Sequence Learning Induces Selectivity to Multiple Task Parameters in Mouse Somatosensory Cortex.

Sequential temporal ordering and patterning are key features of natural signals, used by the brain to decode stimuli and perceive them as sensory objects. To explore how cortical neuronal activity underpins sequence discrimination, we developed a task in which mice distinguished between tactile "word" sequences constructed from distinct vibrations delivered to the whiskers, assembled in different orders. Animals licked to report the presence of the target sequence. Mice could respond to the earliest possible cues allowing discrimination, effectively solving the task as a "detection of change" problem, but enhanced their performance when responding later. Optogenetic inactivation showed that the somatosensory cortex was necessary for sequence discrimination. Two-photon imaging in layer 2/3 of the primary somatosensory "barrel" cortex (S1bf) revealed that, in well-trained animals, neurons had heterogeneous selectivity to multiple task variables including not just sensory input but also the animal's action decision and the trial outcome (presence or absence of the predicted reward). Many neurons were activated preceding goal-directed licking, thus reflecting the animal's learned action in response to the target sequence; these neurons were found as soon as mice learned to associate the rewarded sequence with licking. In contrast, learning evoked smaller changes in sensory response tuning: neurons responding to stimulus features were found in naive mice, and training did not generate neurons with enhanced temporal integration or categorical responses. Therefore, in S1bf, sequence learning results in neurons whose activity reflects the learned association between target sequence and licking rather than a refined representation of sensory features.

Cortical Lifelogging: The Posterior Parietal Cortex as Sensory History Buffer.

To compare information and reach decisions effectively, our brain uses multiple heuristics, which can, however, induce biases in behavior. An elegant study by Akrami et al. (2018) finds evidence for one such heuristic in a sensory-based comparison task and identifies its location to the posterior parietal cortex.

Organization of sensory feature selectivity in the whisker system.

Our sensory receptors are faced with an onslaught of different environmental inputs. Each sensory event or encounter with an object involves a distinct combination of physical energy sources impinging upon receptors. In the rodent whisker system, each primary afferent neuron located in the trigeminal ganglion innervates and responds to a single whisker and encodes a distinct set of physical stimulus properties - features - corresponding to changes in whisker angle and shape and the consequent forces acting on the whisker follicle. Here we review the nature of the features encoded by successive stages of processing along the whisker pathway. At each stage different neurons respond to distinct features, such that the population as a whole represents diverse properties. Different neuronal types also have distinct feature selectivity. Thus, neurons at the same stage of processing and responding to the same whisker nevertheless play different roles in representing objects contacted by the whisker. This diversity, combined with the precise timing and high reliability of responses, enables populations at each stage to represent a wide range of stimuli. Cortical neurons respond to more complex stimulus properties - such as correlated motion across whiskers - than those at early subcortical stages. Temporal integration along the pathway is comparatively weak: neurons up to barrel cortex (BC) are sensitive mainly to fast (tens of milliseconds) fluctuations in whisker motion. The topographic organization of whisker sensitivity is paralleled by systematic organization of neuronal selectivity to certain other physical features, but selectivity to touch and to dynamic stimulus properties is distributed in "salt-and-pepper" fashion.

Learning and recognition of tactile temporal sequences by mice and humans.

The world around us is replete with stimuli that unfold over time. When we hear an auditory stream like music or speech or scan a texture with our fingertip, physical features in the stimulus are concatenated in a particular order. This temporal patterning is critical to interpreting the stimulus. To explore the capacity of mice and humans to learn tactile sequences, we developed a task in which subjects had to recognise a continuous modulated noise sequence delivered to whiskers or fingertips, defined by its temporal patterning over hundreds of milliseconds. GO and NO-GO sequences differed only in that the order of their constituent noise modulation segments was temporally scrambled. Both mice and humans efficiently learned tactile sequences. Mouse sequence recognition depended on detecting transitions in noise amplitude; animals could base their decision on the earliest information available. Humans appeared to use additional cues, including the duration of noise modulation segments.

Efficient population coding of naturalistic whisker motion in the ventro-posterior medial thalamus based on precise spike timing.

The rodent whisker-associated thalamic nucleus (VPM) contains a somatotopic map where whisker representation is divided into distinct neuronal sub-populations, called "barreloids". Each barreloid projects to its associated cortical barrel column and so forms a gateway for incoming sensory stimuli to the barrel cortex. We aimed to determine how the population of neurons within one barreloid encodes naturalistic whisker motion. In rats, we recorded the extracellular activity of up to nine single neurons within a single barreloid, by implanting silicon probes parallel to the longitudinal axis of the barreloids. We found that play-back of texture-induced whisker motion evoked sparse responses, timed with millisecond precision. At the population level, there was synchronous activity: however, different subsets of neurons were synchronously active at different times. Mutual information between population responses and whisker motion increased near linearly with population size. When normalized to factor out firing rate differences, we found that texture was encoded with greater informational-efficiency than white noise. These results indicate that, within each VPM barreloid, there is a rich and efficient population code for naturalistic whisker motion based on precisely timed, population spike patterns.

Microsecond-scale timing precision in rodent trigeminal primary afferents.

Communication in the nervous system occurs by spikes: the timing precision with which spikes are fired is a fundamental limit on neural information processing. In sensory systems, spike-timing precision is constrained by first-order neurons. We found that spike-timing precision of trigeminal primary afferents in rats and mice is limited both by stimulus speed and by electrophysiological sampling rate. High-speed video of behaving mice revealed whisker velocities of at least 17,000°/s, so we delivered an ultrafast "ping" (>50,000°/s) to single whiskers and sampled primary afferent activity at 500 kHz. Median spike jitter was 17.4 µs; 29% of neurons had spike jitter < 10 µs. These results indicate that the input stage of the trigeminal pathway has extraordinary spike-timing precision and very high potential information capacity. This timing precision ranks among the highest in biology.

Transformation of adaptation and gain rescaling along the whisker sensory pathway.

Neurons in all sensory systems have a remarkable ability to adapt their sensitivity to the statistical structure of the sensory signals to which they are tuned. In the barrel cortex, firing rate adapts to the variance of a whisker stimulus and neuronal sensitivity (gain) adjusts in inverse proportion to the stimulus standard deviation. To determine how adaptation might be transformed across the ascending lemniscal pathway, we measured the responses of single units in the first and last subcortical stages, the trigeminal ganglion (TRG) and ventral posterior medial thalamic nucleus (VPM), to controlled whisker stimulation in urethane-anesthetized rats. We probed adaptation using a filtered white noise stimulus that switched between low- and high-variance epochs. We found that the firing rate of both TRG and VPM neurons adapted to stimulus variance. By fitting the responses of each unit to a Linear-Nonlinear-Poisson model, we tested whether adaptation changed feature selectivity and/or sensitivity. We found that, whereas feature selectivity was unaffected by stimulus variance, units often exhibited a marked change in sensitivity. The extent of these sensitivity changes increased systematically along the pathway from TRG to barrel cortex. However, there was marked variability across units, especially in VPM. In sum, in the whisker system, the adaptation properties of subcortical neurons are surprisingly diverse. The significance of this diversity may be that it contributes to a rich population representation of whisker dynamics.

Low-dimensional sensory feature representation by trigeminal primary afferents.

In any sensory system, the primary afferents constitute the first level of sensory representation and fundamentally constrain all subsequent information processing. Here, we show that the spike timing, reliability, and stimulus selectivity of primary afferents in the whisker system can be accurately described by a simple model consisting of linear stimulus filtering combined with spike feedback. We fitted the parameters of the model by recording the responses of primary afferents to filtered, white noise whisker motion in anesthetized rats. The model accurately predicted not only the response of primary afferents to white noise whisker motion (median correlation coefficient 0.92) but also to naturalistic, texture-induced whisker motion. The model accounted both for submillisecond spike-timing precision and for non-Poisson spike train structure. We found substantial diversity in the responses of the afferent population, but this diversity was accurately captured by the model: a 2D filter subspace, corresponding to different mixtures of position and velocity sensitivity, captured 94% of the variance in the stimulus selectivity. Our results suggest that the first stage of the whisker system can be well approximated as a bank of linear filters, forming an overcomplete representation of a low-dimensional feature space.

Comparison of latency and rate coding for the direction of whisker deflection in the subcortical somatosensory pathway.

The response of many neurons in the whisker somatosensory system depends on the direction in which a whisker is deflected. Although it is known that the spike count conveys information about this parameter, it is not known how important spike timing might be. The aim of this study was to compare neural codes based on spike count and first-spike latency, respectively. We extracellularly recorded single units from either the rat trigeminal ganglion (primary sensory afferents) or ventroposteromedial (VPM) thalamic nucleus in response to deflection in different directions and quantified alternative neural codes using mutual information. We found that neurons were diverse: some (58% in ganglion, 32% in VPM) conveyed information only by spike count; others conveyed additional information by latency. An issue with latency coding is that latency is measured with respect to the time of stimulus onset, a quantity known to the experimenter but not directly to the subject's brain. We found a potential solution using the integrated population activity as an internal timing signal: in this way, 91% of the first-spike latency information could be recovered. Finally, we asked how well direction could be decoded. For large populations, spike count and latency codes performed similarly; for small ones, decoding was more accurate using the latency code. Our findings indicate that whisker deflection direction is more efficiently encoded by spike timing than by spike count. Spike timing decreases the population size necessary for reliable information transmission and may thereby bring significant advantages in both wiring and metabolic efficiency.

Transformation in the neural code for whisker deflection direction along the lemniscal pathway.

A prominent characteristic of neurons in the whisker system is their selectivity to the direction in which a whisker is deflected. The aim of this study was to determine how information about whisker direction is encoded at successive levels of the lemniscal pathway. We made extracellular recordings under identical conditions from the trigeminal ganglion, ventro-posterior medial thalamus (VPM), and barrel cortex while varying the direction of whisker deflection. We found a marked increase in the variability of single unit responses along the pathway. To study the consequences of this for information processing, we quantified the responses using mutual information. VPM units conveyed 48% of the mutual information conveyed by ganglion units, and cortical units conveyed 12%. The fraction of neuronal bandwidth used for transmitting direction information decreased from 40% in the ganglion to 24% in VPM and 5% in barrel cortex. To test whether, in cortex, population coding might compensate for this information loss, we made simultaneous recordings. We found that cortical neuron pairs conveyed 2.1 times the mutual information conveyed by single neurons. Overall, these findings indicate a marked transformation from a subcortical neural code based on small numbers of reliable neurons to a cortical code based on populations of unreliable neurons. However, the basic form of the neural code in ganglion, thalamus, and cortex was similar-at each stage, the first poststimulus spike carried the majority of the information.

Diverse and temporally precise kinetic feature selectivity in the VPm thalamic nucleus.

The thalamo-cortical pathway is the crucial sensory gateway into the cerebral cortex. We aimed to determine the nature of the tactile information encoded by neurons in the whisker somatosensory relay nucleus (VPm). We wanted to distinguish whether VPm neurons encode similar stimulus features, acting as a single information channel, or encode diverse features. We recorded responses to whisker deflections that thoroughly explored the space of temporal stimulus variables and identified features to which neurons were selective by reverse correlation. The timescale of the features was typically 1-2 ms, at the limit imposed by our experimental conditions, indicating highly acute feature selectivity. Sensitivity to stimulus kinetics was strikingly diverse. Some neurons (25%) only encoded velocity; others were sensitive to position, acceleration, or more complex features. A minority (19%) encoded two or more features. These results indicate that VPm contains a distributed representation of whisker motion, based on high-resolution kinetic features.

Role of precise spike timing in coding of dynamic vibrissa stimuli in somatosensory thalamus.

Rats discriminate texture by whisking their vibrissae across the surfaces of objects. This process induces corresponding vibrissa vibrations, which must be accurately represented by neurons in the somatosensory pathway. In this study, we investigated the neural code for vibrissa motion in the ventroposterior medial (VPm) nucleus of the thalamus by single-unit recording. We found that neurons conveyed a great deal of information (up to 77.9 bits/s) about vibrissa dynamics. The key was precise spike timing, which typically varied by less than a millisecond from trial to trial. The neural code was sparse, the average spike being remarkably informative (5.8 bits/spike). This implies that as few as four VPm spikes, coding independent information, might reliably differentiate between 10(6) textures. To probe the mechanism of information transmission, we compared the role of time-varying firing rate to that of temporally correlated spike patterns in two ways: 93.9% of the information encoded by a neuron could be accounted for by a hypothetical neuron with the same time-dependent firing rate but no correlations between spikes; moreover, > or =93.4% of the information in the spike trains could be decoded even if temporal correlations were ignored. Taken together, these results suggest that the essence of the VPm code for vibrissa motion is firing rate modulation on a submillisecond timescale. The significance of such a code may be that it enables a small number of neurons, firing only few spikes, to convey distinctions between very many different textures to the barrel cortex.