Fast Coding of Orientation in Primary Visual Cortex (original) (raw)

Early Cortical Orientation Selectivity: How Fast Inhibition Decodes the Order of Spike Latencies

Journal of Computational Neuroscience, 2000

Following a flashed stimulus, I show that a simple neurophysiological mechanism in the primary visual system can generate orientation selectivity based on the first incoming spikes. A biological model of the lateral geniculate nucleus generates an asynchronous wave of spikes, with the most strongly activated neurons firing first. Geniculate activation leads to both the direct excitation of a cortical pyramidal cell and disynaptic feed-forward inhibition. The mechanism provides automatic gain control, so the cortical neurons respond over a wide range of stimulus contrasts. It also demonstrates the biological plausibility of a new computationally efficient neural code: latency rank order coding.

First spikes in visual cortex enable perceptual discrimination

eLife, 2018

Visually guided perceptual decisions involve the sequential activation of a hierarchy of cortical areas. It has been hypothesized that a brief time window of activity in each area is sufficient to enable the decision but direct measurements of this time window are lacking. To address this question, we develop a visual discrimination task in mice that depends on visual cortex and in which we precisely control the time window of visual cortical activity as the animal performs the task at different levels of difficulty. We show that threshold duration of activity in visual cortex enabling perceptual discrimination is between 40 and 80 milliseconds. During this time window the vast majority of neurons discriminating the stimulus fire one or no spikes and less than 16% fire more than two. This result establishes that the firing of the first visually evoked spikes in visual cortex is sufficient to enable a perceptual decision.

Timing precision in population coding of natural scenes in the early visual system

Frontiers in Systems Neuroscience, 2009

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 of neuronal information in a rapid perceptual judgment

Journal of neurophysiology, 2009

In many situations, such as pedestrians crossing a busy street or prey evading predators, rapid decisions based on limited perceptual information are critical for survival. The brevity of these perceptual judgments constrains how neuronal signals are integrated or pooled over time because the underlying sequence of processes, from sensation to perceptual evaluation to motor planning and execution, all occur within several hundred milliseconds. Because most previous physiological studies of these processes have relied on tasks requiring considerably longer temporal integration, the neuronal basis of such rapid decisions remains largely unexplored. In this study, we examine the temporal precision of neuronal activity associated with a rapid perceptual judgment. We find that the activity of individual neurons over tens of milliseconds can reliably convey information about sensory events and was well correlated with the animals' judgments. There was a strong correlation between sensory reliability and the correlation with behavioral choice, suggesting that rapid decisions were preferentially based on the most reliable sensory signals. We also find that a simple model in which the responses of a small number of individual neurons (Ͻ5) are summed can completely explain behavioral performance. These results suggest that neuronal circuits are sufficiently precise to allow for cognitive decisions to be based on small numbers of action potentials from highly reliable neurons.

Stochastic Nature of Precisely Timed Spike Patterns in Visual System Neuronal Responses

1999

Stochastic nature of precisely timed spike patterns in visual system neuronal responses. J. Neurophysiol. 81: 3021-3033, 1999. It is not clear how information related to cognitive or psychological processes is carried by or represented in the responses of single neurons. One provocative proposal is that precisely timed spike patterns play a role in carrying such information. This would require that these spike patterns have the potential for carrying information that would not be available from other measures such as spike count or latency. We examined exactly timed (1-ms precision) triplets and quadruplets of spikes in the stimulus-elicited responses of lateral geniculate nucleus (LGN) and primary visual cortex (V1) neurons of the awake fixating rhesus monkey. Large numbers of these precisely timed spike patterns were found. Information theoretical analysis showed that the precisely timed spike patterns carried only information already available from spike count, suggesting that the number of precisely timed spike patterns was related to firing rate. We therefore examined statistical models relating precisely timed spike patterns to response strength. Previous statistical models use observed properties of neuronal responses such as the peristimulus time histogram, interspike interval, and/or spike count distributions to constrain the parameters of the model. We examined a new stochastic model, which unlike previous models included all three of these constraints and unlike previous models predicted the numbers and types of observed precisely timed spike patterns. This shows that the precise temporal structures of stimulus-elicited responses in LGN and V1 can occur by chance. We show that any deviation of the spike count distribution, no matter how small, from a Poisson distribution necessarily changes the number of precisely timed spike patterns expected in neural responses. Overall the results indicate that the fine temporal structure of responses can only be interpreted once all the coarse temporal statistics of neural responses have been taken into account. PREDICTING REPLICATING PATTERNS OF SPIKE ARRIVAL TIMES

Spike-based strategies for rapid processing

Neural Networks, 2001

Most experimental and theoretical studies of brain function assume that neurons transmit information as a rate code, but recent studies on the speed of visual processing impose temporal constraints that appear incompatible with such a coding scheme. Other coding schemes that use the pattern of spikes across a population a neurons may be much more efficient. For example, since strongly activated neurons tend to fire first, one can use the order of firing as a code. We argue that Rank Order Coding is not only very efficient, but also easy to implement in biological hardware: neurons can be made sensitive to the order of activation of their inputs by including a feed-forward shunting inhibition mechanism that progressively desensitizes the neuronal population during a wave of afferent activity. In such a case, maximum activation will only be produced when the afferent inputs are activated in the order of their synaptic weights.

Cellular Mechanisms of Temporal Sensitivity in Visual Cortex Neurons

The Journal of Neuroscience, 2010

The ability of cortical neurons to accurately encode the temporal pattern of their inputs has important consequences for cortical function and perceptual acuity. Here we identify cellular mechanisms underlying the sensitivity of cortical neurons to the timing of sensory-evoked synaptic inputs. We find that temporally coincident inputs to layer 4 neurons in primary visual cortex evoke an increase in spike precision and supralinear spike summation. Underlying this nonlinear summation are changes in the evoked excitatory conductance and the associated membrane potential response, and a lengthening of the window between excitation and inhibition. Furthermore, fast-spiking inhibitory interneurons in layer 4 exhibit a shorter window of temporal sensitivity compared with excitatory neurons. In contrast to the enhanced response to synchronous inputs by layer 4 neurons, sensory input integration in downstream cortical layers is more linear and less sensitive to timing. Neurons in the input l...

Response variability and timing precision of neuronal spike trains in vivo

Journal of neurophysiology, 1997

We report that neuronal spike trains can exhibit high, stimulus-dependent temporal precision even while the trial-to-trial response variability, measured in several traditional ways, remains substantially independent of the stimulus. We show that retinal ganglion cells and neurons in the lateral geniculate nucleus (LGN) of cats in vivo display both these aspects of firing behavior, which have previously been reported to be contradictory. We develop a simple model that treats neurons as "leaky" integrate-and-fire devices and show that it, too, can exhibit both behaviors. We consider the implications of our findings for the problem of neural coding.