Influence of dendritic location and membrane properties on the effectiveness of synapses on cat motoneurones

Barrett, John N.; Crill, W. E.

doi:10.1113/jphysiol.1974.sp010571

Cited by 134 publications

(89 citation statements)

References 32 publications

(56 reference statements)

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“…This function was chosen only for convenience, because the conductances we mean to represent result from the activation of not one but multiple synapses, which are probably located in different regions of the somatodendritic membrane with different degrees of electrotonic attenuation. The time course of conductance change is faster than that of the Vm because the PSP is the temporal integral of the input current (Barrett and Crill, 1974;Kapur et al, 1997). In brief, our results suggest that in Gr cells, the fast inhibitory conductance (Fig.…”

Section: Effect Of Stimulus Intensity On the Composition Of The Synapmentioning

confidence: 60%

Synaptic Responses to Whisker Deflections in Rat Barrel Cortex as a Function of Cortical Layer and Stimulus Intensity

Wilent¹,

Contreras²

2004

J. Neurosci.

127

115

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To study the synaptic and spike responses of barrel cortex neurons as a function of cortical layer and stimulus intensity, we recorded intracellularly in vivo from barbiturate anesthetized rats while increasing the velocity-acceleration of the whisker deflection. Granular (Gr; layer 4) cells had the EPSP with the shortest peak and onset latency, whereas supragranular (SGr; layers 2-3) cells had the EPSP with longest duration and slowest rate of rise. Infragranular (Igr; layers 5-6) cells had intermediate values, and thus each layer was unique. The spike response peak of Gr cells was followed by IGr and then by SGr cells. In all cells, depolarization reduced the duration and amplitude of the response, but only in Gr cells did it reveal an early IPSP that cut short the EPSP. This early IPSP was associated with a large decrease in input resistance and an apparent reversal potential below spike threshold; consequently, synaptic integration in Gr cells was limited to the initial 5-7 msec of the response. In contrast, in SGr and IGr cells, results suggest an overlap in time of the EPSP and IPSP, with a small drop in input resistance and an apparent reversal potential above spike threshold, facilitating input integration for up to 20 msec. Decreasing stimulus intensity (velocity-acceleration) reduced the amplitude and increased the peak latency of the response without altering its synaptic composition. We propose that layer 4 circuits are better suited to perform coincidence detection, whereas supra and infragranular circuits are better designed for input integration.

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Section: Effect Of Stimulus Intensity On the Composition Of The Synapmentioning

confidence: 60%

Synaptic Responses to Whisker Deflections in Rat Barrel Cortex as a Function of Cortical Layer and Stimulus Intensity

Wilent¹,

Contreras²

2004

J. Neurosci.

127

115

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“…Fine-tuning of dendritic arbors ensures both the proper connectivity of neural circuitry and the intrinsic electrical properties of neurons (Barrett and Crill, 1974;Mainen and Sejnowski, 1996;Libersat and Duch, 2004). Although structural remodeling of dendritic shape or postsynaptic plasticity underlies the physiological process of learning and memory (Lamprecht and LeDoux, 2004), abnormal dendritic development is a consistent hallmark of mental retardation syndromes (Fiala et al, 2002;Zoghbi, 2003).…”

Section: Introductionmentioning

confidence: 99%

Constitutively Active Cytoplasmic c-Jun N-Terminal Kinase 1 Is a Dominant Regulator of Dendritic Architecture: Role of Microtubule-Associated Protein 2 as an Effector

Björkblom¹,

Östman²,

Hongisto³

et al. 2005

J. Neurosci.

162

192

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Normal functioning of the nervous system requires precise regulation of dendritic shape and synaptic connectivity. Here, we report a severe impairment of dendritic structures in the cerebellum and motor cortex of c-Jun N-terminal kinase 1 (JNK1)-deficient mice. Using an unbiased screen for candidate mediators, we identify the dendrite-specific high-molecular-weight microtubule-associated protein 2 (MAP2) as a JNK substrate in the brain. We subsequently show that MAP2 is phosphorylated by JNK in intact cells and that MAP2 proline-rich domain phosphorylation is decreased in JNK1Ϫ/Ϫ brain. We developed compartment-targeted JNK inhibitors to define whether a functional relationship exists between the physiologically active, cytosolic pool of JNK and dendritic architecture. Using these, we demonstrate that cytosolic, but not nuclear, JNK determines dendritic length and arbor complexity in cultured neurons. Moreover, we confirm that MAP2-dependent process elongation is enhanced after activation of JNK. Using JNK1Ϫ/Ϫ neurons, we reveal a dominant role for JNK1 over ERK in regulating dendritic arborization, whereas ERK only regulates dendrite shape under conditions in which JNK activity is low (JNK1Ϫ/Ϫ neurons). These results reveal a novel antagonism between JNK and ERK, potentially providing a mechanism for fine-tuning the dendritic arbor. Together, these data suggest that JNK phosphorylation of MAP2 plays an important role in defining dendritic architecture in the brain.

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“…Even though the existence of such nonlinear interactions in a passive dendritic tree has been long recognized, both theoretically and experimentally (1)(2)(3)(4), it has been customary to assume linear summation of excitatory and inhibitory inputs on the dendrites and to regard the threshold associated with spike generation at the axon hillock as performing the elementary logical operations in the nervous system. It is, however, possible that synapses situated close to each other on the dendrite of a cell may interact in a highly nonlinear way.…”

mentioning

confidence: 99%

Nonlinear interactions in a dendritic tree: localization, timing, and role in information processing.

Koch¹,

Poggio²,

Torre³

1983

Proc. Natl. Acad. Sci. U.S.A.

455

323

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In a passive dendritic tree, inhibitory synaptic inputs activating ionic conductances with an equilibrium potential near the resting potential can effectively veto excitatory inputs. Analog interactions of this type can be very powerful if the inputs are appropriately timed and occur at certain locations. We examine with computer simulations the precise conditions required for strong and specific interactions in the case of a 8-like ganglion cell of the cat retina. We find some critical conditions to be that (i) the peak inhibitory conductance changes must be sufficiently large (i.e., ==50 nS or more), (ii) inhibition must be on the direct path from the location of excitation to the soma, and (iii) the time course of excitation and inhibition must substantially overlap. Analog AND-NOT operations realized by satisfying these conditions may underlie direction selectivity in ganglion cells.When two neighboring regions of a dendritic tree experience simultaneous conductance changes-induced by synaptic inputs-the resulting postsynaptic potential at the soma is usually not the sum of the potentials generated by each synapse alone. Even though the existence of such nonlinear interactions in a passive dendritic tree has been long recognized, both theoretically and experimentally (1)(2)(3)(4), it has been customary to assume linear summation of excitatory and inhibitory inputs on the dendrites and to regard the threshold associated with spike generation at the axon hillock as performing the elementary logical operations in the nervous system. It is, however, possible that synapses situated close to each other on the dendrite of a cell may interact in a highly nonlinear way. For Nonlinear synaptic interactions were found to be maximal for y and 8 cells and relatively weaker for a and ( cells. On the basis of this analysis, we conjectured that cells with a 8-like morphology are the substratum for directional selectivity in the retina. In this note, we wish to show the main properties and critical features of the interaction between transient synaptic inputs for the a cell shown in Fig. la, whose geometry was measured from histological (Golgi) material of Boycott and Wassle (11). The main result consists of a set of critical predictions about direction-selective ganglion cells and the organization and properties of their synaptic input.The branching structure, the length, and the diameters of each dendritic segment were determined as described (10, 12). The dendritic tree was approximated by short segments, each being equivalent to a cylinder. A program using Butz and Cowan's algorithm (13) was used to compute from these data (for a range of values of the membrane capacity Cm, membrane resistance Rm, and intracellular resistance R) the linear electrical properties of the cell. We assumed the dendritic membrane to be passive and the spread of current along dendrites to be adequately described by linear cable theory. In the program, the complex transfer resistances K,(w) for any two locations ij in the dendritic tr...

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Influence of dendritic location and membrane properties on the effectiveness of synapses on cat motoneurones

Cited by 134 publications

References 32 publications

Synaptic Responses to Whisker Deflections in Rat Barrel Cortex as a Function of Cortical Layer and Stimulus Intensity

Synaptic Responses to Whisker Deflections in Rat Barrel Cortex as a Function of Cortical Layer and Stimulus Intensity

Constitutively Active Cytoplasmic c-Jun N-Terminal Kinase 1 Is a Dominant Regulator of Dendritic Architecture: Role of Microtubule-Associated Protein 2 as an Effector

Nonlinear interactions in a dendritic tree: localization, timing, and role in information processing.

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