Instantaneous Firing Rate Research Articles

Implications of polychronous neuronal groups for the continuity of mind.

Is conceptual space continuous? The answer to this question depends on how concepts are represented in the brain. Vector space representations, which ground conceptual states in the instantaneous firing rates of neurons, have successfully captured cognitive dynamics in a broad range of domains. There is a growing body of evidence, however, that conceptual information is encoded in spatiotemporal patterns of neural spikes, sometimes called polychronous neuronal groups (PNGs). The use of PNGs to represent conceptual states, rather than employing a continuous vector space, introduces new challenges, including issues of temporally extended representations, meaning through symbol grounding, compositionality, and representational similarity. In this article, we explore how PNGs support discontinuous transitions between concepts. While the continuous dynamics of vector space approaches require such transitions to activate intermediate and blended concepts, PNGs offer the means to change the activation of concepts discretely, introducing a form of conceptual dynamics unavailable to vector space models.

On firing rate estimation for dependent interspike intervals.

If interspike intervals are dependent, the instantaneous firing rate does not catch important features of spike trains. In this case, the conditional instantaneous rate plays the role of the instantaneous firing rate for the case of samples of independent interspike intervals. If the conditional distribution of the interspikes intervals (ISIs) is unknown, it becomes difficult to evaluate the conditional firing rate. We propose a nonparametric estimator for the conditional instantaneous firing rate for Markov, stationary, and ergodic ISIs. An algorithm to check the reliability of the proposed estimator is introduced, and its consistency properties are proved. The method is applied to data obtained from a stochastic two-compartment model and to in vitro experimental data.

A frequency-resolved mutual information rate and its application to neural systems.

The encoding and processing of time-dependent signals into sequences of action potentials of sensory neurons is still a challenging theoretical problem. Although, with some effort, it is possible to quantify the flow of information in the model-free framework of Shannon's information theory, this yields just a single number, the mutual information rate. This rate does not indicate which aspects of the stimulus are encoded. Several studies have identified mechanisms at the cellular and network level leading to low- or high-pass filtering of information, i.e., the selective coding of slow or fast stimulus components. However, these findings rely on an approximation, specifically, on the qualitative behavior of the coherence function, an approximate frequency-resolved measure of information flow, whose quality is generally unknown. Here, we develop an assumption-free method to measure a frequency-resolved information rate about a time-dependent Gaussian stimulus. We demonstrate its application for three paradigmatic descriptions of neural firing: an inhomogeneous Poisson process that carries a signal in its instantaneous firing rate; an integrator neuron (stochastic integrate-and-fire model) driven by a time-dependent stimulus; and the synchronous spikes fired by two commonly driven integrator neurons. In agreement with previous coherence-based estimates, we find that Poisson and integrate-and-fire neurons are broadband and low-pass filters of information, respectively. The band-pass information filtering observed in the coherence of synchronous spikes is confirmed by our frequency-resolved information measure in some but not all parameter configurations. Our results also explicitly show how the response-response coherence can fail as an upper bound on the information rate.

Selective degeneration of a physiological subtype of spinal motor neuron in mice with SOD1-linked ALS.

Amyotrophic lateral sclerosis (ALS; Lou Gehrig's disease) affects motor neurons (MNs) in the brain and spinal cord. Understanding the pathophysiology of this condition seems crucial for therapeutic design, yet few electrophysiological studies in actively degenerating animal models have been reported. Here, we report a novel preparation of acute slices from adult mouse spinal cord, allowing visualized whole cell patch-clamp recordings of fluorescent lumbar MN cell bodies from ChAT-eGFP or superoxide dismutase 1-yellow fluorescent protein (SOD1YFP) transgenic animals up to 6 mo of age. We examined 11 intrinsic electrophysiologic properties of adult ChAT-eGFP mouse MNs and classified them into four subtypes based on these parameters. The subtypes could be principally correlated with instantaneous (initial) and steady-state firing rates. We used retrograde tracing using fluorescent dye injected into fast or slow twitch lower extremity muscle with slice recordings from the fluorescent-labeled lumbar MN cell bodies to establish that fast and slow firing MNs are connected with fast and slow twitch muscle, respectively. In a G85R SOD1YFP transgenic mouse model of ALS, which becomes paralyzed by 5-6 mo, where MN cell bodies are fluorescent, enabling the same type of recording from spinal cord tissue slices, we observed that all four MN subtypes were present at 2 mo of age. At 4 mo, by which time substantial neuronal SOD1YFP aggregation and cell loss has occurred and symptoms have developed, one of the fast firing subtypes that innvervates fast twitch muscle was lost. These results begin to describe an order of the pathophysiologic events in ALS.

Single motor unit firing behavior in the right trapezius muscle during rapid movement of right or left index finger.

Background: Computer work is associated with low level sustained activity in the trapezius muscle that may cause development of trapezius myalgia. Such a low level activity may be attention related or alternatively, be part of a general multi joint motor program providing stabilization of the shoulder joint as a biomechanical prerequisite for precise finger manipulation. This study examines single motor unit (MU) firing pattern in the right trapezius muscle during fast movements of ipsilateral or contralateral index finger. A modulation of the MU firing rate would support the existence of a general multi joint motor program, while a generally increased and continuous firing rate would support the attention related muscle activation.Method: Twelve healthy female subjects were seated at a computer work place with elbows and forearms supported. Ten double clicks (DC) were performed with right and left index finger on a computer mouse instrumented with a trigger. Surface electromyographic signals (EMG) was recorded from right and left trapezius muscle. Intramuscular EMG was recorded with a quadripolar wire electrode inserted into the right trapezius. Surface EMG was analyzed as RMS and presented as %MVE. The intramuscular EMG signals were decomposed into individual MU action potential trains using a computer algorithm based on signal shape recognition and manual editing. Instantaneous firing rate (IFR) was calculated as the inverse of each inter-spike interval (ISI). All ISI shorter than 20 ms were defined as doublets. For all MU IFR was spike triggered averaged across the 10 DC to show the modulation during DC as well as for calculation of the cross correlation coefficient (CCC).Results: All subjects showed surface EMG activity in both right and left trapezius ranging from 1.8 %MVE to 2.5 %MVE. Regarding intramuscular EMG during right hand DC a total of 32 MUs were identified. Four subjects showed no MU activity. Four showed MU activity with low mean firing rate (MFR) with weak or no variations related to the timing of DC. Four subjects showed firing patterns with large modulation in IFR with a clear temporal relation to the DC. During left hand DC 15 MUs were identified in four subjects, for two of the subjects with IFR modulations clearly related to DC. During both ipsi- and contralateral DC, doublets occurred sporadically as well as related to DCConclusion: In conclusion, DC with ipsi- and contralateral fast movements of the index finger was found to evoke biomechanically as well as attention related activity pattern in the trapezius muscle. Doublets were for three of the subjects found as an integrated part of MU activation in the trapezius muscle and for one subject temporarily related to DC.

Modulation of motoneuron firing by recurrent inhibition in the adult rat in vivo.

Recent reports show that synaptic inhibition can modulate postsynaptic spike timing without having strong effects on firing rate. Thus synaptic inhibition can achieve multiplicity in neural circuit operation through variable modulation of postsynaptic firing rate vs. timing. We tested this possibility for recurrent inhibition (RI) of spinal motoneurons. In in vivo electrophysiological studies of adult Wistar rats anesthetized by isoflurane, we examined repetitive firing of individual lumbosacral motoneurons recorded in current clamp and modulated by synchronous antidromic electrical stimulation of multiple motor axons and their centrally projecting collateral branches. Antidromic stimulation produced recurrent inhibitory postsynaptic potentials (RIPSPs) having properties similar to those detailed in the cat. Although synchronous RI produced marked short-term modulation of motoneuron spike timing and instantaneous firing rate, there was little or no suppression of average firing rate. The bias in firing modulation of timing over average rate was observed even for high-frequency RI stimulation (100 Hz), perhaps because of the brevity of RIPSPs, which were more than twofold shorter during motoneuron firing compared with rest. These findings demonstrate that RI in the mammalian spinal cord has the capacity to support and not impede heightened motor pool activity, possibly during rapid, forceful movements.

Unmasking of spiral ganglion neuron firing dynamics by membrane potential and neurotrophin-3.

Type I spiral ganglion neurons have a unique role relative to other sensory afferents because, as a single population, they must convey the richness, complexity, and precision of auditory information as they shape signals transmitted to the brain. To understand better the sophistication of spiral ganglion response properties, we compared somatic whole-cell current-clamp recordings from basal and apical neurons obtained during the first 2 postnatal weeks from CBA/CaJ mice. We found that during this developmental time period neuron response properties changed from uniformly excitable to differentially plastic. Low-frequency, apical and high-frequency basal neurons at postnatal day 1 (P1)-P3 were predominantly slowly accommodating (SA), firing at low thresholds with little alteration in accommodation response mode induced by changes in resting membrane potential (RMP) or added neurotrophin-3 (NT-3). In contrast, P10-P14 apical and basal neurons were predominately rapidly accommodating (RA), had higher firing thresholds, and responded to elevation of RMP and added NT-3 by transitioning to the SA category without affecting the instantaneous firing rate. Therefore, older neurons appeared to be uniformly less excitable under baseline conditions yet displayed a previously unrecognized capacity to change response modes dynamically within a remarkably stable accommodation framework. Because the soma is interposed in the signal conduction pathway, these specializations can potentially lead to shaping and filtering of the transmitted signal. These results suggest that spiral ganglion neurons possess electrophysiological mechanisms that enable them to adapt their response properties to the characteristics of incoming stimuli and thus have the capacity to encode a wide spectrum of auditory information.

Neural coding strategies for extracting motion estimates from electrosensory contrast

Object saliency is based on the relative local-to-background contrast in the physical signals that underlie perceptual experience. Extracting meaningful stimulus representations from these contrast patterns constitutes a serious inverse problem for neural coding, where many different stimulus features map into a scalar firing rate. This decoding problem is even more acute for neurons whose dynamics are characterized by fixed timescales, which produce distinct firing rate responses to different temporal parameterizations of a stimulus [1]. By studying how looming object distance is extracted from electrosensory contrast, we demonstrate that power law adaptation in the primary electroreceptor afferents of A. leptorhynchus transforms the firing rate, yielding a code for stimulus intensity (distance) that is invariant to the rate of change of intensity with respect to time (speed). As such, estimates of both object distance and approach speed are effectively parsed into distinct measures of an electroreceptor afferent’s firing rate [1]. Despite its important role in neural coding, adaptation suffers a serious caveat for encoding natural inputs: it generates skewed responses when signal intensity changes from increasing to decreasing (or vice versa). As predicted by generic models of spike-frequency adaptation, we report a skew in the electroreceptor afferent firing rate upon motion reversal, introducing further ambiguity into the estimation of object distance from electrosensory contrast [2]. The electrosense compensates for the skewed firing rate by combining the activity of downstream ON and OFF cells into a population rate code characterized by paradoxical responses to local contrast. Under both positive and negative contrast conditions, motion reversal induces a coding switch between ON and OFF cells, whose combined instantaneous firing rates cooperatively produce a symmetric representation of object motion. Whereas the firing rates of the individual ON and OFF cells convey scalar information, such as object distance, their sequential activation over longer timescales encode changes in motion direction.

O28: Comparison of the language lateralizations suggested by magnetoencephalography and navigated transcranial magnetic stimulation in healthy subjects using a picture naming task

O28: Comparison of the language lateralizations suggested by magnetoencephalography and navigated transcranial magnetic stimulation in healthy subjects using a picture naming task

O29: Beyond skeletomotor function of human basal ganglia: oculomotor, visual and affective neurons

Deep brain stimulation (DBS) of targets in basal ganglia is an effective treatment of motor dysfunction in Parkinson’s disease and primary dystonia. However this treatment may be accompanied by unwanted non-motor side effects. To confirm their neurophysiological nature we searched for any neurons in the subthalamic nucleus (STN), substantia nigra pars reticulata (SNr) and globus pallidus (GP) involved in processing of visually presented emotional scenes. Nineteen Parkinson’s disease patients, which underwent implantation of DBS electrodes to STN or GP, were investigated with simultaneous intraoperative microelectrode recordings and single channel electrooculography during a visual emotional task containing a series of photographs varying in emotional valence and arousal. Recordings were analyzed by the WaveClus program which allowed for detection and sorting of individual neurons. Out of 183 neurons that were detected, 130 were found in the STN, 30 in the SNr and 23 in the GP. Twenty percent of the neurons in each of these structures showed eye movement-related activity. In the STN, we observed 35 neurons whose firing rate changed significantly within first 500 ms after presentation of a photograph suggesting their participation in visual or attentional mechanisms. Activity of 14 STN neurons showed significant changes during 500–1500 ms interval in alpha band of the instantaneous firing rate related to the emotional content of presented photographs. Activity of 8 of neurons was related to the arousal while activity of another 6 neurons was changing in relation to the emotional valence. Our results showed that basal ganglia contain relatively high share of oculomotor neurons suggesting their critical role in eye-movement control. In addition, the STN neurons involved in visual processing and in transmission of emotional information provide evidence of separate management of the affective dimensions of valence and arousal. Therefore, it is not surprising that DBS may have various non-motor consequences. Supported by grants: IGA MZ CR NT12282–5/2011; research projects: MSM 0021620849, MSM 6840770012 and PRVOUK-P26/LF1/4.

Motor cortical correlates of arm resting in the context of a reaching task and implications for prosthetic control.

Prosthetic devices are being developed to restore movement for motor-impaired individuals. A robotic arm can be controlled based on models that relate motor-cortical ensemble activity to kinematic parameters. The models are typically built and validated on data from structured trial periods during which a subject actively performs specific movements, but real-world prosthetic devices will need to operate correctly during rest periods as well. To develop a model of motor cortical modulation during rest, we trained monkeys (Macaca mulatta) to perform a reaching task with their own arm while recording motor-cortical single-unit activity. When a monkey spontaneously put its arm down to rest between trials, our traditional movement decoder produced a nonzero velocity prediction, which would cause undesired motion when applied to a prosthetic arm. During these rest periods, a marked shift was found in individual units' tuning functions. The activity pattern of the whole population during rest (Idle state) was highly distinct from that during reaching movements (Active state), allowing us to predict arm resting from instantaneous firing rates with 98% accuracy using a simple classifier. By cascading this state classifier and the movement decoder, we were able to predict zero velocity correctly, which would avoid undesired motion in a prosthetic application. Interestingly, firing rates during hold periods followed the Active pattern even though hold kinematics were similar to those during rest with near-zero velocity. These findings expand our concept of motor-cortical function by showing that population activity reflects behavioral context in addition to the direct parameters of the movement itself.

A neural code for looming and receding motion is distributed over a population of electrosensory ON and OFF contrast cells.

Object saliency is based on the relative local-to-background contrast in the physical signals that underlie perceptual experience. As such, contrast-detecting neurons (ON/OFF cells) are found in many sensory systems, responding respectively to increased or decreased intensity within their receptive field centers. This differential sensitivity suggests that ON and OFF cells initiate segregated streams of information for positive and negative sensory contrast. However, while recording in vivo from the ON and OFF cells of Apteronotus leptorhynchus, we report that the reversal of stimulus motion triggers paradoxical responses to electrosensory contrast. By considering the instantaneous firing rates of both ON and OFF cell populations, a bidirectionally symmetric representation of motion is achieved for both positive and negative contrast stimuli. Whereas the firing rates of the individual contrast detecting neurons convey scalar information, such as object distance, it is their sequential activation over longer timescales that track changes in the direction of movement.

Greater excitability and firing irregularity of tufted cells underlies distinct afferent‐evoked activity of olfactory bulb mitral and tufted cells

Mitral and tufted cells, the two classes of principal neurons in the mammalian main olfactory bulb, exhibit morphological differences but remain widely viewed as functionally equivalent. Results from several recent studies, however, suggest that these two cell classes may encode complementary olfactory information in their distinct patterns of afferent-evoked activity. To understand how these differences in activity arise, we have performed the first systematic comparison of synaptic and intrinsic properties between mitral and tufted cells. Consistent with previous studies, we found that tufted cells fire with higher probability and rates and shorter latencies than mitral cells in response to physiological afferent stimulation. This stronger response of tufted cells could be partially attributed to synaptic differences, as tufted cells received stronger afferent-evoked excitation than mitral cells. However, differences in intrinsic excitability also contributed to the differences between mitral and tufted cell activity. Compared to mitral cells, tufted cells exhibited twofold greater excitability and peak instantaneous firing rates. These differences in excitability probably arise from differential expression of voltage-gated potassium currents, as tufted cells exhibited faster action potential repolarization and afterhyperpolarizations than mitral cells. Surprisingly, mitral and tufted cells also showed firing mode differences. While both cell classes exhibited regular firing and irregular stuttering of action potential clusters, tufted cells demonstrated a greater propensity to stutter than mitral cells. Collectively, stronger afferent-evoked excitation, greater intrinsic excitability and more irregular firing in tufted cells can combine to drive distinct responses of mitral and tufted cells to afferent-evoked input.

18. Beyond skeletomotor function of human basal ganglia: Oculomotor, visual and affective neurons

Deep brain stimulation (DBS) of targets in basal ganglia is an effective treatment of motor dysfunction in Parkinson’s disease and primary dystonia. However this treatment may be accompanied by unwanted non-motor side effects. To confirm their neurophysiological nature we searched for any neurons in the subthalamic nucleus (STN), substantia nigra pars reticulata (SNr) and globus pallidus (GP) involved in processing of visually presented emotional scenes. Nineteen Parkinson’s disease patients, which underwent implantation of DBS electrodes to STN or GP, were investigated with simultaneous intraoperative microelectrode recordings and single channel electrooculography during a visual emotional task containing a series of photographs varying in emotional valence and arousal. Recordings were analyzed by the WaveClus program which allowed for detection and sorting of individual neurons. Out of 183 neurons that were detected, 130 were found in the STN, 30 in the SNr and 23 in the GP. Twenty percent of the neurons in each of these structures showed eye movement-related activity. In the STN, we observed 35 neurons whose firing rate changed significantly within first 500 ms after presentation of a photograph suggesting their participation in visual or attentional mechanisms. Activity of 14 STN neurons showed significant changes during 500–1500 ms interval in alpha band of the instantaneous firing rate related to the emotional content of presented photographs. Activity of 8 of neurons was related to the arousal while activity of another 6 neurons was changing in relation to the emotional valence. Our results showed that basal ganglia contain relatively high share of oculomotor neurons suggesting their critical role in eye-movement control. In addition, the STN neurons involved in visual processing and in transmission of emotional information provide evidence of separate management of the affective dimensions of valence and arousal. Therefore, it is not surprising that DBS may have various non-motor consequences. Supported by grants: IGA MZ ČR NT12282–5/2011; research projects: MŠM 0021620849, MŠM 6840770012 and PRVOUK-P26/LF1/4.

Emergence of Context-Dependent Variability across a Basal Ganglia Network

Context dependence is a key feature of cortical-basal ganglia circuit activity, and in songbirds the cortical outflow of a basal ganglia circuit specialized for song, LMAN, shows striking increases in trial-by-trial variability and bursting when birds sing alone rather than to females. To reveal where this variability and its social regulation emerge, we recorded stepwise from corticostriatal (HVC) neurons and their target spiny and pallidal neurons in Area X. We find that corticostriatal and spiny neurons both show precise singing-related firing across both social settings. Pallidal neurons, in contrast, exhibit markedly increased trial-by-trial variation when birds sing alone, created by highly variable pauses in firing. This variability persists even when recurrent inputs from LMAN are ablated. These data indicate that variability and its context sensitivity emerge within the basal ganglia network, suggest a network mechanism for this emergence, and highlight variability generation and regulation as basal ganglia functions.

Functional Connectivity among Spikes in Low Dimensional Space during Working Memory Task in Rat

Working memory (WM) is critically important in cognitive tasks. The functional connectivity has been a powerful tool for understanding the mechanism underlying the information processing during WM tasks. The aim of this study is to investigate how to effectively characterize the dynamic variations of the functional connectivity in low dimensional space among the principal components (PCs) which were extracted from the instantaneous firing rate series. Spikes were obtained from medial prefrontal cortex (mPFC) of rats with implanted microelectrode array and then transformed into continuous series via instantaneous firing rate method. Granger causality method is proposed to study the functional connectivity. Then three scalar metrics were applied to identify the changes of the reduced dimensionality functional network during working memory tasks: functional connectivity (GC), global efficiency (E) and casual density (CD). As a comparison, GC, E and CD were also calculated to describe the functional connectivity in the original space. The results showed that these network characteristics dynamically changed during the correct WM tasks. The measure values increased to maximum, and then decreased both in the original and in the reduced dimensionality. Besides, the feature values of the reduced dimensionality were significantly higher during the WM tasks than they were in the original space. These findings suggested that functional connectivity among the spikes varied dynamically during the WM tasks and could be described effectively in the low dimensional space.

Theta phase precession of grid and place cell firing in open environments

Place and grid cells in the rodent hippocampal formation tend to fire spikes at successively earlier phases relative to the local field potential theta rhythm as the animal runs through the cell's firing field on a linear track. However, this ‘phase precession’ effect is less well characterized during foraging in two-dimensional open field environments. Here, we mapped runs through the firing fields onto a unit circle to pool data from multiple runs. We asked which of seven behavioural and physiological variables show the best circular–linear correlation with the theta phase of spikes from place cells in hippocampal area CA1 and from grid cells from superficial layers of medial entorhinal cortex. The best correlate was the distance to the firing field peak projected onto the animal's current running direction. This was significantly stronger than other correlates, such as instantaneous firing rate and time-in-field, but similar in strength to correlates with other measures of distance travelled through the firing field. Phase precession was stronger in place cells than grid cells overall, and robust phase precession was seen in traversals through firing field peripheries (although somewhat less than in traversals through the centre), consistent with phase coding of displacement along the current direction. This type of phase coding, of place field distance ahead of or behind the animal, may be useful for allowing calculation of goal directions during navigation.

Surface EMG-force modelling for the biceps brachii and its experimental evaluation during isometric isotonic contractions

The aim of this study was to evaluate a surface electromyography (sEMG) signal and force model for the biceps brachii muscle during isotonic isometric contractions for an experimental set-up as well as for a simulation. The proposed model includes a new rate coding scheme and a new analytical formulation of the muscle force generation. The proposed rate coding scheme supposes varying minimum and peak firing frequencies according to motor unit (MU) type (I or II). Practically, the proposed analytical mechanogram allows us to tune the force contribution of each active MU according to its type and instantaneous firing rate. A subsequent sensitivity analysis using a Monte Carlo simulation allows deducing optimised input parameter ranges that guarantee a realistic behaviour of the proposed model according to two existing criteria and an additional one. In fact, this proposed new criterion evaluates the force generation efficiency according to neural intent. Experiments and simulations, at varying force levels and using the optimised parameter ranges, were performed to evaluate the proposed model. As a result, our study showed that the proposed sEMG–force modelling can emulate the biceps brachii behaviour during isotonic isometric contractions.

Temporal Features of Spike Trains in the Moth Antennal Lobe Revealed by a Comparative Time-Frequency Analysis

The discrimination of complex sensory stimuli in a noisy environment is an immense computational task. Sensory systems often encode stimulus features in a spatiotemporal fashion through the complex firing patterns of individual neurons. To identify these temporal features, we have developed an analysis that allows the comparison of statistically significant features of spike trains localized over multiple scales of time-frequency resolution. Our approach provides an original way to utilize the discrete wavelet transform to process instantaneous rate functions derived from spike trains, and select relevant wavelet coefficients through statistical analysis. Our method uncovered localized features within olfactory projection neuron (PN) responses in the moth antennal lobe coding for the presence of an odor mixture and the concentration of single component odorants, but not for compound identities. We found that odor mixtures evoked earlier responses in biphasic response type PNs compared to single components, which led to differences in the instantaneous firing rate functions with their signal power spread across multiple frequency bands (ranging from 0 to 45.71 Hz) during a time window immediately preceding behavioral response latencies observed in insects. Odor concentrations were coded in excited response type PNs both in low frequency band differences (2.86 to 5.71 Hz) during the stimulus and in the odor trace after stimulus offset in low (0 to 2.86 Hz) and high (22.86 to 45.71 Hz) frequency bands. These high frequency differences in both types of PNs could have particular relevance for recruiting cellular activity in higher brain centers such as mushroom body Kenyon cells. In contrast, neurons in the specialized pheromone-responsive area of the moth antennal lobe exhibited few stimulus-dependent differences in temporal response features. These results provide interesting insights on early insect olfactory processing and introduce a novel comparative approach for spike train analysis applicable to a variety of neuronal data sets.

Likelihood Methods for Point Processes with Refractoriness

Likelihood-based encoding models founded on point processes have received significant attention in the literature because of their ability to reveal the information encoded by spiking neural populations. We propose an approximation to the likelihood of a point-process model of neurons that holds under assumptions about the continuous time process that are physiologically reasonable for neural spike trains: the presence of a refractory period, the predictability of the conditional intensity function, and its integrability. These are properties that apply to a large class of point processes arising in applications other than neuroscience. The proposed approach has several advantages over conventional ones. In particular, one can use standard fitting procedures for generalized linear models based on iteratively reweighted least squares while improving the accuracy of the approximation to the likelihood and reducing bias in the estimation of the parameters of the underlying continuous-time model. As a result, the proposed approach can use a larger bin size to achieve the same accuracy as conventional approaches would with a smaller bin size. This is particularly important when analyzing neural data with high mean and instantaneous firing rates. We demonstrate these claims on simulated and real neural spiking activity. By allowing a substantive increase in the required bin size, our algorithm has the potential to lower the barrier to the use of point-process methods in an increasing number of applications.