53 research outputs found
Author response: Synaptic input sequence discrimination on behavioral timescales mediated by reaction-diffusion chemistry in dendrites
No full textSynaptic input sequence discrimination on behavioral timescales mediated by reaction-diffusion chemistry in dendrites
No full textSequences of events are ubiquitous in sensory, motor, and cognitive function. Key computational operations, including pattern recognition, event prediction, and plasticity, involve neural discrimination of spatio-temporal sequences. Here, we show that synaptically-driven reaction-diffusion pathways on dendrites can perform sequence discrimination on behaviorally relevant time-scales. We used abstract signaling models to show that selectivity arises when inputs at successive locations are aligned with, and amplified by, propagating chemical waves triggered by previous inputs. We incorporated biological detail using sequential synaptic input onto spines in morphologically, electrically, and chemically detailed pyramidal neuronal models based on rat data. Again, sequences were recognized, and local channel modulation downstream of putative sequence-triggered signaling could elicit changes in neuronal firing. We predict that dendritic sequence-recognition zones occupy 5 to 30 microns and recognize time-intervals of 0.2 to 5 s. We suggest that this mechanism provides highly parallel and selective neural computation in a functionally important time range.</jats:p
Trafficking Motifs as the Basis for Two-Compartment Signaling Systems to Form Multiple Stable States
No full textAbstractTransport of molecules in cells is a central part of cell biology. Frequently such trafficking is not just for material transport, but also for information propagation, and serves to couple signaling circuits across cellular compartments. Here, I show that trafficking transforms simple local signaling pathways into self-organizing systems that span compartments and confer distinct states and identities to these compartments. I find that three motifs encapsulate the responses of most single-compartment signaling pathways in the context of trafficking. These motifs combine with different trafficking reactions to generate a diverse set of cellular functions. For example, trafficked bistable switches can oscillate or become quad- or tristable, depending on trafficking mechanisms and rates. Furthermore, the analysis shows how compartments participating in traffic can settle to distinct molecular compositions characteristic of distinct organelle identities. This general framework shows how the interplay between molecular movement and local reactions can generate many system functions, and give distinct identities to different parts of the cell
Developing complex signaling models using GENESIS/Kinetikit
No full textThe development of biologically realistic models of signaling pathways is a demanding process, involving computational challenges as well as those arising from the complexity of detailed pathway models. We have developed the General Neural Simulation System (GENESIS) and Kinetikit (GENESIS/Kinetikit), a graphical simulation environment for modeling biochemical signaling pathways using deterministic and stochastic methods. A library of models of several common signaling pathways complements the software. This combination of numerical computation engines, graphical modeling tools, and library of models is designed to build on the cumulative development of models and techniques from many sources. The complete simulation environment and demonstration models are available from (http://stke.sciencemag.org/cgi/content/full/sigtrans;2004/219/pl4/DC1; also at http://www.ncbs.res.in/~bhalla/kkit/download.html). The associated library of signaling pathways is based on published experimental and simulation studies and is curated to ensure that the simulation outcomes match published results. Models in the library are maintained in a database (http://doqcs.ncbs.res.in). Individual pathway models can be combined to build complex signaling network simulations. The overall goal of this process is to attain sufficient biological realism in models to directly compare their outcomes with experiments and to improve our understanding of complex signaling
Information processing in the mammalian olfactory bulb
No full textA combination of computer modeling and experimental approaches were taken to studying the mammalian olfactory bulb. First, detailed single cell models were developed for the main cell classes in the olfactory bulb. This involved development of simulation techniques and a parameter search method for assigning unknown parameters for neuronal models. This study demonstrated the feasibility of using indirect information, such as spike waveforms, to determine the detailed electrical properties of neurons. The models demonstrated that spikes propagate into the secondary dendrites, which may play a role in long-range spatial interactions in the bulb. Blockage of this spike propagation might be involved in bulbar information processing. Second, a series of recordings were made from neurons in the olfactory bulb of awake unrestrained rats exposed to a cyclical sequence of odorants. These recordings demonstrated a significant amount of variability in the response of individual neurons over time. The neuronal responses were well described as a combination of a consistent component with a component that varied over time. Comparisons made between response properties of the same neuron at different times, between adjacent neurons, between distant neurons and between unrelated neurons showed a clear sequence of increasing difference in the order: same < adjacent < unrelated < distant. However, during sniff periods, the sequence was: adjacent < same < unrelated < distant. This suggests the bulb normally responds evenly to a wide range of odorants, but during sniffing responses to familiar odorants are suppressed so as to preferentially detect novel odorants. The final stage of the study involved the development of detailed models of the bulb as a whole using both the single cell models, and the experimental results previously obtained. It was found that topographical organization of receptor input according to receptor type was not required to produce the range of responses seen in the experiments. The response variability of neurons in the model was much smaller than in experiment. We propose that the bulb can operate in multiple processing modes so as to optimize its responses for different situations and that this leads to variability in single neuron responses
Synaptic input sequence discrimination on behavioral time-scales mediated by reaction-diffusion chemistry in dendrites
No full textAbstractSequences of events are ubiquitous in sensory, motor, and cognitive function. Key computational operations, including pattern recognition, event prediction, and plasticity, involve neural discrimination of spatio-temporal sequences. Here we show that synaptically-driven reaction-diffusion pathways on dendrites can perform sequence discrimination on behaviorally relevant time-scales. We used abstract signaling models to show that this selectivity arises when inputs at successive locations are aligned with, and amplified by, propagating chemical waves triggered by previous inputs. We incorporated biological detail using sequential synaptic input onto spines in morphologically, electrically, and chemically detailed pyramidal neuronal models. Again, sequences were recognized, and local channel modulation on the length-scale of sequence input could elicit changes in neuronal firing. We predict that dendritic sequence-recognition zones occupy 5 to 20 microns and recognize time-intervals of 0.2 to 5s. We suggest that this mechanism provides highly parallel and selective neural computation in a functionally important time range.</jats:p
Robust and Rapid Air-Borne Odor Tracking without Casting
No full textCasting behavior (zigzagging across an odor stream) is common in air/liquid-borne odor tracking in open fields; however, terrestrial odor localization often involves path selection in a familiar environment. To study this, we trained rats to run toward an odor source in a multi-choice olfactory arena with near-laminar airflow. We find that rather than casting, rats run directly toward an odor port, and if this is incorrect, they serially sample other sources. This behavior is consistent and accurate in the presence of perturbations, such as novel odors, background odor, unilateral nostril stitching, and turbulence. We developed a model that predicts that this run-and-scan tracking of air-borne odors is faster than casting, provided there are a small number of targets at known locations. Thus, the combination of best-guess target selection with fallback serial sampling provides a rapid and robust strategy for finding odor sources in familiar surroundings
Odor representations in the mammalian olfactory bulb
No full textA first key step in studying a sensory modality is to define how the brain represents the features of the sensory stimulus. This has proven to be a challenge in olfaction, where even the stimulus features have been a matter of considerable debate. In this review, we focus on olfactory representations in the first stage of the olfactory pathway, the olfactory bulb (OB). We examine the diverging viewpoints on spatially organized versus distributed representations. We then consider how odor sampling through respiration is a key part of the odorant code. Finally, we ask how the bulb handles the challenging task of representing mixtures. We suggest that current evidence points toward a representation that is spatially organized at the inputs but later distributed, with the spatial organization not being used for much computation. Nevertheless, this is a simple representation that effectively represents multiple individual odorants, as well as odor mixtures
Precise excitation-inhibition balance controls gain and timing in the hippocampus
No full textExcitation-inhibition (EI) balance controls excitability, dynamic range, and input gating in many brain circuits. Subsets of synaptic input can be selected or 'gated' by precise modulation of finely tuned EI balance, but assessing the granularity of EI balance requires combinatorial analysis of excitatory and inhibitory inputs. Using patterned optogenetic stimulation of mouse hippocampal CA3 neurons, we show that hundreds of unique CA3 input combinations recruit excitation and inhibition with a nearly identical ratio, demonstrating precise EI balance at the hippocampus. Crucially, the delay between excitation and inhibition decreases as excitatory input increases from a few synapses to tens of synapses. This creates a dynamic millisecond-range window for postsynaptic excitation, controlling membrane depolarization amplitude and timing via subthreshold divisive normalization. We suggest that this combination of precise EI balance and dynamic EI delays forms a general mechanism for millisecond-range input gating and subthreshold gain control in feedforward networks
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