Biomedical subjects

Jorge Golowasch

Publications and source records attributed to Jorge Golowasch.

5 recordsLinked to original sources

PubMed2006

Ionic mechanism underlying recovery of rhythmic activity in adult isolated neurons.

Neurons exhibit long-term excitability changes necessary for maintaining proper cell and network activity in response to various inputs and perturbations. For instance, the adult crustacean pyloric network can spontaneously recover rhythmic activity after complete shutdown resulting from permanent removal of neuromodulatory inputs. Dissociated lobster stomatogastric ganglion (STG) neurons have been shown to spontaneously develop oscillatory activity via excitability changes. Rhythmic electrical stimulation can eliminate these oscillatory patterns in some cells. The ionic mechanisms underlying these changes are only partially understood. We used dissociated crab STG neurons to study the ionic mechanisms underlying spontaneous recovery of rhythmic activity and stimulation-induced activity changes. Similar to lobster neurons, rhythmic activity spontaneously develops in crab STG neurons. Rhythmic hyperpolarizing stimulation can eliminate, but more commonly accelerate, the emergence of stable oscillatory activity depending on Ca(2+) influx at hyperpolarized voltages. Our main finding is that upregulation of a Ca(2+) current and downregulation of a high-threshold K(+) current underlies the spontaneous homeostatic development of oscillatory activity. However, because of a nonlinear dependence on stimulus frequency, hyperpolarization-induced oscillations appear to be inconsistent with a homeostatic regulation of activity. We find no difference in the activity patterns or the underlying ionic currents involved between neurons of the fast pyloric and the slow gastric mill networks during the first 10 days in isolation. Dynamic-clamp experiments confirm that these conductance modifications can explain the observed activity changes. We conclude that spontaneous and stimulation-induced excitability changes in STG neurons can both result in intrinsic oscillatory activity via regulation of the same two conductances.

Action Potentials↗

PubMed2006

Signal transmission between gap-junctionally coupled passive cables is most effective at an optimal diameter.

We analyze simple morphological configurations that represent gap-junctional coupling between neuronal processes or between muscle fibers. Specifically, we use cable theory and simulations to examine the consequences of current flow from one cable to other gap-junctionally coupled passive cables. When the proximal end of the first cable is voltage clamped, the amplitude of the electrical signal in distal portions of the second cable depends on the cable diameter. However, this amplitude does not simply increase if cable diameter is increased, as expected from the larger length constant; instead, an optimal diameter exists. The optimal diameter arises because the dependency of voltage attenuation along the second cable on cable diameter follows two opposing rules. As cable diameter increases, the attenuation decreases because of a larger length constant yet increases because of a reduction in current density arising from the limiting effect of the gap junction on current flow into the second cable. The optimal diameter depends on the gap junction resistance and cable parameters. In branched cables, dependency on diameter is local and thus may serve to functionally compartmentalize branches that are coupled to other cells. Such compartmentalization may be important when periodic signals or action potentials cause the current flow across gap junctions.

Action Potentials↗

PubMed2005

Effect of electrical coupling on ionic current and synaptic potential measurements.

Recent studies have found electrical coupling to be more ubiquitous than previously thought, and coupling through gap junctions is known to play a crucial role in neuronal function and network output. In particular, current spread through gap junctions may affect the activation of voltage-dependent conductances as well as chemical synaptic release. Using voltage-clamp recordings of two strongly electrically coupled neurons of the lobster stomatogastric ganglion and conductance-based models of these neurons, we identified effects of electrical coupling on the measurement of leak and voltage-gated outward currents, as well as synaptic potentials. Experimental measurements showed that both leak and voltage-gated outward currents are recruited by gap junctions from neurons coupled to the clamped cell. Nevertheless, in spite of the strong coupling between these neurons, the errors made in estimating voltage-gated conductance parameters were relatively minor (<10%). Thus in many cases isolation of coupled neurons may not be required if a small degree of measurement error of the voltage-gated currents or the synaptic potentials is acceptable. Modeling results show, however, that such errors may be as high as 20% if the gap-junction position is near the recording site or as high as 90% when measuring smaller voltage-gated ionic currents. Paradoxically, improved space clamp increases the errors arising from electrical coupling because voltage control across gap junctions is poor for even the highest realistic coupling conductances. Furthermore, the common procedure of leak subtraction can add an extra error to the conductance measurement, the sign of which depends on the maximal conductance.

Analysis of Variance↗

PubMed2003

Episodic bouts of activity accompany recovery of rhythmic output by a neuromodulator- and activity-deprived adult neural network.

The pyloric rhythm of the stomatogastric ganglion of the crab, Cancer borealis, slows or stops when descending modulatory inputs are acutely removed. However, the rhythm spontaneously resumes after one or more days in the absence of neuromodulatory input. We recorded continuously for days to characterize quantitatively this recovery process. Activity bouts lasting 40-900 s began several hours after removal of neuromodulatory input and were followed by stable rhythm recovery after 1-4 days. Bout duration was not related to the intervals (0.3-800 min) between bouts. During an individual bout, the frequency rapidly increased and then decreased more slowly. Photoablation of back-filled neuromodulatory terminals in the stomatogastric ganglion (STG) neuropil had no effect on activity bouts or recovery, suggesting that these processes are intrinsic to the STG neuronal network. After removal of neuromodulatory input, the phase relationships of the components of the triphasic pyloric rhythm were altered, and then over time the phase relationships moved toward their control values. Although at low pyloric rhythm frequency the phase relationships among pyloric network neurons depended on frequency, the changes in frequency during recovery did not completely account for the change in phase seen after rhythm recovery. We suggest that activity bouts represent underlying mechanisms controlling the restructuring of the pyloric network to allow resumption of an appropriate output after removal of neuromodulatory input.

Action Potentials↗

PubMed2002

Failure of averaging in the construction of a conductance-based neuron model.

Parameters for models of biological systems are often obtained by averaging over experimental results from a number of different preparations. To explore the validity of this procedure, we studied the behavior of a conductance-based model neuron with five voltage-dependent conductances. We randomly varied the maximal conductance of each of the active currents in the model and identified sets of maximal conductances that generate bursting neurons that fire a single action potential at the peak of a slow membrane potential depolarization. A model constructed using the means of the maximal conductances of this population is not itself a one-spike burster, but rather fires three action potentials per burst. Averaging fails because the maximal conductances of the population of one-spike bursters lie in a highly concave region of parameter space that does not contain its mean. This demonstrates that averages over multiple samples can fail to characterize a system whose behavior depends on interactions involving a number of highly variable components.

Action Potentials↗