Biomedical subjects

W R Softky

Publications and source records attributed to W R Softky.

3 recordsLinked to original sources

PubMed1996

Comparison of discharge variability in vitro and in vivo in cat visual cortex neurons.

1. In neocortical slices, the majority of neurons fire quite regularly in response to constant current injections. But neurons in the intact animal fire irregularly in response to constant current injection as well as to visual stimuli. 2. To quantify this observation, we developed a new measure of variability, which compares only adjacent interspike intervals and is therefore less sensitive to rate variations than existing measures such as the coefficient of variation of interspike intervals. 3. We find that the variability of firing is much higher in cells of primary visual cortex in the anesthetized cat than in slice. The response to current injected from an intracellular electrode in vivo is also variable, but slightly more regular and less bursty than in response to visual stimuli. 4. Using a new technique for analyzing the variability of integrate-and-fire neurons, we prove that this behavior is consistent with a simple integrate-and-fire model receiving a large amount of synaptic background activity, but not with a noisy spiking mechanism.

Animals↗

PubMed1995

Simple codes versus efficient codes.

Transmission of information is an important function of cortical neurons, so it is conceivable that they have evolved to transmit information efficiently, with low noise and high temporal precision. Such precision is consistent with the output generated by various working models that mimick neuronal activity, from simple integrate-and-fire models to elaborate numerical simulations of realistic-looking neurons. But our current inability to match this data with neurons' detailed spike-generating mechanisms in vivo allows us a wide latitude in interpreting the significance of the various components of their spike code. One extreme hypothesis, the 'simple' model, is that each neuron is noisy and slow, performing a simple computation and transmitting a small amount of information. A competing hypothesis, the 'efficient' model, postulates that a neuron transmits large amounts of information through precise, complex, single-spike computations. Both hypotheses are broadly consistent with the available data. The conflict may only be resolved with the development of new measurement techniques that will allow one to investigate directly the properties that make a neuron efficient--that is, to be able to measure highly transient, localized events inside the thinnest dendrites, which are currently experimentally inaccessible.

Cerebral Cortex↗

PubMed1993

The highly irregular firing of cortical cells is inconsistent with temporal integration of random EPSPs.

How random is the discharge pattern of cortical neurons? We examined recordings from primary visual cortex (V1; Knierim and Van Essen, 1992) and extrastriate cortex (MT; Newsome et al., 1989a) of awake, behaving macaque monkey and compared them to analytical predictions. For nonbursting cells firing at sustained rates up to 300 Hz, we evaluated two indices of firing variability: the ratio of the variance to the mean for the number of action potentials evoked by a constant stimulus, and the rate-normalized coefficient of variation (Cv) of the interspike interval distribution. Firing in virtually all V1 and MT neurons was nearly consistent with a completely random process (e.g., Cv approximately 1). We tried to model this high variability by small, independent, and random EPSPs converging onto a leaky integrate-and-fire neuron (Knight, 1972). Both this and related models predicted very low firing variability (Cv << 1) for realistic EPSP depolarizations and membrane time constants. We also simulated a biophysically very detailed compartmental model of an anatomically reconstructed and physiologically characterized layer V cat pyramidal cell (Douglas et al., 1991) with passive dendrites and active soma. If independent, excitatory synaptic input fired the model cell at the high rates observed in monkey, the Cv and the variability in the number of spikes were both very low, in agreement with the integrate-and-fire models but in strong disagreement with the majority of our monkey data. The simulated cell only produced highly variable firing when Hodgkin-Huxley-like currents (INa and very strong IDR) were placed on distal dendrites. Now the simulated neuron acted more as a millisecond-resolution detector of dendritic spike coincidences than as a temporal integrator. We argue that neurons that act as temporal integrators over many synaptic inputs must fire very regularly. Only in the presence of either fast and strong dendritic nonlinearities or strong synchronization among individual synaptic events will the degree of predicted variability approach that of real cortical neurons.

Action Potentials↗