Alfredo Fontanini

Natural stimuli evoke dynamic sequences of states in sensory cortical ensembles

Although temporal coding is a frequent topic of neurophysiology research, trial-to-trial variability in temporal codes is typically dismissed as noise and thought to play no role in sensory function. Here, we show that much of this supposed “noise” faithfully reflects stimulus-related processes carried out in coherent neural networks. Cortical neurons responded to sensory stimuli by progressing through sequences of states, identifiable only in examinations of simultaneously recorded ensembles. The specific times at which ensembles transitioned from state to state varied from trial to trial, but the state sequences were reliable and stimulus-specific. Thus, the characterization of ensemble responses in terms of state sequences captured facets of sensory processing that are missing from, and obscured in, other analyses. This work provides evidence that sensory neurons act as parts of a systems-level dynamic process, the nature of which can best be appreciated through observation of distributed ensembles.

Behavioral States, Network States, and Sensory Response Variability

We review data demonstrating that single-neuron sensory responses change with the states of the neural networks (indexed in terms of spectral properties of local field potentials) in which those neurons are embedded. We start with broad network changes--different levels of anesthesia and sleep--and then move to studies demonstrating that the sensory response plasticity associated with attention and experience can also be conceptualized as functions of network state changes. This leads naturally to the recent data that can be interpreted to suggest that even brief experience can change sensory responses via changes in network states and that trial-to-trial variability in sensory responses is a nonrandom function of network fluctuations, as well. We suggest that the CNS may have evolved specifically to deal with stimulus variability and that the coupling with network states may be central to sensory processing.

Learning-Related Plasticity of Temporal Coding in Simultaneously Recorded Amygdala–Cortical Ensembles

Emotional learning requires the coordinated action of neural populations in limbic and cortical networks. Here, we performed simultaneous extracellular recordings from gustatory cortical (GC) and basolateral amygdalar (BLA) neural ensembles as awake, behaving rats learned to dislike the taste of saccharin [via conditioned taste aversion (CTA)]. Learning-related changes in single-neuron sensory responses were observed in both regions, but the nature of the changes was region specific. In GC, most changes were restricted to relatively late aspects of the response (starting ∼1.0 s after stimulus administration), supporting our hypothesis that in this paradigm palatability-related information resides exclusively in later cortical responses. In contrast, and consistent with data suggesting the amygdalas primary role in judging stimulus palatability, CTA altered all components of BLA taste responses, including the earliest. Finally, learning caused dramatic increases in the functional connectivity (measured in terms of cross-correlation peak heights) between pairs of simultaneously recorded BLA and GC neurons, increases that were evident only during taste processing. Our simultaneous assays of the activity of single neurons in multiple relevant brain regions across learning suggest that the transmission of taste information through amygdala–cortical circuits plays a vital role in CTA memory formation.

Network homeostasis: a matter of coordination.

Brain circuits undergo distributed rearrangements throughout life: development, experience and behavior constantly modify synaptic strength and network connectivity. Despite these changes, neurons and circuits need to preserve their functional stability. Single neurons maintain their spontaneous firing rate within functional working ranges by regulating the efficacy of their synaptic inputs. But how do networks maintain a stable behavior? Is network homeostasis a consequence of cell autonomous mechanisms? In this article we will review recent evidence showing that network homeostasis is more than the sum of single-neuron homeostasis and that high-order network stability can be achieved by coordinated inter-cellular interactions.

Distinct Subtypes of Basolateral Amygdala Taste Neurons Reflect Palatability and Reward

The amygdala processes multiple, dissociable properties of sensory stimuli. Given its central location within a dense network of reciprocally connected regions, it is reasonable to expect that basolateral amygdala (BLA) neurons should produce a rich repertoire of dynamical responses to taste stimuli. Here, we examined single BLA neuron taste responses in awake rats and report the existence of two distinct subgroups of BLA taste neurons operating simultaneously during perceptual processing. One neuron type produced long, protracted responses with dynamics that were strikingly similar to those previously observed in gustatory cortex. These responses reflect cooperation between amygdala and cortex for the purposes of processing palatability. A second type of BLA taste neuron may be part of the system often described as being responsible for reward learning: these neurons produced very brief, short-latency responses to rewarding stimuli; when the rat participated in procuring the taste by pressing a lever in response to a tone, however, those phasic taste responses vanished, phasic responses to the tone appearing instead. Our data provide strong evidence that the neural handling of taste is actually a distributed set of processes and that BLA is a nexus of these multiple processes. These results offer new insights into how amygdala imbues naturalistic sensory stimuli with value.

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.

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.

Cortical Networks Produce Three Distinct 7–12 Hz Rhythms during Single Sensory Responses in the Awake Rat

Cortical rhythms in the α/μ frequency range (7–12 Hz) have been variously related to “idling,” anticipation, seizure, and short-term or working memory. This overabundance of interpretations suggests that sensory cortex may be able to produce more than one (and even more than two) distinct α/μ rhythms. Here we describe simultaneous local field potential and single-neuron recordings made from primary sensory (gustatory) cortex of awake rats and reveal three distinct 7–12 Hz de novo network rhythms within single sessions: an “early,” taste-induced ∼11 Hz rhythm, the first peak of which was a short-latency gustatory evoked potential; a “late,” significantly lower-frequency (∼7 Hz) rhythm that replaced this first rhythm at ∼750–850 ms after stimulus onset (consistently timed with a previously described shift in taste temporal codes); and a “spontaneous” spike-and-wave rhythm of intermediate peak frequency (∼9 Hz) that appeared late in the session, as part of a oft-described reduction in arousal/attention. These rhythms proved dissociable on many grounds: in addition to having different peak frequencies, amplitudes, and shapes and appearing at different time points (although often within single 3 s snippets of activity), the early and late rhythms proved to have completely uncorrelated session-to-session variability, and the spontaneous rhythm affected the early rhythm only (having no impact on the late rhythm). Analysis of spike-to-wave coupling suggested that the early and late rhythms are a unified part of discriminative taste process: the identity of phase-coupled single-neuron ensembles differed from taste to taste, and coupling typically lasted across the change in frequency. These data reveal that even rhythms confined to a narrow frequency band may still have distinct properties.

Processing of Hedonic and Chemosensory Features of Taste in Medial Prefrontal and Insular Networks

Most of the research on cortical processing of taste has focused on either the primary gustatory cortex (GC) or the orbitofrontal cortex (OFC). However, these are not the only areas involved in taste processing. Gustatory information can also reach another frontal region, the medial prefrontal cortex (mPFC), via direct projections from GC. mPFC has been studied extensively in relation to its role in controlling goal-directed action and reward-guided behaviors, yet very little is known about its involvement in taste coding. The experiments presented here address this important point and test whether neurons in mPFC can significantly process the physiochemical and hedonic dimensions of taste. Spiking responses to intraorally delivered tastants were recorded from rats implanted with bundles of electrodes in mPFC and GC. Analysis of single-neuron and ensemble activity revealed similarities and differences between the two areas. Neurons in mPFC can encode the chemosensory identity of gustatory stimuli. However, responses in mPFC are sparser, more narrowly tuned, and have a later onset than in GC. Although taste quality is more robustly represented in GC, taste palatability is coded equally well in the two areas. Additional analysis of responses in neurons processing the hedonic value of taste revealed differences between the two areas in temporal dynamics and sensitivities to palatability. These results add mPFC to the network of areas involved in processing gustatory stimuli and demonstrate significant differences in taste-coding between GC and mPFC.

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.