Low Firing Rates Research Articles

C.01.01 - Cognitive domains affected by major depressive disorder (MDD)

Obsessive-compulsive disorder (OCD) is among the most disabling chronic psychiatric disorders and has a significant negative impact on multiple domains of quality of life. For patients suffering from severe refractory OCD, deep brain stimulation (DBS) of the subthalamic nucleus (STN) has been applied. Reviewing the literature of the last years we believe that through its central position within the cortico-basal ganglia-thalamocortical circuits, the STN has a coordinating role in decision-making and action-selection mechanisms. Dysfunctional information-processing at the level of the STN is responsible for some of the core symptoms of OCD. Research confirms an electrophysiological dysfunction in the associative and limbic (non-motor) parts of the STN. Compared to Parkinson׳s disease patients, STN neurons in OCD exhibit a lower firing rate, less frequent but longer bursts, increased burst activity in the anterior ventromedial area, an asymmetrical left-sided burst distribution, and a predominant oscillatory activity in the δ-band. Moreover, there is direct evidence for the involvement of the STN in both checking behavior and OCD symptoms, which are both related to changes in electrophysiological activity in the non-motor STN. Through a combination of mechanisms, DBS of the STN seems to interrupt the disturbed information-processing, leading to a normalization of connectivity within the cortico-basal ganglia-thalamocortical circuits and consequently to a reduction in symptoms. In conclusion, based on the STN׳s strategic position within cortico-basal ganglia-thalamocortical circuits and its involvement in action-selection mechanisms that are responsible for some of the core symptoms of OCD, the STN is a mechanism-based target for DBS in OCD.

Chaotic Resonance in Coupled Inferior Olive Neurons with the Llinás Approach Neuron Model.

It is well known that cerebellar motor control is fine-tuned by the learning process adjusted according to rich error signals from inferior olive (IO) neurons. Schweighofer and colleagues proposed that these signals can be produced by chaotic irregular firing in the IO neuron assembly; such chaotic resonance (CR) was replicated in their computer demonstration of a Hodgkin-Huxley (HH)-type compartment model. In this study, we examined the response of CR to a periodic signal in the IO neuron assembly comprising the Llinás approach IO neuron model. This system involves empirically observed dynamics of the IO membrane potential and is simpler than the HH-type compartment model. We then clarified its dependence on electrical coupling strength, input signal strength, and frequency. Furthermore, we compared the physiological validity for IO neurons such as low firing rate and sustaining subthreshold oscillation between CR and conventional stochastic resonance (SR) and examined the consistency with asynchronous firings indicated by the previous model-based studies in the cerebellar learning process. In addition, the signal response of CR and SR was investigated in a large neuron assembly. As the result, we confirmed that CR was consistent with the above IO neuron's characteristics, but it was not as easy for SR.

Cardiac Arrest-Induced Global Brain Hypoxia-Ischemia during Development Affects Spontaneous Activity Organization in Rat Sensory and Motor Thalamocortical Circuits during Adulthood.

Normal maturation of sensory information processing in the cortex requires patterned synaptic activity during developmentally regulated critical periods. During early development, spontaneous synaptic activity establishes required patterns of synaptic input, and during later development it influences patterns of sensory experience-dependent neuronal firing. Thalamocortical neurons occupy a critical position in regulating the flow of patterned sensory information from the periphery to the cortex. Abnormal thalamocortical inputs may permanently affect the organization and function of cortical neuronal circuits, especially if they occur during a critical developmental window. We examined the effect of cardiac arrest (CA)-associated global brain hypoxia-ischemia in developing rats on spontaneous and evoked firing of somatosensory thalamocortical neurons and on large-scale correlations in the motor thalamocortical circuit. The mean spontaneous and sensory-evoked firing rate activity and variability were higher in CA injured rats. Furthermore, spontaneous and sensory-evoked activity and variability were correlated in uninjured rats, but not correlated in neurons from CA rats. Abnormal activity patterns of ventroposterior medial nucleus (VPm) neurons persisted into adulthood. Additionally, we found that neurons in the entopeduncular nucleus (EPN) in the basal ganglia had lower firing rates yet had higher variability and higher levels of burst firing after injury. Correlated levels of power in local field potentials (LFPs) between the EPN and the motor cortex (MCx) were also disrupted by injury. Our findings indicate that hypoxic-ischemic injury during development leads to abnormal spontaneous and sensory stimulus-evoked input patterns from thalamus to cortex. Abnormal thalamic inputs likely permanently and detrimentally affect the organization of cortical circuitry and processing of sensory information. Hypoxic-ischemic injury also leads to abnormal single neuron and population level activity in the basal ganglia that may contribute to motor dysfunction after injury. Combination of deficits in sensory and motor thalamocortical circuit function may negatively impact sensorimotor integration in CA survivors. Modulation of abnormal activity patterns post-injury may represent a novel therapeutic target to improve neurologic function in survivors.

Deletion of the murine ATP/UTP receptor P2Y2 alters mechanical and thermal response properties in polymodal cutaneous afferents

P2Y2 is a member of the P2Y family of G protein-coupled nucleotide receptors that is widely co-expressed with TRPV1 in peripheral sensory neurons of the dorsal root ganglia. To characterize P2Y2 function in cutaneous afferents, intracellular recordings from mouse sensory neurons were made using an ex vivo preparation in which hindlimb skin, saphenous nerve, dorsal root ganglia and spinal cord are dissected intact. The peripheral response properties of individual cutaneous C-fibers were analyzed using digitally controlled mechanical and thermal stimuli in male P2Y2+/+ and P2Y2−/− mice. Selected sensory neurons were labeled with Neurobiotin and further characterized by immunohistochemistry. In wildtype preparations, C-fibers responding to both mechanical and thermal stimuli (CMH or CMHC) preferentially bound the lectin marker IB4 and were always immunonegative for TRPV1. Conversely, cells that fired robustly to noxious heat, but were insensitive to mechanical stimuli, were TRPV1-positive and IB4-negative. P2Y2 gene deletion resulted in reduced firing by TRPV1-negative CMH fibers to a range of heat stimuli. However, we also identified an atypical population of IB4-negative, TRPV1-positive CMH fibers. Compared to wildtype CMH fibers, these TRPV1-positive neurons exhibited lower firing rates in response to mechanical stimulation, but had increased firing to noxious heat (43–51°C). Collectively, these results demonstrate that P2Y2 contributes to response properties of cutaneous afferents, as P2Y2 deletion reduces responsiveness of conventional unmyelinated polymodal afferents to heat and appears to result in the acquisition of mechanical responsiveness in a subset of TRPV1-expressing afferents.

Role of CA3 theta-modulated interneurons during the transition to spontaneous seizures

Multiple studies have observed heterogeneous neuronal firing patterns as a local network transitions to spontaneous seizures. We demonstrated that separately examining interneurons and pyramidal cells during this transition in a rat model of temporal lobe epilepsy elucidates some of this heterogeneity. Recently, it was demonstrated that classifying cells into specific theta-related subtypes further clarified the heterogeneity. Moreover, changes in neuronal synchrony with the local field potential were identified and determined to be specific to interneurons during the transition to seizures. To extend our understanding of the chronic changes in epileptic networks, we examined field potentials and single neuron activity in the CA3 hippocampus of pilocarpine-treated rats during interictal periods and compared these to neuronal activity in healthy controls and during preictal periods. Neurons were classified into theta-subtypes based on changes in firing patterns during theta periods. As previously reported, we find a high probability of theta oscillations before seizure onset and a selective increase in theta-on interneuron firing rate immediately preceding seizure onset. However, we also find overall slower theta rhythm and a general decrease in subtype-specific firing during interictal periods compared to that in control animals. The decrease in subtype specific interneuron activity is accompanied by increases in synchrony. Exceptionally, theta-on interneurons, that selectively increase their firing rate at seizure onset, maintain similar firing rates and synchrony as controls during interictal period. These data suggest that increased synchrony during interictal periods may compensate for low firing rates creating instability during theta that is prone to seizure initiation via a transition to hyper-synchronous activation of theta-on interneurons.

Intrapericardial capsaicin and bradykinin induce different cardiac-somatic and cardiovascular reflexes in rats.

Patients with myocardial infarction experience various types of chest pain and autonomic disturbance symptoms. Studies in rats have shown that pericardial infusions of certain chemicals induce cardiac-related muscle pain and cardiovascular reflexes. In the present study, bradykinin or capsaicin was injected into the pericardial sac and the resulting cardiac-somatic reflexes and blood pressure (BP) alterations were record. We found that the cardiac-somatic reflex induced by bradykinin had a longer latency, shorter duration, and lower firing rate than that induced by capsaicin (p<0.05). We also found that bradykinin induced a hypertensive response (p<0.05), while capsaicin induced a hypotensive response (p<0.05). Bilateral vagotomy had no effect on the cardiac-somatic reflex induced by bradykinin (p>0.05) but reduced the reflex induced by capsaicin (p<0.05). However, vagotomy had no effect on the BP alterations induced by both bradykinin and capsaicin (p>0.05). These results suggest that bradykinin and capsaicin activate different pathways to induce cardiac-somatic and cardiovascular reflexes and that the vagus nerve is involved in TRPV1-related muscle pain modulation.

Motor unit firing rates of the gastrocnemii during maximal and sub-maximal isometric contractions in young and old men

The triceps surae comprises an important group of muscles for human posture and gait. The soleus unlike other limb muscles shows atypical lower firing rates in both old and young adults across various voluntary strength levels, including maximal contractions. The other portion of the triceps surae, the gastrocnemii has not been explored in aging, and despite anatomic, histochemical and age-related morphological differences, they share many common functions with soleus. During multiple visits, 10 active young (23–33years) and 10 active old participants (76–86years) performed a series of plantar flexor isometric contractions at a range of contraction intensities including maximal voluntary contraction (MVC) with tungsten microelectrodes inserted into the lateral (LG) and medial (MG) gastrocnemius. Despite equal and near maximal voluntary activation (VA) (∼98%), MVC torque was ∼46% lower, twitch tension was ∼34% lower, and contractile speed was ∼15% slower in the old men compared with the young. At all isometric torque levels tested (25, 50, 75 and 100% MVC) there were no statistically significant differences in mean motor unit firing rates (MUFRs) between young and old men. In both groups, the range of mean MU firing rates was similar (∼8Hz at 25% MVC to ∼22Hz at 100% MVC). The structural age-related changes in the gastrocnemii are not reflected in neural drive adaptations, indicating that MUFRs may not be a common feature with aging and other factors such as habitual use or anatomical location may be influential.

The Roles of the Olivocerebellar Pathway in Motor Learning and Motor Control. A Consensus Paper.

For many decades, the predominant view in the cerebellar field has been that the olivocerebellar system's primary function is to induce plasticity in the cerebellar cortex, specifically, at the parallel fiber-Purkinje cell synapse. However, it has also long been proposed that the olivocerebellar system participates directly in motor control by helping to shape ongoing motor commands being issued by the cerebellum. Evidence consistent with both hypotheses exists; however, they are often investigated as mutually exclusive alternatives. In contrast, here, we take the perspective that the olivocerebellar system can contribute to both the motor learning and motor control functions of the cerebellum and might also play a role in development. We then consider the potential problems and benefits of it having multiple functions. Moreover, we discuss how its distinctive characteristics (e.g., low firing rates, synchronization, and variable complex spike waveforms) make it more or less suitable for one or the other of these functions, and why having multiple functions makes sense from an evolutionary perspective. We did not attempt to reach a consensus on the specific role(s) the olivocerebellar system plays in different types of movements, as that will ultimately be determined experimentally; however, collectively, the various contributions highlight the flexibility of the olivocerebellar system, and thereby suggestthat it has the potential to act in both the motor learning and motor control functions of the cerebellum.

Parvalbumin-Expressing GABAergic Neurons in Mouse Barrel Cortex Contribute to Gating a Goal-Directed Sensorimotor Transformation.

SummarySensory processing in neocortex is primarily driven by glutamatergic excitation, which is counterbalanced by GABAergic inhibition, mediated by a diversity of largely local inhibitory interneurons. Here, we trained mice to lick a reward spout in response to whisker deflection, and we recorded from genetically defined GABAergic inhibitory neurons in layer 2/3 of the primary somatosensory barrel cortex. Parvalbumin-expressing (PV), vasoactive intestinal peptide-expressing (VIP), and somatostatin-expressing (SST) neurons displayed distinct action potential firing dynamics during task performance. Whereas SST neurons fired at low rates, both PV and VIP neurons fired at high rates both spontaneously and in response to whisker stimulation. After an initial outcome-invariant early sensory response, PV neurons had lower firing rates in hit trials compared to miss trials. Optogenetic inhibition of PV neurons during this time period enhanced behavioral performance. Hence, PV neuron activity might contribute causally to gating the sensorimotor transformation of a whisker sensory stimulus into licking motor output.

Entrainment in up and down states of neural populations: non-smooth and stochastic models.

Slow oscillations in firing rate of neural populations are commonly observed during slow wave sleep. These oscillations are partitioned into up and down states, where the population switches between high and low firing rates (Sanchez-Vives and McCormick in Nat Neurosci 3:1027-1034, 2000). Transitions between up and down states can be synchronized at considerably long ranges (Volgushev et al. in J Neurosci 26:5665-5672, 2006). To explore how external perturbations shape the phase of slow oscillations, we analyze a reduced model of up and down state transitions involving a population neural activity variable and a global adaptation variable. The adaptation variable represents the average of all the slow hyperpolarizing currents received by neurons in a large population. Recurrent connectivity leads to a bistable neural population, where a low firing rate state coexists with a high firing rate state, where persistent activity is maintained via excitatory connections. Adaptation eventually inactivates the high activity state, and the low activity state then persists until adaptation has significantly decayed. We analyze the phase response of the rate model by taking advantage of the separation of timescales between the fast activity and slow adaptation variables. This analysis reveals that perturbations to the neural activity variable have a considerably weaker effect on the oscillation phase than adaptation perturbations. When noise is not incorporated into the rate model, the period of the slow oscillation is determined by the timescale of the slow adaptation variable. In the presence of noise, times at which the population transitions between the low and high activity states become variable. This is because the rise and decay of the adaptation variable is now stochastically-driven, leading to a distribution of transition times. Interestingly, common noise in the adaptation variable can lead to a correlation of two distinct slow oscillating populations. This effect is still significant in the event that each population contains its own local sources of noise. We also show this phenomenon can occur a spiking network. Our results demonstrate the relative contributions of excitatory input and hyperpolarizing current fluctuations on the phase of slow oscillations.

Response reliability observed with voltage-sensitive dye imaging of cortical layer 2/3: the probability of activation hypothesis

A central assertion in the study of neural processing is that our perception of the environment directly reflects the activity of our sensory neurons. This assertion reinforces the intuition that the strength of a sensory input directly modulates the amount of neural activity observed in response to that sensory feature: an increase in the strength of the input yields a graded increase in the amount of neural activity. However, cortical activity across a range of sensory pathways can be sparse, with individual neurons having remarkably low firing rates, often exhibiting suprathreshold activity on only a fraction of experimental trials. To compensate for this observed apparent unreliability, it is assumed that instead the local population of neurons, although not explicitly measured, does reliably represent the strength of the sensory input. This assumption, however, is largely untested. In this study, using wide-field voltage-sensitive dye (VSD) imaging of the somatosensory cortex in the anesthetized rat, we show that whisker deflection velocity, or stimulus strength, is not encoded by the magnitude of the population response at the level of cortex. Instead, modulation of whisker deflection velocity affects the likelihood of the cortical response, impacting the magnitude, rate of change, and spatial extent of the cortical response. An ideal observer analysis of the cortical response points to a probabilistic code based on repeated sampling across cortical columns and/or time, which we refer to as the probability of activation hypothesis. This hypothesis motivates a range of testable predictions for both future electrophysiological and future behavioral studies.

An Alternative Method For The Development Of 3D Engineered Neuronal Cultures

An Alternative Method For The Development Of 3D Engineered Neuronal Cultures

A stochastic version of the Potjans-Diesmann cortical column model

Event Abstract Back to Event A stochastic version of the Potjans-Diesmann cortical column model Vinicius L. Cordeiro1, Renan O. Shimoura1, Nilton L. Kamiji1, Osame Kinouchi1 and Antonio C. Roque1* 1 Universidade de São Paulo, Departamento de Física, Brazil Experimental evidence suggests that neurons and neural circuits display stochastic variability [1] and, therefore, it is important to have neural models that capture this stochasticity. There are basically two types of noise model for a neuron [2]: (1) spike generation is modeled deterministically and noise enters the dynamics via additional stochastic terms; or (2) spike generation is directly modeled as a stochastic process. Recently, Galves and Löcherbach [3] introduced a neural model of the latter type in which the firing of a neuron at a given time t is a random event with probability given by a monotonically increasing function of its membrane potential V. The model of Galves and Löcherbach (GL) has as one of its components a graph of interactions between neurons. In this work we consider that this graph has the structure of the Potjans and Diesmann network model of a cortical column [4]. The model of Potjans and Diesmann has four layers and two neuron types, excitatory and inhibitory, so that there are eight cell populations. The population-specific neuron densities and connectivity are taken from comprehensive anatomical and electrophysiological studies [5-6], and the model has approximately 80,000 neurons and 300,000,000 synapses. We adjusted the parameters of the firing probability of the GL model to reproduce the firing behavior of regular (excitatory) and fast (inhibitory) spiking neurons [7]. Then, we replaced the leaky integrate-and-fire neurons of the original Potjans-Diesmann model by these stochastic neurons to obtain a stochastic version of the Potjans-Diesmann model. The parameters of the model are the weights we and wi of the excitatory and inhibitory synaptic weights of the GL model [3]. We studied the firing patterns of the eight cell populations of the stochastic model in the absence of external input and characterized their behavior in the two-dimensional diagram spanned by the excitatory and inhibitory synaptic weights. For a balanced case in which the network activity is asynchronous and irregular the properties of the stochastic model are similar to the properties of the original Potjans-Diesmann model. Different neural populations have different firing rates and inhibitory neurons have higher firing rates than excitatory neurons. In particular, the stochastic model emulates the very low firing rates of layer 2/3 observed in the original model and also experimentally [4]. We also submitted the network to random input spikes applied to layers 4 and 6 to mimic thalamic inputs, as done by Potjans and Diesmann [4], and studied the propagation of activity across layers. In conclusion, the stochastic version of the Potjans-Diesmann model can be a useful replacement for the original Potjans-Diesmann model in studies that require a comparison between stochastic and deterministic models. Acknowledgements This article was produced as part of the activities of FAPESP Research, Innovation and Dissemination Center for Neuromathematics (grant 2013/07699-0), S.Paulo Research Foundation). VLC is supported by a CNPq-PIBIC grant. NLK is supported by a FAPESP postdoctorate grant (2016/03855-5). OK receives support from CNAIPS-USP. ACR is supported by a CNPq research grant (306251/2014-0).

Age-related neuromuscular changes affecting human vastus lateralis.

Key points Skeletal muscle size and strength decline in older age.The vastus lateralis, a large thigh muscle, undergoes extensive neuromuscular remodelling in healthy ageing, as characterized by a loss of motor neurons, enlargement of surviving motor units and instability of neuromuscular junction transmission.The loss of motor axons and changes to motor unit potential transmission precede a clinically‐relevant loss of muscle mass and function. The anterior thigh muscles are particularly susceptible to muscle loss and weakness during ageing, although how this is associated with changes to neuromuscular structure and function in terms of motor unit (MU) number, size and MU potential (MUP) stability remains unclear. Intramuscular (I.M.) and surface electromyographic signals were recorded from the vastus lateralis (VL) during voluntary contractions held at 25% maximal knee extensor strength in 22 young (mean ± SD, 25.3 ± 4.8 years) and 20 physically active older men (71.4 ± 6.2 years). MUP size, firing rates, phases, turns and near fibre (NF) jiggle were determined and MU number estimates (MUNEs) were made by comparing average surface MUP with maximal electrically‐evoked compound muscle action potentials. Quadriceps cross‐sectional area was measured by magnetic resonance imaging. In total, 379 individual MUs were sampled in younger men and 346 in older men. Compared to the MU in younger participants, those in older participants had 8% lower firing rates and larger MUP size (+25%), as well as increased complexity, as indicated by phases (+13%), turns (+20%) and NF jiggle (+11%) (all P < 0.0005). The MUNE values (derived from the area of muscle in range of the surface‐electrode) in older participants were ∼70% of those in the young (P < 0.05). Taking into consideration the 30% smaller cross‐sectional area of the VL, the total number of MUs in the older muscles was between 50% and 60% lower compared to in young muscles (P < 0.0005). A large portion of the VL MU pool is lost in older men and those recruited during moderate intensity contractions were enlarged and less stable. These MU changes were evident before clinically relevant changes to muscle function were apparent; nevertheless, the changes in MU number and size are probably a prelude to future movement problems.

Acid gas emissions from structural clay products containing secondary resources: foundry sand dust and Waelz slag

The estimation of the main changes that occur on heating foundry sand dust (FSD), Waelz slag (WS) and the three clays (C1, C2, C3) used to manufacture three ceramic products, wall bricks (850 °C), roof tiles (950 °C) and face bricks (1050 °C), have been studied at laboratory scale combining different analytical techniques as assessing tool. This involved using differential scanning calorimetry (DSC) and X-ray diffraction (XRD) to characterise changes in the crystalline phases present and evolved gas analysis (EGA) to identify the temperatures at which emissions occurThe combination of these techniques, traditionally used to characterise materials, has been used as an indirect measurement to assess the acid gas emissions during ceramic processes. Acid gas emissions were estimated using mass balance data obtained on compacted samples of the materials by comparing the chemical results for the samples before and after the thermal treatment at 10 °C/min to the sintering temperature of the ceramic products. The percentage reduction in the content of the pollutants during firing was assessed in a representative number of ternary mixes (of clay, FSD and WS) selected using mixture design of experiments, fired simulating the industrial firing cycles used to obtain the products, and correlated to the acid gas emissions. A clear relationship was found between HF and SO2 emissions and the CaO content in the as-received materials. Higher temperatures and lower firing rates gave higher emissions. High WS content was found to decrease the emissions of SO2 and HF below certain temperatures due to the formation of CaF2 and CaSO4 while the emissions of HCl were controlled by the firing temperature. The mineral phases containing Cl decompose below the firing temperatures (850–1050 °C) promoting its emission.

Information filtering in resonant neurons.

Neuronal information transmission is frequency specific. In single cells, a band-pass like frequency preference can arise from the subthreshold dynamics of the membrane potential, shaped by properties of the cell's membrane and its ionic channels. In these cases, a cell is termed resonant and its membrane impedance spectrum exhibits a peak at non-vanishing frequencies. Here, we show that this frequency selectivity of neuronal response amplitudes need not translate into a similar frequency selectivity of information transfer. In particular, neurons with resonant but linear subthreshold voltage dynamics (without threshold) do not show a resonance of information transfer at the level of subthreshold voltage; the corresponding coherence has low-pass characteristics. Interestingly, we find that when combined with nonlinearities, subthreshold resonances do shape the frequency dependence of coherence and the peak in the subthreshold impedance translates to a peak in the coherence function. In other words, the nonlinearity inherent to spike generation allows a subthreshold impedance resonance to shape a resonance of voltage-based information transfer. We demonstrate such nonlinearity-mediated band-pass filtering of information at frequencies close to the subthreshold impedance resonance in three different model systems: the resonate-and-fire model, the conductance-based Morris-Lecar model, and linear resonant dynamics combined with a simple static nonlinearity. In the spiking neuron models, the band-pass filtering is most pronounced for low firing rates and a high variability of interspike intervals, similar to the spiking statistics observed in vivo. We show that band-pass filtering is achieved by reducing information transfer over low-frequency components and, consequently, comes along with an overall reduction of information rate. Our work highlights the crucial role of nonlinearities for the frequency dependence of neuronal information transmission.

Ion channel degeneracy enables robust and tunable neuronal firing rates

Firing rate is an important means of encoding information in the nervous system. To reliably encode a wide range of signals, neurons need to achieve a broad range of firing frequencies and to move smoothly between low and high firing rates. This can be achieved with specific ionic currents, such as A-type potassium currents, which can linearize the frequency-input current curve. By applying recently developed mathematical tools to a number of biophysical neuron models, we show how currents that are classically thought to permit low firing rates can paradoxically cause a jump to a high minimum firing rate when expressed at higher levels. Consequently, achieving and maintaining a low firing rate is surprisingly difficult and fragile in a biological context. This difficulty can be overcome via interactions between multiple currents, implying a need for ion channel degeneracy in the tuning of neuronal properties.

Postnatal development attunes olfactory bulb mitral cells to high-frequency signaling.

Mitral cells (MCs) are a major class of principal neurons in the vertebrate olfactory bulb, conveying odor-evoked activity from the peripheral sensory neurons to olfactory cortex. Previous work has described the development of MC morphology and connectivity during the first few weeks of postnatal development. However, little is known about the postnatal development of MC intrinsic biophysical properties. To understand stimulus encoding in the developing olfactory bulb, we have therefore examined the development of MC intrinsic biophysical properties in acute slices from postnatal day (P)7-P35 mice. Across development, we observed systematic changes in passive membrane properties and action potential waveforms consistent with a developmental increase in sodium and potassium conductances. We further observed developmental decreases in hyperpolarization-evoked membrane potential sag and firing regularity, extending recent links between MC sag heterogeneity and firing patterns. We then applied a novel combination of statistical analyses to examine how the evolution of these intrinsic biophysical properties specifically influenced the representation of fluctuating stimuli by MCs. We found that immature MCs responded to frozen fluctuating stimuli with lower firing rates, lower spike-time reliability, and lower between-cell spike-time correlations than more mature MCs. Analysis of spike-triggered averages revealed that these changes in spike timing were driven by a developmental shift from broad integration of inputs to more selective detection of coincident inputs. Consistent with this shift, generalized linear model fits to MC firing responses demonstrated an enhanced encoding of high-frequency stimulus features by mature MCs.

Inhibitory Gating of Input Comparison in the CA1 Microcircuit

Spatial and temporal features of synaptic inputs engage integration mechanisms on multiple scales, including presynaptic release sites, postsynaptic dendrites, and networks of inhibitory interneurons. Here we investigate how these mechanisms cooperate to filter synaptic input in hippocampal area CA1. Dendritic recordings from CA1 pyramidal neurons reveal that proximal inputs from CA3 as well as distal inputs from entorhinal cortex layer III (ECIII) sum sublinearly or linearly at low firing rates due to feedforward inhibition, but sum supralinearly at high firing rates due to synaptic facilitation, producing a high-pass filter. However, during ECIII and CA3 input comparison, supralinear dendritic integration is dynamically balanced by feedforward and feedback inhibition, resulting in suppression of dendritic complex spiking. We find that a particular subpopulation of CA1 interneurons expressing neuropeptide Y (NPY) contributes prominently to this dynamic filter by integrating both ECIII and CA3 input pathways and potently inhibiting CA1 pyramidal neuron dendrites.

Neuronal response impedance mechanism implementing cooperative networks with low firing rates and μs precision.

Realizations of low firing rates in neural networks usually require globally balanced distributions among excitatory and inhibitory links, while feasibility of temporal coding is limited by neuronal millisecond precision. We show that cooperation, governing global network features, emerges through nodal properties, as opposed to link distributions. Using in vitro and in vivo experiments we demonstrate microsecond precision of neuronal response timings under low stimulation frequencies, whereas moderate frequencies result in a chaotic neuronal phase characterized by degraded precision. Above a critical stimulation frequency, which varies among neurons, response failures were found to emerge stochastically such that the neuron functions as a low pass filter, saturating the average inter-spike-interval. This intrinsic neuronal response impedance mechanism leads to cooperation on a network level, such that firing rates are suppressed toward the lowest neuronal critical frequency simultaneously with neuronal microsecond precision. Our findings open up opportunities of controlling global features of network dynamics through few nodes with extreme properties.