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4. Neural Distributed Autoassociative Memories: A Survey

Author

Gritsenko, V. I., Rachkovskij, D. A., Frolov, A. A., Gayler, R., Kleyko, D., and Osipov, E.

Subjects
Computer Science - Neural and Evolutionary Computing
Abstract

Introduction. Neural network models of autoassociative, distributed memory allow storage and retrieval of many items (vectors) where the number of stored items can exceed the vector dimension (the number of neurons in the network). This opens the possibility of a sublinear time search (in the number of stored items) for approximate nearest neighbors among vectors of high dimension. The purpose of this paper is to review models of autoassociative, distributed memory that can be naturally implemented by neural networks (mainly with local learning rules and iterative dynamics based on information locally available to neurons). Scope. The survey is focused mainly on the networks of Hopfield, Willshaw and Potts, that have connections between pairs of neurons and operate on sparse binary vectors. We discuss not only autoassociative memory, but also the generalization properties of these networks. We also consider neural networks with higher-order connections and networks with a bipartite graph structure for non-binary data with linear constraints. Conclusions. In conclusion we discuss the relations to similarity search, advantages and drawbacks of these techniques, and topics for further research. An interesting and still not completely resolved question is whether neural autoassociative memories can search for approximate nearest neighbors faster than other index structures for similarity search, in particular for the case of very high dimensional vectors., Comment: 31 pages

Published
2017
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27. Brain aging in major depressive disorder: results from the ENIGMA major depressive disorder working group

Author

Han, L.K.M., Dinga, R., Hahn, T., Ching, C.R., Eyler, L.T., Aftanas, L., Aghajani, M., Aleman, A., Baune, B.T., Berger, K., Brak, I., Filho, G.B., Carballedo, A., Connolly, C.G., Couvy-Duchesne, B., Cullen, K.R., Dannlowski, U., Davey, C.G., Dima, D., Duran, F.L.S., Enneking, V., Filimonova, E., Frenzel, S., Frodl, T., Fu, C.H.Y., Godlewska, B.R., Gotlib, I.H., Grabe, H.J., Groenewold, N.A., Grotegerd, D., Gruber, O., Hall, G.B., Harrison, B.J., Hatton, S.N., Hermesdorf, M., Hickie, I.B., Ho, T.C., Hosten, N., Jansen, Andreas, Kähler, C., Kircher, T., Klimes-Dougan, B., Krämer, B., Krug, A., Lagopoulos, J., Leenings, R., MacMaster, F.P., MacQueen, G., McIntosh, A., McLellan, Q., McMahon, K.L., Medland, S.E., Mueller, B.A., Mwangi, B., Osipov, E., Portella, M.J., Pozzi, E., Reneman, L., Repple, J., Rosa, P.G., Sacchet, M.D., Sämann, P.G., Schnell, K., Schrantee, A., Simulionyte, E., Soares, J.C., Sommer, J., Stein, D.J., Steinsträter, O., Strike, L.T., Thomopoulos, S.I., Tol, M.J.D. van, Veer, I.M., Vermeiren, R., Walter, H., Wee, N.J.A. van der, Werff, S.J.A. van der, Whalley, H., Winter, N.R., Wittfeld, K., Wright, M.J., Wu, M.J., Völzke, H., Yang, T.T., Zannias, V., Zubicaray, G.I. de, Zunta-Soares, G.B., Abé, C., Alda, M., Andreassen, O.A., Bøen, E., Bonnin, C.M., Canales-Rodriguez, E.J., Cannon, D., Caseras, X., Chaim-Avancini, T.M., Elvsåshagen, T., Favre, P., Foley, S.F., Fullerton, J.M., Ruhé, H.G., Schene, A.H., Marquand, A.F., Cole, J., Schmaal, L., Han, L.K.M., Dinga, R., Hahn, T., Ching, C.R., Eyler, L.T., Aftanas, L., Aghajani, M., Aleman, A., Baune, B.T., Berger, K., Brak, I., Filho, G.B., Carballedo, A., Connolly, C.G., Couvy-Duchesne, B., Cullen, K.R., Dannlowski, U., Davey, C.G., Dima, D., Duran, F.L.S., Enneking, V., Filimonova, E., Frenzel, S., Frodl, T., Fu, C.H.Y., Godlewska, B.R., Gotlib, I.H., Grabe, H.J., Groenewold, N.A., Grotegerd, D., Gruber, O., Hall, G.B., Harrison, B.J., Hatton, S.N., Hermesdorf, M., Hickie, I.B., Ho, T.C., Hosten, N., Jansen, Andreas, Kähler, C., Kircher, T., Klimes-Dougan, B., Krämer, B., Krug, A., Lagopoulos, J., Leenings, R., MacMaster, F.P., MacQueen, G., McIntosh, A., McLellan, Q., McMahon, K.L., Medland, S.E., Mueller, B.A., Mwangi, B., Osipov, E., Portella, M.J., Pozzi, E., Reneman, L., Repple, J., Rosa, P.G., Sacchet, M.D., Sämann, P.G., Schnell, K., Schrantee, A., Simulionyte, E., Soares, J.C., Sommer, J., Stein, D.J., Steinsträter, O., Strike, L.T., Thomopoulos, S.I., Tol, M.J.D. van, Veer, I.M., Vermeiren, R., Walter, H., Wee, N.J.A. van der, Werff, S.J.A. van der, Whalley, H., Winter, N.R., Wittfeld, K., Wright, M.J., Wu, M.J., Völzke, H., Yang, T.T., Zannias, V., Zubicaray, G.I. de, Zunta-Soares, G.B., Abé, C., Alda, M., Andreassen, O.A., Bøen, E., Bonnin, C.M., Canales-Rodriguez, E.J., Cannon, D., Caseras, X., Chaim-Avancini, T.M., Elvsåshagen, T., Favre, P., Foley, S.F., Fullerton, J.M., Ruhé, H.G., Schene, A.H., Marquand, A.F., Cole, J., and Schmaal, L.

Abstract

Item does not contain fulltext, Major depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced brain aging in adult MDD patients, and whether this process is associated with clinical characteristics in a large multicenter international dataset. We performed a mega-analysis by pooling brain measures derived from T1-weighted MRI scans from 19 samples worldwide. Healthy brain aging was estimated by predicting chronological age (18-75 years) from 7 subcortical volumes, 34 cortical thickness and 34 surface area, lateral ventricles and total intracranial volume measures separately in 952 male and 1236 female controls from the ENIGMA MDD working group. The learned model coefficients were applied to 927 male controls and 986 depressed males, and 1199 female controls and 1689 depressed females to obtain independent unbiased brain-based age predictions. The difference between predicted "brain age" and chronological age was calculated to indicate brain-predicted age difference (brain-PAD). On average, MDD patients showed a higher brain-PAD of +1.08 (SE 0.22) years (Cohen's d = 0.14, 95% CI: 0.08-0.20) compared with controls. However, this difference did not seem to be driven by specific clinical characteristics (recurrent status, remission status, antidepressant medication use, age of onset, or symptom severity). This highly powered collaborative effort showed subtle patterns of age-related structural brain abnormalities in MDD. Substantial within-group variance and overlap between groups were observed. Longitudinal studies of MDD and somatic health outcomes are needed to further assess the clinical value of these brain-PAD estimates.

Published
2021

28. Brain aging in major depressive disorder: results from the ENIGMA major depressive disorder working group

Author

Han, LKM, Dinga, R, Hahn, T, Ching, CRK, Eyler, LT, Aftanas, L, Aghajani, M, Aleman, A, Baune, BT, Berger, K, Brak, I, Busatto Filho, G, Carballedo, A, Connolly, CG, Couvy-Duchesne, B, Cullen, KR, Dannlowski, U, Davey, CG, Dima, D, Duran, FLS, Enneking, V, Filimonova, E, Frenzel, S, Frodl, T, Fu, CHY, Godlewska, BR, Gotlib, IH, Grabe, HJ, Groenewold, NA, Grotegerd, D, Gruber, O, Hall, GB, Harrison, BJ, Hatton, SN, Hermesdorf, M, Hickie, IB, Ho, TC, Hosten, N, Jansen, A, Kaehler, C, Kircher, T, Klimes-Dougan, B, Kraemer, B, Krug, A, Lagopoulos, J, Leenings, R, MacMaster, FP, MacQueen, G, McIntosh, A, McLellan, Q, McMahon, KL, Medland, SE, Mueller, BA, Mwangi, B, Osipov, E, Portella, MJ, Pozzi, E, Reneman, L, Repple, J, Rosa, PGP, Sacchet, MD, Saemann, PG, Schnell, K, Schrantee, A, Simulionyte, E, Soares, JC, Sommer, J, Stein, DJ, Steinstraeter, O, Strike, LT, Thomopoulos, SI, van Tol, M-J, Veer, IM, Vermeiren, RRJM, Walter, H, van der Wee, NJA, van der Werff, SJA, Whalley, H, Winter, NR, Wittfeld, K, Wright, MJ, Wu, M-J, Voelzke, H, Yang, TT, Zannias, V, de Zubicaray, GI, Zunta-Soares, GB, Abe, C, Alda, M, Andreassen, OA, Boen, E, Bonnin, CM, Canales-Rodriguez, EJ, Cannon, D, Caseras, X, Chaim-Avancini, TM, Elvsashagen, T, Favre, P, Foley, SF, Fullerton, JM, Goikolea, JM, Haarman, BCM, Hajek, T, Henry, C, Houenou, J, Howells, FM, Ingvar, M, Kuplicki, R, Lafer, B, Landen, M, Machado-Vieira, R, Malt, UF, McDonald, C, Mitchell, PB, Nabulsi, L, Otaduy, MCG, Overs, BJ, Polosan, M, Pomarol-Clotet, E, Radua, J, Rive, MM, Roberts, G, Ruhe, HG, Salvador, R, Sarro, S, Satterthwaite, TD, Savitz, J, Schene, AH, Schofield, PR, Serpa, MH, Sim, K, Soeiro-de-Souza, MG, Sutherland, AN, Temmingh, HS, Timmons, GM, Uhlmann, A, Vieta, E, Wolf, DH, Zanetti, MV, Jahanshad, N, Thompson, PM, Veltman, DJ, Penninx, BWJH, Marquand, AF, Cole, JH, Schmaal, L, Han, LKM, Dinga, R, Hahn, T, Ching, CRK, Eyler, LT, Aftanas, L, Aghajani, M, Aleman, A, Baune, BT, Berger, K, Brak, I, Busatto Filho, G, Carballedo, A, Connolly, CG, Couvy-Duchesne, B, Cullen, KR, Dannlowski, U, Davey, CG, Dima, D, Duran, FLS, Enneking, V, Filimonova, E, Frenzel, S, Frodl, T, Fu, CHY, Godlewska, BR, Gotlib, IH, Grabe, HJ, Groenewold, NA, Grotegerd, D, Gruber, O, Hall, GB, Harrison, BJ, Hatton, SN, Hermesdorf, M, Hickie, IB, Ho, TC, Hosten, N, Jansen, A, Kaehler, C, Kircher, T, Klimes-Dougan, B, Kraemer, B, Krug, A, Lagopoulos, J, Leenings, R, MacMaster, FP, MacQueen, G, McIntosh, A, McLellan, Q, McMahon, KL, Medland, SE, Mueller, BA, Mwangi, B, Osipov, E, Portella, MJ, Pozzi, E, Reneman, L, Repple, J, Rosa, PGP, Sacchet, MD, Saemann, PG, Schnell, K, Schrantee, A, Simulionyte, E, Soares, JC, Sommer, J, Stein, DJ, Steinstraeter, O, Strike, LT, Thomopoulos, SI, van Tol, M-J, Veer, IM, Vermeiren, RRJM, Walter, H, van der Wee, NJA, van der Werff, SJA, Whalley, H, Winter, NR, Wittfeld, K, Wright, MJ, Wu, M-J, Voelzke, H, Yang, TT, Zannias, V, de Zubicaray, GI, Zunta-Soares, GB, Abe, C, Alda, M, Andreassen, OA, Boen, E, Bonnin, CM, Canales-Rodriguez, EJ, Cannon, D, Caseras, X, Chaim-Avancini, TM, Elvsashagen, T, Favre, P, Foley, SF, Fullerton, JM, Goikolea, JM, Haarman, BCM, Hajek, T, Henry, C, Houenou, J, Howells, FM, Ingvar, M, Kuplicki, R, Lafer, B, Landen, M, Machado-Vieira, R, Malt, UF, McDonald, C, Mitchell, PB, Nabulsi, L, Otaduy, MCG, Overs, BJ, Polosan, M, Pomarol-Clotet, E, Radua, J, Rive, MM, Roberts, G, Ruhe, HG, Salvador, R, Sarro, S, Satterthwaite, TD, Savitz, J, Schene, AH, Schofield, PR, Serpa, MH, Sim, K, Soeiro-de-Souza, MG, Sutherland, AN, Temmingh, HS, Timmons, GM, Uhlmann, A, Vieta, E, Wolf, DH, Zanetti, MV, Jahanshad, N, Thompson, PM, Veltman, DJ, Penninx, BWJH, Marquand, AF, Cole, JH, and Schmaal, L

Abstract

Major depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced brain aging in adult MDD patients, and whether this process is associated with clinical characteristics in a large multicenter international dataset. We performed a mega-analysis by pooling brain measures derived from T1-weighted MRI scans from 19 samples worldwide. Healthy brain aging was estimated by predicting chronological age (18-75 years) from 7 subcortical volumes, 34 cortical thickness and 34 surface area, lateral ventricles and total intracranial volume measures separately in 952 male and 1236 female controls from the ENIGMA MDD working group. The learned model coefficients were applied to 927 male controls and 986 depressed males, and 1199 female controls and 1689 depressed females to obtain independent unbiased brain-based age predictions. The difference between predicted "brain age" and chronological age was calculated to indicate brain-predicted age difference (brain-PAD). On average, MDD patients showed a higher brain-PAD of +1.08 (SE 0.22) years (Cohen's d = 0.14, 95% CI: 0.08-0.20) compared with controls. However, this difference did not seem to be driven by specific clinical characteristics (recurrent status, remission status, antidepressant medication use, age of onset, or symptom severity). This highly powered collaborative effort showed subtle patterns of age-related structural brain abnormalities in MDD. Substantial within-group variance and overlap between groups were observed. Longitudinal studies of MDD and somatic health outcomes are needed to further assess the clinical value of these brain-PAD estimates.

Published
2021

38. P.3.14 Brain structural correlates of insomnia severity in major depressive disorder: Results from the ENIGMA-MDD consortium

Author

Leerssen, J., Blanken, T.F., Pozzi, E., Jahanshad, N., Aftanas, L., Baune, B.T., Dannlowski, U., Frodl, T., Godlewska, B.R., Gotlib, I.H., Grotegerd, D., Gruber, O., Hatton, S.N., Hickie, I.B., Irungu, B., Jaworska, N., Kircher, T., Krug, A., Lagopoulos, J., Li, M., MacMaster, F.P., McIntosh, A.M., Osipov, E., Portella, M.J., Sacchet, M.D., Saemann, P.G., Simulionyte, E., Soares, J.C., Walter, M., Whalley, H., Veltman, D., Thompson, P.M., Schmaal, L., and Van Someren, E.J.W.

Published
2019
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39. Brain structural correlates of insomnia severity in 1053 individuals with major depressive disorder: results from the ENIGMA MDD working group

Author

Leerssen, J, Blanken, TF, Pozzi, E, Jahanshad, N, Aftanas, L, Andreassen, OA, Baune, BT, Ching, CRK, Dannlowski, U, Frodl, T, Godlewska, BR, Gotlib, IH, Grotegerd, D, Gruber, O, Hatton, SN, Hickie, IB, Jaworska, N, Kircher, T, Krug, A, Lagopoulos, J, Li, M, MacMaster, FP, McIntosh, AM, Mwangi, B, Osipov, E, Portella, MJ, Sacchet, MD, Samann, PG, Simulionyte, E, Soares, JC, Walter, M, Whalley, HC, Veltman, DJ, Thompson, PM, Schmaal, L, Van Someren, EJW, Leerssen, J, Blanken, TF, Pozzi, E, Jahanshad, N, Aftanas, L, Andreassen, OA, Baune, BT, Ching, CRK, Dannlowski, U, Frodl, T, Godlewska, BR, Gotlib, IH, Grotegerd, D, Gruber, O, Hatton, SN, Hickie, IB, Jaworska, N, Kircher, T, Krug, A, Lagopoulos, J, Li, M, MacMaster, FP, McIntosh, AM, Mwangi, B, Osipov, E, Portella, MJ, Sacchet, MD, Samann, PG, Simulionyte, E, Soares, JC, Walter, M, Whalley, HC, Veltman, DJ, Thompson, PM, Schmaal, L, and Van Someren, EJW

Published
2020

40. White matter disturbances in major depressive disorder: a coordinated analysis across 20 international cohorts in the ENIGMA MDD working group

Author

van Velzen, LS, Kelly, S, Isaev, D, Aleman, A, Aftanas, L, Bauer, J, Baune, BT, Brak, I, Carballedo, A, Connolly, CG, Couvy-Duchesne, B, Cullen, KR, Danilenko, K, Dannlowski, U, Enneking, V, Filimonova, E, Foerster, K, Frodl, T, Gotlib, IH, Groenewold, NA, Grotegerd, D, Harris, MA, Hatton, SN, Hawkins, EL, Hickie, IB, Ho, TC, Jansen, A, Kircher, T, Klimes-Dougan, B, Kochunov, P, Krug, A, Lagopoulos, J, Lee, R, Lett, TA, Li, M, MacMaster, FP, Martin, NG, McIntosh, AM, McLellan, Q, Meinert, S, Nenadic, I, Osipov, E, Penninx, BWJH, Portella, MJ, Repple, J, Roos, A, Sacchet, MD, Saemann, PG, Schnell, K, Shen, X, Sim, K, Stein, DJ, van Tol, M-J, Tomyshev, AS, Tozzi, L, Veer, IM, Vermeiren, R, Vives-Gilabert, Y, Walter, H, Walter, M, van der Wee, NJA, van der Werff, SJA, Schreiner, MW, Whalley, HC, Wright, MJ, Yang, TT, Zhu, A, Veltman, DJ, Thompson, PM, Jahanshad, N, Schmaal, L, van Velzen, LS, Kelly, S, Isaev, D, Aleman, A, Aftanas, L, Bauer, J, Baune, BT, Brak, I, Carballedo, A, Connolly, CG, Couvy-Duchesne, B, Cullen, KR, Danilenko, K, Dannlowski, U, Enneking, V, Filimonova, E, Foerster, K, Frodl, T, Gotlib, IH, Groenewold, NA, Grotegerd, D, Harris, MA, Hatton, SN, Hawkins, EL, Hickie, IB, Ho, TC, Jansen, A, Kircher, T, Klimes-Dougan, B, Kochunov, P, Krug, A, Lagopoulos, J, Lee, R, Lett, TA, Li, M, MacMaster, FP, Martin, NG, McIntosh, AM, McLellan, Q, Meinert, S, Nenadic, I, Osipov, E, Penninx, BWJH, Portella, MJ, Repple, J, Roos, A, Sacchet, MD, Saemann, PG, Schnell, K, Shen, X, Sim, K, Stein, DJ, van Tol, M-J, Tomyshev, AS, Tozzi, L, Veer, IM, Vermeiren, R, Vives-Gilabert, Y, Walter, H, Walter, M, van der Wee, NJA, van der Werff, SJA, Schreiner, MW, Whalley, HC, Wright, MJ, Yang, TT, Zhu, A, Veltman, DJ, Thompson, PM, Jahanshad, N, and Schmaal, L

Abstract

Alterations in white matter (WM) microstructure have been implicated in the pathophysiology of major depressive disorder (MDD). However, previous findings have been inconsistent, partially due to low statistical power and the heterogeneity of depression. In the largest multi-site study to date, we examined WM anisotropy and diffusivity in 1305 MDD patients and 1602 healthy controls (age range 12-88 years) from 20 samples worldwide, which included both adults and adolescents, within the MDD Working Group of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) consortium. Processing of diffusion tensor imaging (DTI) data and statistical analyses were harmonized across sites and effects were meta-analyzed across studies. We observed subtle, but widespread, lower fractional anisotropy (FA) in adult MDD patients compared with controls in 16 out of 25 WM tracts of interest (Cohen's d between 0.12 and 0.26). The largest differences were observed in the corpus callosum and corona radiata. Widespread higher radial diffusivity (RD) was also observed (all Cohen's d between 0.12 and 0.18). Findings appeared to be driven by patients with recurrent MDD and an adult age of onset of depression. White matter microstructural differences in a smaller sample of adolescent MDD patients and controls did not survive correction for multiple testing. In this coordinated and harmonized multisite DTI study, we showed subtle, but widespread differences in WM microstructure in adult MDD, which may suggest structural disconnectivity in MDD.

Published
2020

44. Sol–Gel Derived Photonic Crystals BaTiO3/SiO2.

Author

Gaponenko, N. V., Kholov, P. A., Karnilava, Yu. D., Lashkovskaya, E. I., Labunov, V. A., Martynov, I. L., Osipov, E. V., Chistyakov, A. A., Kargin, N. I., Raichenok, T. F., and Tikhomirov, S. A.

Subjects
PHOTONIC crystals, PHOTONIC band gap structures, SOL-gel processes
Abstract

It is shown for the first time that multilayer periodic BaTiO3/SiO2 structures formed by the sol–gel method are tunable photonic crystals with dependence of the photonic band gap from the temperature of the sample. The shift of the minimum in the reflection spectrum in the photonic band gap is observed from 616 to 610 nm in the sample-temperature range from +184 to +24°C, respectively, and is reproduced for several samples synthesized at a temperature of 450°C. [ABSTRACT FROM AUTHOR]

Published
2021
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45. Comparison of fluorescence excitation modes for CdsSe semi-conductor quantum dots used in medical research

Author

Kuzishchin, Y., Martynov, I., Osipov, E., Samokhvalov, P., Chistyakov, A., Nabiev, I., The National Research Nuclear University MEPhI (Moscow Engineering Physics Institute) [Moscow, Russia], Laboratoire de Recherche en Nanosciences - EA 4682 (LRN), Université de Reims Champagne-Ardenne (URCA)-SFR CAP Santé (Champagne-Ardenne Picardie Santé), Université de Reims Champagne-Ardenne (URCA)-Université de Picardie Jules Verne (UPJV)-Université de Reims Champagne-Ardenne (URCA)-Université de Picardie Jules Verne (UPJV)-SFR Condorcet, and Université de Reims Champagne-Ardenne (URCA)-Université de Picardie Jules Verne (UPJV)-Centre National de la Recherche Scientifique (CNRS)-Université de Reims Champagne-Ardenne (URCA)-Université de Picardie Jules Verne (UPJV)-Centre National de la Recherche Scientifique (CNRS)

Subjects
photodetection, luminescence, [SPI.OPTI]Engineering Sciences [physics]/Optics / Photonic, excitation, quantum dots, CdSe/ZnS, [SPI.NANO]Engineering Sciences [physics]/Micro and nanotechnologies/Microelectronics
Abstract

International audience; Fluorescence spectroscopy is a powerful tool used in applied biological and medical research. Colloid semi-conductor quantum dots are promising fluorescent tags for simultaneous detection of different biopathogens. The techniques employing these tags can be improved by selecting the optimal modes for signal excitation and detection. The aim of the present work was to derive a mathematical expression to describe the signal-to-noise ratios in the pulsed and modulated excitation modes. Below, we compare these two modes of fluorescence excitation in ultralow quantities of quantum dots. We demonstrate that modulated excitation should be preferred for CdSe/ZnS quantum dots given that signal accumulation time is over 100 mc and the photosensor is exposed to background light of > 1 μW.

Published
2018
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