mode of functioning once the danger is past, humans often are not, and they may find themselves locked into the same, recurring pattern of response tied in with the original danger or trauma. Understanding the signature patterns of these innate responses--the particular components that combine to yield the given pattern of defense-is important for developing treatment interventions. Effective interventions aim to activate or deactivate one or more components of the signature neural pattern, thereby producing a shift in the neural pattern and, with it, in mind-body state. The process of shifting the neural pattern is the necessary first step in unlocking the patient's trauma response, in breaking the cycle of suffering, and in helping the patient to adapt to, and overcome, past trauma.

Organization of Anti-Phase Synchronization Pattern in Neural Networks: What are the Key Factors?

PubMed Central

Li, Dong; Zhou, Changsong

2011-01-01

Anti-phase oscillation has been widely observed in cortical neural network. Elucidating the mechanism underlying the organization of anti-phase pattern is of significance for better understanding more complicated pattern formations in brain networks. In dynamical systems theory, the organization of anti-phase oscillation pattern has usually been considered to relate to time delay in coupling. This is consistent to conduction delays in real neural networks in the brain due to finite propagation velocity of action potentials. However, other structural factors in cortical neural network, such as modular organization (connection density) and the coupling types (excitatory or inhibitory), could also play an important role. In this work, we investigate the anti-phase oscillation pattern organized on a two-module network of either neuronal cell model or neural mass model, and analyze the impact of the conduction delay times, the connection densities, and coupling types. Our results show that delay times and coupling types can play key roles in this organization. The connection densities may have an influence on the stability if an anti-phase pattern exists due to the other factors. Furthermore, we show that anti-phase synchronization of slow oscillations can be achieved with small delay times if there is interaction between slow and fast oscillations. These results are significant for further understanding more realistic spatiotemporal dynamics of cortico-cortical communications. PMID:22232576

Diversity of Sternaspidae (Annelida: Terebellida) in the South China Sea, with descriptions of four new species.

PubMed

Wu, Xuwen; Xu, Kuidong

2017-03-20

Sternaspidae is one of the most common groups of polychaetes in the South China Sea, where however, the knowledge of its diversity and distribution is insufficiently understood and reports of the European species Sternaspis scutata are misidentifications. Based on the examination of material deposited in the Marine Biological Museum of the Chinese Academy of Sciences, we made a comprehensive investigation on the sternaspid polychaetes in the northern South China Sea. Five species belonging to two genera are described: Petersenaspis salazari sp. nov., Sternaspis radiata sp. nov., S. spinosa Sluiter, 1882, S. sunae sp. nov. and S. wui sp. nov. A taxonomic key to ten species of Sternaspidae found in the South China Sea is provided.

Microplastics reduced posterior segment regeneration rate of the polychaete Perinereis aibuhitensis.

PubMed

Leung, Julia; Chan, Kit Yu Karen

2018-04-01

Microplastics are found in abundance in and on coastal sediments, and yet, whether exposure to this emerging pollutant negatively impact whole organism function is unknown. Focusing on a commercially important polychaete, Perinereis aibuhitensis, we demonstrated that presence of microplastics increased mortality and reduced the rate of posterior segment regeneration. The impact of the micro-polystyrene beads was size-dependent with smaller beads (8-12μm in diameter) being more detrimental than those bigger in size (32-38μm). This observed difference suggests microplastic impact could be affected by physical properties, e.g., sinking speed, surface area available for sorption of chemicals and bacteria, and selective feeding behaviors of the target organism. Copyright © 2017 Elsevier Ltd. All rights reserved.

COMMUNICATION Designing a somatosensory neural prosthesis: percepts evoked by different patterns of thalamic stimulation

NASA Astrophysics Data System (ADS)

Heming, Ethan; Sanden, Andrew; Kiss, Zelma H. T.

2010-12-01

Although major advances have been made in the development of motor prostheses, fine motor control requires intuitive somatosensory feedback. Here we explored whether a thalamic site for a somatosensory neural prosthetic could provide natural somatic sensation to humans. Different patterns of electrical stimulation (obtained from thalamic spike trains) were applied in patients undergoing deep brain stimulation surgery. Changes in pattern produced different sensations, while preserving somatotopic representation. While most percepts were reported as 'unnatural', some stimulations produced more 'natural' sensations than others. However, the additional patterns did not elicit more 'natural' percepts than high-frequency (333 Hz) electrical stimulation. These features suggest that despite some limitations, the thalamus may be a feasible site for a somatosensory neural prosthesis and different stimulation patterns may be useful in its development.

Sex differences in autism: a resting-state fMRI investigation of functional brain connectivity in males and females

PubMed Central

Swinnen, Stephan P.; Wenderoth, Nicole

2016-01-01

Autism spectrum disorders (ASD) are far more prevalent in males than in females. Little is known however about the differential neural expression of ASD in males and females. We used a resting-state fMRI-dataset comprising 42 males/42 females with ASD and 75 male/75 female typical-controls to examine whether autism-related alterations in intrinsic functional connectivity are similar or different in males and females, and particularly whether alterations reflect ‘neural masculinization’, as predicted by the Extreme Male Brain theory. Males and females showed a differential neural expression of ASD, characterized by highly consistent patterns of hypo-connectivity in males with ASD (compared to typical males), and hyper-connectivity in females with ASD (compared to typical females). Interestingly, patterns of hyper-connectivity in females with ASD reflected a shift towards the (high) connectivity levels seen in typical males (neural masculinization), whereas patterns of hypo-connectivity observed in males with ASD reflected a shift towards the (low) typical feminine connectivity patterns (neural feminization). Our data support the notion that ASD is a disorder of sexual differentiation rather than a disorder characterized by masculinization in both genders. Future work is needed to identify underlying factors such as sex hormonal alterations that drive these sex-specific neural expressions of ASD. PMID:26989195

AmphiPax3/7, an amphioxus paired box gene: insights into chordate myogenesis, neurogenesis, and the possible evolutionary precursor of definitive vertebrate neural crest.

PubMed

Holland, L Z; Schubert, M; Kozmik, Z; Holland, N D

1999-01-01

Amphioxus probably has only a single gene (AmphiPax3/7) in the Pax3/7 subfamily. Like its vertebrate homologs (Pax3 and Pax7), amphioxus AmphiPax3/7 is probably involved in specifying the axial musculature and muscularized notochord. During nervous system development, AmphiPax3/7 is first expressed in bilateral anteroposterior stripes along the edges of the neural plate. This early neural expression may be comparable to the transcription of Pax3 and Pax7 in some of the anterior neural crest cells of vertebrates. Previous studies by others and ourselves have demonstrated that several genes homologous to genetic markers for vertebrate neural crest are expressed along the neural plate-epidermis boundary in embryos of tunicates and amphioxus. Taken together, the early neural expression patterns of AmphiPax3/7 and other neural crest markers of amphioxus and tunicates suggest that cell populations that eventually gave rise to definitive vertebrate neural crest may have been present in ancestral invertebrate chordates. During later neurogenesis in amphioxus, AmphiPax3/7, like its vertebrate homologs, is expressed dorsally and dorsolaterally in the neural tube and may be involved in dorsoventral patterning. However, unlike its vertebrate homologs, AmphiPax3/7 is expressed only at the anterior end of the central nervous system instead of along much of the neuraxis; this amphioxus pattern may represent the loss of a primitive chordate character.

Oscillator Neural Network Retrieving Sparsely Coded Phase Patterns

NASA Astrophysics Data System (ADS)

Aoyagi, Toshio; Nomura, Masaki

1999-08-01

Little is known theoretically about the associative memory capabilities of neural networks in which information is encoded not only in the mean firing rate but also in the timing of firings. Particularly, in the case of sparsely coded patterns, it is biologically important to consider the timings of firings and to study how such consideration influences storage capacities and quality of recalled patterns. For this purpose, we propose a simple extended model of oscillator neural networks to allow for expression of a nonfiring state. Analyzing both equilibrium states and dynamical properties in recalling processes, we find that the system possesses good associative memory.

Investigating Patterns for Self-Induced Emotion Recognition from EEG Signals.

PubMed

Zhuang, Ning; Zeng, Ying; Yang, Kai; Zhang, Chi; Tong, Li; Yan, Bin

2018-03-12

Most current approaches to emotion recognition are based on neural signals elicited by affective materials such as images, sounds and videos. However, the application of neural patterns in the recognition of self-induced emotions remains uninvestigated. In this study we inferred the patterns and neural signatures of self-induced emotions from electroencephalogram (EEG) signals. The EEG signals of 30 participants were recorded while they watched 18 Chinese movie clips which were intended to elicit six discrete emotions, including joy, neutrality, sadness, disgust, anger and fear. After watching each movie clip the participants were asked to self-induce emotions by recalling a specific scene from each movie. We analyzed the important features, electrode distribution and average neural patterns of different self-induced emotions. Results demonstrated that features related to high-frequency rhythm of EEG signals from electrodes distributed in the bilateral temporal, prefrontal and occipital lobes have outstanding performance in the discrimination of emotions. Moreover, the six discrete categories of self-induced emotion exhibit specific neural patterns and brain topography distributions. We achieved an average accuracy of 87.36% in the discrimination of positive from negative self-induced emotions and 54.52% in the classification of emotions into six discrete categories. Our research will help promote the development of comprehensive endogenous emotion recognition methods.

Investigating Patterns for Self-Induced Emotion Recognition from EEG Signals

PubMed Central

Zeng, Ying; Yang, Kai; Tong, Li; Yan, Bin

2018-01-01

Most current approaches to emotion recognition are based on neural signals elicited by affective materials such as images, sounds and videos. However, the application of neural patterns in the recognition of self-induced emotions remains uninvestigated. In this study we inferred the patterns and neural signatures of self-induced emotions from electroencephalogram (EEG) signals. The EEG signals of 30 participants were recorded while they watched 18 Chinese movie clips which were intended to elicit six discrete emotions, including joy, neutrality, sadness, disgust, anger and fear. After watching each movie clip the participants were asked to self-induce emotions by recalling a specific scene from each movie. We analyzed the important features, electrode distribution and average neural patterns of different self-induced emotions. Results demonstrated that features related to high-frequency rhythm of EEG signals from electrodes distributed in the bilateral temporal, prefrontal and occipital lobes have outstanding performance in the discrimination of emotions. Moreover, the six discrete categories of self-induced emotion exhibit specific neural patterns and brain topography distributions. We achieved an average accuracy of 87.36% in the discrimination of positive from negative self-induced emotions and 54.52% in the classification of emotions into six discrete categories. Our research will help promote the development of comprehensive endogenous emotion recognition methods. PMID:29534515

Rotation-invariant neural pattern recognition system with application to coin recognition.

PubMed

Fukumi, M; Omatu, S; Takeda, F; Kosaka, T

1992-01-01

In pattern recognition, it is often necessary to deal with problems to classify a transformed pattern. A neural pattern recognition system which is insensitive to rotation of input pattern by various degrees is proposed. The system consists of a fixed invariance network with many slabs and a trainable multilayered network. The system was used in a rotation-invariant coin recognition problem to distinguish between a 500 yen coin and a 500 won coin. The results show that the approach works well for variable rotation pattern recognition.

Neural coding in graphs of bidirectional associative memories.

PubMed

Bouchain, A David; Palm, Günther

2012-01-24

In the last years we have developed large neural network models for the realization of complex cognitive tasks in a neural network architecture that resembles the network of the cerebral cortex. We have used networks of several cortical modules that contain two populations of neurons (one excitatory, one inhibitory). The excitatory populations in these so-called "cortical networks" are organized as a graph of Bidirectional Associative Memories (BAMs), where edges of the graph correspond to BAMs connecting two neural modules and nodes of the graph correspond to excitatory populations with associative feedback connections (and inhibitory interneurons). The neural code in each of these modules consists essentially of the firing pattern of the excitatory population, where mainly it is the subset of active neurons that codes the contents to be represented. The overall activity can be used to distinguish different properties of the patterns that are represented which we need to distinguish and control when performing complex tasks like language understanding with these cortical networks. The most important pattern properties or situations are: exactly fitting or matching input, incomplete information or partially matching pattern, superposition of several patterns, conflicting information, and new information that is to be learned. We show simple simulations of these situations in one area or module and discuss how to distinguish these situations based on the overall internal activation of the module. This article is part of a Special Issue entitled "Neural Coding". Copyright © 2011 Elsevier B.V. All rights reserved.

Time and Category Information in Pattern-Based Codes

PubMed Central

Eyherabide, Hugo Gabriel; Samengo, Inés

2010-01-01

Sensory stimuli are usually composed of different features (the what) appearing at irregular times (the when). Neural responses often use spike patterns to represent sensory information. The what is hypothesized to be encoded in the identity of the elicited patterns (the pattern categories), and the when, in the time positions of patterns (the pattern timing). However, this standard view is oversimplified. In the real world, the what and the when might not be separable concepts, for instance, if they are correlated in the stimulus. In addition, neuronal dynamics can condition the pattern timing to be correlated with the pattern categories. Hence, timing and categories of patterns may not constitute independent channels of information. In this paper, we assess the role of spike patterns in the neural code, irrespective of the nature of the patterns. We first define information-theoretical quantities that allow us to quantify the information encoded by different aspects of the neural response. We also introduce the notion of synergy/redundancy between time positions and categories of patterns. We subsequently establish the relation between the what and the when in the stimulus with the timing and the categories of patterns. To that aim, we quantify the mutual information between different aspects of the stimulus and different aspects of the response. This formal framework allows us to determine the precise conditions under which the standard view holds, as well as the departures from this simple case. Finally, we study the capability of different response aspects to represent the what and the when in the neural response. PMID:21151371

Higher-order neural network software for distortion invariant object recognition

NASA Technical Reports Server (NTRS)

Reid, Max B.; Spirkovska, Lilly

1991-01-01

The state-of-the-art in pattern recognition for such applications as automatic target recognition and industrial robotic vision relies on digital image processing. We present a higher-order neural network model and software which performs the complete feature extraction-pattern classification paradigm required for automatic pattern recognition. Using a third-order neural network, we demonstrate complete, 100 percent accurate invariance to distortions of scale, position, and in-plate rotation. In a higher-order neural network, feature extraction is built into the network, and does not have to be learned. Only the relatively simple classification step must be learned. This is key to achieving very rapid training. The training set is much smaller than with standard neural network software because the higher-order network only has to be shown one view of each object to be learned, not every possible view. The software and graphical user interface run on any Sun workstation. Results of the use of the neural software in autonomous robotic vision systems are presented. Such a system could have extensive application in robotic manufacturing.

Flow Pattern Identification of Horizontal Two-Phase Refrigerant Flow Using Neural Networks

DTIC Science & Technology

2015-12-31

AFRL-RQ-WP-TP-2016-0079 FLOW PATTERN IDENTIFICATION OF HORIZONTAL TWO-PHASE REFRIGERANT FLOW USING NEURAL NETWORKS (POSTPRINT) Abdeel J...Journal Article Postprint 01 October 2013 – 22 June 2015 4. TITLE AND SUBTITLE FLOW PATTERN IDENTIFICATION OF HORIZONTAL TWO-PHASE REFRIGERANT FLOW USING...networks were used to automatically identify two-phase flow patterns for refrigerant R-134a flowing in a horizontal tube. In laboratory experiments

Neural network-based system for pattern recognition through a fiber optic bundle

NASA Astrophysics Data System (ADS)

Gamo-Aranda, Javier; Rodriguez-Horche, Paloma; Merchan-Palacios, Miguel; Rosales-Herrera, Pablo; Rodriguez, M.

2001-04-01

A neural network based system to identify images transmitted through a Coherent Fiber-optic Bundle (CFB) is presented. Patterns are generated in a computer, displayed on a Spatial Light Modulator, imaged onto the input face of the CFB, and recovered optically by a CCD sensor array for further processing. Input and output optical subsystems were designed and used to that end. The recognition step of the transmitted patterns is made by a powerful, widely-used, neural network simulator running on the control PC. A complete PC-based interface was developed to control the different tasks involved in the system. An optical analysis of the system capabilities was carried out prior to performing the recognition step. Several neural network topologies were tested, and the corresponding numerical results are also presented and discussed.

Revealing polychaetes invasion patterns: Identification, reproduction and potential risks of the Korean ragworm, Perinereis linea (Treadwell), in the Western Mediterranean

NASA Astrophysics Data System (ADS)

Arias, Andrés; Richter, Alexandra; Anadón, Nuria; Glasby, Christopher J.

2013-10-01

An established population of the polychaetous annelid Perinereis linea (Treadwell) is reported for the first time outside its native distribution range (NW Pacific). This exotic worm has reached the Western Mediterranean (Mar Menor lagoon) via importing live fishing-bait as it is commonly used by anglers in Mar Menor lagoon, an area largely used for recreational fishing. To avoid confusion with other related species, and because the scientific name has been in synonymy for many years, P. linea is redescribed and illustrated. We focus on the reproductive biology and ecology of P. linea to help to understand its introduction, naturalization and spread along this coastal lagoon. Comparison between the Mediterranean population with a native population from South Korea revealed that the species exhibits a great reproductive plasticity and adaptability, which depends on the environmental conditions. Perinereis linea can reproduce after acquiring the epitokous form or prior to complete epitokal modification. In the Mar Menor lagoon population females release eggs asynchronically without completing epitokal modifications. However, under particular laboratory conditions females produce eggs synchronically and release them after complete epitokal transformations. Fertilization can occur internally in the female coelom, and females release zygotes and larvae through openings in their body walls; they are then incubated in gelatinous masses attached to the female parapodia. The sperm morphology is of the ent-aquasperm type. The eggs and larvae are attacked by symbiotic ciliate protozoa that feed on their yolk reserves. These foreign ciliates may act as carriers of disease in native beachworms and constitute an important risk for the ecosystem health. Finally, we provide recommendations on the prevention of the adverse effects that this exotic ragworm can cause in receiving ecosystems.

Macrobenthic Biomass Relations in the Faroe-Shetland Channel: An Arctic-Atlantic Boundary Environment

PubMed Central

Narayanaswamy, Bhavani E.; Bett, Brian J.

2011-01-01

The Faroe-Shetland Channel, located in the NE Atlantic, ranges in depth from 0–1700 m and is an unusual deep-sea environment because of its complex and dynamic hydrographic regime, as well as having numerous different seafloor habitats. Macrofaunal samples have been collected on a 0.5 mm mesh sieve from over 300 stations in a wide area survey and on nested 0.5 and 0.25 mm mesh sieves along a specific depth transect. Contrary to general expectation, macrofauanl biomass in the Channel did not decline with increasing depth. When examined at phylum level, two main biomass patterns with depth were apparent: (a) polychaetes showed little change in biomass on the upper slope then increased markedly below 500 m to a depth of 1100 m before declining; and (b) other phyla showed enhanced biomass between 300–500 m. The polychaete response may be linked with a seafloor environment change to relatively quiescent hydrodynamic conditions and an increasing sediment mud content that occurs at c. 500 m. In contrast, the mid-slope enhancement of other phyla biomass may reflect the hydrodynamically active interface between the warm and cold water masses present in the Channel at c. 300–500 m. Again contrary to expectation, mean macrofaunal body size did not decline with depth, and the relative contribution of smaller (>0.25 mm<0.5 mm) to total (>0.25 mm) macrobenthos did not increase with depth. Overall our total biomass and average individual biomass estimates appear to be greater than those predicted from global analyses. It is clear that global models of benthic biomass distribution may mask significant variations at the local and regional scale. PMID:21526171

Anthropogenic disturbance and biodiversity of marine benthic communities in Antarctica: a regional comparison.

PubMed

Stark, Jonathan S; Kim, Stacy L; Oliver, John S

2014-01-01

The impacts of two Antarctic stations in different regions, on marine sediment macrofaunal communities were compared: McMurdo, a very large station in the Ross Sea; and Casey, a more typical small station in East Antarctica. Community structure and diversity were compared along a gradient of anthropogenic disturbance from heavily contaminated to uncontaminated locations. We examined some of the inherent problems in comparing data from unrelated studies, such as different sampling methods, spatial and temporal scales of sampling and taxonomic uncertainty. These issues generated specific biases which were taken into account when interpreting patterns. Control sites in the two regions had very different communities but both were dominated by crustaceans. Community responses to anthropogenic disturbance (sediment contamination by metals, oils and sewage) were also different. At McMurdo the proportion of crustaceans decreased in disturbed areas and polychaetes became dominant, whereas at Casey, crustaceans increased in response to disturbance, largely through an increase in amphipods. Despite differing overall community responses there were some common elements. Ostracods, cumaceans and echinoderms were sensitive to disturbance in both regions. Capitellid, dorvelleid and orbiniid polychaetes were indicative of disturbed sites. Amphipods, isopods and tanaids had different responses at each station. Biodiversity and taxonomic distinctness were significantly lower at disturbed locations in both regions. The size of the impact, however, was not related to the level of contamination, with a larger reduction in biodiversity at Casey, the smaller, less polluted station. The impacts of small stations, with low to moderate levels of contamination, can thus be as great as those of large or heavily contaminated stations. Regional broad scale environmental influences may be important in determining the composition of communities and thus their response to disturbance, but there are some generalizations regarding responses which will aid future management of stations.

Firing patterns transition and desynchronization induced by time delay in neural networks

NASA Astrophysics Data System (ADS)

Huang, Shoufang; Zhang, Jiqian; Wang, Maosheng; Hu, Chin-Kun

2018-06-01

We used the Hindmarsh-Rose (HR) model (Hindmarsh and Rose, 1984) to study the effect of time delay on the transition of firing behaviors and desynchronization in neural networks. As time delay is increased, neural networks exhibit diversity of firing behaviors, including regular spiking or bursting and firing patterns transitions (FPTs). Meanwhile, the desynchronization of firing and unstable bursting with decreasing amplitude in neural system, are also increasingly enhanced with the increase of time delay. Furthermore, we also studied the effect of coupling strength and network randomness on these phenomena. Our results imply that time delays can induce transition and desynchronization of firing behaviors in neural networks. These findings provide new insight into the role of time delay in the firing activities of neural networks, and can help to better understand the firing phenomena in complex systems of neural networks. A possible mechanism in brain that can cause the increase of time delay is discussed.

Reproductive toxicity assessment of benzo[a]pyrene in the marine polychaete Perinereis nuntia

NASA Astrophysics Data System (ADS)

Wu, Qingyang; Wang, Shuqi; Chen, Xiaopeng; Li, Ping

2017-07-01

Benzo[a]pyrene (B[a]P) is an increasingly present marine environmental pollutant, yet our understanding of the long-term consequences of reproductive toxicity in marine benthic polychaetes remains limited. To test the reproductive toxicity of B[a]P on polychaetes, Perinereis nuntia was exposed to B[a]P-contaminated artificial seawater and sexual maturation, the sex ratio, number of eggs spawned, fertilization and hatching rated, as well as vitellogenin (VTG) mRNA expression levels were analyzed. A low concentration of B[a]P (2.5 μg/L) had no effects on the rate of sexual maturation, spawning, or fertilization but significantly increased the sex ratio (female: male) from 1.6±0.15:1 to 2.3±0.18:1, inhibited hatching rate by 27%, and significantly increased VTG mRNA expression level by 3.7-fold following a 60-day exposure, compared with those in the solvent controls. A higher concentration of B[a]P (25 μg/L) caused more serious effects; sexual maturation, fertilization success, and hatching decreased by 31%, 17% and 46%, respectively, and the sex ratio (female: male) and VTG mRNA gene expression level increased by 54% and 7.1-fold, respectively. These results demonstrate that sublethal concentrations of B[a]P negatively affect reproductive performance of the sandworm P. nuntia.

The biogenic reefs formed by the alien polychaete Hydroides dianthus (Serpulidae, Annelida) favor the polyp stage of Aurelia coerulea (Cnidaria, Scyphozoa) in a coastal artificial lake.

PubMed

Dong, Zhijun; Sun, Tingting; Wang, Lei

2018-04-01

Blooms of the moon jellyfish Aurelia coerulea frequently occur in coastal waters. The increased availability of substrates for the settlement and proliferation of polyps due to the expansion of artificial structures in coastal areas has been proposed as a possible contributing factor in jellyfish blooms. This paper investigates whether a marine artificial lake (Fenghuang Lake) provides additional substrates for A. coerulea polyps and contributes to jellyfish blooms. High densities of A. coerulea ephyrae were discovered in this lake, with a mean density of 41 individuals/m 3 and a maximum measured density of 128 individuals/m 3 . Meanwhile, A. coerulea ephyrae were also found in the two emptying channels outside the lake, with a mean density of 13 individuals/m 3 . Underwater surveys revealed that dense colonies of A. coerulea polyps occurred mainly on biogenic reefs formed by a polychaete, which was identified as an invasive serpulid species Hydroides dianthus, based on the phylogenetic analysis of mitochondrial COI gene sequences. Our study highlights the potential modification of habitats by the alien polychaete H. dianthus, which might provide complex benthic habits suitable for the settlement and proliferation of A. coerulea polyps and may contribute to jellyfish blooms in the marine artificial lake and nearby coastal waters. Copyright © 2018 Elsevier Ltd. All rights reserved.

Influence of environmental properties on macrobenthos in the northwest Indian shelf.

PubMed

Jayaraj, K A; Jayalakshmi, K V; Saraladevi, K

2007-04-01

The paper deals with the standing stock of macrobenthic infauna and associated environmental factors influencing the benthic community in the shelf region of the northwest Indian coast. The data were collected onboard FORV Sagar Sampada during the winter monsoon (January-February, 2003) to understand the community structure and the factors influencing the benthic distribution. The environmental parameters, sediment characteristics and macrobenthic infauna were collected at 26 stations distributed in the depths between 30 and 200 m extending from Mormugao to Porbander. Total benthic abundance was high in lower depths (50-75 m), and low values noticed at 30 m depth contour was peculiar. Polychaetes were the dominant group and were more abundant in shallow and middle depths with moderate organic matter, clay and relatively high dissolved oxygen. On the other hand crustaceans and molluscs were more abundant in deeper areas having sandy sediment and low temperature. High richness and diversity of whole benthic groups observed in deeper depths counter balanced the opposite trend shown by polychaete species. Generally benthos preferred medium grain sized texture with low organic matter and high organic matter had an adverse effect especially on filter feeders. Deposit feeding polychaetes dominated in shallow depths while carnivore species in the middle depths. Ecologically, benthos were controlled by a combination of factors such as temperature, salinity, dissolved oxygen, sand and organic matter and no single factor could be considered as an ecological master factor.

The neural signature of emotional memories in serial crimes.

PubMed

Chassy, Philippe

2017-10-01

Neural plasticity is the process whereby semantic information and emotional responses are stored in neural networks. It is hypothesized that the neural networks built over time to encode the sexual fantasies that motivate serial killers to act should display a unique, detectable activation pattern. The pathological neural watermark hypothesis posits that such networks comprise activation of brain sites that reflect four cognitive components: autobiographical memory, sexual arousal, aggression, and control over aggression. The neural sites performing these cognitive functions have been successfully identified by previous research. The key findings are reviewed to hypothesise the typical pattern of activity that serial killers should display. Through the integration of biological findings into one framework, the neural approach proposed in this paper is in stark contrast with the many theories accounting for serial killers that offer non-medical taxonomies. The pathological neural watermark hypothesis offers a new framework to understand and detect deviant individuals. The technical and legal issues are briefly discussed. Copyright © 2017 Elsevier Ltd. All rights reserved.

Fear and the Defense Cascade: Clinical Implications and Management

PubMed Central

Kozlowska, Kasia; Walker, Peter; McLean, Loyola; Carrive, Pascal

2015-01-01

Abstract Evolution has endowed all humans with a continuum of innate, hard-wired, automatically activated defense behaviors, termed the defense cascade. Arousal is the first step in activating the defense cascade; flight or fight is an active defense response for dealing with threat; freezing is a flight-or-fight response put on hold; tonic immobility and collapsed immobility are responses of last resort to inescapable threat, when active defense responses have failed; and quiescent immobility is a state of quiescence that promotes rest and healing. Each of these defense reactions has a distinctive neural pattern mediated by a common neural pathway: activation and inhibition of particular functional components in the amygdala, hypothalamus, periaqueductal gray, and sympathetic and vagal nuclei. Unlike animals, which generally are able to restore their standard mode of functioning once the danger is past, humans often are not, and they may find themselves locked into the same, recurring pattern of response tied in with the original danger or trauma. Understanding the signature patterns of these innate responses—the particular components that combine to yield the given pattern of defense—is important for developing treatment interventions. Effective interventions aim to activate or deactivate one or more components of the signature neural pattern, thereby producing a shift in the neural pattern and, with it, in mind-body state. The process of shifting the neural pattern is the necessary first step in unlocking the patient’s trauma response, in breaking the cycle of suffering, and in helping the patient to adapt to, and overcome, past trauma. PMID:26062169

Searching for patterns in remote sensing image databases using neural networks

NASA Technical Reports Server (NTRS)

Paola, Justin D.; Schowengerdt, Robert A.

1995-01-01

We have investigated a method, based on a successful neural network multispectral image classification system, of searching for single patterns in remote sensing databases. While defining the pattern to search for and the feature to be used for that search (spectral, spatial, temporal, etc.) is challenging, a more difficult task is selecting competing patterns to train against the desired pattern. Schemes for competing pattern selection, including random selection and human interpreted selection, are discussed in the context of an example detection of dense urban areas in Landsat Thematic Mapper imagery. When applying the search to multiple images, a simple normalization method can alleviate the problem of inconsistent image calibration. Another potential problem, that of highly compressed data, was found to have a minimal effect on the ability to detect the desired pattern. The neural network algorithm has been implemented using the PVM (Parallel Virtual Machine) library and nearly-optimal speedups have been obtained that help alleviate the long process of searching through imagery.

Neural network system for purposeful behavior based on foveal visual preprocessor

NASA Astrophysics Data System (ADS)

Golovan, Alexander V.; Shevtsova, Natalia A.; Klepatch, Arkadi A.

1996-10-01

Biologically plausible model of the system with an adaptive behavior in a priori environment and resistant to impairment has been developed. The system consists of input, learning, and output subsystems. The first subsystems classifies input patterns presented as n-dimensional vectors in accordance with some associative rule. The second one being a neural network determines adaptive responses of the system to input patterns. Arranged neural groups coding possible input patterns and appropriate output responses are formed during learning by means of negative reinforcement. Output subsystem maps a neural network activity into the system behavior in the environment. The system developed has been studied by computer simulation imitating a collision-free motion of a mobile robot. After some learning period the system 'moves' along a road without collisions. It is shown that in spite of impairment of some neural network elements the system functions reliably after relearning. Foveal visual preprocessor model developed earlier has been tested to form a kind of visual input to the system.

Compact holographic optical neural network system for real-time pattern recognition

NASA Astrophysics Data System (ADS)

Lu, Taiwei; Mintzer, David T.; Kostrzewski, Andrew A.; Lin, Freddie S.

1996-08-01

One of the important characteristics of artificial neural networks is their capability for massive interconnection and parallel processing. Recently, specialized electronic neural network processors and VLSI neural chips have been introduced in the commercial market. The number of parallel channels they can handle is limited because of the limited parallel interconnections that can be implemented with 1D electronic wires. High-resolution pattern recognition problems can require a large number of neurons for parallel processing of an image. This paper describes a holographic optical neural network (HONN) that is based on high- resolution volume holographic materials and is capable of performing massive 3D parallel interconnection of tens of thousands of neurons. A HONN with more than 16,000 neurons packaged in an attache case has been developed. Rotation- shift-scale-invariant pattern recognition operations have been demonstrated with this system. System parameters such as the signal-to-noise ratio, dynamic range, and processing speed are discussed.

Long-term memory stabilized by noise-induced rehearsal.

PubMed

Wei, Yi; Koulakov, Alexei A

2014-11-19

Cortical networks can maintain memories for decades despite the short lifetime of synaptic strengths. Can a neural network store long-lasting memories in unstable synapses? Here, we study the effects of ongoing spike-timing-dependent plasticity (STDP) on the stability of memory patterns stored in synapses of an attractor neural network. We show that certain classes of STDP rules can stabilize all stored memory patterns despite a short lifetime of synapses. In our model, unstructured neural noise, after passing through the recurrent network connections, carries the imprint of all memory patterns in temporal correlations. STDP, combined with these correlations, leads to reinforcement of all stored patterns, even those that are never explicitly visited. Our findings may provide the functional reason for irregular spiking displayed by cortical neurons and justify models of system memory consolidation. Therefore, we propose that irregular neural activity is the feature that helps cortical networks maintain stable connections. Copyright © 2014 the authors 0270-6474/14/3415804-12$15.00/0.

Indicators of sewage contamination in sediments beneath a deep-ocean dump site off New York

USGS Publications Warehouse

Bothner, Michael H.; Takada, H.; Knight, I.T.; Hill, R.T.; Butman, B.; Farrington, J.W.; Colwell, R.R.; Grassle, J. F.

1994-01-01

The world's largest discharge of municipal sewage sludge to surface waters of the deep sea has caused measurable changes in the concentration of sludge indicators in sea-floor sediments, in a spatial pattern which agrees with the predictions of a recent sludge deposition model. Silver, linear alkylbenzenes, coprostanol, and spores of the bacterium Clostridium perfringens, in bottom sediments and in near-bottom suspended sediment, provide evidence for rapid settling of a portion of discharged solids, accumulation on the sea floor, and biological mixing beneath the water sediment interface. Biological effects include an increase in 1989 of two species of benthic polychaete worm not abundant at the dump site before sludge dumping began in 1986. These changes in benthic ecology are attributed to the increased deposition of utilizable food in the form of sludge-derived organic matter.

Expansion of TALE homeobox genes and the evolution of spiralian development.

PubMed

Morino, Yoshiaki; Hashimoto, Naoki; Wada, Hiroshi

2017-12-01

Spiralians, including molluscs, annelids and platyhelminths, share a unique development process that includes the typical geometry of early cleavage and early segregation of cell fate in blastomeres along the animal-vegetal axis. However, the molecular mechanisms underlying this early cell fate segregation are largely unknown. Here, we report spiralian-specific expansion of the three-amino-acid loop extension (TALE) class of homeobox genes. During early development, some of these TALE genes are expressed in staggered domains along the animal-vegetal axis in the limpet Nipponacmea fuscoviridis and the polychaete Spirobranchus kraussii. Inhibition or overexpression of these genes alters the developmental fate of blastomeres, as predicted by the gene expression patterns. These results suggest that the expansion of novel TALE genes plays a critical role in the establishment of a novel cell fate segregation mechanism in spiralians.

Infaunal Benthic Communities from the Inner Shelf off Southwestern Africa Are Characterised by Generalist Species

PubMed Central

Steffani, Nina; Sedick, Safiyya; Rogers, John; Gibbons, Mark John

2015-01-01

Infaunal communities of benthic macro-organisms (≥ 1mm length) were studied from 81 samples collected across nine sites to the north and south of the Orange River in the Benguela upwelling ecosystem in 2003, with a view to describing communities and understanding the drivers of regional community structure, as well as to document diversity and to examine geographic affinities. Although the fauna was dominated by polychaetes and peracarid crustaceans, patterns in community structure could only weakly be explained by the measured environment (~35%). This is attributed to the generalist nature of the species recovered, which were widely distributed amongst different sediments, water-depths and latitudes. The fauna is dominated by species that enjoy a widespread regional and global distribution and is characterised by relatively low diversity, which is discussed. PMID:26618477

Axial mesendoderm refines rostrocaudal pattern in the chick nervous system.

PubMed

Rowan, A M; Stern, C D; Storey, K G

1999-07-01

There has long been controversy concerning the role of the axial mesoderm in the induction and rostrocaudal patterning of the vertebrate nervous system. Here we investigate the neural inducing and regionalising properties of defined rostrocaudal regions of head process/prospective notochord in the chick embryo by juxtaposing these tissues with extraembryonic epiblast or neural plate explants. We localise neural inducing signals to the emerging head process and using a large panel of region-specific neural markers, show that different rostrocaudal levels of the head process derived from headfold stage embryos can induce discrete regions of the central nervous system. However, we also find that rostral and caudal head process do not induce expression of any of these molecular markers in explants of the neural plate. During normal development the head process emerges beneath previously induced neural plate, which we show has already acquired some rostrocaudal character. Our findings therefore indicate that discrete regions of axial mesendoderm at headfold stages are not normally responsible for the establishment of rostrocaudal pattern in the neural plate. Strikingly however, we do find that caudal head process inhibits expression of rostral genes in neural plate explants. These findings indicate that despite the ability to induce specific rostrocaudal regions of the CNS de novo, signals provided by the discrete regions of axial mesendoderm do not appear to establish regional differences, but rather refine the rostrocaudal character of overlying neuroepithelium.

Cross-Level Effects Between Neurophysiology and Communication During Team Training.

PubMed

Gorman, Jamie C; Martin, Melanie J; Dunbar, Terri A; Stevens, Ronald H; Galloway, Trysha L; Amazeen, Polemnia G; Likens, Aaron D

2016-02-01

We investigated cross-level effects, which are concurrent changes across neural and cognitive-behavioral levels of analysis as teams interact, between neurophysiology and team communication variables under variations in team training. When people work together as a team, they develop neural, cognitive, and behavioral patterns that they would not develop individually. It is currently unknown whether these patterns are associated with each other in the form of cross-level effects. Team-level neurophysiology and latent semantic analysis communication data were collected from submarine teams in a training simulation. We analyzed whether (a) both neural and communication variables change together in response to changes in training segments (briefing, scenario, or debriefing), (b) neural and communication variables mutually discriminate teams of different experience levels, and (c) peak cross-correlations between neural and communication variables identify how the levels are linked. Changes in training segment led to changes in both neural and communication variables, neural and communication variables mutually discriminated between teams of different experience levels, and peak cross-correlations indicated that changes in communication precede changes in neural patterns in more experienced teams. Cross-level effects suggest that teamwork is not reducible to a fundamental level of analysis and that training effects are spread out across neural and cognitive-behavioral levels of analysis. Cross-level effects are important to consider for theories of team performance and practical aspects of team training. Cross-level effects suggest that measurements could be taken at one level (e.g., neural) to assess team experience (or skill) on another level (e.g., cognitive-behavioral). © 2015, Human Factors and Ergonomics Society.

Dynamic Modulation of Sensory Cortex by Top-Down Spatial Attention

DTIC Science & Technology

2015-04-15

yet only in recent decades has the neural basis for these benefits begun to be studied. The studies presented here use EEG and MEG to identify patterns...presented here use EEG and MEG to identify patterns of neural activity related to the deployment of attention in extrapersonal space, and examine the...we use simultaneously recorded EEG/ MEG to examine the interaction of these top-down signals with neural responses evoked by attended and unattended

The efficacy of using human myoelectric signals to control the limbs of robots in space

NASA Technical Reports Server (NTRS)

Clark, Jane E.; Phillips, Sally J.

1988-01-01

This project was designed to investigate the usefulness of the myoelectric signal as a control in robotics applications. More specifically, the neural patterns associated with human arm and hand actions were studied to determine the efficacy of using these myoelectric signals to control the manipulator arm of a robot. The advantage of this approach to robotic control was the use of well-defined and well-practiced neural patterns already available to the system, as opposed to requiring the human operator to learn new tasks and establish new neural patterns in learning to control a joystick or mechanical coupling device.

Rotation and scale change invariant point pattern relaxation matching by the Hopfield neural network

NASA Astrophysics Data System (ADS)

Sang, Nong; Zhang, Tianxu

1997-12-01

Relaxation matching is one of the most relevant methods for image matching. The original relaxation matching technique using point patterns is sensitive to rotations and scale changes. We improve the original point pattern relaxation matching technique to be invariant to rotations and scale changes. A method that makes the Hopfield neural network perform this matching process is discussed. An advantage of this is that the relaxation matching process can be performed in real time with the neural network's massively parallel capability to process information. Experimental results with large simulated images demonstrate the effectiveness and feasibility of the method to perform point patten relaxation matching invariant to rotations and scale changes and the method to perform this matching by the Hopfield neural network. In addition, we show that the method presented can be tolerant to small random error.

Sex differences in autism: a resting-state fMRI investigation of functional brain connectivity in males and females.

PubMed

Alaerts, Kaat; Swinnen, Stephan P; Wenderoth, Nicole

2016-06-01

Autism spectrum disorders (ASD) are far more prevalent in males than in females. Little is known however about the differential neural expression of ASD in males and females. We used a resting-state fMRI-dataset comprising 42 males/42 females with ASD and 75 male/75 female typical-controls to examine whether autism-related alterations in intrinsic functional connectivity are similar or different in males and females, and particularly whether alterations reflect 'neural masculinization', as predicted by the Extreme Male Brain theory. Males and females showed a differential neural expression of ASD, characterized by highly consistent patterns of hypo-connectivity in males with ASD (compared to typical males), and hyper-connectivity in females with ASD (compared to typical females). Interestingly, patterns of hyper-connectivity in females with ASD reflected a shift towards the (high) connectivity levels seen in typical males (neural masculinization), whereas patterns of hypo-connectivity observed in males with ASD reflected a shift towards the (low) typical feminine connectivity patterns (neural feminization). Our data support the notion that ASD is a disorder of sexual differentiation rather than a disorder characterized by masculinization in both genders. Future work is needed to identify underlying factors such as sex hormonal alterations that drive these sex-specific neural expressions of ASD. © The Author (2016). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Neural dynamics based on the recognition of neural fingerprints

PubMed Central

Carrillo-Medina, José Luis; Latorre, Roberto

2015-01-01

Experimental evidence has revealed the existence of characteristic spiking features in different neural signals, e.g., individual neural signatures identifying the emitter or functional signatures characterizing specific tasks. These neural fingerprints may play a critical role in neural information processing, since they allow receptors to discriminate or contextualize incoming stimuli. This could be a powerful strategy for neural systems that greatly enhances the encoding and processing capacity of these networks. Nevertheless, the study of information processing based on the identification of specific neural fingerprints has attracted little attention. In this work, we study (i) the emerging collective dynamics of a network of neurons that communicate with each other by exchange of neural fingerprints and (ii) the influence of the network topology on the self-organizing properties within the network. Complex collective dynamics emerge in the network in the presence of stimuli. Predefined inputs, i.e., specific neural fingerprints, are detected and encoded into coexisting patterns of activity that propagate throughout the network with different spatial organization. The patterns evoked by a stimulus can survive after the stimulation is over, which provides memory mechanisms to the network. The results presented in this paper suggest that neural information processing based on neural fingerprints can be a plausible, flexible, and powerful strategy. PMID:25852531

Inactivity-induced phrenic and hypoglossal motor facilitation are differentially expressed following intermittent vs. sustained neural apnea

PubMed Central

Baertsch, N. A.

2013-01-01

Reduced respiratory neural activity elicits a rebound increase in phrenic and hypoglossal motor output known as inactivity-induced phrenic and hypoglossal motor facilitation (iPMF and iHMF, respectively). We hypothesized that, similar to other forms of respiratory plasticity, iPMF and iHMF are pattern sensitive. Central respiratory neural activity was reversibly reduced in ventilated rats by hyperventilating below the CO2 apneic threshold to create brief intermittent neural apneas (5, ∼1.5 min each, separated by 5 min), a single brief massed neural apnea (7.5 min), or a single prolonged neural apnea (30 min). Upon restoration of respiratory neural activity, long-lasting (>60 min) iPMF was apparent following brief intermittent and prolonged, but not brief massed, neural apnea. Further, brief intermittent and prolonged neural apnea elicited an increase in the maximum phrenic response to high CO2, suggesting that iPMF is associated with an increase in phrenic dynamic range. By contrast, only prolonged neural apnea elicited iHMF, which was transient in duration (<15 min). Intermittent, massed, and prolonged neural apnea all elicited a modest transient facilitation of respiratory frequency. These results indicate that iPMF, but not iHMF, is pattern sensitive, and that the response to respiratory neural inactivity is motor pool specific. PMID:23493368

Space-Time Neural Networks

NASA Technical Reports Server (NTRS)

Villarreal, James A.; Shelton, Robert O.

1992-01-01

Concept of space-time neural network affords distributed temporal memory enabling such network to model complicated dynamical systems mathematically and to recognize temporally varying spatial patterns. Digital filters replace synaptic-connection weights of conventional back-error-propagation neural network.

Using a neural network to proximity correct patterns written with a Cambridge electron beam microfabricator 10.5 lithography system

NASA Astrophysics Data System (ADS)

Cummings, K. D.; Frye, R. C.; Rietman, E. A.

1990-10-01

This letter describes the initial results of using a theoretical determination of the proximity function and an adaptively trained neural network to proximity-correct patterns written on a Cambridge electron beam lithography system. The methods described are complete and may be applied to any electron beam exposure system that can modify the dose during exposure. The patterns produced in resist show the effects of proximity correction versus noncorrected patterns.

Evidence for a neural law of effect.

PubMed

Athalye, Vivek R; Santos, Fernando J; Carmena, Jose M; Costa, Rui M

2018-03-02

Thorndike's law of effect states that actions that lead to reinforcements tend to be repeated more often. Accordingly, neural activity patterns leading to reinforcement are also reentered more frequently. Reinforcement relies on dopaminergic activity in the ventral tegmental area (VTA), and animals shape their behavior to receive dopaminergic stimulation. Seeking evidence for a neural law of effect, we found that mice learn to reenter more frequently motor cortical activity patterns that trigger optogenetic VTA self-stimulation. Learning was accompanied by gradual shaping of these patterns, with participating neurons progressively increasing and aligning their covariance to that of the target pattern. Motor cortex patterns that lead to phasic dopaminergic VTA activity are progressively reinforced and shaped, suggesting a mechanism by which animals select and shape actions to reliably achieve reinforcement. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Reconstruction of magnetic configurations in W7-X using artificial neural networks

NASA Astrophysics Data System (ADS)

Böckenhoff, Daniel; Blatzheim, Marko; Hölbe, Hauke; Niemann, Holger; Pisano, Fabio; Labahn, Roger; Pedersen, Thomas Sunn; The W7-X Team

2018-05-01

It is demonstrated that artificial neural networks can be used to accurately and efficiently predict details of the magnetic topology at the plasma edge of the Wendelstein 7-X stellarator, based on simulated as well as measured heat load patterns onto plasma-facing components observed with infrared cameras. The connection between heat load patterns and the magnetic topology is a challenging regression problem, but one that suits artificial neural networks well. The use of a neural network makes it feasible to analyze and control the plasma exhaust in real-time, an important goal for Wendelstein 7-X, and for magnetic confinement fusion research in general.

Decoding-Accuracy-Based Sequential Dimensionality Reduction of Spatio-Temporal Neural Activities

NASA Astrophysics Data System (ADS)

Funamizu, Akihiro; Kanzaki, Ryohei; Takahashi, Hirokazu

Performance of a brain machine interface (BMI) critically depends on selection of input data because information embedded in the neural activities is highly redundant. In addition, properly selected input data with a reduced dimension leads to improvement of decoding generalization ability and decrease of computational efforts, both of which are significant advantages for the clinical applications. In the present paper, we propose an algorithm of sequential dimensionality reduction (SDR) that effectively extracts motor/sensory related spatio-temporal neural activities. The algorithm gradually reduces input data dimension by dropping neural data spatio-temporally so as not to undermine the decoding accuracy as far as possible. Support vector machine (SVM) was used as the decoder, and tone-induced neural activities in rat auditory cortices were decoded into the test tone frequencies. SDR reduced the input data dimension to a quarter and significantly improved the accuracy of decoding of novel data. Moreover, spatio-temporal neural activity patterns selected by SDR resulted in significantly higher accuracy than high spike rate patterns or conventionally used spatial patterns. These results suggest that the proposed algorithm can improve the generalization ability and decrease the computational effort of decoding.

Futurism - Neither Nurturing Nor Training for Education.

ERIC Educational Resources Information Center

Kise, Leonard K.; Swanson, Jennie E.

The paper considers the future of education, particularly special education, in terms of theory. Reviewed is research in neurology relating to contra-lateral development in brain hemispheres, cephalo-caudal and caudal-cephalo myelination patterns or neural systems, and integration of neural patterns and neo-cortical control of the brain. Also…

Integrated Photonic Neural Probes for Patterned Brain Stimulation

DTIC Science & Technology

2017-08-14

two -photon imaging Task 3.2: In vivo demonstration of remote optical stimulation using photonic probes and multi -site electrical recording...have patterned nine e-pixels. We can individually address each e-pixel by tuning the color of the input light to the AWG. Figure (8) shows two ...Report: Integrated Photonic Neural Probes for Patterned Brain Stimulation The views , opinions and/or findings contained in this report are those of the

An Intelligent Pattern Recognition System Based on Neural Network and Wavelet Decomposition for Interpretation of Heart Sounds

DTIC Science & Technology

2001-10-25

wavelet decomposition of signals and classification using neural network. Inputs to the system are the heart sound signals acquired by a stethoscope in a...Proceedings. pp. 415–418, 1990. [3] G. Ergun, “An intelligent diagnostic system for interpretation of arterpartum fetal heart rate tracings based on ANNs and...AN INTELLIGENT PATTERN RECOGNITION SYSTEM BASED ON NEURAL NETWORK AND WAVELET DECOMPOSITION FOR INTERPRETATION OF HEART SOUNDS I. TURKOGLU1, A

Influence of Eunice norvegica on feeding and calcification in the coral Lophelia pertusa

NASA Astrophysics Data System (ADS)

Mueller, C. E.; van Oevelen, D.; Middelburg, J. J.; Lundälv, T.

2012-04-01

Lophelia pertusa is the main framework building cold-water coral in the North Atlantic. It forms complex reef structures, extending up to several km in length and several meters in hight. Many species are attracted by the coral frame work, forming a highly diverse community within the reef. Although most work has focused on the corals, the functioning of the system also depends on interactions between corals and associated species. A particular example is the Polychaete Eunice norvegica that lives in close association with the coral host. The Polychaete builds a thin texture-tube between living coral branches and stimulates the coral to calcify the tube. This process strengthens the reef framwork by thickening and connecting coral brances and thereby acts as a positive feedback on the development of large reef structures. This comes however at an metabolic cost for the coral due to the enhanced calcificationrates. Another negative feedback for cold-water coral may be food related, since aquaria observations have shown that Eunice occasionally steels food from its host coral. In this study we investigated the interactions between the coral and polychaete related to calcification and food partitioning for two food types (algae and Artemia). The uptake of 13C and 15N labeled food sources by the worm and the coral was studied in chambers with only corals, only the polychaete and both species present. After 7 days, corals and worms were analyzed for isotope incorporation in bulk tissue and skeleton samples and specific fatty acids (13C) using GC-c-IRMS (gas-chromatography-combustion-isotope ratio mass spectrometry). Corals that were kept in the presence of Eunice indeed showed a higher calcification rates of 7.4 ug C (day* g dw coral)-1, evidencing the stimulation of calcification by Eunice. Interestingly, food uptake of algae and Artemia was higher in the coral-worm treatment for both species as compared to the single species treatments. These results shed new light on trophic and non-trophic interactions in cold-water coral reefs.

Predation of intertidal infauna on juveniles of the bivalve Macoma balthica

NASA Astrophysics Data System (ADS)

Hiddink, J. G.; ter Hofstede, R.; Wolff, W. J.

2002-03-01

Juveniles of the bivalve Macoma balthica live on tidal flats in the Wadden Sea. This study examined the interaction of Macoma with the infaunal polychaetes Arenicola marina and Nereis diversicolor and the gastropod Retusa obtusa. The distribution of M. balthica spat on the flats, shortly after settlement in April, showed a positive correlation with the Arenicola distribution and a negative correlation with Nereis distribution. There were no locations where Macoma spat and Retusa occurred together. In August, Macoma spat had grown too large for predation by intertidal infauna. Small individuals of Macoma spat were found in stomachs of Arenicola (0.14 worm -1) and Nereis (0.05 worm -1). Laboratory experiments showed that Nereis and Retusa could reduce Macoma spat abundance, both in the absence and presence of sediment and alternative prey. Arenicola reduced the abundance of small Macoma (<1 mm) in sediment without, but not with, alternative prey. In field experiments, we manipulated the density of Arenicola in 0.25-1 m 2 plots and of Nereis in 0.03 m 2 cages and examined the effect on Macoma density several weeks later. We found a significant negative relation between densities of polychaetes and Macoma spat for both polychaete species in these experimental plots. Peculiarly, we found a significant positive relation between manipulated Nereis density and adult Macoma density in the cages; we cannot explain this. Consumption rates, calculated both from stomach contents and from field experiments, were 45 to 102 Macoma m -2 d -1 for Arenicola and 5 to 116 Macoma m -2 d -1 for Nereis. These values are higher than recorded consumption rates by epibenthic predators in the same area. Nevertheless, between-year differences in year-class strength could not be explained by differential abundance of these polychaetes. In conclusion, Arenicola and Nereis had a negative effect on the abundance of Macoma <1.5 mm, which was at least partly caused by direct consumption. Retusa obtusa can eat juvenile Macoma, but probably did not so in the study area, because there were no locations where Retusa and Macoma spat occurred together in the period that Macoma was <2 mm.

Predicting neural network firing pattern from phase resetting curve

NASA Astrophysics Data System (ADS)

Oprisan, Sorinel; Oprisan, Ana

2007-04-01

Autonomous neural networks called central pattern generators (CPG) are composed of endogenously bursting neurons and produce rhythmic activities, such as flying, swimming, walking, chewing, etc. Simplified CPGs for quadrupedal locomotion and swimming are modeled by a ring of neural oscillators such that the output of one oscillator constitutes the input for the subsequent neural oscillator. The phase response curve (PRC) theory discards the detailed conductance-based description of the component neurons of a network and reduces them to ``black boxes'' characterized by a transfer function, which tabulates the transient change in the intrinsic period of a neural oscillator subject to external stimuli. Based on open-loop PRC, we were able to successfully predict the phase-locked period and relative phase between neurons in a half-center network. We derived existence and stability criteria for heterogeneous ring neural networks that are in good agreement with experimental data.

Ecological release and niche partitioning under stress: Lessons from dorvilleid polychaetes in sulfidic sediments at methane seeps

NASA Astrophysics Data System (ADS)

Levin, Lisa A.; Ziebis, Wiebke; Mendoza, Guillermo F.; Bertics, Victoria J.; Washington, Tracy; Gonzalez, Jennifer; Thurber, Andrew R.; Ebbe, Brigitte; Lee, Raymond W.

2013-08-01

Organisms inhabiting methane seep sediments are exposed to stress in the form of high levels of hydrogen sulfide, which result mainly from sulfate reduction coupled to anaerobic methane oxidation. Dorvilleidae (Polychaeta) have successfully invaded this ecosystem, and multiple species in divergent genetic clades co-occur at high densities. At methane seeps in the NE Pacific off California and Oregon, the genera Ophryotrocha, Parougia and Exallopus are especially well represented. To test the hypothesis that dorvilleid coexistence is facilitated by niche partitioning through sulfide tolerance and trophic patterns, we examined dorvilleid species-specific patterns of occurrence and nutrition at methane seeps off Eel R. [ER] on the Californian continental slope and at Hydrate Ridge [HR] on the Oregon continental slope, and in two habitats (clam bed and microbial mat) characterized by lower and higher hydrogen sulfide levels, respectively. Microelectrode measurements of hydrogen sulfide enabled characterization of environmental sulfide levels for species sampled in background sediment cores and in colonization trays. Dorvilleids tolerated H2S levels from 10 μM to over 2.6 mM, with the majority of species inhabiting sediments with similar environmental H2S concentrations (median 85-100 μM). Dorvilleid species richness was greater at HR than ER, but did not differ between clam bed and microbial mat habitats. Species distribution patterns reflected preferences for ER clam bed (lower sulfide levels), ER mat and HR clam bed (moderate sulfide levels), or HR mat (very high sulfide levels). Nutritional patterns, including trophic diversity and functional similarity, were examined using community stable isotope metrics based on δ15N and δ13C. Within each region, dorvilleid species exhibited multiple trophic strategies. Co-existing congeners typically exhibited distinct isotope signatures, suggesting trophic partitioning. Trophic diversity and δ15N range for whole assemblages (measured by Total Hull Area and Standard Elliptical Area using species averages) and functional redundancy or species packing (measured as distance to nearest neighbor) among species and individuals were generally higher at ER, where sulfide levels were lower than at HR. In contrast, average trophic diversity among individuals within a species was greater at HR than ER. In colonization experiments involving agar-based manipulations of sulfide in tray sediments that mimicked clam bed and mat conditions, dorvilleids comprised 68% and 48% of colonists at ER and HR, respectively. Dorvilleid species richness was higher in trays that were initially more sulfidic. However, habitat exerted stronger influence on the composition of colonizing dorvilleids than did sulfide additions. In the NE Pacific, regional, habitat and vertical (down-core) variation in hydrogen sulfide creates complex environmental heterogeneity at methane seeps, promoting high diversity of stress-tolerant taxa such as dorvilleid polychaetes.

A deep convolutional neural network to analyze position averaged convergent beam electron diffraction patterns.

PubMed

Xu, W; LeBeau, J M

2018-05-01

We establish a series of deep convolutional neural networks to automatically analyze position averaged convergent beam electron diffraction patterns. The networks first calibrate the zero-order disk size, center position, and rotation without the need for pretreating the data. With the aligned data, additional networks then measure the sample thickness and tilt. The performance of the network is explored as a function of a variety of variables including thickness, tilt, and dose. A methodology to explore the response of the neural network to various pattern features is also presented. Processing patterns at a rate of  ∼ 0.1 s/pattern, the network is shown to be orders of magnitude faster than a brute force method while maintaining accuracy. The approach is thus suitable for automatically processing big, 4D STEM data. We also discuss the generality of the method to other materials/orientations as well as a hybrid approach that combines the features of the neural network with least squares fitting for even more robust analysis. The source code is available at https://github.com/subangstrom/DeepDiffraction. Copyright © 2018 Elsevier B.V. All rights reserved.

Self-organization of neural tissue architectures from pluripotent stem cells.

PubMed

Karus, Michael; Blaess, Sandra; Brüstle, Oliver

2014-08-15

Despite being a subject of intensive research, the mechanisms underlying the formation of neural tissue architectures during development of the central nervous system remain largely enigmatic. So far, studies into neural pattern formation have been restricted mainly to animal experiments. With the advent of pluripotent stem cells it has become possible to explore early steps of nervous system development in vitro. These studies have unraveled a remarkable propensity of primitive neural cells to self-organize into primitive patterns such as neural tube-like rosettes in vitro. Data from more advanced 3D culture systems indicate that this intrinsic propensity for self-organization can even extend to the formation of complex architectures such as a multilayered cortical neuroepithelium or an entire optic cup. These novel experimental paradigms not only demonstrate the enormous self-organization capacity of neural stem cells, they also provide exciting prospects for studying the earliest steps of human neural tissue development and the pathogenesis of brain malformations in reductionist in vitro paradigms. © 2014 Wiley Periodicals, Inc.

Notochord-derived Shh concentrates in close association with the apically positioned basal body in neural target cells and forms a dynamic gradient during neural patterning.

PubMed

Chamberlain, Chester E; Jeong, Juhee; Guo, Chaoshe; Allen, Benjamin L; McMahon, Andrew P

2008-03-01

Sonic hedgehog (Shh) ligand secreted by the notochord induces distinct ventral cell identities in the adjacent neural tube by a concentration-dependent mechanism. To study this process, we genetically engineered mice that produce bioactive, fluorescently labeled Shh from the endogenous locus. We show that Shh ligand concentrates in close association with the apically positioned basal body of neural target cells, forming a dynamic, punctate gradient in the ventral neural tube. Both ligand lipidation and target field response influence the gradient profile, but not the ability of Shh to concentrate around the basal body. Further, subcellular analysis suggests that Shh from the notochord might traffic into the neural target field by means of an apical-to-basal-oriented microtubule scaffold. This study, in which we directly observe, measure, localize and modify notochord-derived Shh ligand in the context of neural patterning, provides several new insights into mechanisms of Shh morphogen action.

Optimization of the kernel functions in a probabilistic neural network analyzing the local pattern distribution.

PubMed

Galleske, I; Castellanos, J

2002-05-01

This article proposes a procedure for the automatic determination of the elements of the covariance matrix of the gaussian kernel function of probabilistic neural networks. Two matrices, a rotation matrix and a matrix of variances, can be calculated by analyzing the local environment of each training pattern. The combination of them will form the covariance matrix of each training pattern. This automation has two advantages: First, it will free the neural network designer from indicating the complete covariance matrix, and second, it will result in a network with better generalization ability than the original model. A variation of the famous two-spiral problem and real-world examples from the UCI Machine Learning Repository will show a classification rate not only better than the original probabilistic neural network but also that this model can outperform other well-known classification techniques.

Sox5 is a DNA binding co-factor for BMP R-Smads that directs target specificity during patterning of the early ectoderm

PubMed Central

Nordin, Kara; LaBonne, Carole

2014-01-01

SUMMARY The SoxD factor, Sox5, is expressed in ectodermal cells at times and places where BMP signaling is active, including the cells of the animal hemisphere at blastula stages, and the neural plate border (NPB) and neural crest (NC) at neurula stages. Sox5 is required for proper ectoderm development, and deficient embryos display patterning defects characteristic of perturbations of BMP signaling, including loss of neural crest and epidermis and expansion of the neural plate. We show that Sox5 is essential for activation of BMP target genes in embryos and explants, that it physically interacts with BMP R-Smads, and that it is essential for recruitment of Smad1/4 to BMP regulatory elements. Our findings identify Sox5 as the long sought DNA binding partner for BMP R-Smads essential to plasticity and pattern in the early ectoderm. PMID:25453832

Developing neuronal networks: Self-organized criticality predicts the future

NASA Astrophysics Data System (ADS)

Pu, Jiangbo; Gong, Hui; Li, Xiangning; Luo, Qingming

2013-01-01

Self-organized criticality emerged in neural activity is one of the key concepts to describe the formation and the function of developing neuronal networks. The relationship between critical dynamics and neural development is both theoretically and experimentally appealing. However, whereas it is well-known that cortical networks exhibit a rich repertoire of activity patterns at different stages during in vitro maturation, dynamical activity patterns through the entire neural development still remains unclear. Here we show that a series of metastable network states emerged in the developing and ``aging'' process of hippocampal networks cultured from dissociated rat neurons. The unidirectional sequence of state transitions could be only observed in networks showing power-law scaling of distributed neuronal avalanches. Our data suggest that self-organized criticality may guide spontaneous activity into a sequential succession of homeostatically-regulated transient patterns during development, which may help to predict the tendency of neural development at early ages in the future.

Amphioxus and lamprey AP-2 genes: implications for neural crest evolution and migration patterns

NASA Technical Reports Server (NTRS)

Meulemans, Daniel; Bronner-Fraser, Marianne

2002-01-01

The neural crest is a uniquely vertebrate cell type present in the most basal vertebrates, but not in cephalochordates. We have studied differences in regulation of the neural crest marker AP-2 across two evolutionary transitions: invertebrate to vertebrate, and agnathan to gnathostome. Isolation and comparison of amphioxus, lamprey and axolotl AP-2 reveals its extensive expansion in the vertebrate dorsal neural tube and pharyngeal arches, implying co-option of AP-2 genes by neural crest cells early in vertebrate evolution. Expression in non-neural ectoderm is a conserved feature in amphioxus and vertebrates, suggesting an ancient role for AP-2 genes in this tissue. There is also common expression in subsets of ventrolateral neurons in the anterior neural tube, consistent with a primitive role in brain development. Comparison of AP-2 expression in axolotl and lamprey suggests an elaboration of cranial neural crest patterning in gnathostomes. However, migration of AP-2-expressing neural crest cells medial to the pharyngeal arch mesoderm appears to be a primitive feature retained in all vertebrates. Because AP-2 has essential roles in cranial neural crest differentiation and proliferation, the co-option of AP-2 by neural crest cells in the vertebrate lineage was a potentially crucial event in vertebrate evolution.

Neurodynamics With Spatial Self-Organization

NASA Technical Reports Server (NTRS)

Zak, Michail A.

1993-01-01

Report presents theoretical study of dynamics of neural network organizing own response in both phase space and in position space. Postulates several mathematical models of dynamics including spatial derivatives representing local interconnections among neurons. Shows how neural responses propagate via these interconnections and how spatial pattern of neural responses formed in homogeneous biological neural network.

Shades of grey; Assessing the contribution of the magno- and parvocellular systems to neural processing of the retinal input in the human visual system from the influence of neural population size and its discharge activity on the VEP.

PubMed

Marcar, Valentine L; Baselgia, Silvana; Lüthi-Eisenegger, Barbara; Jäncke, Lutz

2018-03-01

Retinal input processing in the human visual system involves a phasic and tonic neural response. We investigated the role of the magno- and parvocellular systems by comparing the influence of the active neural population size and its discharge activity on the amplitude and latency of four VEP components. We recorded the scalp electric potential of 20 human volunteers viewing a series of dartboard images presented as a pattern reversing and pattern on-/offset stimulus. These patterns were designed to vary both neural population size coding the temporal- and spatial luminance contrast property and the discharge activity of the population involved in a systematic manner. When the VEP amplitude reflected the size of the neural population coding the temporal luminance contrast property of the image, the influence of luminance contrast followed the contrast response function of the parvocellular system. When the VEP amplitude reflected the size of the neural population responding to the spatial luminance contrast property the image, the influence of luminance contrast followed the contrast response function of the magnocellular system. The latencies of the VEP components examined exhibited the same behavior across our stimulus series. This investigation demonstrates the complex interplay of the magno- and parvocellular systems on the neural response as captured by the VEP. It also demonstrates a linear relationship between stimulus property, neural response, and the VEP and reveals the importance of feedback projections in modulating the ongoing neural response. In doing so, it corroborates the conclusions of our previous study.

Closing the Loop for Memory Prostheses: Detecting the Role of Hippocampal Neural Ensembles Using Nonlinear Models

PubMed Central

Hampson, Robert E.; Song, Dong; Chan, Rosa H.M.; Sweatt, Andrew J.; Riley, Mitchell R.; Goonawardena, Anushka V.; Marmarelis, Vasilis Z.; Gerhardt, Greg A.; Berger, Theodore W.; Deadwyler, Sam A.

2012-01-01

A major factor involved in providing closed loop feedback for control of neural function is to understand how neural ensembles encode online information critical to the final behavioral endpoint. This issue was directly assessed in rats performing a short-term delay memory task in which successful encoding of task information is dependent upon specific spatiotemporal firing patterns recorded from ensembles of CA3 and CA1 hippocampal neurons. Such patterns, extracted by a specially designed nonlinear multi-input multi-output (MIMO) nonlinear mathematical model, were used to predict successful performance online via a closed loop paradigm which regulated trial difficulty (time of retention) as a function of the “strength” of stimulus encoding. The significance of the MIMO model as a neural prosthesis has been demonstrated by substituting trains of electrical stimulation pulses to mimic these same ensemble firing patterns. This feature was used repeatedly to vary “normal” encoding as a means of understanding how neural ensembles can be “tuned” to mimic the inherent process of selecting codes of different strength and functional specificity. The capacity to enhance and tune hippocampal encoding via MIMO model detection and insertion of critical ensemble firing patterns shown here provides the basis for possible extension to other disrupted brain circuitry. PMID:22498704

Propagating waves can explain irregular neural dynamics.

PubMed

Keane, Adam; Gong, Pulin

2015-01-28

Cortical neurons in vivo fire quite irregularly. Previous studies about the origin of such irregular neural dynamics have given rise to two major models: a balanced excitation and inhibition model, and a model of highly synchronized synaptic inputs. To elucidate the network mechanisms underlying synchronized synaptic inputs and account for irregular neural dynamics, we investigate a spatially extended, conductance-based spiking neural network model. We show that propagating wave patterns with complex dynamics emerge from the network model. These waves sweep past neurons, to which they provide highly synchronized synaptic inputs. On the other hand, these patterns only emerge from the network with balanced excitation and inhibition; our model therefore reconciles the two major models of irregular neural dynamics. We further demonstrate that the collective dynamics of propagating wave patterns provides a mechanistic explanation for a range of irregular neural dynamics, including the variability of spike timing, slow firing rate fluctuations, and correlated membrane potential fluctuations. In addition, in our model, the distributions of synaptic conductance and membrane potential are non-Gaussian, consistent with recent experimental data obtained using whole-cell recordings. Our work therefore relates the propagating waves that have been widely observed in the brain to irregular neural dynamics. These results demonstrate that neural firing activity, although appearing highly disordered at the single-neuron level, can form dynamical coherent structures, such as propagating waves at the population level. Copyright © 2015 the authors 0270-6474/15/351591-15$15.00/0.

A cortical neural prosthesis for restoring and enhancing memory

NASA Astrophysics Data System (ADS)

Berger, Theodore W.; Hampson, Robert E.; Song, Dong; Goonawardena, Anushka; Marmarelis, Vasilis Z.; Deadwyler, Sam A.

2011-08-01

A primary objective in developing a neural prosthesis is to replace neural circuitry in the brain that no longer functions appropriately. Such a goal requires artificial reconstruction of neuron-to-neuron connections in a way that can be recognized by the remaining normal circuitry, and that promotes appropriate interaction. In this study, the application of a specially designed neural prosthesis using a multi-input/multi-output (MIMO) nonlinear model is demonstrated by using trains of electrical stimulation pulses to substitute for MIMO model derived ensemble firing patterns. Ensembles of CA3 and CA1 hippocampal neurons, recorded from rats performing a delayed-nonmatch-to-sample (DNMS) memory task, exhibited successful encoding of trial-specific sample lever information in the form of different spatiotemporal firing patterns. MIMO patterns, identified online and in real-time, were employed within a closed-loop behavioral paradigm. Results showed that the model was able to predict successful performance on the same trial. Also, MIMO model-derived patterns, delivered as electrical stimulation to the same electrodes, improved performance under normal testing conditions and, more importantly, were capable of recovering performance when delivered to animals with ensemble hippocampal activity compromised by pharmacologic blockade of synaptic transmission. These integrated experimental-modeling studies show for the first time that, with sufficient information about the neural coding of memories, a neural prosthesis capable of real-time diagnosis and manipulation of the encoding process can restore and even enhance cognitive, mnemonic processes.

Neural representations of the concepts in simple sentences: Concept activation prediction and context effects.

PubMed

Just, Marcel Adam; Wang, Jing; Cherkassky, Vladimir L

2017-08-15

Although it has been possible to identify individual concepts from a concept's brain activation pattern, there have been significant obstacles to identifying a proposition from its fMRI signature. Here we demonstrate the ability to decode individual prototype sentences from readers' brain activation patterns, by using theory-driven regions of interest and semantic properties. It is possible to predict the fMRI brain activation patterns evoked by propositions and words which are entirely new to the model with reliably above-chance rank accuracy. The two core components implemented in the model that reflect the theory were the choice of intermediate semantic features and the brain regions associated with the neurosemantic dimensions. This approach also predicts the neural representation of object nouns across participants, studies, and sentence contexts. Moreover, we find that the neural representation of an agent-verb-object proto-sentence is more accurately characterized by the neural signatures of its components as they occur in a similar context than by the neural signatures of these components as they occur in isolation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Multivariate cross-classification: applying machine learning techniques to characterize abstraction in neural representations

PubMed Central

Kaplan, Jonas T.; Man, Kingson; Greening, Steven G.

2015-01-01

Here we highlight an emerging trend in the use of machine learning classifiers to test for abstraction across patterns of neural activity. When a classifier algorithm is trained on data from one cognitive context, and tested on data from another, conclusions can be drawn about the role of a given brain region in representing information that abstracts across those cognitive contexts. We call this kind of analysis Multivariate Cross-Classification (MVCC), and review several domains where it has recently made an impact. MVCC has been important in establishing correspondences among neural patterns across cognitive domains, including motor-perception matching and cross-sensory matching. It has been used to test for similarity between neural patterns evoked by perception and those generated from memory. Other work has used MVCC to investigate the similarity of representations for semantic categories across different kinds of stimulus presentation, and in the presence of different cognitive demands. We use these examples to demonstrate the power of MVCC as a tool for investigating neural abstraction and discuss some important methodological issues related to its application. PMID:25859202

Mechanisms and Neural Basis of Object and Pattern Recognition: A Study with Chess Experts

ERIC Educational Resources Information Center

Bilalic, Merim; Langner, Robert; Erb, Michael; Grodd, Wolfgang

2010-01-01

Comparing experts with novices offers unique insights into the functioning of cognition, based on the maximization of individual differences. Here we used this expertise approach to disentangle the mechanisms and neural basis behind two processes that contribute to everyday expertise: object and pattern recognition. We compared chess experts and…

Play It Again: Neural Responses to Reunion with Excluders Predicted by Attachment Patterns

ERIC Educational Resources Information Center

White, Lars O.; Wu, Jia; Borelli, Jessica L.; Mayes, Linda C.; Crowley, Michael J.

2013-01-01

Reunion behavior following stressful separations from caregivers is often considered the single most sensitive clue to infant attachment patterns. Extending these ideas to middle childhood/early adolescence, we examined participants' neural responses to reunion with peers who had previously excluded them. We recorded event-related potentials…

The Effects of Simulated Stuttering and Prolonged Speech on the Neural Activation Patterns of Stuttering and Nonstuttering Adults

ERIC Educational Resources Information Center

De Nil, Luc F.; Beal, Deryk S.; Lafaille, Sophie J.; Kroll, Robert M.; Crawley, Adrian P.; Gracco, Vincent L.

2008-01-01

Functional magnetic resonance imaging was used to investigate the neural correlates of passive listening, habitual speech and two modified speech patterns (simulated stuttering and prolonged speech) in stuttering and nonstuttering adults. Within-group comparisons revealed increased right hemisphere biased activation of speech-related regions…

The neural network classification of false killer whale (Pseudorca crassidens) vocalizations.

PubMed

Murray, S O; Mercado, E; Roitblat, H L

1998-12-01

This study reports the use of unsupervised, self-organizing neural network to categorize the repertoire of false killer whale vocalizations. Self-organizing networks are capable of detecting patterns in their input and partitioning those patterns into categories without requiring that the number or types of categories be predefined. The inputs for the neural networks were two-dimensional characterization of false killer whale vocalization, where each vocalization was characterized by a sequence of short-time measurements of duty cycle and peak frequency. The first neural network used competitive learning, where units in a competitive layer distributed themselves to recognize frequently presented input vectors. This network resulted in classes representing typical patterns in the vocalizations. The second network was a Kohonen feature map which organized the outputs topologically, providing a graphical organization of pattern relationships. The networks performed well as measured by (1) the average correlation between the input vectors and the weight vectors for each category, and (2) the ability of the networks to classify novel vocalizations. The techniques used in this study could easily be applied to other species and facilitate the development of objective, comprehensive repertoire models.

Pattern activation/recognition theory of mind

PubMed Central

du Castel, Bertrand

2015-01-01

In his 2012 book How to Create a Mind, Ray Kurzweil defines a “Pattern Recognition Theory of Mind” that states that the brain uses millions of pattern recognizers, plus modules to check, organize, and augment them. In this article, I further the theory to go beyond pattern recognition and include also pattern activation, thus encompassing both sensory and motor functions. In addition, I treat checking, organizing, and augmentation as patterns of patterns instead of separate modules, therefore handling them the same as patterns in general. Henceforth I put forward a unified theory I call “Pattern Activation/Recognition Theory of Mind.” While the original theory was based on hierarchical hidden Markov models, this evolution is based on their precursor: stochastic grammars. I demonstrate that a class of self-describing stochastic grammars allows for unifying pattern activation, recognition, organization, consistency checking, metaphor, and learning, into a single theory that expresses patterns throughout. I have implemented the model as a probabilistic programming language specialized in activation/recognition grammatical and neural operations. I use this prototype to compute and present diagrams for each stochastic grammar and corresponding neural circuit. I then discuss the theory as it relates to artificial network developments, common coding, neural reuse, and unity of mind, concluding by proposing potential paths to validation. PMID:26236228

Pattern activation/recognition theory of mind.

PubMed

du Castel, Bertrand

2015-01-01

In his 2012 book How to Create a Mind, Ray Kurzweil defines a "Pattern Recognition Theory of Mind" that states that the brain uses millions of pattern recognizers, plus modules to check, organize, and augment them. In this article, I further the theory to go beyond pattern recognition and include also pattern activation, thus encompassing both sensory and motor functions. In addition, I treat checking, organizing, and augmentation as patterns of patterns instead of separate modules, therefore handling them the same as patterns in general. Henceforth I put forward a unified theory I call "Pattern Activation/Recognition Theory of Mind." While the original theory was based on hierarchical hidden Markov models, this evolution is based on their precursor: stochastic grammars. I demonstrate that a class of self-describing stochastic grammars allows for unifying pattern activation, recognition, organization, consistency checking, metaphor, and learning, into a single theory that expresses patterns throughout. I have implemented the model as a probabilistic programming language specialized in activation/recognition grammatical and neural operations. I use this prototype to compute and present diagrams for each stochastic grammar and corresponding neural circuit. I then discuss the theory as it relates to artificial network developments, common coding, neural reuse, and unity of mind, concluding by proposing potential paths to validation.

Real-time determination of fringe pattern frequencies: An application to pressure measurement

NASA Astrophysics Data System (ADS)

Sciammarella, Cesar A.; Piroozan, Parham

2007-05-01

Retrieving information in real time from fringe patterns is a topic of a great deal of interest in scientific and engineering applications of optical methods. This paper presents a method for fringe frequency determination based on the capability of neural networks to recognize signals that are similar but not identical to signals used to train the neural network. Sampled patterns are generated by calibration and stored in memory. Incoming patterns are analyzed by a back-propagation neural network at the speed of the recording device, a CCD camera. This method of information retrieval is utilized to measure pressures on a boundary layer flow. The sensor combines optics and electronics to analyze dynamic pressure distributions and to feed information to a control system that is capable to preserve the stability of the flow.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jewett, S.C.; Dean, T.A.

Injuries to the shallow subtidal eelgrass community were observed in the heavily oiled portions of Western Prince William Sound following the Exxon Valdez oil spill. High PAH concentrations were associated with observed differences in communities at oiled vs. reference sites. Dominant taxa within the eelgrass community, including infaunal amphipods, infaunal bivalves, helmet crabs, and leather stars were less abundant at oiled than at reference sites in 1990. Other taxa, including several families of opportunistic or stress-tolerant infaunal polychaetes and gastropods, epifaunal polychaetes and mussels, and small cod, were more abundant at oiled sites. By 1995, there was apparent recovery ofmore » most community constituents. However, not all taxa had recovered fully. Some evidence of slight hydrocarbon contamination still existed at some sites, and three infaunal bivalves, two amphipods, a crab, and a sea star were still more abundant at reference sites than at oiled sites.« less

Polychaete Tubes, Turbulence, and Erosion of Fine-Grained Sediment

NASA Astrophysics Data System (ADS)

Kincke-Tootle, A.; Frank, D. P.; Briggs, K. B.; Calantoni, J.

2016-02-01

The role of polychaete tubes protruding through the benthic boundary layer in promoting or hindering erosion of fine-grained sediment was examined in laboratory experiments. Diver core samples of the top 10cm of sediment were collected west of Trinity Shoal off the Louisiana coast in 10-m depth. Diver cores were used in laboratory experiments conducted in a unidirectional flume. Tubes that were constructed by polychaetes, which comprised 70% of the species from the study area, were inserted into the core sediment surface. The sediment cores were then placed in the 2-m long test section of a small oscillatory flow tunnel and high-speed, stereo particle image velocimetry was used to determine the 2-dimensional, 3-component fluid velocity at high temporal (100 Hz) and spatial (< 1mm vector spacing) resolution. The tubes that protruded above the boundary layer allowed vortices to be initiated. Tubes are made up of shell fragments and fine-grained sediment, allowing for some rigidity and resistance to the flow. Rigidity determines the resistance causing small-scale eddies to form. The small-scale turbulence incited scour erosion, allowing fine-grained particles to be suspended into the water and in some cases coarser particles to be mobilized. Less-rigid tubes succumb to the shear stress, inhibit the formation of small-scale eddies, limit sediment erodibility, and increase the critical shear stress of the sediment. Discussion will focus on a modification to the critical Shields parameter to account for the effects of benthic biological activity.

Environmental impact of bleufin tuna aquaculture on benthic assemblages in the western coast of Baja California, Mexico

NASA Astrophysics Data System (ADS)

Diaz-Castaneda, V.

2013-05-01

Sea-cage farming results in a constant rain of organic waste onto the surrounding benthos. In Baja California there is growing concern over the effects of sea-cages on the local environment: sediment chemistry and benthic communities. Samples were taken in 18 stations using a Van veen grab (0.1 m2) in Bahía Salsipuedes, Baja California in 2003, 2004, 2006 and 2008. Organisms belonging to 7 Phyla were collected: Polychaeta, Mollusca, Crustacea, Echinodermata, Cnidaria, Sipuncula and Bryozoa. Polychaetes were the dominant group followed by crustaceans and mollusks. Polychaetes were represented by 37 families and 157 species. Best represented families were Paraonidae, Cirratulidae, Spionidae, Glyceridae and Maldanidae. This study shows that in the NW area of the bay organic carbon (2.54%) and organic nitrogen (0.95%) are being accumulated (higher concentrations and lower Eh values) and smaller opportunistic species are increasing rapidly near the tuna pens. It is crucial to maintain "healthy" macrofaunal populations in order to enhance decomposition of organic matter and to prevent its excessive accumulation. The most abundant polychaete species were Aphelochaeta multifinis, Mediomastus ambiseta, Prionospio steenstrupi Spiophanes bombyx, Apoprionospio pygnaea, Paraonella sp, Monticellina sp, Aricidea (Allia) ramosa, Spiophanes bombyx and Levinsenia gracilis. The dominant trophic groups were deposit-feeders and carnivores. The buildup of organic matter on the seafloor has attracted scavenger species particularly peracarid crustaceans. Non-metric multidimensional scaling (MDS) separated stations depending of the distance to the tuna pens.

Digestive solubilization of sediment-associated pollutants: In vitro extraction vs. in vivo bioavailability

DOE Office of Scientific and Technical Information (OSTI.GOV)

Weston, D.P.; Mayer, L.M.

1995-12-31

A method using polychaete digestive fluids as a more biologically realistic extractant has recent been proposed as a means to quantify this bioavailable fraction. This work was intended to evaluate this approach with polynuclear aromatic hydrocarbons (PAH), and, in particular, to relate in vitro measures of PAH solubilization by digestive fluids to bioavailability as perceived by the whole animal. In tests with a variety of PAH-contaminated sediments, there were dramatic differences among the sediments in the amounts of PAH extracted by digestive fluids. About 50% of a PAH spike was extracted from a low organic carbon sediment during digestive fluidmore » extraction, while only 20% was extracted from a high organic carbon sediment. The relationships between these differences in PAH solubilization and true bioavailability were evaluated in polychaete bioaccumulation tests measuring PAH uptake rate coefficients and steady state body burdens. The work has also shown that desorption of PAH from ingested sediments in the whole animal approximated the quantities extracted in the in vitro tests. Moreover, desorption of PAH from ingested sediments was found to be greatest in that portion of the polychaete gut with the highest enzymatic activity and from which the digestive fluids had been collected. The digestive fluid extraction approach provides a new tool to examine digestive uptake of contaminants by manipulations that would be impossible in vivo, and may help to quantify a bioavailable contaminant fraction.« less

Neuronal activity during development: permissive or instructive?

PubMed

Crair, M C

1999-02-01

Experimental studies over the past year have shown that neural activity has a range of effects on the development of neural pathways. Although activity appears unimportant for establishing many aspects of the gross morphology and topology of the brain, there are many cases where the presence of neural activity is essential for the formation of a mature system of neural connections; in some instances, the pattern of neural activity actually orchestrates the final arrangement of neural connections.

Dynamic Trial-by-Trial Recoding of Task-Set Representations in the Frontoparietal Cortex Mediates Behavioral Flexibility

PubMed Central

Qiao, Lei; Zhang, Lijie

2017-01-01

Cognitive flexibility forms the core of the extraordinary ability of humans to adapt, but the precise neural mechanisms underlying our ability to nimbly shift between task sets remain poorly understood. Recent functional magnetic resonance imaging (fMRI) studies employing multivoxel pattern analysis (MVPA) have shown that a currently relevant task set can be decoded from activity patterns in the frontoparietal cortex, but whether these regions support the dynamic transformation of task sets from trial to trial is not clear. Here, we combined a cued task-switching protocol with human (both sexes) fMRI, and harnessed representational similarity analysis (RSA) to facilitate a novel assessment of trial-by-trial changes in neural task-set representations. We first used MVPA to define task-sensitive frontoparietal and visual regions and found that neural task-set representations on switch trials are less stably encoded than on repeat trials. We then exploited RSA to show that the neural representational pattern dissimilarity across consecutive trials is greater for switch trials than for repeat trials, and that the degree of this pattern dissimilarity predicts behavior. Moreover, the overall neural pattern of representational dissimilarities followed from the assumption that repeating sets, compared with switching sets, results in stronger neural task representations. Finally, when moving from cue to target phase within a trial, pattern dissimilarities tracked the transformation from previous-trial task representations to the currently relevant set. These results provide neural evidence for the longstanding assumptions of an effortful task-set reconfiguration process hampered by task-set inertia, and they demonstrate that frontoparietal and stimulus processing regions support “dynamic adaptive coding,” flexibly representing changing task sets in a trial-by-trial fashion. SIGNIFICANCE STATEMENT Humans can fluently switch between different tasks, reflecting an ability to dynamically configure “task sets,” rule representations that link stimuli to appropriate responses. Recent studies show that neural signals in frontal and parietal brain regions can tell us which of two tasks a person is currently performing. However, it is not known whether these regions are also involved in dynamically reconfiguring task-set representations when switching between tasks. Here we measured human brain activity during task switching and tracked the similarity of neural task-set representations from trial to trial. We show that frontal and parietal brain regions flexibly recode changing task sets in a trial-by-trial fashion, and that task-set similarity over consecutive trials predicts behavior. PMID:28972126

Briefly Cuing Memories Leads to Suppression of Their Neural Representations

PubMed Central

Norman, Kenneth A.

2014-01-01

Previous studies have linked partial memory activation with impaired subsequent memory retrieval (e.g., Detre et al., 2013) but have not provided an account of this phenomenon at the level of memory representations: How does partial activation change the neural pattern subsequently elicited when the memory is cued? To address this question, we conducted a functional magnetic resonance imaging (fMRI) experiment in which participants studied word-scene paired associates. Later, we weakly reactivated some memories by briefly presenting the cue word during a rapid serial visual presentation (RSVP) task; other memories were more strongly reactivated or not reactivated at all. We tested participants' memory for the paired associates before and after RSVP. Cues that were briefly presented during RSVP triggered reduced levels of scene activity on the post-RSVP memory test, relative to the other conditions. We used pattern similarity analysis to assess how representations changed as a function of the RSVP manipulation. For briefly cued pairs, we found that neural patterns elicited by the same cue on the pre- and post-RSVP tests (preA–postA; preB–postB) were less similar than neural patterns elicited by different cues (preA–postB; preB–postA). These similarity reductions were predicted by neural measures of memory activation during RSVP. Through simulation, we show that our pattern similarity results are consistent with a model in which partial memory activation triggers selective weakening of the strongest parts of the memory. PMID:24899722

Greater neural pattern similarity across repetitions is associated with better memory.

PubMed

Xue, Gui; Dong, Qi; Chen, Chuansheng; Lu, Zhonglin; Mumford, Jeanette A; Poldrack, Russell A

2010-10-01

Repeated study improves memory, but the underlying neural mechanisms of this improvement are not well understood. Using functional magnetic resonance imaging and representational similarity analysis of brain activity, we found that, compared with forgotten items, subsequently remembered faces and words showed greater similarity in neural activation across multiple study in many brain regions, including (but not limited to) the regions whose mean activities were correlated with subsequent memory. This result addresses a longstanding debate in the study of memory by showing that successful episodic memory encoding occurs when the same neural representations are more precisely reactivated across study episodes, rather than when patterns of activation are more variable across time.

Traumatic brain injury causes long-term behavioral changes related to region-specific increases of cerebral blood flow.

PubMed

Pöttker, Bruno; Stöber, Franziska; Hummel, Regina; Angenstein, Frank; Radyushkin, Konstantin; Goldschmidt, Jürgen; Schäfer, Michael K E

2017-12-01

Traumatic brain injury (TBI) is a leading cause of disability and death and survivors often suffer from long-lasting motor impairment, cognitive deficits, anxiety disorders and epilepsy. Few experimental studies have investigated long-term sequelae after TBI and relations between behavioral changes and neural activity patterns remain elusive. We examined these issues in a murine model of TBI combining histology, behavioral analyses and single-photon emission computed tomography (SPECT) imaging of regional cerebral blood flow (CBF) as a proxy for neural activity. Adult C57Bl/6N mice were subjected to unilateral cortical impact injury and investigated at early (15-57 days after lesion, dal) and late (184-225 dal) post-traumatic time points. TBI caused pronounced tissue loss of the parietal cortex and subcortical structures and enduring neurological deficits. Marked perilesional astro- and microgliosis was found at 57 dal and declined at 225 dal. Motor and gait pattern deficits occurred at early time points after TBI and improved over the time. In contrast, impaired performance in the Morris water maze test and decreased anxiety-like behavior persisted together with an increased susceptibility to pentylenetetrazole-induced seizures suggesting alterations in neural activity patterns. Accordingly, SPECT imaging of CBF indicated asymmetric hemispheric baseline neural activity patterns. In the ipsilateral hemisphere, increased baseline neural activity was found in the amygdala. In the contralateral hemisphere, homotopic to the structural brain damage, the hippocampus and distinct cortex regions displayed increased baseline neural activity. Thus, regionally elevated CBF along with behavioral alterations indicate that increased neural activity is critically involved in the long-lasting consequences of TBI.

Surface modification of polydimethylsiloxane (PDMS) induced proliferation and neural-like cells differentiation of umbilical cord blood-derived mesenchymal stem cells.

PubMed

Kim, Sun-Jung; Lee, Jae Kyoo; Kim, Jin Won; Jung, Ji-Won; Seo, Kwangwon; Park, Sang-Bum; Roh, Kyung-Hwan; Lee, Sae-Rom; Hong, Yun Hwa; Kim, Sang Jeong; Lee, Yong-Soon; Kim, Sung June; Kang, Kyung-Sun

2008-08-01

Stem cell-based therapy has recently emerged for use in novel therapeutics for incurable diseases. For successful recovery from neurologic diseases, the most pivotal factor is differentiation and directed neuronal cell growth. In this study, we fabricated three different widths of a micro-pattern on polydimethylsiloxane (PDMS; 1, 2, and 4 microm). Surface modification of the PDMS was investigated for its capacity to manage proliferation and differentiation of neural-like cells from umbilical cord blood-derived mesenchymal stem cells (UCB-MSCs). Among the micro-patterned PDMS fabrications, the 1 microm-patterned PDMS significantly increased cell proliferation and most of the cells differentiated into neuronal cells. In addition, the 1 microm-patterned PDMS induced an increase in cytosolic calcium, while the differentiated cells on the flat and 4 microm-patterned PDMS had no response. PDMS with a 1 microm pattern was also aligned to direct orientation within 10 degrees angles. Taken together, micro-patterned PDMS supported UCB-MSC proliferation and induced neural like-cell differentiation. Our data suggest that micro-patterned PDMS might be a guiding method for stem cell therapy that would improve its therapeutic action in neurological diseases.

INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY: Influence of Blurred Ways on Pattern Recognition of a Scale-Free Hopfield Neural Network

NASA Astrophysics Data System (ADS)

Chang, Wen-Li

2010-01-01

We investigate the influence of blurred ways on pattern recognition of a Barabási-Albert scale-free Hopfield neural network (SFHN) with a small amount of errors. Pattern recognition is an important function of information processing in brain. Due to heterogeneous degree of scale-free network, different blurred ways have different influences on pattern recognition with same errors. Simulation shows that among partial recognition, the larger loading ratio (the number of patterns to average degree P/langlekrangle) is, the smaller the overlap of SFHN is. The influence of directed (large) way is largest and the directed (small) way is smallest while random way is intermediate between them. Under the ratio of the numbers of stored patterns to the size of the network P/N is less than 0. 1 conditions, there are three families curves of the overlap corresponding to directed (small), random and directed (large) blurred ways of patterns and these curves are not associated with the size of network and the number of patterns. This phenomenon only occurs in the SFHN. These conclusions are benefit for understanding the relation between neural network structure and brain function.

Prediction of Slot Shape and Slot Size for Improving the Performance of Microstrip Antennas Using Knowledge-Based Neural Networks.

PubMed

Khan, Taimoor; De, Asok

2014-01-01

In the last decade, artificial neural networks have become very popular techniques for computing different performance parameters of microstrip antennas. The proposed work illustrates a knowledge-based neural networks model for predicting the appropriate shape and accurate size of the slot introduced on the radiating patch for achieving desired level of resonance, gain, directivity, antenna efficiency, and radiation efficiency for dual-frequency operation. By incorporating prior knowledge in neural model, the number of required training patterns is drastically reduced. Further, the neural model incorporated with prior knowledge can be used for predicting response in extrapolation region beyond the training patterns region. For validation, a prototype is also fabricated and its performance parameters are measured. A very good agreement is attained between measured, simulated, and predicted results.

Prediction of Slot Shape and Slot Size for Improving the Performance of Microstrip Antennas Using Knowledge-Based Neural Networks

PubMed Central

De, Asok

2014-01-01

In the last decade, artificial neural networks have become very popular techniques for computing different performance parameters of microstrip antennas. The proposed work illustrates a knowledge-based neural networks model for predicting the appropriate shape and accurate size of the slot introduced on the radiating patch for achieving desired level of resonance, gain, directivity, antenna efficiency, and radiation efficiency for dual-frequency operation. By incorporating prior knowledge in neural model, the number of required training patterns is drastically reduced. Further, the neural model incorporated with prior knowledge can be used for predicting response in extrapolation region beyond the training patterns region. For validation, a prototype is also fabricated and its performance parameters are measured. A very good agreement is attained between measured, simulated, and predicted results. PMID:27382616

Articulated Wiwaxia from the Cambrian Stage 3 Xiaoshiba lagerstätte.

PubMed

Yang, Jie; Smith, Martin R; Lan, Tian; Hou, Jin-bo; Zhang, Xi-guang

2014-04-10

Wiwaxia is a bizarre metazoan that has been interpreted as a primitive mollusc and as a polychaete annelid worm. Extensive material from the Burgess Shale provides a detailed picture of its morphology and ontogeny, but the fossil record outside this lagerstätte is scarce, and complete wiwaxiids are particularly rare. Here we report small articulated specimens of Wiwaxia foliosa sp. nov. from the Xiaoshiba fauna (Cambrian Stage 3, Hongjingshao Formation, Kunming, south China). Although spines are absent, the fossils' sclerites - like those of W. corrugata - are symmetrically arranged in five distinct zones. They form rows across the body, and were individually added and shed throughout growth to retain an approximately symmetrical body shape. Their development pattern suggests a molluscan affinity. The basic body plan of wiwaxiids is fundamentally conserved across two continents through Cambrian Stages 3-5 - revealing morphological stasis in the wake of the Cambrian explosion.

Risk-taking on the road and in the mind: behavioural and neural patterns of decision making between risky and safe drivers.

PubMed

Ba, Yutao; Zhang, Wei; Peng, QiJia; Salvendy, Gavriel; Crundall, David

2016-01-01

Drivers' risk-taking is a key issue of road safety. This study explored individual differences in drivers' decision-making, linking external behaviours to internal neural activity, to reveal the cognitive mechanisms of risky driving. Twenty-four male drivers were split into two groups (risky vs. safe drivers) via the Drivier Behaviour Questionnaire-violation. The risky drivers demonstrated higher preference for the risky choices in the paradigms of Iowa Gambling Task and Balloon Analogue Risk Task. More importantly, the risky drivers showed lower amplitudes of feedback-related negativity (FRN) and loss-minus-gain FRN in both paradigms, which indicated their neural processing of error-detection. A significant difference of P300 amplitudes was also reported between groups, which indicated their neural processing of reward-evaluation and were modified by specific paradigm and feedback. These results suggested that the neural basis of risky driving was the decision patterns less revised by losses and more motivated by rewards. Risk-taking on the road is largely determined by inherent cognitive mechanisms, which can be indicated by the behavioural and neural patterns of decision-making. In this regard, it is feasible to quantize drivers’ riskiness in the cognitive stage before actual risky driving or accidents, and intervene accordingly.

An orthologue of the kit-related gene fms is required for development of neural crest-derived xanthophores and a subpopulation of adult melanocytes in the zebrafish, Danio rerio.

PubMed

Parichy, D M; Ransom, D G; Paw, B; Zon, L I; Johnson, S L

2000-07-01

Developmental mechanisms underlying traits expressed in larval and adult vertebrates remain largely unknown. Pigment patterns of fishes provide an opportunity to identify genes and cell behaviors required for postembryonic morphogenesis and differentiation. In the zebrafish, Danio rerio, pigment patterns reflect the spatial arrangements of three classes of neural crest-derived pigment cells: black melanocytes, yellow xanthophores and silver iridophores. We show that the D. rerio pigment pattern mutant panther ablates xanthophores in embryos and adults and has defects in the development of the adult pattern of melanocyte stripes. We find that panther corresponds to an orthologue of the c-fms gene, which encodes a type III receptor tyrosine kinase and is the closest known homologue of the previously identified pigment pattern gene, kit. In mouse, fms is essential for the development of macrophage and osteoclast lineages and has not been implicated in neural crest or pigment cell development. In contrast, our analyses demonstrate that fms is expressed and required by D. rerio xanthophore precursors and that fms promotes the normal patterning of melanocyte death and migration during adult stripe formation. Finally, we show that fms is required for the appearance of a late developing, kit-independent subpopulation of adult melanocytes. These findings reveal an unexpected role for fms in pigment pattern development and demonstrate that parallel neural crest-derived pigment cell populations depend on the activities of two essentially paralogous genes, kit and fms.

Behavioral and Physiological Neural Network Analyses: A Common Pathway toward Pattern Recognition and Prediction

ERIC Educational Resources Information Center

Ninness, Chris; Lauter, Judy L.; Coffee, Michael; Clary, Logan; Kelly, Elizabeth; Rumph, Marilyn; Rumph, Robin; Kyle, Betty; Ninness, Sharon K.

2012-01-01

Using 3 diversified datasets, we explored the pattern-recognition ability of the Self-Organizing Map (SOM) artificial neural network as applied to diversified nonlinear data distributions in the areas of behavioral and physiological research. Experiment 1 employed a dataset obtained from the UCI Machine Learning Repository. Data for this study…

Nonlinear Time Series Analysis via Neural Networks

NASA Astrophysics Data System (ADS)

Volná, Eva; Janošek, Michal; Kocian, Václav; Kotyrba, Martin

This article deals with a time series analysis based on neural networks in order to make an effective forex market [Moore and Roche, J. Int. Econ. 58, 387-411 (2002)] pattern recognition. Our goal is to find and recognize important patterns which repeatedly appear in the market history to adapt our trading system behaviour based on them.

Effect of inhibitory firing pattern on coherence resonance in random neural networks

NASA Astrophysics Data System (ADS)

Yu, Haitao; Zhang, Lianghao; Guo, Xinmeng; Wang, Jiang; Cao, Yibin; Liu, Jing

2018-01-01

The effect of inhibitory firing patterns on coherence resonance (CR) in random neuronal network is systematically studied. Spiking and bursting are two main types of firing pattern considered in this work. Numerical results show that, irrespective of the inhibitory firing patterns, the regularity of network is maximized by an optimal intensity of external noise, indicating the occurrence of coherence resonance. Moreover, the firing pattern of inhibitory neuron indeed has a significant influence on coherence resonance, but the efficacy is determined by network property. In the network with strong coupling strength but weak inhibition, bursting neurons largely increase the amplitude of resonance, while they can decrease the noise intensity that induced coherence resonance within the neural system of strong inhibition. Different temporal windows of inhibition induced by different inhibitory neurons may account for the above observations. The network structure also plays a constructive role in the coherence resonance. There exists an optimal network topology to maximize the regularity of the neural systems.

Optical Neural Classification Of Binary Patterns

NASA Astrophysics Data System (ADS)

Gustafson, Steven C.; Little, Gordon R.

1988-05-01

Binary pattern classification that may be implemented using optical hardware and neural network algorithms is considered. Pattern classification problems that have no concise description (as in classifying handwritten characters) or no concise computation (as in NP-complete problems) are expected to be particularly amenable to this approach. For example, optical processors that efficiently classify binary patterns in accordance with their Boolean function complexity might be designed. As a candidate for such a design, an optical neural network model is discussed that is designed for binary pattern classification and that consists of an optical resonator with a dynamic multiplex-recorded reflection hologram and a phase conjugate mirror with thresholding and gain. In this model, learning or training examples of binary patterns may be recorded on the hologram such that one bit in each pattern marks the pattern class. Any input pattern, including one with an unknown class or marker bit, will be modified by a large number of parallel interactions with the reflection hologram and nonlinear mirror. After perhaps several seconds and 100 billion interactions, a steady-state pattern may develop with a marker bit that represents a minimum-Boolean-complexity classification of the input pattern. Computer simulations are presented that illustrate progress in understanding the behavior of this model and in developing a processor design that could have commanding and enduring performance advantages compared to current pattern classification techniques.

Orthogonal patterns in binary neural networks

NASA Technical Reports Server (NTRS)

Baram, Yoram

1988-01-01

A binary neural network that stores only mutually orthogonal patterns is shown to converge, when probed by any pattern, to a pattern in the memory space, i.e., the space spanned by the stored patterns. The latter are shown to be the only members of the memory space under a certain coding condition, which allows maximum storage of M=(2N) sup 0.5 patterns, where N is the number of neurons. The stored patterns are shown to have basins of attraction of radius N/(2M), within which errors are corrected with probability 1 in a single update cycle. When the probe falls outside these regions, the error correction capability can still be increased to 1 by repeatedly running the network with the same probe.

Regulation of Facial Morphogenesis by Endothelin Signaling: Insights from Mice and Fish

PubMed Central

Clouthier, David E.; Garcia, Elvin; Schilling, Thomas F.

2010-01-01

Craniofacial morphogenesis is accomplished through a complex set of developmental events, most of which are initiated in neural crest cells within the pharyngeal arches. Local patterning cues from the surrounding environment induce gene expression within neural crest cells, leading to formation of a diverse set of skeletal elements. Endothelin-1 (Edn1) is one of the primary signals that establish the identities of neural crest cells within the mandibular portion of the first pharyngeal arch. Signaling through its cognate receptor, the endothelin-A receptor, is critical for patterning the ventral/distal portion of the arch (lower jaw) and also participates with Hox genes in patterning more posterior arches. Edn1/Ednra signaling is highly conserved between mouse and zebrafish, and genetic analyses in these two species have provided complementary insights into the patterning cues responsible for establishing the craniofacial complex as well as the genetic basis of facial birth defect syndromes. PMID:20684004

Fgfr1 regulates patterning of the pharyngeal region

PubMed Central

Trokovic, Nina; Trokovic, Ras; Mai, Petra; Partanen, Juha

2003-01-01

Development of the pharyngeal region depends on the interaction and integration of different cell populations, including surface ectoderm, foregut endoderm, paraxial mesoderm, and neural crest. Mice homozygous for a hypomorphic allele of Fgfr1 have craniofacial defects, some of which appeared to result from a failure in the early development of the second branchial arch. A stream of neural crest cells was found to originate from the rhombomere 4 region and migrate toward the second branchial arch in the mutants. Neural crest cells mostly failed to enter the second arch, however, but accumulated in a region proximal to it. Both rescue of the hypomorphic Fgfr1 allele and inactivation of a conditional Fgfr1 allele specifically in neural crest cells indicated that Fgfr1 regulates the entry of neural crest cells into the second branchial arch non-cell-autonomously. Gene expression in the pharyngeal ectoderm overlying the developing second branchial arch was affected in the hypomorphic Fgfr1 mutants at a stage prior to neural crest entry. Our results indicate that Fgfr1 patterns the pharyngeal region to create a permissive environment for neural crest cell migration. PMID:12514106

The neural processing of taste

PubMed Central

Lemon, Christian H; Katz, Donald B

2007-01-01

Although there have been many recent advances in the field of gustatory neurobiology, our knowledge of how the nervous system is organized to process information about taste is still far from complete. Many studies on this topic have focused on understanding how gustatory neural circuits are spatially organized to represent information about taste quality (e.g., "sweet", "salty", "bitter", etc.). Arguments pertaining to this issue have largely centered on whether taste is carried by dedicated neural channels or a pattern of activity across a neural population. But there is now mounting evidence that the timing of neural events may also importantly contribute to the representation of taste. In this review, we attempt to summarize recent findings in the field that pertain to these issues. Both space and time are variables likely related to the mechanism of the gustatory neural code: information about taste appears to reside in spatial and temporal patterns of activation in gustatory neurons. What is more, the organization of the taste network in the brain would suggest that the parameters of space and time extend to the neural processing of gustatory information on a much grander scale. PMID:17903281

Neural Network Computing and Natural Language Processing.

ERIC Educational Resources Information Center

Borchardt, Frank

1988-01-01

Considers the application of neural network concepts to traditional natural language processing and demonstrates that neural network computing architecture can: (1) learn from actual spoken language; (2) observe rules of pronunciation; and (3) reproduce sounds from the patterns derived by its own processes. (Author/CB)

A neural network with modular hierarchical learning

NASA Technical Reports Server (NTRS)

Baldi, Pierre F. (Inventor); Toomarian, Nikzad (Inventor)

1994-01-01

This invention provides a new hierarchical approach for supervised neural learning of time dependent trajectories. The modular hierarchical methodology leads to architectures which are more structured than fully interconnected networks. The networks utilize a general feedforward flow of information and sparse recurrent connections to achieve dynamic effects. The advantages include the sparsity of units and connections, the modular organization. A further advantage is that the learning is much more circumscribed learning than in fully interconnected systems. The present invention is embodied by a neural network including a plurality of neural modules each having a pre-established performance capability wherein each neural module has an output outputting present results of the performance capability and an input for changing the present results of the performance capabilitiy. For pattern recognition applications, the performance capability may be an oscillation capability producing a repeating wave pattern as the present results. In the preferred embodiment, each of the plurality of neural modules includes a pre-established capability portion and a performance adjustment portion connected to control the pre-established capability portion.

Neural coordination can be enhanced by occasional interruption of normal firing patterns: a self-optimizing spiking neural network model.

PubMed

Woodward, Alexander; Froese, Tom; Ikegami, Takashi

2015-02-01

The state space of a conventional Hopfield network typically exhibits many different attractors of which only a small subset satisfies constraints between neurons in a globally optimal fashion. It has recently been demonstrated that combining Hebbian learning with occasional alterations of normal neural states avoids this problem by means of self-organized enlargement of the best basins of attraction. However, so far it is not clear to what extent this process of self-optimization is also operative in real brains. Here we demonstrate that it can be transferred to more biologically plausible neural networks by implementing a self-optimizing spiking neural network model. In addition, by using this spiking neural network to emulate a Hopfield network with Hebbian learning, we attempt to make a connection between rate-based and temporal coding based neural systems. Although further work is required to make this model more realistic, it already suggests that the efficacy of the self-optimizing process is independent from the simplifying assumptions of a conventional Hopfield network. We also discuss natural and cultural processes that could be responsible for occasional alteration of neural firing patterns in actual brains. Copyright © 2014 Elsevier Ltd. All rights reserved.

Whole person-evoked fMRI activity patterns in human fusiform gyrus are accurately modeled by a linear combination of face- and body-evoked activity patterns

PubMed Central

Kaiser, Daniel; Strnad, Lukas; Seidl, Katharina N.; Kastner, Sabine

2013-01-01

Visual cues from the face and the body provide information about another's identity, emotional state, and intentions. Previous neuroimaging studies that investigated neural responses to (bodiless) faces and (headless) bodies have reported overlapping face- and body-selective brain regions in right fusiform gyrus (FG). In daily life, however, faces and bodies are typically perceived together and are effortlessly integrated into the percept of a whole person, raising the possibility that neural responses to whole persons are qualitatively different than responses to isolated faces and bodies. The present study used fMRI to examine how FG activity in response to a whole person relates to activity in response to the same face and body but presented in isolation. Using multivoxel pattern analysis, we modeled person-evoked response patterns in right FG through a linear combination of face- and body-evoked response patterns. We found that these synthetic patterns were able to accurately approximate the response patterns to whole persons, with face and body patterns each adding unique information to the response patterns evoked by whole person stimuli. These results suggest that whole person responses in FG primarily arise from the coactivation of independent face- and body-selective neural populations. PMID:24108794

Changing the Spatial Scope of Attention Alters Patterns of Neural Gain in Human Cortex

PubMed Central

Garcia, Javier O.; Rungratsameetaweemana, Nuttida; Sprague, Thomas C.

2014-01-01

Over the last several decades, spatial attention has been shown to influence the activity of neurons in visual cortex in various ways. These conflicting observations have inspired competing models to account for the influence of attention on perception and behavior. Here, we used electroencephalography (EEG) to assess steady-state visual evoked potentials (SSVEP) in human subjects and showed that highly focused spatial attention primarily enhanced neural responses to high-contrast stimuli (response gain), whereas distributed attention primarily enhanced responses to medium-contrast stimuli (contrast gain). Together, these data suggest that different patterns of neural modulation do not reflect fundamentally different neural mechanisms, but instead reflect changes in the spatial extent of attention. PMID:24381272

Hetero-association for pattern translation

NASA Astrophysics Data System (ADS)

Yu, Francis T. S.; Lu, Thomas T.; Yang, Xiangyang

1991-09-01

A hetero-association neural network using an interpattern association algorithm is presented. By using simple logical rules, hetero-association memory can be constructed based on the association between the input-output reference patterns. For optical implementation, a compact size liquid crystal television neural network is used. Translations between the English letters and the Chinese characters as well as Arabic and Chinese numerics are demonstrated. The authors have shown that the hetero-association model can perform more effectively in comparison to the Hopfield model in retrieving large numbers of similar patterns.

A neural network prototyping package within IRAF

NASA Technical Reports Server (NTRS)

Bazell, D.; Bankman, I.

1992-01-01

We outline our plans for incorporating a Neural Network Prototyping Package into the IRAF environment. The package we are developing will allow the user to choose between different types of networks and to specify the details of the particular architecture chosen. Neural networks consist of a highly interconnected set of simple processing units. The strengths of the connections between units are determined by weights which are adaptively set as the network 'learns'. In some cases, learning can be a separate phase of the user cycle of the network while in other cases the network learns continuously. Neural networks have been found to be very useful in pattern recognition and image processing applications. They can form very general 'decision boundaries' to differentiate between objects in pattern space and they can be used for associative recall of patterns based on partial cures and for adaptive filtering. We discuss the different architectures we plan to use and give examples of what they can do.

Large memory capacity in chaotic artificial neural networks: a view of the anti-integrable limit.

PubMed

Lin, Wei; Chen, Guanrong

2009-08-01

In the literature, it was reported that the chaotic artificial neural network model with sinusoidal activation functions possesses a large memory capacity as well as a remarkable ability of retrieving the stored patterns, better than the conventional chaotic model with only monotonic activation functions such as sigmoidal functions. This paper, from the viewpoint of the anti-integrable limit, elucidates the mechanism inducing the superiority of the model with periodic activation functions that includes sinusoidal functions. Particularly, by virtue of the anti-integrable limit technique, this paper shows that any finite-dimensional neural network model with periodic activation functions and properly selected parameters has much more abundant chaotic dynamics that truly determine the model's memory capacity and pattern-retrieval ability. To some extent, this paper mathematically and numerically demonstrates that an appropriate choice of the activation functions and control scheme can lead to a large memory capacity and better pattern-retrieval ability of the artificial neural network models.

Control of Wind Tunnel Operations Using Neural Net Interpretation of Flow Visualization Records

NASA Technical Reports Server (NTRS)

Buggele, Alvin E.; Decker, Arthur J.

1994-01-01

Neural net control of operations in a small subsonic/transonic/supersonic wind tunnel at Lewis Research Center is discussed. The tunnel and the layout for neural net control or control by other parallel processing techniques are described. The tunnel is an affordable, multiuser platform for testing instrumentation and components, as well as parallel processing and control strategies. Neural nets have already been tested on archival schlieren and holographic visualizations from this tunnel as well as recent supersonic and transonic shadowgraph. This paper discusses the performance of neural nets for interpreting shadowgraph images in connection with a recent exercise for tuning the tunnel in a subsonic/transonic cascade mode of operation. That mode was operated for performing wake surveys in connection with NASA's Advanced Subsonic Technology (AST) noise reduction program. The shadowgraph was presented to the neural nets as 60 by 60 pixel arrays. The outputs were tunnel parameters such as valve settings or tunnel state identifiers for selected tunnel operating points, conditions, or states. The neural nets were very sensitive, perhaps too sensitive, to shadowgraph pattern detail. However, the nets exhibited good immunity to variations in brightness, to noise, and to changes in contrast. The nets are fast enough so that ten or more can be combined per control operation to interpret flow visualization data, point sensor data, and model calculations. The pattern sensitivity of the nets will be utilized and tested to control wind tunnel operations at Mach 2.0 based on shock wave patterns.

Neural mechanism of optimal limb coordination in crustacean swimming

PubMed Central

Zhang, Calvin; Guy, Robert D.; Mulloney, Brian; Zhang, Qinghai; Lewis, Timothy J.

2014-01-01

A fundamental challenge in neuroscience is to understand how biologically salient motor behaviors emerge from properties of the underlying neural circuits. Crayfish, krill, prawns, lobsters, and other long-tailed crustaceans swim by rhythmically moving limbs called swimmerets. Over the entire biological range of animal size and paddling frequency, movements of adjacent swimmerets maintain an approximate quarter-period phase difference with the more posterior limbs leading the cycle. We use a computational fluid dynamics model to show that this frequency-invariant stroke pattern is the most effective and mechanically efficient paddling rhythm across the full range of biologically relevant Reynolds numbers in crustacean swimming. We then show that the organization of the neural circuit underlying swimmeret coordination provides a robust mechanism for generating this stroke pattern. Specifically, the wave-like limb coordination emerges robustly from a combination of the half-center structure of the local central pattern generating circuits (CPGs) that drive the movements of each limb, the asymmetric network topology of the connections between local CPGs, and the phase response properties of the local CPGs, which we measure experimentally. Thus, the crustacean swimmeret system serves as a concrete example in which the architecture of a neural circuit leads to optimal behavior in a robust manner. Furthermore, we consider all possible connection topologies between local CPGs and show that the natural connectivity pattern generates the biomechanically optimal stroke pattern most robustly. Given the high metabolic cost of crustacean swimming, our results suggest that natural selection has pushed the swimmeret neural circuit toward a connection topology that produces optimal behavior. PMID:25201976

Classification of Company Performance using Weighted Probabilistic Neural Network

NASA Astrophysics Data System (ADS)

Yasin, Hasbi; Waridi Basyiruddin Arifin, Adi; Warsito, Budi

2018-05-01

Classification of company performance can be judged by looking at its financial status, whether good or bad state. Classification of company performance can be achieved by some approach, either parametric or non-parametric. Neural Network is one of non-parametric methods. One of Artificial Neural Network (ANN) models is Probabilistic Neural Network (PNN). PNN consists of four layers, i.e. input layer, pattern layer, addition layer, and output layer. The distance function used is the euclidean distance and each class share the same values as their weights. In this study used PNN that has been modified on the weighting process between the pattern layer and the addition layer by involving the calculation of the mahalanobis distance. This model is called the Weighted Probabilistic Neural Network (WPNN). The results show that the company's performance modeling with the WPNN model has a very high accuracy that reaches 100%.

A neural network for recognizing movement patterns during repetitive self-paced movements of the fingers in opposition to the thumb.

PubMed

Van Vaerenbergh, J; Vranken, R; Briers, L; Briers, H

2001-11-01

A data glove is a typical input device to control a virtual environment. At the same time it measures movements of wrist and fingers. The purposes of this investigation were to assess the ability of BrainMaker, a neural network, to recognize movement patterns during an opposition task that consisted of repetitive self-paced movements of the fingers in opposition to the thumb. The neural network contained 56 inputs, 3 hidden layers of 20 neurons, and one output. The 5th glove '95 (5DT), a commercial glove especially designed for virtual reality games, was used for finger motion capture. The training of the neural network was successful for recognizing the thumb, the index finger and the ring finger movements during the repetitive self-paced movements and neural network performed well during testing.

Characterization of an anthraquinone fluor from the bioluminescent, pelagic polychaete Tomopteris

PubMed Central

Francis, Warren R; Powers, Meghan L; Haddock, Steven H D

2014-01-01

Tomopteris is a cosmopolitan genus of polychaetes. Many species produce yellow luminescence in the parapodia when stimulated. Yellow bioluminescence is rare in the ocean, and the components of this luminescent reaction have not been identified. Only a brief description, half a century ago, noted fluorescence in the parapodia with a remarkably similar spectrum to the bioluminescence, which suggested that it may be the luciferin or terminal light-emitter. Here, we report the isolation of the fluorescent yellow–orange pigment found in the luminous exudate and in the body of the animals. Liquid chromatography-mass spectrometry revealed the mass to be 270 m/z with a molecular formula of C15H10O5, which ultimately was shown to be aloe-emodin, an anthraquinone previously found in plants. We speculate that aloe-emodin could be a factor for resonant-energy transfer or the oxyluciferin for Tomopteris bioluminescence. PMID:24760626

A new species of Paraonis and an annotated checklist of polychaetes from mangroves of the Brazilian Amazon Coast (Annelida, Paraonidae)

PubMed Central

Ribeiro, Rannyele Passos; Alves, Paulo Ricardo; de Almeida, Zafira da Silva; Ruta, Christine

2018-01-01

Abstract The polychaete fauna from the mangroves of the Amazon Coast in Maranhão state, Brazil, is reported in this study. Fourteen species are listed, namely Alitta succinea (Leuckart, 1847); Arabella (Arabella) iricolor Montagu, 1804; Capitella capitata (Fabricius, 1780) complex; Exogone (Exogone) breviantennata Hartmann-Schröder, 1959; Heteromastus filiformis (Claparède, 1864); Isolda pulchella Müller, 1858; Mediomastus californiensis Hartman, 1944; Namalycastis fauveli Nageswara Rao, 1981; Namalycastis geayi (Gravier, 1901); Namalycastis senegalensis (Saint-Joseph, 1901); Nephtys simoni Perkins, 1980; Paraonis amazonica sp. n.; Sigambra bassi (Hartman, 1945); and Sigambra grubii Müller, 1858. Among them, Namalycastis fauveli and Namalycastis geayi are recorded for the first time in Brazil. Paraonis amazonica sp. n. is a new species for science, characterized by a rounded prostomium, 4–8 pairs of foliaceous branchiae, absent eyes, and two types of modified neurochaetae, acicular and hook-shaped. PMID:29674886

Isolation of bacterial metabolites as natural inducers for larval settlement in the marine polychaete Hydroides elegans (Haswell).

PubMed

Harder, Tilmann; Lau, Stanley Chun Kwan; Dahms, Hans-Uwe; Qian, Pei-Yuan

2002-10-01

The bacterial component of marine biofilms plays an important role in the induction of larval settlement in the polychaete Hydroides elegans. In this study, we provide experimental evidence that bacterial metabolites comprise the chemical signal for larval settlement. Bacteria were isolated from biofilms, purified and cultured according to standard procedures. Bacterial metabolites were isolated from spent culture broth by chloroform extraction as well as by closed-loop stripping and adsorption of volatile components on surface-modified silica gel. A pronounced biological activity was exclusively observed when concentrated metabolites were adsorbed on activated charcoal. Larvae did not respond to waterbome metabolites when prevented from contacting the bacterial film surface. These results indicate that an association of the chemical signal with a sorbent-like substratum may be an essential cofactor for the expression of biological activity. The functional role of bacterial exopolymers as an adsorptive matrix for larval settlement signals is discussed.

Unusual benthic fauna associated with a whale fall in Monterey Canyon, California

NASA Astrophysics Data System (ADS)

Goffredi, Shana K.; Paull, Charles K.; Fulton-Bennett, Kim; Hurtado, Luis A.; Vrijenhoek, Robert C.

2004-10-01

On February 6, 2002, we discovered an unusual assemblage of deep-sea animals associated with a well-preserved carcass of a gray whale (Eschrichtius robustus) at 2891 m depth in the axis of Monterey Canyon, California. The 9-10 m long carcass was found approximately 31 km off shore, where it settled to the bottom against the northern wall of the canyon's sedimented floor. This carcass delivered approximately 20,000 kg of organic material to a typically food-limited seafloor. Particularly noteworthy were the low occurrence of large mobile scavengers, the large number of opportunistic deep-sea species, and an abundance of unusual polychaetes. Two of these polychaetes, a spionid and a siboglinid, are new to science. Since this discovery, we visited the whale fall on two subsequent occasions (March and October 2002) to document faunal community changes in one of the deepest large food falls known to date.

[Benthic fauna associated to a Thalassia testudinum (Hydrocharitaceae) bed in Parque Nacional Morrocoy, Venezuela].

PubMed

Rodríguez, C; Villamizar, E

2000-12-01

The benthic fauna and diel variation in a shallow seagrass bed (Thalassia testudinum) were studied in Playa Mero, Venezuela. Samples of organisms and sediments were taken using PVC cylinders, 5cm in diameter, along a transect perpendicular to the coast. Seagrass cover, shoot density and biomass were estimated. The seagrass cover was homogeneous along the transect. The intermediate zone had the highest number of shoots and of above-ground and rhizome biomass. Composition and abundance of benthic organisms were related with seagrass and sediment characteristics. Sediment organic matter content and organism abundance were highest near the shore Molluscs, polychaetes, oligochaetes and nematodes were the most abundant groups. Species richness was higher in daytime (40 versus 28 at night). Gastropods were the most abundant organisms both at day and night while polychaetes and crustaceans increased during the day, and holoturids were more numerous at night.

Digestive determinants of benzo[a]pyrene and phenanthrene bioaccumulation by a deposit-feeding polychaete

DOE Office of Scientific and Technical Information (OSTI.GOV)

Penry, D.L.; Weston, D.P.

1998-11-01

The uptake of hydrophobic contaminants from ingested sediment can contribute significantly to body burdens of deposit feeders, and feeding behavior and digestive physiology can play important roles in bioaccumulation. The authors examined the uptake of polycyclic aromatic hydrocarbons (PAHs) by the deposit-feeding polychaete Abarenicola pacifica in experiments in which worms were first acclimated to low or high organic carbon sediments with 0.08 or 0.45% total organic carbon, respectively and then transferred to low or high organic carbon test sediments contaminated with radiolabeled phenanthrene or benzo[a]pyrene. Ingestion rate was measurements are essential in many types of bioaccumulation studies because differences inmore » ingestion rates between sediment types may confound some traditional measures of bioavailability. Physiological acclimation to the low or high organic carbon sediments did not appear to affect PAH uptake from the test sediments, but acclimation did affect biotransformation capabilities, particularly for phenanthrene.« less

Cross-Domain Effects of Music and Language Experience on the Representation of Pitch in the Human Auditory Brainstem

ERIC Educational Resources Information Center

Bidelman, Gavin M.; Gandour, Jackson T.; Krishnan, Ananthanarayan

2011-01-01

Neural encoding of pitch in the auditory brainstem is known to be shaped by long-term experience with language or music, implying that early sensory processing is subject to experience-dependent neural plasticity. In language, pitch patterns consist of sequences of continuous, curvilinear contours; in music, pitch patterns consist of relatively…

Applying Neural Networks in Optical Communication Systems: Possible Pitfalls

NASA Astrophysics Data System (ADS)

Eriksson, Tobias A.; Bulow, Henning; Leven, Andreas

2017-12-01

We investigate the risk of overestimating the performance gain when applying neural network based receivers in systems with pseudo random bit sequences or with limited memory depths, resulting in repeated short patterns. We show that with such sequences, a large artificial gain can be obtained which comes from pattern prediction rather than predicting or compensating the studied channel/phenomena.

Neural Correlates of Sensory Hyporesponsiveness in Toddlers at High Risk for Autism Spectrum Disorder

ERIC Educational Resources Information Center

Simon, David M.; Damiano, Cara R.; Woynaroski, Tiffany G.; Ibañez, Lisa V.; Murias, Michael; Stone, Wendy L.; Wallace, Mark T.; Cascio, Carissa J.

2017-01-01

Altered patterns of sensory responsiveness are a frequently reported feature of Autism Spectrum Disorder (ASD). Younger siblings of individuals with ASD are at a greatly elevated risk of a future diagnosis of ASD, but little is known about the neural basis of sensory responsiveness patterns in this population. Younger siblings (n = 20) of children…

A generalized locomotion CPG architecture based on oscillatory building blocks.

PubMed

Yang, Zhijun; França, Felipe M G

2003-07-01

Neural oscillation is one of the most extensively investigated topics of artificial neural networks. Scientific approaches to the functionalities of both natural and artificial intelligences are strongly related to mechanisms underlying oscillatory activities. This paper concerns itself with the assumption of the existence of central pattern generators (CPGs), which are the plausible neural architectures with oscillatory capabilities, and presents a discrete and generalized approach to the functionality of locomotor CPGs of legged animals. Based on scheduling by multiple edge reversal (SMER), a primitive and deterministic distributed algorithm, it is shown how oscillatory building block (OBB) modules can be created and, hence, how OBB-based networks can be formulated as asymmetric Hopfield-like neural networks for the generation of complex coordinated rhythmic patterns observed among pairs of biological motor neurons working during different gait patterns. It is also shown that the resulting Hopfield-like network possesses the property of reproducing the whole spectrum of different gaits intrinsic to the target locomotor CPGs. Although the new approach is not restricted to the understanding of the neurolocomotor system of any particular animal, hexapodal and quadrupedal gait patterns are chosen as illustrations given the wide interest expressed by the ongoing research in the area.

Disentangling neural representations of value and salience in the human brain

PubMed Central

Kahnt, Thorsten; Park, Soyoung Q; Haynes, John-Dylan; Tobler, Philippe N.

2014-01-01

A large body of evidence has implicated the posterior parietal and orbitofrontal cortex in the processing of value. However, value correlates perfectly with salience when appetitive stimuli are investigated in isolation. Accordingly, considerable uncertainty has remained about the precise nature of the previously identified signals. In particular, recent evidence suggests that neurons in the primate parietal cortex signal salience instead of value. To investigate neural signatures of value and salience, here we apply multivariate (pattern-based) analyses to human functional MRI data acquired during a noninstrumental outcome-prediction task involving appetitive and aversive outcomes. Reaction time data indicated additive and independent effects of value and salience. Critically, we show that multivoxel ensemble activity in the posterior parietal cortex encodes predicted value and salience in superior and inferior compartments, respectively. These findings reinforce the earlier reports of parietal value signals and reconcile them with the recent salience report. Moreover, we find that multivoxel patterns in the orbitofrontal cortex correlate with value. Importantly, the patterns coding for the predicted value of appetitive and aversive outcomes are similar, indicating a common neural scale for appetite and aversive values in the orbitofrontal cortex. Thus orbitofrontal activity patterns satisfy a basic requirement for a neural value signal. PMID:24639493

Developmental trajectory of neural specialization for letter and number visual processing.

PubMed

Park, Joonkoo; van den Berg, Berry; Chiang, Crystal; Woldorff, Marty G; Brannon, Elizabeth M

2018-05-01

Adult neuroimaging studies have demonstrated dissociable neural activation patterns in the visual cortex in response to letters (Latin alphabet) and numbers (Arabic numerals), which suggest a strong experiential influence of reading and mathematics on the human visual system. Here, developmental trajectories in the event-related potential (ERP) patterns evoked by visual processing of letters, numbers, and false fonts were examined in four different age groups (7-, 10-, 15-year-olds, and young adults). The 15-year-olds and adults showed greater neural sensitivity to letters over numbers in the left visual cortex and the reverse pattern in the right visual cortex, extending previous findings in adults to teenagers. In marked contrast, 7- and 10-year-olds did not show this dissociable neural pattern. Furthermore, the contrast of familiar stimuli (letters or numbers) versus unfamiliar ones (false fonts) showed stark ERP differences between the younger (7- and 10-year-olds) and the older (15-year-olds and adults) participants. These results suggest that both coarse (familiar versus unfamiliar) and fine (letters versus numbers) tuning for letters and numbers continue throughout childhood and early adolescence, demonstrating a profound impact of uniquely human cultural inventions on visual cognition and its development. © 2017 John Wiley & Sons Ltd.

What can be found in scalp EEG spectrum beyond common frequency bands. EEG-fMRI study

NASA Astrophysics Data System (ADS)

Marecek, R.; Lamos, M.; Mikl, M.; Barton, M.; Fajkus, J.; I, Rektor; Brazdil, M.

2016-08-01

Objective. The scalp EEG spectrum is a frequently used marker of neural activity. Commonly, the preprocessing of EEG utilizes constraints, e.g. dealing with a predefined subset of electrodes or a predefined frequency band of interest. Such treatment of the EEG spectrum neglects the fact that particular neural processes may be reflected in several frequency bands and/or several electrodes concurrently, and can overlook the complexity of the structure of the EEG spectrum. Approach. We showed that the EEG spectrum structure can be described by parallel factor analysis (PARAFAC), a method which blindly uncovers the spatial-temporal-spectral patterns of EEG. We used an algorithm based on variational Bayesian statistics to reveal nine patterns from the EEG of 38 healthy subjects, acquired during a semantic decision task. The patterns reflected neural activity synchronized across theta, alpha, beta and gamma bands and spread over many electrodes, as well as various EEG artifacts. Main results. Specifically, one of the patterns showed significant correlation with the stimuli timing. The correlation was higher when compared to commonly used models of neural activity (power fluctuations in distinct frequency band averaged across a subset of electrodes) and we found significantly correlated hemodynamic fluctuations in simultaneously acquired fMRI data in regions known to be involved in speech processing. Further, we show that the pattern also occurs in EEG data which were acquired outside the MR machine. Two other patterns reflected brain rhythms linked to the attentional and basal ganglia large scale networks. The other patterns were related to various EEG artifacts. Significance. These results show that PARAFAC blindly identifies neural activity in the EEG spectrum and that it naturally handles the correlations among frequency bands and electrodes. We conclude that PARAFAC seems to be a powerful tool for analysis of the EEG spectrum and might bring novel insight to the relationships between EEG activity and brain hemodynamics.

Improved Adjoint-Operator Learning For A Neural Network

NASA Technical Reports Server (NTRS)

Toomarian, Nikzad; Barhen, Jacob

1995-01-01

Improved method of adjoint-operator learning reduces amount of computation and associated computational memory needed to make electronic neural network learn temporally varying pattern (e.g., to recognize moving object in image) in real time. Method extension of method described in "Adjoint-Operator Learning for a Neural Network" (NPO-18352).

Seasonal population dynamics of the invasive polychaete genus Marenzelleria spp. in contrasting soft-sediment habitats

NASA Astrophysics Data System (ADS)

Kauppi, L.; Norkko, A.; Norkko, J.

2018-01-01

Three species of the invasive polychaete genus Marenzelleria are among the dominant benthic taxa in many, especially deeper, areas in the Baltic Sea. The population dynamics of the polychaetes in the Baltic are, however, still largely unknown. We conducted monthly samplings of the benthic communities and environmental parameters at five sites with differing depths and sediment characteristics in the northern Baltic Sea (59°50.896‧, 23°15.092‧) to study the population dynamics, productivity and growth of Marenzelleria spp. from April 2013 to June 2014. The species of Marenzelleria occurring at the study sites were identified by genetic analyses. At the deepest site (33 m) only M. arctia was present, while all three species were found at the shallower, muddy sites (up to 20 m depth). At the shallow (6 m) sandy site only M. viridis and M. neglecta occurred. The sites differed in the seasonal dynamics of the Marenzelleria spp. population, reflecting the different species identities. The muddy sites up to 20 m depth showed clear seasonal dynamics, with the population practically disappearing by winter, whereas more stable populations occurred at the deepest site and at the sandy site. The highest density, biomass and production were observed at the 20 m deep, organic-rich muddy site where all three species recruited. The seasonally very high densities are likely to have important consequences for organic matter processing, and species interactions at these sites. The observed high productivity of the populations has possibly facilitated their establishment, and considerably increased secondary production in especially the deeper areas.

Physical processes dominate in shaping invertebrate assemblages in reef-associated sediments of an exposed Hawaiian coast

USGS Publications Warehouse

DeFelice, R.C.; Parrish, J.D.

2001-01-01

The invertebrate assemblages in sediments bordering exposed fringing reefs at Hanalei Bay, Kauai, Hawaii, were examined during July to September 1994. Densities of invertebrate animals larger than 0.5 mm in sediments of the bay ranged from counts of 10 260 m-2 in the fine carbonate sands of the central bay to 870 m-2 in the habitat dominated by terrigenous silt near the reef edge close to the Hanalei river mouth. Similar sediment types supported broadly similar infaunal communities. Within the primarily carbonate sediments, mean grain size and wave exposure appear to have an important influence on the community. Taxonomic richness, number of individuals, and diversity showed significant negative relationships with exposure to wave energy (as estimated by sand ripple wavelength). The number of individuals was also significantly correlated with mean grain size. Overall, polychaetes and small crustaceans were numerically dominant among the major taxonomic groups investigated. Macrophagous and microphagous polychaetes had significant, but opposite, associations with grain size. In addition, microphagous polychaetes were significantly negatively correlated with wave exposure. No habitat variable measured could explain the variation in percent composition of crustaceans or echinoderms in the sedimentary habitats. The percentage of gastropods in the community was significantly negatively correlated with grain size, grain-size standard deviation and exposure, and positively with percent organic carbon. Bivalves were significantly positively associated with depth and grain size. These strong relationships imply that, in Hanalei Bay, physical processes are especially important in influencing assemblage structure, and that community structure and composition vary continuously along environmental gradients.

Minimal perceptrons for memorizing complex patterns

NASA Astrophysics Data System (ADS)

Pastor, Marissa; Song, Juyong; Hoang, Danh-Tai; Jo, Junghyo

2016-11-01

Feedforward neural networks have been investigated to understand learning and memory, as well as applied to numerous practical problems in pattern classification. It is a rule of thumb that more complex tasks require larger networks. However, the design of optimal network architectures for specific tasks is still an unsolved fundamental problem. In this study, we consider three-layered neural networks for memorizing binary patterns. We developed a new complexity measure of binary patterns, and estimated the minimal network size for memorizing them as a function of their complexity. We formulated the minimal network size for regular, random, and complex patterns. In particular, the minimal size for complex patterns, which are neither ordered nor disordered, was predicted by measuring their Hamming distances from known ordered patterns. Our predictions agree with simulations based on the back-propagation algorithm.

SoxB1-driven transcriptional network underlies neural-specific interpretation of morphogen signals.

PubMed

Oosterveen, Tony; Kurdija, Sanja; Ensterö, Mats; Uhde, Christopher W; Bergsland, Maria; Sandberg, Magnus; Sandberg, Rickard; Muhr, Jonas; Ericson, Johan

2013-04-30

The reiterative deployment of a small cadre of morphogen signals underlies patterning and growth of most tissues during embyogenesis, but how such inductive events result in tissue-specific responses remains poorly understood. By characterizing cis-regulatory modules (CRMs) associated with genes regulated by Sonic hedgehog (Shh), retinoids, or bone morphogenetic proteins in the CNS, we provide evidence that the neural-specific interpretation of morphogen signaling reflects a direct integration of these pathways with SoxB1 proteins at the CRM level. Moreover, expression of SoxB1 proteins in the limb bud confers on mesodermal cells the potential to activate neural-specific target genes upon Shh, retinoid, or bone morphogenetic protein signaling, and the collocation of binding sites for SoxB1 and morphogen-mediatory transcription factors in CRMs faithfully predicts neural-specific gene activity. Thus, an unexpectedly simple transcriptional paradigm appears to conceptually explain the neural-specific interpretation of pleiotropic signaling during vertebrate development. Importantly, genes induced in a SoxB1-dependent manner appear to constitute repressive gene regulatory networks that are directly interlinked at the CRM level to constrain the regional expression of patterning genes. Accordingly, not only does the topology of SoxB1-driven gene regulatory networks provide a tissue-specific mode of gene activation, but it also determines the spatial expression pattern of target genes within the developing neural tube.

Similar patterns of neural activity predict memory function during encoding and retrieval.

PubMed

Kragel, James E; Ezzyat, Youssef; Sperling, Michael R; Gorniak, Richard; Worrell, Gregory A; Berry, Brent M; Inman, Cory; Lin, Jui-Jui; Davis, Kathryn A; Das, Sandhitsu R; Stein, Joel M; Jobst, Barbara C; Zaghloul, Kareem A; Sheth, Sameer A; Rizzuto, Daniel S; Kahana, Michael J

2017-07-15

Neural networks that span the medial temporal lobe (MTL), prefrontal cortex, and posterior cortical regions are essential to episodic memory function in humans. Encoding and retrieval are supported by the engagement of both distinct neural pathways across the cortex and common structures within the medial temporal lobes. However, the degree to which memory performance can be determined by neural processing that is common to encoding and retrieval remains to be determined. To identify neural signatures of successful memory function, we administered a delayed free-recall task to 187 neurosurgical patients implanted with subdural or intraparenchymal depth electrodes. We developed multivariate classifiers to identify patterns of spectral power across the brain that independently predicted successful episodic encoding and retrieval. During encoding and retrieval, patterns of increased high frequency activity in prefrontal, MTL, and inferior parietal cortices, accompanied by widespread decreases in low frequency power across the brain predicted successful memory function. Using a cross-decoding approach, we demonstrate the ability to predict memory function across distinct phases of the free-recall task. Furthermore, we demonstrate that classifiers that combine information from both encoding and retrieval states can outperform task-independent models. These findings suggest that the engagement of a core memory network during either encoding or retrieval shapes the ability to remember the past, despite distinct neural interactions that facilitate encoding and retrieval. Copyright © 2017 Elsevier Inc. All rights reserved.

In-vivo determination of chewing patterns using FBG and artificial neural networks

NASA Astrophysics Data System (ADS)

Pegorini, Vinicius; Zen Karam, Leandro; Rocha Pitta, Christiano S.; Ribeiro, Richardson; Simioni Assmann, Tangriani; Cardozo da Silva, Jean Carlos; Bertotti, Fábio L.; Kalinowski, Hypolito J.; Cardoso, Rafael

2015-09-01

This paper reports the process of pattern classification of the chewing process of ruminants. We propose a simplified signal processing scheme for optical fiber Bragg grating (FBG) sensors based on machine learning techniques. The FBG sensors measure the biomechanical forces during jaw movements and an artificial neural network is responsible for the classification of the associated chewing pattern. In this study, three patterns associated to dietary supplement, hay and ryegrass were considered. Additionally, two other important events for ingestive behavior studies were monitored, rumination and idle period. Experimental results show that the proposed approach for pattern classification has been capable of differentiating the materials involved in the chewing process with a small classification error.

Repair and Dredging of Bear Creek Marina Final Environmental Assessment

DTIC Science & Technology

2007-06-01

vegetation typically adapted for life in saturated soil conditions” (USACE, 1987). The majority of jurisdictional wetlands in the United States are...invertebrates, including amphipods, lancelets, insect larvae, mollusks, polychaetes, gastropods , shrimp, isopods, brachiopods, and crustaceans. Little is

Benthic Community Response to Hypoxia: Baseline Data

DTIC Science & Technology

2009-01-01

were represented by six different phyla, namely Annelida, Sipuncula, Arthropoda, Cnidaria , Mollusca and Echinodermata (Table II). The phylum Annelida...was solely represented by polychaetes and the phylum Cnidaria was represented solely by hydroids. However, the phylum Mollusca was represented by

Competitive STDP Learning of Overlapping Spatial Patterns.

PubMed

Krunglevicius, Dalius

2015-08-01

Spike-timing-dependent plasticity (STDP) is a set of Hebbian learning rules firmly based on biological evidence. It has been demonstrated that one of the STDP learning rules is suited for learning spatiotemporal patterns. When multiple neurons are organized in a simple competitive spiking neural network, this network is capable of learning multiple distinct patterns. If patterns overlap significantly (i.e., patterns are mutually inclusive), however, competition would not preclude trained neuron's responding to a new pattern and adjusting synaptic weights accordingly. This letter presents a simple neural network that combines vertical inhibition and Euclidean distance-dependent synaptic strength factor. This approach helps to solve the problem of pattern size-dependent parameter optimality and significantly reduces the probability of a neuron's forgetting an already learned pattern. For demonstration purposes, the network was trained for the first ten letters of the Braille alphabet.

Exploring Neural Network Models with Hierarchical Memories and Their Use in Modeling Biological Systems

NASA Astrophysics Data System (ADS)

Pusuluri, Sai Teja

Energy landscapes are often used as metaphors for phenomena in biology, social sciences and finance. Different methods have been implemented in the past for the construction of energy landscapes. Neural network models based on spin glass physics provide an excellent mathematical framework for the construction of energy landscapes. This framework uses a minimal number of parameters and constructs the landscape using data from the actual phenomena. In the past neural network models were used to mimic the storage and retrieval process of memories (patterns) in the brain. With advances in the field now, these models are being used in machine learning, deep learning and modeling of complex phenomena. Most of the past literature focuses on increasing the storage capacity and stability of stored patterns in the network but does not study these models from a modeling perspective or an energy landscape perspective. This dissertation focuses on neural network models both from a modeling perspective and from an energy landscape perspective. I firstly show how the cellular interconversion phenomenon can be modeled as a transition between attractor states on an epigenetic landscape constructed using neural network models. The model allows the identification of a reaction coordinate of cellular interconversion by analyzing experimental and simulation time course data. Monte Carlo simulations of the model show that the initial phase of cellular interconversion is a Poisson process and the later phase of cellular interconversion is a deterministic process. Secondly, I explore the static features of landscapes generated using neural network models, such as sizes of basins of attraction and densities of metastable states. The simulation results show that the static landscape features are strongly dependent on the correlation strength and correlation structure between patterns. Using different hierarchical structures of the correlation between patterns affects the landscape features. These results show how the static landscape features can be controlled by adjusting the correlations between patterns. Finally, I explore the dynamical features of landscapes generated using neural network models such as the stability of minima and the transition rates between minima. The results from this project show that the stability depends on the correlations between patterns. It is also found that the transition rates between minima strongly depend on the type of bias applied and the correlation between patterns. The results from this part of the dissertation can be useful in engineering an energy landscape without even having the complete information about the associated minima of the landscape.

Neural Global Pattern Similarity Underlies True and False Memories.

PubMed

Ye, Zhifang; Zhu, Bi; Zhuang, Liping; Lu, Zhonglin; Chen, Chuansheng; Xue, Gui

2016-06-22

The neural processes giving rise to human memory strength signals remain poorly understood. Inspired by formal computational models that posit a central role of global matching in memory strength, we tested a novel hypothesis that the strengths of both true and false memories arise from the global similarity of an item's neural activation pattern during retrieval to that of all the studied items during encoding (i.e., the encoding-retrieval neural global pattern similarity [ER-nGPS]). We revealed multiple ER-nGPS signals that carried distinct information and contributed differentially to true and false memories: Whereas the ER-nGPS in the parietal regions reflected semantic similarity and was scaled with the recognition strengths of both true and false memories, ER-nGPS in the visual cortex contributed solely to true memory. Moreover, ER-nGPS differences between the parietal and visual cortices were correlated with frontal monitoring processes. By combining computational and neuroimaging approaches, our results advance a mechanistic understanding of memory strength in recognition. What neural processes give rise to memory strength signals, and lead to our conscious feelings of familiarity? Using fMRI, we found that the memory strength of a given item depends not only on how it was encoded during learning, but also on the similarity of its neural representation with other studied items. The global neural matching signal, mainly in the parietal lobule, could account for the memory strengths of both studied and unstudied items. Interestingly, a different global matching signal, originated from the visual cortex, could distinguish true from false memories. The findings reveal multiple neural mechanisms underlying the memory strengths of events registered in the brain. Copyright © 2016 the authors 0270-6474/16/366792-11$15.00/0.

Spatio-temporal conditional inference and hypothesis tests for neural ensemble spiking precision

PubMed Central

Harrison, Matthew T.; Amarasingham, Asohan; Truccolo, Wilson

2014-01-01

The collective dynamics of neural ensembles create complex spike patterns with many spatial and temporal scales. Understanding the statistical structure of these patterns can help resolve fundamental questions about neural computation and neural dynamics. Spatio-temporal conditional inference (STCI) is introduced here as a semiparametric statistical framework for investigating the nature of precise spiking patterns from collections of neurons that is robust to arbitrarily complex and nonstationary coarse spiking dynamics. The main idea is to focus statistical modeling and inference, not on the full distribution of the data, but rather on families of conditional distributions of precise spiking given different types of coarse spiking. The framework is then used to develop families of hypothesis tests for probing the spatio-temporal precision of spiking patterns. Relationships among different conditional distributions are used to improve multiple hypothesis testing adjustments and to design novel Monte Carlo spike resampling algorithms. Of special note are algorithms that can locally jitter spike times while still preserving the instantaneous peri-stimulus time histogram (PSTH) or the instantaneous total spike count from a group of recorded neurons. The framework can also be used to test whether first-order maximum entropy models with possibly random and time-varying parameters can account for observed patterns of spiking. STCI provides a detailed example of the generic principle of conditional inference, which may be applicable in other areas of neurostatistical analysis. PMID:25380339

Operant conditioning of synaptic and spiking activity patterns in single hippocampal neurons.

PubMed

Ishikawa, Daisuke; Matsumoto, Nobuyoshi; Sakaguchi, Tetsuya; Matsuki, Norio; Ikegaya, Yuji

2014-04-02

Learning is a process of plastic adaptation through which a neural circuit generates a more preferable outcome; however, at a microscopic level, little is known about how synaptic activity is patterned into a desired configuration. Here, we report that animals can generate a specific form of synaptic activity in a given neuron in the hippocampus. In awake, head-restricted mice, we applied electrical stimulation to the lateral hypothalamus, a reward-associated brain region, when whole-cell patch-clamped CA1 neurons exhibited spontaneous synaptic activity that met preset criteria. Within 15 min, the mice learned to generate frequently the excitatory synaptic input pattern that satisfied the criteria. This reinforcement learning of synaptic activity was not observed for inhibitory input patterns. When a burst unit activity pattern was conditioned in paired and nonpaired paradigms, the frequency of burst-spiking events increased and decreased, respectively. The burst reinforcement occurred in the conditioned neuron but not in other adjacent neurons; however, ripple field oscillations were concomitantly reinforced. Neural conditioning depended on activation of NMDA receptors and dopamine D1 receptors. Acutely stressed mice and depression model mice that were subjected to forced swimming failed to exhibit the neural conditioning. This learning deficit was rescued by repetitive treatment with fluoxetine, an antidepressant. Therefore, internally motivated animals are capable of routing an ongoing action potential series into a specific neural pathway of the hippocampal network.

Distributed patterns of activity in sensory cortex reflect the precision of multiple items maintained in visual short-term memory.

PubMed

Emrich, Stephen M; Riggall, Adam C; Larocque, Joshua J; Postle, Bradley R

2013-04-10

Traditionally, load sensitivity of sustained, elevated activity has been taken as an index of storage for a limited number of items in visual short-term memory (VSTM). Recently, studies have demonstrated that the contents of a single item held in VSTM can be decoded from early visual cortex, despite the fact that these areas do not exhibit elevated, sustained activity. It is unknown, however, whether the patterns of neural activity decoded from sensory cortex change as a function of load, as one would expect from a region storing multiple representations. Here, we use multivoxel pattern analysis to examine the neural representations of VSTM in humans across multiple memory loads. In an important extension of previous findings, our results demonstrate that the contents of VSTM can be decoded from areas that exhibit a transient response to visual stimuli, but not from regions that exhibit elevated, sustained load-sensitive delay-period activity. Moreover, the neural information present in these transiently activated areas decreases significantly with increasing load, indicating load sensitivity of the patterns of activity that support VSTM maintenance. Importantly, the decrease in classification performance as a function of load is correlated with within-subject changes in mnemonic resolution. These findings indicate that distributed patterns of neural activity in putatively sensory visual cortex support the representation and precision of information in VSTM.

Artificial Neural Network with Regular Graph for Maximum Air Temperature Forecasting:. the Effect of Decrease in Nodes Degree on Learning

NASA Astrophysics Data System (ADS)

Ghaderi, A. H.; Darooneh, A. H.

The behavior of nonlinear systems can be analyzed by artificial neural networks. Air temperature change is one example of the nonlinear systems. In this work, a new neural network method is proposed for forecasting maximum air temperature in two cities. In this method, the regular graph concept is used to construct some partially connected neural networks that have regular structures. The learning results of fully connected ANN and networks with proposed method are compared. In some case, the proposed method has the better result than conventional ANN. After specifying the best network, the effect of input pattern numbers on the prediction is studied and the results show that the increase of input patterns has a direct effect on the prediction accuracy.

Noise in Neural Networks: Thresholds, Hysteresis, and Neuromodulation of Signal-To-Noise

NASA Astrophysics Data System (ADS)

Keeler, James D.; Pichler, Elgar E.; Ross, John

1989-03-01

We study a neural-network model including Gaussian noise, higher-order neuronal interactions, and neuromodulation. For a first-order network, there is a threshold in the noise level (phase transition) above which the network displays only disorganized behavior and critical slowing down near the noise threshold. The network can tolerate more noise if it has higher-order feedback interactions, which also lead to hysteresis and multistability in the network dynamics. The signal-to-noise ratio can be adjusted in a biological neural network by neuromodulators such as norepinephrine. Comparisons are made to experimental results and further investigations are suggested to test the effects of hysteresis and neuromodulation in pattern recognition and learning. We propose that norepinephrine may ``quench'' the neural patterns of activity to enhance the ability to learn details.

What does the fruitless gene tell us about nature vs. nurture in the sex life of Drosophila?

PubMed

Yamamoto, Daisuke; Kohatsu, Soh

2017-04-03

The fruitless (fru) gene in Drosophila has been proposed to play a master regulator role in the formation of neural circuitries for male courtship behavior, which is typically considered to be an innate behavior composed of a fixed action pattern as generated by the central pattern generator. However, recent studies have shed light on experience-dependent changes and sensory-input-guided plasticity in courtship behavior. For example, enhanced male-male courtship, a fru mutant "hallmark," disappears when fru-mutant males are raised in isolation. The fact that neural fru expression is induced by neural activities in the adult invites the supposition that Fru as a chromatin regulator mediates experience-dependent epigenetic modification, which underlies the neural and behavioral plasticity.

Global Neural Pattern Similarity as a Common Basis for Categorization and Recognition Memory

PubMed Central

Xue, Gui; Love, Bradley C.; Preston, Alison R.; Poldrack, Russell A.

2014-01-01

Familiarity, or memory strength, is a central construct in models of cognition. In previous categorization and long-term memory research, correlations have been found between psychological measures of memory strength and activation in the medial temporal lobes (MTLs), which suggests a common neural locus for memory strength. However, activation alone is insufficient for determining whether the same mechanisms underlie neural function across domains. Guided by mathematical models of categorization and long-term memory, we develop a theory and a method to test whether memory strength arises from the global similarity among neural representations. In human subjects, we find significant correlations between global similarity among activation patterns in the MTLs and both subsequent memory confidence in a recognition memory task and model-based measures of memory strength in a category learning task. Our work bridges formal cognitive theories and neuroscientific models by illustrating that the same global similarity computations underlie processing in multiple cognitive domains. Moreover, by establishing a link between neural similarity and psychological memory strength, our findings suggest that there may be an isomorphism between psychological and neural representational spaces that can be exploited to test cognitive theories at both the neural and behavioral levels. PMID:24872552

Implicit Race Bias Decreases the Similarity of Neural Representations of Black and White Faces

PubMed Central

Brosch, Tobias; Bar-David, Eyal; Phelps, Elizabeth A.

2013-01-01

Implicit race bias has been shown to affect decisions and behaviors. It may also change perceptual experience by increasing perceived differences between social groups. We investigated how this phenomenon may be expressed at the neural level by testing whether the distributed blood-oxygenation-level-dependent (BOLD) patterns representing Black and White faces are more dissimilar in participants with higher implicit race bias. We used multivoxel pattern analysis to predict the race of faces participants were viewing. We successfully predicted the race of the faces on the basis of BOLD activation patterns in early occipital visual cortex, occipital face area, and fusiform face area (FFA). Whereas BOLD activation patterns in early visual regions, likely reflecting different perceptual features, allowed successful prediction for all participants, successful prediction on the basis of BOLD activation patterns in FFA, a high-level face-processing region, was restricted to participants with high pro-White bias. These findings suggest that stronger implicit pro-White bias decreases the similarity of neural representations of Black and White faces. PMID:23300228

Neural Cross-Frequency Coupling: Connecting Architectures, Mechanisms, and Functions.

PubMed

Hyafil, Alexandre; Giraud, Anne-Lise; Fontolan, Lorenzo; Gutkin, Boris

2015-11-01

Neural oscillations are ubiquitously observed in the mammalian brain, but it has proven difficult to tie oscillatory patterns to specific cognitive operations. Notably, the coupling between neural oscillations at different timescales has recently received much attention, both from experimentalists and theoreticians. We review the mechanisms underlying various forms of this cross-frequency coupling. We show that different types of neural oscillators and cross-frequency interactions yield distinct signatures in neural dynamics. Finally, we associate these mechanisms with several putative functions of cross-frequency coupling, including neural representations of multiple environmental items, communication over distant areas, internal clocking of neural processes, and modulation of neural processing based on temporal predictions. Copyright © 2015 Elsevier Ltd. All rights reserved.

Selective and Efficient Neural Coding of Communication Signals Depends on Early Acoustic and Social Environment

PubMed Central

Amin, Noopur; Gastpar, Michael; Theunissen, Frédéric E.

2013-01-01

Previous research has shown that postnatal exposure to simple, synthetic sounds can affect the sound representation in the auditory cortex as reflected by changes in the tonotopic map or other relatively simple tuning properties, such as AM tuning. However, their functional implications for neural processing in the generation of ethologically-based perception remain unexplored. Here we examined the effects of noise-rearing and social isolation on the neural processing of communication sounds such as species-specific song, in the primary auditory cortex analog of adult zebra finches. Our electrophysiological recordings reveal that neural tuning to simple frequency-based synthetic sounds is initially established in all the laminae independent of patterned acoustic experience; however, we provide the first evidence that early exposure to patterned sound statistics, such as those found in native sounds, is required for the subsequent emergence of neural selectivity for complex vocalizations and for shaping neural spiking precision in superficial and deep cortical laminae, and for creating efficient neural representations of song and a less redundant ensemble code in all the laminae. Our study also provides the first causal evidence for ‘sparse coding’, such that when the statistics of the stimuli were changed during rearing, as in noise-rearing, that the sparse or optimal representation for species-specific vocalizations disappeared. Taken together, these results imply that a layer-specific differential development of the auditory cortex requires patterned acoustic input, and a specialized and robust sensory representation of complex communication sounds in the auditory cortex requires a rich acoustic and social environment. PMID:23630587

Dynamic sensory cues shape song structure in Drosophila

NASA Astrophysics Data System (ADS)

Coen, Philip; Clemens, Jan; Weinstein, Andrew J.; Pacheco, Diego A.; Deng, Yi; Murthy, Mala

2014-03-01

The generation of acoustic communication signals is widespread across the animal kingdom, and males of many species, including Drosophilidae, produce patterned courtship songs to increase their chance of success with a female. For some animals, song structure can vary considerably from one rendition to the next; neural noise within pattern generating circuits is widely assumed to be the primary source of such variability, and statistical models that incorporate neural noise are successful at reproducing the full variation present in natural songs. In direct contrast, here we demonstrate that much of the pattern variability in Drosophila courtship song can be explained by taking into account the dynamic sensory experience of the male. In particular, using a quantitative behavioural assay combined with computational modelling, we find that males use fast modulations in visual and self-motion signals to pattern their songs, a relationship that we show is evolutionarily conserved. Using neural circuit manipulations, we also identify the pathways involved in song patterning choices and show that females are sensitive to song features. Our data not only demonstrate that Drosophila song production is not a fixed action pattern, but establish Drosophila as a valuable new model for studies of rapid decision-making under both social and naturalistic conditions.

Distributed Patterns of Reactivation Predict Vividness of Recollection.

PubMed

St-Laurent, Marie; Abdi, Hervé; Buchsbaum, Bradley R

2015-10-01

According to the principle of reactivation, memory retrieval evokes patterns of brain activity that resemble those instantiated when an event was first experienced. Intuitively, one would expect neural reactivation to contribute to recollection (i.e., the vivid impression of reliving past events), but evidence of a direct relationship between the subjective quality of recollection and multiregional reactivation of item-specific neural patterns is lacking. The current study assessed this relationship using fMRI to measure brain activity as participants viewed and mentally replayed a set of short videos. We used multivoxel pattern analysis to train a classifier to identify individual videos based on brain activity evoked during perception and tested how accurately the classifier could distinguish among videos during mental replay. Classification accuracy correlated positively with memory vividness, indicating that the specificity of multivariate brain patterns observed during memory retrieval was related to the subjective quality of a memory. In addition, we identified a set of brain regions whose univariate activity during retrieval predicted both memory vividness and the strength of the classifier's prediction irrespective of the particular video that was retrieved. Our results establish distributed patterns of neural reactivation as a valid and objective marker of the quality of recollection.

The role of sensorimotor learning in the perception of letter-like forms: tracking the causes of neural specialization for letters.

PubMed

James, Karin H; Atwood, Thea P

2009-02-01

Functional specialization in the brain is considered a hallmark of efficient processing. It is therefore not surprising that there are brain areas specialized for processing letters. To better understand the causes of functional specialization for letters, we explore the emergence of this pattern of response in the ventral processing stream through a training paradigm. Previously, we hypothesized that the specialized response pattern seen during letter perception may be due in part to our experience in writing letters. The work presented here investigates whether or not this aspect of letter processing-the integration of sensorimotor systems through writing-leads to functional specialization in the visual system. To test this idea, we investigated whether or not different types of experiences with letter-like stimuli ("pseudoletters") led to functional specialization similar to that which exists for letters. Neural activation patterns were measured using functional magnetic resonance imaging (fMRI) before and after three different types of training sessions. Participants were trained to recognize pseudoletters by writing, typing, or purely visual practice. Results suggested that only after writing practice did neural activation patterns to pseudoletters resemble patterns seen for letters. That is, neural activation in the left fusiform and dorsal precentral gyrus was greater when participants viewed pseudoletters than other, similar stimuli but only after writing experience. Neural activation also increased after typing practice in the right fusiform and left precentral gyrus, suggesting that in some areas, any motor experience may change visual processing. The results of this experiment suggest an intimate interaction among perceptual and motor systems during pseudoletter perception that may be extended to everyday letter perception.

Neural electrical activity and neural network growth.

PubMed

Gafarov, F M

2018-05-01

The development of central and peripheral neural system depends in part on the emergence of the correct functional connectivity in its input and output pathways. Now it is generally accepted that molecular factors guide neurons to establish a primary scaffold that undergoes activity-dependent refinement for building a fully functional circuit. However, a number of experimental results obtained recently shows that the neuronal electrical activity plays an important role in the establishing of initial interneuronal connections. Nevertheless, these processes are rather difficult to study experimentally, due to the absence of theoretical description and quantitative parameters for estimation of the neuronal activity influence on growth in neural networks. In this work we propose a general framework for a theoretical description of the activity-dependent neural network growth. The theoretical description incorporates a closed-loop growth model in which the neural activity can affect neurite outgrowth, which in turn can affect neural activity. We carried out the detailed quantitative analysis of spatiotemporal activity patterns and studied the relationship between individual cells and the network as a whole to explore the relationship between developing connectivity and activity patterns. The model, developed in this work will allow us to develop new experimental techniques for studying and quantifying the influence of the neuronal activity on growth processes in neural networks and may lead to a novel techniques for constructing large-scale neural networks by self-organization. Copyright © 2018 Elsevier Ltd. All rights reserved.

Disentangling diversity patterns in sandy beaches along environmental gradients.

PubMed

Barboza, Francisco R; Gómez, Julio; Lercari, Diego; Defeo, Omar

2012-01-01

Species richness in sandy beaches is strongly affected by concurrent variations in morphodynamics and salinity. However, as in other ecosystems, different groups of species may exhibit contrasting patterns in response to these environmental variables, which would be obscured if only aggregate richness is considered. Deconstructing biodiversity, i.e. considering richness patterns separately for different groups of species according to their taxonomic affiliation, dispersal mode or mobility, could provide a more complete understanding about factors that drive species richness patterns. This study analyzed macroscale variations in species richness at 16 Uruguayan sandy beaches with different morphodynamics, distributed along the estuarine gradient generated by the Rio de la Plata over a 2 year period. Species richness estimates were deconstructed to discriminate among taxonomic groups, supralittoral and intertidal forms, and groups with different feeding habits and development modes. Species richness was lowest at intermediate salinities, increasing towards oceanic and inner estuarine conditions, mainly following the patterns shown for intertidal forms. Moreover, there was a differential tolerance to salinity changes according to the habitat occupied and development mode, which determines the degree of sensitivity of faunal groups to osmotic stress. Generalized (additive and linear) mixed models showed a clear increase of species richness towards dissipative beaches. All taxonomic categories exhibited the same trend, even though responses to grain size and beach slope were less marked for crustaceans and insects than for molluscs or polychaetes. However, supralittoral crustaceans exhibited the opposite trend. Feeding groups decreased from dissipative to reflective systems, deposit feeders being virtually absent in the latter. This deconstructive approach highlights the relevance of life history strategies in structuring communities, highlighting the relative importance that salinity and morphodynamic gradients have on macroscale diversity patterns in sandy beaches.

Motor Cortical Visuomotor Feedback Activity Is Initially Isolated from Downstream Targets in Output-Null Neural State Space Dimensions.

PubMed

Stavisky, Sergey D; Kao, Jonathan C; Ryu, Stephen I; Shenoy, Krishna V

2017-07-05

Neural circuits must transform new inputs into outputs without prematurely affecting downstream circuits while still maintaining other ongoing communication with these targets. We investigated how this isolation is achieved in the motor cortex when macaques received visual feedback signaling a movement perturbation. To overcome limitations in estimating the mapping from cortex to arm movements, we also conducted brain-machine interface (BMI) experiments where we could definitively identify neural firing patterns as output-null or output-potent. This revealed that perturbation-evoked responses were initially restricted to output-null patterns that cancelled out at the neural population code readout and only later entered output-potent neural dimensions. This mechanism was facilitated by the circuit's large null space and its ability to strongly modulate output-potent dimensions when generating corrective movements. These results show that the nervous system can temporarily isolate portions of a circuit's activity from its downstream targets by restricting this activity to the circuit's output-null neural dimensions. Copyright © 2017 Elsevier Inc. All rights reserved.

Mapping of Courtship Behavior-Induced Neural Activity in the Thoracic Ganglia of Silkmoth Bombyx mori by an Immediate Early Gene, Hr38.

PubMed

Morishita, Koudai; Iwami, Masafumi; Kiya, Taketoshi

2018-06-01

In the central nervous system of insects, motor patterns are generated in the thoracic ganglia under the control of brain, where sensory information is integrated and behavioral decisions are made. Previously, we established neural activity-mapping methods using an immediate early gene, BmHr38, as a neural activity marker in the brain of male silkmoth Bombyx mori. In the present study, to gain insights into neural mechanisms of motor-pattern generation in the thoracic ganglia, we investigated expression of BmHr38 in response to sex pheromone-induced courtship behavior. Levels of BmHr38 expression were strongly correlated between the brain and thoracic ganglia, suggesting that neural activity in the thoracic ganglia is tightly controlled by the brain. In situ hybridization of BmHr38 revealed that 20-30% of thoracic neurons are activated by courtship behavior. Using serial sections, we constructed a comprehensive map of courtship behaviorinduced activity in the thoracic ganglia. These results provide important clues into how complex courtship behavior is generated in the neural circuits of thoracic ganglia.

Shared memories reveal shared structure in neural activity across individuals

PubMed Central

Chen, J.; Leong, Y.C.; Honey, C.J.; Yong, C.H.; Norman, K.A.; Hasson, U.

2016-01-01

Our lives revolve around sharing experiences and memories with others. When different people recount the same events, how similar are their underlying neural representations? Participants viewed a fifty-minute movie, then verbally described the events during functional MRI, producing unguided detailed descriptions lasting up to forty minutes. As each person spoke, event-specific spatial patterns were reinstated in default-network, medial-temporal, and high-level visual areas. Individual event patterns were both highly discriminable from one another and similar between people, suggesting consistent spatial organization. In many high-order areas, patterns were more similar between people recalling the same event than between recall and perception, indicating systematic reshaping of percept into memory. These results reveal the existence of a common spatial organization for memories in high-level cortical areas, where encoded information is largely abstracted beyond sensory constraints; and that neural patterns during perception are altered systematically across people into shared memory representations for real-life events. PMID:27918531

Recognition of neural brain activity patterns correlated with complex motor activity

NASA Astrophysics Data System (ADS)

Kurkin, Semen; Musatov, Vyacheslav Yu.; Runnova, Anastasia E.; Grubov, Vadim V.; Efremova, Tatyana Yu.; Zhuravlev, Maxim O.

2018-04-01

In this paper, based on the apparatus of artificial neural networks, a technique for recognizing and classifying patterns corresponding to imaginary movements on electroencephalograms (EEGs) obtained from a group of untrained subjects was developed. The works on the selection of the optimal type, topology, training algorithms and neural network parameters were carried out from the point of view of the most accurate and fast recognition and classification of patterns on multi-channel EEGs associated with the imagination of movements. The influence of the number and choice of the analyzed channels of a multichannel EEG on the quality of recognition of imaginary movements was also studied, and optimal configurations of electrode arrangements were obtained. The effect of pre-processing of EEG signals is analyzed from the point of view of improving the accuracy of recognition of imaginary movements.

Recognition and classification of oscillatory patterns of electric brain activity using artificial neural network approach

NASA Astrophysics Data System (ADS)

Pchelintseva, Svetlana V.; Runnova, Anastasia E.; Musatov, Vyacheslav Yu.; Hramov, Alexander E.

2017-03-01

In the paper we study the problem of recognition type of the observed object, depending on the generated pattern and the registered EEG data. EEG recorded at the time of displaying cube Necker characterizes appropriate state of brain activity. As an image we use bistable image Necker cube. Subject selects the type of cube and interpret it either as aleft cube or as the right cube. To solve the problem of recognition, we use artificial neural networks. In our paper to create a classifier we have considered a multilayer perceptron. We examine the structure of the artificial neural network and define cubes recognition accuracy.

Modeling the Electrode-Neuron Interface of Cochlear Implants: Effects of Neural Survival, Electrode Placement, and the Partial Tripolar Configuration

PubMed Central

Goldwyn, Joshua H.; Bierer, Steven M.; Bierer, Julie A.

2010-01-01

The partial tripolar electrode configuration is a relatively novel stimulation strategies that can generate more spatially focused electric fields than the commonly used monopolar configuration. Focused stimulation strategies should improve spectral resolution in cochlear implant users, but may also be more sensitive to local irregularities in the electrode-neuron interface. In this study, we develop a practical computer model of cochlear implant stimulation that can simulate neural activation in a simplified cochlear geometry and we relate the resulting patterns of neural activity to basic psychophysical measures. We examine how two types of local irregularities in the electrode-neuron interface, variations in spiral ganglion nerve density and electrode position within the scala tympani, affect the simulated neural activation patterns and how these patterns change with electrode configuration. The model shows that higher partial tripolar fractions activate more spatially restricted populations of neurons at all current levels and require higher current levels to excite a given number of neurons. We find that threshold levels are more sensitive at high partial tripolar fractions to both types of irregularities, but these effects are not independent. In particular, at close electrode-neuron distances, activation is typically more spatially localized which leads to a greater influence of neural dead regions. PMID:20580801

CELL SEGREGATION, MIXING, AND TISSUE PATTERN IN THE SPINAL CORD OF THE XENOPUS LAEVIS NEURULA

PubMed Central

Davidson, Lance A.; Keller, Raymond E.

2014-01-01

Background During Xenopus laevis neurulation, neural ectodermal cells of the spinal cord are patterned at the same time that they intercalate mediolaterally and radially, moving within and between two cell layers. Curious if these rearrangements disrupt early cell identities, we lineage-traced cells in each layer from neural plate stages to the closed neural tube, and used in situ hybridization to assay gene expression in the moving cells. Results Our biotin- and fluorescent labeling of deep and superficial cells reveals that mediolateral intercalation does not disrupt cell cohorts, in other words it is conservative. However, outside the midline notoplate, later radial intercalation does displace superficial cells dorsoventrally, radically disrupting cell cohorts. The tube roof is composed almost exclusively of superficial cells, including some displaced from ventral positions; gene expression in these displaced cells must now be surveyed further. Superficial cells also flank the tube’s floor, which is, itself, almost exclusively composed of deep cells. Conclusions Our data provide: 1) a fate map of superficial- and deep-cell positions within the Xenopus neural tube, 2) the paths taken to these positions, and 3) preliminary evidence of re-patterning in cells carried out of one environment and into another, during neural morphogenesis. PMID:23813905

Category-Specific Neural Oscillations Predict Recall Organization During Memory Search

PubMed Central

Morton, Neal W.; Kahana, Michael J.; Rosenberg, Emily A.; Baltuch, Gordon H.; Litt, Brian; Sharan, Ashwini D.; Sperling, Michael R.; Polyn, Sean M.

2013-01-01

Retrieved-context models of human memory propose that as material is studied, retrieval cues are constructed that allow one to target particular aspects of past experience. We examined the neural predictions of these models by using electrocorticographic/depth recordings and scalp electroencephalography (EEG) to characterize category-specific oscillatory activity, while participants studied and recalled items from distinct, neurally discriminable categories. During study, these category-specific patterns predict whether a studied item will be recalled. In the scalp EEG experiment, category-specific activity during study also predicts whether a given item will be recalled adjacent to other same-category items, consistent with the proposal that a category-specific retrieval cue is used to guide memory search. Retrieved-context models suggest that integrative neural circuitry is involved in the construction and maintenance of the retrieval cue. Consistent with this hypothesis, we observe category-specific patterns that rise in strength as multiple same-category items are studied sequentially, and find that individual differences in this category-specific neural integration during study predict the degree to which a participant will use category information to organize memory search. Finally, we track the deployment of this retrieval cue during memory search: Category-specific patterns are stronger when participants organize their responses according to the category of the studied material. PMID:22875859

Discrete Neural Signatures of Basic Emotions.

PubMed

Saarimäki, Heini; Gotsopoulos, Athanasios; Jääskeläinen, Iiro P; Lampinen, Jouko; Vuilleumier, Patrik; Hari, Riitta; Sams, Mikko; Nummenmaa, Lauri

2016-06-01

Categorical models of emotions posit neurally and physiologically distinct human basic emotions. We tested this assumption by using multivariate pattern analysis (MVPA) to classify brain activity patterns of 6 basic emotions (disgust, fear, happiness, sadness, anger, and surprise) in 3 experiments. Emotions were induced with short movies or mental imagery during functional magnetic resonance imaging. MVPA accurately classified emotions induced by both methods, and the classification generalized from one induction condition to another and across individuals. Brain regions contributing most to the classification accuracy included medial and inferior lateral prefrontal cortices, frontal pole, precentral and postcentral gyri, precuneus, and posterior cingulate cortex. Thus, specific neural signatures across these regions hold representations of different emotional states in multimodal fashion, independently of how the emotions are induced. Similarity of subjective experiences between emotions was associated with similarity of neural patterns for the same emotions, suggesting a direct link between activity in these brain regions and the subjective emotional experience. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Evaluation of Sex-Specific Movement Patterns in Judo Using Probabilistic Neural Networks.

PubMed

Miarka, Bianca; Sterkowicz-Przybycien, Katarzyna; Fukuda, David H

2017-10-01

The purpose of the present study was to create a probabilistic neural network to clarify the understanding of movement patterns in international judo competitions by gender. Analysis of 773 male and 638 female bouts was utilized to identify movements during the approach, gripping, attack (including biomechanical designations), groundwork, defense, and pause phases. Probabilistic neural network and chi-square (χ 2 ) tests modeled and compared frequencies (p ≤ .05). Women (mean [interquartile range]: 9.9 [4; 14]) attacked more than men (7.0 [3; 10]) while attempting a greater number of arm/leg lever (women: 2.7 [1; 6]; men: 4.0 [0; 4]) and trunk/leg lever (women: 0.8 [0; 1]; men: 2.4 [0; 4]) techniques but fewer maximal length-moment arm techniques (women: 0.7 [0; 1]; men: 1.0 [0; 2]). Male athletes displayed one-handed gripping of the back and sleeve, whereas female athletes executed a greater number of groundwork techniques. An optimized probabilistic neural network model, using patterns from the gripping, attack, groundwork, and pause phases, produced an overall prediction accuracy of 76% for discrimination between men and women.

Heterogeneity in perceptual category learning by high functioning children with autism spectrum disorder

PubMed Central

Mercado, Eduardo; Church, Barbara A.; Coutinho, Mariana V. C.; Dovgopoly, Alexander; Lopata, Christopher J.; Toomey, Jennifer A.; Thomeer, Marcus L.

2015-01-01

Previous research suggests that high functioning (HF) children with autism spectrum disorder (ASD) sometimes have problems learning categories, but often appear to perform normally in categorization tasks. The deficits that individuals with ASD show when learning categories have been attributed to executive dysfunction, general deficits in implicit learning, atypical cognitive strategies, or abnormal perceptual biases and abilities. Several of these psychological explanations for category learning deficits have been associated with neural abnormalities such as cortical underconnectivity. The present study evaluated how well existing neurally based theories account for atypical perceptual category learning shown by HF children with ASD across multiple category learning tasks involving novel, abstract shapes. Consistent with earlier results, children’s performances revealed two distinct patterns of learning and generalization associated with ASD: one was indistinguishable from performance in typically developing children; the other revealed dramatic impairments. These two patterns were evident regardless of training regimen or stimulus set. Surprisingly, some children with ASD showed both patterns. Simulations of perceptual category learning could account for the two observed patterns in terms of differences in neural plasticity. However, no current psychological or neural theory adequately explains why a child with ASD might show such large fluctuations in category learning ability across training conditions or stimulus sets. PMID:26157368

A circular model for song motor control in Serinus canaria

PubMed Central

Alonso, Rodrigo G.; Trevisan, Marcos A.; Amador, Ana; Goller, Franz; Mindlin, Gabriel B.

2015-01-01

Song production in songbirds is controlled by a network of nuclei distributed across several brain regions, which drives respiratory and vocal motor systems to generate sound. We built a model for birdsong production, whose variables are the average activities of different neural populations within these nuclei of the song system. We focus on the predictions of respiratory patterns of song, because these can be easily measured and therefore provide a validation for the model. We test the hypothesis that it is possible to construct a model in which (1) the activity of an expiratory related (ER) neural population fits the observed pressure patterns used by canaries during singing, and (2) a higher forebrain neural population, HVC, is sparsely active, simultaneously with significant motor instances of the pressure patterns. We show that in order to achieve these two requirements, the ER neural population needs to receive two inputs: a direct one, and its copy after being processed by other areas of the song system. The model is capable of reproducing the measured respiratory patterns and makes specific predictions on the timing of HVC activity during their production. These results suggest that vocal production is controlled by a circular network rather than by a simple top-down architecture. PMID:25904860

SOX1 links the function of neural patterning and Notch signalling in the ventral spinal cord during the neuron-glial fate switch

DOE Office of Scientific and Technical Information (OSTI.GOV)

Genethliou, Nicholas; Panayiotou, Elena; Department of Biological Sciences, University of Cyprus, P.O. Box 20537, 1678 Nicosia

2009-12-25

During neural development the transition from neurogenesis to gliogenesis, known as the neuron-glial ({Nu}/G) fate switch, requires the coordinated function of patterning factors, pro-glial factors and Notch signalling. How this process is coordinated in the embryonic spinal cord is poorly understood. Here, we demonstrate that during the N/G fate switch in the ventral spinal cord (vSC) SOX1 links the function of neural patterning and Notch signalling. We show that, SOX1 expression in the vSC is regulated by PAX6, NKX2.2 and Notch signalling in a domain-specific manner. We further show that SOX1 regulates the expression of Hes1 and that loss ofmore » Sox1 leads to enhanced production of oligodendrocyte precursors from the pMN. Finally, we show that Notch signalling functions upstream of SOX1 during this fate switch and is independently required for the acquisition of the glial fate perse by regulating Nuclear Factor I A expression in a PAX6/SOX1/HES1/HES5-independent manner. These data integrate functional roles of neural patterning factors, Notch signalling and SOX1 during gliogenesis.« less

Ex vivo determination of chewing patterns using FBG and artificial neural networks

NASA Astrophysics Data System (ADS)

Karam, L. Z.; Pegorini, V.; Pitta, C. S. R.; Assmann, T. S.; Cardoso, R.; Kalinowski, H. J.; Silva, J. C. C.

2014-05-01

This paper reports the experimental procedures performed in a bovine head for the determination of chewing patterns during the mastication process. Mandible movements during the chewing have been simulated either by using two plasticine materials with different textures or without material. Fibre Bragg grating sensors were fixed in the jaw to monitor the biomechanical forces involved in the chewing process. The acquired signals from the sensors fed the input of an artificial neural network aiming at the classification of the measured chewing patterns for each material used in the experiment. The results obtained from the simulation of the chewing process presented different patterns for the different textures of plasticine, resulting on the determination of three chewing patterns with a classification error of 5%.

Predicting variations of perceptual performance across individuals from neural activity using pattern classifiers.

PubMed

Das, Koel; Giesbrecht, Barry; Eckstein, Miguel P

2010-07-15

Within the past decade computational approaches adopted from the field of machine learning have provided neuroscientists with powerful new tools for analyzing neural data. For instance, previous studies have applied pattern classification algorithms to electroencephalography data to predict the category of presented visual stimuli, human observer decision choices and task difficulty. Here, we quantitatively compare the ability of pattern classifiers and three ERP metrics (peak amplitude, mean amplitude, and onset latency of the face-selective N170) to predict variations across individuals' behavioral performance in a difficult perceptual task identifying images of faces and cars embedded in noise. We investigate three different pattern classifiers (Classwise Principal Component Analysis, CPCA; Linear Discriminant Analysis, LDA; and Support Vector Machine, SVM), five training methods differing in the selection of training data sets and three analyses procedures for the ERP measures. We show that all three pattern classifier algorithms surpass traditional ERP measurements in their ability to predict individual differences in performance. Although the differences across pattern classifiers were not large, the CPCA method with training data sets restricted to EEG activity for trials in which observers expressed high confidence about their decisions performed the highest at predicting perceptual performance of observers. We also show that the neural activity predicting the performance across individuals was distributed through time starting at 120ms, and unlike the face-selective ERP response, sustained for more than 400ms after stimulus presentation, indicating that both early and late components contain information correlated with observers' behavioral performance. Together, our results further demonstrate the potential of pattern classifiers compared to more traditional ERP techniques as an analysis tool for modeling spatiotemporal dynamics of the human brain and relating neural activity to behavior. Copyright 2010 Elsevier Inc. All rights reserved.

Unsupervised discrimination of patterns in spiking neural networks with excitatory and inhibitory synaptic plasticity.

PubMed

Srinivasa, Narayan; Cho, Youngkwan

2014-01-01

A spiking neural network model is described for learning to discriminate among spatial patterns in an unsupervised manner. The network anatomy consists of source neurons that are activated by external inputs, a reservoir that resembles a generic cortical layer with an excitatory-inhibitory (EI) network and a sink layer of neurons for readout. Synaptic plasticity in the form of STDP is imposed on all the excitatory and inhibitory synapses at all times. While long-term excitatory STDP enables sparse and efficient learning of the salient features in inputs, inhibitory STDP enables this learning to be stable by establishing a balance between excitatory and inhibitory currents at each neuron in the network. The synaptic weights between source and reservoir neurons form a basis set for the input patterns. The neural trajectories generated in the reservoir due to input stimulation and lateral connections between reservoir neurons can be readout by the sink layer neurons. This activity is used for adaptation of synapses between reservoir and sink layer neurons. A new measure called the discriminability index (DI) is introduced to compute if the network can discriminate between old patterns already presented in an initial training session. The DI is also used to compute if the network adapts to new patterns without losing its ability to discriminate among old patterns. The final outcome is that the network is able to correctly discriminate between all patterns-both old and new. This result holds as long as inhibitory synapses employ STDP to continuously enable current balance in the network. The results suggest a possible direction for future investigation into how spiking neural networks could address the stability-plasticity question despite having continuous synaptic plasticity.

Cross-Modal Multivariate Pattern Analysis

PubMed Central

Meyer, Kaspar; Kaplan, Jonas T.

2011-01-01

Multivariate pattern analysis (MVPA) is an increasingly popular method of analyzing functional magnetic resonance imaging (fMRI) data1-4. Typically, the method is used to identify a subject's perceptual experience from neural activity in certain regions of the brain. For instance, it has been employed to predict the orientation of visual gratings a subject perceives from activity in early visual cortices5 or, analogously, the content of speech from activity in early auditory cortices6. Here, we present an extension of the classical MVPA paradigm, according to which perceptual stimuli are not predicted within, but across sensory systems. Specifically, the method we describe addresses the question of whether stimuli that evoke memory associations in modalities other than the one through which they are presented induce content-specific activity patterns in the sensory cortices of those other modalities. For instance, seeing a muted video clip of a glass vase shattering on the ground automatically triggers in most observers an auditory image of the associated sound; is the experience of this image in the "mind's ear" correlated with a specific neural activity pattern in early auditory cortices? Furthermore, is this activity pattern distinct from the pattern that could be observed if the subject were, instead, watching a video clip of a howling dog? In two previous studies7,8, we were able to predict sound- and touch-implying video clips based on neural activity in early auditory and somatosensory cortices, respectively. Our results are in line with a neuroarchitectural framework proposed by Damasio9,10, according to which the experience of mental images that are based on memories - such as hearing the shattering sound of a vase in the "mind's ear" upon seeing the corresponding video clip - is supported by the re-construction of content-specific neural activity patterns in early sensory cortices. PMID:22105246

Strategy of arm movement control is determined by minimization of neural effort for joint coordination.

PubMed

Dounskaia, Natalia; Shimansky, Yury

2016-06-01

Optimality criteria underlying organization of arm movements are often validated by testing their ability to adequately predict hand trajectories. However, kinematic redundancy of the arm allows production of the same hand trajectory through different joint coordination patterns. We therefore consider movement optimality at the level of joint coordination patterns. A review of studies of multi-joint movement control suggests that a 'trailing' pattern of joint control is consistently observed during which a single ('leading') joint is rotated actively and interaction torque produced by this joint is the primary contributor to the motion of the other ('trailing') joints. A tendency to use the trailing pattern whenever the kinematic redundancy is sufficient and increased utilization of this pattern during skillful movements suggests optimality of the trailing pattern. The goal of this study is to determine the cost function minimization of which predicts the trailing pattern. We show that extensive experimental testing of many known cost functions cannot successfully explain optimality of the trailing pattern. We therefore propose a novel cost function that represents neural effort for joint coordination. That effort is quantified as the cost of neural information processing required for joint coordination. We show that a tendency to reduce this 'neurocomputational' cost predicts the trailing pattern and that the theoretically developed predictions fully agree with the experimental findings on control of multi-joint movements. Implications for future research of the suggested interpretation of the trailing joint control pattern and the theory of joint coordination underlying it are discussed.

The neural architecture of expert calendar calculation: a matter of strategy?

PubMed

Fehr, Thorsten; Wallace, Gregory L; Erhard, Peter; Herrmann, Manfred

2011-08-01

Savants and prodigies are individuals with exceptional skills in particular mental domains. In the present study we used functional magnetic resonance imaging to examine neural correlates of calendar calculation in two individuals, a savant with Asperger's disorder and a self-taught mathematical prodigy. If there is a modular neural organization of exceptional performance in a specific mental domain, calendar calculation should be reflected in a considerable overlap in the recruitment of brain circuits across expert individuals. However, considerable individual differences in activation patterns during calendar calculation were noted. The present results indicate that activation patterns produced by complex mental processing, such as calendar calculation, seem to be influenced strongly by learning history and idiosyncratic strategy usage rather than a modular neural organization. Thus, well-known individual differences in complex cognition play a major role even in experts with exceptional abilities in a particular mental domain and should in particular be considered when examining the neural architecture of complex mental processes and skills.

Multivariate neural biomarkers of emotional states are categorically distinct

PubMed Central

Kragel, Philip A.

2015-01-01

Understanding how emotions are represented neurally is a central aim of affective neuroscience. Despite decades of neuroimaging efforts addressing this question, it remains unclear whether emotions are represented as distinct entities, as predicted by categorical theories, or are constructed from a smaller set of underlying factors, as predicted by dimensional accounts. Here, we capitalize on multivariate statistical approaches and computational modeling to directly evaluate these theoretical perspectives. We elicited discrete emotional states using music and films during functional magnetic resonance imaging scanning. Distinct patterns of neural activation predicted the emotion category of stimuli and tracked subjective experience. Bayesian model comparison revealed that combining dimensional and categorical models of emotion best characterized the information content of activation patterns. Surprisingly, categorical and dimensional aspects of emotion experience captured unique and opposing sources of neural information. These results indicate that diverse emotional states are poorly differentiated by simple models of valence and arousal, and that activity within separable neural systems can be mapped to unique emotion categories. PMID:25813790

Semantic representation in the white matter pathway

PubMed Central

Fang, Yuxing; Wang, Xiaosha; Zhong, Suyu; Song, Luping; Han, Zaizhu; Gong, Gaolang

2018-01-01

Object conceptual processing has been localized to distributed cortical regions that represent specific attributes. A challenging question is how object semantic space is formed. We tested a novel framework of representing semantic space in the pattern of white matter (WM) connections by extending the representational similarity analysis (RSA) to structural lesion pattern and behavioral data in 80 brain-damaged patients. For each WM connection, a neural representational dissimilarity matrix (RDM) was computed by first building machine-learning models with the voxel-wise WM lesion patterns as features to predict naming performance of a particular item and then computing the correlation between the predicted naming score and the actual naming score of another item in the testing patients. This correlation was used to build the neural RDM based on the assumption that if the connection pattern contains certain aspects of information shared by the naming processes of these two items, models trained with one item should also predict naming accuracy of the other. Correlating the neural RDM with various cognitive RDMs revealed that neural patterns in several WM connections that connect left occipital/middle temporal regions and anterior temporal regions associated with the object semantic space. Such associations were not attributable to modality-specific attributes (shape, manipulation, color, and motion), to peripheral picture-naming processes (picture visual similarity, phonological similarity), to broad semantic categories, or to the properties of the cortical regions that they connected, which tended to represent multiple modality-specific attributes. That is, the semantic space could be represented through WM connection patterns across cortical regions representing modality-specific attributes. PMID:29624578

msh/Msx gene family in neural development.

PubMed

Ramos, Casto; Robert, Benoît

2005-11-01

The involvement of Msx homeobox genes in skull and tooth formation has received a great deal of attention. Recent studies also indicate a role for the msh/Msx gene family in development of the nervous system. In this article, we discuss the functions of these transcription factors in neural-tissue organogenesis. We will deal mainly with the interactions of the Drosophila muscle segment homeobox (msh) gene with other homeobox genes and the repressive cascade that leads to neuroectoderm patterning; the role of Msx genes in neural-crest induction, focusing especially on the differences between lower and higher vertebrates; their implication in patterning of the vertebrate neural tube, particularly in diencephalon midline formation. Finally, we will examine the distinct activities of Msx1, Msx2 and Msx3 genes during neurogenesis, taking into account their relationships with signalling molecules such as BMP.

Cortical activity patterns predict robust speech discrimination ability in noise

PubMed Central

Shetake, Jai A.; Wolf, Jordan T.; Cheung, Ryan J.; Engineer, Crystal T.; Ram, Satyananda K.; Kilgard, Michael P.

2012-01-01

The neural mechanisms that support speech discrimination in noisy conditions are poorly understood. In quiet conditions, spike timing information appears to be used in the discrimination of speech sounds. In this study, we evaluated the hypothesis that spike timing is also used to distinguish between speech sounds in noisy conditions that significantly degrade neural responses to speech sounds. We tested speech sound discrimination in rats and recorded primary auditory cortex (A1) responses to speech sounds in background noise of different intensities and spectral compositions. Our behavioral results indicate that rats, like humans, are able to accurately discriminate consonant sounds even in the presence of background noise that is as loud as the speech signal. Our neural recordings confirm that speech sounds evoke degraded but detectable responses in noise. Finally, we developed a novel neural classifier that mimics behavioral discrimination. The classifier discriminates between speech sounds by comparing the A1 spatiotemporal activity patterns evoked on single trials with the average spatiotemporal patterns evoked by known sounds. Unlike classifiers in most previous studies, this classifier is not provided with the stimulus onset time. Neural activity analyzed with the use of relative spike timing was well correlated with behavioral speech discrimination in quiet and in noise. Spike timing information integrated over longer intervals was required to accurately predict rat behavioral speech discrimination in noisy conditions. The similarity of neural and behavioral discrimination of speech in noise suggests that humans and rats may employ similar brain mechanisms to solve this problem. PMID:22098331

DIGESTIVE BIOAVAILABILITY TO A DEPOSIT FEDDER (ARENICOLA MARINA) OF POLYCYCLIC AROMATIC HYDROCARBONS ASSOCIATED WITH ANTHRPOGENIC PARTICLES

EPA Science Inventory

Marine sediments around urban areas serve as catch basins for anthropogenic particles containing polycyclic aromatic hydrocarbons (PAHs). Using incubations with gut fluids extracted from a deposit-feeding polychaete (Arenicola marina), we determined the digestive bioavailability ...

"Binaural Rivalry": Dichotic Listening as a Tool for the Investigation of the Neural Correlate of Consciousness

ERIC Educational Resources Information Center

Brancucci, Alfredo; Tommasi, Luca

2011-01-01

Since about two decades neuroscientists have systematically faced the problem of consciousness: the aim is to discover the neural activity specifically related to conscious perceptions, i.e. the biological properties of what philosophers call qualia. In this view, a neural correlate of consciousness (NCC) is a precise pattern of brain activity…

Blood flukes Cardicola parvus and C. laruei (Trematoda: Aporocotylidae): life cycles and cryptic infection in spotted seatrout, Cynoscion nebulosus (Teleost: Sciaenidae).

PubMed

Siegel, Sasha V; Rivero, Andrea V; Oberstaller, Jenna; Colon, Beatrice L; de Buron, Isaure; Kyle, Dennis E

2018-04-01

Aporocotylidae comprises a diverse family of fish blood flukes, with adults found in blood or body cavity of marine, brackish, or freshwater fish. Aporocotylids are unique among the Digenea with many developing in polychaetes. The life cycle has been elucidated for only a few species that develop in polychaetes from marine/brackish environments and none for western Atlantic aporocotylids. The basis for this study was observations of blood fluke larvae in annelids from South Carolina, USA in 1982 prior to possible usage of molecular tools to specifically identify parasite larvae. Recent description of aporocotylid species and genotyping tools prompted revisiting original collection sites to examine polychaetes and fish as potential hosts. Polycirrid Enoplobranchus sanguineus and terebellids Amphitrite ornata, and Terebella lapidaria revealed infections with aporocotylid larvae. Adult blood flukes were also collected from fish commonly encountered in the same habitat: spotted seatrout (Cynoscion nebulosus), red drum (Sciaenops ocellatus), black drum (Pogonias cromis), and Atlantic croaker (Micropogonias undulatus). Sporocysts containing cercariae were found in individuals of each annelid species. Adult Cardicola parvus were found in spotted seatrout and Atlantic croaker, C. laruei in spotted seatrout, C. currani in red drum, and C. palmeri in black drum. Genotype analysis of ITS-2 and lsrDNA of all forms confirmed conspecific infections by C. parvus in E. sanguineus and A. ornata and C. laruei in T. lapidaria. This is the first description of complete life cycles of aporocotylids in the Western Atlantic and first evidence of cryptic infections of Cy. nebulosus with C. parvus. Copyright © 2017 Elsevier B.V. All rights reserved.

Estuarine resources use by juvenile Flagfin mojarra ( Eucinostomus melanopterus) in an inverse tropical estuary (Sine Saloum, Senegal)

NASA Astrophysics Data System (ADS)

Gning, Ndombour; Le Loc'h, François; Thiaw, Omar T.; Aliaume, Catherine; Vidy, Guy

2010-03-01

The Flagfin mojarra, Eucinostomus melanopterus, is a marine spawner whose young individuals are common in the Sine Saloum inverse estuary (Senegal). The species offers the opportunity to study both the use of the estuarine nursery resources and the impact of the particular environment of the inverse estuary on these resources. This will lead to a better understanding of the functioning of the nursery. We investigated the resources used by juvenile Flagfin mojarra by coupling stomach contents and stable isotopes methods. Young Flagfin mojarra feed on a wide range of invertebrates. Diet changed from copepods in the smallest size class (10-40 mm), to a range of invertebrates including amphipods, insect larvae, polychaetes and mollusc in the medium size class (up to 60 mm) and mainly polychaetes for individuals >60 mm in size. In mangrove habitats with moderate salinity, the diet was dominated by polychaetes and decapod larvae (crabs) whereas in habitats with higher salinity, diet was dominated by amphipods. In very hypersaline areas with scarce mangroves, diet comprised benthic copepods, chironomid larvae and ostracods. This agreed with a clear change in δ13C measured in fish sampled at downstream or upstream sites. Comparison with signatures of primary producers suggested that the local food web exploited by young Flagfin mojarra is mainly based on phytoplankton in the downstream mangrove area, and mainly on benthic microalgae in the upstream hypersaline area. As in many studies considering the food webs in mangrove, mangrove was not identified as a major contributor to the food web exploited by E. melanopterus. This needs further investigation particularly because the exportation of estuarine materials to the sea is limited in an inverse estuary.

Freshwater polychaetes (Manayunkia speciosa) near the Detroit River, western Lake Erie: Abundance and life‐history characteristics

USGS Publications Warehouse

Schloesser, Donald W.; Malakauskas, David M.; Malakauskas, Sarah J.

2016-01-01

Freshwater polychaetes are relatively rare and little-studied members of the benthos of lakes and rivers. We studied one polychaete species (Manayunkia speciosa) in Lake Erie near the mouth of the Detroit River. Abundances at one site were determined between 1961 and 2013 and life‐history characteristics at two sites were determined seasonally (March–November) in 2009–2010 and 2012–2013. Life‐history characteristics included abundances, length‐frequency distributions, presence/absence of constructed tubes, sexual maturity, and number and maturation of young of year (YOY) in tubes. Long-term abundances decreased in successive time periods between 1961 and 2003 (mean range = 57,570 to 2583/m2) but few changes occurred between 2003 and 2013 (mean = 5007/m2; range/y = 2355–8216/m2). Seasonal abundances varied substantially between sites and years, but overall, abundances were low in March–April, high in May–August, and low in September–November. Although reproduction was continuous throughout warmer months, en masse recruitment, as revealed by length–frequency distributions, occurred in a brief period late‐June to mid-July, and possibly in early-September. All life history characteristics, including tube construction, were dependent on water temperatures (> 5 °C in spring and < 15 °C in fall). These results generally agree with and complement laboratory studies of M. speciosa in the Pacific Northwest where M. speciosa hosts parasites that cause substantial fish mortalities. Although abundance ofM. speciosa near the mouth of the Detroit River was 33-fold lower in 2013 than it was in 1961, this population has persisted for five decades and, therefore, has the potential to harbor parasites that may cause fish mortalities in the Great Lakes.

Eiders Somateria mollissima scavenging behind a lugworm boat

NASA Astrophysics Data System (ADS)

Leopold, Mardik F.

2002-02-01

The eider is one of the most important molluscivorous birds in the Wadden Sea, where it feeds mainly on blue mussels Mytilus edulis and edible cockles Cerastoderma edule. These prey species are within reach of the birds at all times. Other potential prey of suitable size that are abundantly present, such as several polychaete worms, or the clam Mya arenaria, are taken to a much lesser extent, possibly because they live buried in the sediment and digging them out would take too much effort. Mya may pose another problem because they grow to sizes that prevent eiders from swallowing them. Large Mya also live too deep down in the sediment, but young (small) specimens should be available to eiders. Yet, even these have only rarely been found as prey in eiders in the Wadden Sea. However, diet studies in relation to food abundance have been few, and may have missed prey that do not leave large shell fragments (i.e. in faeces studies). This paper describes observations on eiders taking both Mya and polychaete worms. The eiders fed on these prey in a fashion reminiscent of gulls that scavenge behind fishing vessels: some eiders have learnt to follow professional worm-digging boats that supply a bycatch of molluscs (mainly Mya arenaria) and polychaete worms (mainly Arenicola marina and Nephtys hombergii) .Mya and worms were also the main targets of the eiders that fed in a dense flock close to the boat's stern. Faeces found on the flats at low tide comprised mainly cockle shell fragments, a prey rarely taken by the eiders behind the boat. Faeces studies may thus give a highly biased impression of local eider diet.

Biodiversity and distribution of polynoid and spionid polychaetes (Annelida) in the Vema Fracture Zone, tropical North Atlantic

NASA Astrophysics Data System (ADS)

Guggolz, Theresa; Lins, Lidia; Meißner, Karin; Brandt, Angelika

2018-02-01

During the Vema-TRANSIT (Bathymetry of the Vema-Fracture Zone and Puerto Rico TRench and Abyssal AtlaNtic BiodiverSITy Study) expedition from December, 2014 to January, 2015, a transect along the Vema Fracture Zone in the equatorial Atlantic was surveyed and sampled at about 10°N. The Vema Fracture Zone is one of the largest fracture zones of the Mid-Atlantic Ridge and it is characterized by a large left-lateral offset. Benthic communities of the transect and the abyssal basins on both sides were investigated to examine whether the Mid-Atlantic Ridge serves as a physical barrier for these organisms, or if there is a potential connection from east to west via the Vema Fracture Zone. Samples comprised 4149 polychaetes, belonging to 42 families. Exemplary, Polynoidae and Spionidae, both typical deep-sea families with high abundances in all investigated regions, were identified up to species level. The present results show significant differences in polychaete faunistic composition between both sides of the Mid-Atlantic Ridge. Moreover, the eastern and western Vema Fracture Zone characterizes divergent habitats, since the two basins differ in sedimentology and environmental variables (e.g. temperature, salinity), hence characterizing divergent habitats. Most species found were restricted to either eastern or western VFZ, but there was a trans-Mid-Atlantic Ridge distribution of certain abundant species observed, indicating that the Mid-Atlantic Ridge might rather act limiting to dispersal between ocean basins than as an absolute barrier. Given the abyssal valley formed by the Vema Fracture Zone and its role in oceanic currents, this seafloor feature may well represent exchange routes between eastern and western faunas.

Morphological distinction between estuarine polychaetes: Laeonereis culveri and L. nota (Phyllodocida: Nereididae).

PubMed

de Jesus-Flores, Citlalli; Salazar-González, S Alejandro; Salazar-Vallejo, Sergio I

2016-03-01

The family Nereididae includes more than 500 polychaete species described worldwide, and includes species common in many benthic environments, but some other species may tolerate freshwater or can even thrive in humid substrates in tropical forests. In estuarine environments, nereidid polychaetes can be abundant and relevant as a food source for resident or migratory birds. Laeonereis culveri (Webster, 1879) is a common estuarine species found in tropical and subtropical Atlantic American shores and was described from New Jersey; its median and posterior parapodia have upper notopodial ligules usually longer than the lower ones, and the latter are parallel to the notaciculae throughout the body. L. culveri distribution is from Connecticut to central Argentina; however, this wide distribution might be due to the inclusion of several other species as junior synonyms, despite that some morphological differences were found between them. One of such species is L. nota (Treadwell, 1941), that was described from Texas; its parapodia have notopodial ligules of about the same size, and the lower ones are oblique to the notaciculae. In order to clarify the differences between these two species, and to define which inhabits the Northwestern Caribbean region, topotype materials from these two species and specimens from Chetumal Bay were collected, and their morphological features were compared. Our results indicated that L. culveri and L. nota are different species and that the latter is found in Chetumal Bay. On the basis of mature specimens, L. culveri is hereby restricted to the Northern Gulf of Mexico and Northwestern Atlantic Ocean, and L. nota are reinstated and its distribution extends from Texas, in the Gulf of Mexico to Chetumal Bay, in the Northwestern Caribbean Sea. A key to identify all species in Laeonereis Hartman (1945) is also included.

A connectionist model of category learning by individuals with high-functioning autism spectrum disorder.

PubMed

Dovgopoly, Alexander; Mercado, Eduardo

2013-06-01

Individuals with autism spectrum disorder (ASD) show atypical patterns of learning and generalization. We explored the possible impacts of autism-related neural abnormalities on perceptual category learning using a neural network model of visual cortical processing. When applied to experiments in which children or adults were trained to classify complex two-dimensional images, the model can account for atypical patterns of perceptual generalization. This is only possible, however, when individual differences in learning are taken into account. In particular, analyses performed with a self-organizing map suggested that individuals with high-functioning ASD show two distinct generalization patterns: one that is comparable to typical patterns, and a second in which there is almost no generalization. The model leads to novel predictions about how individuals will generalize when trained with simplified input sets and can explain why some researchers have failed to detect learning or generalization deficits in prior studies of category learning by individuals with autism. On the basis of these simulations, we propose that deficits in basic neural plasticity mechanisms may be sufficient to account for the atypical patterns of perceptual category learning and generalization associated with autism, but they do not account for why only a subset of individuals with autism would show such deficits. If variations in performance across subgroups reflect heterogeneous neural abnormalities, then future behavioral and neuroimaging studies of individuals with ASD will need to account for such disparities.

Reference ability neural networks and behavioral performance across the adult life span.

PubMed

Habeck, Christian; Eich, Teal; Razlighi, Ray; Gazes, Yunglin; Stern, Yaakov

2018-05-15

To better understand the impact of aging, along with other demographic and brain health variables, on the neural networks that support different aspects of cognitive performance, we applied a brute-force search technique based on Principal Components Analysis to derive 4 corresponding spatial covariance patterns (termed Reference Ability Neural Networks -RANNs) from a large sample of participants across the age range. 255 clinically healthy, community-dwelling adults, aged 20-77, underwent fMRI while performing 12 tasks, 3 tasks for each of the following cognitive reference abilities: Episodic Memory, Reasoning, Perceptual Speed, and Vocabulary. The derived RANNs (1) showed selective activation to their specific cognitive domain and (2) correlated with behavioral performance. Quasi out-of-sample replication with Monte-Carlo 5-fold cross validation was built into our approach, and all patterns indicated their corresponding reference ability and predicted performance in held-out data to a degree significantly greater than chance level. RANN-pattern expression for Episodic Memory, Reasoning and Vocabulary were associated selectively with age, while the pattern for Perceptual Speed showed no such age-related influences. For each participant we also looked at residual activity unaccounted for by the RANN-pattern derived for the cognitive reference ability. Higher residual activity was associated with poorer brain-structural health and older age, but -apart from Vocabulary-not with cognitive performance, indicating that older participants with worse brain-structural health might recruit alternative neural resources to maintain performance levels. Copyright © 2018 Elsevier Inc. All rights reserved.

Planar induction of anteroposterior pattern in the developing central nervous system of Xenopus laevis

NASA Technical Reports Server (NTRS)

Doniach, T.; Phillips, C. R.; Gerhart, J. C.

1992-01-01

It has long been thought that anteroposterior (A-P) pattern in the vertebrate central nervous system is induced in the embryo's dorsal ectoderm exclusively by signals passing vertically from underlying, patterned dorsal mesoderm. Explants from early gastrulae of the frog Xenopus laevis were prepared in which vertical contact between dorsal ectoderm and mesoderm was prevented but planar contact was maintained. In these, four position-specific neural markers (engrailed-2, Krox-20, XlHbox 1, and XlHbox 6) were expressed in the ectoderm in the same A-P order as in the embryo. Thus, planar signals alone, following a path available in the normal embryo, can induce A-P neural pattern.

Using c-Jun to identify fear extinction learning-specific patterns of neural activity that are affected by single prolonged stress.

PubMed

Knox, Dayan; Stanfield, Briana R; Staib, Jennifer M; David, Nina P; DePietro, Thomas; Chamness, Marisa; Schneider, Elizabeth K; Keller, Samantha M; Lawless, Caroline

2018-04-02

Neural circuits via which stress leads to disruptions in fear extinction is often explored in animal stress models. Using the single prolonged stress (SPS) model of post traumatic stress disorder and the immediate early gene (IEG) c-Fos as a measure of neural activity, we previously identified patterns of neural activity through which SPS disrupts extinction retention. However, none of these stress effects were specific to fear or extinction learning and memory. C-Jun is another IEG that is sometimes regulated in a different manner to c-Fos and could be used to identify emotional learning/memory specific patterns of neural activity that are sensitive to SPS. Animals were either fear conditioned (CS-fear) or presented with CSs only (CS-only) then subjected to extinction training and testing. C-Jun was then assayed within neural substrates critical for extinction memory. Inhibited c-Jun levels in the hippocampus (Hipp) and enhanced functional connectivity between the ventromedial prefrontal cortex (vmPFC) and basolateral amygdala (BLA) during extinction training was disrupted by SPS in the CS-fear group only. As a result, these effects were specific to emotional learning/memory. SPS also disrupted inhibited Hipp c-Jun levels, enhanced BLA c-Jun levels, and altered functional connectivity among the vmPFC, BLA, and Hipp during extinction testing in SPS rats in the CS-fear and CS-only groups. As a result, these effects were not specific to emotional learning/memory. Our findings suggest that SPS disrupts neural activity specific to extinction memory, but may also disrupt the retention of fear extinction by mechanisms that do not involve emotional learning/memory. Copyright © 2017 Elsevier B.V. All rights reserved.

Different propagation speeds of recalled sequences in plastic spiking neural networks

NASA Astrophysics Data System (ADS)

Huang, Xuhui; Zheng, Zhigang; Hu, Gang; Wu, Si; Rasch, Malte J.

2015-03-01

Neural networks can generate spatiotemporal patterns of spike activity. Sequential activity learning and retrieval have been observed in many brain areas, and e.g. is crucial for coding of episodic memory in the hippocampus or generating temporal patterns during song production in birds. In a recent study, a sequential activity pattern was directly entrained onto the neural activity of the primary visual cortex (V1) of rats and subsequently successfully recalled by a local and transient trigger. It was observed that the speed of activity propagation in coordinates of the retinotopically organized neural tissue was constant during retrieval regardless how the speed of light stimulation sweeping across the visual field during training was varied. It is well known that spike-timing dependent plasticity (STDP) is a potential mechanism for embedding temporal sequences into neural network activity. How training and retrieval speeds relate to each other and how network and learning parameters influence retrieval speeds, however, is not well described. We here theoretically analyze sequential activity learning and retrieval in a recurrent neural network with realistic synaptic short-term dynamics and STDP. Testing multiple STDP rules, we confirm that sequence learning can be achieved by STDP. However, we found that a multiplicative nearest-neighbor (NN) weight update rule generated weight distributions and recall activities that best matched the experiments in V1. Using network simulations and mean-field analysis, we further investigated the learning mechanisms and the influence of network parameters on recall speeds. Our analysis suggests that a multiplicative STDP rule with dominant NN spike interaction might be implemented in V1 since recall speed was almost constant in an NMDA-dominant regime. Interestingly, in an AMPA-dominant regime, neural circuits might exhibit recall speeds that instead follow the change in stimulus speeds. This prediction could be tested in experiments.

CNN: a speaker recognition system using a cascaded neural network.

PubMed

Zaki, M; Ghalwash, A; Elkouny, A A

1996-05-01

The main emphasis of this paper is to present an approach for combining supervised and unsupervised neural network models to the issue of speaker recognition. To enhance the overall operation and performance of recognition, the proposed strategy integrates the two techniques, forming one global model called the cascaded model. We first present a simple conventional technique based on the distance measured between a test vector and a reference vector for different speakers in the population. This particular distance metric has the property of weighting down the components in those directions along which the intraspeaker variance is large. The reason for presenting this method is to clarify the discrepancy in performance between the conventional and neural network approach. We then introduce the idea of using unsupervised learning technique, presented by the winner-take-all model, as a means of recognition. Due to several tests that have been conducted and in order to enhance the performance of this model, dealing with noisy patterns, we have preceded it with a supervised learning model--the pattern association model--which acts as a filtration stage. This work includes both the design and implementation of both conventional and neural network approaches to recognize the speakers templates--which are introduced to the system via a voice master card and preprocessed before extracting the features used in the recognition. The conclusion indicates that the system performance in case of neural network is better than that of the conventional one, achieving a smooth degradation in respect of noisy patterns, and higher performance in respect of noise-free patterns.

Identifying bilingual semantic neural representations across languages

PubMed Central

Buchweitz, Augusto; Shinkareva, Svetlana V.; Mason, Robert A.; Mitchell, Tom M.; Just, Marcel Adam

2015-01-01

The goal of the study was to identify the neural representation of a noun's meaning in one language based on the neural representation of that same noun in another language. Machine learning methods were used to train classifiers to identify which individual noun bilingual participants were thinking about in one language based solely on their brain activation in the other language. The study shows reliable (p < .05) pattern-based classification accuracies for the classification of brain activity for nouns across languages. It also shows that the stable voxels used to classify the brain activation were located in areas associated with encoding information about semantic dimensions of the words in the study. The identification of the semantic trace of individual nouns from the pattern of cortical activity demonstrates the existence of a multi-voxel pattern of activation across the cortex for a single noun common to both languages in bilinguals. PMID:21978845

Human brain networks function in connectome-specific harmonic waves.

PubMed

Atasoy, Selen; Donnelly, Isaac; Pearson, Joel

2016-01-21

A key characteristic of human brain activity is coherent, spatially distributed oscillations forming behaviour-dependent brain networks. However, a fundamental principle underlying these networks remains unknown. Here we report that functional networks of the human brain are predicted by harmonic patterns, ubiquitous throughout nature, steered by the anatomy of the human cerebral cortex, the human connectome. We introduce a new technique extending the Fourier basis to the human connectome. In this new frequency-specific representation of cortical activity, that we call 'connectome harmonics', oscillatory networks of the human brain at rest match harmonic wave patterns of certain frequencies. We demonstrate a neural mechanism behind the self-organization of connectome harmonics with a continuous neural field model of excitatory-inhibitory interactions on the connectome. Remarkably, the critical relation between the neural field patterns and the delicate excitation-inhibition balance fits the neurophysiological changes observed during the loss and recovery of consciousness.

Structural qualia: a solution to the hard problem of consciousness.

PubMed

Loorits, Kristjan

2014-01-01

The hard problem of consciousness has been often claimed to be unsolvable by the methods of traditional empirical sciences. It has been argued that all the objects of empirical sciences can be fully analyzed in structural terms but that consciousness is (or has) something over and above its structure. However, modern neuroscience has introduced a theoretical framework in which also the apparently non-structural aspects of consciousness, namely the so called qualia or qualitative properties, can be analyzed in structural terms. That framework allows us to see qualia as something compositional with internal structures that fully determine their qualitative nature. Moreover, those internal structures can be identified which certain neural patterns. Thus consciousness as a whole can be seen as a complex neural pattern that misperceives some of its own highly complex structural properties as monadic and qualitative. Such neural pattern is analyzable in fully structural terms and thereby the hard problem is solved.

Structural qualia: a solution to the hard problem of consciousness

PubMed Central

Loorits, Kristjan

2014-01-01

The hard problem of consciousness has been often claimed to be unsolvable by the methods of traditional empirical sciences. It has been argued that all the objects of empirical sciences can be fully analyzed in structural terms but that consciousness is (or has) something over and above its structure. However, modern neuroscience has introduced a theoretical framework in which also the apparently non-structural aspects of consciousness, namely the so called qualia or qualitative properties, can be analyzed in structural terms. That framework allows us to see qualia as something compositional with internal structures that fully determine their qualitative nature. Moreover, those internal structures can be identified which certain neural patterns. Thus consciousness as a whole can be seen as a complex neural pattern that misperceives some of its own highly complex structural properties as monadic and qualitative. Such neural pattern is analyzable in fully structural terms and thereby the hard problem is solved. PMID:24672510

Visual Circuit Development Requires Patterned Activity Mediated by Retinal Acetylcholine Receptors

PubMed Central

Burbridge, Timothy J.; Xu, Hong-Ping; Ackman, James B.; Ge, Xinxin; Zhang, Yueyi; Ye, Mei-Jun; Zhou, Z. Jimmy; Xu, Jian; Contractor, Anis; Crair, Michael C.

2014-01-01

SUMMARY The elaboration of nascent synaptic connections into highly ordered neural circuits is an integral feature of the developing vertebrate nervous system. In sensory systems, patterned spontaneous activity before the onset of sensation is thought to influence this process, but this conclusion remains controversial largely due to the inherent difficulty recording neural activity in early development. Here, we describe novel genetic and pharmacological manipulations of spontaneous retinal activity, assayed in vivo, that demonstrate a causal link between retinal waves and visual circuit refinement. We also report a de-coupling of downstream activity in retinorecipient regions of the developing brain after retinal wave disruption. Significantly, we show that the spatiotemporal characteristics of retinal waves affect the development of specific visual circuits. These results conclusively establish retinal waves as necessary and instructive for circuit refinement in the developing nervous system and reveal how neural circuits adjust to altered patterns of activity prior to experience. PMID:25466916

Self-regulation via neural simulation

PubMed Central

Gilead, Michael; Boccagno, Chelsea; Silverman, Melanie; Hassin, Ran R.; Weber, Jochen; Ochsner, Kevin N.

2016-01-01

Can taking the perspective of other people modify our own affective responses to stimuli? To address this question, we examined the neurobiological mechanisms supporting the ability to take another person’s perspective and thereby emotionally experience the world as they would. We measured participants’ neural activity as they attempted to predict the emotional responses of two individuals that differed in terms of their proneness to experience negative affect. Results showed that behavioral and neural signatures of negative affect (amygdala activity and a distributed multivoxel pattern reflecting affective negativity) simulated the presumed affective state of the target person. Furthermore, the anterior medial prefrontal cortex (mPFC)—a region implicated in mental state inference—exhibited a perspective-dependent pattern of connectivity with the amygdala, and the multivoxel pattern of activity within the mPFC differentiated between the two targets. We discuss the implications of these findings for research on perspective-taking and self-regulation. PMID:27551094

Clonal and molecular analysis of the prospective anterior neural boundary in the mouse embryo

PubMed Central

Cajal, Marieke; Lawson, Kirstie A.; Hill, Bill; Moreau, Anne; Rao, Jianguo; Ross, Allyson; Collignon, Jérôme; Camus, Anne

2012-01-01

In the mouse embryo the anterior ectoderm undergoes extensive growth and morphogenesis to form the forebrain and cephalic non-neural ectoderm. We traced descendants of single ectoderm cells to study cell fate choice and cell behaviour at late gastrulation. In addition, we provide a comprehensive spatiotemporal atlas of anterior gene expression at stages crucial for anterior ectoderm regionalisation and neural plate formation. Our results show that, at late gastrulation stage, expression patterns of anterior ectoderm genes overlap significantly and correlate with areas of distinct prospective fates but do not define lineages. The fate map delineates a rostral limit to forebrain contribution. However, no early subdivision of the presumptive forebrain territory can be detected. Lineage analysis at single-cell resolution revealed that precursors of the anterior neural ridge (ANR), a signalling centre involved in forebrain development and patterning, are clonally related to neural ectoderm. The prospective ANR and the forebrain neuroectoderm arise from cells scattered within the same broad area of anterior ectoderm. This study establishes that although the segregation between non-neural and neural precursors in the anterior midline ectoderm is not complete at late gastrulation stage, this tissue already harbours elements of regionalisation that prefigure the later organisation of the head. PMID:22186731

Global neural pattern similarity as a common basis for categorization and recognition memory.

PubMed

Davis, Tyler; Xue, Gui; Love, Bradley C; Preston, Alison R; Poldrack, Russell A

2014-05-28

Familiarity, or memory strength, is a central construct in models of cognition. In previous categorization and long-term memory research, correlations have been found between psychological measures of memory strength and activation in the medial temporal lobes (MTLs), which suggests a common neural locus for memory strength. However, activation alone is insufficient for determining whether the same mechanisms underlie neural function across domains. Guided by mathematical models of categorization and long-term memory, we develop a theory and a method to test whether memory strength arises from the global similarity among neural representations. In human subjects, we find significant correlations between global similarity among activation patterns in the MTLs and both subsequent memory confidence in a recognition memory task and model-based measures of memory strength in a category learning task. Our work bridges formal cognitive theories and neuroscientific models by illustrating that the same global similarity computations underlie processing in multiple cognitive domains. Moreover, by establishing a link between neural similarity and psychological memory strength, our findings suggest that there may be an isomorphism between psychological and neural representational spaces that can be exploited to test cognitive theories at both the neural and behavioral levels. Copyright © 2014 the authors 0270-6474/14/347472-13$15.00/0.

Size matters: The contribution of mega-infauna to the food webs and ecosystem services of an Oregon estuary - ESA

EPA Science Inventory

Background/Questions/Methods Large-bodied invertebrates (bivalves, polychaetes, burrowing shrimps) are common to infaunal communities of NE Pacific estuaries, but their contribution to estuarine community structure, function and ecosystem services is poorly understood because ...

NATURAL HALOGENATED ORGANIC COMPOUNDS IN MARINE SEDIMENTS ARE FROM POLYCHAETE INDICATOR SPECIES. (R824776)

EPA Science Inventory

The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...

HALOGENATED METABOLITES IN TWO MARINE POLYCHAETES AND THEIR PLANKTOTROPHIC AND LECITHOTROPHIC LARVAE. (R824776)

EPA Science Inventory

The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...

Allantoinase in the marine polychaete Eudistylia vancouveri

USGS Publications Warehouse

Passino, Dora R.M.; Brown, G.W.

1976-01-01

Allantoinase, an enzyme in the purine-urea cycle, was found in Eudistylia vancouveri (Polychaeta). The enzyme had a pH optimum at 7.6. The Km was 0.012 M allantoin, and the Arrhenius energy of activation was 12.6 to 14.6 kcal/mol.

Ingestion and transfer of microplastics in the planktonic food web.

PubMed

Setälä, Outi; Fleming-Lehtinen, Vivi; Lehtiniemi, Maiju

2014-02-01

Experiments were carried out with different Baltic Sea zooplankton taxa to scan their potential to ingest plastics. Mysid shrimps, copepods, cladocerans, rotifers, polychaete larvae and ciliates were exposed to 10 μm fluorescent polystyrene microspheres. These experiments showed ingestion of microspheres in all taxa studied. The highest percentage of individuals with ingested spheres was found in pelagic polychaete larvae, Marenzelleria spp. Experiments with the copepod Eurytemora affinis and the mysid shrimp Neomysis integer showed egestion of microspheres within 12 h. Food web transfer experiments were done by offering zooplankton labelled with ingested microspheres to mysid shrimps. Microscopy observations of mysid intestine showed the presence of zooplankton prey and microspheres after 3 h incubation. This study shows for the first time the potential of plastic microparticle transfer via planktonic organisms from one trophic level (mesozooplankton) to a higher level (macrozooplankton). The impacts of plastic transfer and possible accumulation in the food web need further investigations. Copyright © 2013 Elsevier Ltd. All rights reserved.

Redescriptions of Nereis oligohalina (Rioja, 1946) and N. garwoodi González-Escalante & Salazar-Vallejo, 2003 and description of N. confusa sp. n. (Annelida, Nereididae).

PubMed

Conde-Vela, Víctor M; Salazar-Vallejo, Sergio I

2015-01-01

Type material of several polychaete species described by Enrique Rioja from Mexican coasts are lost, and the current status of some species is doubtful. Nereis oligohalina (Rioja, 1946) was described from the Gulf of Mexico, but it has been considered a junior synonym of Nereis occidentalis Hartman, 1945, or regarded as a distinct species with an amphiamerican distribution. On the other hand, Nereis garwoodi González-Escalante & Salazar-Vallejo, 2003, described from Chetumal Bay, Caribbean coasts, could be confused with Nereis oligohalina. In order to clarify these uncertainties, Nereis oligohalina is redescribed based on specimens from the Mexican Gulf of Mexico, including a proposed neotype; further, Nereis garwoodi is redescribed including the selection of lectotype and paralectotypes, and Nereis confusa sp. n. is described with material from the Gulf of California. A key for the identification of similar species and some comments about speciation in nereidid polychaetes are also included.

Linking genotoxic responses and reproductive success in ecotoxicology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Anderson, S.L.; Wild, G.C.

1994-12-01

The potential of genotoxicity biomarkers as predictors of detrimental environmental effects, such as altered reproductive success of wild organisms, must be rigorously determined. Recent research to evaluate relationships between genotoxic responses and indicators of reproductive success in model animals is described from an ecotoxicological perspective. Genotoxicity can be correlated with reproductive effects such as gamete loss due to cell death; embryonic mortality; and heritable mutations in a range of model animals including polychaete worms, nematodes, sea urchins, amphibians, and fish. In preliminary studies, the polychaete worm, Neanthes arenaceodentata, and the nematode, Caenorhabditis elegans, have also shown the potential for cumulativemore » DNA damage in gametes. If DNA repair capacity is limited in gametes, then selected life history traits such as long and synchronous periods of gametogenesis may confer vulnerability to genotoxic substances in chronic exposures. Recommendations for future research include strategic development of animal models that can be used to elucidate multiple mechanisms of effect (multiend point) at varying levels of biological organization (multilevel). 27 refs., 2 tabs.« less

Bacteria associated with sabellids (Polychaeta: Annelida) as a novel source of surface active compounds.

PubMed

Rizzo, Carmen; Michaud, Luigi; Hörmann, Barbara; Gerçe, Berna; Syldatk, Christoph; Hausmann, Rudolf; De Domenico, Emilio; Lo Giudice, Angelina

2013-05-15

A total of 69 bacteria were isolated from crude oil enrichments of the polychaetes Megalomma claparedei, Sabella spallanzanii and Branchiomma luctuosum, and screened for biosurfactant (BS) production by conventional methods. Potential BS-producers (30 isolates) were primarily selected due to the production of both interesting spots on thin layer chromatography (TLC) plates and highly stable emulsions (E₂₄ ≥ 50%). Only few strains grew on cetyltrimethylammonium bromide and blood agar plates, indicating the probable production of anionic surfactants. The 16S rRNA gene sequencing revealed that selected isolates mainly belonged to the CFB group of Bacteroidetes, followed by Gammaproteobacteria and Alphaproteobacteria. A number of BS-producers belonged to genera (i.e., Cellulophaga, Cobetia, Cohaesibacter, Idiomarina, Pseudovibrio and Thalassospira) that have been never reported as able to produce BSs, even if they have been previously detected in hydrocarbon-enriched samples. Our results suggest that filter-feeding Polychaetes could represent a novel and yet unexplored source of biosurfactant-producing bacteria. Copyright © 2013 Elsevier Ltd. All rights reserved.

Macrobenthic community structure in the northern Saudi waters of the Gulf, 14 years after the 1991 oil spill.

PubMed

Joydas, T V; Qurban, Mohammad A; Al-Suwailem, Abdulaziz; Krishnakumar, P K; Nazeer, Zahid; Cali, N A

2012-02-01

The 1991 Gulf oil spill heavily impacted the coastal areas of the Saudi waters of the Arabian Gulf and recent studies have indicated that even 15 years after the incident, macrobenthos had not completely recovered in the sheltered bays in the affected region such as, Manifa Bay. This study investigates the community conditions of macrobenthos in the open waters in one of the impacted areas, Al-Khafji waters, about 14 years after the spill. Diversity measures and community structure analyses indicate a healthy status of polychaete communities. The BOPA index reveals that oil sensitive amphipods were recolonized in the study area. This confirms that the benthic communities of the oil spill impacted area had taken only <14 years to recover in the open waters of the impacted areas. The study also reveals the existence of three distinct polychaete communities along the depth and sediment gradients. Copyright © 2011 Elsevier Ltd. All rights reserved.

Microplastic fibers in the intertidal ecosystem surrounding Halifax Harbor, Nova Scotia.

PubMed

Mathalon, Alysse; Hill, Paul

2014-04-15

Humans continue to increase the use and disposal of plastics by producing over 240 million tonnes per year, polluting the oceans with persistent waste. The majority of plastic in the oceans are microplastics (<5 mm). In this study, the contamination of microplastic fibers was quantified in sediments from the intertidal zones of one exposed beach and two protected beaches along Nova Scotia's Eastern Shore. From the two protected beaches, polychaete worm fecal casts and live blue mussels (Mytilus edulis) were analyzed for microplastic content. Store-bought mussels from an aquaculture site were also analyzed. The average microplastic abundance observed from 10 g sediment subsamples was between 20 and 80 fibers, with higher concentrations at the high tide line from the exposed beach and at the low tide line from the protected beaches. Microplastic concentrations from polychaete fecal casts resembled concentrations quantified from low tide sediments. In two separate mussel analyses, significantly more microplastics were enumerated in farmed mussels compared to wild ones. Copyright © 2014 Elsevier Ltd. All rights reserved.

Redescriptions of Nereis oligohalina (Rioja, 1946) and N. garwoodi González-Escalante & Salazar-Vallejo, 2003 and description of N. confusa sp. n. (Annelida, Nereididae)

PubMed Central

Conde-Vela, Víctor M.; Salazar-Vallejo, Sergio I.

2015-01-01

Abstract Type material of several polychaete species described by Enrique Rioja from Mexican coasts are lost, and the current status of some species is doubtful. Nereis oligohalina (Rioja, 1946) was described from the Gulf of Mexico, but it has been considered a junior synonym of Nereis occidentalis Hartman, 1945, or regarded as a distinct species with an amphiamerican distribution. On the other hand, Nereis garwoodi González-Escalante & Salazar-Vallejo, 2003, described from Chetumal Bay, Caribbean coasts, could be confused with Nereis oligohalina. In order to clarify these uncertainties, Nereis oligohalina is redescribed based on specimens from the Mexican Gulf of Mexico, including a proposed neotype; further, Nereis garwoodi is redescribed including the selection of lectotype and paralectotypes, and Nereis confusa sp. n. is described with material from the Gulf of California. A key for the identification of similar species and some comments about speciation in nereidid polychaetes are also included. PMID:26448699

Ultrastructure of the genital organs in interstitial polychaetes. III. Penes and ejaculatory ducts in Hesionides arenaria (Hesionidae)

NASA Astrophysics Data System (ADS)

Westheide, W.

1982-12-01

The ejaculatory ducts of the two paired copulatory organs in the interstitial polychaete Hesionides arenaria are ciliated tubes, which open into simple, partly groove-like, non-stiffened penis papillae. The larger part of the ducts within the dorsal body wall is surrounded by circular muscle cells. Voluminous gland cell bodies lie between the pharynx-gut system and the body wall in the anterior part of the body; they extend anteriorly like long, thin necks, of which severl are always united in prominent strands. Their distal ends are expanded and penetrate the ducts. Six different types of glands can be distinguished according to the ultrastructure of their secretory granules. They produce the sheath of the double spermatophore or probably contain lytic enzymes that provide for the penetration of sperm into the body of the female. Differences in ultrastructure of the male organs in the interstitial genera Hesionides and Microphthalmus do not support the recent erection of the subfamily “Microphthalminae”.

Current state of macrobenthic communities in Baydaratskaya Bay (Kara Sea)

NASA Astrophysics Data System (ADS)

Kokarev, V. N.; Kozlovsky, V. V.; Azovsky, A. I.

2015-09-01

Macrobenthic communities in Baydaratskaya Bay were studied before and after the seafloor pipeline was begun to be laid out in the year 2011. Materials were collected during three surveys in 2007, 2012, and 2013. Ordination of the data based on community structure and composition revealed a clear depthrelated zonality of the communities. Stations deeper than 10 meters were dominated by bivalves, while shallower stations were dominated by nephtyid polychaetes. This structure persisted though the whole period studied, without any pronounced temporal trends. However, several deep-water stations near the pipeline path in the year 2013 revealed a distinct shift in the structure of macrofauna, with large bivalves disappearing, an increased abundance of small polychaetes, and a decrease in total biodiversity. Moreover, macrofauna were absent at one of these stations. We conclude that the structure and distribution of communities are relatively stable and mainly driven by depth. However, there are some local but evident disturbance effects, probably caused by recent human activity (dumping of dredged sediments).

Polychaete/amphipod ratio as an indicator of environmental impact related to offshore oil and gas production along the Norwegian continental shelf.

PubMed

Andrade, Hector; Renaud, Paul E

2011-12-01

Benthic faunal data is regularly collected worldwide to assess the ecological quality of marine environments. Recently, there has been renewed interest in developing biological indices able to identify environmental status and potential anthropogenic impacts. In this paper we evaluate the performance of a general polychaete/amphipod ratio along the Norwegian continental shelf as an environmental indicator for offshore oil and gas impacts. Two main trends are apparent: first, a contamination gradient is discernible from where production takes place compared to stations 10,000 m away. Second, the quality of the marine environment has improved over time. These results are consistent with monitoring reports employing a combination of uni- and multi-variate statistics. Thus, we consider this ratio as a relatively simple, useful and potentially cost-effective complement to other more demanding assessment techniques. Because of its strong theoretical basis, it may also be useful for detecting ecological change as a result of other activities. Copyright © 2011 Elsevier Ltd. All rights reserved.

Impact of flood events on macrobenthic community structure on an intertidal flat developing in the Ohta River Estuary.

PubMed

Nishijima, Wataru; Nakano, Yoichi; Nakai, Satoshi; Okuda, Tetsuji; Imai, Tsuyoshi; Okada, Mitsumasa

2013-09-15

We investigated the effects of river floods on the macrobenthic community of the intertidal flat in the Ohta River Estuary, Japan, from 2005 to 2010. Sediment erosion by flood events ranged from about 2-3 cm to 12 cm, and the salinity dropped to 0‰ even during low-intensity flood events. Cluster analysis of the macrobenthic population showed that the community structure was controlled by the physical disturbance, decreased salinity, or both. The opportunistic polychaete Capitella sp. was the most dominant species in all clusters, and populations of the long-lived polychaete Ceratonereis erythraeensis increased in years with stable flow and almost disappeared in years with intense flooding. The bivalve Musculista senhousia was also an important opportunistic species that formed mats in summer of the stable years and influenced the structure of the macrobenthic community. Our results demonstrate the substantial effects of flood events on the macrobenthic community structure. Copyright © 2013 Elsevier Ltd. All rights reserved.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

Seagrass communities are a major feature of shallow marine areas throughout the world. The marine spermatophyte, Thalassia testudinum Konig, is the dominant seagrass in southeast Florida and the Florida Gulf coast. The trophic interaction between the fishes and the macrobenthic and cryptic fauna found in the area was examined. Based on digestive tract analysis, the principal interaction between the primary consumers of the study area and the higher trophic level predators was via the polychaetes and peracaridean crustaceans. The mollusks which contributed significantly to the benthic biomass were not a preferred food for the animals frequenting the study site. Themore » maximum biomass in any benthic and cryptic samples was 3.35 g dry/m/sup 2/. The majority of the fishes captured were foragers over a wide area. The main residents were the syngnathids and the goldspotted killifish, Floridichthys carpio. It was felt that the predator population was limited by the small stock of polychaetes and peracaridean crustaceans which had a maximum biomass in any one sample equivalent to 1.40 g dry/m/sup 2/.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brook, I.M.

Seagrass communities are a major feature of shallow marine areas throughout the world. The marine spermatophyte Thalassia testudinum is the dominant seagrass in southeast Florida and the Florida Gulf coast. The trophic interaction between the fishes and the macrobenthic and cryptic fauna found in the area was examined. Based on digestive tract analysis, the principal interaction between the primary consumers of the study area and the higher trophic level predators was via the polychaetes and peracaridean crustaceans. The mollusks which contributed significantly to the benthic biomass were not a preferred food for the animals frequenting the study site. The maximummore » mollusk biomass in any benthic and cryptic sample was 2.31 g dry/m/sup 2/. It was felt that the predator population was limited by the small stock of polychaetes and peracaridean crustaceans which had a maximum biomass in any one sample equivalent to 1.74 g dry/m/sup 2/. The majority of the fishes captured were foragers over a wide area. The main residents were the syngnathids and the gold-spotted killifish, Floridichthys carpio.« less

The role of certain infauna and vascular plants in the mediation of redox reactions in marine sediments

NASA Technical Reports Server (NTRS)

Hines, Mark E.

1992-01-01

The mechanisms by which certain animals and plants affect redox processes in sediments was examined by studying three environments: (1) subtidal sediments dominated by the deposit-feeding polychaete Heteromastus filiformis; (2) a saltmarsh inhabited by the tall form of Spartina alterniflora; and (3) tropical carbonate sediments inhabited by three species of seagrasses. S-35-sulfide production rates were compared to pool sizes of dissolved sulfide and dissolved iron. In all of the sediments studied, rates of sulfide reduction were enhanced by macroorganisms while the rate of turnover of dissolved sulfide increased. The polychaete enhanced microbial activity and redox cycling primarily by subducting particles of organic matter and oxidized iron during sediment reworking. The Spartina species enhanced anaerobic activity by transporting primarily dissolved organic matter and oxidants. Although the final result of both animal and plant activities was the enhancement of sub-surface cycling of sulfur and iron, decreased dissolved sulfide and increased dissolved iron concentrations, the mechanisms which produced these results differed dramatically.

SNW1 Is a Critical Regulator of Spatial BMP Activity, Neural Plate Border Formation, and Neural Crest Specification in Vertebrate Embryos

PubMed Central

Wu, Mary Y.; Ramel, Marie-Christine; Howell, Michael; Hill, Caroline S.

2011-01-01

Bone morphogenetic protein (BMP) gradients provide positional information to direct cell fate specification, such as patterning of the vertebrate ectoderm into neural, neural crest, and epidermal tissues, with precise borders segregating these domains. However, little is known about how BMP activity is regulated spatially and temporally during vertebrate development to contribute to embryonic patterning, and more specifically to neural crest formation. Through a large-scale in vivo functional screen in Xenopus for neural crest fate, we identified an essential regulator of BMP activity, SNW1. SNW1 is a nuclear protein known to regulate gene expression. Using antisense morpholinos to deplete SNW1 protein in both Xenopus and zebrafish embryos, we demonstrate that dorsally expressed SNW1 is required for neural crest specification, and this is independent of mesoderm formation and gastrulation morphogenetic movements. By exploiting a combination of immunostaining for phosphorylated Smad1 in Xenopus embryos and a BMP-dependent reporter transgenic zebrafish line, we show that SNW1 regulates a specific domain of BMP activity in the dorsal ectoderm at the neural plate border at post-gastrula stages. We use double in situ hybridizations and immunofluorescence to show how this domain of BMP activity is spatially positioned relative to the neural crest domain and that of SNW1 expression. Further in vivo and in vitro assays using cell culture and tissue explants allow us to conclude that SNW1 acts upstream of the BMP receptors. Finally, we show that the requirement of SNW1 for neural crest specification is through its ability to regulate BMP activity, as we demonstrate that targeted overexpression of BMP to the neural plate border is sufficient to restore neural crest formation in Xenopus SNW1 morphants. We conclude that through its ability to regulate a specific domain of BMP activity in the vertebrate embryo, SNW1 is a critical regulator of neural plate border formation and thus neural crest specification. PMID:21358802

Distinct neural and neuromuscular strategies underlie independent evolution of simplified advertisement calls

PubMed Central

Leininger, Elizabeth C.; Kelley, Darcy B.

2013-01-01

Independent or convergent evolution can underlie phenotypic similarity of derived behavioural characters. Determining the underlying neural and neuromuscular mechanisms sheds light on how these characters arose. One example of evolutionarily derived characters is a temporally simple advertisement call of male African clawed frogs (Xenopus) that arose at least twice independently from a more complex ancestral pattern. How did simplification occur in the vocal circuit? To distinguish shared from divergent mechanisms, we examined activity from the calling brain and vocal organ (larynx) in two species that independently evolved simplified calls. We find that each species uses distinct neural and neuromuscular strategies to produce the simplified calls. Isolated  Xenopus borealis brains produce fictive vocal patterns that match temporal patterns of actual male calls; the larynx converts nerve activity faithfully into muscle contractions and single clicks. In contrast, fictive patterns from isolated Xenopus boumbaensis brains are short bursts of nerve activity; the isolated larynx requires stimulus bursts to produce a single click of sound. Thus, unlike X. borealis, the output of the X. boumbaensis hindbrain vocal pattern generator is an ancestral burst-type pattern, transformed by the larynx into single clicks. Temporally simple advertisement calls in genetically distant species of Xenopus have thus arisen independently via reconfigurations of central and peripheral vocal neuroeffectors. PMID:23407829

Distinct neural and neuromuscular strategies underlie independent evolution of simplified advertisement calls.

PubMed

Leininger, Elizabeth C; Kelley, Darcy B

2013-04-07

Independent or convergent evolution can underlie phenotypic similarity of derived behavioural characters. Determining the underlying neural and neuromuscular mechanisms sheds light on how these characters arose. One example of evolutionarily derived characters is a temporally simple advertisement call of male African clawed frogs (Xenopus) that arose at least twice independently from a more complex ancestral pattern. How did simplification occur in the vocal circuit? To distinguish shared from divergent mechanisms, we examined activity from the calling brain and vocal organ (larynx) in two species that independently evolved simplified calls. We find that each species uses distinct neural and neuromuscular strategies to produce the simplified calls. Isolated Xenopus borealis brains produce fictive vocal patterns that match temporal patterns of actual male calls; the larynx converts nerve activity faithfully into muscle contractions and single clicks. In contrast, fictive patterns from isolated Xenopus boumbaensis brains are short bursts of nerve activity; the isolated larynx requires stimulus bursts to produce a single click of sound. Thus, unlike X. borealis, the output of the X. boumbaensis hindbrain vocal pattern generator is an ancestral burst-type pattern, transformed by the larynx into single clicks. Temporally simple advertisement calls in genetically distant species of Xenopus have thus arisen independently via reconfigurations of central and peripheral vocal neuroeffectors.

Comparison of Computational-Model and Experimental-Example Trained Neural Networks for Processing Speckled Fringe Patterns

NASA Technical Reports Server (NTRS)

Decker, A. J.; Fite, E. B.; Thorp, S. A.; Mehmed, O.

1998-01-01

The responses of artificial neural networks to experimental and model-generated inputs are compared for detection of damage in twisted fan blades using electronic holography. The training-set inputs, for this work, are experimentally generated characteristic patterns of the vibrating blades. The outputs are damage-flag indicators or second derivatives of the sensitivity-vector-projected displacement vectors from a finite element model. Artificial neural networks have been trained in the past with computational-model-generated training sets. This approach avoids the difficult inverse calculations traditionally used to compare interference fringes with the models. But the high modeling standards are hard to achieve, even with fan-blade finite-element models.

Comparison of Computational, Model and Experimental, Example Trained Neural Networks for Processing Speckled Fringe Patterns

NASA Technical Reports Server (NTRS)

Decker, A. J.; Fite, E. B.; Thorp, S. A.; Mehmed, O.

1998-01-01

The responses of artificial neural networks to experimental and model-generated inputs are compared for detection of damage in twisted fan blades using electronic holography. The training-set inputs, for this work, are experimentally generated characteristic patterns of the vibrating blades. The outputs are damage-flag indicators or second derivatives of the sensitivity-vector-projected displacement vectors from a finite element model. Artificial neural networks have been trained in the past with computational-model- generated training sets. This approach avoids the difficult inverse calculations traditionally used to compare interference fringes with the models. But the high modeling standards are hard to achieve, even with fan-blade finite-element models.

Application of artificial neural networks with backpropagation technique in the financial data

NASA Astrophysics Data System (ADS)

Jaiswal, Jitendra Kumar; Das, Raja

2017-11-01

The propensity of applying neural networks has been proliferated in multiple disciplines for research activities since the past recent decades because of its powerful control with regulatory parameters for pattern recognition and classification. It is also being widely applied for forecasting in the numerous divisions. Since financial data have been readily available due to the involvement of computers and computing systems in the stock market premises throughout the world, researchers have also developed numerous techniques and algorithms to analyze the data from this sector. In this paper we have applied neural network with backpropagation technique to find the data pattern from finance section and prediction for stock values as well.

What Neural Substrates Trigger the Adept Scientific Pattern Discovery by Biologists?

NASA Astrophysics Data System (ADS)

Lee, Jun-Ki; Kwon, Yong-Ju

2011-04-01

This study investigated the neural correlates of experts and novices during biological object pattern detection using an fMRI approach in order to reveal the neural correlates of a biologist's superior pattern discovery ability. Sixteen healthy male participants (8 biologists and 8 non-biologists) volunteered for the study. Participants were shown fifteen series of organism pictures and asked to detect patterns amid stimulus pictures. Primary findings showed significant activations in the right middle temporal gyrus and inferior parietal lobule amongst participants in the biologist (expert) group. Interestingly, the left superior temporal gyrus was activated in participants from the non-biologist (novice) group. These results suggested that superior pattern discovery ability could be related to a functional facilitation of the parieto-temporal network, which is particularly driven by the right middle temporal gyrus and inferior parietal lobule in addition to the recruitment of additional brain regions. Furthermore, the functional facilitation of the network might actually pertain to high coherent processing skills and visual working memory capacity. Hence, study results suggested that adept scientific thinking ability can be detected by neuronal substrates, which may be used as criteria for developing and evaluating a brain-based science curriculum and test instrument.

The Human Central Pattern Generator for Locomotion.

PubMed

Minassian, Karen; Hofstoetter, Ursula S; Dzeladini, Florin; Guertin, Pierre A; Ijspeert, Auke

2017-03-01

The ability of dedicated spinal circuits, referred to as central pattern generators (CPGs), to produce the basic rhythm and neural activation patterns underlying locomotion can be demonstrated under specific experimental conditions in reduced animal preparations. The existence of CPGs in humans is a matter of debate. Equally elusive is the contribution of CPGs to normal bipedal locomotion. To address these points, we focus on human studies that utilized spinal cord stimulation or pharmacological neuromodulation to generate rhythmic activity in individuals with spinal cord injury, and on neuromechanical modeling of human locomotion. In the absence of volitional motor control and step-specific sensory feedback, the human lumbar spinal cord can produce rhythmic muscle activation patterns that closely resemble CPG-induced neural activity of the isolated animal spinal cord. In this sense, CPGs in humans can be defined by the activity they produce. During normal locomotion, CPGs could contribute to the activation patterns during specific phases of the step cycle and simplify supraspinal control of step cycle frequency as a feedforward component to achieve a targeted speed. Determining how the human CPGs operate will be essential to advance the theory of neural control of locomotion and develop new locomotor neurorehabilitation paradigms.

Vascular pattern of the dentate gyrus is regulated by neural progenitors.

PubMed

Pombero, Ana; Garcia-Lopez, Raquel; Estirado, Alicia; Martinez, Salvador

2018-05-01

Neurogenesis is a vital process that begins during early embryonic development and continues until adulthood, though in the latter case, it is restricted to the subventricular zone and the subgranular zone of the dentate gyrus (DG). In particular, the DG's neurogenic properties are structurally and functionally unique, which may be related to its singular vascular pattern. Neurogenesis and angiogenesis share molecular signals and act synergistically, supporting the concept of a neurogenic niche as a functional unit between neural precursors cells and their environment, in which the blood vessels play an important role. Whereas it is well known that vascular development controls neural proliferation in the embryonary and in the adult brain, by releasing neurotrophic factors; the potential influence of neural cells on vascular components during angiogenesis is largely unknown. We have demonstrated that the reduction of neural progenitors leads to a significant impairment of vascular development. Since VEGF is a potential regulator in the neurogenesis-angiogenesis crosstalk, we were interested in assessing the possible role of this molecule in the hippocampal neurovascular development. Our results showed that VEGF is the molecule involved in the regulation of vascular development by neural progenitor cells in the DG.

Neural codes of seeing architectural styles

PubMed Central

Choo, Heeyoung; Nasar, Jack L.; Nikrahei, Bardia; Walther, Dirk B.

2017-01-01

Images of iconic buildings, such as the CN Tower, instantly transport us to specific places, such as Toronto. Despite the substantial impact of architectural design on people’s visual experience of built environments, we know little about its neural representation in the human brain. In the present study, we have found patterns of neural activity associated with specific architectural styles in several high-level visual brain regions, but not in primary visual cortex (V1). This finding suggests that the neural correlates of the visual perception of architectural styles stem from style-specific complex visual structure beyond the simple features computed in V1. Surprisingly, the network of brain regions representing architectural styles included the fusiform face area (FFA) in addition to several scene-selective regions. Hierarchical clustering of error patterns further revealed that the FFA participated to a much larger extent in the neural encoding of architectural styles than entry-level scene categories. We conclude that the FFA is involved in fine-grained neural encoding of scenes at a subordinate-level, in our case, architectural styles of buildings. This study for the first time shows how the human visual system encodes visual aspects of architecture, one of the predominant and longest-lasting artefacts of human culture. PMID:28071765

Compositionality in neural control: an interdisciplinary study of scribbling movements in primates

PubMed Central

Abeles, Moshe; Diesmann, Markus; Flash, Tamar; Geisel, Theo; Herrmann, Michael; Teicher, Mina

2013-01-01

This article discusses the compositional structure of hand movements by analyzing and modeling neural and behavioral data obtained from experiments where a monkey (Macaca fascicularis) performed scribbling movements induced by a search task. Using geometrically based approaches to movement segmentation, it is shown that the hand trajectories are composed of elementary segments that are primarily parabolic in shape. The segments could be categorized into a small number of classes on the basis of decreasing intra-class variance over the course of training. A separate classification of the neural data employing a hidden Markov model showed a coincidence of the neural states with the behavioral categories. An additional analysis of both types of data by a data mining method provided evidence that the neural activity patterns underlying the behavioral primitives were formed by sets of specific and precise spike patterns. A geometric description of the movement trajectories, together with precise neural timing data indicates a compositional variant of a realistic synfire chain model. This model reproduces the typical shapes and temporal properties of the trajectories; hence the structure and composition of the primitives may reflect meaningful behavior. PMID:24062679

Neural codes of seeing architectural styles.

PubMed

Choo, Heeyoung; Nasar, Jack L; Nikrahei, Bardia; Walther, Dirk B

2017-01-10

Images of iconic buildings, such as the CN Tower, instantly transport us to specific places, such as Toronto. Despite the substantial impact of architectural design on people's visual experience of built environments, we know little about its neural representation in the human brain. In the present study, we have found patterns of neural activity associated with specific architectural styles in several high-level visual brain regions, but not in primary visual cortex (V1). This finding suggests that the neural correlates of the visual perception of architectural styles stem from style-specific complex visual structure beyond the simple features computed in V1. Surprisingly, the network of brain regions representing architectural styles included the fusiform face area (FFA) in addition to several scene-selective regions. Hierarchical clustering of error patterns further revealed that the FFA participated to a much larger extent in the neural encoding of architectural styles than entry-level scene categories. We conclude that the FFA is involved in fine-grained neural encoding of scenes at a subordinate-level, in our case, architectural styles of buildings. This study for the first time shows how the human visual system encodes visual aspects of architecture, one of the predominant and longest-lasting artefacts of human culture.

Reduction of the dimension of neural network models in problems of pattern recognition and forecasting

NASA Astrophysics Data System (ADS)

Nasertdinova, A. D.; Bochkarev, V. V.

2017-11-01

Deep neural networks with a large number of parameters are a powerful tool for solving problems of pattern recognition, prediction and classification. Nevertheless, overfitting remains a serious problem in the use of such networks. A method of solving the problem of overfitting is proposed in this article. This method is based on reducing the number of independent parameters of a neural network model using the principal component analysis, and can be implemented using existing libraries of neural computing. The algorithm was tested on the problem of recognition of handwritten symbols from the MNIST database, as well as on the task of predicting time series (rows of the average monthly number of sunspots and series of the Lorentz system were used). It is shown that the application of the principal component analysis enables reducing the number of parameters of the neural network model when the results are good. The average error rate for the recognition of handwritten figures from the MNIST database was 1.12% (which is comparable to the results obtained using the "Deep training" methods), while the number of parameters of the neural network can be reduced to 130 times.

Artificial neural network classification using a minimal training set - Comparison to conventional supervised classification

NASA Technical Reports Server (NTRS)

Hepner, George F.; Logan, Thomas; Ritter, Niles; Bryant, Nevin

1990-01-01

Recent research has shown an artificial neural network (ANN) to be capable of pattern recognition and the classification of image data. This paper examines the potential for the application of neural network computing to satellite image processing. A second objective is to provide a preliminary comparison and ANN classification. An artificial neural network can be trained to do land-cover classification of satellite imagery using selected sites representative of each class in a manner similar to conventional supervised classification. One of the major problems associated with recognition and classifications of pattern from remotely sensed data is the time and cost of developing a set of training sites. This reseach compares the use of an ANN back propagation classification procedure with a conventional supervised maximum likelihood classification procedure using a minimal training set. When using a minimal training set, the neural network is able to provide a land-cover classification superior to the classification derived from the conventional classification procedure. This research is the foundation for developing application parameters for further prototyping of software and hardware implementations for artificial neural networks in satellite image and geographic information processing.

Data-driven inference of network connectivity for modeling the dynamics of neural codes in the insect antennal lobe

PubMed Central

Shlizerman, Eli; Riffell, Jeffrey A.; Kutz, J. Nathan

2014-01-01

The antennal lobe (AL), olfactory processing center in insects, is able to process stimuli into distinct neural activity patterns, called olfactory neural codes. To model their dynamics we perform multichannel recordings from the projection neurons in the AL driven by different odorants. We then derive a dynamic neuronal network from the electrophysiological data. The network consists of lateral-inhibitory neurons and excitatory neurons (modeled as firing-rate units), and is capable of producing unique olfactory neural codes for the tested odorants. To construct the network, we (1) design a projection, an odor space, for the neural recording from the AL, which discriminates between distinct odorants trajectories (2) characterize scent recognition, i.e., decision-making based on olfactory signals and (3) infer the wiring of the neural circuit, the connectome of the AL. We show that the constructed model is consistent with biological observations, such as contrast enhancement and robustness to noise. The study suggests a data-driven approach to answer a key biological question in identifying how lateral inhibitory neurons can be wired to excitatory neurons to permit robust activity patterns. PMID:25165442

Controlling selective stimulations below a spinal cord hemisection using brain recordings with a neural interface system approach

NASA Astrophysics Data System (ADS)

Panetsos, Fivos; Sanchez-Jimenez, Abel; Torets, Carlos; Largo, Carla; Micera, Silvestro

2011-08-01

In this work we address the use of realtime cortical recordings for the generation of coherent, reliable and robust motor activity in spinal-lesioned animals through selective intraspinal microstimulation (ISMS). The spinal cord of adult rats was hemisectioned and groups of multielectrodes were implanted in both the central nervous system (CNS) and the spinal cord below the lesion level to establish a neural system interface (NSI). To test the reliability of this new NSI connection, highly repeatable neural responses recorded from the CNS were used as a pattern generator of an open-loop control strategy for selective ISMS of the spinal motoneurons. Our experimental procedure avoided the spontaneous non-controlled and non-repeatable neural activity that could have generated spurious ISMS and the consequent undesired muscle contractions. Combinations of complex CNS patterns generated precisely coordinated, reliable and robust motor actions.

Signal processing method and system for noise removal and signal extraction

DOEpatents

Fu, Chi Yung; Petrich, Loren

2009-04-14

A signal processing method and system combining smooth level wavelet pre-processing together with artificial neural networks all in the wavelet domain for signal denoising and extraction. Upon receiving a signal corrupted with noise, an n-level decomposition of the signal is performed using a discrete wavelet transform to produce a smooth component and a rough component for each decomposition level. The n.sup.th level smooth component is then inputted into a corresponding neural network pre-trained to filter out noise in that component by pattern recognition in the wavelet domain. Additional rough components, beginning at the highest level, may also be retained and inputted into corresponding neural networks pre-trained to filter out noise in those components also by pattern recognition in the wavelet domain. In any case, an inverse discrete wavelet transform is performed on the combined output from all the neural networks to recover a clean signal back in the time domain.

From sensation to perception: Using multivariate classification of visual illusions to identify neural correlates of conscious awareness in space and time.

PubMed

Hogendoorn, Hinze

2015-01-01

An important goal of cognitive neuroscience is understanding the neural underpinnings of conscious awareness. Although the low-level processing of sensory input is well understood in most modalities, it remains a challenge to understand how the brain translates such input into conscious awareness. Here, I argue that the application of multivariate pattern classification techniques to neuroimaging data acquired while observers experience perceptual illusions provides a unique way to dissociate sensory mechanisms from mechanisms underlying conscious awareness. Using this approach, it is possible to directly compare patterns of neural activity that correspond to the contents of awareness, independent from changes in sensory input, and to track these neural representations over time at high temporal resolution. I highlight five recent studies using this approach, and provide practical considerations and limitations for future implementations.

Engaging and disengaging recurrent inhibition coincides with sensing and unsensing of a sensory stimulus

PubMed Central

Saha, Debajit; Sun, Wensheng; Li, Chao; Nizampatnam, Srinath; Padovano, William; Chen, Zhengdao; Chen, Alex; Altan, Ege; Lo, Ray; Barbour, Dennis L.; Raman, Baranidharan

2017-01-01

Even simple sensory stimuli evoke neural responses that are dynamic and complex. Are the temporally patterned neural activities important for controlling the behavioral output? Here, we investigated this issue. Our results reveal that in the insect antennal lobe, due to circuit interactions, distinct neural ensembles are activated during and immediately following the termination of every odorant. Such non-overlapping response patterns are not observed even when the stimulus intensity or identities were changed. In addition, we find that ON and OFF ensemble neural activities differ in their ability to recruit recurrent inhibition, entrain field-potential oscillations and more importantly in their relevance to behaviour (initiate versus reset conditioned responses). Notably, we find that a strikingly similar strategy is also used for encoding sound onsets and offsets in the marmoset auditory cortex. In sum, our results suggest a general approach where recurrent inhibition is associated with stimulus ‘recognition' and ‘derecognition'. PMID:28534502

Decoding fMRI Signatures of Real-world Autobiographical Memory Retrieval.

PubMed

Rissman, Jesse; Chow, Tiffany E; Reggente, Nicco; Wagner, Anthony D

2016-04-01

Extant neuroimaging data implicate frontoparietal and medial-temporal lobe regions in episodic retrieval, and the specific pattern of activity within and across these regions is diagnostic of an individual's subjective mnemonic experience. For example, in laboratory-based paradigms, memories for recently encoded faces can be accurately decoded from single-trial fMRI patterns [Uncapher, M. R., Boyd-Meredith, J. T., Chow, T. E., Rissman, J., & Wagner, A. D. Goal-directed modulation of neural memory patterns: Implications for fMRI-based memory detection. Journal of Neuroscience, 35, 8531-8545, 2015; Rissman, J., Greely, H. T., & Wagner, A. D. Detecting individual memories through the neural decoding of memory states and past experience. Proceedings of the National Academy of Sciences, U.S.A., 107, 9849-9854, 2010]. Here, we investigated the neural patterns underlying memory for real-world autobiographical events, probed at 1- to 3-week retention intervals as well as whether distinct patterns are associated with different subjective memory states. For 3 weeks, participants (n = 16) wore digital cameras that captured photographs of their daily activities. One week later, they were scanned while making memory judgments about sequences of photos depicting events from their own lives or events captured by the cameras of others. Whole-brain multivoxel pattern analysis achieved near-perfect accuracy at distinguishing correctly recognized events from correctly rejected novel events, and decoding performance did not significantly vary with retention interval. Multivoxel pattern classifiers also differentiated recollection from familiarity and reliably decoded the subjective strength of recollection, of familiarity, or of novelty. Classification-based brain maps revealed dissociable neural signatures of these mnemonic states, with activity patterns in hippocampus, medial PFC, and ventral parietal cortex being particularly diagnostic of recollection. Finally, a classifier trained on previously acquired laboratory-based memory data achieved reliable decoding of autobiographical memory states. We discuss the implications for neuroscientific accounts of episodic retrieval and comment on the potential forensic use of fMRI for probing experiential knowledge.

Neural activity in the hippocampus during conflict resolution.

PubMed

Sakimoto, Yuya; Okada, Kana; Hattori, Minoru; Takeda, Kozue; Sakata, Shogo

2013-01-15

This study examined configural association theory and conflict resolution models in relation to hippocampal neural activity during positive patterning tasks. According to configural association theory, the hippocampus is important for responses to compound stimuli in positive patterning tasks. In contrast, according to the conflict resolution model, the hippocampus is important for responses to single stimuli in positive patterning tasks. We hypothesized that if configural association theory is applicable, and not the conflict resolution model, the hippocampal theta power should be increased when compound stimuli are presented. If, on the other hand, the conflict resolution model is applicable, but not configural association theory, then the hippocampal theta power should be increased when single stimuli are presented. If both models are valid and applicable in the positive patterning task, we predict that the hippocampal theta power should be increased by presentation of both compound and single stimuli during the positive patterning task. To examine our hypotheses, we measured hippocampal theta power in rats during a positive patterning task. The results showed that hippocampal theta power increased during the presentation of a single stimulus, but did not increase during the presentation of a compound stimulus. This finding suggests that the conflict resolution model is more applicable than the configural association theory for describing neural activity during positive patterning tasks. Copyright © 2012 Elsevier B.V. All rights reserved.

Development and function of human cerebral cortex neural networks from pluripotent stem cells in vitro

PubMed Central

Kirwan, Peter; Turner-Bridger, Benita; Peter, Manuel; Momoh, Ayiba; Arambepola, Devika; Robinson, Hugh P. C.; Livesey, Frederick J.

2015-01-01

A key aspect of nervous system development, including that of the cerebral cortex, is the formation of higher-order neural networks. Developing neural networks undergo several phases with distinct activity patterns in vivo, which are thought to prune and fine-tune network connectivity. We report here that human pluripotent stem cell (hPSC)-derived cerebral cortex neurons form large-scale networks that reflect those found in the developing cerebral cortex in vivo. Synchronised oscillatory networks develop in a highly stereotyped pattern over several weeks in culture. An initial phase of increasing frequency of oscillations is followed by a phase of decreasing frequency, before giving rise to non-synchronous, ordered activity patterns. hPSC-derived cortical neural networks are excitatory, driven by activation of AMPA- and NMDA-type glutamate receptors, and can undergo NMDA-receptor-mediated plasticity. Investigating single neuron connectivity within PSC-derived cultures, using rabies-based trans-synaptic tracing, we found two broad classes of neuronal connectivity: most neurons have small numbers (<10) of presynaptic inputs, whereas a small set of hub-like neurons have large numbers of synaptic connections (>40). These data demonstrate that the formation of hPSC-derived cortical networks mimics in vivo cortical network development and function, demonstrating the utility of in vitro systems for mechanistic studies of human forebrain neural network biology. PMID:26395144

Fluctuation-Driven Neural Dynamics Reproduce Drosophila Locomotor Patterns

PubMed Central

Cruchet, Steeve; Gustafson, Kyle; Benton, Richard; Floreano, Dario

2015-01-01

The neural mechanisms determining the timing of even simple actions, such as when to walk or rest, are largely mysterious. One intriguing, but untested, hypothesis posits a role for ongoing activity fluctuations in neurons of central action selection circuits that drive animal behavior from moment to moment. To examine how fluctuating activity can contribute to action timing, we paired high-resolution measurements of freely walking Drosophila melanogaster with data-driven neural network modeling and dynamical systems analysis. We generated fluctuation-driven network models whose outputs—locomotor bouts—matched those measured from sensory-deprived Drosophila. From these models, we identified those that could also reproduce a second, unrelated dataset: the complex time-course of odor-evoked walking for genetically diverse Drosophila strains. Dynamical models that best reproduced both Drosophila basal and odor-evoked locomotor patterns exhibited specific characteristics. First, ongoing fluctuations were required. In a stochastic resonance-like manner, these fluctuations allowed neural activity to escape stable equilibria and to exceed a threshold for locomotion. Second, odor-induced shifts of equilibria in these models caused a depression in locomotor frequency following olfactory stimulation. Our models predict that activity fluctuations in action selection circuits cause behavioral output to more closely match sensory drive and may therefore enhance navigation in complex sensory environments. Together these data reveal how simple neural dynamics, when coupled with activity fluctuations, can give rise to complex patterns of animal behavior. PMID:26600381

Modeling the electrode-neuron interface of cochlear implants: effects of neural survival, electrode placement, and the partial tripolar configuration.

PubMed

Goldwyn, Joshua H; Bierer, Steven M; Bierer, Julie Arenberg

2010-09-01

The partial tripolar electrode configuration is a relatively novel stimulation strategy that can generate more spatially focused electric fields than the commonly used monopolar configuration. Focused stimulation strategies should improve spectral resolution in cochlear implant users, but may also be more sensitive to local irregularities in the electrode-neuron interface. In this study, we develop a practical computer model of cochlear implant stimulation that can simulate neural activation in a simplified cochlear geometry and we relate the resulting patterns of neural activity to basic psychophysical measures. We examine how two types of local irregularities in the electrode-neuron interface, variations in spiral ganglion nerve density and electrode position within the scala tympani, affect the simulated neural activation patterns and how these patterns change with electrode configuration. The model shows that higher partial tripolar fractions activate more spatially restricted populations of neurons at all current levels and require higher current levels to excite a given number of neurons. We find that threshold levels are more sensitive at high partial tripolar fractions to both types of irregularities, but these effects are not independent. In particular, at close electrode-neuron distances, activation is typically more spatially localized which leads to a greater influence of neural dead regions. Copyright (c) 2010 Elsevier B.V. All rights reserved.

Development and function of human cerebral cortex neural networks from pluripotent stem cells in vitro.

PubMed

Kirwan, Peter; Turner-Bridger, Benita; Peter, Manuel; Momoh, Ayiba; Arambepola, Devika; Robinson, Hugh P C; Livesey, Frederick J

2015-09-15

A key aspect of nervous system development, including that of the cerebral cortex, is the formation of higher-order neural networks. Developing neural networks undergo several phases with distinct activity patterns in vivo, which are thought to prune and fine-tune network connectivity. We report here that human pluripotent stem cell (hPSC)-derived cerebral cortex neurons form large-scale networks that reflect those found in the developing cerebral cortex in vivo. Synchronised oscillatory networks develop in a highly stereotyped pattern over several weeks in culture. An initial phase of increasing frequency of oscillations is followed by a phase of decreasing frequency, before giving rise to non-synchronous, ordered activity patterns. hPSC-derived cortical neural networks are excitatory, driven by activation of AMPA- and NMDA-type glutamate receptors, and can undergo NMDA-receptor-mediated plasticity. Investigating single neuron connectivity within PSC-derived cultures, using rabies-based trans-synaptic tracing, we found two broad classes of neuronal connectivity: most neurons have small numbers (<10) of presynaptic inputs, whereas a small set of hub-like neurons have large numbers of synaptic connections (>40). These data demonstrate that the formation of hPSC-derived cortical networks mimics in vivo cortical network development and function, demonstrating the utility of in vitro systems for mechanistic studies of human forebrain neural network biology. © 2015. Published by The Company of Biologists Ltd.

The neural dynamics of task context in free recall.

PubMed

Polyn, Sean M; Kragel, James E; Morton, Neal W; McCluey, Joshua D; Cohen, Zachary D

2012-03-01

Multivariate pattern analysis (MVPA) is a powerful tool for relating theories of cognitive function to the neural dynamics observed while people engage in cognitive tasks. Here, we use the Context Maintenance and Retrieval model of free recall (CMR; Polyn et al., 2009a) to interpret variability in the strength of task-specific patterns of distributed neural activity as participants study and recall lists of words. The CMR model describes how temporal and source-related (here, encoding task) information combine in a contextual representation that is responsible for guiding memory search. Each studied word in the free-recall paradigm is associated with one of two encoding tasks (size and animacy) that have distinct neural representations during encoding. We find evidence for the context retrieval hypothesis central to the CMR model: Task-specific patterns of neural activity are reactivated during memory search, as the participant recalls an item previously associated with a particular task. Furthermore, we find that the fidelity of these task representations during study is related to task-shifting, the serial position of the studied item, and variability in the magnitude of the recency effect across participants. The CMR model suggests that these effects may be related to a central parameter of the model that controls the rate that an internal contextual representation integrates information from the surrounding environment. Copyright © 2011 Elsevier Ltd. All rights reserved.

Multi-Connection Pattern Analysis: Decoding the representational content of neural communication.

PubMed

Li, Yuanning; Richardson, Robert Mark; Ghuman, Avniel Singh

2017-11-15

The lack of multivariate methods for decoding the representational content of interregional neural communication has left it difficult to know what information is represented in distributed brain circuit interactions. Here we present Multi-Connection Pattern Analysis (MCPA), which works by learning mappings between the activity patterns of the populations as a factor of the information being processed. These maps are used to predict the activity from one neural population based on the activity from the other population. Successful MCPA-based decoding indicates the involvement of distributed computational processing and provides a framework for probing the representational structure of the interaction. Simulations demonstrate the efficacy of MCPA in realistic circumstances. In addition, we demonstrate that MCPA can be applied to different signal modalities to evaluate a variety of hypothesis associated with information coding in neural communications. We apply MCPA to fMRI and human intracranial electrophysiological data to provide a proof-of-concept of the utility of this method for decoding individual natural images and faces in functional connectivity data. We further use a MCPA-based representational similarity analysis to illustrate how MCPA may be used to test computational models of information transfer among regions of the visual processing stream. Thus, MCPA can be used to assess the information represented in the coupled activity of interacting neural circuits and probe the underlying principles of information transformation between regions. Copyright © 2017 Elsevier Inc. All rights reserved.

Designation of a neotype and redescription of Hesione reticulata von Marenzeller, 1879 from Japan (Annelida, Hesionidae).

PubMed

Jimi, Naoto; Salazar-Vallejo, Sergio I; Kajihara, Hiroshi

2017-01-01

The hesionid polychaete Hesione reticulata von Marenzeller, 1879 was described from Enoshima Island, Japan and has been recorded also from the Red Sea. Depending on researchers, it has been regarded as either a distinct species or synonymous with older established ones. The type specimen has been lost. In order to clarify its taxonomic status, Hesione reticulata is herein redescribed, illustrated, and a neotype is proposed based on recent material collected near the type locality. The diagnostic features include the presence of several dorsal, discontinuous longitudinal bands, interrupted by pale segmental spots; prostomium with tiny antennae; a tuberculated dorsal integument; acicular lobes double; and neurochaetal blades with guards approaching the distal tooth. The dorsal color pattern in life enables a clear distinction from similar species such as Hesione intertexta Grube, 1878 amongst others. Mitochondrial COI barcoding sequences are deposited in the DNA Data Bank of Japan. A key to Hesione species from Japan is also included.

Toxic effects of brominated indoles and phenols on zebrafish embryos.

PubMed

Kammann, U; Vobach, M; Wosniok, W

2006-07-01

Organobromine compounds in the marine environment have been the focus of growing attention in past years. In contrast to anthropogenic brominated flame retardants, other brominated compounds are produced naturally, e.g., by common polychaete worms and algae. Brominated phenols and indoles assumed to be of biogenic origin have been detected in water and sediment extracts from the German Bight. These substances as well as some of their isomers have been tested with the zebrafish embryo test and were found to cause lethal as well as nonlethal malformations. The zebrafish test was able to detect a log K(OW)-related toxicity for bromophenols, suggesting nonpolar narcosis as a major mode of action. Different effect patterns could be observed for brominated indoles and bromophenols. The comparison of effective concentrations in the zebrafish embryo test with the concentrations determined in water samples suggests the possibility that brominated indoles may affect early life stages of marine fish species in the North Sea.

Reciprocal experimental transplantations to assess effects of organic enrichment on the recolonization of benthic macrofauna in a subtropical estuary.

PubMed

Gern, Fabiana Regina; Lana, Paulo da Cunha

2013-02-15

Coastal benthic habitats are usually in a state of continuous recolonization as a consequence of natural disturbances or human activities. Recolonization patterns can be strongly affected by the quality of the sediment. We evaluated herein the macrobenthic recolonization of organically enriched sediments through a manipulative experiment involving reciprocal transplants between contaminated and non-contaminated intertidal areas. Regardless of the experimental treatments, the density of the polychaete Capitella sp. was extremely high in the contaminated area as well as the density of the gastropod Cylichna sp. in the non-contaminated area. We rejected the hypothesis that differences in sediment quality would determine macrofaunal recolonization at least in the considered scales of space in meters and time in weeks. The recolonization process in a subtropical estuarine environment was strongly dependent on the migration of adults present in the sediments adjacent to the experimental units. Copyright © 2012 Elsevier Ltd. All rights reserved.

Bioaccumulation and biotransformation of arsenic compounds in Hediste diversicolor (Muller 1776) after exposure to spiked sediments.

PubMed

Gaion, Andrea; Sartori, Davide; Scuderi, Alice; Fattorini, Daniele

2014-05-01

This study focused on the exposure of the common ragworm Hediste diversicolor (Müller 1776) to sediments enriched with different arsenic compounds, namely arsenate, dimethyl-arsinate, and arsenobetaine. Speciation analysis was carried out on both the spiked sediments and the exposed polychaetes in order to investigate H. diversicolor capability of arsenic bioaccumulation and biotransformation. Two levels of contamination (acute and moderate dose) were chosen for enriched sediments to investigate possible differences in the arsenic bioaccumulation patterns. The highest value of arsenic in tissues was reached after 15 days of exposure to dimethyl-arsinate (acute dose) spiked sediment (1,172 ± 176 μg/g). A significant increase was also obtained in worms exposed both to arsenate and arsenobetaine. Speciation analysis showed that trimethyl-arsine oxide was the predominant chemical form in tissues of H. diversicolor exposed to all the spiked sediments, confirming the importance of this intermediate in biological transformation of arsenic.

Goal-Directed Modulation of Neural Memory Patterns: Implications for fMRI-Based Memory Detection.

PubMed

Uncapher, Melina R; Boyd-Meredith, J Tyler; Chow, Tiffany E; Rissman, Jesse; Wagner, Anthony D

2015-06-03

Remembering a past event elicits distributed neural patterns that can be distinguished from patterns elicited when encountering novel information. These differing patterns can be decoded with relatively high diagnostic accuracy for individual memories using multivoxel pattern analysis (MVPA) of fMRI data. Brain-based memory detection--if valid and reliable--would have clear utility beyond the domain of cognitive neuroscience, in the realm of law, marketing, and beyond. However, a significant boundary condition on memory decoding validity may be the deployment of "countermeasures": strategies used to mask memory signals. Here we tested the vulnerability of fMRI-based memory detection to countermeasures, using a paradigm that bears resemblance to eyewitness identification. Participants were scanned while performing two tasks on previously studied and novel faces: (1) a standard recognition memory task; and (2) a task wherein they attempted to conceal their true memory state. Univariate analyses revealed that participants were able to strategically modulate neural responses, averaged across trials, in regions implicated in memory retrieval, including the hippocampus and angular gyrus. Moreover, regions associated with goal-directed shifts of attention and thought substitution supported memory concealment, and those associated with memory generation supported novelty concealment. Critically, whereas MVPA enabled reliable classification of memory states when participants reported memory truthfully, the ability to decode memory on individual trials was compromised, even reversing, during attempts to conceal memory. Together, these findings demonstrate that strategic goal states can be deployed to mask memory-related neural patterns and foil memory decoding technology, placing a significant boundary condition on their real-world utility. Copyright © 2015 the authors 0270-6474/15/358531-15$15.00/0.

Consciousness of Unification: The Mind-Matter Phallacy Bites the Dust

NASA Astrophysics Data System (ADS)

Beichler, James E.

A complete theoretical model of how consciousness arises in neural nets can be developed based on a mixed quantum/classical basis. Both mind and consciousness are multi-leveled scalar and vector electromagnetic complexity patterns, respectively, which emerge within all living organisms through the process of evolution. Like life, the mind and consciousness patterns extend throughout living organisms (bodies), but the neural nets and higher level groupings that distinguish higher levels of consciousness only exist in the brain so mind and consciousness have been traditionally associated with the brain alone. A close study of neurons and neural nets in the brain shows that the microtubules within axons are classical bio-magnetic inductors that emit and absorb electromagnetic pulses from each other. These pulses establish interference patterns that influence the quantized vector potential patterns of interstitial water molecules within the neurons as well as create the coherence within neurons and neural nets that scientists normally associate with more complex memories, thought processes and streams of thought. Memory storage and recall are guided by the microtubules and the actual memory patterns are stored as magnetic vector potential complexity patterns in the points of space at the quantum level occupied by the water molecules. This model also accounts for the plasticity of the brain and implies that mind and consciousness, like life itself, are the result of evolutionary processes. However, consciousness can evolve independent of an organism's birth genetics once it has evolved by normal bottom-up genetic processes and thus force a new type of top-down evolution on living organisms and species as a whole that can be explained by expanding the laws of thermodynamics to include orderly systems.

Unsupervised discrimination of patterns in spiking neural networks with excitatory and inhibitory synaptic plasticity

PubMed Central

Srinivasa, Narayan; Cho, Youngkwan

2014-01-01

A spiking neural network model is described for learning to discriminate among spatial patterns in an unsupervised manner. The network anatomy consists of source neurons that are activated by external inputs, a reservoir that resembles a generic cortical layer with an excitatory-inhibitory (EI) network and a sink layer of neurons for readout. Synaptic plasticity in the form of STDP is imposed on all the excitatory and inhibitory synapses at all times. While long-term excitatory STDP enables sparse and efficient learning of the salient features in inputs, inhibitory STDP enables this learning to be stable by establishing a balance between excitatory and inhibitory currents at each neuron in the network. The synaptic weights between source and reservoir neurons form a basis set for the input patterns. The neural trajectories generated in the reservoir due to input stimulation and lateral connections between reservoir neurons can be readout by the sink layer neurons. This activity is used for adaptation of synapses between reservoir and sink layer neurons. A new measure called the discriminability index (DI) is introduced to compute if the network can discriminate between old patterns already presented in an initial training session. The DI is also used to compute if the network adapts to new patterns without losing its ability to discriminate among old patterns. The final outcome is that the network is able to correctly discriminate between all patterns—both old and new. This result holds as long as inhibitory synapses employ STDP to continuously enable current balance in the network. The results suggest a possible direction for future investigation into how spiking neural networks could address the stability-plasticity question despite having continuous synaptic plasticity. PMID:25566045

Stability Switches, Hopf Bifurcations, and Spatio-temporal Patterns in a Delayed Neural Model with Bidirectional Coupling

NASA Astrophysics Data System (ADS)

Song, Yongli; Zhang, Tonghua; Tadé, Moses O.

2009-12-01

The dynamical behavior of a delayed neural network with bi-directional coupling is investigated by taking the delay as the bifurcating parameter. Some parameter regions are given for conditional/absolute stability and Hopf bifurcations by using the theory of functional differential equations. As the propagation time delay in the coupling varies, stability switches for the trivial solution are found. Conditions ensuring the stability and direction of the Hopf bifurcation are determined by applying the normal form theory and the center manifold theorem. We also discuss the spatio-temporal patterns of bifurcating periodic oscillations by using the symmetric bifurcation theory of delay differential equations combined with representation theory of Lie groups. In particular, we obtain that the spatio-temporal patterns of bifurcating periodic oscillations will alternate according to the change of the propagation time delay in the coupling, i.e., different ranges of delays correspond to different patterns of neural activities. Numerical simulations are given to illustrate the obtained results and show the existence of bursts in some interval of the time for large enough delay.

Sequence memory based on coherent spin-interaction neural networks.

PubMed

Xia, Min; Wong, W K; Wang, Zhijie

2014-12-01

Sequence information processing, for instance, the sequence memory, plays an important role on many functions of brain. In the workings of the human brain, the steady-state period is alterable. However, in the existing sequence memory models using heteroassociations, the steady-state period cannot be changed in the sequence recall. In this work, a novel neural network model for sequence memory with controllable steady-state period based on coherent spininteraction is proposed. In the proposed model, neurons fire collectively in a phase-coherent manner, which lets a neuron group respond differently to different patterns and also lets different neuron groups respond differently to one pattern. The simulation results demonstrating the performance of the sequence memory are presented. By introducing a new coherent spin-interaction sequence memory model, the steady-state period can be controlled by dimension parameters and the overlap between the input pattern and the stored patterns. The sequence storage capacity is enlarged by coherent spin interaction compared with the existing sequence memory models. Furthermore, the sequence storage capacity has an exponential relationship to the dimension of the neural network.

Neural crest apoptosis and the establishment of craniofacial pattern: an honorable death.

PubMed

Graham, A; Koentges, G; Lumsden, A

1996-01-01

During development of the vertebrate head neural crest cells emigrate from the hindbrain and populate the branchial arches, giving rise to distinct skeletal elements and muscle connective tissues in each arch. The production of neural crest from the hindbrain is discontinuous and crest cells destined for different arches, carrying different positional cues, are separated by regions of apoptosis centered on rhombomeres (r) 3 and r5. This cell death program is under the interactive control of the neighboring hindbrain segments. Both r3 and r5 produce large numbers of crest cells when freed from their flanking rhombomere, but when conjoined with their neighbor the cell death program is restored. Two key components of this program are Bmp 4 and msx-2, both of which are expressed in the apoptotic foci of r3 and r5 and which are also regulated by neighbor interactions. Importantly, the addition of recombinant Bmp 4 to isolated cultures of r3 and r5 induces the expression of Bmp 4 and msx-2 and restores the cell death program. This early neural crest segregation is maintained during development and it has profound effects upon the final craniofacial pattern. Even though crest cells from different axial origins will contribute to compound skeletal elements, these distinct populations do not intermingle. Furthermore head muscle connective tissues are exclusively anchored to skeletal domains arising from neural crest from the same axial level. Thus the discontinuous production of neural crest sculpts the crest into nonmixing streams and consequently ensures the fidelity of patterning.

Largely overlapping neuronal substrates of reactivity to drug, gambling, food and sexual cues: A comprehensive meta-analysis.

PubMed

Noori, Hamid R; Cosa Linan, Alejandro; Spanagel, Rainer

2016-09-01

Cue reactivity to natural and social rewards is essential for motivational behavior. However, cue reactivity to drug rewards can also elicit craving in addicted subjects. The degree to which drug and natural rewards share neural substrates is not known. The objective of this study is to conduct a comprehensive meta-analysis of neuroimaging studies on drug, gambling and natural stimuli (food and sex) to identify the common and distinct neural substrates of cue reactivity to drug and natural rewards. Neural cue reactivity studies were selected for the meta-analysis by means of activation likelihood estimations, followed by sensitivity and clustering analyses of averaged neuronal response patterns. Data from 176 studies (5573 individuals) suggests largely overlapping neural response patterns towards all tested reward modalities. Common cue reactivity to natural and drug rewards was expressed by bilateral neural responses within anterior cingulate gyrus, insula, caudate head, inferior frontal gyrus, middle frontal gyrus and cerebellum. However, drug cues also generated distinct activation patterns in medial frontal gyrus, middle temporal gyrus, posterior cingulate gyrus, caudate body and putamen. Natural (sexual) reward cues induced unique activation of the pulvinar in thalamus. Neural substrates of cue reactivity to alcohol, drugs of abuse, food, sex and gambling are largely overlapping and comprise a network that processes reward, emotional responses and habit formation. This suggests that cue-mediated craving involves mechanisms that are not exclusive for addictive disorders but rather resemble the intersection of information pathways for processing reward, emotional responses, non-declarative memory and obsessive-compulsive behavior. Copyright © 2016 Elsevier B.V. and ECNP. All rights reserved.

Artificial Neural Network approach to develop unique Classification and Raga identification tools for Pattern Recognition in Carnatic Music

NASA Astrophysics Data System (ADS)

Srimani, P. K.; Parimala, Y. G.

2011-12-01

A unique approach has been developed to study patterns in ragas of Carnatic Classical music based on artificial neural networks. Ragas in Carnatic music which have found their roots in the Vedic period, have grown on a Scientific foundation over thousands of years. However owing to its vastness and complexities it has always been a challenge for scientists and musicologists to give an all encompassing perspective both qualitatively and quantitatively. Cognition, comprehension and perception of ragas in Indian classical music have always been the subject of intensive research, highly intriguing and many facets of these are hitherto not unravelled. This paper is an attempt to view the melakartha ragas with a cognitive perspective using artificial neural network based approach which has given raise to very interesting results. The 72 ragas of the melakartha system were defined through the combination of frequencies occurring in each of them. The data sets were trained using several neural networks. 100% accurate pattern recognition and classification was obtained using linear regression, TLRN, MLP and RBF networks. Performance of the different network topologies, by varying various network parameters, were compared. Linear regression was found to be the best performing network.

Artificial neural network detects human uncertainty

NASA Astrophysics Data System (ADS)

Hramov, Alexander E.; Frolov, Nikita S.; Maksimenko, Vladimir A.; Makarov, Vladimir V.; Koronovskii, Alexey A.; Garcia-Prieto, Juan; Antón-Toro, Luis Fernando; Maestú, Fernando; Pisarchik, Alexander N.

2018-03-01

Artificial neural networks (ANNs) are known to be a powerful tool for data analysis. They are used in social science, robotics, and neurophysiology for solving tasks of classification, forecasting, pattern recognition, etc. In neuroscience, ANNs allow the recognition of specific forms of brain activity from multichannel EEG or MEG data. This makes the ANN an efficient computational core for brain-machine systems. However, despite significant achievements of artificial intelligence in recognition and classification of well-reproducible patterns of neural activity, the use of ANNs for recognition and classification of patterns in neural networks still requires additional attention, especially in ambiguous situations. According to this, in this research, we demonstrate the efficiency of application of the ANN for classification of human MEG trials corresponding to the perception of bistable visual stimuli with different degrees of ambiguity. We show that along with classification of brain states associated with multistable image interpretations, in the case of significant ambiguity, the ANN can detect an uncertain state when the observer doubts about the image interpretation. With the obtained results, we describe the possible application of ANNs for detection of bistable brain activity associated with difficulties in the decision-making process.

New roles for Nanos in neural cell fate determination revealed by studies in a cnidarian.

PubMed

Kanska, Justyna; Frank, Uri

2013-07-15

Nanos is a pan-metazoan germline marker, important for germ cell development and maintenance. In flies, Nanos also acts in posterior and neural development, but these functions have not been demonstrated experimentally in other animals. Using the cnidarian Hydractinia we have uncovered novel roles for Nanos in neural cell fate determination. Ectopic expression of Nanos2 increased the numbers of embryonic stinging cell progenitors, but decreased the numbers of neurons. Downregulation of Nanos2 had the opposite effect. Furthermore, Nanos2 blocked maturation of committed, post-mitotic nematoblasts. Hence, Nanos2 acts as a switch between two differentiation pathways, increasing the numbers of nematoblasts at the expense of neuroblasts, but preventing nematocyte maturation. Nanos2 ectopic expression also caused patterning defects, but these were not associated with deregulation of Wnt signaling, showing that the basic anterior-posterior polarity remained intact, and suggesting that numerical imbalance between nematocytes and neurons might have caused these defects, affecting axial patterning only indirectly. We propose that the functions of Nanos in germ cells and in neural development are evolutionarily conserved, but its role in posterior patterning is an insect or arthropod innovation.

Patterns of brain reorganization subsequent to left fusiform damage: fMRI evidence from visual processing of words and pseudowords, faces and objects.

PubMed

Tsapkini, Kyrana; Vindiola, Manuel; Rapp, Brenda

2011-04-01

Little is known about the neural reorganization that takes place subsequent to lesions that affect orthographic processing (reading and/or spelling). We report on an fMRI investigation of an individual with a left mid-fusiform resection that affected both reading and spelling (Tsapkini & Rapp, 2010). To investigate possible patterns of functional reorganization, we compared the behavioral and neural activation patterns of this individual with those of a group of control participants for the tasks of silent reading of words and pseudowords and the passive viewing of faces and objects, all tasks that typically recruit the inferior temporal lobes. This comparison was carried out with methods that included a novel application of Mahalanobis distance statistics, and revealed: (1) normal behavioral and neural responses for face and object processing, (2) evidence of neural reorganization bilaterally in the posterior fusiform that supported normal performance in pseudoword reading and which contributed to word reading (3) evidence of abnormal recruitment of the bilateral anterior temporal lobes indicating compensatory (albeit insufficient) recruitment of mechanisms for circumventing the word reading deficit. Copyright © 2010 Elsevier Inc. All rights reserved.

Development of neural network techniques for finger-vein pattern classification

NASA Astrophysics Data System (ADS)

Wu, Jian-Da; Liu, Chiung-Tsiung; Tsai, Yi-Jang; Liu, Jun-Ching; Chang, Ya-Wen

2010-02-01

A personal identification system using finger-vein patterns and neural network techniques is proposed in the present study. In the proposed system, the finger-vein patterns are captured by a device that can transmit near infrared through the finger and record the patterns for signal analysis and classification. The biometric system for verification consists of a combination of feature extraction using principal component analysis and pattern classification using both back-propagation network and adaptive neuro-fuzzy inference systems. Finger-vein features are first extracted by principal component analysis method to reduce the computational burden and removes noise residing in the discarded dimensions. The features are then used in pattern classification and identification. To verify the effect of the proposed adaptive neuro-fuzzy inference system in the pattern classification, the back-propagation network is compared with the proposed system. The experimental results indicated the proposed system using adaptive neuro-fuzzy inference system demonstrated a better performance than the back-propagation network for personal identification using the finger-vein patterns.

Edge-preserving image compression for magnetic-resonance images using dynamic associative neural networks (DANN)-based neural networks

NASA Astrophysics Data System (ADS)

Wan, Tat C.; Kabuka, Mansur R.

1994-05-01

With the tremendous growth in imaging applications and the development of filmless radiology, the need for compression techniques that can achieve high compression ratios with user specified distortion rates becomes necessary. Boundaries and edges in the tissue structures are vital for detection of lesions and tumors, which in turn requires the preservation of edges in the image. The proposed edge preserving image compressor (EPIC) combines lossless compression of edges with neural network compression techniques based on dynamic associative neural networks (DANN), to provide high compression ratios with user specified distortion rates in an adaptive compression system well-suited to parallel implementations. Improvements to DANN-based training through the use of a variance classifier for controlling a bank of neural networks speed convergence and allow the use of higher compression ratios for `simple' patterns. The adaptation and generalization capabilities inherent in EPIC also facilitate progressive transmission of images through varying the number of quantization levels used to represent compressed patterns. Average compression ratios of 7.51:1 with an averaged average mean squared error of 0.0147 were achieved.

Neural networks application to divergence-based passive ranging

NASA Technical Reports Server (NTRS)

Barniv, Yair

1992-01-01

The purpose of this report is to summarize the state of knowledge and outline the planned work in divergence-based/neural networks approach to the problem of passive ranging derived from optical flow. Work in this and closely related areas is reviewed in order to provide the necessary background for further developments. New ideas about devising a monocular passive-ranging system are then introduced. It is shown that image-plan divergence is independent of image-plan location with respect to the focus of expansion and of camera maneuvers because it directly measures the object's expansion which, in turn, is related to the time-to-collision. Thus, a divergence-based method has the potential of providing a reliable range complementing other monocular passive-ranging methods which encounter difficulties in image areas close to the focus of expansion. Image-plan divergence can be thought of as some spatial/temporal pattern. A neural network realization was chosen for this task because neural networks have generally performed well in various other pattern recognition applications. The main goal of this work is to teach a neural network to derive the divergence from the imagery.

Multivariate neural biomarkers of emotional states are categorically distinct.

PubMed

Kragel, Philip A; LaBar, Kevin S

2015-11-01

Understanding how emotions are represented neurally is a central aim of affective neuroscience. Despite decades of neuroimaging efforts addressing this question, it remains unclear whether emotions are represented as distinct entities, as predicted by categorical theories, or are constructed from a smaller set of underlying factors, as predicted by dimensional accounts. Here, we capitalize on multivariate statistical approaches and computational modeling to directly evaluate these theoretical perspectives. We elicited discrete emotional states using music and films during functional magnetic resonance imaging scanning. Distinct patterns of neural activation predicted the emotion category of stimuli and tracked subjective experience. Bayesian model comparison revealed that combining dimensional and categorical models of emotion best characterized the information content of activation patterns. Surprisingly, categorical and dimensional aspects of emotion experience captured unique and opposing sources of neural information. These results indicate that diverse emotional states are poorly differentiated by simple models of valence and arousal, and that activity within separable neural systems can be mapped to unique emotion categories. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

UniEnt: uniform entropy model for the dynamics of a neuronal population

NASA Astrophysics Data System (ADS)

Hernandez Lahme, Damian; Nemenman, Ilya

Sensory information and motor responses are encoded in the brain in a collective spiking activity of a large number of neurons. Understanding the neural code requires inferring statistical properties of such collective dynamics from multicellular neurophysiological recordings. Questions of whether synchronous activity or silence of multiple neurons carries information about the stimuli or the motor responses are especially interesting. Unfortunately, detection of such high order statistical interactions from data is especially challenging due to the exponentially large dimensionality of the state space of neural collectives. Here we present UniEnt, a method for the inference of strengths of multivariate neural interaction patterns. The method is based on the Bayesian prior that makes no assumptions (uniform a priori expectations) about the value of the entropy of the observed multivariate neural activity, in contrast to popular approaches that maximize this entropy. We then study previously published multi-electrode recordings data from salamander retina, exposing the relevance of higher order neural interaction patterns for information encoding in this system. This work was supported in part by Grants JSMF/220020321 and NSF/IOS/1208126.

Feature to prototype transition in neural networks

NASA Astrophysics Data System (ADS)

Krotov, Dmitry; Hopfield, John

Models of associative memory with higher order (higher than quadratic) interactions, and their relationship to neural networks used in deep learning are discussed. Associative memory is conventionally described by recurrent neural networks with dynamical convergence to stable points. Deep learning typically uses feedforward neural nets without dynamics. However, a simple duality relates these two different views when applied to problems of pattern classification. From the perspective of associative memory such models deserve attention because they make it possible to store a much larger number of memories, compared to the quadratic case. In the dual description, these models correspond to feedforward neural networks with one hidden layer and unusual activation functions transmitting the activities of the visible neurons to the hidden layer. These activation functions are rectified polynomials of a higher degree rather than the rectified linear functions used in deep learning. The network learns representations of the data in terms of features for rectified linear functions, but as the power in the activation function is increased there is a gradual shift to a prototype-based representation, the two extreme regimes of pattern recognition known in cognitive psychology. Simons Center for Systems Biology.

Neural-net Processed Electronic Holography for Rotating Machines

NASA Technical Reports Server (NTRS)

Decker, Arthur J.

2003-01-01

This report presents the results of an R&D effort to apply neural-net processed electronic holography to NDE of rotors. Electronic holography was used to generate characteristic patterns or mode shapes of vibrating rotors and rotor components. Artificial neural networks were trained to identify damage-induced changes in the characteristic patterns. The development and optimization of a neural-net training method were the most significant contributions of this work, and the training method and its optimization are discussed in detail. A second positive result was the assembly and testing of a fiber-optic holocamera. A major disappointment was the inadequacy of the high-speed-holography hardware selected for this effort, but the use of scaled holograms to match the low effective resolution of an image intensifier was one interesting attempt to compensate. This report also discusses in some detail the physics and environmental requirements for rotor electronic holography. The major conclusions were that neural-net and electronic-holography inspections of stationary components in the laboratory and the field are quite practical and worthy of continuing development, but that electronic holography of moving rotors is still an expensive high-risk endeavor.

Combinatorial Fgf and Bmp signalling patterns the gastrula ectoderm into prospective neural and epidermal domains

PubMed Central

Kudoh, Tetsuhiro; Concha, Miguel L.; Houart, Corinne; Dawid, Igor B.; Wilson, Stephen W.

2009-01-01

Summary Studies in fish and amphibia have shown that graded Bmp signalling activity regulates dorsal-to-ventral (DV) patterning of the gastrula embryo. In the ectoderm, it is thought that high levels of Bmp activity promote epidermal development ventrally, whereas secreted Bmp antagonists emanating from the organiser induce neural tissue dorsally. However, in zebrafish embryos, the domain of cells destined to contribute to the spinal cord extends all the way to the ventral side of the gastrula, a long way from the organiser. We show that in vegetal (trunk and tail) regions of the zebrafish gastrula, neural specification is initiated at all DV positions of the ectoderm in a manner that is unaffected by levels of Bmp activity and independent of organiser-derived signals. Instead, we find that Fgf activity is required to induce vegetal prospective neural markers and can do so without suppressing Bmp activity. We further show that Bmp signalling does occur within the vegetal prospective neural domain and that Bmp activity promotes the adoption of caudal fate by this tissue. PMID:15262889

Multi-voxel Patterns Reveal Functionally Differentiated Networks Underlying Auditory Feedback Processing of Speech

PubMed Central

Zheng, Zane Z.; Vicente-Grabovetsky, Alejandro; MacDonald, Ewen N.; Munhall, Kevin G.; Cusack, Rhodri; Johnsrude, Ingrid S.

2013-01-01

The everyday act of speaking involves the complex processes of speech motor control. An important component of control is monitoring, detection and processing of errors when auditory feedback does not correspond to the intended motor gesture. Here we show, using fMRI and converging operations within a multi-voxel pattern analysis framework, that this sensorimotor process is supported by functionally differentiated brain networks. During scanning, a real-time speech-tracking system was employed to deliver two acoustically different types of distorted auditory feedback or unaltered feedback while human participants were vocalizing monosyllabic words, and to present the same auditory stimuli while participants were passively listening. Whole-brain analysis of neural-pattern similarity revealed three functional networks that were differentially sensitive to distorted auditory feedback during vocalization, compared to during passive listening. One network of regions appears to encode an ‘error signal’ irrespective of acoustic features of the error: this network, including right angular gyrus, right supplementary motor area, and bilateral cerebellum, yielded consistent neural patterns across acoustically different, distorted feedback types, only during articulation (not during passive listening). In contrast, a fronto-temporal network appears sensitive to the speech features of auditory stimuli during passive listening; this preference for speech features was diminished when the same stimuli were presented as auditory concomitants of vocalization. A third network, showing a distinct functional pattern from the other two, appears to capture aspects of both neural response profiles. Taken together, our findings suggest that auditory feedback processing during speech motor control may rely on multiple, interactive, functionally differentiated neural systems. PMID:23467350

Context-dependent plasticity in the subcortical encoding of linguistic pitch patterns

PubMed Central

Lau, Joseph C. Y.; Wong, Patrick C. M.

2016-01-01

We examined the mechanics of online experience-dependent auditory plasticity by assessing the influence of prior context on the frequency-following responses (FFRs), which reflect phase-locked responses from neural ensembles within the subcortical auditory system. FFRs were elicited to a Cantonese falling lexical pitch pattern from 24 native speakers of Cantonese in a variable context, wherein the falling pitch pattern randomly occurred in the context of two other linguistic pitch patterns; in a patterned context, wherein, the falling pitch pattern was presented in a predictable sequence along with two other pitch patterns, and in a repetitive context, wherein the falling pitch pattern was presented with 100% probability. We found that neural tracking of the stimulus pitch contour was most faithful and accurate when listening context was patterned and least faithful when the listening context was variable. The patterned context elicited more robust pitch tracking relative to the repetitive context, suggesting that context-dependent plasticity is most robust when the context is predictable but not repetitive. Our study demonstrates a robust influence of prior listening context that works to enhance online neural encoding of linguistic pitch patterns. We interpret these results as indicative of an interplay between contextual processes that are responsive to predictability as well as novelty in the presentation context. NEW & NOTEWORTHY Human auditory perception in dynamic listening environments requires fine-tuning of sensory signal based on behaviorally relevant regularities in listening context, i.e., online experience-dependent plasticity. Our finding suggests what partly underlie online experience-dependent plasticity are interplaying contextual processes in the subcortical auditory system that are responsive to predictability as well as novelty in listening context. These findings add to the literature that looks to establish the neurophysiological bases of auditory system plasticity, a central issue in auditory neuroscience. PMID:27832606

Context-dependent plasticity in the subcortical encoding of linguistic pitch patterns.

PubMed

Lau, Joseph C Y; Wong, Patrick C M; Chandrasekaran, Bharath

2017-02-01

We examined the mechanics of online experience-dependent auditory plasticity by assessing the influence of prior context on the frequency-following responses (FFRs), which reflect phase-locked responses from neural ensembles within the subcortical auditory system. FFRs were elicited to a Cantonese falling lexical pitch pattern from 24 native speakers of Cantonese in a variable context, wherein the falling pitch pattern randomly occurred in the context of two other linguistic pitch patterns; in a patterned context, wherein, the falling pitch pattern was presented in a predictable sequence along with two other pitch patterns, and in a repetitive context, wherein the falling pitch pattern was presented with 100% probability. We found that neural tracking of the stimulus pitch contour was most faithful and accurate when listening context was patterned and least faithful when the listening context was variable. The patterned context elicited more robust pitch tracking relative to the repetitive context, suggesting that context-dependent plasticity is most robust when the context is predictable but not repetitive. Our study demonstrates a robust influence of prior listening context that works to enhance online neural encoding of linguistic pitch patterns. We interpret these results as indicative of an interplay between contextual processes that are responsive to predictability as well as novelty in the presentation context. Human auditory perception in dynamic listening environments requires fine-tuning of sensory signal based on behaviorally relevant regularities in listening context, i.e., online experience-dependent plasticity. Our finding suggests what partly underlie online experience-dependent plasticity are interplaying contextual processes in the subcortical auditory system that are responsive to predictability as well as novelty in listening context. These findings add to the literature that looks to establish the neurophysiological bases of auditory system plasticity, a central issue in auditory neuroscience. Copyright © 2017 the American Physiological Society.

Different dynamic resting state fMRI patterns are linked to different frequencies of neural activity

PubMed Central

Thompson, Garth John; Pan, Wen-Ju

2015-01-01

Resting state functional magnetic resonance imaging (rsfMRI) results have indicated that network mapping can contribute to understanding behavior and disease, but it has been difficult to translate the maps created with rsfMRI to neuroelectrical states in the brain. Recently, dynamic analyses have revealed multiple patterns in the rsfMRI signal that are strongly associated with particular bands of neural activity. To further investigate these findings, simultaneously recorded invasive electrophysiology and rsfMRI from rats were used to examine two types of electrical activity (directly measured low-frequency/infraslow activity and band-limited power of higher frequencies) and two types of dynamic rsfMRI (quasi-periodic patterns or QPP, and sliding window correlation or SWC). The relationship between neural activity and dynamic rsfMRI was tested under three anesthetic states in rats: dexmedetomidine and high and low doses of isoflurane. Under dexmedetomidine, the lightest anesthetic, infraslow electrophysiology correlated with QPP but not SWC, whereas band-limited power in higher frequencies correlated with SWC but not QPP. Results were similar under isoflurane; however, the QPP was also correlated to band-limited power, possibly due to the burst-suppression state induced by the anesthetic agent. The results provide additional support for the hypothesis that the two types of dynamic rsfMRI are linked to different frequencies of neural activity, but isoflurane anesthesia may make this relationship more complicated. Understanding which neural frequency bands appear as particular dynamic patterns in rsfMRI may ultimately help isolate components of the rsfMRI signal that are of interest to disorders such as schizophrenia and attention deficit disorder. PMID:26041826

Real-time cerebellar neuroprosthetic system based on a spiking neural network model of motor learning.

PubMed

Xu, Tao; Xiao, Na; Zhai, Xiaolong; Kwan Chan, Pak; Tin, Chung

2018-02-01

Damage to the brain, as a result of various medical conditions, impacts the everyday life of patients and there is still no complete cure to neurological disorders. Neuroprostheses that can functionally replace the damaged neural circuit have recently emerged as a possible solution to these problems. Here we describe the development of a real-time cerebellar neuroprosthetic system to substitute neural function in cerebellar circuitry for learning delay eyeblink conditioning (DEC). The system was empowered by a biologically realistic spiking neural network (SNN) model of the cerebellar neural circuit, which considers the neuronal population and anatomical connectivity of the network. The model simulated synaptic plasticity critical for learning DEC. This SNN model was carefully implemented on a field programmable gate array (FPGA) platform for real-time simulation. This hardware system was interfaced in in vivo experiments with anesthetized rats and it used neural spikes recorded online from the animal to learn and trigger conditioned eyeblink in the animal during training. This rat-FPGA hybrid system was able to process neuronal spikes in real-time with an embedded cerebellum model of ~10 000 neurons and reproduce learning of DEC with different inter-stimulus intervals. Our results validated that the system performance is physiologically relevant at both the neural (firing pattern) and behavioral (eyeblink pattern) levels. This integrated system provides the sufficient computation power for mimicking the cerebellar circuit in real-time. The system interacts with the biological system naturally at the spike level and can be generalized for including other neural components (neuron types and plasticity) and neural functions for potential neuroprosthetic applications.

Differential spatial activity patterns of acupuncture by a machine learning based analysis

NASA Astrophysics Data System (ADS)

You, Youbo; Bai, Lijun; Xue, Ting; Zhong, Chongguang; Liu, Zhenyu; Tian, Jie

2011-03-01

Acupoint specificity, lying at the core of the Traditional Chinese Medicine, underlies the theoretical basis of acupuncture application. However, recent studies have reported that acupuncture stimulation at nonacupoint and acupoint can both evoke similar signal intensity decreases in multiple regions. And these regions were spatially overlapped. We used a machine learning based Support Vector Machine (SVM) approach to elucidate the specific neural response pattern induced by acupuncture stimulation. Group analysis demonstrated that stimulation at two different acupoints (belong to the same nerve segment but different meridians) could elicit distinct neural response patterns. Our findings may provide evidence for acupoint specificity.

Alteration of neural action potential patterns by axonal stimulation: the importance of stimulus location.

PubMed

Crago, Patrick E; Makowski, Nathaniel S

2014-10-01

Stimulation of peripheral nerves is often superimposed on ongoing motor and sensory activity in the same axons, without a quantitative model of the net action potential train at the axon endpoint. We develop a model of action potential patterns elicited by superimposing constant frequency axonal stimulation on the action potentials arriving from a physiologically activated neural source. The model includes interactions due to collision block, resetting of the neural impulse generator, and the refractory period of the axon at the point of stimulation. Both the mean endpoint firing rate and the probability distribution of the action potential firing periods depend strongly on the relative firing rates of the two sources and the intersite conduction time between them. When the stimulus rate exceeds the neural rate, neural action potentials do not reach the endpoint and the rate of endpoint action potentials is the same as the stimulus rate, regardless of the intersite conduction time. However, when the stimulus rate is less than the neural rate, and the intersite conduction time is short, the two rates partially sum. Increases in stimulus rate produce non-monotonic increases in endpoint rate and continuously increasing block of neurally generated action potentials. Rate summation is reduced and more neural action potentials are blocked as the intersite conduction time increases. At long intersite conduction times, the endpoint rate simplifies to being the maximum of either the neural or the stimulus rate. This study highlights the potential of increasing the endpoint action potential rate and preserving neural information transmission by low rate stimulation with short intersite conduction times. Intersite conduction times can be decreased with proximal stimulation sites for muscles and distal stimulation sites for sensory endings. The model provides a basis for optimizing experiments and designing neuroprosthetic interventions involving motor or sensory stimulation.

Neural Mechanisms of Emotion.

ERIC Educational Resources Information Center

Derryberry, Douglas; Tucker, Don M.

1992-01-01

Views neural mechanisms of emotion from an evolutionary perspective, seeing them distributed across the brainstem, limbic, paralimbic, and neocortical regions. Discusses descending and ascending connections among these levels in relation to three types of emotional processes: peripheral effects on patterned bodily responses, central effects on…

Linking dynamic patterns of neural activity in orbitofrontal cortex with decision making.

PubMed

Rich, Erin L; Stoll, Frederic M; Rudebeck, Peter H

2018-04-01

Humans and animals demonstrate extraordinary flexibility in choice behavior, particularly when deciding based on subjective preferences. We evaluate options on different scales, deliberate, and often change our minds. Little is known about the neural mechanisms that underlie these dynamic aspects of decision-making, although neural activity in orbitofrontal cortex (OFC) likely plays a central role. Recent evidence from studies in macaques shows that attention modulates value responses in OFC, and that ensembles of OFC neurons dynamically signal different options during choices. When contexts change, these ensembles flexibly remap to encode the new task. Determining how these dynamic patterns emerge and relate to choices will inform models of decision-making and OFC function. Copyright © 2017 Elsevier Ltd. All rights reserved.

Terminal attractors in neural networks

NASA Technical Reports Server (NTRS)

Zak, Michail

1989-01-01

A new type of attractor (terminal attractors) for content-addressable memory, associative memory, and pattern recognition in artificial neural networks operating in continuous time is introduced. The idea of a terminal attractor is based upon a violation of the Lipschitz condition at a fixed point. As a result, the fixed point becomes a singular solution which envelopes the family of regular solutions, while each regular solution approaches such an attractor in finite time. It will be shown that terminal attractors can be incorporated into neural networks such that any desired set of these attractors with prescribed basins is provided by an appropriate selection of the synaptic weights. The applications of terminal attractors for content-addressable and associative memories, pattern recognition, self-organization, and for dynamical training are illustrated.

Pencil-and-Paper Neural Networks: An Undergraduate Laboratory Exercise in Computational Neuroscience

PubMed Central

Crisp, Kevin M.; Sutter, Ellen N.; Westerberg, Jacob A.

2015-01-01

Although it has been more than 70 years since McCulloch and Pitts published their seminal work on artificial neural networks, such models remain primarily in the domain of computer science departments in undergraduate education. This is unfortunate, as simple network models offer undergraduate students a much-needed bridge between cellular neurobiology and processes governing thought and behavior. Here, we present a very simple laboratory exercise in which students constructed, trained and tested artificial neural networks by hand on paper. They explored a variety of concepts, including pattern recognition, pattern completion, noise elimination and stimulus ambiguity. Learning gains were evident in changes in the use of language when writing about information processing in the brain. PMID:26557791

Silicon synaptic transistor for hardware-based spiking neural network and neuromorphic system

NASA Astrophysics Data System (ADS)

Kim, Hyungjin; Hwang, Sungmin; Park, Jungjin; Park, Byung-Gook

2017-10-01

Brain-inspired neuromorphic systems have attracted much attention as new computing paradigms for power-efficient computation. Here, we report a silicon synaptic transistor with two electrically independent gates to realize a hardware-based neural network system without any switching components. The spike-timing dependent plasticity characteristics of the synaptic devices are measured and analyzed. With the help of the device model based on the measured data, the pattern recognition capability of the hardware-based spiking neural network systems is demonstrated using the modified national institute of standards and technology handwritten dataset. By comparing systems with and without inhibitory synapse part, it is confirmed that the inhibitory synapse part is an essential element in obtaining effective and high pattern classification capability.

Silicon synaptic transistor for hardware-based spiking neural network and neuromorphic system.

PubMed

Kim, Hyungjin; Hwang, Sungmin; Park, Jungjin; Park, Byung-Gook

2017-10-06

Brain-inspired neuromorphic systems have attracted much attention as new computing paradigms for power-efficient computation. Here, we report a silicon synaptic transistor with two electrically independent gates to realize a hardware-based neural network system without any switching components. The spike-timing dependent plasticity characteristics of the synaptic devices are measured and analyzed. With the help of the device model based on the measured data, the pattern recognition capability of the hardware-based spiking neural network systems is demonstrated using the modified national institute of standards and technology handwritten dataset. By comparing systems with and without inhibitory synapse part, it is confirmed that the inhibitory synapse part is an essential element in obtaining effective and high pattern classification capability.

Probabilistic and Other Neural Nets in Multi-Hole Probe Calibration and Flow Angularity Pattern Recognition

NASA Technical Reports Server (NTRS)

Baskaran, Subbiah; Ramachandran, Narayanan; Noever, David

1998-01-01

The use of probabilistic (PNN) and multilayer feed forward (MLFNN) neural networks are investigated for calibration of multi-hole pressure probes and the prediction of associated flow angularity patterns in test flow fields. Both types of networks are studied in detail for their calibration and prediction characteristics. The current formalism can be applied to any multi-hole probe, however the test results for the most commonly used five-hole Cone and Prism probe types alone are reported in this article.

Size matters: The contribution of mega-infauna to the food webs and ecosystem services of an Oregon estuary - 9-30-12

EPA Science Inventory

Large-bodied invertebrates (bivalves, polychaetes, burrowing shrimps) are common to infaunal communities of NE Pacific estuaries, but their contribution to estuarine community structure, function and ecosystem services is poorly understood because they are difficult to sample and...

Size Matters: The Contribution of Mega-Infauna to the Food Webs and Ecosystem Services of an Oregon Estuary

EPA Science Inventory

Large-bodied, invertebrates are common to infaunal communities of NE Pacific estuaries (e.g., bivalves, polychaetes, burrowing shrimps), but their contribution to the ecological structure, function and ecosystem services of most estuaries has been poorly characterized because the...

INFLUENCE OF SOOT CARBON ON THE BIOACCULUMATION OF SEDIMENT-BOUND POLYCYCLIC AROMATIC HYDROCARBONS BY MARINE BENTHIC INVERTEBRATES: AN INTERSPECIES COMPARISON

EPA Science Inventory

The sorption of polycyclic aromatic hydrocarbons (PAHs) to soot carbon in marine sediments has been hypothesized to reduce PAH bioavailability. This hypothesis was tested for eight species of marine benthic invertebrates (four polychaete worms, Clymenella torquata, Nereis virens,...

Effects of Hypoxia on Animal Burrow Constraction and Consequent Effects on Sediment Redox Profiles (SETAC08)

EPA Science Inventory

We investigated the effects of mild hypoxia on the burrowing behavior of three marine species (the hard clam Mercenaria mercenaria, the polychaete worm Nereis virens, and the amphipod Leptocheirus plumulosus) and consequent effects on sediment redox profiles. Animals were introdu...

Effects of experimental otter trawling on benthic assemblages on Western Bank, northwest Atlantic Ocean

NASA Astrophysics Data System (ADS)

Kenchington, Ellen L. R.; Gilkinson, Kent D.; MacIsaac, Kevin G.; Bourbonnais-Boyce, Cynthia; Kenchington, Trevor J.; Smith, Stephen J.; Gordon, Donald C., Jr.

2006-10-01

The effects of otter trawling on a hard-bottom ecosystem on Western Bank on Canada's Scotian Shelf were examined experimentally from 1997 to 1999 with an asymmetrical BACI design. The site was located within an area that had been closed to fishing since 1987 to protect juvenile haddock. An experimental line was trawled 12-14 times on three separate occasions over a 20 month period. The benthic macrofauna and megafauna were sampled before and after trawling on both impact and control lines with both a grab and a photographic system. The 100 grab samples collected contained 341 taxa, primarily polychaetes, amphipods and molluscs, the majority (60%) of which were epifaunal. Biomass was dominated by the horse-mussel Modiolus modiolus, a long-lived bivalve, while the tube-building amphipod Ericthonius fasciatus was the most abundant species. Through the study period the benthos on the control lines showed little qualitative or quantitative change in individual taxa or community metrics. However, the abundance of 24 individual taxa (polychaetes, amphipods, echinoderms and molluscs) changed significantly, with the majority of these increasing. This resulted in a significantly different relative abundance of taxa between years as detected through ANOSIM. A significant change in relative biomass amongst the taxa was also observed. Trawling had few detectable immediate effects on the abundance or biomass of individual taxa and none on community composition. A few taxa, primarily a mixture of polychaetes and amphipods, decreased significantly after trawling and data from fish stomachs collected during the experiment (Kenchington, E.L., Gordon Jr., D.C., Bourbonnais-Boyce, C., MacIsaac, K.G., Gilkinson, K.D., McKeown, D.L., Vass, W.P., 2005. Effects of experimental otter trawling on the feeding of demersal fish on Western Bank, Nova Scotia. Amer. Fish. Soc. Symp. 41, 391-409) showed that some of these were scavenged by demersal fish. Fifteen taxa showed significant decreases after trawling when the cumulative effects of trawling were considered. As in the analyses of individual years the species affected were primarily high turn-over species such as polychaetes and amphipods. Dominance curves prepared for both control and impact samples before trawling in 1997 and after trawling in 1999 showed a marked decrease in the biomass values of the highest ranking taxa, particularly of the first species, M. modiolus, only on the impact line at the conclusion of the experiment. The proportion of epifaunal biomass also declined significantly from 90% to 77% on the impact line by the conclusion of the experiment. These changes are in part due to trawl-induced damage and subsequent predation by demersal fish of the top ranking species. Analysis of the photographic images showed that the three top-ranking species in terms of biomass, M. modiolus, the tube-building polychaete Thelepus cincinnatus, and the brachiopod Terebratulina septentrionalis, were visibly damaged more than other species by the trawl gear. Two of these species, M. modiolus and T. cincinnatus, were preyed upon by scavenging demersal fish. The use of multiple sampling devices at the experimental site (grab, photographic system reported here and trawl and fish stomachs reported by Kenchington, E.L., Gordon Jr., D.C., Bourbonnais-Boyce, C., MacIsaac, K.G., Gilkinson, K.D., McKeown, D.L., Vass, W.P., 2005. Effects of experimental otter trawling on the feeding of demersal fish on Western Bank, Nova Scotia. Amer. Fish. Soc. Symp. 41, 391-409) enabled us to link trawl-induced changes to the benthos to predation by demersal fish.

Photopolymerized materials and patterning for improved performance of neural prosthetics

NASA Astrophysics Data System (ADS)

Tuft, Bradley William

Neural prosthetics are used to replace or substantially augment remaining motor and sensory functions of neural pathways that were lost or damaged due to physical trauma, disease, or genetics. However, due to poor spatial signal resolution, neural prostheses fail to recapitulate the intimate, precise interactions inherent to neural networks. Designing materials and interfaces that direct de novo nerve growth to spatially specific stimulating elements is, therefore, a promising method to enhance signal specificity and performance of prostheses such as the successful cochlear implant (CI) and the developing retinal implant. In this work, the spatial and temporal reaction control inherent to photopolymerization was used to develop methods to generate micro and nanopatterned materials that direct neurite growth from prosthesis relevant neurons. In particular, neurite growth and directionality has been investigated in response to physical, mechanical, and chemical cues on photopolymerized surfaces. Spiral ganglion neurons (SGNs) serve as the primary neuronal model as they are the principal target for CI stimulation. The objective of the research is to rationally design materials that spatially direct neurite growth and to translate fundamental understanding of nerve cell-material interactions into methods of nerve regeneration that improve neural prosthetic performance. A rapid, single-step photopolymerization method was developed to fabricate micro and nanopatterned physical cues on methacrylate surfaces by selectively blocking light with photomasks. Feature height is readily tuned by modulating parameters of the photopolymerizaiton including initiator concentration and species, light intensity, separation distance from the photomask, and radiation exposure time. Alignment of neural elements increases significantly with increasing feature amplitude and constant periodicity, as well as with decreasing periodicity and constant amplitude. SGN neurite alignment strongly correlates with the maximum feature slope. Neurite alignment is compared on unpatterned, unidirectional, and multidirectional photopolymerized micropatterns. The effect of substrate rigidity on neurite alignment to physical cues was determined by maintaining equivalent pattern microfeatures, afforded by the reaction control of photopolymerization, while concomitantly altering the composition of several copolymer platforms to tune matrix stiffness. For each platform, neurite alignment to unidirectional patterns increases with increasing substrate rigidity. Interestingly, SGN neurites respond to material stiffness cues that are orders of magnitude higher (GPa) than what is typically ascribed to neural environments (kPa). Finally, neurite behavior at bioactive borders of various adhesion modulating molecules was evaluated on micropatterned materials to determine which cues took precedence in establishing neurite directionality. At low microfeatures aspect ratios, neurites align to the pattern direction but are then caused to turn and repel from or turn and align to bioactive borders. Conversely, physical cues dominate neurite path-finding as pattern feature slope increases, i.e. aspect ratio of sloping photopolymerized features increases, causing neurites to readily cross bioactive borders. The photopolymerization method developed in this work to generate micro and nanopatterned materials serves as an additional surface engineering tool that enables investigation of cell-material interactions including directed de novo neurite growth. The results of this interdisciplinary effort contribute substantially to polymer neural regeneration technology and will lead to development of advanced biomaterials that improve neural prosthetic tissue integration and performance by spatially directing nerve growth.

Ultrasonographic Diagnosis of Cirrhosis Based on Preprocessing Using Pyramid Recurrent Neural Network

NASA Astrophysics Data System (ADS)

Lu, Jianming; Liu, Jiang; Zhao, Xueqin; Yahagi, Takashi

In this paper, a pyramid recurrent neural network is applied to characterize the hepatic parenchymal diseases in ultrasonic B-scan texture. The cirrhotic parenchymal diseases are classified into 4 types according to the size of hypoechoic nodular lesions. The B-mode patterns are wavelet transformed , and then the compressed data are feed into a pyramid neural network to diagnose the type of cirrhotic diseases. Compared with the 3-layer neural networks, the performance of the proposed pyramid recurrent neural network is improved by utilizing the lower layer effectively. The simulation result shows that the proposed system is suitable for diagnosis of cirrhosis diseases.

Neural Substrates of Spontaneous Musical Performance: An fMRI Study of Jazz Improvisation

PubMed Central

Limb, Charles J.; Braun, Allen R.

2008-01-01

To investigate the neural substrates that underlie spontaneous musical performance, we examined improvisation in professional jazz pianists using functional MRI. By employing two paradigms that differed widely in musical complexity, we found that improvisation (compared to production of over-learned musical sequences) was consistently characterized by a dissociated pattern of activity in the prefrontal cortex: extensive deactivation of dorsolateral prefrontal and lateral orbital regions with focal activation of the medial prefrontal (frontal polar) cortex. Such a pattern may reflect a combination of psychological processes required for spontaneous improvisation, in which internally motivated, stimulus-independent behaviors unfold in the absence of central processes that typically mediate self-monitoring and conscious volitional control of ongoing performance. Changes in prefrontal activity during improvisation were accompanied by widespread activation of neocortical sensorimotor areas (that mediate the organization and execution of musical performance) as well as deactivation of limbic structures (that regulate motivation and emotional tone). This distributed neural pattern may provide a cognitive context that enables the emergence of spontaneous creative activity. PMID:18301756

Neural substrates of spontaneous musical performance: an FMRI study of jazz improvisation.

PubMed

Limb, Charles J; Braun, Allen R

2008-02-27

To investigate the neural substrates that underlie spontaneous musical performance, we examined improvisation in professional jazz pianists using functional MRI. By employing two paradigms that differed widely in musical complexity, we found that improvisation (compared to production of over-learned musical sequences) was consistently characterized by a dissociated pattern of activity in the prefrontal cortex: extensive deactivation of dorsolateral prefrontal and lateral orbital regions with focal activation of the medial prefrontal (frontal polar) cortex. Such a pattern may reflect a combination of psychological processes required for spontaneous improvisation, in which internally motivated, stimulus-independent behaviors unfold in the absence of central processes that typically mediate self-monitoring and conscious volitional control of ongoing performance. Changes in prefrontal activity during improvisation were accompanied by widespread activation of neocortical sensorimotor areas (that mediate the organization and execution of musical performance) as well as deactivation of limbic structures (that regulate motivation and emotional tone). This distributed neural pattern may provide a cognitive context that enables the emergence of spontaneous creative activity.

Cortical Development and Neuroplasticity in Auditory Neuropathy Spectrum Disorder

PubMed Central

Sharma, Anu; Cardon, Garrett

2015-01-01

Cortical development is dependent to a large extent on stimulus-driven input. Auditory Neuropathy Spectrum Disorder (ANSD) is a recently described form of hearing impairment where neural dys-synchrony is the predominant characteristic. Children with ANSD provide a unique platform to examine the effects of asynchronous and degraded afferent stimulation on cortical auditory neuroplasticity and behavioral processing of sound. In this review, we describe patterns of auditory cortical maturation in children with ANSD. The disruption of cortical maturation that leads to these various patterns includes high levels of intra-individual cortical variability and deficits in cortical phase synchronization of oscillatory neural responses. These neurodevelopmental changes, which are constrained by sensitive periods for central auditory maturation, are correlated with behavioral outcomes for children with ANSD. Overall, we hypothesize that patterns of cortical development in children with ANSD appear to be markers of the severity of the underlying neural dys-synchrony, providing prognostic indicators of success of clinical intervention with amplification and/or electrical stimulation. PMID:26070426

Emergence of an abstract categorical code enabling the discrimination of temporally structured tactile stimuli

PubMed Central

Rossi-Pool, Román; Salinas, Emilio; Zainos, Antonio; Alvarez, Manuel; Vergara, José; Parga, Néstor; Romo, Ranulfo

2016-01-01

The problem of neural coding in perceptual decision making revolves around two fundamental questions: (i) How are the neural representations of sensory stimuli related to perception, and (ii) what attributes of these neural responses are relevant for downstream networks, and how do they influence decision making? We studied these two questions by recording neurons in primary somatosensory (S1) and dorsal premotor (DPC) cortex while trained monkeys reported whether the temporal pattern structure of two sequential vibrotactile stimuli (of equal mean frequency) was the same or different. We found that S1 neurons coded the temporal patterns in a literal way and only during the stimulation periods and did not reflect the monkeys’ decisions. In contrast, DPC neurons coded the stimulus patterns as broader categories and signaled them during the working memory, comparison, and decision periods. These results show that the initial sensory representation is transformed into an intermediate, more abstract categorical code that combines past and present information to ultimately generate a perceptually informed choice. PMID:27872293

Dimensionality of brain networks linked to life-long individual differences in self-control.

PubMed

Berman, Marc G; Yourganov, Grigori; Askren, Mary K; Ayduk, Ozlem; Casey, B J; Gotlib, Ian H; Kross, Ethan; McIntosh, Anthony R; Strother, Stephen; Wilson, Nicole L; Zayas, Vivian; Mischel, Walter; Shoda, Yuichi; Jonides, John

2013-01-01

The ability to delay gratification in childhood has been linked to positive outcomes in adolescence and adulthood. Here we examine a subsample of participants from a seminal longitudinal study of self-control throughout a subject's life span. Self-control, first studied in children at age 4 years, is now re-examined 40 years later, on a task that required control over the contents of working memory. We examine whether patterns of brain activation on this task can reliably distinguish participants with consistently low and high self-control abilities (low versus high delayers). We find that low delayers recruit significantly higher-dimensional neural networks when performing the task compared with high delayers. High delayers are also more homogeneous as a group in their neural patterns compared with low delayers. From these brain patterns, we can predict with 71% accuracy, whether a participant is a high or low delayer. The present results suggest that dimensionality of neural networks is a biological predictor of self-control abilities.

An experimental vestibular neural prosthesis: design and preliminary results with rhesus monkeys stimulated with modulated pulses.

PubMed

Nie, Kaibao; Ling, Leo; Bierer, Steven M; Kaneko, Chris R S; Fuchs, Albert F; Oxford, Trey; Rubinstein, Jay T; Phillips, James O

2013-06-01

A vestibular neural prosthesis was designed on the basis of a cochlear implant for treatment of Meniere's disease and other vestibular disorders. Computer control software was developed to generate patterned pulse stimuli for exploring optimal parameters to activate the vestibular nerve. Two rhesus monkeys were implanted with the prototype vestibular prosthesis and they were behaviorally evaluated post implantation surgery. Horizontal and vertical eye movement responses to patterned electrical pulse stimulations were collected on both monkeys. Pulse amplitude modulated (PAM) and pulse rate modulated (PRM) trains were applied to the lateral canal of each implanted animal. Robust slow-phase nystagmus responses following the PAM or PRM modulation pattern were observed in both implanted monkeys in the direction consistent with the activation of the implanted canal. Both PAM and PRM pulse trains can elicit a significant amount of in-phase modulated eye velocity changes and they could potentially be used for efficiently coding head rotational signals in future vestibular neural prostheses.

The use of global image characteristics for neural network pattern recognitions

NASA Astrophysics Data System (ADS)

Kulyas, Maksim O.; Kulyas, Oleg L.; Loshkarev, Aleksey S.

2017-04-01

The recognition system is observed, where the information is transferred by images of symbols generated by a television camera. For descriptors of objects the coefficients of two-dimensional Fourier transformation generated in a special way. For solution of the task of classification the one-layer neural network trained on reference images is used. Fast learning of a neural network with a single neuron calculation of coefficients is applied.

Neural activity to intense positive versus negative stimuli can help differentiate bipolar disorder from unipolar major depressive disorder in depressed adolescents: a pilot fMRI study.

PubMed

Diler, Rasim Somer; de Almeida, Jorge Renner Cardoso; Ladouceur, Cecile; Birmaher, Boris; Axelson, David; Phillips, Mary

2013-12-30

Failure to distinguish bipolar depression (BDd) from the unipolar depression of major depressive disorder (UDd) in adolescents has significant clinical consequences. We aimed to identify differential patterns of functional neural activity in BDd versus UDd and employed two (fearful and happy) facial expression/ gender labeling functional magnetic resonance imaging (fMRI) experiments to study emotion processing in 10 BDd (8 females, mean age=15.1 ± 1.1) compared to age- and gender-matched 10 UDd and 10 healthy control (HC) adolescents who were age- and gender-matched to the BDd group. BDd adolescents, relative to UDd, showed significantly lower activity to both intense happy (e.g., insula and temporal cortex) and intense fearful faces (e.g., frontal precentral cortex). Although the neural regions recruited in each group were not the same, both BDd and UDd adolescents, relative to HC, showed significantly lower neural activity to intense happy and mild happy faces, but elevated neural activity to mild fearful faces. Our results indicated that patterns of neural activity to intense positive and negative emotional stimuli can help differentiate BDd from UDd in adolescents. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

A systematic review on the neural effects of music on emotion regulation: implications for music therapy practice.

PubMed

Moore, Kimberly Sena

2013-01-01

Emotion regulation (ER) is an internal process through which a person maintains a comfortable state of arousal by modulating one or more aspects of emotion. The neural correlates underlying ER suggest an interplay between cognitive control areas and areas involved in emotional reactivity. Although some studies have suggested that music may be a useful tool in ER, few studies have examined the links between music perception/production and the neural mechanisms that underlie ER and resulting implications for clinical music therapy treatment. Objectives of this systematic review were to explore and synthesize what is known about how music and music experiences impact neural structures implicated in ER, and to consider clinical implications of these findings for structuring music stimuli to facilitate ER. A comprehensive electronic database search resulted in 50 studies that met predetermined inclusion and exclusion criteria. Pertinent data related to the objective were extracted and study outcomes were analyzed and compared for trends and common findings. Results indicated there are certain music characteristics and experiences that produce desired and undesired neural activation patterns implicated in ER. Desired activation patterns occurred when listening to preferred and familiar music, when singing, and (in musicians) when improvising; undesired activation patterns arose when introducing complexity, dissonance, and unexpected musical events. Furthermore, the connection between music-influenced changes in attention and its link to ER was explored. Implications for music therapy practice are discussed and preliminary guidelines for how to use music to facilitate ER are shared.

Typology of nonlinear activity waves in a layered neural continuum.

PubMed

Koch, Paul; Leisman, Gerry

2006-04-01

Neural tissue, a medium containing electro-chemical energy, can amplify small increments in cellular activity. The growing disturbance, measured as the fraction of active cells, manifests as propagating waves. In a layered geometry with a time delay in synaptic signals between the layers, the delay is instrumental in determining the amplified wavelengths. The growth of the waves is limited by the finite number of neural cells in a given region of the continuum. As wave growth saturates, the resulting activity patterns in space and time show a variety of forms, ranging from regular monochromatic waves to highly irregular mixtures of different spatial frequencies. The type of wave configuration is determined by a number of parameters, including alertness and synaptic conditioning as well as delay. For all cases studied, using numerical solution of the nonlinear Wilson-Cowan (1973) equations, there is an interval in delay in which the wave mixing occurs. As delay increases through this interval, during a series of consecutive waves propagating through a continuum region, the activity within that region changes from a single-frequency to a multiple-frequency pattern and back again. The diverse spatio-temporal patterns give a more concrete form to several metaphors advanced over the years to attempt an explanation of cognitive phenomena: Activity waves embody the "holographic memory" (Pribram, 1991); wave mixing provides a plausible cause of the competition called "neural Darwinism" (Edelman, 1988); finally the consecutive generation of growing neural waves can explain the discontinuousness of "psychological time" (Stroud, 1955).

Understanding the dynamical control of animal movement

NASA Astrophysics Data System (ADS)

Edwards, Donald

2008-03-01

Over the last 50 years, neurophysiologists have described many neural circuits that transform sensory input into motor commands, while biomechanicians and behavioral biologists have described many patterns of animal movement that occur in response to sensory input. Attempts to link these two have been frustrated by our technical inability to record from the necessary neurons in a freely behaving animal. As a result, we don't know how these neural circuits function in the closed loop context of free behavior, where the sensory and motor context changes on a millisecond time-scale. To address this problem, we have developed a software package, AnimatLab (www.AnimatLab.com), that enables users to reconstruct an animal's body and its relevant neural circuits, to link them at the sensory and motor ends, and through simulation, to test their ability to reproduce appropriate patterns of the animal's movements in a simulated Newtonian world. A Windows-based program, AnimatLab consists of a neural editor, a body editor, a world editor, stimulus and recording facilities, neural and physics engines, and an interactive 3-D graphical display. We have used AnimatLab to study three patterns of behavior: the grasshopper jump, crayfish escape, and crayfish leg movements used in postural control, walking, reaching and grasping. In each instance, the simulation helped identify constraints on both nervous function and biomechanical performance that have provided the basis for new experiments. Colleagues elsewhere have begun to use AnimatLab to study control of paw movements in cats and postural control in humans. We have also used AnimatLab simulations to guide the development of an autonomous hexapod robot in which the neural control circuitry is downloaded to the robot from the test computer.

Aberrant transcriptional networks in step-wise neurogenesis of paroxysmal kinesigenic dyskinesia-induced pluripotent stem cells.

PubMed

Li, Chun; Ma, Yu; Zhang, Kunshan; Gu, Junjie; Tang, Fan; Chen, Shengdi; Cao, Li; Li, Siguang; Jin, Ying

2016-08-16

Paroxysmal kinesigenic dyskinesia (PKD) is an episodic movement disorder with autosomal-dominant inheritance and marked variability in clinical manifestations.Proline-rich transmembrane protein 2 (PRRT2) has been identified as a causative gene of PKD, but the molecular mechanism underlying the pathogenesis of PKD still remains a mystery. The phenotypes and transcriptional patterns of the PKD disease need further clarification. Here, we report the generation and neural differentiation of iPSC lines from two familial PKD patients with c.487C>T (p. Gln163X) and c.573dupT (p. Gly192Trpfs*8) PRRT2 mutations, respectively. Notably, an extremely lower efficiency in neural conversion from PKD-iPSCs than control-iPSCs is observed by a step-wise neural differentiation method of dual inhibition of SMAD signaling. Moreover, we show the high expression level of PRRT2 throughout the human brain and the expression pattern of PRRT2 in other human tissues for the first time. To gain molecular insight into the development of the disease, we conduct global gene expression profiling of PKD cells at four different stages of neural induction and identify altered gene expression patterns, which peculiarly reflect dysregulated neural transcriptome signatures and a differentiation tendency to mesodermal development, in comparison to control-iPSCs. Additionally, functional and signaling pathway analyses indicate significantly different cell fate determination between PKD-iPSCs and control-iPSCs. Together, the establishment of PKD-specific in vitro models and the illustration of transcriptome features in PKD cells would certainly help us with better understanding of the defects in neural conversion as well as further investigations in the pathogenesis of the PKD disease.

Differences in neural activation as a function of risk-taking task parameters.

PubMed

Congdon, Eliza; Bato, Angelica A; Schonberg, Tom; Mumford, Jeanette A; Karlsgodt, Katherine H; Sabb, Fred W; London, Edythe D; Cannon, Tyrone D; Bilder, Robert M; Poldrack, Russell A

2013-01-01

Despite evidence supporting a relationship between impulsivity and naturalistic risk-taking, the relationship of impulsivity with laboratory-based measures of risky decision-making remains unclear. One factor contributing to this gap in our understanding is the degree to which different risky decision-making tasks vary in their details. We conducted an fMRI investigation of the Angling Risk Task (ART), which is an improved behavioral measure of risky decision-making. In order to examine whether the observed pattern of neural activation was specific to the ART or generalizable, we also examined correlates of the Balloon Analog Risk Taking (BART) task in the same sample of 23 healthy adults. Exploratory analyses were conducted to examine the relationship between neural activation, performance, impulsivity and self-reported risk-taking. While activation in a valuation network was associated with reward tracking during the ART but not the BART, increased fronto-cingulate activation was seen during risky choice trials in the BART as compared to the ART. Thus, neural activation during risky decision-making trials differed between the two tasks, and this observation was likely driven by differences in task parameters, namely the absence vs. presence of ambiguity and/or stationary vs. increasing probability of loss on the ART and BART, respectively. Exploratory association analyses suggest that sensitivity of neural response to the magnitude of potential reward during the ART was associated with a suboptimal performance strategy, higher scores on a scale of dysfunctional impulsivity (DI) and a greater likelihood of engaging in risky behaviors, while this pattern was not seen for the BART. Our results suggest that the ART is decomposable and associated with distinct patterns of neural activation; this represents a preliminary step toward characterizing a behavioral measure of risky decision-making that may support a better understanding of naturalistic risk-taking.

Oscillatory patterns in temporal lobe reveal context reinstatement during memory search.

PubMed

Manning, Jeremy R; Polyn, Sean M; Baltuch, Gordon H; Litt, Brian; Kahana, Michael J

2011-08-02

Psychological theories of memory posit that when people recall a past event, they not only recover the features of the event itself, but also recover information associated with other events that occurred nearby in time. The events surrounding a target event, and the thoughts they evoke, may be considered to represent a context for the target event, helping to distinguish that event from similar events experienced at different times. The ability to reinstate this contextual information during memory search has been considered a hallmark of episodic, or event-based, memory. We sought to determine whether context reinstatement may be observed in electrical signals recorded from the human brain during episodic recall. Analyzing electrocorticographic recordings taken as 69 neurosurgical patients studied and recalled lists of words, we uncovered a neural signature of context reinstatement. Upon recalling a studied item, we found that the recorded patterns of brain activity were not only similar to the patterns observed when the item was studied, but were also similar to the patterns observed during study of neighboring list items, with similarity decreasing reliably with positional distance. The degree to which individual patients displayed this neural signature of context reinstatement was correlated with their tendency to recall neighboring list items successively. These effects were particularly strong in temporal lobe recordings. Our findings show that recalling a past event evokes a neural signature of the temporal context in which the event occurred, thus pointing to a neural basis for episodic memory.

Refinement and Pattern Formation in Neural Circuits by the Interaction of Traveling Waves with Spike-Timing Dependent Plasticity

PubMed Central

Bennett, James E. M.; Bair, Wyeth

2015-01-01

Traveling waves in the developing brain are a prominent source of highly correlated spiking activity that may instruct the refinement of neural circuits. A candidate mechanism for mediating such refinement is spike-timing dependent plasticity (STDP), which translates correlated activity patterns into changes in synaptic strength. To assess the potential of these phenomena to build useful structure in developing neural circuits, we examined the interaction of wave activity with STDP rules in simple, biologically plausible models of spiking neurons. We derive an expression for the synaptic strength dynamics showing that, by mapping the time dependence of STDP into spatial interactions, traveling waves can build periodic synaptic connectivity patterns into feedforward circuits with a broad class of experimentally observed STDP rules. The spatial scale of the connectivity patterns increases with wave speed and STDP time constants. We verify these results with simulations and demonstrate their robustness to likely sources of noise. We show how this pattern formation ability, which is analogous to solutions of reaction-diffusion systems that have been widely applied to biological pattern formation, can be harnessed to instruct the refinement of postsynaptic receptive fields. Our results hold for rich, complex wave patterns in two dimensions and over several orders of magnitude in wave speeds and STDP time constants, and they provide predictions that can be tested under existing experimental paradigms. Our model generalizes across brain areas and STDP rules, allowing broad application to the ubiquitous occurrence of traveling waves and to wave-like activity patterns induced by moving stimuli. PMID:26308406

Refinement and Pattern Formation in Neural Circuits by the Interaction of Traveling Waves with Spike-Timing Dependent Plasticity.

PubMed

Bennett, James E M; Bair, Wyeth

2015-08-01

Traveling waves in the developing brain are a prominent source of highly correlated spiking activity that may instruct the refinement of neural circuits. A candidate mechanism for mediating such refinement is spike-timing dependent plasticity (STDP), which translates correlated activity patterns into changes in synaptic strength. To assess the potential of these phenomena to build useful structure in developing neural circuits, we examined the interaction of wave activity with STDP rules in simple, biologically plausible models of spiking neurons. We derive an expression for the synaptic strength dynamics showing that, by mapping the time dependence of STDP into spatial interactions, traveling waves can build periodic synaptic connectivity patterns into feedforward circuits with a broad class of experimentally observed STDP rules. The spatial scale of the connectivity patterns increases with wave speed and STDP time constants. We verify these results with simulations and demonstrate their robustness to likely sources of noise. We show how this pattern formation ability, which is analogous to solutions of reaction-diffusion systems that have been widely applied to biological pattern formation, can be harnessed to instruct the refinement of postsynaptic receptive fields. Our results hold for rich, complex wave patterns in two dimensions and over several orders of magnitude in wave speeds and STDP time constants, and they provide predictions that can be tested under existing experimental paradigms. Our model generalizes across brain areas and STDP rules, allowing broad application to the ubiquitous occurrence of traveling waves and to wave-like activity patterns induced by moving stimuli.

Denoising by coupled partial differential equations and extracting phase by backpropagation neural networks for electronic speckle pattern interferometry.

PubMed

Tang, Chen; Lu, Wenjing; Chen, Song; Zhang, Zhen; Li, Botao; Wang, Wenping; Han, Lin

2007-10-20

We extend and refine previous work [Appl. Opt. 46, 2907 (2007)]. Combining the coupled nonlinear partial differential equations (PDEs) denoising model with the ordinary differential equations enhancement method, we propose the new denoising and enhancing model for electronic speckle pattern interferometry (ESPI) fringe patterns. Meanwhile, we propose the backpropagation neural networks (BPNN) method to obtain unwrapped phase values based on a skeleton map instead of traditional interpolations. We test the introduced methods on the computer-simulated speckle ESPI fringe patterns and experimentally obtained fringe pattern, respectively. The experimental results show that the coupled nonlinear PDEs denoising model is capable of effectively removing noise, and the unwrapped phase values obtained by the BPNN method are much more accurate than those obtained by the well-known traditional interpolation. In addition, the accuracy of the BPNN method is adjustable by changing the parameters of networks such as the number of neurons.

Neural Language Processing in Adolescent First-Language Learners

PubMed Central

Ferjan Ramirez, Naja; Leonard, Matthew K.; Torres, Christina; Hatrak, Marla; Halgren, Eric; Mayberry, Rachel I.

2014-01-01

The relation between the timing of language input and development of neural organization for language processing in adulthood has been difficult to tease apart because language is ubiquitous in the environment of nearly all infants. However, within the congenitally deaf population are individuals who do not experience language until after early childhood. Here, we investigated the neural underpinnings of American Sign Language (ASL) in 2 adolescents who had no sustained language input until they were approximately 14 years old. Using anatomically constrained magnetoencephalography, we found that recently learned signed words mainly activated right superior parietal, anterior occipital, and dorsolateral prefrontal areas in these 2 individuals. This spatiotemporal activity pattern was significantly different from the left fronto-temporal pattern observed in young deaf adults who acquired ASL from birth, and from that of hearing young adults learning ASL as a second language for a similar length of time as the cases. These results provide direct evidence that the timing of language experience over human development affects the organization of neural language processing. PMID:23696277

Computer interpretation of thallium SPECT studies based on neural network analysis

NASA Astrophysics Data System (ADS)

Wang, David C.; Karvelis, K. C.

1991-06-01

A class of artificial intelligence (Al) programs known as neural networks are well suited to pattern recognition. A neural network is trained rather than programmed to recognize patterns. This differs from "expert system" Al programs in that it is not following an extensive set of rules determined by the programmer, but rather bases its decision on a gestalt interpretation of the image. The "bullseye" images from cardiac stress thallium tests performed on 50 male patients, as well as several simulated images were used to train the network. The network was able to accurately classify all patients in the training set. The network was then tested against 50 unknown patients and was able to correctly categorize 77% of the areas of ischemia and 92% of the areas of infarction. While not yet matching the ability of a trained physician, the neural network shows great promise in this area and has potential application in other areas of medical imaging.

Shared neural circuits for mentalizing about the self and others.

PubMed

Lombardo, Michael V; Chakrabarti, Bhismadev; Bullmore, Edward T; Wheelwright, Sally J; Sadek, Susan A; Suckling, John; Baron-Cohen, Simon

2010-07-01

Although many examples exist for shared neural representations of self and other, it is unknown how such shared representations interact with the rest of the brain. Furthermore, do high-level inference-based shared mentalizing representations interact with lower level embodied/simulation-based shared representations? We used functional neuroimaging (fMRI) and a functional connectivity approach to assess these questions during high-level inference-based mentalizing. Shared mentalizing representations in ventromedial prefrontal cortex, posterior cingulate/precuneus, and temporo-parietal junction (TPJ) all exhibited identical functional connectivity patterns during mentalizing of both self and other. Connectivity patterns were distributed across low-level embodied neural systems such as the frontal operculum/ventral premotor cortex, the anterior insula, the primary sensorimotor cortex, and the presupplementary motor area. These results demonstrate that identical neural circuits are implementing processes involved in mentalizing of both self and other and that the nature of such processes may be the integration of low-level embodied processes within higher level inference-based mentalizing.

Cognon Neural Model Software Verification and Hardware Implementation Design

NASA Astrophysics Data System (ADS)

Haro Negre, Pau

Little is known yet about how the brain can recognize arbitrary sensory patterns within milliseconds using neural spikes to communicate information between neurons. In a typical brain there are several layers of neurons, with each neuron axon connecting to ˜104 synapses of neurons in an adjacent layer. The information necessary for cognition is contained in theses synapses, which strengthen during the learning phase in response to newly presented spike patterns. Continuing on the model proposed in "Models for Neural Spike Computation and Cognition" by David H. Staelin and Carl H. Staelin, this study seeks to understand cognition from an information theoretic perspective and develop potential models for artificial implementation of cognition based on neuronal models. To do so we focus on the mathematical properties and limitations of spike-based cognition consistent with existing neurological observations. We validate the cognon model through software simulation and develop concepts for an optical hardware implementation of a network of artificial neural cognons.

A mixed-signal implementation of a polychronous spiking neural network with delay adaptation

PubMed Central

Wang, Runchun M.; Hamilton, Tara J.; Tapson, Jonathan C.; van Schaik, André

2014-01-01

We present a mixed-signal implementation of a re-configurable polychronous spiking neural network capable of storing and recalling spatio-temporal patterns. The proposed neural network contains one neuron array and one axon array. Spike Timing Dependent Delay Plasticity is used to fine-tune delays and add dynamics to the network. In our mixed-signal implementation, the neurons and axons have been implemented as both analog and digital circuits. The system thus consists of one FPGA, containing the digital neuron array and the digital axon array, and one analog IC containing the analog neuron array and the analog axon array. The system can be easily configured to use different combinations of each. We present and discuss the experimental results of all combinations of the analog and digital axon arrays and the analog and digital neuron arrays. The test results show that the proposed neural network is capable of successfully recalling more than 85% of stored patterns using both analog and digital circuits. PMID:24672422

A mixed-signal implementation of a polychronous spiking neural network with delay adaptation.

PubMed

Wang, Runchun M; Hamilton, Tara J; Tapson, Jonathan C; van Schaik, André

2014-01-01

We present a mixed-signal implementation of a re-configurable polychronous spiking neural network capable of storing and recalling spatio-temporal patterns. The proposed neural network contains one neuron array and one axon array. Spike Timing Dependent Delay Plasticity is used to fine-tune delays and add dynamics to the network. In our mixed-signal implementation, the neurons and axons have been implemented as both analog and digital circuits. The system thus consists of one FPGA, containing the digital neuron array and the digital axon array, and one analog IC containing the analog neuron array and the analog axon array. The system can be easily configured to use different combinations of each. We present and discuss the experimental results of all combinations of the analog and digital axon arrays and the analog and digital neuron arrays. The test results show that the proposed neural network is capable of successfully recalling more than 85% of stored patterns using both analog and digital circuits.

Artificial Neural Networks for Processing Graphs with Application to Image Understanding: A Survey

NASA Astrophysics Data System (ADS)

Bianchini, Monica; Scarselli, Franco

In graphical pattern recognition, each data is represented as an arrangement of elements, that encodes both the properties of each element and the relations among them. Hence, patterns are modelled as labelled graphs where, in general, labels can be attached to both nodes and edges. Artificial neural networks able to process graphs are a powerful tool for addressing a great variety of real-world problems, where the information is naturally organized in entities and relationships among entities and, in fact, they have been widely used in computer vision, f.i. in logo recognition, in similarity retrieval, and for object detection. In this chapter, we propose a survey of neural network models able to process structured information, with a particular focus on those architectures tailored to address image understanding applications. Starting from the original recursive model (RNNs), we subsequently present different ways to represent images - by trees, forests of trees, multiresolution trees, directed acyclic graphs with labelled edges, general graphs - and, correspondingly, neural network architectures appropriate to process such structures.

Real-time cerebellar neuroprosthetic system based on a spiking neural network model of motor learning

NASA Astrophysics Data System (ADS)

Xu, Tao; Xiao, Na; Zhai, Xiaolong; Chan, Pak Kwan; Tin, Chung

2018-02-01

Objective. Damage to the brain, as a result of various medical conditions, impacts the everyday life of patients and there is still no complete cure to neurological disorders. Neuroprostheses that can functionally replace the damaged neural circuit have recently emerged as a possible solution to these problems. Here we describe the development of a real-time cerebellar neuroprosthetic system to substitute neural function in cerebellar circuitry for learning delay eyeblink conditioning (DEC). Approach. The system was empowered by a biologically realistic spiking neural network (SNN) model of the cerebellar neural circuit, which considers the neuronal population and anatomical connectivity of the network. The model simulated synaptic plasticity critical for learning DEC. This SNN model was carefully implemented on a field programmable gate array (FPGA) platform for real-time simulation. This hardware system was interfaced in in vivo experiments with anesthetized rats and it used neural spikes recorded online from the animal to learn and trigger conditioned eyeblink in the animal during training. Main results. This rat-FPGA hybrid system was able to process neuronal spikes in real-time with an embedded cerebellum model of ~10 000 neurons and reproduce learning of DEC with different inter-stimulus intervals. Our results validated that the system performance is physiologically relevant at both the neural (firing pattern) and behavioral (eyeblink pattern) levels. Significance. This integrated system provides the sufficient computation power for mimicking the cerebellar circuit in real-time. The system interacts with the biological system naturally at the spike level and can be generalized for including other neural components (neuron types and plasticity) and neural functions for potential neuroprosthetic applications.

The neural basis of visual word form processing: a multivariate investigation.

PubMed

Nestor, Adrian; Behrmann, Marlene; Plaut, David C

2013-07-01

Current research on the neurobiological bases of reading points to the privileged role of a ventral cortical network in visual word processing. However, the properties of this network and, in particular, its selectivity for orthographic stimuli such as words and pseudowords remain topics of significant debate. Here, we approached this issue from a novel perspective by applying pattern-based analyses to functional magnetic resonance imaging data. Specifically, we examined whether, where and how, orthographic stimuli elicit distinct patterns of activation in the human cortex. First, at the category level, multivariate mapping found extensive sensitivity throughout the ventral cortex for words relative to false-font strings. Secondly, at the identity level, the multi-voxel pattern classification provided direct evidence that different pseudowords are encoded by distinct neural patterns. Thirdly, a comparison of pseudoword and face identification revealed that both stimulus types exploit common neural resources within the ventral cortical network. These results provide novel evidence regarding the involvement of the left ventral cortex in orthographic stimulus processing and shed light on its selectivity and discriminability profile. In particular, our findings support the existence of sublexical orthographic representations within the left ventral cortex while arguing for the continuity of reading with other visual recognition skills.

Neural Correlates of Sexual Orientation in Heterosexual, Bisexual, and Homosexual Men

PubMed Central

Safron, Adam; Sylva, David; Klimaj, Victoria; Rosenthal, A. M.; Li, Meng; Walter, Martin; Bailey, J. Michael

2017-01-01

Studies of subjective and genital sexual arousal in monosexual (i.e. heterosexual and homosexual) men have repeatedly found that erotic stimuli depicting men’s preferred sex produce strong responses, whereas erotic stimuli depicting the other sex produce much weaker responses. Inconsistent results have previously been obtained in bisexual men, who have sometimes demonstrated distinctly bisexual responses, but other times demonstrated patterns more similar to those observed in monosexual men. We used fMRI to investigate neural correlates of responses to erotic pictures and videos in heterosexual, bisexual, and homosexual men, ages 25–50. Sixty participants were included in video analyses, and 62 were included in picture analyses. We focused on the ventral striatum (VS), due to its association with incentive motivation. Patterns were consistent with sexual orientation, with heterosexual and homosexual men showing female-favoring and male-favoring responses, respectively. Bisexual men tended to show less differentiation between male and female stimuli. Consistent patterns were observed in the whole brain, including the VS, and also in additional regions such as occipitotemporal, anterior cingulate, and orbitofrontal cortices. This study extends previous findings of gender-specific neural responses in monosexual men, and provides initial evidence for distinct brain activity patterns in bisexual men. PMID:28145518

Limited Transfer of Newly Acquired Movement Patterns across Walking and Running in Humans

PubMed Central

Ogawa, Tetsuya; Kawashima, Noritaka; Ogata, Toru; Nakazawa, Kimitaka

2012-01-01

The two major modes of locomotion in humans, walking and running, may be regarded as a function of different speed (walking as slower and running as faster). Recent results using motor learning tasks in humans, as well as more direct evidence from animal models, advocate for independence in the neural control mechanisms underlying different locomotion tasks. In the current study, we investigated the possible independence of the neural mechanisms underlying human walking and running. Subjects were tested on a split-belt treadmill and adapted to walking or running on an asymmetrically driven treadmill surface. Despite the acquisition of asymmetrical movement patterns in the respective modes, the emergence of asymmetrical movement patterns in the subsequent trials was evident only within the same modes (walking after learning to walk and running after learning to run) and only partial in the opposite modes (walking after learning to run and running after learning to walk) (thus transferred only limitedly across the modes). Further, the storage of the acquired movement pattern in each mode was maintained independently of the opposite mode. Combined, these results provide indirect evidence for independence in the neural control mechanisms underlying the two locomotive modes. PMID:23029490