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Comparisons to experimental leg angular velocity data for running cockroaches reveal that while the proposed protocol is qualitatively correct, smaller leg angular accelerations occur during the second half of the swing phase. Modifications made to the recirculation protocol to better match experimental observations yield large improvements in the basin of stability.",{"EN":458},"Leg recirculation in horizontal plane locomotion",{"VOID":460},"[\"16919143092594898890\"]",{"VOID":462},"Altendorfer R, Koditschek D, Holmes P (2004) Stability analysis of legged locomotion models by symmetry-factored return maps. Int J Robot Res 23(11): 979–1000\nBassler U, Buschges A (1998) Pattern generation for stick insect walking movements—multisensory control of a locomotor program. Brain Res Rev 27: 65–88\nDean J, Cruse H (1986) Evidence for the control of velocity as well as position in leg protraction and retraction by the stick insect. Exp Brain Res 15: 263–274\nFull R, Koditschek D (1999) Templates and anchors: neuromechanical hypotheses of legged locomotion on land. J Exp Biol 202: 3325–3332\nFull R, Autmn K, Chung J, Ahn A (1998) Rapid negotiation of rough terrain by the death-head cockroach. Am Zool 38: 81A\nFull R, Kubow T, Schmitt J, Holmes P, Koditschek D (2002) Quantifying dynamic stability and maneuverability in legged locomotion. Integr Compd Biol 42(1): 149–157\nGhigliazza R, Altendorfer R, Holmes P, Koditschek D (2003) A simply stabilized running model. SIAM J Appl Dyn Syst 2(2): 187–218\nGuckenheimer J, Holmes P (1990) Nonlinear oscillations, dynamical systems, and bifurcations of vector fields. Springer, New York\nHooper S, Guschlbauer C, Blumel M, Rosenbaum P, Gruhn M, Akay T, Buschges A (2009) Neural control of unloaded leg posture and of leg swing in stick insect, cockroach, and mouse differs from that in larger animals. J Neurosci 29(13): 4109–4119\nHurwitz A (1964) On the conditions under which an equation has only roots with negative real parts. In: Ballman R, Kalaba R (eds) Selected papers on mathematical trends in control theory. Dover, New York\nJindrich D (2001) Stability, maneuverability, and control of rapid hexapedal locomotion. University of California, Berkeley\nJindrich D, Full R (2002) Dynamic stabilization of rapid hexapedal locomotion. J Exp Biol 205: 2803–2823\nKram R, Wong B, Full R (1997) Three-dimensional kinematics and limb kinetic energy of running cockroaches. J Exp Biol 200: 1919–1929\nKubow T, Full R (1999) The role of the mechanical system in control: a hypothesis of self-stabilization in hexapedal runners. Philos Trans R Soc Lond B 354: 849–861\nKukillaya R, Holmes P (2007) A hexapedal jointed-leg model for insect locomotion in the horizontal plane. Biol Cybernet 97(5–6): 379–395\nLarsen G, Frazier S, Zill S (1997) The tarso-pretarsal chordotonal organ as an element in cockroach walking. J Comp Physiol A 180: 683–700\nLee J, Lamperski A, Schmitt J, Cowan N (2006) Task-level control of the lateral leg spring model of cockroach locomotion. Lect Notes Control Inform Sci 340: 167–188\nRuina A (1998) Non-holonomic stability aspects of piecewise holonomic systems. Rep Math Phys 42(1–2): 91–100\nSaranli U, Buehler M, Koditschek D (2001) Rhex: a simple and highly mobile hexapod robot. Int J Robot Res 20(7): 616–631\nSchmitt J (2007) Incorporating energy variations into controlled sagittal plane locomotion dynamics. In: Proceedings of the international design engineering and technical conference, IDETC07\nSchmitt J, Holmes P (2000a) Mechanical models for insect locomotion: dynamics and stability in the horizontal plane – application. Biol Cybernet 83(6): 517–527\nSchmitt J, Holmes P (2000b) Mechanical models for insect locomotion: dynamics and stability in the horizontal plane – theory. Biol Cybernet 83(6): 501–515\nSchmitt J, Holmes P (2001) Mechanical models for insect locomotion: Stability and parameter studies. Physica D 156(1-2): 139–168\nSchmitt J, Garcia M, Razo R, Holmes P, Full R (2002) Dynamics and stability of legged locomotion in the horizontal plane: a test case using insects. Biol Cybernet 86(5): 343–353\nSchwind W, Koditschek D (1998) Characterization of monopod equilibrium gaits. Preprint, Department of EECS, University of Michigan\nSchwind W, Koditschek D (2000) Approximating the stance map of a 2 dof monoped runner. J Nonlinear Sci 10(5): 533–568\nSeipel J, Holmes P (2005) Running in three dimensions: analysis of a point-mass sprung-leg model. Int J Robot Res 24(8): 657–674\nSeipel J, Holmes P, Full R (2004) Dynamics and stability of insect locomotion: a hexapedal model for horizontal plane motions. Biol Cybernet 91: 76–90\nSeyfarth A, Geyer H, Herr H (2003) Swing-leg retraction: a simple control model for stable running. J Exp Biol 206: 2547–2555\nSponberg S, Full R (2008) Neuromechanical response of musculo-skeletal structures in cockroachs during rapid running on rough terrain. J Exp Biol 211: 433–446\nTing L, Blickhan R, Full R (1994) Dynamic and static stability in hexapedal runners. J Exp Biol 197: 251–269\nWatson J, Ritzmann R (1998) Leg kinematics and muscle activity during treadmill running in the cockroach, blaberus discoidalis: I. slow running. J Comp Physiol A 182: 11–22\nWickramasuriya A, Schmitt J (2009) Improving horizontal plane locomotion via leg angle control. J Theor Biol 256: 414–427\nZill S (1990) Mechanoreceptors: exteroceptors and proprioceptors. In: Huber I, Masler E, Rao B (eds) Cockroaches as models for neurobiology: applications in biomedical research, vol II. 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Cogn Psychol 1:225–241",{"doi":921},"10.1016\u002F0010-0285(70)90016-2",{"id":18,"text":923,"url":18,"identifiers":924},"Grau JW, Kemler-Nelson DG (1988) The distinction between integral and separable dimensions: Evidence for the integrality of pitch and loudness. J Exp Psychol Gen 117:347–370",{"doi":925},"10.1037\u002F0096-3445.117.4.347",{"id":18,"text":927,"url":18,"identifiers":928},"Handel S, Imai S (1972) The free classification of analyzable and unanalyzable stimuli. Percept Psychophys 12:108–116",{"doi":929},"10.3758\u002FBF03212854",{"id":18,"text":931,"url":18,"identifiers":932},"Krantz DH, Tversky A (1975) Similarity of rectangles: An analysis of subjective dimensions. J Math Psychol 12:4–34",{"doi":933},"10.1016\u002F0022-2496(75)90047-4",{"id":18,"text":935,"url":18,"identifiers":936},"Lockhead GR (1966) Effects of dimensional redundancy on visual discrimination. J Exp Psychol 72:95–104",{"doi":937},"10.1037\u002Fh0023319",{"id":18,"text":939,"url":18,"identifiers":940},"Lockhead GR (1972) Processing dimensional stimuli: a note. Psychol Rev 79:410–419",{"doi":941},"10.1037\u002Fh0033129",{"id":18,"text":943,"url":18,"identifiers":944},"Lockhead GR (1979) Holistic versus analytic process models: A reply. J Exp Psychol Hum Perc Perf 5:746–755.",{"doi":945},"10.1037\u002F0096-1523.5.4.746",{"id":18,"text":947,"url":18,"identifiers":948},"Noma E, Baird JC (1975) Psychophysical study of numbers. II. Theoretical models of number generation. Psychol Res 38:81–95",{"doi":949},"10.1007\u002FBF00308940",{"id":18,"text":951,"url":18,"identifiers":952},"Pomerantz JR, Pristach EA (1989) Emergent features, attention, and perceptual glue in visual form perception. J Exp Psychol Hum Perc Perf 15:635–649",{"doi":953},"10.1037\u002F0096-1523.15.4.635",{"id":18,"text":955,"url":18,"identifiers":956},"Ronacher B (1984) Human pattern recognition: Evidence for a switching between strategies in analyzing complex stimuli. Biol Cybern 51:205–210",{"doi":957},"10.1007\u002FBF00346142",{"id":18,"text":959,"url":18,"identifiers":960},"Ronacher B, Bautz W (1985) Human pattern recognition: Individually different strategies in analyzing complex stimuli. Biol Cybern 51:249–261",{"doi":961},"10.1007\u002FBF00337150",{"id":18,"text":963,"url":18,"identifiers":964},"Shepard RN (1964) Attention and the metric structure of the stimulus space. J Math Psychol 1:54–87",{"doi":965},"10.1016\u002F0022-2496(64)90017-3",{"id":18,"text":967,"url":18,"identifiers":968},"Shepard RN (1981) Psychological relations and psychophysical scales: On the status of ‘direct’ psychophysical measurement. J Math Psychol 24:21–57",{"doi":969},"10.1016\u002F0022-2496(81)90034-1",{"id":18,"text":971,"url":18,"identifiers":972},"Shepard RN (1987) Toward a universal law of generalization for psychological science. Science 237:1317–1323",{"doi":973},"10.1126\u002Fscience.3629243",{"id":18,"text":975,"url":18,"identifiers":976},"Shepp BE (1983) The analyzability of multidimensional objects: Some constraints on perceived structure, the development of perceived structure, and attention. In: Tighe TJ (ed) Perception, cognition and development. Erlbaum, Hillsdale, NJ, pp 39–75",{},{"id":18,"text":978,"url":18,"identifiers":979},"Smith JD, Baron J (1981) Individual differences in the classification of stimuli by dimensions. J Exp Psychol Hum Perc Perf 7:1132–1145",{"doi":980},"10.1037\u002F0096-1523.7.5.1132",{"id":18,"text":982,"url":18,"identifiers":983},"Smith JD, Kemler-Nelson DG (1984) Overall similarity in adults' classification: The child in all of us. J Exp Psychol Gen 113:137–159",{"doi":984},"10.1037\u002F0096-3445.113.1.137",{"id":18,"text":986,"url":18,"identifiers":987},"Smith LB, Kemler DG (1977) Developmental trends in free classification: Evidence for a new conceptualization of perceptual development. J Exp Child Psychol 24:279–298",{"doi":988},"10.1016\u002F0022-0965(77)90007-8",{"id":18,"text":990,"url":18,"identifiers":991},"Smith LB, Kemler DG (1978) Levels of experienced dimensionality in children and adults. Cogn Psychol 10:502–532",{"doi":992},"10.1016\u002F0010-0285(78)90009-9",{"id":18,"text":994,"url":18,"identifiers":995},"Smith LB, Kilroy MC (1979) A continuum of dimensional separability. Percept Psychophys 25:285–291",{"doi":996},"10.3758\u002FBF03198807",{"id":18,"text":998,"url":18,"identifiers":999},"Stevens SS (1957) On the psychophysical law. Psychol Rev 64:153–181",{"doi":1000},"10.1037\u002Fh0046162",{"id":18,"text":1002,"url":18,"identifiers":1003},"Stevens SS (1962) The surprising simplicity of sensory metrics. Am Psychol 17:29–39",{"doi":1004},"10.1037\u002Fh0045795",{"id":18,"text":1006,"url":18,"identifiers":1007},"Stevens SS (1966) On the operation known as judgment. Am Sci 54:385–401",{},{"id":18,"text":1009,"url":18,"identifiers":1010},"Suchowerskyj W (1976) Untersuchungen über die subjektive Bewertung von Unterschieden zwischen akustischen Signalen. Dissertation TU\u002FElektrotechnik München",{},{"id":18,"text":1012,"url":18,"identifiers":1013},"Torgerson WS (1958) Theory and methods of scaling. Wiley, New York",{},{"id":18,"text":1015,"url":18,"identifiers":1016},"Treisman A (1986) Properties, parts, and objects. In: Boff K, Kaufmann K, Thomas J (eds) Handbook of perception and human performance. Wiley, New York, pp 1–71",{},{"id":18,"text":1018,"url":18,"identifiers":1019},"Tversky M (1977) Features of similarity. Psychol Rev 84:327–352",{"doi":1020},"10.1037\u002F0033-295X.84.4.327",{"id":18,"text":1022,"url":18,"identifiers":1023},"Tversky A, Gati I (1982) Similarity, separability, and the triangle inequality. Psychol Rev 89:123–154",{"doi":1024},"10.1037\u002F0033-295X.89.2.123",{"id":18,"text":1026,"url":18,"identifiers":1027},"Tversky A, Krantz DH (1970) The dimensional representation and the metric structure of similarity data. J Math Psychol 7:572–596",{"doi":1028},"10.1016\u002F0022-2496(70)90041-6",{"id":18,"text":1030,"url":18,"identifiers":1031},"Ward TB (1980) Separable and integral responding by children and adults to the dimensions of length and density. Child Dev 51:676–684",{"doi":1032},"10.2307\u002F1129452",{"id":18,"text":1034,"url":18,"identifiers":1035},"Ward TB (1983) Response tempo and separable-integral responding: Evidence for an integral-to-separable processing sequence in visual perception. J Exp Psychol Hum Perc Perf 9:103–112",{"doi":1036},"10.1037\u002F0096-1523.9.1.103",{"id":18,"text":1038,"url":18,"identifiers":1039},"Ward TB (1985) Individual differences in processing stimulus dimensions: relation to selective processing abilities. Percept Psychophys 37:471–482",{"doi":1040},"10.3758\u002FBF03202880",{"id":18,"text":1042,"url":18,"identifiers":1043},"Ward TB, Foley CM, Cole J (1986) Classifying multidimensional stimuli: Stimulus, task, and observer factors. J Exp Psychol Hum Perc Perf 12:211–225",{"doi":1044},"10.1037\u002F0096-1523.12.2.211",{"id":18,"text":1046,"url":18,"identifiers":1047},"Wiener-Ehrlich WK (1978) Dimensional and metric structures in multidimensional stimuli. Percept Psychophys 24:399–414",{"doi":1048},"10.3758\u002FBF03199737",{"id":1050,"createTime":1051,"updateTime":1052,"relativeEntities":1053,"slug":1054,"properties":1055,"entityType":120,"verifyStatus":121,"verifyTime":1065,"verifyNote":123,"languages":18,"translateLanguages":18,"viewCount":486,"primaryUrl":1066,"fullTextUrl":18,"authors":1067,"publicationType":149,"publisherRelationship":1096,"citationCount":18,"citationInfo":18,"publishDate":1147,"publishYear":1148,"citationAnalyzeStatus":868,"lastCitationAnalyze":1149,"indexDatabases":1150,"openAccess":18,"references":18,"isForceReanalyzing":271},"dce88dcf-01d1-4485-8172-8713ac1318fe","2024-01-23T06:02:34.412+00:00","2026-08-14T20:14:37.226+00:00",[],"Responses-of-the-spinal-%CE%B1-motoneurone-Renshaw-cell-system-to-various-differentially-distributed-segmental-afferent-and-descending-inputs",{"abstract":1056,"title":1058,"gsPaper":1060,"references":1061,"doi":1063},{"EN":1057},"A previously presented multi-loop model of the mammalian spinal α-motoneurone-Renshaw cell system was extended to incorporate different physiological input patterns: Ia fibres from primary muscle spindle endings, spinal input systems descending in the ventral quadrant and from the nucleus ruber. The main goal of the computer simulation calculations was to present a number of dynamic input-output relations between these inputs which are distributed inhomogenously to different types of α-MNs (that is, S-, FR-, and FF-type MNs) and the outputs of pools of the latter, for the purpose of experimental testing. The main outcome was that the phase relations of the outputs of the different types of MNs depend very much on the overall strength of recurrent inhibition, such that small changes of this strength, which appears to be small anyway, can significantly alter these phase relations. Since this strength is alterable through descending and segmental afferent inputs, this provides a physiological means of phase-decorrelation although it is unlikely to put the discharges of different MN types totally out of phase (by about 180°). Also, the inhomogeneity of recurrent inhibition would help to prevent a strong phase separation of this kind. Yet a decorrelation at the microscopic level could help suppress physiological tremor.",{"EN":1059},"Responses of the spinal α-motoneurone-Renshaw cell system to various differentially distributed segmental afferent and descending inputs",{"VOID":770},{"VOID":1062},"Adam, D., Windhorst, U., Inbar, G.F.: The effects of recurrent inhibition on the cross-correlated firing patterns of motoneurones (and their relation to signal transmission in the spinal cord-muscle channel). Biol. Cybern. 29, 299–235 (1978)\nAgarwal, G.C., Gottlieb, G.L.: Mathematical modeling and simulation of the postural control loop. Part I. CRC Crit. Rev. Biomed. Eng. 8, 93–134 (1980)\nBaldissera, F., Campadelli, P., Piccinelli, L.: Neural encoding of input transients investigated by intracellular injection of ramp currents in cat α-motoneurones. J. Physiol. (Lond.) 328, 73–86 (1982)\nBaldissera, F., Campadelli, P., Piccinelli, L.: The dynamic response of cat α-motoneurones investigated by intracellular injection of sinusoidal currents. Exp. Brain Res. 54, 275–282 (1984)\nBaldissera, F., Parmiggiani, F.: Relevance of motoneuronal firing adaptation to tension development in the motor unit. Brain Res. 91, 315–320 (1975)\nBarrett, J.N., Crill, W.E.: Specific membrane properties of cat motoneurones. J. Physiol. (Lond.) 239, 301–324 (1974)\nBurke, R.E.: Motor units: anatomy, physiology, and functional organization. In: Handbook of physiology. Brooks, V.B. (ed.). Sect. 1: The nervous system, Vol. II. Motor control, Part 1, pp. 345–422. Bethesda: Am. Physiol. Soc. 1981\nBurke, R.E., Jankowska, E., ten Bruggencate, G.: A comparison of peripheral and rubrospinal synaptic input to slow and fast twitch motor units of triceps surae. J. Physiol. (Lond.) 207, 709–732 (1970)\nBurke, R.E., Rymer, W.Z., Walsh, J.V., Jr.: Relative strength of synaptic input from short-latency pathways to motor units of defined type in cat medial gastrocnemius. J. Neurophysiol. 39, 447–458 (1976)\nCleveland, S., Ross, H.-G.: Dynamic properties of Renshaw cells: frequency response characteristics. Biol. Cybern. 27, 175–184 (1977)\nDiStefano III, J.J., Stubberud, A.R., Williams, I.J.: Theory and problems of feedback and control systems. Schaum's outline series. New York, St. Louis, San Francisco, Toronto, Sydney: McGraw-Hill 1967\nDum, R.P., Kennedy, T.T.: Synaptic organization of defined motor-unit types in cat tibialis anterior. J. Neurophysiol. 43, 1631–1644 (1980)\nFleshman, J.W., Munson, J.B., Sypert, G.W., Friedman, W.A.: Rheobase, input resistance, and motor-unit type in medial gastrocnemius motoneurons in the cat. J. Neurophysiol. 46, 1326–1338 (1981a)\nFleshman, J.W., Munson, J.B., Sypert, G.W.: Homonymous projection of individual group Ia-fibers to physiologically characterized medial gastrocnemius motoneurons in the cat. J. Neurophysiol. 46, 1339–1348 (1981b)\nFreund, H.-J.: Motor unit and muscle activity in voluntary motor control. Physiol. Rev. 63, 387–436 (1983)\nGelfand, I.M., Gurfinkel, V.S., Kots, Y.M., Tsetlin, M.L., Shik, M.L.: Synchronization of motor units and associated model concepts. Biofiz. 8, 475–486 (1963)\nGranit, R., Rutledge, L.T.: Surplus excitation in reflex action of motoneurones as measured by recurrent inhibition. J. Physiol. (Lond.) 154, 288–307 (1960)\nHarrison, P.J., Taylor, A.: Individual excitatory post-synaptic potentials due to muscle spindle Ia afferents in cat triceps surae motoneurones. J. Physiol. (Lond.) 312, 455–470 (1981)\nKanda, K., Burke, R.E., Walmsley, B.: Differential control of fast and slow twitch motor units in the decerebrate cat. Exp. Brain Res. 29, 57–74 (1977)\nMori, S., Kawahara, K., Sakamoto, T., Aoki, M., Tomiyama, T.: Setting and resetting of level of postural muscle tone in decerebrate cat by stimulation of brain stem. J. Neurophysiol. 48, 737–748 (1982)\nMunson, J.B., Sypert, G.W., Zengel, J.E., Lofton, S.A., Fleshman, J.W.: Monosynaptic projections of individual spindle group II afferents to type-identified medial gastrocnemius motoneurons in the cat. J. Neurophysiol. 48, 1164–1174 (1982)\nPoppele, R.E., Terzuolo, C.A.: Myotatic reflex: its input-output relation. Science 159, 743–754 (1968)\nRedman, S.J., Lampard, D.G.: Monosynaptic stochastic stimulation of cat spinal motoneurons. I. Response of motoneurons to sustained stimulation. J. Neurophysiol. 31, 485–498 (1968)\nRedman, S.J., Lampard, D.G., Annal, P.: Monosynaptic stochastic stimulation of cat spinal motoneurons. II. Frequency transfer characteristics of tonically discharging motoneurons. J. Neurophysiol. 31, 499–508 (1968)\nRosenthal, N.P., McKean, T.A., Roberts, W.J., Terzuolo, C.A.: Frequency analysis of stretch reflex and its main subsystems in triceps surae muscles of the cat. J. Neurophysiol. 33, 713–749 (1970)\nWindhorst, U.: Auxiliary spinal networks for signal focussing in the segmental stretch reflex system. Biol. Cybern. 34, 125–135 (1979)\nWindhorst, U.: Neural activity states in different forms of physiological tremor. Facts and hypotheses. Biol. Cybern. 50, 143–154 (1984)\nWindhorst, U., Adam, D., Inbar, G.F.: The effect of recurrent inhibitory feedback in shaping discharge patterns of motoneurones excited by phasic muscle stretches. Biol. Cybern. 29, 221–227 (1978a)\nWindhorst, U., Koehler, W.: Dynamic behaviour of α motoneurone sub-pools subjected to inhomogeneous Renshaw cell inhibition. Biol. Cybern. 46, 217–228 (1983)\nWindhorst, U., Ptok, M., Meyer-Lohmann, J., Schmidt, J.: Effects of conditioning stimulation of the contralateral N. ruber on antidromic Renshaw cell responses and monosynaptic reflexes. Pflügers Arch. 373, R 70 (1978b)",{"VOID":1064},"10.1007\u002FBF00350782","2024-09-04T21:58:10.265+00:00","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002FBF00350782",[1068,1083],{"id":1069,"sortIndex":19,"researcher":18,"roles":1070,"affiliations":1071,"properties":1080,"displayName":1082,"givenName":18,"familyName":18},"da9c7bd8-26b9-4f16-a44b-9e6abcdb3d9e",[471],[1072],{"id":1073,"sortIndex":19,"affiliation":1074,"properties":18},"d82ba095-f5d3-43d5-a2a0-c9e99c250d38",{"id":1073,"createTime":18,"updateTime":18,"relativeEntities":1075,"slug":18,"properties":1076,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":1079,"statistic":18},[],{"title":1077},{"VI":1078},"Abteilung Neuro- und Sinnesphysiologie, Zentrum Physiologie und Pathophysiologie der Universität Göttingen, Göttingen, Germany",[],{"title":1081},{"VI":1082},"W. Koehler",{"id":1084,"sortIndex":486,"researcher":18,"roles":1085,"affiliations":1086,"properties":1093,"displayName":1095,"givenName":18,"familyName":18},"f0c64438-e1ed-4af2-80c1-0bd4031bf88b",[471],[1087],{"id":1073,"sortIndex":19,"affiliation":1088,"properties":18},{"id":1073,"createTime":18,"updateTime":18,"relativeEntities":1089,"slug":18,"properties":1090,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":1092,"statistic":18},[],{"title":1091},{"VI":1078},[],{"title":1094},{"VI":1095},"U. 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The responses of the isopotential soma to a maintained current density of less than 10 μA cm-2 includes repetitive discharges of action potentials, sawtooth oscillations and amplitudemodulated oscillations. The frequency of the maintained response increases as the injected current increases, while the amplitude decreases until the maintained response is a stable steady state at a membrane potential of about -20mV. This bifurcation from small amplitude periodic solutions to a depolarized stable steady state has the characteristics of a supercritical Hopf bifurcation.",{"EN":1161},"Repetitive activity of a molluscan neurone driven by maintained currents: A supercritical bifurcation",{"VOID":1163},"[\"6800821276350463189\"]",{"VOID":1165},"Adams, D.J., Smith, S.J., Thompson, S.H.: Ionic currents in molluscan soma. Ann. Rev. Neurosci. 3, 141–167 (1980)\nAldrich, R.W., jr., Getting, P.A., Thompson, S.H.: Mechanism of frequency-dependent broadening of molluscan neurone soma spikes. J. Physiol. 291, 531–544 (1979)\nChiu, S.Y., Richie, J.M., Rogart, R.B., Stagg, D.: A quantiative description of membrane currents in rabbit myelinated nerve. J. Physiol. 292, 149–166 (1979)\nConnor, J.A., Stevens, C.F.: Prediction of repetitive firing behaviour from voltage clamp data on an isolated neurone soma. J. Physyiol. 213, 31–33 (1971)\nFuortes, M.G.F., Mantegazzini, F.: Interpretation of the repetitive firing of nerve cells. J. Gen. Physiol. 45, 1163–1179 (1962)\nHagiwara, S., Oomura, Y.: The critical depolarisation for the spike in squid giant axon. Jap. J. Physiol. 8, 234–235 (1958)\nHassard, B.: Bifurcation of periodic solutions of the Hodgkin-Huxley model for the squid giant axon. J. Theor. Biol. 71, 401–420 (1978)\nHodgkin, A.L., Huxley, A.F.: A quantitative description of membrane current and its application to conduction and excitation in nerve. J. Physiol. 117, 500–544 (1952)\nHolden, A.V.: Autorythmicity and entrainment in excitable membranes. Biol. Cybern. 38, 1–8 (1980)\nHolden, A.V.: Membrane current fluctations and neuronal information processing. In: Advances in physiological sciences, Vol. 30. Neural Communications and Control, pp. 23–43. Szekely, G. (ed.). Oxford: Pergamon 1981\nHolden, A.V.: The mathematics of excitation. In: Biomathematics: current status and future perspectives. Ricciardi, L. (ed.). Amsterdam: North-Holland (1981) (in press)\nHolden, A.V., Ramadan, S.M.: Identification of endogenous and exogenous activity in a molluscan neurone by spike train analysis. Biol. Cybern. 37, 107–114 (1980)\nHolden, A.V., Ramadan, S.M.: The response of a molluscan neurone to a cyclic input: entrainment and phase-locking. Biol. Cybern. (1981) (in press)\nHolden, A.V., Winlow, W.: Bifurcation of periodic activity from periodic activity in a molluscan neurone. Biol. Cybern. (1981) (in press)\nKrylov, B.V., Makovsky, V.S.: Spike frequency adaptation in amphibian sensory fibres is probably due to slow K+ channels. Nature 275, 549–551 (1978)\nMagura, I.S., Zamekhovsky, I.Z.: Repetitive firing in molluscan giant neurones. J. Exp. Biol. 59, 767–780 (1973)\nMarsden, J.E., McCracken, M.: The Hopf bifurcation and its applications. Berlin, Heidelberg, New York: Springer 1976\nPartridge, L.D., Stevens, C.F.: A mechanism for spike frequency adaptation. J. Physiol. 256, 315–332 (1976)\nRinzel, J.: On repetitive activity in nerve. Fed. Proc. 37, 2793–2802 (1978)\nTeorell, T.: A biophysical analysis of mechano-electrical transduction. In: Handbook of sensory physiology. Vol. 1. Principles of receptor physiology. pp. 291–339. Loewenstein, W.R. (ed.). Berlin, Heidelberg, New York: Springer 1971\nTroy, W.C.: The bifurcation of periodic solutions in the Hodgkin-Huxley equations. Quart. Appl. Math. 36, 73–83 (1978)\nWinlow, W., Benjamin, P.R.: Neuronal mapping of the brain of the pond-snail, Lymmaea stagnalis (L.). In: Neurobiology of invertebrates, gastropoda brain. pp. 41–59. Salanki, J. (ed.). Budapest: Akademiai Kiado 1975",{"VOID":1167},"10.1007\u002FBF00336725","2024-05-14T10:23:44.614+00:00","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002FBF00336725",[1171,1186],{"id":1172,"sortIndex":19,"researcher":18,"roles":1173,"affiliations":1174,"properties":1183,"displayName":1185,"givenName":18,"familyName":18},"17451605-65a4-46b5-a2b3-e8da337502ff",[471],[1175],{"id":1176,"sortIndex":19,"affiliation":1177,"properties":18},"9ca13e8a-bcc6-4fa6-a8f2-e85555f534cb",{"id":1176,"createTime":18,"updateTime":18,"relativeEntities":1178,"slug":18,"properties":1179,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":1182,"statistic":18},[],{"title":1180},{"VI":1181},"Department of Physiology, University of Leeds, Leeds, England",[],{"title":1184},{"VI":1185},"A. V. Holden",{"id":1187,"sortIndex":486,"researcher":18,"roles":1188,"affiliations":1189,"properties":1196,"displayName":1198,"givenName":18,"familyName":18},"989ab6ce-f9d8-4a95-b3b0-a8d0ee1415ea",[471],[1190],{"id":1176,"sortIndex":19,"affiliation":1191,"properties":18},{"id":1176,"createTime":18,"updateTime":18,"relativeEntities":1192,"slug":18,"properties":1193,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":1195,"statistic":18},[],{"title":1194},{"VI":1181},[],{"title":1197},{"VI":1198},"S. M. Ramadan",{"url":1169,"publisher":1200,"properties":1245},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":1201,"slug":10,"properties":1202,"entityType":16,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":19,"subjectFields":1205,"manageAffiliations":1214,"indexDatabases":1225,"url":18,"thumbnailPath":18,"statistic":1240,"gsStatistic":18,"type":18,"analyzePriority":18},[],{"title":1203,"eissn":1204},{"EN":13},{"VOID":15},[1206,1210],{"id":22,"createTime":18,"updateTime":18,"relativeEntities":1207,"label":1208,"description":1209,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":25},{},{"id":28,"createTime":18,"updateTime":18,"relativeEntities":1211,"label":1212,"description":1213,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":31},{},[1215,1220],{"id":35,"createTime":18,"updateTime":18,"relativeEntities":1216,"slug":18,"properties":1217,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":1219,"statistic":18},[],{"title":1218},{"EN":39},[],{"id":42,"createTime":18,"updateTime":18,"relativeEntities":1221,"slug":18,"properties":1222,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":1224,"statistic":18},[],{"title":1223},{"EN":46},[48],[1226,1233],{"id":51,"indexDatabase":1227,"url":62,"indexYears":63,"academicFieldIds":1232,"indexDatabaseRanking":67},{"id":53,"createTime":18,"updateTime":18,"relativeEntities":1228,"label":1229,"description":1230,"key":59,"publicationTags":1231,"standard":18},[],{"EN":56,"VI":56},{"EN":56,"VI":58},[61],[65,66],{"id":69,"indexDatabase":1234,"url":18,"indexYears":18,"academicFieldIds":1239,"indexDatabaseRanking":18},{"id":71,"createTime":18,"updateTime":18,"relativeEntities":1235,"label":1236,"description":1237,"key":78,"publicationTags":1238,"standard":18},[],{"EN":74,"VI":74},{"EN":76,"VI":77},[80,81],[83,84],{"impactFactor":19,"impactFactorByYear":1241,"i10Index":19,"i10IndexLast5Year":19,"totalPublication":88,"totalPublicationByYear":1242,"totalCitation":91,"totalCitationByYear":1243,"totalCitationPerPublication":94,"totalCitationPerPublicationByYear":1244,"hindexLast5Year":97,"hindex":97},{"2023":87},{"2022":90},{"2022":93},{"2022":96},{"pages":1246,"volume":1248},{"VOID":1247},"79-85",{"VOID":1249},"42",{"total":19,"publishYear":1251,"statisticByYear":1252},1981,{},"1981-11-01","DONE_ANALYZE_CITATION","2026-07-24T12:41:38.612+00:00",[80,67],{"id":1258,"createTime":1259,"updateTime":1260,"relativeEntities":1261,"slug":1262,"properties":1263,"entityType":120,"verifyStatus":121,"verifyTime":1272,"verifyNote":123,"languages":18,"translateLanguages":18,"viewCount":19,"primaryUrl":1273,"fullTextUrl":18,"authors":1274,"publicationType":149,"publisherRelationship":1290,"citationCount":97,"citationInfo":1341,"publishDate":1344,"publishYear":1342,"citationAnalyzeStatus":1254,"lastCitationAnalyze":1260,"indexDatabases":1345,"openAccess":18,"references":1346,"isForceReanalyzing":271},"7e74477c-a00c-422c-8076-3e2758bc3e1c","2023-12-25T17:31:05.325+00:00","2026-07-23T08:18:30.604+00:00",[],"Emergence-of-orientation-selective-inhibition-in-the-primary-visual-cortex-a-Bayes-Markov-computational-model",{"abstract":1264,"title":1266,"gsPaper":1268,"doi":1270},{"EN":1265},"The recent consensus is that virtually all aspects of response selectivity exhibited by the primary visual cortex are either created or sharpened by cortical inhibitory interneurons. Experimental studies have shown that there are cortical inhibitory cells that are driven by geniculate cells and that, like their cortical excitatory counterparts, are orientation selective, though less sharply tuned. The main goal of this article is to demonstrate how orientation-selective inhibition might be created by the circuitry of the primary visual cortex (striate cortex, V1) from its nonoriented geniculate inputs. To fulfill this goal, first, a Bayes–Markov computational model is developed for the V1 area dedicated to foveal vision. The developed model consists of three parts: (i) a two-layered hierarchical Markov random field that is assumed to generate the activity patterns of the geniculate and cortical inhibitory cells, (ii) a Bayesian computational goal that is formulated based on the maximum a posteriori (MAP) estimation principle, and (iii) an iterative, deterministic, parallel algorithm that leads the cortical circuitry to achieve its assigned computational goal. The developed model is not fully LGN driven and it is not implementable by the neural machinery of V1. The model, then, is transformed into a fully LGN-driven and physiologically plausible form. Computer simulation is used to demonstrate the performance of the developed models.",{"EN":1267},"Emergence of orientation-selective inhibition in the primary visual cortex: a Bayes–Markov computational model",{"VOID":1269},"[\"16587646820806727210\"]",{"VOID":1271},"10.1007\u002Fs00422-004-0483-5","2024-05-03T11:55:39.843+00:00","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs00422-004-0483-5",[1275],{"id":1276,"sortIndex":19,"researcher":18,"roles":1277,"affiliations":1278,"properties":1287,"displayName":1289,"givenName":18,"familyName":18},"c50f1b42-3cfa-4a68-b412-d93d3f95a554",[471],[1279],{"id":1280,"sortIndex":19,"affiliation":1281,"properties":18},"0a8b5929-2459-49c0-a40d-e579a6340ab7",{"id":1280,"createTime":18,"updateTime":18,"relativeEntities":1282,"slug":18,"properties":1283,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":1286,"statistic":18},[],{"title":1284},{"VI":1285},"Osaka Institute of Technology, Faculty of Information Science, Osaka, Japan",[],{"title":1288},{"VI":1289},"Mehdi N. 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Vis Neurosci 16:303–318","https:\u002F\u002Fwww.cambridge.org\u002Fcore\u002Fproduct\u002Fidentifier\u002FS0952523899162114\u002Ftype\u002Fjournal_article",{"doi":1352},"10.1017\u002Fs0952523899162114",{"id":1354,"text":1355,"url":1356,"identifiers":1357},"13894f73-cc73-4b10-9381-df702892524c","Ben-Yishai R, Bar-Or RL, Sompolinsky H (1995) Theory of orientation tuning in visual cortex. Proc Natl Acad Sci USA 92: 3844–3848","https:\u002F\u002Fpnas.org\u002Fdoi\u002Ffull\u002F10.1073\u002Fpnas.92.9.3844",{"doi":1358},"10.1073\u002Fpnas.92.9.3844",{"id":1360,"text":1361,"url":1362,"identifiers":1363},"4c68646b-0035-4279-8000-0006b275d4fa","Besag JE (1974) Spatial interaction and the statistical analysis of lattice systems. J R Stat Soc Ser B 36:192–226","https:\u002F\u002Flink.springer.com\u002F10.1007\u002Fs10440-022-00541-7",{"doi":1364},"10.1007\u002Fs10440-022-00541-7",{"id":1360,"text":1366,"url":1362,"identifiers":1367},"Bishop PO, Coombs JS, Henry H (1973) Receptive fields of simple cells in the cat striate cortex. J Physiol 231:31–60",{"doi":1364},{"id":1360,"text":1369,"url":1362,"identifiers":1370},"Blakemore C, Rose D (1974) Effects of bicuculline on functions of inhibition in visual cortex. Nature 249:375–377",{"doi":1364},{"id":18,"text":1372,"url":18,"identifiers":1373},"Bonds AB, DeBruyn EJ (1985) Inhibition cortex: the cooperative neuronal network revisited. In: Rose D, Dobson VG (eds) Models of the visual cortex. Wiley, New York, pp 292–300",{},{"id":1375,"text":1376,"url":1377,"identifiers":1378},"35f004f3-756e-48aa-933f-af69e0a9bba8","Burr D, Morrone C, Maffei L (1981) Intra-cortical inhibition prevents simple cells from responding to textured visual patterns. Exp Brain Res 43:455–458","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002FBF00238391",{"doi":1379},"10.1007\u002FBF00238391",{"id":18,"text":1381,"url":18,"identifiers":1382},"Callaway EM (1998) Local circuits in primary visual cortex of the macaque monkey. Annu Rev Neurosci 21:47–74",{},{"id":1384,"text":1385,"url":1386,"identifiers":1387},"2c86eaaf-c281-4abf-8afc-f22c3875d382","Carandini M, Ringach DL (1997) Predictions of a recurrent model of orientation selectivity. Vision Res 37:3061–3071","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002FS0042698997001004",{"doi":1388},"10.1016\u002Fs0042-6989(97)00100-4",{"id":1360,"text":1390,"url":1362,"identifiers":1391},"Chapman B, Zahs KR, Stryker MP (1991) Relation of cortical cell orientation selectivity to alignment of receptive fields of the geniculocortical afferents that arborize within a single orientation column in ferret visual cortex. J Neurosci 11(5):1347–1358",{"doi":1364},{"id":1360,"text":1393,"url":1362,"identifiers":1394},"Chung S, Ferster D (1998) Strength and orientation tuning of the thalamic input to simple cells revealed by electrically evoked cortical suppression. Neuron 20:1171–1189",{"doi":1364},{"id":18,"text":1396,"url":18,"identifiers":1397},"Colonnier M (1964) The tangential organization of the cortex. J Anat 98:327–344",{},{"id":18,"text":1399,"url":18,"identifiers":1400},"Colonnier M (1974) Spatial interrelationships as physiological mechanisms in the central nervous system. In: Bellairs R, Gray EG (eds) Essay on the nervous system. Clarendon, Oxford, pp 344–366",{},{"id":1360,"text":1402,"url":1362,"identifiers":1403},"Crook JM, Eysel UT (1992) GABA-induced inactivation functionally characterized sites in cat visual cortex (Area 18): effects on orientation tuning. 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For the range of parameters used we find that such systems respond in a specific manner to specific stimuli, and furthermore, whatever memory is transferred to one simulated hemisphere is also transferred to the other. However, this behavior changes when the two hemispheres are separated. We find that memory is not transferred from one hemisphere to the other when the interconnecting commissures are severed. The above findings verify Sperry's experimental observation that the split brain behaves as if it were indeed two separate brains, each performing concurrently and simultaneously diametrically opposite tasks.",{"EN":1863},"A computer model for learning processes and the role of the cerebral commissures",{"VOID":1865},"[\"13009487056962044310\"]",{"EN":1867},"",{"VOID":1869},"10.1007\u002FBF00336957","2024-06-26T02:29:00.729+00:00",[125],"https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002FBF00336957",[1874,1889,1904],{"id":1875,"sortIndex":19,"researcher":18,"roles":1876,"affiliations":1877,"properties":1886,"displayName":1888,"givenName":18,"familyName":18},"c34390f3-750e-493e-a0cd-aaae0374171d",[],[1878],{"id":1879,"sortIndex":19,"affiliation":1880,"properties":18},"e5781e0e-42d4-4424-8572-23045b0ced76",{"id":1879,"createTime":18,"updateTime":18,"relativeEntities":1881,"slug":18,"properties":1882,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":1885,"statistic":18},[],{"title":1883},{"VI":1884},"Department of Physics, University of Crete, Crete, Greece",[],{"title":1887},{"EN":1888},"P. 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