Ehsan Arabzadeh

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 rats 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 rats 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 animals judgment of texture.

Whisker Vibration Information Carried by Rat Barrel Cortex Neurons

Rats can make extremely fine texture discriminations by “whisking” their vibrissa across the surface of an object. We have investigated one hypothesis for the neuronal basis of texture representation by measuring how clusters of neurons in the barrel cortex of anesthetized rats encode the kinetic features of sinusoidal whisker vibrations. Mutual information analyses of spike counts led to a number of findings. Information about vibration kinetics became available as early as 6 msec after stimulus onset and reached a peak at ∼20-30 msec. Vibration speed, proportional to the product of vibration amplitude (A) and frequency (f), was the kinetic property most reliably reported by cortical neurons. Indeed, by measuring information when the complete stimulus set was collapsed into feature-defined groups, we found that neurons reduced the dimensionality of the stimulus from two features (A, f) to a single feature, the product Af. Moreover, because different neurons encode stimuli in the same manner, information loss was negligible even when the activity of separate neuronal clusters was pooled. This suggests a decoding scheme whereby target neurons could capture all available information simply by summating the signals from separate barrel cortex neurons. These results indicate that neuronal population activity provides sufficient information to allow nearly perfect discrimination of two vibrations, based on their deflection speeds, within a time scale comparable with that of a single whisking motion across a surface.

Deciphering the Spike Train of a Sensory Neuron: Counts and Temporal Patterns in the Rat Whisker Pathway

Rats achieve remarkable texture discriminations by sweeping their facial whiskers along surfaces. This work explores how neurons at two levels of the sensory pathway, trigeminal ganglion and barrel cortex, carry information about such stimuli. We identified two biologically plausible coding mechanisms, spike counts and patterns, and used “mutual information” to quantify how reliably neurons in anesthetized rats reported texture when “decoded” according to these candidate mechanisms. For discriminations between surfaces of different coarseness, spike counts could be decoded reliably and rapidly (within 30 ms after stimulus onset in cortex). Information increased as responses were considered as spike patterns with progressively finer temporal precision. At highest temporal resolution (spike sequences across six bins of 4 ms), the quantity of “information” in patterns rose 150% for ganglion neurons and 110% for cortical neurons above that in spike counts. In some cases, patterns permitted discriminations not supported by spike counts alone.

Encoding of whisker vibration by rat barrel cortex neurons: implications for texture discrimination.

Rats, using their whiskers, have excellent capabilities in texture discrimination. What is the representation of texture in rat somatosensory cortex? We hypothesize that as rats “whisk” over a surface, the spatial frequency of a grooved or pebbled texture is converted to a temporal frequency of whisker vibration. Surface features such as groove depth or grain size modulate the amplitude of this vibration. Validation of the hypothesis depends on showing that vibration parameters have distinct neuronal representations in cortex. To test this, we delivered sinusoidal vibrations to the whisker shaft and analyzed cortical neuronal activity. Seven amplitudes and seven frequencies were combined to construct 49 stimuli while recording activity through a 10 × 10 microelectrode array inserted into the middle layers of barrel cortex. We find that cortical neurons do not explicitly encode vibration frequency (f) or amplitude (A) by any coding measure (average spike counts over different time windows, spike timing patterns in the peristimulus time histograms or in autocorrelograms). Instead, neurons explicitly encode the product of frequency and amplitude, which is proportional to the mean speed of the vibration. The quantity Af is an invariant because neuronal response encodes this feature independently of the values of the individual terms A and f. This was true across a wide time scale of firing rate measurements, from 5 to 500 msec. We conclude that vibration kinetics are rapidly and reliably encoded in the firing rate of cortical ensembles. Therefore, the cortical representation of vibration speed could underlie texture discrimination.

The impact of high-order interactions on the rate of synchronous discharge and information transmission in somatosensory cortex

Understanding the operations of neural networks in the brain requires an understanding of whether interactions among neurons can be described by a pairwise interaction model, or whether a higher order interaction model is needed. In this article we consider the rate of synchronous discharge of a local population of neurons, a macroscopic index of the activation of the neural network that can be measured experimentally. We analyse a model based on physics’ maximum entropy principle that evaluates whether the probability of synchronous discharge can be described by interactions up to any given order. When compared with real neural population activity obtained from the rat somatosensory cortex, the model shows that interactions of at least order three or four are necessary to explain the data. We use Shannon information to compute the impact of high-order correlations on the amount of somatosensory information transmitted by the rate of synchronous discharge, and we find that correlations of higher order progressively decrease the information available through the neural population. These results are compatible with the hypothesis that high-order interactions play a role in shaping the dynamics of neural networks, and that they should be taken into account when computing the representational capacity of neural populations.

Whisker-Mediated Texture Discrimination

Rats use their whiskers to rapidly and accurately measure the texture of objects. The authors evaluate recent evidence about how whisker movement across a surface produces texture-specific motion signals, and how the signals are represented by the brain.

Adaptation Improves Neural Coding Efficiency Despite Increasing Correlations in Variability

Exposure of cortical cells to sustained sensory stimuli results in changes in the neuronal response function. This phenomenon, known as adaptation, is a common feature across sensory modalities. Here, we quantified the functional effect of adaptation on the ensemble activity of cortical neurons in the rat whisker-barrel system. A multishank array of electrodes was used to allow simultaneous sampling of neuronal activity. We characterized the response of neurons to sinusoidal whisker vibrations of varying amplitude in three states of adaptation. The adaptors produced a systematic rightward shift in the neuronal response function. Consistently, mutual information revealed that peak discrimination performance was not aligned to the adaptor but to test amplitudes 3–9 μm higher. Stimulus presentation reduced single neuron trial-to-trial response variability (captured by Fano factor) and correlations in the population response variability (noise correlation). We found that these two types of variability were inversely proportional to the average firing rate regardless of the adaptation state. Adaptation transferred the neuronal operating regime to lower rates with higher Fano factor and noise correlations. Noise correlations were positive and in the direction of signal, and thus detrimental to coding efficiency. Interestingly, across all population sizes, the net effect of adaptation was to increase the total information despite increasing the noise correlation between neurons.

Improving Visual Sensitivity with Subthreshold Transcranial Magnetic Stimulation

We probed for improvement of visual sensitivity in human participants using transcranial magnetic stimulation (TMS). Stimulation of visual cortex can induce an illusory visual percept known as a phosphene. It is known that TMS, delivered at intensities above the threshold to induce phosphenes, impairs the detection of visual stimuli. We investigated how the detection of a simple visual stimulus is affected by TMS applied to visual cortex at or below the phosphene threshold. Participants performed the detection task while the contrast of the visual stimulus was varied from trial to trial according to an adaptive staircase procedure. Detection of the stimulus was enhanced when a single pulse of TMS was delivered to the contralateral visual cortex 100 or 120 ms after stimulus onset at intensities just below the phosphene threshold. No improvement in visual sensitivity was observed when TMS was applied to the visual cortex in the opposite hemisphere (ipsilateral to the visual stimulus). We conclude that TMS-induced neuronal activity can sum with stimulus-evoked activity to augment visual perception.

2010 Special Issue: Information-theoretic methods for studying population codes

Population coding is the quantitative study of which algorithms or representations are used by the brain to combine together and evaluate the messages carried by different neurons. Here, we review an information-theoretic approach to population coding. We first discuss how to compute the information carried by simultaneously recorded neural populations, and in particular how to reduce the limited sampling bias which affects the calculation of information from a limited amount of experimental data. We then discuss how to quantify the contribution of individual members of the population, or the interaction between them, to the overall information encoded by the considered group of neurons. We focus in particular on evaluating what is the contribution of interactions up to any given order to the total information. We illustrate this formalism with applications to simulated data with realistic neuronal statistics and to real simultaneous recordings of multiple spike trains.

Getting technical about awareness

It has recently been argued that post-decision wagering provides an objective measure of awareness. We critically evaluate this claim, emphasizing the distinction between performance without awareness and a reluctance to gamble in full awareness of weak sensory evidence. We address two key methodological issues. The first is the design of the pay-off matrix to reward a strategy of wagering that reflects the strength of sensory evidence. The second is the use of signal detection theory to analyze the resulting data. We argue that proper treatment of these issues is essential if post-decision wagering is to prove valuable in validating claims of perception without awareness in normal subjects and neuropsychological patients.