Distributed processing of sensory information in the leech. III. A dynamical neural network model of the local bending reflex

The subpopulation of identified interneurons in the local bending reflex receive multiple inputs from dorsal and ventral mechanoreceptors and have outputs to dorsal and ventral motor neurons. Their connections suggest a distributed processing mechanism in which withdrawal from dorsal, ventral, or lateral stimuli is controlled by a single population of approximately 40 multifunctional interneurons, but it is unclear whether additional interneurons dedicated to particular inputs are needed to account for each kind of bend. We therefore asked whether a model could be constructed that reproduced all behaviors without dedicated interneurons. Interneurons in the model were constrained to receive both dorsal and ventral inputs. Connection strengths were adjusted by gradient descent optimization until the model reproduced the amplitude and time course of motor neuron synaptic potentials in intracellular recordings of the response to many different stimuli. After optimization, the similarity between model and identified interneurons showed that additional dedicated interneurons are not necessary to produce all forms of the behavior. Successful optimization of networks with many fewer interneurons showed that the 40-interneuron network is redundant, raising the possibility that the interneurons have additional functions. Finally, optimizing networks with additional constraints produced better matches to some of the identified interneurons and showed that local bending can be produced by two populations of interneurons: one with outputs consistent with dorsal bending, the other with ventral bending. This suggests a simple model in which two principal types of interneurons produce many different behaviors and predicts the type of interneuron that remains to be identified.

[1]  D. Baylor,et al.  Specific modalities and receptive fields of sensory neurons in CNS of the leech. , 1968, Journal of neurophysiology.

[2]  A. E. Stuart Physiological and morphological properties of motoneurones in the central nervous system of the leech , 1970, The Journal of physiology.

[3]  J. Nicholls,et al.  Modulation of transmission at an inhibitory synapse in the central nervous system of the leech. , 1978, The Journal of physiology.

[4]  T. Poggio,et al.  Retinal ganglion cells: a functional interpretation of dendritic morphology. , 1982, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[5]  W. Kristan SENSORY AND MOTOR NEURONES RESPONSIBLE FOR THE LOCAL BENDING RESPONSE IN LEECHES , 1982 .

[6]  W. O. Friesen,et al.  Physiological and morphological analysis of synaptic transmission between leech motor neurons , 1985, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[7]  D. Rumelhart Learning internal representations by back-propagating errors , 1986 .

[8]  H. Cline Evidence for GABA as a neurotransmitter in the leech , 1986, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[9]  Robert A. Jacobs,et al.  Increased rates of convergence through learning rate adaptation , 1987, Neural Networks.

[10]  W. Kristan,et al.  Function of identified interneurons in the leech elucidated using neural networks trained by back-propagation , 1989, Nature.

[11]  Barak A. Pearlmutter Learning State Space Trajectories in Recurrent Neural Networks , 1989, Neural Computation.

[12]  William W. Lytton,et al.  Localization of a leech inhibitory synapse by photo-ablation of individual dendrites , 1989, Brain Research.

[13]  Kenji Doya,et al.  Adaptive neural oscillator using continuous-time back-propagation learning , 1989, Neural Networks.

[14]  Idan Segev,et al.  Compartmental models of complex neurons , 1989 .

[15]  Terrence J. Sejnowski,et al.  Faster Learning for Dynamic Recurrent Backpropagation , 1990, Neural Computation.

[16]  W. Kristan,et al.  Distributed processing of sensory information in the leech. I. Input- output relations of the local bending reflex , 1990, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[17]  Terrence J. Sejnowski,et al.  A dynamical neural network model of sensorimotor transformations in the leech , 1990, 1990 IJCNN International Joint Conference on Neural Networks.

[18]  S. Lockery,et al.  Distributed processing of sensory information in the leech. II. Identification of interneurons contributing to the local bending reflex , 1990, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[19]  Terrence J. Sejnowski,et al.  A Dynamic Neural Network Model of Sensorimotor Transformations in the Leech , 1990, Neural Computation.

[20]  A. Selverston,et al.  Learning algorithms for oscillatory networks with gap junctions and membrane currents , 1991 .

[21]  R. Calabrese,et al.  Calcium currents and graded synaptic transmission between heart interneurons of the leech , 1991, The Journal of neuroscience : the official journal of the Society for Neuroscience.