Faculty Bibliography

Olfactory systems encode odours by which neurons respond and by when they respond. In mammals, every sniff evokes a precise, odour-specific sequence of activity across olfactory neurons. Likewise, in a variety of neural systems, ranging from sensory periphery to cognitive centres, neuronal activity is timed relative to sampling behaviour and/or internally generated oscillations. As in these neural systems, relative timing of activity may represent information in the olfactory system. However, there is no evidence that mammalian olfactory systems read such cues. To test whether mice perceive the timing of olfactory activation relative to the sniff cycle ('sniff phase'), we used optogenetics in gene-targeted mice to generate spatially constant, temporally controllable olfactory input. Here we show that mice can behaviourally report the sniff phase of optogenetically driven activation of olfactory sensory neurons. Furthermore, mice can discriminate between light-evoked inputs that are shifted in the sniff cycle by as little as 10 milliseconds, which is similar to the temporal precision of olfactory bulb odour responses. Electrophysiological recordings in the olfactory bulb of awake mice show that individual cells encode the timing of photoactivation in relation to the sniff in both the timing and the amplitude of their responses. Our work provides evidence that the mammalian olfactory system can read temporal patterns, and suggests that timing of activity relative to sampling behaviour is a potent cue that may enable accurate olfactory percepts to form quickly.

The ability of human subjects to choose between disparate kinds of rewards suggests that the neural circuits for valuing different reward types must converge. Economic theory suggests that these convergence points represent the subjective values (SVs) of different reward types on a common scale for comparison. To examine these hypotheses and to map the neural circuits for reward valuation we had food and water-deprived subjects make risky choices for money, food, and water both in and out of a brain scanner. We found that risk preferences across reward types were highly correlated; the level of risk aversion an individual showed when choosing among monetary lotteries predicted their risk aversion toward food and water. We also found that partially distinct neural networks represent the SVs of monetary and food rewards and that these distinct networks showed specific convergence points. The hypothalamic region mainly represented the SV for food, and the posterior cingulate cortex mainly represented the SV for money. In both the ventromedial prefrontal cortex (vmPFC) and striatum there was a common area representing the SV of both reward types, but only the vmPFC significantly represented the SVs of money and food on a common scale appropriate for choice in our data set. A correlation analysis demonstrated interactions across money and food valuation areas and the common areas in the vmPFC and striatum. This may suggest that partially distinct valuation networks for different reward types converge on a unified valuation network, which enables a direct comparison between different reward types and hence guides valuation and choice.

During light slow-wave sleep, the thalamo-cortical network oscillates in waxing-and-waning patterns at about 7 to 14 Hz and lasting for 500 ms to 3 s, called spindles, with the thalamus rhythmically sending strong excitatory volleys to the cortex. Concurrently, the hippocampal activity is characterized by transient and strong excitatory events, Sharp-Waves-Ripples (SPWRs), directly affecting neocortical activity--in particular the medial prefrontal cortex (mPFC)--which receives monosynaptic fibers from the ventral hippocampus and subiculum. Both spindles and SPWRs have been shown to be strongly involved in memory consolidation. However, the dynamics of the cortical network during natural sleep spindles and how prefrontal circuits simultaneously process hippocampal and thalamo-cortical activity remain largely undetermined. Using multisite neuronal recordings in rat mPFC, we show that during sleep spindles, oscillatory responses of cortical cells are different for different cell types and cortical layers. Superficial neurons are more phase-locked and tonically recruited during spindle episodes. Moreover, in a given layer, interneurons were always more modulated than pyramidal cells, both in firing rate and phase, suggesting that the dynamics are dominated by inhibition. In the deep layers, where most of the hippocampal fibers make contacts, pyramidal cells respond phasically to SPWRs, but not during spindles. Similar observations were obtained when analyzing gamma-oscillation modulation in the mPFC. These results demonstrate that during sleep spindles, the cortex is functionnaly "deafferented" from its hippocampal inputs, based on processes of cortical origin, and presumably mediated by the strong recruitment of inhibitory interneurons. The interplay between hippocampal and thalamic inputs may underlie a global mechanism involved in the consolidation of recently formed memory traces.

Sensory systems with high discriminatory power use neurons that express only one of several alternative sensory receptor proteins. This exclusive receptor gene expression restricts the sensitivity spectrum of neurons and is coordinated with the choice of their synaptic targets. However, little is known about how it is maintained throughout the life of a neuron. Here we show that the green-light sensing receptor rhodopsin 6 (Rh6) acts to exclude an alternative blue-sensitive rhodopsin 5 (Rh5) from a subset of Drosophila R8 photoreceptor neurons. Loss of Rh6 leads to a gradual expansion of Rh5 expression into all R8 photoreceptors of the ageing adult retina. The Rh6 feedback signal results in repression of the rh5 promoter and can be mimicked by other Drosophila rhodopsins; it is partly dependent on activation of rhodopsin by light, and relies on G(alphaq) activity, but not on the subsequent steps of the phototransduction cascade. Our observations reveal a thus far unappreciated spectral plasticity of R8 photoreceptors, and identify rhodopsin feedback as an exclusion mechanism.

Mitral/tufted cells of the olfactory bulb receive odorant information from receptor neurons and transmit this information to the cortex. Studies in awake behaving animals have found that sustained responses of mitral cells to odorants are rare, suggesting sparse combinatorial representation of the odorants. Careful alignment of mitral cell firing with the phase of the respiration cycle revealed brief transient activity in the larger population of mitral cells, which respond to odorants during a small fraction of the respiration cycle. Responses of these cells are therefore temporally sparse. Here, we propose a mathematical model for the olfactory bulb network that can reproduce both combinatorially and temporally sparse mitral cell codes. We argue that sparse codes emerge as a result of the balance between mitral cells' excitatory inputs and inhibition provided by the granule cells. Our model suggests functional significance for the dendrodendritic synapses mediating interactions between mitral and granule cells.

Network oscillations support transient communication across brain structures. We show here, in rats, that task-related neuronal activity in the medial prefrontal cortex (PFC), the hippocampus, and the ventral tegmental area (VTA), regions critical for working memory, is coordinated by a 4 Hz oscillation. A prominent increase of power and coherence of the 4 Hz oscillation in the PFC and the VTA and its phase modulation of gamma power in both structures was present in the working memory part of the task. Subsets of both PFC and hippocampal neurons predicted the turn choices of the rat. The goal-predicting PFC pyramidal neurons were more strongly phase locked to both 4 Hz and hippocampal theta oscillations than nonpredicting cells. The 4 Hz and theta oscillations were phase coupled and jointly modulated both gamma waves and neuronal spikes in the PFC, the VTA, and the hippocampus. Thus, multiplexed timing mechanisms in the PFC-VTA-hippocampus axis may support processing of information, including working memory

BDNF is produced from many transcripts that display distinct subcellular localization, suggesting that spatially restricted effects occur as a function of genetic and physiological regulation. Different BDNF 5' splice variants give a restricted localization in the cell body or the proximal and distal compartments of dendrites; however, the functional consequences are not known. Silencing individual endogenous transcripts or overexpressing BDNF-GFP transcripts in cultured neurons demonstrated that whereas some transcripts (1 and 4) selectively affected proximal dendrites, others (2C and 6) affected distal dendrites. Moreover, segregation of BDNF transcripts resulted in a highly selective activation of the BDNF TrkB receptor. These studies indicate that spatial segregation of BDNF transcripts enables BDNF to differentially shape distinct dendritic compartments

The extracellular space (ECS) consists of the narrow channels between brain cells together with their geometrical configuration and contents. Despite being only 20-60 nm in width, the ECS typically occupies 20% of the brain volume. Numerous experiments over the last 50 years have established that molecules moving through the ECS obey the laws of diffusion but with an effective diffusion coefficient reduced by a factor of about 2.6 compared to free diffusion. This review considers the origins of the diffusion barrier arising from the ECS and its properties. The paper presents a brief overview of software for implementing two point-source paradigms for measurements of localized diffusion properties: the real-time iontophoresis or pressure method for small ions and the integrative optical imaging method for macromolecules. Selected results are presented. This is followed by a discussion of the application of the MCell Monte Carlo simulation program to determining the importance of geometrical constraints, especially dead-space microdomains, and the possible role of interaction with the extracellular matrix. It is concluded that we can predict the impediment to diffusion of many molecules of practical importance and also use studies of the diffusion of selected molecular probes to reveal the barrier properties of the ECS.

We consider the problem of decomposing a signal into a linear combination of features, each a continuously translated version of one of a small set of elementary features. Although these constituents are drawn from a continuous family, most current signal decomposition methods rely on a finite dictionary of discrete examples selected from this family (e.g., shifted copies of a set of basic waveforms), and apply sparse optimization methods to select and solve for the relevant coefficients. Here, we generate a dictionary that includes auxiliary interpolation functions that approximate translates of features via adjustment of their coefficients. We formulate a constrained convex optimization problem, in which the full set of dictionary coefficients represents a linear approximation of the signal, the auxiliary coefficients are constrained so as to only represent translated features, and sparsity is imposed on the primary coefficients using an L1 penalty. The basis pursuit denoising (BP) method may be seen as a special case, in which the auxiliary interpolation functions are omitted, and we thus refer to our methodology as continuous basis pursuit (CBP). We develop two implementations of CBP for a one-dimensional translation-invariant source, one using a first-order Taylor approximation, and another using a form of trigonometric spline. We examine the tradeoff between sparsity and signal reconstruction accuracy in these methods, demonstrating empirically that trigonometric CBP substantially outperforms Taylor CBP, which in turn offers substantial gains over ordinary BP. In addition, the CBP bases can generally achieve equally good or better approximations with much coarser sampling than BP, leading to a reduction in dictionary dimensionality.

Objective: Individuals with ADHD are often characterized as inconsistent across many contexts. ADHD is also associated with deficits in executive function. We examined the relationships between response time (RT) variability on five brief computer tasks to parents' ratings of ADHD-related features and executive function in a group of children with a broad range of ADHD symptoms from none to full diagnosis. Methods: We tested 98 children (mean age 9.9 +/- 1.4 years; 66 boys) from community clinics on short tasks of executive control (TEC) and the Eriksen Flanker task, while a parent completed the Conners' Parent Rating Scale and Behavior Rating Inventory of Executive Function. Results: Variability for two of the TEC tasks explained significant proportions of the variance of all five ADHD-related Conners' subscales and several executive function subscales. By contrast, variability on the flanker task or mean RTs for any task were not associated with any rating scale. Conclusion: The significant dimensional relationships observed between variability measures and parent ratings supported the utility of RT variability as an objective measure in ADHD and aspects of executive functioning that is superior to RT means or accuracy measures