Information Carried by Population Spike Times in the Whisker Sensory Cortex can be Decoded Without Knowledge of Stimulus Time

Computational analyses have revealed that precisely timed spikes emitted by somatosensory cortical neuronal populations encode basic stimulus features in the rat's whisker sensory system. Efficient spike time based decoding schemes both for the spatial location of a stimulus and for the kinetic features of complex whisker movements have been defined. To date, these decoding schemes have been based upon spike times referenced to an external temporal frame – the time of the stimulus itself. Such schemes are limited by the requirement of precise knowledge of the stimulus time signal, and it is not clear whether stimulus times are known to rats making sensory judgments. Here, we first review studies of the information obtained from spike timing referenced to the stimulus time. Then we explore new methods for extracting spike train information independently of any external temporal reference frame. These proposed methods are based on the detection of stimulus-dependent differences in the firing time within a neuronal population. We apply them to a data set using single-whisker stimulation in anesthetized rats and find that stimulus site can be decoded based on the millisecond-range relative differences in spike times even without knowledge of stimulus time. If spike counts alone are measured over tens or hundreds of milliseconds rather than milliseconds, such decoders are much less effective. These results suggest that decoding schemes based on millisecond-precise spike times are likely to subserve robust and information-rich transmission of information in the somatosensory system

Neuronal Encoding of Texture in the Whisker Sensory Pathway

A major challenge of sensory systems neuroscience is to quantify brain activity underlying perceptual experiences and to explain this activity as the outcome of elemental neuronal response properties. Rats make extremely fine discriminations of texture by “whisking” their vibrissae across an object's surface, yet the neuronal coding underlying texture sensations remains unknown. Measuring whisker vibrations during active whisking across surfaces, we found that each texture results in a unique “kinetic signature” defined by the temporal profile of whisker velocity. We presented these texture-induced vibrations as stimuli while recording responses of first-order sensory neurons and neurons in the whisker area of cerebral cortex. Each texture is encoded by a distinctive, temporally precise firing pattern. To look for the neuronal coding properties that give rise to texture-specific firing patterns, we delivered horizontal and vertical whisker movements that varied randomly in time (“white noise”) and found that the response probabilities of first-order neurons and cortical neurons vary systematically according to whisker speed and direction. We applied the velocity-tuned spike probabilities derived from white noise to the sequence of velocity features in the texture to construct a simulated texture response. The close match between the simulated and real responses indicates that texture coding originates in the selectivity of neurons to elemental kinetic events

Supralinear and Supramodal Integration of Visual and Tactile Signals in Rats: Psychophysics and Neuronal Mechanisms

To better understand how object recognition can be triggered independently of the sensory channel through which information is acquired, we devised a task in which rats judged the orientation of a raised, black and white grating. They learned to recognize two categories of orientation: 0° ± 45° ("horizontal") and 90° ± 45° ("vertical"). Each trial required a visual (V), a tactile (T), or a visual-tactile (VT) discrimination; VT performance was better than that predicted by optimal linear combination of V and T signals, indicating synergy between sensory channels. We examined posterior parietal cortex (PPC) and uncovered key neuronal correlates of the behavioral findings: PPC carried both graded information about object orientation and categorical information about the rat's upcoming choice; single neurons exhibited identical responses under the three modality conditions. Finally, a linear classifier of neuronal population firing replicated the behavioral findings. Taken together, these findings suggest that PPC is involved in the supramodal processing of shape. Knowledge about objects can be accessed through multiple sensory pathways. Nikbakht et al. find that rats judge object orientation by synergistically combining signals from vision and touch; posterior parietal cortex seems to be involved in the supramodal knowledge of orientation

Auditory stimuli elicit hippocampal neuronal responses during sleep

To investigate how hippocampal neurons code behaviorally salient stimuli, we recorded from neurons in the CA1 region of hippocampus in rats while they learned to associate the presence of sound with water reward. Rats learned to alternate between two reward ports at which, in 50% of the trials, sound stimuli were presented followed by water reward after a 3-s delay. Sound at the water port predicted subsequent reward delivery in 100% of the trials and the absence of sound predicted reward omission. During this task, 40% of recorded neurons fired differently according to which of the two reward ports the rat was visiting. A smaller fraction of neurons demonstrated onset response to sound/nosepoke (19%) and reward delivery (24%). When the sounds were played during passive wakefulness, 8% of neurons responded with short latency onset responses; 25% of neurons responded to sounds when they were played during sleep. During sleep the short-latency responses in hippocampus are intermingled with long lasting responses which in the current experiment could last for 1–2 s. Based on the current findings and the results of previous experiments we described the existence of two types of hippocampal neuronal responses to sounds: sound-onset responses with very short latency and longer-lasting sound-specific responses that are likely to be present when the animal is actively engaged in the task

A sensory integration account for time perception

The connection between stimulus perception and time perception remains unknown. The present study combines human and rat psychophysics with sensory cortical neuronal firing to construct a computational model for the percept of elapsed time embedded within sense of touch. When subjects judged the duration of a vibration applied to the fingertip (human) or whiskers (rat), increasing stimulus intensity led to increasing perceived duration. Symmetrically, increasing vibration duration led to increasing perceived intensity. We modeled spike trains from vibrissal somatosensory cortex as input to dual leaky integrators \u2013 an intensity integrator with short time constant and a duration integrator with long time constant \u2013 generating neurometric functions that replicated the actual psychophysical functions of rats. Returning to human psychophysics, we then confirmed specific predictions of the dual leaky integrator model. This study offers a framework, based on sensory coding and subsequent accumulation of sensory drive, to account for how a feeling of the passage of time accompanies the tactile sensory experience

Learning not to feel: reshaping the resolution of tactile perception

We asked whether biased feedback during training could cause human subjects to lose perceptual acuity in a vibrotactile frequency discrimination task. Prior to training, we determined each subject\ueds vibration frequency discrimination capacity on one fingertip, the Just Noticeable Difference (JND). Subjects then received 850 trials in which they performed a same/different judgment on two vibrations presented to that fingertip. They gained points whenever their judgment matched the computer-generated feedback on that trial. Feedback, however, was biased: the probability per trial of \uecsame\uee feedback was drawn from a normal distribution with standard deviation twice as wide as the subject\ueds JND. After training, the JND was significantly widened: stimulus pairs previously perceived as different were now perceived as the same. The widening of the JND extended to the untrained hand, indicating that the decrease in resolution originated in non-topographic brain regions. In sum, the acuity of subjects\ued sensory-perceptual systems shifted in order to match the feedback received during training. \ua9 2013 Omrani, Lak and Diamond

Reading spike timing without a clock: intrinsic decoding of spike trains

The precise timing of action potentials of sensory neurons relative to the time of stimulus presentation carries substantial sensory information that is lost or degraded when these responses are summed over longer time windows. However, it is unclear whether and how downstream networks can access information in precise time-varying neural responses. Here, we review approaches to test the hypothesis that the activity of neural populations provides the temporal reference frames needed to decode temporal spike patterns. These approaches are based on comparing the single-trial stimulus discriminability obtained from neural codes defined with respect to network-intrinsic reference frames to the discriminability obtained from codes defined relative to the experimenter's computer clock. Application of this formalism to auditory, visual and somatosensory data shows that information carried by millisecond-scale spike times can be decoded robustly even with little or no independent external knowledge of stimulus time. In cortex, key components of such intrinsic temporal reference frames include dedicated neural populations that signal stimulus onset with reliable and precise latencies, and low-frequency oscillations that can serve as reference for partitioning extended neuronal responses into informative spike patterns

Neuronal Activity in Rat Barrel Cortex Underlying Texture Discrimination

Rats and mice palpate objects with their whiskers to generate tactile sensations. This form of active sensing endows the animals with the capacity for fast and accurate texture discrimination. The present work is aimed at understanding the nature of the underlying cortical signals. We recorded neuronal activity from barrel cortex while rats used their whiskers to discriminate between rough and smooth textures. On whisker contact with either texture, firing rate increased by a factor of two to ten. Average firing rate was significantly higher for rough than for smooth textures, and we therefore propose firing rate as the fundamental coding mechanism. The rat, however, cannot take an average across trials, but must make an immediate decision using the signals generated on each trial. To estimate single-trial signals, we calculated the mutual information between stimulus and firing rate in the time window leading to the rat's observed choice. Activity during the last 75 ms before choice transmitted the most informative signal; in this window, neuronal clusters carried, on average, 0.03 bits of information about the stimulus on trials in which the rat's behavioral response was correct. To understand how cortical activity guides behavior, we examined responses in incorrect trials and found that, in contrast to correct trials, neuronal firing rate was higher for smooth than for rough textures. Analysis of high-speed films suggested that the inappropriate signal on incorrect trials was due, at least in part, to nonoptimal whisker contact. In conclusion, these data suggest that barrel cortex firing rate on each trial leads directly to the animal's judgment of texture

Optimal decision-making in mammals : insights from a robot study of rodent texture discrimination

Texture perception is studied here in a physical model of the rat whisker system consisting of a robot equipped with a biomimetic vibrissal sensor. Investigations of whisker motion in rodents have led to several explanations for texture discrimination, such as resonance or stick-slips. Meanwhile, electrophysiological studies of decision-making in monkeys have suggested a neural mechanism of evidence accumulation to threshold for competing percepts, described by a probabilistic model of Bayesian sequential analysis. For our robot whisker data, we find that variable reaction-time decision-making with sequential analysis performs better than the fixed response-time maximum-likelihood estimation. These probabilistic classifiers also use whatever available features of the whisker signals aid the discrimination, giving improved performance over a single-feature strategy, such as matching the peak power spectra of whisker vibrations. These results cast new light on how the various proposals for texture discrimination in rodents depend on the whisker contact mechanics and suggest the possibility of a common account of decision-making across mammalian species