Psychophysical properties of odor processing can be quantitatively described by relative action potential latency patterns in mitral and tufted cells

Electrophysiological and population imaging data in rodents show that olfactory bulb (OB) activity is profoundly modulated by the odor sampling process while behavioral experiments indicate that odor discrimination can occur within a single sniff. This paper addresses the question of whether action potential (AP) latencies occurring across the mitral and tufted cell (M/TC) population within an individual sampling cycle could account for the psychophysical properties of odor processing. To determine this we created an OB model (50,000 M/TCs) exhibiting hallmarks of published in vivo properties and used a template-matching algorithm to assess stimulus separation. Such an AP latency-based scheme showed high reproducibility and sensitivity such that odor stimuli could be reliably separated independent of concentration. As in behavioral experiments we found that very dissimilar odors (“A vs. B”) were accurately and rapidly discerned while very similar odors (binary mixtures, 0.4A/0.6B vs. 0.6A/0.4B) required up to 90 ms longer. As in lesion studies we find that AP latency-based representation is rather insensitive to disruption of large regions of the OB. The AP latency-based scheme described here, therefore, captures both temporal and psychophysical properties of olfactory processing and suggests that the onset patterns of M/TC activity in the OB represent stimulus specific features of olfactory stimuli

Sparse connectivity for MAP inference in linear models using sister mitral cells

Sensory processing is hard because the variables of interest are encoded in spike trains in a relatively complex way. A major goal in studies of sensory processing is to understand how the brain extracts those variables. Here we revisit a common encoding model in which variables are encoded linearly. Although there are typically more variables than neurons, this problem is still solvable because only a small number of variables appear at any one time (sparse prior). However, previous solutions require all-to-all connectivity, inconsistent with the sparse connectivity seen in the brain. Here we propose an algorithm that provably reaches the MAP (maximum a posteriori) inference solution, but does so using sparse connectivity. Our algorithm is inspired by the circuit of the mouse olfactory bulb, but our approach is general enough to apply to other modalities. In addition, it should be possible to extend it to nonlinear encoding models

Coupling of Mouse Olfactory Bulb Projection Neurons to Fluctuating Odor Pulses

Odours are transported by turbulent air currents, creating complex temporal fluctuations in odour concentration that provide a potentially informative stimulus dimension. Recently, we have shown that mice are able to discriminate odour stimuli based on their temporal structure, indicating that information contained in the temporal structure of odour plumes can be extracted by the mouse olfactory system. Here, using in vivo extra- and intracellular electrophysiological recordings, we show that mitral and tufted cells (M/TCs) of the male C57BL/6 mouse olfactory bulb can encode the dominant temporal frequencies present in odour stimuli up to at least 20 Hz. A substantial population of cell-odour pairs showed significant coupling of their subthreshold membrane potential with the odour stimulus at both 2Hz (29/70) and the supra-sniff frequency 20Hz (24/70). Furthermore, M/TCs show differential coupling of their membrane potential to odour concentration fluctuations with tufted cells coupling more strongly for the 20Hz stimulation. Frequency coupling was always observed to be invariant to odour identity and M/TCs that coupled well to a mixture also coupled to at least one of the components of the mixture. Interestingly, pharmacological blocking of the inhibitory circuitry strongly modulated frequency coupling of cell-odour pairs at both 2Hz (10/15) and 20Hz (9/15). These results provide insight into how both cellular and circuit properties contribute to the encoding of temporal odour features in the mouse olfactory bulb.SIGNIFICANCE STATEMENTOdours in the natural environment have a strong temporal structure which can be extracted and used by mice in their behaviour. Here, using in vivo extra- and intracellular electrophysiological techniques, we show that the projection neurons in the olfactory bulb can encode and couple to the dominant frequency present in an odour stimulus. Furthermore, frequency coupling was observed to be differential between mitral and tufted cells, was odour-invariant but strongly modulated by local inhibitory circuits. In summary, this study provides insight into how both cellular and circuit properties modulate encoding of odour temporal features in the mouse olfactory bulb

Endogenous enforcement of intellectual property, North-South trade, and growth

Now that most countries have harmonized intellectual property right (IPR) legislation as a consequence of signing the Agreement on Trade-Related Aspects of Intellectual Property Rights (TRIPs), the dispute about the optimal level of IPR protection has shifted toward IPR enforcement. This paper develops an endogenous growth framework with two open economies satisfying the classical North–South assumptions to study (a) the regions' incentives to enforce IPRs in a decentralized game, (b) the desired IPR enforcement of the two regions in negotiation rounds on global harmonization, and (c) the constrained efficient enforcement level. We show how the different solutions relate to each other and how the results depend on the research productivity in the North and the regions' relative market sizes. Although growth rates increase substantially when IPR enforcement is harmonized at the North's desired level, our numerical simulation suggests that the South may also benefit in terms of long-run welfare.</jats:p

Rapid task-dependent tuning of the mouse olfactory bulb

Adapting neural representation to rapidly changing behavioural demands is a key challenge for the nervous system. Here, we demonstrate that the output of the primary olfactory area of the mouse, the olfactory bulb, is already a target of dynamic and reproducible modulation. The modulation depends on the stimulus tuning of a given neuron, making olfactory responses more discriminable through selective amplification in a demand-specific way

Sample Preparation and Warping Accuracy for Correlative Multimodal Imaging in the Mouse Olfactory Bulb Using 2-Photon, Synchrotron X-Ray and Volume Electron Microscopy

Integrating physiology with structural insights of the same neuronal circuit provides a unique approach to understanding how the mammalian brain computes information. However, combining the techniques that provide both streams of data represents an experimental challenge. When studying glomerular column circuits in the mouse olfactory bulb, this approach involves e.g., recording the neuronal activity with in vivo 2-photon (2P) calcium imaging, retrieving the circuit structure with synchrotron X-ray computed tomography with propagation-based phase contrast (SXRT) and/or serial block-face scanning electron microscopy (SBEM) and correlating these datasets. Sample preparation and dataset correlation are two key bottlenecks in this correlative workflow. Here, we first quantify the occurrence of different artefacts when staining tissue slices with heavy metals to generate X-ray or electron contrast. We report improvements in the staining procedure, ultimately achieving perfect staining in ∼67% of the 0.6 mm thick olfactory bulb slices that were previously imaged in vivo with 2P. Secondly, we characterise the accuracy of the spatial correlation between functional and structural datasets. We demonstrate that direct, single-cell precise correlation between in vivo 2P and SXRT tissue volumes is possible and as reliable as correlating between 2P and SBEM. Altogether, these results pave the way for experiments that require retrieving physiology, circuit structure and synaptic signatures in targeted regions. These correlative function-structure studies will bring a more complete understanding of mammalian olfactory processing across spatial scales and time

Respiration-Locking of Olfactory Receptor and Projection Neurons in the Mouse Olfactory Bulb and Its Modulation by Brain State

For sensory systems of the brain, the dynamics of an animal’s own sampling behavior has a direct consequence on ensuing computations. This is particularly the case for mammalian olfaction, where a rhythmic flow of air over the nasal epithelium entrains activity in olfactory system neurons in a phenomenon known as sniff-locking. Parameters of sniffing can, however, change drastically with brain states. Coupled to the fact that different observation methods have different kinetics, consensus on the sniff-locking properties of neurons is lacking. To address this, we investigated the sniff-related activity of olfactory sensory neurons (OSNs), as well as the principal neurons of the olfactory bulb (OB), using 2-photon calcium imaging and intracellular whole-cell patch-clamp recordings in vivo, both in anesthetized and awake mice. Our results indicate that OSNs and OB output neurons lock robustly to the sniff rhythm, but with a slight temporal shift between behavioral states. We also observed a slight delay between methods. Further, the divergent sniff-locking by tufted cells (TCs) and mitral cells (MCs) in the absence of odor can be used to determine the cell type reliably using a simple linear classifier. Using this classification on datasets where morphological identification is unavailable, we find that MCs use a wider range of temporal shifts to encode odors than previously thought, while TCs have a constrained timing of activation due to an early-onset hyperpolarization. We conclude that the sniff rhythm serves as a fundamental rhythm but its impact on odor encoding depends on cell type, and this difference is accentuated in awake mice

Neurosurgical team acceptability of brain-computer interfaces: a two-stage international cross-sectional survey

OBJECTIVE: Invasive brain-computer interfaces (BCIs) require neurosurgical implantation, which confers a range of risks. Despite this, no studies have assessed the acceptability of invasive BCIs amongst the neurosurgical team. This study aims to establish baseline knowledge of BCIs within the neurosurgical team and identify attitudes towards different applications of invasive BCI. METHOD: A two-stage cross-sectional international survey of the neurosurgical team (neurosurgeons, anaesthetists, and operating room nurses) was conducted. Results from the first, qualitative, survey were used to guide the second stage quantitative survey, which assessed acceptability of invasive BCI applications. 5-part Likert Scales were used to collect quantitative data. Surveys were distributed internationally via social media and collaborators. RESULTS: 108 qualitative responses were collected. Themes included the promise of BCIs positively impacting disease targets, concerns regarding stability, and an overall positive emotional reaction to BCI technology. The quantitative survey generated 538 responses from 32 countries. Baseline knowledge of BCI technology was poor, with 9% claiming to have a ‘good’ or ‘expert’ knowledge of BCIs. Acceptability of invasive BCI for rehabilitative purposes was >80%. Invasive BCI for augmentation in healthy populations divided opinion. CONCLUSION: The neurosurgical team’s view of the acceptability of BCI was divided across a range of indications. Some applications (for example stroke rehabilitation) were viewed as more appropriate than other applications (such as augmentation for military use). This range in views highlights the need for stakeholder consultation on acceptable use cases along with regulation and guidance to govern initial BCI implantations if patients are to realise the potential benefits

Silicon Valley new focus on brain computer interface: hype or hope for new applications? [version 1; referees: 2 approved, 1 approved with reservations]

In the last year there has been increasing interest and investment into developing devices to interact with the central nervous system, in particular developing a robust brain-computer interface (BCI). In this article, we review the most recent research advances and the current host of engineering and neurological challenges that must be overcome for clinical application. In particular, space limitations, isolation of targeted structures, replacement of probes following failure, delivery of nanomaterials and processing and understanding recorded data. Neural engineering has developed greatly over the past half-century, which has allowed for the development of better neural recording techniques and clinical translation of neural interfaces. Implementation of general purpose BCIs face a number of constraints arising from engineering, computational, ethical and neuroscientific factors that still have to be addressed. Electronics have become orders of magnitude smaller and computationally faster than neurons, however there is much work to be done in decoding the neural circuits. New interest and funding from the non-medical community may be a welcome catalyst for focused research and development; playing an important role in future advancements in the neuroscience community