Prinz, Astrid A., Cyrus P. Billimoria, and Eve Marder. Alternative to hand-tuning conductance-based models: construction and analysis of databases of model neurons. J Neurophysiol 90: 3998 -4015, 2003. First published August 27, 2003 10.1152/jn.00641.2003. Conventionally, the parameters of neuronal models are hand-tuned using trial-and-error searches to produce a desired behavior. Here, we present an alternative approach. We have generated a database of about 1.7 million single-compartment model neurons by independently varying 8 maximal membrane conductances based on measurements from lobster stomatogastric neurons. We classified the spontaneous electrical activity of each model neuron and its responsiveness to inputs during runtime with an adaptive algorithm and saved a reduced version of each neuron's activity pattern. Our analysis of the distribution of different activity types (silent, spiking, bursting, irregular) in the 8-dimensional conductance space indicates that the coarse grid of conductance values we chose is sufficient to capture the salient features of the distribution. The database can be searched for different combinations of neuron properties such as activity type, spike or burst frequency, resting potential, frequency-current relation, and phaseresponse curve. We demonstrate how the database can be screened for models that reproduce the behavior of a specific biological neuron and show that the contents of the database can give insight into the way a neuron's membrane conductances determine its activity pattern and response properties. Similar databases can be constructed to explore parameter spaces in multicompartmental models or small networks, or to examine the effects of changes in the voltage dependence of currents. In all cases, database searches can provide insight into how neuronal and network properties depend on the values of the parameters in the models. I N T R O D U C T I O NThe spontaneous firing pattern of a neuron and how it responds to inputs from other neurons is crucially determined by the densities and dynamics of the ion channels in the neuron's membrane. These membrane conductances have a nonlinear dependence on the membrane potential, which itself is changed by the currents flowing through the conductances. A neuron with even a small number of membrane conductances is a complex dynamical system, and predicting the behavior of a cell with a physiologically realistic set of currents becomes very difficult.Faced with ongoing channel turnover, neurons must constantly adjust their membrane currents to maintain their electrical identity (Marder and Prinz 2002). Experiments and simulations have shown that even small changes in one or a few currents can dramatically alter the activity of a neuron (De Schutter and Bower 1994;Goldman et al. 2001). On the other hand, similar activity can be achieved with widely varying sets of conductances in biological and model neurons (Bhalla and Bower 1993;De Schutter and Bower 1994;Foster et al. 1993;Goldman et al. 2001;Golowasch et al. 1999a...

The crustacean stomatogastric ganglion (STG) is modulated by both locally released neuroactive compounds and circulating hormones. This study presents mass spectrometric characterization of the complement of peptide hormones present in one of the major neurosecretory structures, the pericardial organs (POs), and the detection of neurohormones released from the POs. Direct peptide profiling of Cancer borealis PO tissues using matrix-assisted laser desorption/ ionization (MALDI) time-of-flight (TOF) mass spectrometry (MS) revealed many previously identified peptides, including proctolin, red pigment concentrating hormone (RPCH), crustacean cardioactive peptide (CCAP), several orcokinins, and SDRNFLRFamide. This technique also detected corazonin, a well-known insect hormone, in the POs for the first time.However, most mass spectral peaks did not correspond to previously known peptides. To characterize and identify these novel peptides, we performed MALDI postsource decay (PSD) and electrospray ionization (ESI) MS/MS de novo sequencing of peptides fractionated from PO extracts. We characterized a truncated form of previously identified TNRNFLRFamide, NRNFLRFamide. In addition, we sequenced five other novel peptides sharing a common C-terminus of RYamide from the PO tissue extracts. High K + depolarization of isolated POs released many peptides present in this tissue, including several of the novel peptides sequenced in the current study.

Neurons in the avian auditory forebrain show strong sensitivity to the spatial configuration of two competing sources, even though there is only weak spatial dependence for any single source.

The neuropeptide allatostatin decreases the spike rate in response to time-varying stretches of two different crustacean mechanoreceptors, the gastropyloric receptor 2 in the crab Cancer borealis and the coxobasal chordotonal organ (CBCTO) in the crab Carcinus maenas. In each system, the decrease in firing rate is accompanied by an increase in the timing precision of spikes triggered by discrete temporal features in the stimulus. This was quantified by calculating the standard deviation or "jitter" in the times of individual identified spikes elicited in response to repeated presentations of the stimulus. Conversely, serotonin increases the firing rate but decreases the timing precision of the CBCTO response. Intracellular recordings from the afferents of this receptor demonstrate that allatostatin increases the conductance of the neurons, consistent with its inhibitory action on spike rate, whereas serotonin decreases the overall membrane conductance. We conclude that spike-timing precision of mechanoreceptor afferents in response to dynamic stimulation can be altered by neuromodulators acting directly on the afferent neurons.

Neuromodulators can modify the magnitude and kinetics of the response of a sensory neuron to a stimulus. Six neuroactive substances modified the activity of the gastropyloric receptor 2 (GPR2) neuron of the stomatogastric nervous system (STNS) of the crab Cancer borealis during muscle stretch. Stretches were applied to the gastric mill 9 (gm9) and the cardio-pyloric valve 3a (cpv3a) muscles. SDRNFLRFamide and dopamine had excitatory effects on GPR2. Serotonin, GABA, and the peptide allatostatin-3 (AST) decreased GPR2 firing during stretch. Moreover, SDRNFLRFamide and TNRNFLRFamide increased the unstimulated spontaneous firing rate, whereas AST and GABA decreased it. The actions of AST and GABA were amplitude- and history-dependent. In fully recovered preparations, AST and GABA decreased the response to small-amplitude stretches proportionally more than to those evoked by large-amplitude stretches. For large-amplitude stretches, the effects of AST and GABA were more pronounced as the number of recent stretches increased. The modulators that affected the stretch-induced GPR2 firing rate were also tested when the neuron was operating in a bursting mode of activity. Application of SDRNFLRFamide increased the bursting frequency transiently, whereas high concentrations of serotonin, AST, and GABA abolished bursting altogether. Together these data demonstrate that the effects of neuromodulators depend on the previous activity and current state of the sensory neuron.

Intensity variation poses a fundamental problem for sensory discrimination because changes in the response of sensory neurons as a result of stimulus identity, e.g., a change in the identity of the speaker uttering a word, can potentially be confused with changes resulting from stimulus intensity, for example, the loudness of the utterance. Here we report on the responses of neurons in field L, the primary auditory cortex homolog in songbirds, which allow for accurate discrimination of birdsongs that is invariant to intensity changes over a large range. Such neurons comprise a subset of a population that is highly diverse, in terms of both discrimination accuracy and intensity sensitivity. We find that the neurons with a high degree of invariance also display a high discrimination performance, and that the degree of invariance is significantly correlated with the reproducibility of spike timing on a short time scale and the temporal sparseness of spiking activity. Our results indicate that a temporally sparse spike timing-based code at a primary cortical stage can provide a substrate for intensity-invariant discrimination of natural sounds.

Proprioception in the first two joints of crustacean limbs is mediated by chordotonal organs that utilize spike-mediated information coding and transmission and by nonspiking proprioceptive afferents that use graded transmission at information rates in excess of 2,500 bits/s. Chordotonal organs operate in parallel with the graded receptors, but the information rates of the spiking chordotonal afferents have not been previously determined. Lower-bound estimates of chordotonal afferent information rates were calculated using stimulus reconstruction, which assumes linear encoding of the stimulus. The information rate was also directly estimated from the spike train entropy, which makes no a priori assumptions with respect to the coding scheme used by the system. Lower-bound information rate estimates ranged from 43 to 69 bits/s, whereas the direct estimates ranged from 24 to 278 bits/s. Comparison of both estimates derived from the same data set indicates that a linear decoder could recover an average of 59% of the information from the spike train. Afferent spike timing was found to be extremely precise, with spikes evoked with an average timing jitter of 0.55 ms. Information rate was correlated with the mean jitter and the noise entropy of the spike train could be predicted from the mean firing rate and mean jitter. Direct stimulation of single afferents by current injection into the soma revealed that the average timing jitter was <0.1 ms, indicating that intrinsic membrane properties, spike generation, and mechanotransduction mechanisms are the major sources of timing jitter in this system.

Larson E, Billimoria CP, Sen K. A biologically plausible computational model for auditory object recognition. J Neurophysiol 101: 323-331, 2009. First published November 5, 2008 doi:10.1152/jn.90664.2008. Object recognition is a task of fundamental importance for sensory systems. Although this problem has been intensively investigated in the visual system, relatively little is known about the recognition of complex auditory objects. Recent work has shown that spike trains from individual sensory neurons can be used to discriminate between and recognize stimuli. Multiple groups have developed spike similarity or dissimilarity metrics to quantify the differences between spike trains. Using a nearest-neighbor approach the spike similarity metrics can be used to classify the stimuli into groups used to evoke the spike trains. The nearest prototype spike train to the tested spike train can then be used to identify the stimulus. However, how biological circuits might perform such computations remains unclear. Elucidating this question would facilitate the experimental search for such circuits in biological systems, as well as the design of artificial circuits that can perform such computations. Here we present a biologically plausible model for discrimination inspired by a spike distance metric using a network of integrate-and-fire model neurons coupled to a decision network. We then apply this model to the birdsong system in the context of song discrimination and recognition. We show that the model circuit is effective at recognizing individual songs, based on experimental input data from field L, the avian primary auditory cortex analog. We also compare the performance and robustness of this model to two alternative models of song discrimination: a model based on coincidence detection and a model based on firing rate.