To investigate the dynamic aspects of gustatory activity, we recorded the responses of small ensembles of cortical neurons to tastants administered to awake rats. Multiple trials of each tastant were delivered during recordings made in oral somatosensory (SI) and gustatory cortex (GC). When integrated tastant responses (firing rates averaged across 2.5 sec) were compared with water responses, 14.4% (13/90) of the GC neurons responded in a taste-specific manner. When time was considered as a source of information, however, the incidence of taste-specific firing increased: as many as 41% (37/90) of the recorded GC neurons exhibited taste-specific patterns of response. For 17% of the neurons identified as responding with taste-specific patterns, the stimulus that caused the most significant response was a function of the time since stimulus delivery. That is, a single neuron might respond most strongly to one tastant in the first 500 msec of a response and then respond most strongly to another tastant later in the response. Further analysis of the time courses of GC and SI cortical neural responses revealed that modulations of GC firing rate arose from three separable processes: early somatosensory input (less than ϳ0.2 sec post-stimulus), later chemosensory input (ϳ0.2-1 sec), and delayed somatosensory input related to orofacial responses (more than ϳ1.0 sec). These data demonstrate that sensory information is available in the time course of GC responses and suggest the viability of views of gustatory processing that treat the temporal structure of cortical responses as an integral part of the neural code.

Summary It has been postulated that homeostatic mechanisms maintain stable circuit function by keeping neuronal firing within a set-point range, but such firing rate homeostasis has never been demonstrated in vivo. Here we use chronic multielectrode recordings to monitor firing rates in visual cortex of freely behaving rats during chronic monocular visual deprivation (MD). Firing rates in V1 were suppressed over the first 2 d of MD, but then rebounded to baseline over the next 2–3 d despite continued MD. This drop and rebound in firing was accompanied by bi-directional changes in mEPSC amplitude measured ex vivo. The rebound in firing was independent of sleep-wake state but was cell-type specific, as putative FS and regular spiking neurons responded to MD with different time-courses. These data establish for the first time that homeostatic mechanisms within the intact CNS act to stabilize neuronal firing rates in the face of sustained sensory perturbations.

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 stimulusspecific. 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.gustatory ͉ hidden Markov model T he time courses of sensory neural responses are rich with structure. Taking time into consideration increases the amount of information that can be extracted from neural codes (1-5) and changes the nature of that information (6-8). Such temporal complexity is the natural result of interactions among neural populations (9-11), a concept recently illustrated in studies of olfactory antennal lobe responses in insects (12)(13)(14).The behavior of mammalian sensory systems has proven more difficult to characterize, due in part to the relative complexity of these networks and of the behaviors and neural activity that they subtend. Feedback and convergence found in mammalian brains are extensive and diffuse (15), a fact that contributes to high trial-to-trial variability of mammalian cortical sensory responses (16). This variability is usually dismissed as noise, a decision formalized by the use of across-trial averages such as peristimulus time histograms (PSTHs) (8) and compilations of sequentially recorded neurons (13) to characterize temporal codes.If the variability in neural responses is not noise, however [if, for instance, it reflects network processes evolving at different speeds from trial to trial (17, 18)], then trial-averaging techniques will obscure features of the underlying neural processes. Recent evidence indirectly suggests that this possibility may be the case: repeating multineuronal temporal patterns that are not reflected in PSTHs follow application of sensory stimuli (19, 20) and precede initiation of motor behaviors (21-23), although the search algorithms used to identify such patterns are controversial (24, 25); furthermore, the speed of perceptual identification itself varies from trial to trial (26, 27) in a manner linked to the dynamics of network activity (27)(28)(29)(30).Here, we provide direct evidence that trial-to-trial variability is a reliable, information-rich part of ensemble sensory processing in awake rats, by using hidden Markov models [HMM (31)...

Proper neuronal function and several forms of synaptic plasticity are highly dependent on precise control of mRNA translation, particularly in dendrites. We find that eIF4AIII, a core exon junction complex (EJC) component loaded onto mRNAs by pre-mRNA splicing, is associated with neuronal mRNA granules and dendritic mRNAs. eIF4AIII knockdown markedly increases both synaptic strength and GLUR1 AMPA receptor abundance at synapses. eIF4AIII depletion also increases ARC, a protein required for maintenance of long-term potentiation; arc mRNA, one of the most abundant in dendrites, is a natural target for nonsense-mediated decay (NMD). Numerous new NMD candidates, some with potential to affect synaptic activity, were also identified computationally. Two models are presented for how translation-dependent decay pathways such as NMD might advantageously function as critical brakes for protein synthesis in cells such as neurons that are highly dependent on spatially and temporally restricted protein expression.

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 ϳ1.0 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 amygdala's 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.