Control of prestimulus activity related to improved sensory coding within a discrimination task

Deficits in taste-guided behaviors and central processing of taste in the transgenic TDP-43Q331K mouse model of frontotemporal dementia

Frontotemporal dementia (FTD) is the second most prevalent form of presenile dementia. Patients with FTD show prominent chemosensory symptoms such as abnormal detection and recognition thresholds for various gustatory stimuli. The chemosensory symptoms of FTD may be related to damage of the gustatory insular cortex (GC) as the insular cortex is one of the primary targets in FTD disease progression. Little is known about how circuitry changes in GC lead to deficits in taste processing in FTD. Here we tested the hypothesis that gustatory deficits are present in a mouse model of FTD, and that they are related to abnormal patterns of neural activity in GC. We behaviorally evaluated a transgenic FTD mouse model overexpressing human TDP-43 with a Q331K mutation (TDP-43Q331K) in a brief access test and a taste-based two alternative forced choice (2AFC) task probing the ability to discriminate sucrose/NaCl mixtures. TDP-43Q331K mice showed abnormal sucrose consumption and an impaired ability to discriminate taste mixtures compared to non-transgenic control mice. To assess deficits in GC taste processing, we relied on electrophysiological recordings using chronically implanted tetrodes in alert TDP-43Q331K and non-transgenic control mice. The proportion of taste-selective neurons in TDP-43Q331K mice decreased over time compared to control mice. Similarly, encoding of chemosensory information and processing of taste palatability were impaired in TDP-43Q331K mice compared to control mice. Overall, these results demonstrate taste-related symptoms in a mouse model of FTD and provide evidence for altered taste processing in GC of TDP-43Q331K mice compared to control mice.

Neural Processing of Taste-Related Signals in the Mediodorsal Thalamus of Mice

Our consummatory decisions depend on the taste of food and the reward experienced while eating, which are processed through neural computations in interconnected brain areas. Although many gustatory regions of rodents have been explored, the mediodorsal nucleus of the thalamus (MD) remains understudied. The MD, a multimodal brain area connected with gustatory centers, is often studied for its role in processing associative and cognitive information and has been shown to represent intraorally delivered chemosensory stimuli after strong retronasal odor-taste associations. Key questions remain about whether MD neurons can process taste quality independently of odor-taste associations and how they represent extraoral signals predicting rewarding and aversive gustatory outcomes. Here, using C57 male and female mice we present electrophysiological evidence demonstrating how MD neurons represent and encode 1) the identity and concentrations of basic taste qualities during active licking, and 2) auditory signals anticipating rewarding and aversive taste outcomes. Our data reveal that MD neurons can reliably and dynamically encode taste identity in a broadly tuned manner and taste concentrations with spiking activity positively and negatively correlated with stimulus intensity. Our data also show that MD can represent information related to predictive cues and their associated outcomes, regardless of whether the cue predicts a rewarding or aversive outcome. In summary, our findings suggest that the mediodorsal thalamus is integral to the taste pathway, as it can encode sensory-discriminative dimensions of tastants and participate in processing associative information essential for ingestive behaviors.Significance Statement Dietary decisions are driven by the taste of the food and the reward experienced while eating. This information is processed through neural computations across interconnected brain areas. Given its neural connections, the mediodorsal thalamus (MD) could be part of this network. However, its involvement in gustatory processing is largely ignored. This study examines how MD neurons respond to taste quality, intensity, and expectation by analyzing the electrical activity of MD neurons in mice allowed to freely lick a spout to obtain different tastes. Our findings support the idea that the MD is part of the brain network responsible for processing sensory and associative information relevant to eating.

Neural Processing of Taste-Related Signals in the Mediodorsal Thalamus of Mice

Our consummatory decisions depend on the taste of food and the reward experienced while eating, which are processed through neural computations in interconnected brain areas. Although many gustatory regions of rodents have been explored, the mediodorsal nucleus of the thalamus (MD) remains understudied. The MD, a multimodal brain area connected with gustatory centers, is often studied for its role in processing associative and cognitive information and has been shown to represent intraorally-delivered chemosensory stimuli after strong retronasal odor-taste associations. Key questions remain about whether MD neurons can process taste quality independently of odor-taste associations and how they represent extraoral signals predicting rewarding and aversive gustatory outcomes. Here, using C57 male and female mice we present electrophysiological evidence demonstrating how MD neurons represent and encode 1) the identity and concentrations of basic taste qualities during active licking, and 2) auditory signals anticipating rewarding and aversive taste outcomes. Our data reveal that MD neurons can reliably and dynamically encode taste identity in a broadly tuned manner and taste concentrations with spiking activity positively and negatively correlated with stimulus intensity. Our data also show that MD can represent information related to predictive cues and their associated outcomes, regardless of whether the cue predicts a rewarding or aversive outcome. In summary, our findings suggest that the mediodorsal thalamus is integral to the taste pathway, as it can encode sensory-discriminative dimensions of tastants and participate in processing associative information essential for ingestive behaviors.

Orbitofrontal cortex modulates auditory cortical sensitivity and sound perception in Mongolian gerbils

Sensory perception is dynamic, quickly adapting to sudden shifts in environmental or behavioral context. Although decades of work have established that these dynamics are mediated by rapid fluctuations in sensory cortical activity, we have a limited understanding of the brain regions and pathways that orchestrate these changes. Neurons in the orbitofrontal cortex (OFC) encode contextual information, and recent data suggest that some of these signals are transmitted to sensory cortices. Whether and how these signals shape sensory encoding and perceptual sensitivity remain uncertain. Here, we asked whether the OFC mediates context-dependent changes in auditory cortical sensitivity and sound perception by monitoring and manipulating OFC activity in freely moving Mongolian gerbils of both sexes under two behavioral contexts: passive sound exposure and engagement in an amplitude modulation (AM) detection task. We found that the majority of OFC neurons, including the specific subset that innervates the auditory cortex, were strongly modulated by task engagement. Pharmacological inactivation of the OFC prevented rapid context-dependent changes in auditory cortical firing and significantly impaired behavioral AM detection. Our findings suggest that contextual information from the OFC mediates rapid plasticity in the auditory cortex and facilitates the perception of behaviorally relevant sounds.

Learning enhances representations of taste-guided decisions in the mouse gustatory insular cortex

Learning to discriminate overlapping gustatory stimuli that predict distinct outcomes-a feat known as discrimination learning-can mean the difference between ingesting a poison or a nutritive meal. Despite the obvious importance of this process, very little is known about the neural basis of taste discrimination learning. In other sensory modalities, this form of learning can be mediated by either the sharpening of sensory representations or the enhanced ability of "decision-making" circuits to interpret sensory information. Given the dual role of the gustatory insular cortex (GC) in encoding both sensory and decision-related variables, this region represents an ideal site for investigating how neural activity changes as animals learn a novel taste discrimination. Here, we present results from experiments relying on two-photon calcium imaging of GC neural activity in mice performing a taste-guided mixture discrimination task. The task allows for the recording of neural activity before and after learning induced by training mice to discriminate increasingly similar pairs of taste mixtures. Single-neuron and population analyses show a time-varying pattern of activity, with early sensory responses emerging after taste delivery and binary, choice-encoding responses emerging later in the delay before a decision is made. Our results demonstrate that, while both sensory and decision-related information is encoded by GC in the context of a taste mixture discrimination task, learning and improved performance are associated with a specific enhancement of decision-related responses.

Orbitofrontal Cortex Modulates Auditory Cortical Sensitivity and Sound Perception

Sensory perception is dynamic, quickly adapting to sudden shifts in environmental or behavioral context. Though decades of work have established that these dynamics are mediated by rapid fluctuations in sensory cortical activity, we have a limited understanding of the brain regions and pathways that orchestrate these changes. Neurons in the orbitofrontal cortex (OFC) encode contextual information, and recent data suggest that some of these signals are transmitted to sensory cortices. Whether and how these signals shape sensory encoding and perceptual sensitivity remains uncertain. Here, we asked whether the OFC mediates context-dependent changes in auditory cortical sensitivity and sound perception by monitoring and manipulating OFC activity in freely moving animals under two behavioral contexts: passive sound exposure and engagement in an amplitude modulation (AM) detection task. We found that the majority of OFC neurons, including the specific subset that innervate the auditory cortex, were strongly modulated by task engagement. Pharmacological inactivation of the OFC prevented rapid context-dependent changes in auditory cortical firing, and significantly impaired behavioral AM detection. Our findings suggest that contextual information from the OFC mediates rapid plasticity in the auditory cortex and facilitates the perception of behaviorally relevant sounds.

Significance Statement

Sensory perception depends on the context in which stimuli are presented. For example, perception is enhanced when stimuli are informative, such as when they are important to solve a task. Perceptual enhancements result from an increase in the sensitivity of sensory cortical neurons; however, we do not fully understand how such changes are initiated in the brain. Here, we tested the role of the orbitofrontal cortex (OFC) in controlling auditory cortical sensitivity and sound perception. We found that OFC neurons change their activity when animals perform a sound detection task. Inactivating OFC impairs sound detection and prevents task-dependent increases in auditory cortical sensitivity. Our findings suggest that the OFC controls contextual modulations of the auditory cortex and sound perception.

Learning enhances representations of taste-guided decisions in the mouse gustatory insular cortex

Learning to discriminate overlapping gustatory stimuli that predict distinct outcomes - a feat known as discrimination learning - can mean the difference between ingesting a poison or a nutritive meal. Despite the obvious importance of this process, very little is known on the neural basis of taste discrimination learning. In other sensory modalities, this form of learning can be mediated by either sharpening of sensory representations, or enhanced ability of "decision-making" circuits to interpret sensory information. Given the dual role of the gustatory insular cortex (GC) in encoding both sensory and decision-related variables, this region represents an ideal site for investigating how neural activity changes as animals learn a novel taste discrimination. Here we present results from experiments relying on two photon calcium imaging of GC neural activity in mice performing a taste-guided mixture discrimination task. The task allows for recording of neural activity before and after learning induced by training mice to discriminate increasingly similar pairs of taste mixtures. Single neuron and population analyses show a time-varying pattern of activity, with early sensory responses emerging after taste delivery and binary, choice encoding responses emerging later in the delay before a decision is made. Our results demonstrate that while both sensory and decision-related information is encoded by GC in the context of a taste mixture discrimination task, learning and improved performance are associated with a specific enhancement of decision-related responses.

Organization of orbitofrontal-auditory pathways in the Mongolian gerbil

Sound perception is highly malleable, rapidly adjusting to the acoustic environment and behavioral demands. This flexibility is the result of ongoing changes in auditory cortical activity driven by fluctuations in attention, arousal, or prior expectations. Recent work suggests that the orbitofrontal cortex (OFC) may mediate some of these rapid changes, but the anatomical connections between the OFC and the auditory system are not well characterized. Here, we used virally mediated fluorescent tracers to map the projection from OFC to the auditory midbrain, thalamus, and cortex in a classic animal model for auditory research, the Mongolian gerbil (Meriones unguiculatus). We observed no connectivity between the OFC and the auditory midbrain, and an extremely sparse connection between the dorsolateral OFC and higher order auditory thalamic regions. In contrast, we observed a robust connection between the ventral and medial subdivisions of the OFC and the auditory cortex, with a clear bias for secondary auditory cortical regions. OFC axon terminals were found in all auditory cortical lamina but were significantly more concentrated in the infragranular layers. Tissue-clearing and lightsheet microscopy further revealed that auditory cortical-projecting OFC neurons send extensive axon collaterals throughout the brain, targeting both sensory and non-sensory regions involved in learning, decision-making, and memory. These findings provide a more detailed map of orbitofrontal-auditory connections and shed light on the possible role of the OFC in supporting auditory cognition.

Oral thermal processing in the gustatory cortex of awake mice

Oral temperature is a sensory cue relevant to food preference and nutrition. To understand how orally sourced thermal inputs are represented in the gustatory cortex (GC), we recorded neural responses from the GC of male and female mice presented with deionized water at different innocuous temperatures (14 °C, 25 °C, and 36 °C) and taste stimuli (room temperature). Our results demonstrate that GC neurons encode orally sourced thermal information in the absence of classical taste qualities at the single neuron and population levels, as confirmed through additional experiments comparing GC neuron responses to water and artificial saliva. Analysis of thermal-evoked responses showed broadly tuned neurons that responded to temperature in a mostly monotonic manner. Spatial location may play a minor role regarding thermosensory activity; aside from the most ventral GC, neurons reliably responded to and encoded thermal information across the dorso-ventral and antero-postero cortical axes. Additional analysis revealed that more than half of the GC neurons that encoded chemosensory taste stimuli also accurately discriminated thermal information, providing additional evidence of the GC's involvement in processing thermosensory information important for ingestive behaviors. In terms of convergence, we found that GC neurons encoding information about both taste and temperature were broadly tuned and carried more information than taste-selective-only neurons; both groups encoded similar information about the palatability of stimuli. Altogether, our data reveal new details of the cortical code for the mammalian oral thermosensory system in behaving mice and pave the way for future investigations on GC functions and operational principles with respect to thermogustation.

Audiovisual task switching rapidly modulates sound encoding in mouse auditory cortex

In everyday behavior, sensory systems are in constant competition for attentional resources, but the cellular and circuit-level mechanisms of modality-selective attention remain largely uninvestigated. We conducted translaminar recordings in mouse auditory cortex (AC) during an audiovisual (AV) attention shifting task. Attending to sound elements in an AV stream reduced both pre-stimulus and stimulus-evoked spiking activity, primarily in deep-layer neurons and neurons without spectrotemporal tuning. Despite reduced spiking, stimulus decoder accuracy was preserved, suggesting improved sound encoding efficiency. Similarly, task-irrelevant mapping stimuli during inter-trial intervals evoked fewer spikes without impairing stimulus encoding, indicating that attentional modulation generalized beyond training stimuli. Importantly, spiking reductions predicted trial-to-trial behavioral accuracy during auditory attention, but not visual attention. Together, these findings suggest auditory attention facilitates sound discrimination by filtering sound-irrelevant background activity in AC, and that the deepest cortical layers serve as a hub for integrating extramodal contextual information.

Oxytocin Differentially Modulates Amygdala Responses during Top-Down and Bottom-Up Aversive Anticipation

The ability to successfully regulate negative emotions such as fear and anxiety is vital for mental health. Intranasal administration of the neuropeptide oxytocin (OXT) has been shown to reduce amygdala activity but to increase amygdala-prefrontal cortex connectivity during exposure to threatening stimuli suggesting that it may act as an important modulator of emotion regulation. The present randomized, between-subject, placebo-controlled pharmacological study combines the intranasal administration of OXT with functional magnetic resonance imaging (fMRI) during an explicit emotion regulation paradigm in 65 healthy male participants to investigate the modulatory effects of OXT on both bottom-up and top-down emotion regulation. OXT attenuates the activation in the posterior insular cortex and amygdala during anticipation of top-down regulation of predictable threat stimuli in participants with high trait anxiety. In contrast, OXT enhances amygdala activity during the bottom-up anticipation of unpredictable threat stimuli in participants with low trait anxiety. OXT may facilitate top-down goal-directed attention by attenuating amygdala activity in high anxiety individuals, while promoting bottom-up attention/vigilance to unexpected threats by enhancing amygdala activity in low anxiety individuals. OXT may thus have the potential to promote an adaptive balance between bottom-up and top-down attention systems depending on an individual's trait anxiety level.

Cortical processing of chemosensory and hedonic features of taste in active licking mice

In the last two decades, a considerable amount of work has been devoted to investigating the neural processing and dynamics of the primary taste cortex of rats. Surprisingly, much less information is available on cortical taste electrophysiology in awake mice, an animal model that is taking on a more prominent role in taste research. Here we present electrophysiological evidence demonstrating how the gustatory cortex (GC) encodes the basic taste qualities (sweet, salty, sour, and bitter) and water when stimuli are actively sampled through licking, the stereotyped behavior by which mice control the access of fluids in the mouth. Mice were trained to receive each stimulus on a fixed ratio schedule in which they had to lick a dry spout six times to receive a tastant on the seventh lick. Electrophysiological recordings confirmed that GC neurons encode both chemosensory and hedonic aspects of actively sampled tastants. In addition, our data revealed two other main findings: GC neurons rapidly encode information about taste qualities in as little as 120 ms, and nearly half of the recorded neurons exhibit spiking activity entrained to licking at rates up to 8 Hz. Overall, our results highlight how the GC of active licking mice rapidly encodes information about taste qualities as well as ongoing sampling behavior, expanding our knowledge on cortical taste processing.NEW & NOTEWORTHY Relatively little information is available on the neural dynamics of taste processing in the mouse gustatory cortex (GC). In this study we investigate how the GC encodes chemosensory and palatability features of a wide panel of gustatory stimuli when actively sampled through licking. Our results show that GC neurons broadly encode basic taste qualities but also process taste hedonics and licking information in a temporally dynamic manner.

Taste Responses in the Nucleus of the Solitary Tract of Awake Obese Rats Are Blunted Compared With Those in Lean Rats

Taste perception changes with obesity but the underlying neural changes remain poorly understood. To address this issue, we recorded taste responses from single cells in the nucleus tractus solitarius (NTS, the first synapse in the central gustatory circuit) in awake, diet-induced obese [(DIO; ≥ 8 weeks on a high-energy diet (45%fat, 17% sugar; HED)], and lean rats. Rats were implanted with a bundle of microelectrodes in the NTS and allowed to recover. Water-deprived rats were allowed to freely lick various tastants in an experimental chamber. Taste stimuli included an array of sapid stimuli dissolved in artificial saliva (AS). Each taste trial consisted of five consecutive licks followed by five AS licks presented on a VR5 schedule. Results showed that taste responses (n = 49 for DIO; n = 74 for lean rats) in NTS cells in DIO rats were smaller in magnitude, shorter in duration, and longer in latency that those in lean rats. However, there were proportionately more taste-responsive cells in DIO than in lean rats. Lick coherence in DIO rats was significantly lower than in lean rats, both in taste-responsive, and lick-related cells (n = 172 in lean; n = 65 in DIO). Analyses of temporal coding showed that taste cells in DIO rats conveyed less information about taste quality than cells in lean rats. Collectively, results suggest that a HED produces blunted, but more prevalent, responses to taste in the NTS, and a weakened association of taste responses with ingestive behavior. These neural adaptations may represent both negative effects and compensatory mechanisms of a HED that may underlie deficits in taste-related behavior associated with obesity.

Expectation-induced modulation of metastable activity underlies faster coding of sensory stimuli

Sensory stimuli can be recognized more rapidly when they are expected. This phenomenon depends on expectation affecting the cortical processing of sensory information. However, the mechanisms responsible for the effects of expectation on sensory circuits remain elusive. Here, we report a novel computational mechanism underlying the expectation-dependent acceleration of coding observed in the gustatory cortex of alert rats. We use a recurrent spiking network model with a clustered architecture capturing essential features of cortical activity, such as its intrinsically generated metastable dynamics. Relying on network theory and computer simulations, we propose that expectation exerts its function by modulating the intrinsically generated dynamics preceding taste delivery. Our model’s predictions were confirmed in the experimental data, demonstrating how the modulation of ongoing activity can shape sensory coding. Altogether, these results provide a biologically plausible theory of expectation and ascribe a new functional role to intrinsically generated, metastable activity.

Open Source Tools for Temporally Controlled Rodent Behavior Suitable for Electrophysiology and Optogenetic Manipulations

Understanding how the brain controls behavior requires observing and manipulating neural activity in awake behaving animals. Neuronal firing is timed at millisecond precision. Therefore, to decipher temporal coding, it is necessary to monitor and control animal behavior at the same level of temporal accuracy. However, it is technically challenging to deliver sensory stimuli and reinforcers as well as to read the behavioral responses they elicit with millisecond precision. Presently available commercial systems often excel in specific aspects of behavior control, but they do not provide a customizable environment allowing flexible experimental design while maintaining high standards for temporal control necessary for interpreting neuronal activity. Moreover, delay measurements of stimulus and reinforcement delivery are largely unavailable. We combined microcontroller-based behavior control with a sound delivery system for playing complex acoustic stimuli, fast solenoid valves for precisely timed reinforcement delivery and a custom-built sound attenuated chamber using high-end industrial insulation materials. Together this setup provides a physical environment to train head-fixed animals, enables calibrated sound stimuli and precisely timed fluid and air puff presentation as reinforcers. We provide latency measurements for stimulus and reinforcement delivery and an algorithm to perform such measurements on other behavior control systems. Combined with electrophysiology and optogenetic manipulations, the millisecond timing accuracy will help interpret temporally precise neural signals and behavioral changes. Additionally, since software and hardware provided here can be readily customized to achieve a large variety of paradigms, these solutions enable an unusually flexible design of rodent behavioral experiments.

Encoding of Sucrose's Palatability in the Nucleus Accumbens Shell and Its Modulation by Exteroceptive Auditory Cues

Although the palatability of sucrose is the primary reason for why it is over consumed, it is not well understood how it is encoded in the nucleus accumbens shell (NAcSh), a brain region involved in reward, feeding, and sensory/motor transformations. Similarly, untouched are issues regarding how an external auditory stimulus affects sucrose palatability and, in the NAcSh, the neuronal correlates of this behavior. To address these questions in behaving rats, we investigated how food-related auditory cues modulate sucrose's palatability. The goals are to determine whether NAcSh neuronal responses would track sucrose's palatability (as measured by the increase in hedonically positive oromotor responses lick rate), sucrose concentration, and how it processes auditory information. Using brief-access tests, we found that sucrose's palatability was enhanced by exteroceptive auditory cues that signal the start and the end of a reward epoch. With only the start cue the rejection of water was accelerated, and the sucrose/water ratio was enhanced, indicating greater palatability. However, the start cue also fragmented licking patterns and decreased caloric intake. In the presence of both start and stop cues, the animals fed continuously and increased their caloric intake. Analysis of the licking microstructure confirmed that auditory cues (either signaling the start alone or start/stop) enhanced sucrose's oromotor-palatability responses. Recordings of extracellular single-unit activity identified several distinct populations of NAcSh responses that tracked either the sucrose palatability responses or the sucrose concentrations by increasing or decreasing their activity. Another neural population fired synchronously with licking and exhibited an enhancement in their coherence with increasing sucrose concentrations. The population of NAcSh's Palatability-related and Lick-Inactive neurons were the most important for decoding sucrose's palatability. Only the Lick-Inactive neurons were phasically activated by both auditory cues and may play a sentinel role monitoring relevant auditory cues to increase caloric intake and sucrose's palatability. In summary, we found that auditory cues that signal the availability of sucrose modulate its palatability and caloric intake in a task dependent-manner and had neural correlates in the NAcSh. These findings show that exteroceptive cues associated with feeding may enhance positive hedonic oromotor-responses elicited by sucrose's palatability.

BOLD temporal variability differentiates wakefulness from anesthesia-induced unconsciousness

Even though a number of findings, based on information content or information integration, are shown to define neural underpinnings characteristic of a conscious experience, the neurophysiological mechanism of consciousness is still poorly understood. Here, we investigated the brain activity and functional connectivity changes that occur in the isoflurane-anesthetized unconscious state in contrast to the awake state in rats (awake and/or anesthetized, n = 68 rats). We examined nine information measures previously shown to distinguish between conscious states: blood oxygen level-dependent (BOLD) variability, functional connectivity strength, modularity, weighted modularity, efficiency, clustering coefficient, small-worldness, and spatial and temporal Lempel-Ziv complexity measure. We also identified modular membership, seed-based network connectivity, and absolute and normalized power spectrums to assess the integrity of the BOLD functional networks between awake and anesthesia. fMRI BOLD variability and related absolute power were the only information measures significantly higher during the awake state compared with isoflurane anesthesia across animals, and with varying levels of anesthesia, after correcting for motion and respiration confounds. Thus, we conclude that, at least under the specific conditions examined here, global measures of information integration/sharing do not properly distinguish the anesthetized state from wakefulness, and heightened overall, global and local, BOLD variability is the most reliable determinant of conscious brain activity relative to isoflurane anesthesia. NEW & NOTEWORTHY Multiple metrics previously suggested to be able to distinguish between states of consciousness were compared, within and across rats in awake and isoflurane anesthesia-induced unconsciousness. All measures tested showed sensitivity to confounds, correcting for motion and for respiration changes due to anesthesia. Resting state local BOLD variability and the related absolute power were the only information measures that robustly differentiated wakefulness states. These results caution against the general applicability of global information measures in identifying levels of consciousness, thus challenging the popular concept that these measures reflect states of consciousness, and also pointing to local signal variability as a more reliable indicator of states of wakefulness.

A Decline in Response Variability Improves Neural Signal Detection during Auditory Task Performance

The detection of a sensory stimulus arises from a significant change in neural activity, but a sensory neuron's response is rarely identical to successive presentations of the same stimulus. Large trial-to-trial variability would limit the central nervous system's ability to reliably detect a stimulus, presumably affecting perceptual performance. However, if response variability were to decrease while firing rate remained constant, then neural sensitivity could improve. Here, we asked whether engagement in an auditory detection task can modulate response variability, thereby increasing neural sensitivity. We recorded telemetrically from the core auditory cortex of gerbils, both while they engaged in an amplitude-modulation detection task and while they sat quietly listening to the identical stimuli. Using a signal detection theory framework, we found that neural sensitivity was improved during task performance, and this improvement was closely associated with a decrease in response variability. Moreover, units with the greatest change in response variability had absolute neural thresholds most closely aligned with simultaneously measured perceptual thresholds. Our findings suggest that the limitations imposed by response variability diminish during task performance, thereby improving the sensitivity of neural encoding and potentially leading to better perceptual sensitivity.

SIGNIFICANCE STATEMENT

The detection of a sensory stimulus arises from a significant change in neural activity. However, trial-to-trial variability of the neural response may limit perceptual performance. If the neural response to a stimulus is quite variable, then the response on a given trial could be confused with the pattern of neural activity generated when the stimulus is absent. Therefore, a neural mechanism that served to reduce response variability would allow for better stimulus detection. By recording from the cortex of freely moving animals engaged in an auditory detection task, we found that variability of the neural response becomes smaller during task performance, thereby improving neural detection thresholds.

Associative learning changes cross-modal representations in the gustatory cortex

A growing body of literature has demonstrated that primary sensory cortices are not exclusively unimodal, but can respond to stimuli of different sensory modalities. However, several questions concerning the neural representation of cross-modal stimuli remain open. Indeed, it is poorly understood if cross-modal stimuli evoke unique or overlapping representations in a primary sensory cortex and whether learning can modulate these representations. Here we recorded single unit responses to auditory, visual, somatosensory, and olfactory stimuli in the gustatory cortex (GC) of alert rats before and after associative learning. We found that, in untrained rats, the majority of GC neurons were modulated by a single modality. Upon learning, both prevalence of cross-modal responsive neurons and their breadth of tuning increased, leading to a greater overlap of representations. Altogether, our results show that the gustatory cortex represents cross-modal stimuli according to their sensory identity, and that learning changes the overlap of cross-modal representations.

DOI:http://dx.doi.org/10.7554/eLife.16420.001

Imagine that you are waiting for a cappuccino at your favorite café. You hear the sound of the steamer, and shortly afterwards the barista calls your name and announces that your cappuccino is ready. As they hand it to you, you see the foam sprinkled with cocoa and the aroma of the cappuccino reaches your nose. You can almost taste it. When you finally take your first sip, the taste is hardly a surprise; it is just as your eyes and nose predicted.

How does the brain deal with such a rich and multisensory experience? How does it learn to associate the sight and smell of a cappuccino with its taste? Specialized regions of the brain called associative areas were traditionally thought to perform this task. These areas receive inputs from every sensory system and can link information from these different sources together. According to this view, the job of each individual sensory system is to pass along information relevant to one particular sense.

More recent results, however, challenge this strict division of labor and suggest that individual sensory systems may be able to combine information from multiple senses. Thus the sights, sounds and odors associated with our cappuccino may also activate the area of the brain in charge of processing taste: the gustatory cortex. To investigate this possibility, Vincis and Fontanini set out to determine whether neurons in the gustatory cortex of rats can process stimuli belonging to senses other than taste.

As predicted, neurons in the gustatory cortex did change their firing rates in response to odors, touch, sounds and light. However, more of the gustatory neurons responded to odors and touch than to sounds and light. In addition, of the four stimuli, the rats most easily learned to associate odors and touch with a sugary solution. This is consistent with the fact that rodents rely more upon their whiskers and their sense of smell to find food they do their eyes and ears. Finally, learning to associate a stimulus other than taste with a sugary solution increased the number of neurons in the gustatory cortex that subsequently responded to other senses and changed their response properties.

Further studies are now required to answer three questions. Why can some senses more effectively influence the activity of the gustatory cortex than others? Can gustatory neurons distinguish between different stimuli of the same type – different odors, for example? What are the neural pathways that convey multisensory information to the gustatory cortex? Answering these questions will help us to better understand how sensory systems link information from multiple senses.

DOI:http://dx.doi.org/10.7554/eLife.16420.002

The Behavioral Relevance of Cortical Neural Ensemble Responses Emerges Suddenly

Whereas many laboratory-studied decisions involve a highly trained animal identifying an ambiguous stimulus, many naturalistic decisions do not. Consumption decisions, for instance, involve determining whether to eject or consume an already identified stimulus in the mouth and are decisions that can be made without training. By standard analyses, rodent cortical single-neuron taste responses come to predict such consumption decisions across the 500 ms preceding the consumption or rejection itself; decision-related firing emerges well after stimulus identification. Analyzing single-trial ensemble activity using hidden Markov models, we show these decision-related cortical responses to be part of a reliable sequence of states (each defined by the firing rates within the ensemble) separated by brief state-to-state transitions, the latencies of which vary widely between trials. When we aligned data to the onset of the (late-appearing) state that dominates during the time period in which single-neuron firing is correlated to taste palatability, the apparent ramp in stimulus-aligned choice-related firing was shown to be a much more precipitous coherent jump. This jump in choice-related firing resembled a step function more than it did the output of a standard (ramping) decision-making model, and provided a robust prediction of decision latency in single trials. Together, these results demonstrate that activity related to naturalistic consumption decisions emerges nearly instantaneously in cortical ensembles. Significance statement: This paper provides a description of how the brain makes evaluative decisions. The majority of work on the neurobiology of decision making deals with "what is it?" decisions; out of this work has emerged a model whereby neurons accumulate information about the stimulus in the form of slowly increasing firing rates and reach a decision when those firing rates reach a threshold. Here, we study a different kind of more naturalistic decision--a decision to evaluate "what shall I do with it?" after the identity of a taste in the mouth has been identified--and show that this decision is not made through the gradual increasing of stimulus-related firing, but rather that this decision appears to be made in a sudden moment of "insight."

Large-Scale Simulations of Plastic Neural Networks on Neuromorphic Hardware

SpiNNaker is a digital, neuromorphic architecture designed for simulating large-scale spiking neural networks at speeds close to biological real-time. Rather than using bespoke analog or digital hardware, the basic computational unit of a SpiNNaker system is a general-purpose ARM processor, allowing it to be programmed to simulate a wide variety of neuron and synapse models. This flexibility is particularly valuable in the study of biological plasticity phenomena. A recently proposed learning rule based on the Bayesian Confidence Propagation Neural Network (BCPNN) paradigm offers a generic framework for modeling the interaction of different plasticity mechanisms using spiking neurons. However, it can be computationally expensive to simulate large networks with BCPNN learning since it requires multiple state variables for each synapse, each of which needs to be updated every simulation time-step. We discuss the trade-offs in efficiency and accuracy involved in developing an event-based BCPNN implementation for SpiNNaker based on an analytical solution to the BCPNN equations, and detail the steps taken to fit this within the limited computational and memory resources of the SpiNNaker architecture. We demonstrate this learning rule by learning temporal sequences of neural activity within a recurrent attractor network which we simulate at scales of up to 2.0 × 104 neurons and 5.1 × 107 plastic synapses: the largest plastic neural network ever to be simulated on neuromorphic hardware. We also run a comparable simulation on a Cray XC-30 supercomputer system and find that, if it is to match the run-time of our SpiNNaker simulation, the super computer system uses approximately 45× more power. This suggests that cheaper, more power efficient neuromorphic systems are becoming useful discovery tools in the study of plasticity in large-scale brain models.

State Dependency of Chemosensory Coding in the Gustatory Thalamus (VPMpc) of Alert Rats

The parvicellular portion of the ventroposteromedial nucleus (VPMpc) is the part of the thalamus that processes gustatory information. Anatomical evidence shows that the VPMpc receives ascending gustatory inputs from the parabrachial nucleus (PbN) in the brainstem and sends projections to the gustatory cortex (GC). Although taste processing in PbN and GC has been the subject of intense investigation in behaving rodents, much less is known on how VPMpc neurons encode gustatory information. Here we present results from single-unit recordings in the VPMpc of alert rats receiving multiple tastants. Thalamic neurons respond to taste with time-varying modulations of firing rates, consistent with those observed in GC and PbN. These responses encode taste quality as well as palatability. Comparing responses to tastants either passively delivered, or self-administered after a cue, unveiled the effects of general expectation on taste processing in VPMpc. General expectation led to an improvement of taste coding by modulating response dynamics, and single neuron ability to encode multiple tastants. Our results demonstrate that the time course of taste coding as well as single neurons' ability to encode for multiple qualities are not fixed but rather can be altered by the state of the animal. Together, the data presented here provide the first description that taste coding in VPMpc is dynamic and state-dependent.

SIGNIFICANCE STATEMENT

Over the past years, a great deal of attention has been devoted to understanding taste coding in the brainstem and cortex of alert rodents. Thanks to this research, we now know that taste coding is dynamic, distributed, and context-dependent. Alas, virtually nothing is known on how the gustatory thalamus (VPMpc) processes gustatory information in behaving rats. This manuscript investigates taste processing in the VPMpc of behaving rats. Our results show that thalamic neurons encode taste and palatability with time-varying patterns of activity and that thalamic coding of taste is modulated by general expectation. Our data will appeal not only to researchers interested in taste, but also to a broader audience of sensory and systems neuroscientists interested in the thalamocortical system.

State Dependency of Chemosensory Coding in the Gustatory Thalamus (VPMpc) of Alert Rats

The parvicellular portion of the ventroposteromedial nucleus (VPMpc) is the part of the thalamus that processes gustatory information. Anatomical evidence shows that the VPMpc receives ascending gustatory inputs from the parabrachial nucleus (PbN) in the brainstem and sends projections to the gustatory cortex (GC). Although taste processing in PbN and GC has been the subject of intense investigation in behaving rodents, much less is known on how VPMpc neurons encode gustatory information. Here we present results from single-unit recordings in the VPMpc of alert rats receiving multiple tastants. Thalamic neurons respond to taste with time-varying modulations of firing rates, consistent with those observed in GC and PbN. These responses encode taste quality as well as palatability. Comparing responses to tastants either passively delivered, or self-administered after a cue, unveiled the effects of general expectation on taste processing in VPMpc. General expectation led to an improvement of taste coding by modulating response dynamics, and single neuron ability to encode multiple tastants. Our results demonstrate that the time course of taste coding as well as single neurons' ability to encode for multiple qualities are not fixed but rather can be altered by the state of the animal. Together, the data presented here provide the first description that taste coding in VPMpc is dynamic and state-dependent.

SIGNIFICANCE STATEMENT

Over the past years, a great deal of attention has been devoted to understanding taste coding in the brainstem and cortex of alert rodents. Thanks to this research, we now know that taste coding is dynamic, distributed, and context-dependent. Alas, virtually nothing is known on how the gustatory thalamus (VPMpc) processes gustatory information in behaving rats. This manuscript investigates taste processing in the VPMpc of behaving rats. Our results show that thalamic neurons encode taste and palatability with time-varying patterns of activity and that thalamic coding of taste is modulated by general expectation. Our data will appeal not only to researchers interested in taste, but also to a broader audience of sensory and systems neuroscientists interested in the thalamocortical system.

A reduction for spiking integrate-and-fire network dynamics ranging from homogeneity to synchrony

In this paper we provide a general methodology for systematically reducing the dynamics of a class of integrate-and-fire networks down to an augmented 4-dimensional system of ordinary-differential-equations. The class of integrate-and-fire networks we focus on are homogeneously-structured, strongly coupled, and fluctuation-driven. Our reduction succeeds where most current firing-rate and population-dynamics models fail because we account for the emergence of 'multiple-firing-events' involving the semi-synchronous firing of many neurons. These multiple-firing-events are largely responsible for the fluctuations generated by the network and, as a result, our reduction faithfully describes many dynamic regimes ranging from homogeneous to synchronous. Our reduction is based on first principles, and provides an analyzable link between the integrate-and-fire network parameters and the relatively low-dimensional dynamics underlying the 4-dimensional augmented ODE.

Encoding and tracking of outcome-specific expectancy in the gustatory cortex of alert rats

In natural conditions, gustatory stimuli are typically expected. Anticipatory and contextual cues provide information that allows animals to predict the availability and the identity of the substance to be ingested. Recording in alert rats trained to self-administer tastants following a go signal revealed that neurons in the primary gustatory cortex (GC) can respond to anticipatory cues. These experiments were optimized to demonstrate that even the most general form of expectation can activate neurons in GC, and did not provide indications on whether cues predicting different tastants could be encoded selectively by GC neurons. Here we recorded single-neuron activity in GC of rats engaged in a task where one auditory cue predicted sucrose, while another predicted quinine. We found that GC neurons respond differentially to the two cues. Cue-selective responses develop in parallel with learning. Comparison between cue and sucrose responses revealed that cues could trigger the activation of anticipatory representations. Additional experiments showed that an expectation of sucrose leads a subset of neurons to produce sucrose-like responses even when the tastant was omitted. Altogether, the data show that primary sensory cortices can encode for cues predicting different outcomes, and that specific expectations result in the activation of anticipatory representations.

Temporal signatures of taste quality driven by active sensing

Animals actively acquire sensory information from the outside world, with rodents sniffing to smell and whisking to feel. Licking, a rapid motor sequence used for gustation, serves as the primary means of controlling stimulus access to taste receptors in the mouth. Using a novel taste-quality discrimination task in head-restrained mice, we measured and compared reaction times to four basic taste qualities (salt, sour, sweet, and bitter) and found that certain taste qualities are perceived inherently faster than others, driven by the precise biomechanics of licking and functional organization of the peripheral gustatory system. The minimum time required for accurate perception was strongly dependent on taste quality, ranging from the sensory-motor limits of a single lick (salt, ∼100 ms) to several sampling cycles (bitter, >500 ms). Further, disruption of sensory input from the anterior tongue significantly impaired the speed of perception of some taste qualities, with little effect on others. Overall, our results show that active sensing may play an important role in shaping the timing of taste-quality representations and perception in the gustatory system.

Behaviorally gated reduction of spontaneous discharge can improve detection thresholds in auditory cortex

Animals often listen selectively for particular sounds, a strategy that could alter neural encoding mechanisms to maximize the ability to detect the target. Here, we recorded auditory cortex neuron responses in well trained, freely moving gerbils as they performed a tone detection task. Each trial was initiated by the animal, providing a predictable time window during which to listen. No sound was presented on nogo trials, permitting us to assess spontaneous activity on trials in which a signal could have been expected, but was not delivered. Immediately after animals initiated a trial, auditory cortex neurons displayed a 26% reduction in spontaneous activity. Moreover, when stimulus-driven discharge rate was referenced to this reduced baseline, a larger fraction of auditory cortex neurons displayed a detection threshold within 10 dB of the behavioral threshold. These findings suggest that auditory cortex spontaneous discharge rate can be modulated transiently during task performance, thereby increasing the signal-to-noise ratio and enhancing signal detection.

Sensory cortical population dynamics uniquely track behavior across learning and extinction

Neural responses in many cortical regions encode information relevant to behavior: information that necessarily changes as that behavior changes with learning. Although such responses are reasonably theorized to be related to behavior causation, the true nature of that relationship cannot be clarified by simple learning studies, which show primarily that responses change with experience. Neural activity that truly tracks behavior (as opposed to simply changing with experience) will not only change with learning but also change back when that learning is extinguished. Here, we directly probed for this pattern, recording the activity of ensembles of gustatory cortical single neurons as rats that normally consumed sucrose avidly were trained first to reject it (i.e., conditioned taste aversion learning) and then to enjoy it again (i.e., extinction), all within 49 h. Both learning and extinction altered cortical responses, consistent with the suggestion (based on indirect evidence) that extinction is a novel form of learning. But despite the fact that, as expected, postextinction single-neuron responses did not resemble "naive responses," ensemble response dynamics changed with learning and reverted with extinction: both the speed of stimulus processing and the relationships among ensemble responses to the different stimuli tracked behavioral relevance. These data suggest that population coding is linked to behavior with a fidelity that single-neuron coding is not.

Speed and accuracy of taste identification and palatability: impact of learning, reward expectancy, and consummatory licking

Despite decades of study, it remains a matter of controversy as to whether in rats taste identification is a rapid process that occurs in about 250-600 ms (one to three licks) or a slow process that evolves over seconds. To address this issue, we trained rats to perform a taste-cued two-response discrimination task (2-RDT). It was found that, after learning, regardless of intensity, the delivery of 10 μl of a tastant (e.g., NaCl or monopotassium glutamate, MPG) was sufficient to identify its taste with maximal accuracy within 400 ms. However, despite overtraining, rats rarely stopped licking in one lick. Thus, a one-drop lick reaction task was developed in which subjects had to rapidly stop licking after release of a stop signal (tastants including water) to obtain rewards. The faster they stopped licking, the greater the reward. Rats did not stop licking after receiving either hedonically positive or negative stop signals, and thus failed to maximize rewards even when reinforced with even larger rewards. In fact, the higher the sucrose concentration given as a stop signal, the greater the number of consummatory licks elicited. However, with a stop signal of 2 mM quinine HCl, they stopped licking in ~370 ms, a time faster than that for sucrose or water, thus showing that in this rapid period, quinine HCl evoked an unpalatable response. Indeed, only when rats licked an empty sipper tube would they usually elicit a single lick to obtain a reward (operant licking). In summary, these data indicate that within 400 ms, taste identification and palatability, must either occur simultaneously or with marked overlap.

Accuracy and response-time distributions for decision-making: linear perfect integrators versus nonlinear attractor-based neural circuits

Animals choose actions based on imperfect, ambiguous data. “Noise” inherent in neural processing adds further variability to this already-noisy input signal. Mathematical analysis has suggested that the optimal apparatus (in terms of the speed/accuracy trade-off) for reaching decisions about such noisy inputs is perfect accumulation of the inputs by a temporal integrator. Thus, most highly cited models of neural circuitry underlying decision-making have been instantiations of a perfect integrator. Here, in accordance with a growing mathematical and empirical literature, we describe circumstances in which perfect integration is rendered suboptimal. In particular we highlight the impact of three biological constraints: (1) significant noise arising within the decision-making circuitry itself; (2) bounding of integration by maximal neural firing rates; and (3) time limitations on making a decision. Under conditions (1) and (2), an attractor system with stable attractor states can easily best an integrator when accuracy is more important than speed. Moreover, under conditions in which such stable attractor networks do not best the perfect integrator, a system with unstable initial states can do so if readout of the system’s final state is imperfect. Ubiquitously, an attractor system with a nonselective time-dependent input current is both more accurate and more robust to imprecise tuning of parameters than an integrator with such input. Given that neural responses that switch stochastically between discrete states can “masquerade” as integration in single-neuron and trial-averaged data, our results suggest that such networks should be considered as plausible alternatives to the integrator model.

Optimal balance of the striatal medium spiny neuron network

Slowly varying activity in the striatum, the main Basal Ganglia input structure, is important for the learning and execution of movement sequences. Striatal medium spiny neurons (MSNs) form cell assemblies whose population firing rates vary coherently on slow behaviourally relevant timescales. It has been shown that such activity emerges in a model of a local MSN network but only at realistic connectivities of 10 ~ 20% and only when MSN generated inhibitory post-synaptic potentials (IPSPs) are realistically sized. Here we suggest a reason for this. We investigate how MSN network generated population activity interacts with temporally varying cortical driving activity, as would occur in a behavioural task. We find that at unrealistically high connectivity a stable winners-take-all type regime is found where network activity separates into fixed stimulus dependent regularly firing and quiescent components. In this regime only a small number of population firing rate components interact with cortical stimulus variations. Around 15% connectivity a transition to a more dynamically active regime occurs where all cells constantly switch between activity and quiescence. In this low connectivity regime, MSN population components wander randomly and here too are independent of variations in cortical driving. Only in the transition regime do weak changes in cortical driving interact with many population components so that sequential cell assemblies are reproducibly activated for many hundreds of milliseconds after stimulus onset and peri-stimulus time histograms display strong stimulus and temporal specificity. We show that, remarkably, this activity is maximized at striatally realistic connectivities and IPSP sizes. Thus, we suggest the local MSN network has optimal characteristics - it is neither too stable to respond in a dynamically complex temporally extended way to cortical variations, nor is it too unstable to respond in a consistent repeatable way. Rather, it is optimized to generate stimulus dependent activity patterns for long periods after variations in cortical excitation.

Neural dynamics in response to binary taste mixtures

Taste stimuli encountered in the natural environment are usually combinations of multiple tastants. Although a great deal is known about how neurons in the taste system respond to single taste stimuli in isolation, less is known about how the brain deals with such mixture stimuli. Here, we probe the responses of single neurons in primary gustatory cortex (GC) of awake rats to an array of taste stimuli including 100% citric acid (100 mM), 100% sodium chloride (100 mM), 100% sucrose (100 mM), and a range of binary mixtures (90/10, 70/30, 50/50, 30/70, and 10/90%). We tested for the presence of three different hypothetical response patterns: 1) responses varying monotonically as a function of concentration of sucrose (or acid) in the mixture (the "monotonic" pattern); 2) responses increasing or decreasing as a function of degree of mixture of the stimulus (the "mixture" pattern); and 3) responses that change abruptly from being similar to one pure taste to being similar the other (the "categorical" pattern). Our results demonstrate the presence of both monotonic and mixture patterns within responses of GC neurons. Specifically, further analysis (that included the presentation of 50 mM sucrose and citric acid) made it clear that mixture suppression reliably precedes a palatability-related pattern. The temporal dynamics of the emergence of the palatability-related pattern parallel the temporal dynamics of the emergence of preference behavior for the same mixtures as measured by a brief access test. We saw no evidence of categorical coding.

A satisficing and bricoleur approach to sensorimotor cognition

In this manuscript I present a set of neural processing principles and evolutionary constraints that should be taken into account in the characterization of sensorimotor cognition. I review evidence supporting the choice of the set of principles, and then I assess how such principles apply to two cases, object perception-action and peripersonal space. The aim is to emphasize the importance of focusing cognitive models on how evolution shapes functional paths to adaptations, as well as to adopt fitness maximization analyses of cognitive functions. Such an approach contrasts with the widespread reverse-engineering assumption that the neural system comprises a set of specialized circuits designed to comply with its assumed functions. The evidence presented in the manuscript points to the fact that neural systems should not be seen as a seat of optimal processes and circuits addressing particular problems in sensorimotor cognition, but as a set of satisficing and tinkered components, mostly not addressing the problems that are supposed to solve, but solving them as secondary effects of the engaged processes. I conclude with a corollary of the challenges lying ahead of the proposed approach.

Choice ball: a response interface for two-choice psychometric discrimination in head-fixed mice

The mouse is an important model system for investigating the neural circuits mediating behavior. Because of advances in imaging and optogenetic methods, head-fixed mouse preparations provide an unparalleled opportunity to observe and control neural circuits. To investigate how neural circuits produce behavior, these methods need to be paired with equally well-controlled and monitored behavioral paradigms. Here, we introduce the choice ball, a response device that enables two-alternative forced-choice (2AFC) tasks in head-fixed mice based on the readout of lateral paw movements. We demonstrate the advantages of the choice ball by training mice in the random-click task, a two-choice auditory discrimination behavior. For each trial, mice listened to binaural streams of Poisson-distributed clicks and were required to roll the choice ball laterally toward the side with the greater click rate. In this assay, mice performed hundreds of trials per session with accuracy ranging from 95% for easy stimuli (large interaural click-rate contrast) to near chance level for low-contrast stimuli. We also show, using the record of individual paw strokes, that mice often reverse decisions they have already initiated and that decision reversals correlate with improved performance. The choice ball enables head-fixed 2AFC paradigms, facilitating the circuit-level analysis of sensory processing, decision making, and motor control in mice.

Effects of cue-triggered expectation on cortical processing of taste

Animals are not passive spectators of the sensory world in which they live. In natural conditions they often sense objects on the bases of expectations initiated by predictive cues. Expectation profoundly modulates neural activity by altering the background state of cortical networks and modulating sensory processing. The link between these two effects is not known. Here, we studied how cue-triggered expectation of stimulus availability influences processing of sensory stimuli in the gustatory cortex (GC). We found that expected tastants were coded more rapidly than unexpected stimuli. The faster onset of sensory coding related to anticipatory priming of GC by associative auditory cues. Simultaneous recordings and pharmacological manipulations of GC and basolateral amygdala revealed the role of top-down inputs in mediating the effects of anticipatory cues. Altogether, these data provide a model for how cue-triggered expectation changes the state of sensory cortices to achieve rapid processing of natural stimuli.

Not so fast: taste stimulus coding time in the rat revisited

Behavioral and electrophysiological studies suggest that rats can identify a taste stimulus with a single lick, in <200 ms. However, the conditions under which these conclusions were drawn varied widely across experiments. We designed a series of experiments to assess the effects of the number of licks of a tastant that are available, tastant concentration and prior learning experience on the speed with which a tastant can modify behavior. To accomplish this we tested exemplars of four basic taste qualities (quinine, 0.1 mM; NaCl, 100 mM; saccharin, 4 mM, or sucrose, 100 mM; citric acid, 10 mM) in rats that were conditioned to avoid quinine. Taste stimuli were available for one, two, or three licks on separate days. All tastants were presented in a randomized order interspersed with water rinse licks presented on a variable ratio schedule. A tastant-specific significant increase in the proportion of long pauses in licking following quinine presentation was defined as evidence of “behavioral identification.” Rats with aversion training given three licks of all taste stimuli paused significantly more often after quinine by the fourth interlick interval, ~580 ms. Control rats showed no evidence of quinine (0.1 mM) identification. When rats in all conditioning groups were tested with a high concentration of quinine (10 mM), a single lick was sufficient to produce significant pausing after quinine, but not until the fourth interlick interval, i.e., ~580 ms. Testing rats with only two tastants rather than four in a session had no effect on the speed of quinine identification. Present data confirm that a single lick is sufficient for rats to identify a taste stimulus, but that additional licks occur before evidence of identification is apparent. Furthermore, learning, tastant concentration and motivation to drink can all modify the speed of behavioral identification.

Distinct neural ensembles in the rat gustatory cortex encode salt and water tastes

The gustatory cortex (GC) is important for perceiving the intensity of tastants but it remains unclear as to how single neurons in the region carry out this function. Previous studies have shown that taste-evoked activity from single neurons in GC can be correlated or anticorrelated with tastant concentration, yet whether one or both neural responses signal intensity is poorly characterized because animals from these studies were not trained to report the intensity of the concentration that they tasted. To address this issue, we designed a two-alternative forced choice (2-AFC) task in which freely licking rats distinguished among concentrations of NaCl and recorded from ensembles of neurons in the GC. We identified three neural ensembles that rapidly (<300 ms or ∼2 licks) processed NaCl concentration. For two ensembles, their NaCl evoked activity was anticorrelated with NaCl concentration but could be further distinguished by their response to water; in one ensemble, water evoked the greatest response while in the other ensemble the lowest tested NaCl concentration evoked the greatest response. However, the concentration sensitive activity from each of these ensembles did not show a strong association with the behaviour of the rat in the 2-AFC task, suggesting a lesser role for signalling tastant intensity. Conversely, for a third neural ensemble, its neural activity was well correlated with increases in NaCl concentration, and this relationship best matched the intensity perceived by the rat. These results suggest that this neuronal ensemble in GC whose activity monotonically increases with concentration plays an important role in signalling the intensity of the taste of NaCl.

Neural processing of gustatory information in insular circuits

The insular cortex is the primary cortical site devoted to taste processing. A large body of evidence is available for how insular neurons respond to gustatory stimulation in both anesthetized and behaving animals. Most of the reports describe broadly tuned neurons that are involved in processing the chemosensory, physiological and psychological aspects of gustatory experience. However little is known about how these neural responses map onto insular circuits. Particularly mysterious is the functional role of the three subdivisions of the insular cortex: the granular, the dysgranular and the agranular insular cortices. In this article we review data on the organization of the local and long-distance circuits in the three subdivisions. The functional significance of these results is discussed in light of the latest electrophysiological data. A view of the insular cortex as a functionally integrated system devoted to processing gustatory, multimodal, cognitive and affective information is proposed.