Coding and learning of chemosensor array patterns in a neurodynamic model of the olfactory system

Arrays of broadly-selective chemical sensors, also known as electronic noses, have been developed during the past two decades as a low-cost and high-throughput alternative to analytical instruments for the measurement of odorant chemicals. Signal processing in these gas-sensor arrays has been traditionally performed by means of statistical and neural pattern recognition techniques. The objective of this dissertation is to develop new computational models to process gas sensor array signals inspired by coding and learning mechanisms of the biological olfactory system. We have used a neurodynamic model of the olfactory system, the KIII, to develop and demonstrate four odor processing computational functions: robust recovery of overlapping patterns, contrast enhancement, background suppression, and novelty detection. First, a coding mechanism based on the synchrony of neural oscillations is used to extract information from the associative memory of the KIII model. This temporal code allows the KIII to recall overlapping patterns in a robust manner. Second, a new learning rule that combines Hebbian and anti-Hebbian terms is proposed. This learning rule is shown to achieve contrast enhancement on gas-sensor array patterns. Third, a new local learning mechanism based on habituation is proposed to perform odor background suppression. Combining the Hebbian/anti-Hebbian rule and the local habituation mechanism, the KIII is able to suppress the response to continuously presented odors, facilitating the detection of the new ones. Finally, a new learning mechanism based on anti-Hebbian learning is proposed to perform novelty detection. This learning mechanism allows the KIII to detect the introduction of new odors even in the presence of strong backgrounds. The four computational models are characterized with synthetic data and validated on gas sensor array patterns obtained from an e-nose prototype developed for this purpose

Oscillatory architecture of memory circuits

The coordinated activity between remote brain regions underlies cognition and memory function. Although neuronal oscillations have been proposed as a mechanistic substrate for the coordination of information transfer and memory consolidation during sleep, little is known about the mechanisms that support the widespread synchronization of brain regions and the relationship of neuronal dynamics with other bodily rhythms, such as breathing. During exploratory behavior, the hippocampus and the prefrontal cortex are organized by theta oscillations, known to support memory encoding and retrieval, while during sleep the same structures are dominated by slow oscillations that are believed to underlie the consolidation of recent experiences. The expression of conditioned fear and extinction memories relies on the coordinated activity between the mPFC and the basolateral amygdala (BLA), a neuronal structure encoding associative fear memories. However, to date, the mechanisms allowing this long-range network synchronization of neuronal activity between the mPFC and BLA during fear behavior remain virtually unknown. Using a combination of extracellular recordings and open- and closed-loop optogenetic manipulations, we investigated the oscillatory and coding mechanisms mediating the organization and coupling of the limbic circuit in the awake and asleep brain, as well as during memory encoding and retrieval. We found that freezing, a behavioral expression of fear, is tightly associated with an internally generated brain state that manifests in sustained 4Hz oscillatory dynamics in prefrontal-amygdala circuits. 4Hz oscillations accurately predict the onset and termination of the freezing state. These oscillations synchronize prefrontal-amygdala circuits and entrain neuronal activity to dynamically regulate the development of neuronal ensembles. This enables the precise timing of information transfer between the two structures and the expression of fear responses. Optogenetic induction of prefrontal 4Hz oscillations promotes freezing behavior and the formation of long-lasting fear memory, while closed-loop phase specific manipulations bidirectionally modulate fear expression. Our results unravel a physiological signature of fear memory and identify a novel internally generated brain state, characterized by 4Hz oscillations. This oscillation enables the temporal coordination and information transfer in the prefrontal-amygdala circuit via a phase-specific coding mechanism, facilitating the encoding and expression of fear memory. In the search for the origin of this oscillation, we focused our attention on breathing, the most fundamental and ubiquitous rhythmic activity in life. Using large-scale extracellular recordings from a number of structures, including the medial prefrontal cortex, hippocampus, thalamus, amygdala and nucleus accumbens in mice we identified and characterized the entrainment by breathing of a host of network dynamics across the limbic circuit. We established that fear-related 4Hz oscillations are a state-specific manifestation of this cortical entrainment by the respiratory rhythm. We characterized the translaminar and transregional profile of this entrainment and demonstrated a causal role of breathing in synchronizing neuronal activity and network dynamics between these structures in a variety of behavioral scenarios in the awake and sleep state. We further revealed a dual mechanism of respiratory entrainment, in the form of an intracerebral corollary discharge that acts jointly with an olfactory reafference to coordinate limbic network dynamics, such as hippocampal ripples and cortical UP and DOWN states, involved in memory consolidation. Respiration provides a perennial stream of rhythmic input to the brain. In addition to its role as the condicio sine qua non for life, here we provide evidence that breathing rhythm acts as a global pacemaker for the brain, providing a reference signal that enables the integration of exteroceptive and interoceptive inputs with the internally generated dynamics of the hippocampus and the neocortex. Our results highlight breathing, a perennial rhythmic input to the brain, as an oscillatory scaffold for the functional coordination of the limbic circuit, enabling the segregation and integration of information flow across neuronal networks

Olfactory bulb coding and odor discrimination.

Olfactory system second-order neurons, mitral-tufted cells, have odorant receptive fields (ORFs) (molecular receptive ranges in odorant space for carbon chain length in organic odorant molecules). This study quantified several dimensions of these excitatory odorant receptive fields to novel odorants in rats and then examined the effects of passive odorant exposure on the shape of the ORF-tuning curve. ORFs for carbon chain length of novel ethyl esters (pure odorants that the animals had not been exposed to previously) were determined before and after a 50 sec prolonged exposure to one of the odorants. In response to novel odorants, quantitative analysis of mitral-tufted cell excitatory ORFs revealed that the median ORF width spanned 3--4 carbons, generally with a single-most excitatory odorant. Exposure to either the most excitatory odorant (ON-PEAK) or an odorant that was two carbons longer (OFF-PEAK) for 50 sec produced whole ORF suppression immediately after the end of the prolonged exposure, with the ON-PEAK exposure producing the greatest suppression. These results are consistent with a feature-detecting function for mitral-tufted cells. Redetermination of the ORF 15 and 60 min after the exposure revealed that OFF-PEAK exposure produced a reduction in responsiveness to the best odorant and an increase in responsiveness to the exposed odorant. In contrast, exposure to the ON-PEAK odorant or no odorant did not affect ORFs. Given that mitral-tufted cells receive exclusively excitatory input from olfactory receptor neurons expressing identical receptor proteins, it is hypothesized that experience-induced mitral-tufted cell ORF changes reflect modulation of lateral and centrifugal olfactory bulb circuits

Olfactory consciousness across disciplines

Our sense of smell pervasively influences our most common behaviors and daily experience, yet little is known about olfactory consciousness. Over the past decade and a half research in both the fields of Consciousness Studies and Olfaction has blossomed, however, olfactory consciousness has received little to no attention. The olfactory systems unique anatomy, functional organization, sensory processes, and perceptual experiences offers a fecund area for exploring all aspects of consciousness, as well as a external perspective for re-examining the assumptions of contemporary theories of consciousness. It has even been suggested that the olfactory system may represent the minimal neuroanatomy that is required for conscious processing. Given the variegated nature of research on consciousness, we include original papers concerning the nature of olfactory consciousness. The scope of the special edition widely incorporates olfaction as it relates to Consciousness, Awareness, Attention, Phenomenal- or Access-Consciousness, and Qualia. Research concerning olfaction and cross-modal integration as it relates to conscious experience is also address. As the initial foray into this uncharted area of research, we include contributions from across all disciplines contributing to cognitive neuroscience, including neurobiology, neurology, psychology, philosophy, linguistics, and computer sciences. It is our hope that this Research Topic will serve as the impetus for future interdisciplinary research on olfaction and consciousness

25th Annual Computational Neuroscience Meeting: CNS-2016

Abstracts of the 25th Annual Computational Neuroscience Meeting: CNS-2016 Seogwipo City, Jeju-do, South Korea. 2–7 July 201

25th annual computational neuroscience meeting: CNS-2016

The same neuron may play different functional roles in the neural circuits to which it belongs. For example, neurons in the Tritonia pedal ganglia may participate in variable phases of the swim motor rhythms [1]. While such neuronal functional variability is likely to play a major role the delivery of the functionality of neural systems, it is difficult to study it in most nervous systems. We work on the pyloric rhythm network of the crustacean stomatogastric ganglion (STG) [2]. Typically network models of the STG treat neurons of the same functional type as a single model neuron (e.g. PD neurons), assuming the same conductance parameters for these neurons and implying their synchronous firing [3, 4]. However, simultaneous recording of PD neurons shows differences between the timings of spikes of these neurons. This may indicate functional variability of these neurons. Here we modelled separately the two PD neurons of the STG in a multi-neuron model of the pyloric network. Our neuron models comply with known correlations between conductance parameters of ionic currents. Our results reproduce the experimental finding of increasing spike time distance between spikes originating from the two model PD neurons during their synchronised burst phase. The PD neuron with the larger calcium conductance generates its spikes before the other PD neuron. Larger potassium conductance values in the follower neuron imply longer delays between spikes, see Fig. 17.Neuromodulators change the conductance parameters of neurons and maintain the ratios of these parameters [5]. Our results show that such changes may shift the individual contribution of two PD neurons to the PD-phase of the pyloric rhythm altering their functionality within this rhythm. Our work paves the way towards an accessible experimental and computational framework for the analysis of the mechanisms and impact of functional variability of neurons within the neural circuits to which they belong

The neural circuit basis of learning

The astounding capacity for learning ranks among the nervous system’s most impressive features. This thesis comprises studies employing varied approaches to improve understanding, at the level of neural circuits, of the brain’s capacity for learning. The first part of the thesis contains investigations of hippocampal circuitry – both theoretical work and experimental work in the mouse Mus musculus – as a model system for declarative memory. To begin, Chapter 2 presents a theory of hippocampal memory storage and retrieval that reflects nonlinear dendritic processing within hippocampal pyramidal neurons. As a prelude to the experimental work that comprises the remainder of this part, Chapter 3 describes an open source software platform that we have developed for analysis of data acquired with in vivo Ca2+ imaging, the main experimental technique used throughout the remainder of this part of the thesis. As a first application of this technique, Chapter 4 characterizes the content of signaling at synapses between GABAergic neurons of the medial septum and interneurons in stratum oriens of hippocampal area CA1. Chapter 5 then combines these techniques with optogenetic, pharmacogenetic, and pharmacological manipulations to uncover inhibitory circuit mechanisms underlying fear learning. The second part of this thesis focuses on the cerebellum-like electrosensory lobe in the weakly electric mormyrid fish Gnathonemus petersii, as a model system for non-declarative memory. In Chapter 6, we study how short-duration EOD motor commands are recoded into a complex temporal basis in the granule cell layer, which can be used to cancel Purkinje-like cell firing to the longer duration and temporally varying EOD-driven sensory responses. In Chapter 7, we consider not only the temporal aspects of the granule cell code, but also the encoding of body position provided from proprioceptive and efference copy sources. Together these studies clarify how the cerebellum-like circuitry of the electrosensory lobe combines information of different forms and then uses this combined information to predict the complex dependence of sensory responses on body position and timing relative to electric organ discharge