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.

We developed a new method to estimate the spatial extent of summation, the cortical spread, of the local field potential (LFP) throughout all layers of macaque primary visual cortex V1 by taking advantage of the V1 retinotopic map. We mapped multi-unit activity and LFP visual responses with sparse-noise at several cortical sites simultaneously. The cortical magnification factor near the recording sites was precisely estimated by track reconstruction. The new method combined experimental measurements together with a model of signal summation to obtain the cortical spread of the LFP. This new method could be extended to cortical areas that have topographic maps such as S1 or A1, and to cortical areas without functional columnar maps, such as rodent visual cortex. In macaque V1, the LFP was the sum of signals from a very local region, the radius of which was on average 250 m. The LFP's cortical spread varied across cortical layers, reaching a minimum value of 120 m in layer 4B. An important functional consequence of the small cortical spread of the LFP is that the visual field maps of LFP and MUA recorded at a single electrode site were very similar. The similar spatial scale of the visual responses, the restricted cortical spread, and their laminar variation led to new insights about the sources and possible applications of the LFP.

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.

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Studying the laminar pattern of neural activity is crucial for understanding the processing of neural signals in the cerebral cortex. We measured neural population activity [multiunit spike activity (MUA) and local field potential, LFP] in Macaque primary visual cortex (V1) in response to drifting grating stimuli. Sustained visually driven MUA was at an approximately constant level across cortical depth in V1. However, sustained, visually driven, local field potential power, which was concentrated in the γ-band (20-60 Hz), was greatest at the cortical depth corresponding to corticocortical output layers 2, 3, and 4B. γ-band power also tends to be more sustained in the output layers. Overall, cortico-cortical output layers accounted for 67% of total γ-band activity in V1, whereas 56% of total spikes evoked by drifting gratings were from layers 2, 3, and 4B. The high-resolution layer specificity of γ-band power, the laminar distribution of MUA and γ-band activity, and their dynamics imply that neural activity in V1 is generated by laminar-specific mechanisms. In particular, visual responses of MUA and γ-band activity in cortico-cortical output layers 2, 3, and 4B seem to be strongly influenced by laminar-specific recurrent circuitry and/or feedback.B ased on anatomy and neurophysiology, our view of the cerebral cortex has changed. Instead of viewing the cortex as a single network, we now conceive of the cortical laminae as a stack of loosely interconnected but distinct neuronal networks (1-5). Each lamina has different specific inputs, projection targets, and feedback connections.The goal of this study is the determination of the spatial distribution of stimulus-driven neural activity throughout the depth of the cortex and across cortical laminae. Pursuing this goal, we chose to study Macaque primary visual cortex (V1), because V1 is a cortical area where the experimenter has control of the neuronal input by controlling visual stimulation. V1 laminar inputs, outputs, and local connections are well-known (1, 3, 6). Signals come from the thalamus [lateral geniculate nucleus (LGN)] into V1 layers 4C and 6. After intracortical processing, neuronal signals are routed to other cortical areas from cells in superficial layers 2, 3, and 4B of V1; subcortical targets receive cortical outputs from cells in layers 5 and 6. Extrastriate cortical feedback targets layers 2, 3, and 6 (1, 3, 7). The visual functional properties of cells in different layers are markedly different (2, 8-13), reflecting local circuitry that is layer-specific (1, 3, 6). Because of the similarities of laminar cortical circuitry throughout the cerebral cortex (14-16), we used V1 as a test bed to study laminar patterns of stimulus-driven responses.To sample from many neurons in each layer, we measured multiunit spike activity (MUA) and the local field potential (LFP) with multiple microelectrodes (Methods details the operational definitions of MUA and LFP). We measured the power in the LFP at frequencies < 100 Hz, because the largest changes in LFP power...

Oscillatory neural activity within the gamma band (25-90 Hz) is generally thought to be able to provide a timing signal for harmonizing neural computations across different brain regions. Using time-frequency analyses of the dynamics of gamma-band activity in the local field potentials recorded from monkey primary visual cortex, we found identical temporal characteristics of gamma activity in both awake and anesthetized brain states, including large variability of peak frequency, brief oscillatory epochs (Ͻ100 ms on average), and stochastic statistics of the incidence and duration of oscillatory events. These findings indicate that gamma-band activity is temporally unstructured and is inherently a stochastic signal generated by neural networks. This idea was corroborated further by our neuralnetwork simulations. Our results suggest that gamma-band activity is too random to serve as a clock signal for synchronizing neuronal responses in awake as in anesthetized monkeys. Instead, gamma-band activity is more likely to be filtered neuronal network noise. Its mean frequency changes with global state and is reduced under anesthesia.

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.

Consistent with human perceptual data, we found many more black-dominant than white-dominant responses in layer 2/3 neurons of the macaque primary visual cortex (V1). Seeking the mechanism of this black dominance of layer 2/3 neurons, we measured the laminar pattern of population responses (multiunit activity and local field potential) and found that a small preference for black is observable in early responses in layer 4C␤, the parvocellular-input layer, but not in the magnocellular-input layer 4C␣. Surprisingly, further analysis of the dynamics of black-white responses in layers 4C␤ and 2/3 suggested that black-dominant responses in layer 2/3 were not generated simply because of the weak black-dominant inputs from 4C␤. Instead, our results indicated the neural circuitry in V1 is wired with a preference to strengthen black responses. We hypothesize that this selective wiring could be due to (1) feedforward connectivity from black-dominant neurons in layer 4C to cells in layer 2/3 or (2) recurrent interactions between black-dominant neurons in layer 2/3, or a combination of both.