David Ferster

Stimulus onset quenches neural variability: a widespread cortical phenomenon

Neural responses are typically characterized by computing the mean firing rate, but response variability can exist across trials. Many studies have examined the effect of a stimulus on the mean response, but few have examined the effect on response variability. We measured neural variability in 13 extracellularly recorded datasets and one intracellularly recorded dataset from seven areas spanning the four cortical lobes in monkeys and cats. In every case, stimulus onset caused a decline in neural variability. This occurred even when the stimulus produced little change in mean firing rate. The variability decline was observed in membrane potential recordings, in the spiking of individual neurons and in correlated spiking variability measured with implanted 96-electrode arrays. The variability decline was observed for all stimuli tested, regardless of whether the animal was awake, behaving or anaesthetized. This widespread variability decline suggests a rather general property of cortex, that its state is stabilized by an input.

Synchronous Membrane Potential Fluctuations in Neurons of the Cat Visual Cortex

We have recorded intracellularly from pairs of neurons less than 500 microm distant from one another in V1 of anesthetized cats. Cross-correlation of spontaneous fluctuations in membrane potential revealed significant correlations between the cells in each pair. This synchronization was not dependent on the occurrence of action potentials, indicating that it was not caused by mutual interconnections. The cells were synchronized continuously rather than for brief epochs. Much weaker correlations were found between the EEG and intracellular potentials, suggesting local, rather than global, synchrony. The highest correlation occurred among cells with similar connectivity from the LGN and similar receptive fields. During visual stimulation, correlations increased when both cells responded to the stimulus and decreased when neither cell responded.

Strength and orientation tuning of the thalamic input to simple cells revealed by electrically evoked cortical suppression

Is thalamic input to the visual cortex strong and well tuned for orientation, as predicted by Hubel and Wiesels (1962) model of orientation selectivity in simple cells? We directly measured the size of the thalamic input to single simple cells intracellularly by combining electrical stimulation of the cortex with a briefly flashed visual stimulus. In nearby cells, the electrical stimulation evoked a long-lasting inhibition that prevented them from firing in response to the visual stimulus. The visually evoked excitatory postsynaptic potentials (EPSPs) recorded during the period of cortical suppression, therefore, reflected largely the thalamic input. In 16 neurons that received monosynaptic input from the thalamus, cortical suppression left 46% of normal visual response on average (12%-86% in range). In those cells tested, this remaining visual response was as well tuned for orientation as the normal response to the visual stimulus alone. We conclude that the thalamic input to cortical simple cells with monosynaptic input from the thalamus is strong and well tuned in orientation, and that the intracortical input does not appear to sharpen orientation tuning in these cells.

Inhibition, Spike Threshold, and Stimulus Selectivity in Primary Visual Cortex

Ever since Hubel and Wiesel described orientation selectivity in the visual cortex, the question of how precise selectivity emerges has been marked by considerable debate. There are essentially two views of how selectivity arises. Feed-forward models rely entirely on the organization of thalamocortical inputs. Feedback models rely on lateral inhibition to refine selectivity relative to a weak bias provided by thalamocortical inputs. The debate is driven by two divergent lines of evidence. On the one hand, many response properties appear to require lateral inhibition, including precise orientation and direction selectivity and crossorientation suppression. On the other hand, intracellular recordings have failed to find consistent evidence for lateral inhibition. Here we demonstrate a resolution to this paradox. Feed-forward models incorporating the intrinsic nonlinear properties of cortical neurons and feed-forward circuits (i.e., spike threshold, contrast saturation, and spike-rate rectification) can account for properties that have previously appeared to require lateral inhibition.

Inhibitory Stabilization of the Cortical Network Underlies Visual Surround Suppression

In what regime does the cortical circuit operate? Our intracellular studies of surround suppression in cat primary visual cortex (V1) provide strong evidence on this question. Although suppression has been thought to arise from an increase in lateral inhibition, we find that the inhibition that cells receive is reduced, not increased, by a surround stimulus. Instead, suppression is mediated by a withdrawal of excitation. Thalamic recordings and previous work show that these effects cannot be explained by a withdrawal of thalamic input. We find in theoretical work that this behavior can only arise if V1 operates as an inhibition-stabilized network (ISN), in which excitatory recurrence alone is strong enough to destabilize visual responses but feedback inhibition maintains stability. We confirm two strong tests of this scenario experimentally and show through simulation that observed cell-to-cell variability in surround effects, from facilitation to suppression, can arise naturally from variability in the ISN.

Direction Selectivity of Excitation and Inhibition in Simple Cells of the Cat Primary Visual Cortex

Direction selectivity in simple cells of primary visual cortex, defined from their spike responses, cannot be predicted using linear models. It has been suggested that the shunting inhibition evoked by visual stimulation is responsible for the nonlinear component of direction selectivity. Cortical inhibition would suppress a neurons firing when stimuli move in the nonpreferred direction, but would allow responses to stimuli in the preferred direction. Models of direction selectivity based solely on input from the lateral geniculate nucleus, however, propose that the nonlinear response is caused by spike threshold. By extracting excitatory and inhibitory components of synaptic inputs from intracellular records obtained in vivo, we demonstrate that excitation and inhibition are tuned for the same direction, but differ in relative timing. Further, membrane potential responses combine in a linear fashion. Spike threshold, however, quantitatively accounts for the nonlinear component of direction selectivity, amplifying the direction selectivity of spike output relative to that of synaptic inputs.

Stimulus dependence of two-state fluctuations of membrane potential in cat visual cortex

Membrane potentials of cortical neurons fluctuate between a hyperpolarized (‘down’) state and a depolarized (‘up’) state which may be separated by up to 30 mV, reflecting rapid but infrequent transitions between two patterns of synaptic input. Here we show that such fluctuations may contribute to representation of visual stimuli by cortical cells. In complex cells of anesthetized cats, where such fluctuations are most prominent, prolonged visual stimulation increased the probability of the up state. This probability increase was related to stimulus strength: its dependence on stimulus orientation and contrast matched each cells averaged membrane potential. Thus large fluctuations in membrane potential are not simply noise on which visual responses are superimposed, but may provide a substrate for encoding sensory information.

The contribution of spike threshold to the dichotomy of cortical simple and complex cells.

The existence of two classes of cells, simple and complex, discovered by Hubel and Wiesel in 1962, is one of the fundamental features of cat primary visual cortex. A quantitative measure used to distinguish simple and complex cells is the ratio between modulated and unmodulated components of spike responses to drifting gratings, an index that forms a bimodal distribution. We have found that the modulation ratio, when derived from the subthreshold membrane potential instead of from spike rate, is unimodally distributed, but highly skewed. The distribution of the modulation ratio as derived from spike rate can, in turn, be predicted quantitatively by the nonlinear properties of spike threshold applied to the skewed distribution of the subthreshold modulation ratio. Threshold also increases the spatial segregation of ON and OFF regions of the receptive field, a defining attribute of simple cells. The distinction between simple and complex cells is therefore enhanced by threshold, much like the selectivity for stimulus features such as orientation and direction. In this case, however, a continuous distribution in the spatial organization of synaptic inputs is transformed into two distinct classes of cells.

The Emergence of Contrast-Invariant Orientation Tuning in Simple Cells of Cat Visual Cortex

Simple cells in primary visual cortex exhibit contrast-invariant orientation tuning, in seeming contradiction to feed-forward models that rely on lateral geniculate nucleus (LGN) input alone. Contrast invariance has therefore been thought to depend on the presence of intracortical lateral inhibition. In vivo intracellular recordings instead suggest that contrast invariance can be explained by three properties of the excitatory pathway. (1) Depolarizations evoked by orthogonal stimuli are determined by the amount of excitation a cell receives from the LGN, relative to the excitation it receives from other cortical cells. (2) Depolarizations evoked by preferred stimuli saturate at lower contrasts than the spike output of LGN relay cells. (3) Visual stimuli evoke contrast-dependent changes in trial-to-trial variability, which lead to contrast-dependent changes in the relationship between membrane potential and spike rate. Thus, high-contrast, orthogonally oriented stimuli that evoke significant depolarizations evoke few spikes. Together these mechanisms, without lateral inhibition, can account for contrast-invariant stimulus selectivity.

Cracking the neuronal code

How does the brain code information? Ferster and Spruston weigh the evidence in favor of a rate code (that the rate of action-potential firing carries the key information) and a temporal code (in which the pattern of firing is crucial, not just the rate).