Adaptive information processing of network modules to dynamic and spatial stimuli.
ABSTRACT: BACKGROUND:Adaptation and homeostasis are basic features of information processing in cells and seen in a broad range of contexts. Much of the current understanding of adaptation in network modules/motifs is based on their response to simple stimuli. Recently, there have also been studies of adaptation in dynamic stimuli. However a broader synthesis of how different circuits of adaptation function, and which circuits enable a broader adaptive behaviour in classes of more complex and spatial stimuli is largely missing. RESULTS:We study the response of a variety of adaptive circuits to time-varying stimuli such as ramps, periodic stimuli and static and dynamic spatial stimuli. We find that a variety of responses can be seen in ramp stimuli, making this a basis for discriminating between even similar circuits. We also find that a number of circuits adapt exactly to ramp stimuli, and dissect these circuits to pinpoint what characteristics (architecture, feedback, biochemical aspects, information processing ingredients) allow for this. These circuits include incoherent feedforward motifs, inflow-outflow motifs and transcritical circuits. We find that changes in location in such circuits where a signal acts can result in non-adaptive behaviour in ramps, even though the location was associated with exact adaptation in step stimuli. We also demonstrate that certain augmentations of basic inflow-outflow motifs can alter the behaviour of the circuit from exact adaptation to non-adaptive behaviour. When subject to periodic stimuli, some circuits (inflow-outflow motifs and transcritical circuits) are able to maintain an average output independent of the characteristics of the input. We build on this to examine the response of adaptive circuits to static and dynamic spatial stimuli. We demonstrate how certain circuits can exhibit a graded response in spatial static stimuli with an exact maintenance of the spatial mean-value. Distinct features which emerge from the consideration of dynamic spatial stimuli are also discussed. Finally, we also build on these results to show how different circuits which show any combination of presence or absence of exact adaptation in ramps, exact mainenance of time average output in periodic stimuli and exact maintenance of spatial average of output in static spatial stimuli may be realized. CONCLUSIONS:By studying a range of network circuits/motifs on one hand and a range of stimuli on the other, we isolate characteristics of these circuits (structural) which enable different degrees of exact adaptive and homeostatic behaviour in such stimuli, how they may be combined, and also identify cases associated with non-homeostatic behaviour. We also reveal constraints associated with locations where signals may act to enable homeostatic behaviour and constraints associated with augmentations of circuits. This consideration of multiple experimentally/naturally relevant stimuli along with circuits of adaptation of relevance in natural and engineered biology, provides a platform for deepening our understanding of adaptive and homeostatic behaviour in natural systems, bridging the gap between models of adaptation and experiments and in engineering homeostatic synthetic circuits.
Project description:Biological systems can maintain constant steady-state output despite variation in biochemical parameters, a property known as exact adaptation. Exact adaptation is achieved using integral feedback, an engineering strategy that ensures that the output of a system robustly tracks its desired value. However, it is unclear how physiological circuits also keep their output dynamics precise-including the amplitude and response time to a changing input. Such robustness is crucial for endocrine and neuronal homeostatic circuits because they need to provide a precise dynamic response in the face of wide variation in the physiological parameters of their target tissues; how such circuits compensate their dynamics for unavoidable natural fluctuations in parameters is unknown. Here, we present a design principle that provides the desired robustness, which we call dynamical compensation (DC). We present a class of circuits that show DC by means of a nonlinear feedback loop in which the regulated variable controls the functional mass of the controlling endocrine or neuronal tissue. This mechanism applies to the control of blood glucose by insulin and explains several experimental observations on insulin resistance. We provide evidence that this mechanism may also explain compensation and organ size control in other physiological circuits.
Project description:Neural circuits for appetites are regulated by both homeostatic perturbations and ingestive behaviour. However, the circuit organization that integrates these internal and external stimuli is unclear. Here we show in mice that excitatory neural populations in the lamina terminalis form a hierarchical circuit architecture to regulate thirst. Among them, nitric oxide synthase-expressing neurons in the median preoptic nucleus (MnPO) are essential for the integration of signals from the thirst-driving neurons of the subfornical organ (SFO). Conversely, a distinct inhibitory circuit, involving MnPO GABAergic neurons that express glucagon-like peptide 1 receptor (GLP1R), is activated immediately upon drinking and monosynaptically inhibits SFO thirst neurons. These responses are induced by the ingestion of fluids but not solids, and are time-locked to the onset and offset of drinking. Furthermore, loss-of-function manipulations of GLP1R-expressing MnPO neurons lead to a polydipsic, overdrinking phenotype. These neurons therefore facilitate rapid satiety of thirst by monitoring real-time fluid ingestion. Our study reveals dynamic thirst circuits that integrate the homeostatic-instinctive requirement for fluids and the consequent drinking behaviour to maintain internal water balance.
Project description:Neuronal circuits' ability to maintain the delicate balance between stability and flexibility in changing environments is critical for normal neuronal functioning. However, to what extent individual neurons and neuronal populations maintain internal firing properties remains largely unknown. In this study, we show that distributions of spontaneous population firing rates and synchrony are subject to accurate homeostatic control following increase of synaptic inhibition in cultured hippocampal networks. Reduction in firing rate triggered synaptic and intrinsic adaptive responses operating as global homeostatic mechanisms to maintain firing macro-stability, without achieving local homeostasis at the single-neuron level. Adaptive mechanisms, while stabilizing population firing properties, reduced short-term facilitation essential for synaptic discrimination of input patterns. Thus, invariant ongoing population dynamics emerge from intrinsically unstable activity patterns of individual neurons and synapses. The observed differences in the precision of homeostatic control at different spatial scales challenge cell-autonomous theory of network homeostasis and suggest the existence of network-wide regulation rules.
Project description:The integration of direct bottom-up inputs with contextual information is a core feature of neocortical circuits. In area V1, neurons may reduce their firing rates when their receptive field input can be predicted by spatial context. Gamma-synchronized (30-80 Hz) firing may provide a complementary signal to rates, reflecting stronger synchronization between neuronal populations receiving mutually predictable inputs. We show that large uniform surfaces, which have high spatial predictability, strongly suppressed firing yet induced prominent gamma synchronization in macaque V1, particularly when they were colored. Yet, chromatic mismatches between center and surround, breaking predictability, strongly reduced gamma synchronization while increasing firing rates. Differences between responses to different colors, including strong gamma-responses to red, arose from stimulus adaptation to a full-screen background, suggesting prominent differences in adaptation between M- and L-cone signaling pathways. Thus, synchrony signaled whether RF inputs were predicted from spatial context, while firing rates increased when stimuli were unpredicted from context.
Project description:Immune dysfunction is commonly associated with several neurological and mental disorders. Although the mechanisms by which peripheral immunity may influence neuronal function are largely unknown, recent findings implicate meningeal immunity influencing behaviour, such as spatial learning and memory. Here we show that meningeal immunity is also critical for social behaviour; mice deficient in adaptive immunity exhibit social deficits and hyper-connectivity of fronto-cortical brain regions. Associations between rodent transcriptomes from brain and cellular transcriptomes in response to T-cell-derived cytokines suggest a strong interaction between social behaviour and interferon-? (IFN-?)-driven responses. Concordantly, we demonstrate that inhibitory neurons respond to IFN-? and increase GABAergic (?-aminobutyric-acid) currents in projection neurons, suggesting that IFN-? is a molecular link between meningeal immunity and neural circuits recruited for social behaviour. Meta-analysis of the transcriptomes of a range of organisms reveals that rodents, fish, and flies elevate IFN-?/JAK-STAT-dependent gene signatures in a social context, suggesting that the IFN-? signalling pathway could mediate a co-evolutionary link between social/aggregation behaviour and an efficient anti-pathogen response. This study implicates adaptive immune dysfunction, in particular IFN-?, in disorders characterized by social dysfunction and suggests a co-evolutionary link between social behaviour and an anti-pathogen immune response driven by IFN-? signalling.
Project description:In recent years, a number of tools have become available for remotely activating neural circuits in Drosophila. Despite widespread and growing use, very little work has been done to characterize exactly how these tools affect activity in identified fly neurons. Using the GAL4-UAS system, we expressed blue light-gated Channelrhodopsin-2 (ChR2) and a mutated form of ChR2 (H134R-ChR2) in motor and sensory neurons of the Drosophila third-instar locomotor circuit. Neurons expressing H134R-ChR2 show enhanced responses to blue light pulses and less spike frequency adaptation than neurons expressing ChR2. Although H134R-ChR2 was more effective at manipulating behavior than ChR2, the behavioral consequences of firing rate adaptation were different in sensory and motor neurons. For comparison, we examined the effects of ectopic expression of the warmth-activated cation channel Drosophila TRPA1 (dTRPA1). When dTRPA1 was expressed in larval motor neurons, heat ramps from 21 to 27 degrees C evoked tonic spiking at approximately 25 degrees C that showed little adaptation over many minutes. dTRPA1 activation had stronger and longer-lasting effects on behavior than ChR2 variants. These results suggest that dTRPA1 may be particularly useful for researchers interested in activating fly neural circuits over long time scales. Overall, this work suggests that understanding the cellular effects of these genetic tools and their temporal dynamics is important for the design and interpretation of behavioral experiments.
Project description:The nervous system and the immune system are the principal sensory interfaces between the internal and external environment. They are responsible for recognizing, integrating, and responding to varied stimuli, and have the capacity to form memories of these encounters leading to learned or 'adaptive' future responses. We review current understanding of the cross-regulation between these systems. The autonomic and somatosensory nervous systems regulate both the development and deployment of immune cells, with broad functions that impact on hematopoiesis as well as on priming, migration, and cytokine production. In turn, specific immune cell subsets contribute to homeostatic neural circuits such as those controlling metabolism, hypertension, and the inflammatory reflex. We examine the contribution of the somatosensory system to autoimmune, autoinflammatory, allergic, and infectious processes in barrier tissues and, in this context, discuss opportunities for therapeutic manipulation of neuro-immune interactions.
Project description:The age at which gap detection becomes adultlike differs, depending on the stimulus characteristics. The present study evaluated whether the developmental trajectory differs as a function of stimulus frequency region or duration of the onset and offset ramps bounding the gap.Thresholds were obtained for wideband noise (500-4500 Hz) with 4- or 40-ms raised-cosine ramps and for a 25-Hz-wide low-fluctuation narrowband noise centered on either 500 or 5000 Hz with 40-ms ramps. Stimuli were played continuously at 70 dB SPL, and the task was to indicate which of 3 intervals contained a gap. Listeners were 5.2- to 15.1-year-old children (n = 40) and adults (n = 10) with normal hearing.Regardless of listener age, gap detection thresholds for the wideband noise tended to be lower when gaps were shaped using 4-ms rather than 40-ms ramps. Thresholds also tended to be lower for the low-fluctuation narrowband noise centered on 5000 Hz than 500 Hz. Performance reached adult levels after 11 years of age for all 4 stimuli. Maturation was not uniform across individuals, however; a subset of young children performed like adults, including some 5-year-olds.For these stimuli, the developmental trajectory was similar regardless of narrowband noise center frequency or wideband noise onset and offset ramp duration.
Project description:Investigating the complex systems dynamics of the aging process requires integration of a broad range of cellular processes describing damage and functional decline co-existing with adaptive and protective regulatory mechanisms. We evolve an integrated generic cell network to represent the connectivity of key cellular mechanisms structured into positive and negative feedback loop motifs centrally important for aging. The conceptual network is casted into a fuzzy-logic, hybrid-intelligent framework based on interaction rules assembled from a priori knowledge. Based upon a classical homeostatic representation of cellular energy metabolism, we first demonstrate how positive-feedback loops accelerate damage and decline consistent with a vicious cycle. This model is iteratively extended towards an adaptive response model by incorporating protective negative-feedback loop circuits. Time-lapse simulations of the adaptive response model uncover how transcriptional and translational changes, mediated by stress sensors NF-kappaB and mTOR, counteract accumulating damage and dysfunction by modulating mitochondrial respiration, metabolic fluxes, biosynthesis, and autophagy, crucial for cellular survival. The model allows consideration of lifespan optimization scenarios with respect to fitness criteria using a sensitivity analysis. Our work establishes a novel extendable and scalable computational approach capable to connect tractable molecular mechanisms with cellular network dynamics underlying the emerging aging phenotype.
Project description:Visual perception is affected by spatial context. In visual cortex, neuronal responses to stimuli inside the receptive field (RF) are suppressed by stimuli in the RF surround. To understand the circuits and cortical layers processing spatial context, we simultaneously recorded across all layers of macaque primary visual cortex while presenting stimuli at increasing distances from the recorded cells' RF. We find that near versus far-surround stimuli activate distinct layers, thus revealing unique laminar contributions to the processing of local and global spatial context. Stimuli in the near-surround evoke the earliest subthreshold responses in superficial and upper-deep layers, and earliest suppression of spiking responses in superficial layers. Conversely, far-surround stimuli evoke the earliest subthreshold responses in feedback-recipient layer 1 and lower-deep layers, and earliest suppression of spiking responses almost simultaneously in all layers, except 4C, where suppression emerges last. Our results suggest distinct circuits for local and global signal integration.