Odor representations in olfactory cortex: distributed rate coding and decorrelated population activity

Acquisition of non-olfactory encoding improves odour discrimination in olfactory cortex

Olfaction is influenced by contextual factors, past experiences, and the animal's internal state. Whether this information is integrated at the initial stages of cortical odour processing is not known, nor how these signals may influence odour encoding. Here we revealed multiple and diverse non-olfactory responses in the primary olfactory (piriform) cortex (PCx), which dynamically enhance PCx odour discrimination according to behavioural demands. We performed recordings of PCx neurons from mice trained in a virtual reality task to associate odours with visual contexts to obtain a reward. We found that learning shifts PCx activity from encoding solely odours to a regime in which positional, contextual, and associative responses emerge on odour-responsive neurons that become mixed-selective. The modulation of PCx activity by these non-olfactory signals was dynamic, improving odour decoding during task engagement and in rewarded contexts. This improvement relied on the acquired mixed-selectivity, demonstrating how integrating extra-sensory inputs in sensory cortices can enhance sensory processing while encoding the behavioural relevance of stimuli.

Common principles for odour coding across vertebrates and invertebrates

The olfactory system is an ideal and tractable system for exploring how the brain transforms sensory inputs into behaviour. The basic tasks of any olfactory system include odour detection, discrimination and categorization. The challenge for the olfactory system is to transform the high-dimensional space of olfactory stimuli into the much smaller space of perceived objects and valence that endows odours with meaning. Our current understanding of how neural circuits address this challenge has come primarily from observations of the mechanisms of the brain for processing other sensory modalities, such as vision and hearing, in which optimized deep hierarchical circuits are used to extract sensory features that vary along continuous physical dimensions. The olfactory system, by contrast, contends with an ill-defined, high-dimensional stimulus space and discrete stimuli using a circuit architecture that is shallow and parallelized. Here, we present recent observations in vertebrate and invertebrate systems that relate the statistical structure and state-dependent modulation of olfactory codes to mechanisms of perception and odour-guided behaviour.

Odors in space

As an evolutionarily ancient sense, olfaction is key to learning where to find food, shelter, mates, and important landmarks in an animal's environment. Brain circuitry linking odor and navigation appears to be a well conserved multi-region system among mammals; the anterior olfactory nucleus, piriform cortex, entorhinal cortex, and hippocampus each represent different aspects of olfactory and spatial information. We review recent advances in our understanding of the neural circuits underlying odor-place associations, highlighting key choices of behavioral task design and neural circuit manipulations for investigating learning and memory.

A mechanosensory feedback that uncouples external and self-generated sensory responses in the olfactory cortex

Sampling behaviors have sensory consequences that can hinder perceptual stability. In olfaction, sniffing affects early odor encoding, mimicking a sudden change in odor concentration. We examined how the inhalation speed affects the representation of odor concentration in the main olfactory cortex. Neurons combine the odor input with a global top-down signal preceding the sniff and a mechanosensory feedback generated by the air passage through the nose during inhalation. Still, the population representation of concentration is remarkably sniff invariant. This is because the mechanosensory and olfactory responses are uncorrelated within and across neurons. Thus, faster odor inhalation and an increase in concentration change the cortical activity pattern in distinct ways. This encoding strategy affords tolerance to potential concentration fluctuations caused by varying inhalation speeds. Since mechanosensory reafferences are widespread across sensory systems, the coding scheme described here may be a canonical strategy to mitigate the sensory ambiguities caused by movements.

Distinct information conveyed to the olfactory bulb by feedforward input from the nose and feedback from the cortex

Sensory systems are organized hierarchically, but feedback projections frequently disrupt this order. In the olfactory bulb (OB), cortical feedback projections numerically match sensory inputs. To unravel information carried by these two streams, we imaged the activity of olfactory sensory neurons (OSNs) and cortical axons in the mouse OB using calcium indicators, multiphoton microscopy, and diverse olfactory stimuli. Here, we show that odorant mixtures of increasing complexity evoke progressively denser OSN activity, yet cortical feedback activity is of similar sparsity for all stimuli. Also, representations of complex mixtures are similar in OSNs but are decorrelated in cortical axons. While OSN responses to increasing odorant concentrations exhibit a sigmoidal relationship, cortical axonal responses are complex and nonmonotonic, which can be explained by a model with activity-dependent feedback inhibition in the cortex. Our study indicates that early-stage olfactory circuits have access to local feedforward signals and global, efficiently formatted information about odor scenes through cortical feedback.

Endogenous cannabinoids in the piriform cortex tune olfactory perception

Sensory perception depends on interactions between external inputs transduced by peripheral sensory organs and internal network dynamics generated by central neuronal circuits. In the sensory cortex, desynchronized network states associate with high signal-to-noise ratio stimulus-evoked responses and heightened perception. Cannabinoid-type-1-receptors (CB1Rs) - which influence network coordination in the hippocampus - are present in anterior piriform cortex (aPC), a sensory paleocortex supporting olfactory perception. Yet, how CB1Rs shape aPC network activity and affect odor perception is unknown. Using pharmacological manipulations coupled with multi-electrode recordings or fiber photometry in the aPC of freely moving male mice, we show that systemic CB1R blockade as well as local drug infusion increases the amplitude of gamma oscillations in aPC, while simultaneously reducing the occurrence of synchronized population events involving aPC excitatory neurons. In animals exposed to odor sources, blockade of CB1Rs reduces correlation among aPC excitatory units and lowers behavioral olfactory detection thresholds. These results suggest that endogenous endocannabinoid signaling promotes synchronized population events and dampen gamma oscillations in the aPC which results in a reduced sensitivity to external sensory inputs.

Adaptive olfactory circuitry restores function despite severe olfactory bulb degeneration

The olfactory bulb (OB) is a critical component of mammalian olfactory neuroanatomy. Beyond being the first and sole relay station for olfactory information to the rest of the brain, it also contains elaborate stereotypical circuitry that is considered essential for olfaction. Indeed, substantial lesions of the OB in rodents lead to anosmia. Here, we examined the circuitry that underlies olfaction in a mouse model with severe developmental degeneration of the OB. These mice could perform odor-guided tasks and even responded normally to innate olfactory cues. Despite the near total loss of the OB, piriform cortices in these mice responded to odors, and its neural activity sufficed to decode odor identity. We found that sensory neurons express the full repertoire of olfactory receptors, and their axons project primarily to the rudiments of the OB but also, ectopically, to olfactory cortical regions. Within the OB, the number of principal neurons was greatly reduced, and the morphology of their dendrites was abnormal, extending over large regions within the OB. Glomerular organization was totally lost in the severe cases of OB degeneration and altered in the more conserved OBs. This study shows that olfactory functionality can be preserved despite reduced and aberrant circuitry that is missing many of the elements believed to be essential for olfaction, and it may explain reported retention of olfaction in humans with degenerated OBs.

Stable sound decoding despite modulated sound representation in the auditory cortex

The activity of neurons in the auditory cortex is driven by both sounds and non-sensory context. To investigate the neuronal correlates of non-sensory context, we trained head-fixed mice to perform a two-alternative-choice auditory task in which either reward or stimulus expectation (prior) was manipulated in blocks. Using two-photon calcium imaging to record populations of single neurons in the auditory cortex, we found that both stimulus and reward expectation modulated the activity of these neurons. A linear decoder trained on this population activity could decode stimuli as well or better than predicted by the animal's performance. Interestingly, the optimal decoder was stable even in the face of variable sensory representations. Neither the context nor the mouse's choice could be reliably decoded from the recorded neural activity. Our findings suggest that, in spite of modulation of auditory cortical activity by task priors, the auditory cortex does not represent sufficient information about these priors to exploit them optimally. Thus, the combination of rapidly changing sensory information with more slowly varying task information required for decisions in this task might be represented in brain regions other than the auditory cortex.

Biologically plausible local synaptic learning rules robustly implement deep supervised learning

In deep neural networks, representational learning in the middle layer is essential for achieving efficient learning. However, the currently prevailing backpropagation learning rules (BP) are not necessarily biologically plausible and cannot be implemented in the brain in their current form. Therefore, to elucidate the learning rules used by the brain, it is critical to establish biologically plausible learning rules for practical memory tasks. For example, learning rules that result in a learning performance worse than that of animals observed in experimental studies may not be computations used in real brains and should be ruled out. Using numerical simulations, we developed biologically plausible learning rules to solve a task that replicates a laboratory experiment where mice learned to predict the correct reward amount. Although the extreme learning machine (ELM) and weight perturbation (WP) learning rules performed worse than the mice, the feedback alignment (FA) rule achieved a performance equal to that of BP. To obtain a more biologically plausible model, we developed a variant of FA, FA_Ex-100%, which implements direct dopamine inputs that provide error signals locally in the layer of focus, as found in the mouse entorhinal cortex. The performance of FA_Ex-100% was comparable to that of conventional BP. Finally, we tested whether FA_Ex-100% was robust against rule perturbations and biologically inevitable noise. FA_Ex-100% worked even when subjected to perturbations, presumably because it could calibrate the correct prediction error (e.g., dopaminergic signals) in the next step as a teaching signal if the perturbation created a deviation. These results suggest that simplified and biologically plausible learning rules, such as FA_Ex-100%, can robustly facilitate deep supervised learning when the error signal, possibly conveyed by dopaminergic neurons, is accurate.

Effects of stochastic coding on olfactory discrimination in flies and mice

Sparse coding can improve discrimination of sensory stimuli by reducing overlap between their representations. Two factors, however, can offset sparse coding's benefits: similar sensory stimuli have significant overlap and responses vary across trials. To elucidate the effects of these 2 factors, we analyzed odor responses in the fly and mouse olfactory regions implicated in learning and discrimination-the mushroom body (MB) and the piriform cortex (PCx). We found that neuronal responses fall along a continuum from extremely reliable across trials to extremely variable or stochastic. Computationally, we show that the observed variability arises from noise within central circuits rather than sensory noise. We propose this coding scheme to be advantageous for coarse- and fine-odor discrimination. More reliable cells enable quick discrimination between dissimilar odors. For similar odors, however, these cells overlap and do not provide distinguishing information. By contrast, more unreliable cells are decorrelated for similar odors, providing distinguishing information, though these benefits only accrue with extended training with more trials. Overall, we have uncovered a conserved, stochastic coding scheme in vertebrates and invertebrates, and we identify a candidate mechanism, based on variability in a winner-take-all (WTA) inhibitory circuit, that improves discrimination with training.

Stable sound decoding despite modulated sound representation in the auditory cortex

The activity of neurons in the auditory cortex is driven by both sounds and non-sensory context. To investigate the neuronal correlates of non-sensory context, we trained head-fixed mice to perform a two-alternative choice auditory task in which either reward or stimulus expectation (prior) was manipulated in blocks. Using two-photon calcium imaging to record populations of single neurons in auditory cortex, we found that both stimulus and reward expectation modulated the activity of these neurons. A linear decoder trained on this population activity could decode stimuli as well or better than predicted by the animal's performance. Interestingly, the optimal decoder was stable even in the face of variable sensory representations. Neither the context nor the mouse's choice could be reliably decoded from the recorded neural activity. Our findings suggest that in spite of modulation of auditory cortical activity by task priors, auditory cortex does not represent sufficient information about these priors to exploit them optimally and that decisions in this task require that rapidly changing sensory information be combined with more slowly varying task information extracted and represented in brain regions other than auditory cortex.

Fast updating feedback from piriform cortex to the olfactory bulb relays multimodal reward contingency signals during rule-reversal

While animals readily adjust their behavior to adapt to relevant changes in the environment, the neural pathways enabling these changes remain largely unknown. Here, using multiphoton imaging, we investigated whether feedback from the piriform cortex to the olfactory bulb supports such behavioral flexibility. To this end, we engaged head-fixed mice in a multimodal rule-reversal task guided by olfactory and auditory cues. Both odor and, surprisingly, the sound cues triggered cortical bulbar feedback responses which preceded the behavioral report. Responses to the same sensory cue were strongly modulated upon changes in stimulus-reward contingency (rule reversals). The re-shaping of individual bouton responses occurred within seconds of the rule-reversal events and was correlated with changes in the behavior. Optogenetic perturbation of cortical feedback within the bulb disrupted the behavioral performance. Our results indicate that the piriform-to-olfactory bulb feedback carries reward contingency signals and is rapidly re-formatted according to changes in the behavioral context.

High-precision mapping reveals the structure of odor coding in the human brain

Odor perception is inherently subjective. Previous work has shown that odorous molecules evoke distributed activity patterns in olfactory cortices, but how these patterns map on to subjective odor percepts remains unclear. In the present study, we collected neuroimaging responses to 160 odors from 3 individual subjects (18 h per subject) to probe the neural coding scheme underlying idiosyncratic odor perception. We found that activity in the orbitofrontal cortex (OFC) represents the fine-grained perceptual identity of odors over and above coarsely defined percepts, whereas this difference is less pronounced in the piriform cortex (PirC) and amygdala. Furthermore, the implementation of perceptual encoding models enabled us to predict olfactory functional magnetic resonance imaging responses to new odors, revealing that the dimensionality of the encoded perceptual spaces increases from the PirC to the OFC. Whereas encoding of lower-order dimensions generalizes across subjects, encoding of higher-order dimensions is idiosyncratic. These results provide new insights into cortical mechanisms of odor coding and suggest that subjective olfactory percepts reside in the OFC.

Basal Forebrain Modulation of Olfactory Coding In Vivo

Sensory perception is one of the most fundamental brain functions, allowing individuals to properly interact and adapt to a constantly changing environment. This process requires the integration of bottom-up and topdown neuronal activity, which is centrally mediated by the basal forebrain, a brain region that has been linked to a series of cognitive processes such as attention and alertness. Here, we review the latest research using optogenetic approaches in rodents and in vivo electrophysiological recordings that are shedding light on the role of this region, in regulating olfactory processing and decisionmaking. Moreover, we summarize evidence highlighting the anatomical and physiological differences in the basal forebrain of individuals with autism spectrum disorder, which could underpin the sensory perception abnormalities they exhibit, and propose this research line as a potential opportunity to understand the neurobiological basis of this disorder.

Multisensory integration of orally-sourced gustatory and olfactory inputs to the posterior piriform cortex in awake rats

Flavour refers to the sensory experience of food, which is a combination of sensory inputs sourced from multiple modalities during consumption, including taste and odour. Previous work has demonstrated that orally-sourced taste and odour cues interact to determine perceptual judgements of flavour stimuli, although the underlying cellular- and circuit-level neural mechanisms remain unknown. We recently identified a region of the piriform olfactory cortex in rats that responds to both taste and odour stimuli. Here, we investigated how converging taste and odour inputs to this area interact to affect single neuron responsiveness ensemble coding of flavour identity. To accomplish this, we recorded spiking activity from ensembles of single neurons in the posterior piriform cortex (pPC) in awake, tasting rats while delivering taste solutions, odour solutions and taste + odour mixtures directly into the oral cavity. Our results show that taste and odour inputs evoke highly selective, temporally-overlapping responses in multisensory pPC neurons. Comparing responses to mixtures and their unisensory components revealed that taste and odour inputs interact in a non-linear manner to produce unique response patterns. Taste input enhances trial-by-trial decoding of odour identity from small ensembles of simultaneously recorded neurons. Together, these results demonstrate that taste and odour inputs to pPC interact in complex, non-linear ways to form amodal flavour representations that enhance identity coding. KEY POINTS: Experience of food involves taste and smell, although how information from these different senses is combined by the brain to create our sense of flavour remains unknown. We recorded from small groups of neurons in the olfactory cortex of awake rats while they consumed taste solutions, odour solutions and taste + odour mixtures. Taste and smell solutions evoke highly selective responses. When presented in a mixture, taste and smell inputs interacted to alter responses, resulting in activation of unique sets of neurons that could not be predicted by the component responses. Synergistic interactions increase discriminability of odour representations. The olfactory cortex uses taste and smell to create new information representing multisensory flavour identity.

Long-range functional loops in the mouse olfactory system and their roles in computing odor identity

Elucidating the neural circuits supporting odor identification remains an open challenge. Here, we analyze the contribution of the two output cell types of the mouse olfactory bulb (mitral and tufted cells) to decode odor identity and concentration and its dependence on top-down feedback from their respective major cortical targets: piriform cortex versus anterior olfactory nucleus. We find that tufted cells substantially outperform mitral cells in decoding both odor identity and intensity. Cortical feedback selectively regulates the activity of its dominant bulb projection cell type and implements different computations. Piriform feedback specifically restructures mitral responses, whereas feedback from the anterior olfactory nucleus preferentially controls the gain of tufted representations without altering their odor tuning. Our results identify distinct functional loops involving the mitral and tufted cells and their cortical targets. We suggest that in addition to the canonical mitral-to-piriform pathway, tufted cells and their target regions are ideally positioned to compute odor identity.

High-Frequency Local Field Potential Oscillations May Modulate Aggressive Behaviors in Mice

Aggressive behavior is one of congenital social behaviors in many species, which could be promoted by social neglect or isolation in the early stages of life. Many brain regions including the medial prefrontal cortex (mPFC), medial amygdala (MeA) and ventromedial hypothalamus (VMH) are demonstrated to relate to aggressive behavior; however, the dynamic patterns of neural activities during the occurrence of this behavior remain unclear. In this study, 21-day-old male CD-1 mice were reared in social isolation conditions and cohousing conditions for two weeks. Aggressive behaviors of each subject were estimated by the resident-intruder test. Simultaneously, the local field potentials of mPFC, MeA and VMH were recorded for exploring differences in the relative power spectra of different oscillations when aggressive behaviors occurred. The results showed that the following: (1) Compared with the cohousing mice, the socially isolated mice exhibited more aggression. (2) Regardless of "time condition" (pre-, during- and post- attack), the relative power spectra of beta band in the cohousing mice were significantly greater than those in the socially isolated mice, and inversely, the relative power spectra of gamma band in the cohousing mice were significantly smaller than those in the socially isolated mice. (3) The bilateral mPFC exhibited significantly smaller beta power spectra but greater gamma power spectra compared with other brain areas regardless of rearing patterns. (4) For the right VMH of the socially isolated mice, the relative power spectra of the gamma band during attacks were significantly greater than those before attack. These results suggest that aggressive behaviors in mice could be shaped by rearing patterns and that high-frequency oscillations (beta and gamma bands) may engage in mediating aggressive behaviors in mice.

High-throughput sequencing of single neuron projections reveals spatial organization in the olfactory cortex

In most sensory modalities, neuronal connectivity reflects behaviorally relevant stimulus features, such as spatial location, orientation, and sound frequency. By contrast, the prevailing view in the olfactory cortex, based on the reconstruction of dozens of neurons, is that connectivity is random. Here, we used high-throughput sequencing-based neuroanatomical techniques to analyze the projections of 5,309 mouse olfactory bulb and 30,433 piriform cortex output neurons at single-cell resolution. Surprisingly, statistical analysis of this much larger dataset revealed that the olfactory cortex connectivity is spatially structured. Single olfactory bulb neurons targeting a particular location along the anterior-posterior axis of piriform cortex also project to matched, functionally distinct, extra-piriform targets. Moreover, single neurons from the targeted piriform locus also project to the same matched extra-piriform targets, forming triadic circuit motifs. Thus, as in other sensory modalities, olfactory information is routed at early stages of processing to functionally diverse targets in a coordinated manner.

Perceptual enhancement and suppression correlate with V1 neural activity during active sensing

Perception in multiple sensory modalities is an active process that involves exploratory behaviors. In humans and other primates, vision results from sensory sampling guided by saccadic eye movements. Saccades are known to modulate visual perception, and a corollary discharge signal associated with saccades appears to establish a sense of visual stability. Neural recordings have shown that saccades also modulate activity widely across the brain. To investigate the neural basis of saccadic effects on perception, simultaneous recordings from multiple neurons in area V1 were made as animals performed a contrast detection task. Perceptual and neural measures were compared when the animal made real saccades that brought a stimulus into V1 receptive fields and when simulated saccades were made (identical retinal stimulation but no eye movement). When real saccades were made and low spatial frequency stimuli were presented, we observed a reduction in both perceptual sensitivity and neural activity compared with simulated saccades; conversely, with higher spatial frequency stimuli, saccades increased visual sensitivity and neural activity. The performance of neural decoders, which used the activity of the population of simultaneously recorded neurons, showed saccade effects on sensitivity that mirrored the frequency-dependent perceptual changes, suggesting that the V1 population activity could support the perceptual effects. A minority of V1 neurons had significant choice probabilities, and the saccades decreased both average choice probability and pairwise noise correlations. Taken together, the findings suggest that a signal related to saccadic eye movements alters V1 spiking to increase the independence of spiking neurons and bias the system toward processing higher spatial frequencies, presumably to enhance object recognition. The effects of saccades on visual perception and noise correlations appear to parallel effects observed in other sensory modalities, suggesting a general principle of active sensory processing.

Organization and engagement of a prefrontal-olfactory network during olfactory selective attention

BACKGROUND

Sensory perception is profoundly shaped by attention. Attending to an odor strongly regulates if and how it is perceived - yet the brain systems involved in this process are unknown. Here we report integration of the medial prefrontal cortex (mPFC), a collection of brain regions integral to attention, with the olfactory system in the context of selective attention to odors.

METHODS

First, we used tracing methods to establish the tubular striatum (TuS, also known as the olfactory tubercle) as the primary olfactory region to receive direct mPFC input in rats. Next, we recorded (i) local field potentials from the olfactory bulb (OB), mPFC, and TuS, or (ii) sniffing, while rats completed an olfactory selective attention task.

RESULTS

Gamma power and coupling of gamma oscillations with theta phase were consistently high as rats flexibly switched their attention to odors. Beta and theta synchrony between mPFC and olfactory regions were elevated as rats switched their attention to odors. Finally, we found that sniffing was consistent despite shifting attentional demands, suggesting that the mPFC-OB theta coherence is independent of changes in active sampling.

CONCLUSIONS

Together, these findings begin to define an olfactory attention network wherein mPFC activity, as well as that within olfactory regions, are coordinated based upon attentional states.

Upstream γ-synchronization enhances odor processing in downstream neurons

γ-oscillatory activity is ubiquitous across brain areas. Numerous studies have suggested that γ-synchrony is likely to enhance the transmission of sensory information. However, direct causal evidence is still lacking. Here, we test this hypothesis in the mouse olfactory system, where local GABAergic granule cells (GCs) in the olfactory bulb shape mitral/tufted cell (MTC) excitatory output from the olfactory bulb. By optogenetically modulating GC activity, we successfully dissociate MTC γ-synchronization from its firing rates. Recording of odor responses in downstream piriform cortex neurons shows that increasing MTC γ-synchronization enhances cortical neuron odor-evoked firing rates, reduces response variability, and improves odor ensemble representation. These gains occur despite a reduction in MTC firing rates. Furthermore, reducing MTC γ-synchronization without changing the MTC firing rates, by suppressing GC activity, degrades piriform cortex odor-evoked responses. These findings provide causal evidence that increased γ-synchronization enhances the transmission of sensory information between two brain regions.

Top-down feedback enables flexible coding strategies in the olfactory cortex

In chemical sensation, multiple models have been proposed to explain how odors are represented in the olfactory cortex. One hypothesis is that the combinatorial identity of active neurons within sniff-related time windows is critical, whereas another model proposes that it is the temporal structure of neural activity that is essential for encoding odor information. We find that top-down feedback to the main olfactory bulb dictates the information transmitted to the piriform cortex and switches between these coding strategies. Using a detailed network model, we demonstrate that feedback control of inhibition influences the excitation-inhibition balance in mitral cells, restructuring the dynamics of piriform cortical cells. This results in performance improvement in odor discrimination tasks. These findings present a framework for early olfactory computation, where top-down feedback to the bulb flexibly shapes the temporal structure of neural activity in the piriform cortex, allowing the early olfactory system to dynamically switch between two distinct coding models.

State-dependent olfactory processing in freely behaving mice

Decreased responsiveness to sensory stimuli during sleep is presumably mediated via thalamic gating. Without an obligatory thalamic relay in the olfactory system, the anterior piriform cortex (APC) is suggested to be a gate in anesthetized states. However, olfactory processing in natural sleep states remains undetermined. Here, we simultaneously record local field potentials (LFPs) in hierarchical olfactory regions (olfactory bulb [OB], APC, and orbitofrontal cortex) while optogenetically activating olfactory sensory neurons, ensuring consistent peripheral inputs across states in behaving mice. Surprisingly, evoked LFPs in sleep states (both non-rapid eye movement [NREM] and rapid eye movement [REM]) are larger and contain greater gamma-band power and cross-region coherence (compared to wakefulness) throughout the olfactory pathway, suggesting the lack of a central gate. Single-unit recordings from the OB and APC reveal a higher percentage of responsive neurons during sleep with a higher incidence of suppressed firing. Additionally, nasal breathing is slower and shallower during sleep, suggesting a partial peripheral gating mechanism.

Schreck et al. examine how the olfactory system responds to the same peripheral stimulus during natural sleep and wake in mice. Larger responses along the pathway during sleep suggest the lack of a central gate, but slower and shallower breathing may act as a partial peripheral gate to reduce olfactory input.

Rapid odor processing by layer 2 subcircuits in lateral entorhinal cortex

Olfactory information is encoded in lateral entorhinal cortex (LEC) by two classes of layer 2 (L2) principal neurons: fan and pyramidal cells. However, the functional properties of L2 cells and how they contribute to odor coding are unclear. Here, we show in awake mice that L2 cells respond to odors early during single sniffs and that LEC is essential for rapid discrimination of both odor identity and intensity. Population analyses of L2 ensembles reveal that rate coding distinguishes odor identity, but firing rates are only weakly concentration dependent and changes in spike timing can represent odor intensity. L2 principal cells differ in afferent olfactory input and connectivity with inhibitory circuits and the relative timing of pyramidal and fan cell spikes provides a temporal code for odor intensity. Downstream, intensity is encoded purely by spike timing in hippocampal CA1. Together, these results reveal the unique processing of odor information by LEC subcircuits and highlight the importance of temporal coding in higher olfactory areas.

Machine learning-based feature combination analysis for odor-dependent hemodynamic responses of rat olfactory bulb

Rodents have a well-developed sense of smell and are used to detect explosives, mines, illegal substances, hidden currency, and contraband, but it is impossible to keep their concentration constantly. Therefore, there is an ongoing effort to infer odors detected by animals without behavioral readings with brain-computer interface (BCI) technology. However, the invasive BCI technique has the disadvantage that long-term studies are limited by the immune response and electrode movement. On the other hand, near-infrared spectroscopy (NIRS)-based BCI technology is a non-invasive method that can measure neuronal activity without worrying about the immune response or electrode movement. This study confirmed that the NIRS-based BCI technology can be used as an odor detection and identification from the rat olfactory system. In addition, we tried to present features optimized for machine learning models by extracting six features, such as slopes, peak, variance, mean, kurtosis, and skewness, from the hemodynamic response, and analyzing the importance of individuals or combinations. As a result, the feature with the highest F1-Score was indicated as slopes, and it was investigated that the combination of the features including slopes and mean was the most important for odor inference. On the other hand, the inclusion of other features with a low correlation with slopes had a positive effect on the odor inference, but most of them resulted in insignificant or rather poor performance. The results presented in this paper are expected to serve as a basis for suggesting the development direction of the hemodynamic response-based bionic nose in the future.

Spatial maps in piriform cortex during olfactory navigation

Odours are a fundamental part of the sensory environment used by animals to guide behaviours such as foraging and navigation^1,2. Primary olfactory (piriform) cortex is thought to be the main cortical region for encoding odour identity^3-8. Here, using neural ensemble recordings in freely moving rats performing an odour-cued spatial choice task, we show that posterior piriform cortex neurons carry a robust spatial representation of the environment. Piriform spatial representations have features of a learned cognitive map, being most prominent near odour ports, stable across behavioural contexts and independent of olfactory drive or reward availability. The accuracy of spatial information carried by individual piriform neurons was predicted by the strength of their functional coupling to the hippocampal theta rhythm. Ensembles of piriform neurons concurrently represented odour identity as well as spatial locations of animals, forming an odour-place map. Our results reveal a function for piriform cortex in spatial cognition and suggest that it is well-suited to form odour-place associations and guide olfactory-cued spatial navigation.

Cortical Hub for Flavor Sensation in Rodents

The experience of eating is inherently multimodal, combining intraoral gustatory, olfactory, and somatosensory signals into a single percept called flavor. As foods and beverages enter the mouth, movements associated with chewing and swallowing activate somatosensory receptors in the oral cavity, dissolve tastants in the saliva to activate taste receptors, and release volatile odorant molecules to retronasally activate olfactory receptors in the nasal epithelium. Human studies indicate that sensory cortical areas are important for intraoral multimodal processing, yet their circuit-level mechanisms remain unclear. Animal models allow for detailed analyses of neural circuits due to the large number of molecular tools available for tracing and neuronal manipulations. In this review, we concentrate on the anatomical and neurophysiological evidence from rodent models toward a better understanding of the circuit-level mechanisms underlying the cortical processing of flavor. While more work is needed, the emerging view pertaining to the multimodal processing of food and beverages is that the piriform, gustatory, and somatosensory cortical regions do not function solely as independent areas. Rather they act as an intraoral cortical hub, simultaneously receiving and processing multimodal sensory information from the mouth to produce the rich and complex flavor experience that guides consummatory behavior.

Time Course of Odor Categorization Processing

The brain’s mechanisms for categorizing different odors have long been a research focus. Previous studies suggest that odor categorization may involve multiple neurological processes within the brain with temporal and spatial neuronal activation. However, there is limited evidence regarding temporally mediated mechanisms in humans, especially millisecond odor processing. Such mechanisms may be important because different brain areas may play different roles at a particular activation time during sensory processing. Here, we focused on how the brain categorizes odors at specific time intervals. Using multivariate electroencephalography (EEG) analysis, we found that similarly perceived odors induced similar EEG signals during 50–100, 150–200, and 350–400 ms at the theta frequency. We also found significant activation at 100–150 and 350–400 ms at the gamma frequency. At these two frequencies, significant activation was observed in some olfactory-associated areas, including the orbitofrontal cortex. Our findings provide essential evidence that specific periods may be related to odor quality processing during central olfactory processing.

Unraveling the Role of Dopaminergic and Calretinin Interneurons in the Olfactory Bulb

The perception and discriminating of odors are sensory activities that are an integral part of our daily life. The first brain region where odors are processed is the olfactory bulb (OB). Among the different cell populations that make up this brain area, interneurons play an essential role in this sensory activity. Moreover, probably because of their activity, they represent an exception compared to other parts of the brain, since OB interneurons are continuously generated in the postnatal and adult period. In this review, we will focus on periglomerular (PG) cells which are a class of interneurons found in the glomerular layer of the OB. These interneurons can be classified into distinct subtypes based on their neurochemical nature, based on the neurotransmitter and calcium-binding proteins expressed by these cells. Dopaminergic (DA) periglomerular cells and calretinin (CR) cells are among the newly generated interneurons and play an important role in the physiology of OB. In the OB, DA cells are involved in the processing of odors and the adaptation of the bulbar network to external conditions. The main role of DA cells in OB appears to be the inhibition of glutamate release from olfactory sensory fibers. Calretinin cells are probably the best morphologically characterized interneurons among PG cells in OB, but little is known about their function except for their inhibitory effect on noisy random excitatory signals arriving at the main neurons. In this review, we will mainly describe the electrophysiological properties related to the excitability profiles of DA and CR cells, with a particular view on the differences that characterize DA mature interneurons from cells in different stages of adult neurogenesis.

Odor-evoked increases in olfactory bulb mitral cell spiking variability

The spiking variability of neural networks has important implications for how information is encoded to higher brain regions. It has been well documented by numerous labs in many cortical and motor regions that spiking variability decreases with stimulus onset, yet whether this principle holds in the OB has not been tested. In stark contrast to this common view, we demonstrate that the onset of sensory input can cause an increase in the variability of neural activity in the mammalian OB. We show this in both anesthetized and awake rodents. Furthermore, we use computational models to describe the mechanisms of this phenomenon. Our findings establish sensory evoked increases in spiking variability as a viable alternative coding strategy.

An Emergent Population Code in Primary Auditory Cortex Supports Selective Attention to Spectral and Temporal Sound Features

Textbook descriptions of primary sensory cortex (PSC) revolve around single neurons' representation of low-dimensional sensory features, such as visual object orientation in primary visual cortex (V1), location of somatic touch in primary somatosensory cortex (S1), and sound frequency in primary auditory cortex (A1). Typically, studies of PSC measure neurons' responses along few (one or two) stimulus and/or behavioral dimensions. However, real-world stimuli usually vary along many feature dimensions and behavioral demands change constantly. In order to illuminate how A1 supports flexible perception in rich acoustic environments, we recorded from A1 neurons while rhesus macaques (one male, one female) performed a feature-selective attention task. We presented sounds that varied along spectral and temporal feature dimensions (carrier bandwidth and temporal envelope, respectively). Within a block, subjects attended to one feature of the sound in a selective change detection task. We found that single neurons tend to be high-dimensional, in that they exhibit substantial mixed selectivity for both sound features, as well as task context. We found no overall enhancement of single-neuron coding of the attended feature, as attention could either diminish or enhance this coding. However, a population-level analysis reveals that ensembles of neurons exhibit enhanced encoding of attended sound features, and this population code tracks subjects' performance. Importantly, surrogate neural populations with intact single-neuron tuning but shuffled higher-order correlations among neurons fail to yield attention- related effects observed in the intact data. These results suggest that an emergent population code not measurable at the single-neuron level might constitute the functional unit of sensory representation in PSC.SIGNIFICANCE STATEMENT The ability to adapt to a dynamic sensory environment promotes a range of important natural behaviors. We recorded from single neurons in monkey primary auditory cortex (A1), while subjects attended to either the spectral or temporal features of complex sounds. Surprisingly, we found no average increase in responsiveness to, or encoding of, the attended feature across single neurons. However, when we pooled the activity of the sampled neurons via targeted dimensionality reduction (TDR), we found enhanced population-level representation of the attended feature and suppression of the distractor feature. This dissociation of the effects of attention at the level of single neurons versus the population highlights the synergistic nature of cortical sound encoding and enriches our understanding of sensory cortical function.

Bridging neuronal correlations and dimensionality reduction

Two commonly used approaches to study interactions among neurons are spike count correlation, which describes pairs of neurons, and dimensionality reduction, applied to a population of neurons. Although both approaches have been used to study trial-to-trial neuronal variability correlated among neurons, they are often used in isolation and have not been directly related. We first established concrete mathematical and empirical relationships between pairwise correlation and metrics of population-wide covariability based on dimensionality reduction. Applying these insights to macaque V4 population recordings, we found that the previously reported decrease in mean pairwise correlation associated with attention stemmed from three distinct changes in population-wide covariability. Overall, our work builds the intuition and formalism to bridge between pairwise correlation and population-wide covariability and presents a cautionary tale about the inferences one can make about population activity by using a single statistic, whether it be mean pairwise correlation or dimensionality.

A Biologically Plausible Neural Network for Multichannel Canonical Correlation Analysis

Cortical pyramidal neurons receive inputs from multiple distinct neural populations and integrate these inputs in separate dendritic compartments. We explore the possibility that cortical microcircuits implement canonical correlation analysis (CCA), an unsupervised learning method that projects the inputs onto a common subspace so as to maximize the correlations between the projections. To this end, we seek a multichannel CCA algorithm that can be implemented in a biologically plausible neural network. For biological plausibility, we require that the network operates in the online setting and its synaptic update rules are local. Starting from a novel CCA objective function, we derive an online optimization algorithm whose optimization steps can be implemented in a single-layer neural network with multicompartmental neurons and local non-Hebbian learning rules. We also derive an extension of our online CCA algorithm with adaptive output rank and output whitening. Interestingly, the extension maps onto a neural network whose neural architecture and synaptic updates resemble neural circuitry and non-Hebbian plasticity observed in the cortex.

Finding the Brain in the Nose

Olfaction is fundamentally distinct from other sensory modalities. Natural odor stimuli are complex mixtures of volatile chemicals that interact in the nose with a receptor array that, in rodents, is built from more than 1,000 unique receptors. These interactions dictate a peripheral olfactory code, which in the brain is transformed and reformatted as it is broadcast across a set of highly interconnected olfactory regions. Here we discuss the problems of characterizing peripheral population codes for olfactory stimuli, of inferring the specific functions of different higher olfactory areas given their extensive recurrence, and of ultimately understanding how odor representations are linked to perception and action. We argue that, despite the differences between olfaction and other sensory modalities, addressing these specific questions will reveal general principles underlying brain function.

Principles of odor coding in vertebrates and artificial chemosensory systems

The biological olfactory system is the sensory system responsible for the detection of the chemical composition of the environment. Several attempts to mimic biological olfactory systems have led to various artificial olfactory systems using different technical approaches. Here we provide a parallel description of biological olfactory systems and their technical counterparts. We start with a presentation of the input to the systems, the stimuli, and treat the interface between the external world and the environment where receptor neurons or artificial chemosensors reside. We then delineate the functions of receptor neurons and chemosensors as well as their overall I-O relationships. Up to this point, our account of the systems goes along similar lines. The next processing steps differ considerably: while in biology the processing step following the receptor neurons is the "integration" and "processing" of receptor neuron outputs in the olfactory bulb, this step has various realizations in electronic noses. For a long period of time, the signal processing stages beyond the olfactory bulb, i.e., the higher olfactory centers were little studied. Only recently there has been a marked growth of studies tackling the information processing in these centers. In electronic noses, a third stage of processing has virtually never been considered. In this review, we provide an up-to-date overview of the current knowledge of both fields and, for the first time, attempt to tie them together. We hope it will be a breeding ground for better information, communication, and data exchange between very related but so far little connected fields.

Representational drift in primary olfactory cortex

Perceptual constancy requires the brain to maintain a stable representation of sensory input. In the olfactory system, activity in primary olfactory cortex (piriform cortex) is thought to determine odour identity^1-5. Here we present the results of electrophysiological recordings of single units maintained over weeks to examine the stability of odour-evoked responses in mouse piriform cortex. Although activity in piriform cortex could be used to discriminate between odorants at any moment in time, odour-evoked responses drifted over periods of days to weeks. The performance of a linear classifier trained on the first recording day approached chance levels after 32 days. Fear conditioning did not stabilize odour-evoked responses. Daily exposure to the same odorant slowed the rate of drift, but when exposure was halted the rate increased again. This demonstration of continuous drift poses the question of the role of piriform cortex in odour perception. This instability might reflect the unstructured connectivity of piriform cortex^6-12, and may be a property of other unstructured cortices.

Bi-directional encoding of context-based odors and behavioral states by the nucleus of the lateral olfactory tract

The nucleus of the lateral olfactory tract (NLOT) is not only a part of the olfactory cortex that receives olfactory sensory inputs but also a part of the cortical amygdala, which regulates motivational behaviors. To examine how neural activity of the NLOT is modulated by decision-making processes that occur during various states of learned goal-directed behaviors, we recorded NLOT spike activities of mice performing odor-guided go/no-go tasks to obtain a water reward. We observed that several NLOT neurons exhibited sharp go-cue excitation and persistent no-go-cue suppression responses triggered by an odor onset. The bidirectional cue encoding introduced NLOT population response dynamics and provided a high odor decoding accuracy before executing cue-odor-evoked behaviors. The go-cue responsive neurons were also activated in the reward drinking state, indicating context-based odor-outcome associations. These findings suggest that NLOT neurons play an important role in the translation from context-based odor information to appropriate behavior.

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We recorded NLOT spike activities in the odor-guided goal-directed behaviors

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NLOT neurons were classified into five response types in the odor-sampling epoch

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Many NLOT neurons exhibited go-cue excitation and no-go-cue suppression responses

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The bidirectional responsive neurons were also activated in the reward drinking

Chronic loss of inhibition in piriform cortex following brief, daily optogenetic stimulation

It is well established that seizures beget seizures, yet the cellular processes that underlie progressive epileptogenesis remain unclear. Here, we use optogenetics to briefly activate targeted populations of mouse piriform cortex (PCx) principal neurons in vivo. After just 3 or 4 days of stimulation, previously subconvulsive stimuli trigger massive, generalized seizures. Highly recurrent allocortices are especially prone to “optokindling.” Optokindling upsets the balance of recurrent excitation and feedback inhibition. To understand how this balance is disrupted, we then selectively reactivate the same neurons in vitro. Surprisingly, we find no evidence of heterosynaptic potentiation; instead, we observe a marked, pathway-specific decrease in feedback inhibition. We find no loss of inhibitory interneurons; rather, decreased GABA synthesis in feedback inhibitory neurons appears to underlie weakened inhibition. Optokindling will allow precise identification of the molecular processes by which brain activity patterns can progressively and pathologically disrupt the balance of cortical excitation and inhibition.

Ryu et al. use optogenetics to briefly activate principal neurons in mouse piriform cortex. After 4 days, previously innocuous stimuli evoke massive, generalized seizures. “Optokindling” does not strengthen recurrent excitation; instead, it weakens feedback inhibition by decreasing synaptic cleft GABA concentrations and slowing vesicle refilling, consistent with decreased GABA synthesis.

Mixture Coding and Segmentation in the Anterior Piriform Cortex

Coding of odorous stimuli has been mostly studied using single isolated stimuli. However, a single sniff of air in a natural environment is likely to introduce airborne chemicals emitted by multiple objects into the nose. The olfactory system is therefore faced with the task of segmenting odor mixtures to identify objects in the presence of rich and often unpredictable backgrounds. The piriform cortex is thought to be the site of object recognition and scene segmentation, yet the nature of its responses to odorant mixtures is largely unknown. In this study, we asked two related questions. (1) How are mixtures represented in the piriform cortex? And (2) Can the identity of individual mixture components be read out from mixture representations in the piriform cortex? To answer these questions, we recorded single unit activity in the piriform cortex of naïve mice while sequentially presenting single odorants and their mixtures. We find that a normalization model explains mixture responses well, both at the single neuron, and at the population level. Additionally, we show that mixture components can be identified from piriform cortical activity by pooling responses of a small population of neurons-in many cases a single neuron is sufficient. These results indicate that piriform cortical representations are well suited to perform figure-background segmentation without the need for learning.

CHIME: CMOS-Hosted in vivo Microelectrodes for Massively Scalable Neuronal Recordings

Mammalian brains consist of 10s of millions to 100s of billions of neurons operating at millisecond time scales, of which current recording techniques only capture a tiny fraction. Recording techniques capable of sampling neural activity at high spatiotemporal resolution have been difficult to scale. The most intensively studied mammalian neuronal networks, such as the neocortex, show a layered architecture, where the optimal recording technology samples densely over large areas. However, the need for application-specific designs as well as the mismatch between the three-dimensional architecture of the brain and largely two-dimensional microfabrication techniques profoundly limits both neurophysiological research and neural prosthetics. Here, we discuss a novel strategy for scalable neuronal recording by combining bundles of glass-ensheathed microwires with large-scale amplifier arrays derived from high-density CMOS in vitro MEA systems or high-speed infrared cameras. High signal-to-noise ratio (<25 μV RMS noise floor, SNR up to 25) is achieved due to the high conductivity of core metals in glass-ensheathed microwires allowing for ultrathin metal cores (down to <1 μm) and negligible stray capacitance. Multi-step electrochemical modification of the tip enables ultra-low access impedance with minimal geometric area, which is largely independent of the core diameter. We show that the microwire size can be reduced to virtually eliminate damage to the blood-brain-barrier upon insertion and we demonstrate that microwire arrays can stably record single-unit activity. Combining microwire bundles and CMOS arrays allows for a highly scalable neuronal recording approach, linking the progress in electrical neuronal recordings to the rapid progress in silicon microfabrication. The modular design of the system allows for custom arrangement of recording sites. Our approach of employing bundles of minimally invasive, highly insulated and functionalized microwires to extend a two-dimensional CMOS architecture into the 3rd dimension can be translated to other CMOS arrays, such as electrical stimulation devices.

Tuning of olfactory cortex ventral tenia tecta neurons to distinct task elements of goal-directed behavior

The ventral tenia tecta (vTT) is a component of the olfactory cortex and receives both bottom-up odor signals and top-down signals. However, the roles of the vTT in odor-coding and integration of inputs are poorly understood. Here, we investigated the involvement of the vTT in these processes by recording the activity from individual vTT neurons during the performance of learned odor-guided reward-directed tasks in mice. We report that individual vTT cells are highly tuned to a specific behavioral epoch of learned tasks, whereby the duration of increased firing correlated with the temporal length of the behavioral epoch. The peak time for increased firing among recorded vTT cells encompassed almost the entire temporal window of the tasks. Collectively, our results indicate that vTT cells are selectively activated during a specific behavioral context and that the function of the vTT changes dynamically in a context-dependent manner during goal-directed behaviors.

Recurrent circuitry is required to stabilize piriform cortex odor representations across brain states

Pattern completion, or the ability to retrieve stable neural activity patterns from noisy or partial cues, is a fundamental feature of memory. Theoretical studies indicate that recurrently connected auto-associative or discrete attractor networks can perform this process. Although pattern completion and attractor dynamics have been observed in various recurrent neural circuits, the role recurrent circuitry plays in implementing these processes remains unclear. In recordings from head-fixed mice, we found that odor responses in olfactory bulb degrade under ketamine/xylazine anesthesia while responses immediately downstream, in piriform cortex, remain robust. Recurrent connections are required to stabilize cortical odor representations across states. Moreover, piriform odor representations exhibit attractor dynamics, both within and across trials, and these are also abolished when recurrent circuitry is eliminated. Here, we present converging evidence that recurrently-connected piriform populations stabilize sensory representations in response to degraded inputs, consistent with an auto-associative function for piriform cortex supported by recurrent circuitry.

Top-Down Control of Inhibitory Granule Cells in the Main Olfactory Bulb Reshapes Neural Dynamics Giving Rise to a Diversity of Computations

Growing evidence shows that top-down projections from excitatory neurons in piriform cortex selectively synapse onto local inhibitory granule cells in the main olfactory bulb, effectively gating their own inputs by controlling inhibition. An open question in olfaction is the role this feedback plays in shaping the dynamics of local circuits, and the resultant computational benefits it provides. Using rate models of neuronal firing in a network consisting of excitatory mitral and tufted cells, inhibitory granule cells and top-down piriform cortical neurons, we found that changes in the weight of feedback to inhibitory neurons generated diverse network dynamics and complex transitions between these dynamics. Changes in the weight of top-down feedback supported a number of computations, including both pattern separation and oscillatory synchrony. Additionally, the network could generate gamma oscillations though a mechanism we termed Top-down control of Inhibitory Neuron Gamma (TING). Collectively, these functions arose from a codimension-2 bifurcation in the dynamical system. Our results highlight a key role for this top-down feedback, gating inhibition to facilitate often diametrically different computations.

Phasic dopamine reinforces distinct striatal stimulus encoding in the olfactory tubercle driving dopaminergic reward prediction

The learning of stimulus-outcome associations allows for predictions about the environment. Ventral striatum and dopaminergic midbrain neurons form a larger network for generating reward prediction signals from sensory cues. Yet, the network plasticity mechanisms to generate predictive signals in these distributed circuits have not been entirely clarified. Also, direct evidence of the underlying interregional assembly formation and information transfer is still missing. Here we show that phasic dopamine is sufficient to reinforce the distinctness of stimulus representations in the ventral striatum even in the absence of reward. Upon such reinforcement, striatal stimulus encoding gives rise to interregional assemblies that drive dopaminergic neurons during stimulus-outcome learning. These assemblies dynamically encode the predicted reward value of conditioned stimuli. Together, our data reveal that ventral striatal and midbrain reward networks form a reinforcing loop to generate reward prediction coding.

It is not entirely understood how network plasticity produces the coding of predicted value during stimulus-outcome learning. Here, the authors reveal a reinforcing loop in distributed limbic circuits, transforming sensory stimuli into reward prediction coding broadcasted by dopamine neurons to the brain.

Odor coding in piriform cortex: mechanistic insights into distributed coding

Olfaction facilitates a large variety of animal behaviors such as feeding, mating, and communication. Recent work has begun to reveal the logic of odor transformations that occur throughout the olfactory system to form the odor percept. In this review, we describe the coding principles and mechanisms by which the piriform cortex and other olfactory areas encode three key odor features: odor identity, intensity, and valence. We argue that the piriform cortex produces a multiplexed odor code that allows non-interfering representations of distinct features of the odor stimulus to facilitate odor recognition and learning, which ultimately drives behavior.

Rapid Learning of Odor-Value Association in the Olfactory Striatum

Rodents can successfully learn multiple novel stimulus-response associations after only a few repetitions when the contingencies predict reward. The circuits modified during such reinforcement learning to support decision-making are not known, but the olfactory tubercle (OT) and posterior piriform cortex (pPC) are candidates for decoding reward category from olfactory sensory input and relaying this information to cognitive and motor areas. Through single-cell recordings in behaving male and female C57BL/6 mice, we show here that an explicit representation for reward category emerges in the OT within minutes of learning a novel odor-reward association, whereas the pPC lacks an explicit representation even after weeks of overtraining. The explicit reward category representation in OT is visible in the first sniff (50-100 ms) of an odor on each trial, and precedes the motor action. Together, these results suggest that the coding of stimulus information required for reward prediction does not occur within olfactory cortex, but rather in circuits involving the olfactory striatum.SIGNIFICANCE STATEMENT Rodents are olfactory specialists and can use odors to learn contingencies quickly and well. We have found that mice can readily learn to place multiple odors into rewarded and unrewarded categories. Once they have learned the rule, they can do such categorization in a matter of minutes (<10 trials). We found that neural activity in olfactory cortex largely reflects sensory coding, with very little explicit information about categories. By contrast, neural activity in a brain region in the ventral striatum is rapidly modified in a matter of minutes to reflect reward category. Our experiments set up a paradigm for studying rapid sensorimotor reinforcement in a circuit that is right at the interface of sensory input and reward areas.

Massively parallel microwire arrays integrated with CMOS chips for neural recording

Multi-channel electrical recordings of neural activity in the brain is an increasingly powerful method revealing new aspects of neural communication, computation, and prosthetics. However, while planar silicon-based CMOS devices in conventional electronics scale rapidly, neural interface devices have not kept pace. Here, we present a new strategy to interface silicon-based chips with three-dimensional microwire arrays, providing the link between rapidly-developing electronics and high density neural interfaces. The system consists of a bundle of microwires mated to large-scale microelectrode arrays, such as camera chips. This system has excellent recording performance, demonstrated via single unit and local-field potential recordings in isolated retina and in the motor cortex or striatum of awake moving mice. The modular design enables a variety of microwire types and sizes to be integrated with different types of pixel arrays, connecting the rapid progress of commercial multiplexing, digitisation and data acquisition hardware together with a three-dimensional neural interface.

The asynchronous state's relation to large-scale potentials in cortex

Understanding the relation between large-scale potentials (M/EEG) and their underlying neural activity can improve the precision of research and clinical diagnosis. Recent insights into cortical dynamics highlighted a state of strongly reduced spike count correlations, termed the asynchronous state (AS). The AS has received considerable attention from experimenters and theorists alike, regarding its implications for cortical dynamics and coding of information. However, how reconcilable are these vanishing correlations in the AS with large-scale potentials such as M/EEG observed in most experiments? Typically the latter are assumed to be based on underlying correlations in activity, in particular between subthreshold potentials. We survey the occurrence of the AS across brain states, regions, and layers and argue for a reconciliation of this seeming disparity: large-scale potentials are either observed, first, at transitions between cortical activity states, which entail transient changes in population firing rate, as well as during the AS, and, second, on the basis of sufficiently large, asynchronous populations that only need to exhibit weak correlations in activity. Cells with no or little spiking activity can contribute to large-scale potentials via their subthreshold currents, while they do not contribute to the estimation of spiking correlations, defining the AS. Furthermore, third, the AS occurs only within particular cortical regions and layers associated with the currently selected modality, allowing for correlations at other times and between other areas and layers.