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A neural mechanism of AM frequency selectivity of pyramidal cell circuit in electrosensory lateral-line lobe of weakly electric fish
Neurocomputing 26 }27 (1999) 403}409
A neural mechanism of AM frequency selectivity of pyramidal cell circuit in electrosensory lateral-line lobe of weakly electric "sh Yoshiki Kashimori*, Osamu Hoshino, Takeshi Kambara Department of Applied Physics and Chemistry, The University of Electro-communications, Chofu, Tokyo 182-8585, Japan Accepted 18 December 1998
Abstract To clarify the neuronal mechanism by which a certain amplitude modulation (AM) frequency of electric organ discharge (EOD) is extracted from a single EOD stimulus whose amplitude is modulated simultaneously with various frequency components, we proposed a microscopic model of electrosensory lateral-line lobe (ELL). We showed that the selective extraction of AM frequency comes from the tuning property of a single bp cell and the synchronization of activity among the cells connected mutually with the electric synapses in ELL. 1999 Elsevier Science B.V. All rights reserved. Keywords: Multiple brain map; Weakly electric "sh; AM frequency; Electrosensory lateral-line lobe; A neural model
1. Introduction The electrosensory system allows "sh to locate and identify an object in the absence of visual cues or signals from other "shes [1]. A weakly electric "sh generates an electric signal from its tail, and the current #ow resulting from the electric organ discharge (EOD) causes a voltage to develop across the "sh's skin. The changes in
* Corresponding author. Tel.: #81-424-43-5470; fax: #81-424-89-9748. E-mail address: [email protected] (Y. Kashimori) 0925-2312/99/$ } see front matter 1999 Elsevier Science B.V. All rights reserved. PII: S 0 9 2 5 - 2 3 1 2 ( 9 9 ) 0 0 0 4 5 - 4
404
Y. Kashimori et al. / Neurocomputing 26}27 (1999) 403}409
magnitude and phase of EOD are measured by electroreceptors distributed over the body surface. An object, whose impedance is di!erent from that of the surrounding water, may alter the spatio-temporal pattern of transepidamal voltage, and this alteration is encoded into neural impulse trains by the electroreceptors. The information about the amplitude modulations encoded by the receptors are conveyed to the electrosensory lateral-line lobe (ELL). In natural situations, the modulated EOD stimulus includes multiple information such as moving orientation, velocity, and position of an object, and communication cues. Although it has not been clari"ed yet how these multiple information are represented by EOD modulations, the frequency of modulation of the EOD amplitude is a highly possible way into which the position and velocity of an object and the communication cues are encoded. For example, the signals re#ected by a slow moving object has lower frequencies of amplitude modulation (AM), while the signals re#ected by a rapid moving object has higher AM frequencies. The electrocommunication cue has much higher frequencies [7]. ELL consists of four regions corresponding to four maps extracting information included in four kinds of EOD amplitude modulations, respectively. That is, the four maps are tuned to four di!erent ranges of AM frequencies. Shumway [8] found that pyramidal cells in the three regions of ELL respond best in vivo to three ranges of AM frequencies of EOD waves: 1}3, 4}32, and 64}120 Hz, respectively. It seems reasonable that by using these four kinds of maps, ELL can extract various information contained in the EOD waveforms modulated by multiple sources. In the present paper, we proposed a model of ELL maps with speci"c frequency tunings to clarify the mechanism by which the selective tuning of the AM frequency across the maps is achieved, based on the microscopic properties of ELL pyramidal cells and of connections between them.
2. A model of pyramidal cell circuit of ELL The extensive experimental studies about the structure and function of ELL [2] have been made to understand the neural mechanism of the information processing in ELL. We present here a neural network model of ELL based on its anatomical structure. Fig. 1 shows the innervation structures between P type of receptors and a basilar pyramidal (bp) cell. The bp cells receive not only the a!erent input but also the e!erent input from the higher regions (NPd and EGp) as shown in Fig. 1. A bp cell is excited directly by the inputs from central P-a!erent nerves and inhibited indirectly via two types of granule cells by the inputs from peripheral nerves. The type II granule cell (gr2) and the apical dendrites of the bp cell receive the descending signals from nucleus praeeminentialis (NPd) and posterior eminentia granularis (EGp). The descending input plays an important role in the gain control and adaptation processes of the bp cells. We present a model of a single pyramidal cell which consists of a soma, and apical and basal dendrites. The soma includes active Na> and K> channels, and both the dendrites include active Na>, K>, Ca>, and Ca>-activated K> channels.
Y. Kashimori et al. / Neurocomputing 26}27 (1999) 403}409
405
Fig. 1. Model of the ELL system with receptors and higher brain regions.
The membrane potentials of soma (<), apical dendrite (< "), and basal dendrite G G (< ") are described by G d< G "!g mh (<!E )!g n(<!E )!g (<!E )#I #I C , G , ) G ) * G *
dt 1 # [(< "!<)/i #(< "!<)/i ] G G " G G " S #g [(< !<)#(< !<)], G> G G\ G
(1)
d< " G "! g " (m" )h" (< "!E" )!g "m"h"(< "!E") C , , , G , ) ) ) G )
dt ! g "(m" )h" (< "!E" )!g " m" h" (< "!E") ! ! !? G ! !) !) !) G ) 1 ! g"(< "!E")# (<!< ")#> (t)#> (t), * G * G G , #% So i " "
(2)
d< " G "! g " (m" )h" (< "!E" )!g "m"h"(< "!E") C
dt , , , G , ) ) ) G ) ! g " (m" )h" (< "!E" )!g " (m) )h" (< "!E") ! ! ! G ! !) !) !) G ) 1 ! g"(< "!E")# (<!< ")#I , * G * G G $ So i " " d[Ca>] 6"(!1;10;I6 /2F)!([Ca>] ![Ca>] )/q , ! 6 6 0 dt
(3) (4)
406
Y. Kashimori et al. / Neurocomputing 26}27 (1999) 403}409
where i"1&N, the dynamical variables m , h ,n , of active channels in the soma were calculated based on the Hodgkin}Huxley model [3], and those in apical and basal dendrites, m" and h" (X " Na, K, Ca, CaK), were calculated based 6 6 on the model proposed by Mainen and Sejnowski [6]. [Ca>] (X " AD, BD) 6 is the intracellular Ca> concentration of the X dendrite. S is the surface area of the soma, o (X " AD, BD) is the ratio of the surface area of the X dendrite 6 to that of soma, i (X " AD, BD) are the resistivity of connection between soma and 6 the X dendrite. The bp cell soma are connected with each other by the electric synapse whose conductance is g . Soma and basal dendrite receive the peripheral input from gr cells and a!erent input, respectively. I and I are the synaptic currents from gr1 and gr2 cells, respectively, and I is the synaptic current from P-a!erents. The mathematical $ descriptions of I , I , and I were described in Ref. [5]. $ The apical dendrite receives the descending signals from NPd and EGp as shown in Fig. 1. The descending inputs are induced originally by outputs of bp cells. In the present model, the descending inputs were assumed to be proportional to the sum of the membrane potentials of bp cells with time delay q (Z " NPd, EGp). > and 8 ,. > are the postsynaptic currents of apical dendrite which are induced by the #% descending inputs.
3. Results 3.1. Frequency tuning of a single pyramidal cell We calculated the tuning ability of a pyramidal cell under application of external stimuli with single AM frequency. We used here ten P receptors per receptive "eld of a single bp cell where each receptor has di!erent channel conductances [4]. Six receptors were connected to the basal dendrite of the bp cell, and two receptors were connected with gr2 cells, and two P receptors were connected with gr1 cells. Fig. 2a shows the tuning ability of single bp cell model. The bp cell model generates burst spikes with inherent frequency depending on the somatodendritic interaction. The period of the burst spikes and the number of spikes in a single burst depend on the depolarization after polarization (DAP) which is induced by the current #owing from dendrite to soma. The tuning frequency of the bp cell model is 33 Hz. When the AM frequency of EOD wave is close to the tuning frequency of the pyramidal cell, the cell generates periodically spike bursts where interburst spike distance is close to the period of tuning frequency (see Fig. 2a). The cell cannot be excited cyclically with the frequency of EOD AM, when the AM frequency of the stimulus is much higher than the tuning frequency. When the AM frequency is much lower than the tuning frequency, the cell also cannot "re with the frequency. When the AM frequency is close to the optimal burst frequency of the cell, the burst generation is facilitated by synchronizing with the spike frequency of P-a!erent. When the stimulus amplitude is changed more rapidly than the optimal modulation, the cell cannot follow the rapid variation. When the stimulus amplitude is changed more slowly, the "ring frequency
Y. Kashimori et al. / Neurocomputing 26}27 (1999) 403}409
407
Fig. 2. (a) Responses of single P a!erent and bp cell to EOD stimulus with single AM frequency of 33 Hz. (b) Responses of three bp cells with tuning frequencies of 33, 31, 35 Hz, respectively, in the network to EOD stimulus with single AM frequency of 33 Hz. The bp cells are connected through the electric synapses.
of P-a!erent decreases and as a result the contribution of excitatory input to the cell becomes weaker than that of inhibitory input from peripheral granule cells. 3.2. Frequency extraction based on activity synchronization among bp cells We investigated the response property of a network model in which the tuning frequencies of constituent pyramidal cells are distributed within a certain frequency range. We assumed that the pyramidal cells in the network are connected with each other by electric synapses. Fig. 2b shows that the electric synapses induce the synchronization of burst frequency among the three cells. The tuning frequencies of three bp cells are 31, 33, and 35 Hz, respectively. Only when the bp cells are connected mutually with appropriate synaptic strength, the three bp cells can "re synchronously with a common frequency. This suggests that the bp cells in the network can extract a main component with a single relevant frequency from an EOD stimulus whose amplitude is modulated by various frequency components. The synchronization plays an essentially important role in the extraction of stimulus AM frequency. A single map does not respond to a single EOD AM frequency, but to a range of EOD AM frequencies. When a single bp cell within a map is broadly tuned to a range of EOD AM frequencies, which AM frequency the map extracts is determined by the activity of the bp cell assembly induced by the stimulus.
4. Concluding remarks The next stage of our study is to investigate the neural mechanism by which the multiple maps extract the relevant temporal information from EOD AM stimulus
408
Y. Kashimori et al. / Neurocomputing 26}27 (1999) 403}409
which is modulated simultaneously with di!erent AM frequencies. We will make a model of ELL multiple maps which consists of three kinds of networks with di!erent tuning ranges, in order to simulate the function of the maps somatotopically arranged from the lower AM frequency section to the higher one.
References [1] J. Bastian, Electrolocation, behavior, anatomy, and physiology, in: T.H. Bullock, W. Heiligenberg (Eds.), Electroreception, Wiley, New York, 1986, pp. 577}612. [2] W. Heiligenberg, Neural Nets in Electric Fish, MIT Press, Cambridge, 1991. [3] A.L. Hodgkin, A.F. Huxley, A quantitative description of membrane current and its application to conductance and excitation in nerve, J. Physiol. 117 (1952) 500}544. [4] Y. Kashimori, M. Goto, T. Kambara, A model of P- and T-electroreceptors of weakly electric "sh, Biophys. J. 70 (1996) 2513}2526. [5] Y. Kashimori, T. Kambara, Neural mechanism for elimination of negative e!ect arising from "sh's own motion on electrolocation, in: N. Kasabov, R. Kosma, K. Ko, R. O'shea, G. Coghill, T. Gedeon (Eds.), Progress in Connectionist-based Information Systems, Vol. 1, Springer, Singapore, 1997, pp. 141}144. [6] Z.F. Mainen, T.J. Sejnowski, In#uence of dendrite structure on "ring pattern in model neocortial neurons, Nature 382 (1996) 363}366. [7] W. Metzner, W. Heiligenberg, The coding of signals in the electric communication of the gymnotiform "sh Eigenmannia: from electroreceptors to neurons in the torus semicircularis of the midbrain, J. Comput. Physiol. A 169 (1991) 135}150. [8] C.A. Shumway, Multiple electrosensory maps in the medulla of weakly electric Gymnotiform "sh I. Physiological di!erence, J. Neurosci. 9 (1989) 4388}4399.
Yoshiki Kashimori received his Ph.D. from Osaka City University in 1985. He is a research associate in the Department of Applied Physics and Chemistry, at the University of Electro-Communications. His research interest is to clarify the neural mechanism of information processing in the electrosensory, auditory, gustatory systems, based on modeling of neurons and their network. He also investigates the emergence of dynamical orders in various biological systems, based on the nonlinear dynamics.
Osamu Hoshino received his Ph.D. in Biophysics from the University of ElectroCommunications in 1998. He is presently an assistant professor, Department of Human Welfare Engineering, Faculty of Engineering at Oita University, Oita, Japan. His research interests include neural basis of brain function and animal behavior.
Y. Kashimori et al. / Neurocomputing 26}27 (1999) 403}409
409
Takeshi Kambara received his Ph.D. from Tokyo Institute of Technology in 1970. He is a Professor of biophysics in the Department of Applied Physics and Chemistry and a Professor of biological information science in the Graduate School of Information Systems, at University of Electro-Communications. His scienti"c interests cover the neural mechanism of information processing in olfactory, auditory, visual, gustatory, and electro-sensory systems, and emergence of dynamical orders in various biological complex systems. His research work uses the `in silicoa method.
A neural mechanism of AM frequency selectivity of pyramidal cell circuit in electrosensory lateral-line lobe of weakly electric "sh Yoshiki Kashimori*, Osamu Hoshino, Takeshi Kambara Department of Applied Physics and Chemistry, The University of Electro-communications, Chofu, Tokyo 182-8585, Japan Accepted 18 December 1998
Abstract To clarify the neuronal mechanism by which a certain amplitude modulation (AM) frequency of electric organ discharge (EOD) is extracted from a single EOD stimulus whose amplitude is modulated simultaneously with various frequency components, we proposed a microscopic model of electrosensory lateral-line lobe (ELL). We showed that the selective extraction of AM frequency comes from the tuning property of a single bp cell and the synchronization of activity among the cells connected mutually with the electric synapses in ELL. 1999 Elsevier Science B.V. All rights reserved. Keywords: Multiple brain map; Weakly electric "sh; AM frequency; Electrosensory lateral-line lobe; A neural model
1. Introduction The electrosensory system allows "sh to locate and identify an object in the absence of visual cues or signals from other "shes [1]. A weakly electric "sh generates an electric signal from its tail, and the current #ow resulting from the electric organ discharge (EOD) causes a voltage to develop across the "sh's skin. The changes in
* Corresponding author. Tel.: #81-424-43-5470; fax: #81-424-89-9748. E-mail address: [email protected] (Y. Kashimori) 0925-2312/99/$ } see front matter 1999 Elsevier Science B.V. All rights reserved. PII: S 0 9 2 5 - 2 3 1 2 ( 9 9 ) 0 0 0 4 5 - 4
404
Y. Kashimori et al. / Neurocomputing 26}27 (1999) 403}409
magnitude and phase of EOD are measured by electroreceptors distributed over the body surface. An object, whose impedance is di!erent from that of the surrounding water, may alter the spatio-temporal pattern of transepidamal voltage, and this alteration is encoded into neural impulse trains by the electroreceptors. The information about the amplitude modulations encoded by the receptors are conveyed to the electrosensory lateral-line lobe (ELL). In natural situations, the modulated EOD stimulus includes multiple information such as moving orientation, velocity, and position of an object, and communication cues. Although it has not been clari"ed yet how these multiple information are represented by EOD modulations, the frequency of modulation of the EOD amplitude is a highly possible way into which the position and velocity of an object and the communication cues are encoded. For example, the signals re#ected by a slow moving object has lower frequencies of amplitude modulation (AM), while the signals re#ected by a rapid moving object has higher AM frequencies. The electrocommunication cue has much higher frequencies [7]. ELL consists of four regions corresponding to four maps extracting information included in four kinds of EOD amplitude modulations, respectively. That is, the four maps are tuned to four di!erent ranges of AM frequencies. Shumway [8] found that pyramidal cells in the three regions of ELL respond best in vivo to three ranges of AM frequencies of EOD waves: 1}3, 4}32, and 64}120 Hz, respectively. It seems reasonable that by using these four kinds of maps, ELL can extract various information contained in the EOD waveforms modulated by multiple sources. In the present paper, we proposed a model of ELL maps with speci"c frequency tunings to clarify the mechanism by which the selective tuning of the AM frequency across the maps is achieved, based on the microscopic properties of ELL pyramidal cells and of connections between them.
2. A model of pyramidal cell circuit of ELL The extensive experimental studies about the structure and function of ELL [2] have been made to understand the neural mechanism of the information processing in ELL. We present here a neural network model of ELL based on its anatomical structure. Fig. 1 shows the innervation structures between P type of receptors and a basilar pyramidal (bp) cell. The bp cells receive not only the a!erent input but also the e!erent input from the higher regions (NPd and EGp) as shown in Fig. 1. A bp cell is excited directly by the inputs from central P-a!erent nerves and inhibited indirectly via two types of granule cells by the inputs from peripheral nerves. The type II granule cell (gr2) and the apical dendrites of the bp cell receive the descending signals from nucleus praeeminentialis (NPd) and posterior eminentia granularis (EGp). The descending input plays an important role in the gain control and adaptation processes of the bp cells. We present a model of a single pyramidal cell which consists of a soma, and apical and basal dendrites. The soma includes active Na> and K> channels, and both the dendrites include active Na>, K>, Ca>, and Ca>-activated K> channels.
Y. Kashimori et al. / Neurocomputing 26}27 (1999) 403}409
405
Fig. 1. Model of the ELL system with receptors and higher brain regions.
The membrane potentials of soma (<), apical dendrite (< "), and basal dendrite G G (< ") are described by G d< G "!g mh (<!E )!g n(<!E )!g (<!E )#I #I C , G , ) G ) * G *
dt 1 # [(< "!<)/i #(< "!<)/i ] G G " G G " S #g [(< !<)#(< !<)], G> G G\ G
(1)
d< " G "! g " (m" )h" (< "!E" )!g "m"h"(< "!E") C , , , G , ) ) ) G )
dt ! g "(m" )h" (< "!E" )!g " m" h" (< "!E") ! ! !? G ! !) !) !) G ) 1 ! g"(< "!E")# (<!< ")#> (t)#> (t), * G * G G , #% So i " "
(2)
d< " G "! g " (m" )h" (< "!E" )!g "m"h"(< "!E") C
dt , , , G , ) ) ) G ) ! g " (m" )h" (< "!E" )!g " (m) )h" (< "!E") ! ! ! G ! !) !) !) G ) 1 ! g"(< "!E")# (<!< ")#I , * G * G G $ So i " " d[Ca>] 6"(!1;10;I6 /2F)!([Ca>] ![Ca>] )/q , ! 6 6 0 dt
(3) (4)
406
Y. Kashimori et al. / Neurocomputing 26}27 (1999) 403}409
where i"1&N, the dynamical variables m , h ,n , of active channels in the soma were calculated based on the Hodgkin}Huxley model [3], and those in apical and basal dendrites, m" and h" (X " Na, K, Ca, CaK), were calculated based 6 6 on the model proposed by Mainen and Sejnowski [6]. [Ca>] (X " AD, BD) 6 is the intracellular Ca> concentration of the X dendrite. S is the surface area of the soma, o (X " AD, BD) is the ratio of the surface area of the X dendrite 6 to that of soma, i (X " AD, BD) are the resistivity of connection between soma and 6 the X dendrite. The bp cell soma are connected with each other by the electric synapse whose conductance is g . Soma and basal dendrite receive the peripheral input from gr cells and a!erent input, respectively. I and I are the synaptic currents from gr1 and gr2 cells, respectively, and I is the synaptic current from P-a!erents. The mathematical $ descriptions of I , I , and I were described in Ref. [5]. $ The apical dendrite receives the descending signals from NPd and EGp as shown in Fig. 1. The descending inputs are induced originally by outputs of bp cells. In the present model, the descending inputs were assumed to be proportional to the sum of the membrane potentials of bp cells with time delay q (Z " NPd, EGp). > and 8 ,. > are the postsynaptic currents of apical dendrite which are induced by the #% descending inputs.
3. Results 3.1. Frequency tuning of a single pyramidal cell We calculated the tuning ability of a pyramidal cell under application of external stimuli with single AM frequency. We used here ten P receptors per receptive "eld of a single bp cell where each receptor has di!erent channel conductances [4]. Six receptors were connected to the basal dendrite of the bp cell, and two receptors were connected with gr2 cells, and two P receptors were connected with gr1 cells. Fig. 2a shows the tuning ability of single bp cell model. The bp cell model generates burst spikes with inherent frequency depending on the somatodendritic interaction. The period of the burst spikes and the number of spikes in a single burst depend on the depolarization after polarization (DAP) which is induced by the current #owing from dendrite to soma. The tuning frequency of the bp cell model is 33 Hz. When the AM frequency of EOD wave is close to the tuning frequency of the pyramidal cell, the cell generates periodically spike bursts where interburst spike distance is close to the period of tuning frequency (see Fig. 2a). The cell cannot be excited cyclically with the frequency of EOD AM, when the AM frequency of the stimulus is much higher than the tuning frequency. When the AM frequency is much lower than the tuning frequency, the cell also cannot "re with the frequency. When the AM frequency is close to the optimal burst frequency of the cell, the burst generation is facilitated by synchronizing with the spike frequency of P-a!erent. When the stimulus amplitude is changed more rapidly than the optimal modulation, the cell cannot follow the rapid variation. When the stimulus amplitude is changed more slowly, the "ring frequency
Y. Kashimori et al. / Neurocomputing 26}27 (1999) 403}409
407
Fig. 2. (a) Responses of single P a!erent and bp cell to EOD stimulus with single AM frequency of 33 Hz. (b) Responses of three bp cells with tuning frequencies of 33, 31, 35 Hz, respectively, in the network to EOD stimulus with single AM frequency of 33 Hz. The bp cells are connected through the electric synapses.
of P-a!erent decreases and as a result the contribution of excitatory input to the cell becomes weaker than that of inhibitory input from peripheral granule cells. 3.2. Frequency extraction based on activity synchronization among bp cells We investigated the response property of a network model in which the tuning frequencies of constituent pyramidal cells are distributed within a certain frequency range. We assumed that the pyramidal cells in the network are connected with each other by electric synapses. Fig. 2b shows that the electric synapses induce the synchronization of burst frequency among the three cells. The tuning frequencies of three bp cells are 31, 33, and 35 Hz, respectively. Only when the bp cells are connected mutually with appropriate synaptic strength, the three bp cells can "re synchronously with a common frequency. This suggests that the bp cells in the network can extract a main component with a single relevant frequency from an EOD stimulus whose amplitude is modulated by various frequency components. The synchronization plays an essentially important role in the extraction of stimulus AM frequency. A single map does not respond to a single EOD AM frequency, but to a range of EOD AM frequencies. When a single bp cell within a map is broadly tuned to a range of EOD AM frequencies, which AM frequency the map extracts is determined by the activity of the bp cell assembly induced by the stimulus.
4. Concluding remarks The next stage of our study is to investigate the neural mechanism by which the multiple maps extract the relevant temporal information from EOD AM stimulus
408
Y. Kashimori et al. / Neurocomputing 26}27 (1999) 403}409
which is modulated simultaneously with di!erent AM frequencies. We will make a model of ELL multiple maps which consists of three kinds of networks with di!erent tuning ranges, in order to simulate the function of the maps somatotopically arranged from the lower AM frequency section to the higher one.
References [1] J. Bastian, Electrolocation, behavior, anatomy, and physiology, in: T.H. Bullock, W. Heiligenberg (Eds.), Electroreception, Wiley, New York, 1986, pp. 577}612. [2] W. Heiligenberg, Neural Nets in Electric Fish, MIT Press, Cambridge, 1991. [3] A.L. Hodgkin, A.F. Huxley, A quantitative description of membrane current and its application to conductance and excitation in nerve, J. Physiol. 117 (1952) 500}544. [4] Y. Kashimori, M. Goto, T. Kambara, A model of P- and T-electroreceptors of weakly electric "sh, Biophys. J. 70 (1996) 2513}2526. [5] Y. Kashimori, T. Kambara, Neural mechanism for elimination of negative e!ect arising from "sh's own motion on electrolocation, in: N. Kasabov, R. Kosma, K. Ko, R. O'shea, G. Coghill, T. Gedeon (Eds.), Progress in Connectionist-based Information Systems, Vol. 1, Springer, Singapore, 1997, pp. 141}144. [6] Z.F. Mainen, T.J. Sejnowski, In#uence of dendrite structure on "ring pattern in model neocortial neurons, Nature 382 (1996) 363}366. [7] W. Metzner, W. Heiligenberg, The coding of signals in the electric communication of the gymnotiform "sh Eigenmannia: from electroreceptors to neurons in the torus semicircularis of the midbrain, J. Comput. Physiol. A 169 (1991) 135}150. [8] C.A. Shumway, Multiple electrosensory maps in the medulla of weakly electric Gymnotiform "sh I. Physiological di!erence, J. Neurosci. 9 (1989) 4388}4399.
Yoshiki Kashimori received his Ph.D. from Osaka City University in 1985. He is a research associate in the Department of Applied Physics and Chemistry, at the University of Electro-Communications. His research interest is to clarify the neural mechanism of information processing in the electrosensory, auditory, gustatory systems, based on modeling of neurons and their network. He also investigates the emergence of dynamical orders in various biological systems, based on the nonlinear dynamics.
Osamu Hoshino received his Ph.D. in Biophysics from the University of ElectroCommunications in 1998. He is presently an assistant professor, Department of Human Welfare Engineering, Faculty of Engineering at Oita University, Oita, Japan. His research interests include neural basis of brain function and animal behavior.
Y. Kashimori et al. / Neurocomputing 26}27 (1999) 403}409
409
Takeshi Kambara received his Ph.D. from Tokyo Institute of Technology in 1970. He is a Professor of biophysics in the Department of Applied Physics and Chemistry and a Professor of biological information science in the Graduate School of Information Systems, at University of Electro-Communications. His scienti"c interests cover the neural mechanism of information processing in olfactory, auditory, visual, gustatory, and electro-sensory systems, and emergence of dynamical orders in various biological complex systems. His research work uses the `in silicoa method.