Chong Weng

Temporal precision in the neural code and the timescales of natural vision.

The timing of action potentials relative to sensory stimuli can be precise down to milliseconds in the visual system, even though the relevant timescales of natural vision are much slower. The existence of such precision contributes to a fundamental debate over the basis of the neural code and, specifically, what timescales are important for neural computation. Using recordings in the lateral geniculate nucleus, here we demonstrate that the relevant timescale of neuronal spike trains depends on the frequency content of the visual stimulus, and that ‘relative’, not absolute, precision is maintained both during spatially uniform white-noise visual stimuli and naturalistic movies. Using information-theoretic techniques, we demonstrate a clear role of relative precision, and show that the experimentally observed temporal structure in the neuronal response is necessary to represent accurately the more slowly changing visual world. By establishing a functional role of precision, we link visual neuron function on slow timescales to temporal structure in the response at faster timescales, and uncover a straightforward purpose of fine-timescale features of neuronal spike trains.

On and off domains of geniculate afferents in cat primary visual cortex

On- and off-center geniculate afferents form two major channels of visual processing that are thought to converge in the primary visual cortex. However, humans with severely reduced on responses can have normal visual acuity when tested in a white background, which indicates that off channels can function relatively independently from on channels under certain conditions. Consistent with this functional independence of channels, we demonstrate here that on- and off-center geniculate afferents segregate in different domains of the cat primary visual cortex and that off responses dominate the cortical representation of the area centralis. On average, 70% of the geniculate afferents converging at the same cortical domain had receptive fields of the same contrast polarity. Moreover, off-center afferents dominated the representation of the area centralis in the cortex, but not in the thalamus, indicating that on- and off-center afferents are balanced in number, but not in the amount of cortical territory that they cover.

Adaptation to stimulus contrast and correlations during natural visual stimulation

In this study, we characterize the adaptation of neurons in the cat lateral geniculate nucleus to changes in stimulus contrast and correlations. By comparing responses to high- and low-contrast natural scene movie and white noise stimuli, we show that an increase in contrast or correlations results in receptive fields with faster temporal dynamics and stronger antagonistic surrounds, as well as decreases in gain and selectivity. We also observe contrast- and correlation-induced changes in the reliability and sparseness of neural responses. We find that reliability is determined primarily by processing in the receptive field (the effective contrast of the stimulus), while sparseness is determined by the interactions between several functional properties. These results reveal a number of adaptive phenomena and suggest that adaptation to stimulus contrast and correlations may play an important role in visual coding in a dynamic natural environment.

Dynamic encoding of natural luminance sequences by LGN bursts

In the lateral geniculate nucleus (LGN) of the thalamus, visual stimulation produces two distinct types of responses known as tonic and burst. Due to the dynamics of the T-type Ca 2+ channels involved in burst generation, the type of response evoked by a particular stimulus depends on the resting membrane potential, which is controlled by a network of modulatory connections from other brain areas. In this study, we use simulated responses to natural scene movies to describe how modulatory and stimulus-driven changes in LGN membrane potential interact to determine the luminance sequences that trigger burst responses. We find that at low resting potentials, when the T channels are de-inactivated and bursts are relatively frequent, an excitatory stimulus transient alone is sufficient to evoke a burst. However, to evoke a burst at high resting potentials, when the T channels are inactivated and bursts are relatively rare, prolonged inhibitory stimulation followed by an excitatory transient is required. We also observe evidence of these effects in vivo, where analysis of experimental recordings demonstrates that the luminance sequences that trigger bursts can vary dramatically with the overall burst percentage of the response. To characterize the functional consequences of the effects of resting potential on burst generation, we simulate LGN responses to different luminance sequences at a range of resting potentials with and without a mechanism for generating bursts. Using analysis based on signal detection theory, we show that bursts enhance detection of specific luminance sequences, ranging from the onset of excitatory sequences at low resting potentials to the offset of inhibitory sequences at high resting potentials. These results suggest a dynamic role for burst responses during visual processing that may change according to behavioral state.

Timing Precision in Population Coding of Natural Scenes in the Early Visual System

The timing of spiking activity across neurons is a fundamental aspect of the neural population code. Individual neurons in the retina, thalamus, and cortex can have very precise and repeatable responses but exhibit degraded temporal precision in response to suboptimal stimuli. To investigate the functional implications for neural populations in natural conditions, we recorded in vivo the simultaneous responses, to movies of natural scenes, of multiple thalamic neurons likely converging to a common neuronal target in primary visual cortex. We show that the response of individual neurons is less precise at lower contrast, but that spike timing precision across neurons is relatively insensitive to global changes in visual contrast. Overall, spike timing precision within and across cells is on the order of 10 ms. Since closely timed spikes are more efficient in inducing a spike in downstream cortical neurons, and since fine temporal precision is necessary to represent the more slowly varying natural environment, we argue that preserving relative spike timing at a ∼10-ms resolution is a crucial property of the neural code entering cortex.

Temporal Precision in the Visual Pathway through the Interplay of Excitation and Stimulus-Driven Suppression

Visual neurons can respond with extremely precise temporal patterning to visual stimuli that change on much slower time scales. Here, we investigate how the precise timing of cat thalamic spike trains—which can have timing as precise as 1 ms—is related to the stimulus, in the context of both artificial noise and natural visual stimuli. Using a nonlinear modeling framework applied to extracellular data, we demonstrate that the precise timing of thalamic spike trains can be explained by the interplay between an excitatory input and a delayed suppressive input that resembles inhibition, such that neuronal responses only occur in brief windows where excitation exceeds suppression. The resulting description of thalamic computation resembles earlier models of contrast adaptation, suggesting a more general role for mechanisms of contrast adaptation in visual processing. Thus, we describe a more complex computation underlying thalamic responses to artificial and natural stimuli that has implications for understanding how visual information is represented in the early stages of visual processing.

Functional Consequences of Neuronal Divergence Within the Retinogeniculate Pathway

The neuronal connections from the retina to the dorsal lateral geniculate nucleus (dLGN) are characterized by a high specificity. Each retinal ganglion cell diverges to connect to a small group of geniculate cells and each geniculate cell receives input from a small number of retinal ganglion cells. Consistent with the high specificity of the connections, geniculate cells sharing input from the same retinal afferent are thought to have very similar receptive fields. However, the magnitude of the receptive-field mismatches, which has not been systematically measured across the different cell types in dLGN, seems to be in contradiction with the functional anatomy of the Y visual pathway: Y retinal afferents in the cat diverge into two geniculate layers (A and C) that have Y geniculate cells (Y(A) and Y(C)) with different receptive-field sizes, response latencies, nonlinearity of spatial summation, and contrast sensitivity. To better understand the functional consequences of retinogeniculate divergence, we recorded from pairs of geniculate cells that shared input from a common retinal afferent across layers and within the same layer in dLGN. We found that nearly all cell pairs that shared retinal input across layers had Y-type receptive fields of the same sign (i.e., both on-center) that overlapped by >70%, but frequently differed in size and response latency. The receptive-field mismatches were relatively small in value (receptive-field size ratio <5; difference in peak response <5 ms), but were robustly correlated with the strength of the synchronous firing generated by the shared retinal connections (R(2) = 0.75). On average, the percentage of geniculate spikes that could be attributed to shared retinal inputs was about 10% for all cell-pair combinations studied. These results are used to provide new estimates of retinogeniculate divergence for different cell classes.