Propagation of correlated activity through multiple stages of a neural circuit

Dynamic top-down biasing implements rapid adaptive changes to individual movements

Complex behaviors depend on the coordinated activity of neural ensembles in interconnected brain areas. The behavioral function of such coordination, often measured as co-fluctuations in neural activity across areas, is poorly understood. One hypothesis is that rapidly varying co-fluctuations may be a signature of moment-by-moment task-relevant influences of one area on another. We tested this possibility for error-corrective adaptation of birdsong, a form of motor learning which has been hypothesized to depend on the top-down influence of a higher-order area, LMAN (lateral magnocellular nucleus of the anterior nidopallium), in shaping moment-by-moment output from a primary motor area, RA (robust nucleus of the arcopallium). In paired recordings of LMAN and RA in singing birds, we discovered a neural signature of a top-down influence of LMAN on RA, quantified as an LMAN-leading co-fluctuation in activity between these areas. During learning, this co-fluctuation strengthened in a premotor temporal window linked to the specific movement, sequential context, and acoustic modification associated with learning. Moreover, transient perturbation of LMAN activity specifically within this premotor window caused rapid occlusion of pitch modifications, consistent with LMAN conveying a temporally localized motor-biasing signal. Combined, our results reveal a dynamic top-down influence of LMAN on RA that varies on the rapid timescale of individual movements and is flexibly linked to contexts associated with learning. This finding indicates that inter-area co-fluctuations can be a signature of dynamic top-down influences that support complex behavior and its adaptation.

Signatures of cochlear processing in neuronal coding of auditory information

The vertebrate ear is endowed with remarkable perceptual capabilities. The faintest sounds produce vibrations of magnitudes comparable to those generated by thermal noise and can nonetheless be detected through efficient amplification of small acoustic stimuli. Two mechanisms have been proposed to underlie such sound amplification in the mammalian cochlea: somatic electromotility and active hair-bundle motility. These biomechanical mechanisms may work in concert to tune auditory sensitivity. In addition to amplitude sensitivity, the hearing system shows exceptional frequency discrimination allowing mammals to distinguish complex sounds with great accuracy. For instance, although the wide hearing range of humans encompasses frequencies from 20 Hz to 20 kHz, our frequency resolution extends to one-thirtieth of the interval between successive keys on a piano. In this article, we review the different cochlear mechanisms underlying sound encoding in the auditory system, with a particular focus on the frequency decomposition of sounds. The relation between peak frequency of activation and location along the cochlea - known as tonotopy - arises from multiple gradients in biophysical properties of the sensory epithelium. Tonotopic mapping represents a major organizational principle both in the peripheral hearing system and in higher processing levels and permits the spectral decomposition of complex tones. The ribbon synapses connecting sensory hair cells to auditory afferents and the downstream spiral ganglion neurons are also tuned to process periodic stimuli according to their preferred frequency. Though sensory hair cells and neurons necessarily filter signals beyond a few kHz, many animals can hear well beyond this range. We finally describe how the cochlear structure shapes the neural code for further processing in order to send meaningful information to the brain. Both the phase-locked response of auditory nerve fibers and tonotopy are key to decode sound frequency information and place specific constraints on the downstream neuronal network.

Distinct roles of parvalbumin and somatostatin interneurons in gating the synchronization of spike times in the neocortex

Synchronization of precise spike times across multiple neurons carries information about sensory stimuli. Inhibitory interneurons are suggested to promote this synchronization, but it is unclear whether distinct interneuron subtypes provide different contributions. To test this, we examined single-unit recordings from barrel cortex in vivo and used optogenetics to determine the contribution of parvalbumin (PV)- and somatostatin (SST)-positive interneurons to the synchronization of spike times across cortical layers. We found that PV interneurons preferentially promote the synchronization of spike times when instantaneous firing rates are low (<12 Hz), whereas SST interneurons preferentially promote the synchronization of spike times when instantaneous firing rates are high (>12 Hz). Furthermore, using a computational model, we demonstrate that these effects can be explained by PV and SST interneurons having preferential contributions to feedforward and feedback inhibition, respectively. Our findings demonstrate that distinct subtypes of inhibitory interneurons have frequency-selective roles in the spatiotemporal synchronization of precise spike times.

Expression of the potassium-chloride co-transporter, KCC2, within the avian song system

Songbirds learn to produce vocalizations early in life by listening to, then copying the songs of conspecific males. The anterior forebrain pathway, homologous to a basal ganglia-forebrain circuit, is essential for song learning. The projection between the striato-pallidal structure, Area X, and the medial portion of the dorsolateral thalamic nucleus (DLM) is strongly hyperpolarizing in adults, due to a very negative chloride reversal potential (Person & Perkel, Neuron 46:129-140, 2005). The chloride reversal potential is determined, in part, by the expression level of a neuron-specific potassium-chloride cotransporter, KCC2, which is developmentally upregulated in mammals. To determine whether a similar upregulation in KCC2 expression occurs at the Area X to DLM synapse during development, we examined the expression level of KCC2 in adult zebra finches across the song system as well as during development in the Area X - DLM synapse. We demonstrate that KCC2 is expressed in a subset of neurons throughout the song system, including HVC (used as a proper name), robust nucleus of the arcopallium (RA), lateral magnocellular nucleus of the anterior nidopallium (LMAN), Area X, and DLM. The majority of pallidal-like projection neurons in Area X showed KCC2 immunoreactivity. In adults, KCC2 expression was robust within DLM, and was upregulated between 14 and 24 days post hatching, before the onset of song learning. Light and electron microscopic analysis indicated that KCC2 immunoreactivity is strongly associated with the plasma membrane. Thus, in the song system as in the mammalian brain, KCC2 expression is well placed to modulate the GABAA reversal potential.

Dopaminergic modulation of basal ganglia output through coupled excitation-inhibition

Learning and maintenance of skilled movements require exploration of motor space and selection of appropriate actions. Vocal learning and social context-dependent plasticity in songbirds depend on a basal ganglia circuit, which actively generates vocal variability. Dopamine in the basal ganglia reduces trial-to-trial neural variability when the bird engages in courtship song. Here, we present evidence for a unique, tonically active, excitatory interneuron in the songbird basal ganglia that makes strong synaptic connections onto output pallidal neurons, often linked in time with inhibitory events. Dopamine receptor activity modulates the coupling of these excitatory and inhibitory events in vitro, which results in a dynamic change in the synchrony of a modeled population of basal ganglia output neurons receiving excitatory and inhibitory inputs. The excitatory interneuron thus serves as one biophysical mechanism for the introduction or modulation of neural variability in this circuit.

Dysregulated corticostriatal activity in open-field behavior and the head-twitch response induced by the hallucinogen 2,5-dimethoxy-4-iodoamphetamine

The substituted amphetamine, 2,5-dimethoxy-4-iodoamphetamine (DOI), is a hallucinogen that has been used to model a variety of psychiatric conditions. Here, we studied the effect of DOI on neural activity recorded simultaneously in the primary motor cortex (M1) and dorsal striatum of freely behaving FvB/N mice. DOI significantly decreased the firing rate of individually isolated neurons in M1 and dorsal striatum relative to pre-drug baseline. It also induced a bursting pattern of activity by increasing both the number of spikes within a burst and burst duration. In addition, DOI increased coincident firing between simultaneously recorded neuron pairs within the striatum and between M1 and dorsal striatum. Local field potential (LFP) activity also increased in coherence between M1 and dorsal striatum after DOI in the low frequency gamma band (30-50 Hz), while corticostriatal coherence in delta, theta, alpha, and beta activity decreased. We also assessed corticostriatal LFP activity in relation to the DOI-induced head-twitch response (HTR), a readily identifiable behavior used to assess potential treatments for the conditions it models. The HTR was associated with increased delta and decreased theta power in both M1 and dorsal striatum. Together, our results suggest that DOI dysregulates corticostriatal communication and that the HTR is associated with this dysregulation.

A Distributed Recurrent Network Contributes to Temporally Precise Vocalizations

How do forebrain and brainstem circuits interact to produce temporally precise and reproducible behaviors? Birdsong is an elaborate, temporally precise, and stereotyped vocal behavior controlled by a network of forebrain and brainstem nuclei. An influential idea is that song premotor neurons in a forebrain nucleus (HVC) form a synaptic chain that dictates song timing in a top-down manner. Here we combine physiological, dynamical, and computational methods to show that song timing is not generated solely by a mechanism localized to HVC but instead is the product of a distributed and recurrent synaptic network spanning the forebrain and brainstem, of which HVC is a component.

Naturalistic stimulation drives opposing heterosynaptic plasticity at two inputs to songbird cortex

Songbirds learn precisely sequenced motor skills (songs) subserved by distinct brain areas, including the premotor cortical analog HVC, which is essential for producing learned song, and a 'cortical'-basal ganglia loop required for song plasticity. Inputs from these nuclei converge in RA (robust nucleus of the arcopallium), making it a likely locus for song learning. However, activity-dependent synaptic plasticity has never been described in either input. Using a slice preparation, we found that stimulation patterns based on singing-related activity were able to drive opposing changes in the strength of RA's inputs: when one input was potentiated, the other was depressed, with the direction and magnitude of changes depending on the relative timing of stimulation of the inputs. Moreover, pharmacological manipulations that blocked synaptic plasticity in vitro also prevented reinforcement-driven changes to song in vivo. Together, these findings highlight the importance of precise timing in the basal ganglia-motor cortical interactions subserving adaptive motor skills.

Rhythmic cortical neurons increase their oscillations and sculpt basal ganglia signaling during motor learning

The function and modulation of neural circuits underlying motor skill may involve rhythmic oscillations (Feller, 1999; Marder and Goaillard, 2006; Churchland et al., 2012). In the proposed pattern generator for birdsong, the cortical nucleus HVC, the frequency and power of oscillatory bursting during singing increases with development (Crandall et al., 2007; Day et al., 2009). We examined the maturation of cellular activity patterns that underlie these changes. Single unit ensemble recording combined with antidromic identification (Day et al., 2011) was used to study network development in anesthetized zebra finches. Autocovariance quantified oscillations within single units. A subset of neurons oscillated in the theta/alpha/mu/beta range (8-20 Hz), with greater power in adults compared to juveniles. Across the network, the normalized oscillatory power in the 8-20 Hz range was greater in adults than juveniles. In addition, the correlated activity between rhythmic neuron pairs increased with development. We next examined the functional impact of the oscillators on the output neurons of HVC. We found that the firing of oscillatory neurons negatively correlated with the activity of cortico-basal ganglia neurons (HVC(X)s), which project to Area X (the song basal ganglia). If groups of oscillators work together to tonically inhibit and precisely control the spike timing of adult HVC(X)s with coordinated release from inhibition, then the activity of HVC(X)s in juveniles should be decreased relative to adults due to uncorrelated, tonic inhibition. Consistent with this hypothesis, HVC(X)s had lower activity in juveniles. These data reveal network changes that shape cortical-to-basal ganglia signaling during motor learning.

Directed functional connectivity matures with motor learning in a cortical pattern generator

Sequential motor skills may be encoded by feedforward networks that consist of groups of neurons that fire in sequence (Abeles 1991; Long et al. 2010). However, there has been no evidence of an anatomic map of activation sequence in motor control circuits, which would be potentially detectable as directed functional connectivity of coactive neuron groups. The proposed pattern generator for birdsong, the HVC (Long and Fee 2008; Vu et al. 1994), contains axons that are preferentially oriented in the rostrocaudal axis (Nottebohm et al. 1982; Stauffer et al. 2012). We used four-tetrode recordings to assess the activity of ensembles of single neurons along the rostrocaudal HVC axis in anesthetized zebra finches. We found an axial, polarized neural network in which sequential activity is directionally organized along the rostrocaudal axis in adult males, who produce a stereotyped song. Principal neurons fired in rostrocaudal order and with interneurons that were rostral to them, suggesting that groups of excitatory neurons fire at the leading edge of travelling waves of inhibition. Consistent with the synchronization of neurons by caudally travelling waves of inhibition, the activity of interneurons was more coherent in the orthogonal mediolateral axis than in the rostrocaudal axis. If directed functional connectivity within the HVC is important for stereotyped, learned song, then it may be lacking in juveniles, which sing a highly variable song. Indeed, we found little evidence for network directionality in juveniles. These data indicate that a functionally directed network within the HVC matures during sensorimotor learning and may underlie vocal patterning.

Circuit mechanisms revealed by spike-timing correlations in macaque area MT

We recorded simultaneously from pairs of motion-sensitive neurons in the middle temporal cortex (MT) of macaque monkeys and used cross-correlations in the timing of spikes between neurons to gain insights into cortical circuitry. We characterized the time course and stimulus dependency of the cross-correlogram (CCG) for each pair of neurons and of the auto-correlogram (ACG) of the individual neurons. For some neuron pairs, the CCG showed negative flanks that emerged next to the central peak during stimulus-driven responses. Similar negative flanks appeared in the ACG of many neurons. Negative flanks were most prevalent and deepest when the neurons were driven to high rates by visual stimuli that moved in the neurons' preferred directions. The temporal development of the negative flanks in the CCG coincided with a parallel, modest reduction of the noise correlation between the spike counts of the neurons. Computational analysis of a model cortical circuit suggested that negative flanks in the CCG arise from the excitation-triggered mutual cross-inhibition between pairs of excitatory neurons. Intracortical recurrent inhibition and afterhyperpolarization caused by intrinsic outward currents, such as the calcium-activated potassium current of small conductance, can both contribute to the negative flanks in the ACG. In the model circuit, stronger intracortical inhibition helped to maintain the temporal precision between the spike trains of pairs of neurons and led to weaker noise correlations. Our results suggest a neural circuit architecture that can leverage activity-dependent intracortical inhibition to adaptively modulate both the synchrony of spike timing and the correlations in response variability.

Comparison of LFP-based and spike-based spectro-temporal receptive fields and cross-correlation in cat primary auditory cortex

Multi-electrode array recordings of spike and local field potential (LFP) activity were made from primary auditory cortex of 12 normal hearing, ketamine-anesthetized cats. We evaluated 259 spectro-temporal receptive fields (STRFs) and 492 frequency-tuning curves (FTCs) based on LFPs and spikes simultaneously recorded on the same electrode. We compared their characteristic frequency (CF) gradients and their cross-correlation distances. The CF gradient for spike-based FTCs was about twice that for 2–40 Hz-filtered LFP-based FTCs, indicating greatly reduced frequency selectivity for LFPs. We also present comparisons for LFPs band-pass filtered between 4–8 Hz, 8–16 Hz and 16–40 Hz, with spike-based STRFs, on the basis of their marginal frequency distributions. We find on average a significantly larger correlation between the spike based marginal frequency distributions and those based on the 16–40 Hz filtered LFP, compared to those based on the 4–8 Hz, 8–16 Hz and 2–40 Hz filtered LFP. This suggests greater frequency specificity for the 16–40 Hz LFPs compared to those of lower frequency content. For spontaneous LFP and spike activity we evaluated 1373 pair correlations for pairs with >200 spikes in 900 s per electrode. Peak correlation-coefficient space constants were similar for the 2–40 Hz filtered LFP (5.5 mm) and the 16–40 Hz LFP (7.4 mm), whereas for spike-pair correlations it was about half that, at 3.2 mm. Comparing spike-pairs with 2–40 Hz (and 16–40 Hz) LFP-pair correlations showed that about 16% (9%) of the variance in the spike-pair correlations could be explained from LFP-pair correlations recorded on the same electrodes within the same electrode array. This larger correlation distance combined with the reduced CF gradient and much broader frequency selectivity suggests that LFPs are not a substitute for spike activity in primary auditory cortex.

Vocal babbling in songbirds requires the basal ganglia-recipient motor thalamus but not the basal ganglia

Young songbirds produce vocal "babbling," and the variability of their songs is thought to underlie a process of trial-and-error vocal learning. It is known that this exploratory variability requires the "cortical" component of a basal ganglia (BG) thalamocortical loop, but less understood is the role of the BG and thalamic components in this behavior. We found that large bilateral lesions to the songbird BG homolog Area X had little or no effect on song variability during vocal babbling. In contrast, lesions to the BG-recipient thalamic nucleus DLM (medial portion of the dorsolateral thalamus) largely abolished normal vocal babbling in young birds and caused a dramatic increase in song stereotypy. These findings support the idea that the motor thalamus plays a key role in the expression of exploratory juvenile behaviors during learning.

Improved stimulus representation by short interspike intervals in primary auditory cortex

We analyzed the receptive field information conveyed by interspike intervals (ISIs) in the auditory cortex. In the visual system, different ISIs may both code for different visual features and convey differing amounts of stimulus information. To determine their potential role in auditory signal processing, we obtained extracellular recordings in the primary auditory cortex (AI) of the cat while presenting a dynamic moving ripple stimulus and then used the responses to construct spectrotemporal receptive fields (STRFs). For each neuron, we constructed three STRFs, one for short-ISI events (ISI < 15 ms); one for isolated, long-ISI events (ISI > 15 ms); and one including all events. To characterize stimulus encoding, we calculated the feature selectivity and event information for each of the STRFs. Short-ISI spikes were more feature selective and conveyed information more efficiently. The different ISI regimens of AI neurons did not represent different stimulus features, but short-ISI spike events did contribute over-proportionately to the full spike train STRF information. Thus short-ISIs constitute a robust representation of auditory features, and they are particularly effective at driving postsynaptic activity. This suggests that short-ISI events are especially suited to provide noise immunity and high-fidelity information transmission in AI.

Spiking activity propagation in neuronal networks: reconciling different perspectives on neural coding

The brain is a highly modular structure. To exploit modularity, it is necessary that spiking activity can propagate from one module to another while preserving the information it carries. Therefore, reliable propagation is one of the key properties of a candidate neural code. Surprisingly, the conditions under which spiking activity can be propagated have received comparatively little attention in the experimental literature. By contrast, several computational studies in the last decade have addressed this issue. Using feedforward networks (FFNs) as a generic network model, they have identified two dynamical activity modes that support the propagation of either asynchronous (rate code) or synchronous (temporal code) spiking. Here, we review the dichotomy of asynchronous and synchronous propagation in FFNs, propose their integration into a single extended conceptual framework and suggest experimental strategies to test our hypothesis.

A few strong connections: optimizing information retention in neuronal avalanches

BACKGROUND

How living neural networks retain information is still incompletely understood. Two prominent ideas on this topic have developed in parallel, but have remained somewhat unconnected. The first of these, the "synaptic hypothesis," holds that information can be retained in synaptic connection strengths, or weights, between neurons. Recent work inspired by statistical mechanics has suggested that networks will retain the most information when their weights are distributed in a skewed manner, with many weak weights and only a few strong ones. The second of these ideas is that information can be represented by stable activity patterns. Multineuron recordings have shown that sequences of neural activity distributed over many neurons are repeated above chance levels when animals perform well-learned tasks. Although these two ideas are compelling, no one to our knowledge has yet linked the predicted optimum distribution of weights to stable activity patterns actually observed in living neural networks.

RESULTS

Here, we explore this link by comparing stable activity patterns from cortical slice networks recorded with multielectrode arrays to stable patterns produced by a model with a tunable weight distribution. This model was previously shown to capture central features of the dynamics in these slice networks, including neuronal avalanche cascades. We find that when the model weight distribution is appropriately skewed, it correctly matches the distribution of repeating patterns observed in the data. In addition, this same distribution of weights maximizes the capacity of the network model to retain stable activity patterns. Thus, the distribution that best fits the data is also the distribution that maximizes the number of stable patterns.

CONCLUSIONS

We conclude that local cortical networks are very likely to use a highly skewed weight distribution to optimize information retention, as predicted by theory. Fixed distributions impose constraints on learning, however. The network must have mechanisms for preserving the overall weight distribution while allowing individual connection strengths to change with learning.

Neuron-specific cholinergic modulation of a forebrain song control nucleus

Cholinergic activation profoundly affects vertebrate forebrain networks, but pathway, cell type, and modality specificity remain poorly understood. Here we investigated cell-specific cholinergic modulation of neurons in the zebra finch forebrain song control nucleus HVC using in vitro whole cell recordings. The HVC contains projection neurons that exclusively project to either another song motor nucleus RA (robust nucleus of the arcopallium) (HVC-RAn) or the basal ganglia Area X (HVC-Xn) and these populations are synaptically coupled by a network of GABAergic interneurons. Among HVC-RAn, we observed two physiologically distinct classes that fire either phasically or tonically to injected current. Muscarine excited phasic HVC-RAn and most HVC-Xn. Effects were observed under conditions of blockade of fast synaptic transmission and were reversed by atropine. In contrast, unlike what is commonly observed in mammalian systems, HVC interneurons were inhibited by muscarine and these effects were reversed by atropine. Thus cholinergic modulation reconfigures the HVC network in a more complex fashion than that implied by monolithic "gating." The two projection pathways are decoupled through suppression of the inhibitory network that links them, whereas each is simultaneously predominantly excited. We speculate that fluctuating cholinergic tone in HVC could modulate the interaction of song motor commands with basal ganglia circuitry associated with song perception and modification. Furthermore, if the in vitro distinction between RA-projecting neurons that we observed is also present in vivo, then the song system motor pathway exhibits greater physiological diversity than has been commonly assumed.

Behavioral state-dependent reconfiguration of song-related network activity and cholinergic systems

The song system of oscine songbirds mediates multiple complex perceptive and productive behaviors. These discrete behaviors are modulated according to external variables such as social context, directed attention and other forms of experience. In addition, sleep has been implicated in song learning and song maintenance. Changes in behavioral state are associated with complex changes in auditory responsiveness and tonic/bursting properties of song system neurons. Cholinergic input, principally from the basal forebrain has been implicated in some of these state-dependent properties. Cholinergic modulation may affect numerous song system nuclei, with in vivo and in vitro studies indicating that a major target of cholinergic input is the forebrain nucleus HVC. Within HVC, a muscarinic cholinergic system has strong regulatory effects on most neurons, and may serve to couple and uncouple circuitry within HVC projecting along the premotor pathway with circuitry within HVC projecting along the cortico-basal ganglia pathway. These observations begin to describe how neuromodulatory regulation in the song system may contribute to learning phenomena.

Brain stem feedback in a computational model of birdsong sequencing

Uncovering the roles of neural feedback in the brain is an active area of experimental research. In songbirds, the telencephalic premotor nucleus HVC receives neural feedback from both forebrain and brain stem areas. Here we present a computational model of birdsong sequencing that incorporates HVC and associated nuclei and builds on the model of sparse bursting presented in our preceding companion paper. Our model embodies the hypotheses that 1) different networks in HVC control different syllables or notes of birdsong, 2) interneurons in HVC not only participate in sparse bursting but also provide mutual inhibition between networks controlling syllables or notes, and 3) these syllable networks are sequentially excited by neural feedback via the brain stem and the afferent thalamic nucleus Uva, or a similar feedback pathway. We discuss the model's ability to unify physiological, behavioral, and lesion results and we use it to make novel predictions that can be tested experimentally. The model suggests a neural basis for sequence variations, shows that stimulation in the feedback pathway may have different effects depending on the balance of excitation and inhibition at the input to HVC from Uva, and predicts deviations from uniform expansion of syllables and gaps during HVC cooling.

Maximum decoding abilities of temporal patterns and synchronized firings: application to auditory neurons responding to click trains and amplitude modulated white noise

Simultaneous recordings of an increasing number of neurons have recently become available, but few methods have been proposed to handle this activity. Here, we extract and investigate all the possible temporal neural activity patterns based on synchronized firings of neurons recorded on multiple electrodes, or based on bursts of single-electrode activity in cat primary auditory cortex. We apply this to responses to periodic click trains or sinusoïdal amplitude modulated noise by obtaining for each pattern its temporal modulation transfer function. An algorithm that maximizes the mutual information between all patterns and stimuli subsequently leads to the identification of patterns that optimally decode modulation frequency (MF). We show that stimulus information contained in multi-electrode synchronized firing is not redundant with single-electrode firings and leads to improved efficiency of MF decoding. We also show that the combined use of firing rate and temporal codes leads to a better discrimination of the MF.

Temporal spike pattern learning

Sensory systems pass information about an animal's environment to higher nervous system units through sequences of action potentials. When these action potentials have essentially equivalent wave forms, all information is contained in the interspike intervals (ISIs) of the spike sequence. How do neural circuits recognize and read these ISI sequences? We address this issue of temporal sequence learning by a neuronal system utilizing spike timing dependent plasticity (STDP). We present a general architecture of neural circuitry that can perform the task of ISI recognition. The essential ingredients of this neural circuit, which we refer to as "interspike interval recognition unit" (IRU) are (i) a spike selection unit, the function of which is to selectively distribute input spikes to downstream IRU circuitry; (ii) a time-delay unit that can be tuned by STDP; and (iii) a detection unit, which is the output of the IRU and a spike from which indicates successful ISI recognition by the IRU. We present two distinct configurations for the time-delay circuit within the IRU using excitatory and inhibitory synapses, respectively, to produce a delayed output spike at time t_{0}+tau(R) in response to the input spike received at time t_{0} . R is the tunable parameter of the time-delay circuit that controls the timing of the delayed output spike. We discuss the forms of STDP rules for excitatory and inhibitory synapses, respectively, that allow for modulation of R for the IRU to perform its task of ISI recognition. We then present two specific implementations for the IRU circuitry, derived from the general architecture that can both learn the ISIs of a training sequence and then recognize the same ISI sequence when it is presented on subsequent occasions.

Synchrony between orientation-selective neurons is modulated during adaptation-induced plasticity in cat visual cortex

BACKGROUND

Visual neurons respond essentially to luminance variations occurring within their receptive fields. In primary visual cortex, each neuron is a filter for stimulus features such as orientation, motion direction and velocity, with the appropriate combination of features eliciting maximal firing rate. Temporal correlation of spike trains was proposed as a potential code for linking the neuronal responses evoked by various features of a same object. In the present study, synchrony strength was measured between cells following an adaptation protocol (prolonged exposure to a non-preferred stimulus) which induce plasticity of neurons' orientation preference.

RESULTS

Multi-unit activity from area 17 of anesthetized adult cats was recorded. Single cells were sorted out and (1) orientation tuning curves were measured before and following 12 min adaptation and 60 min after adaptation (2) pairwise synchrony was measured by an index that was normalized in relation to the cells' firing rate. We first observed that the prolonged presentation of a non-preferred stimulus produces attractive (58%) and repulsive (42%) shifts of cell's tuning curves. It follows that the adaptation-induced plasticity leads to changes in preferred orientation difference, i.e. increase or decrease in tuning properties between neurons. We report here that, after adaptation, the neuron pairs that shared closer tuning properties display a significant increase of synchronization. Recovery from adaptation was accompanied by a return to the initial synchrony level.

CONCLUSION

We conclude that synchrony reflects the similarity in neurons' response properties, and varies accordingly when these properties change.

Brain networks for integrative rhythm formation

BACKGROUND

Performance of externally paced rhythmic movements requires brain and behavioral integration of sensory stimuli with motor commands. The underlying brain mechanisms to elaborate beat-synchronized rhythm and polyrhythms that musicians readily perform may differ. Given known roles in perceiving time and repetitive movements, we hypothesized that basal ganglia and cerebellar structures would have greater activation for polyrhythms than for on-the-beat rhythms.

METHODOLOGY/PRINCIPAL FINDINGS

Using functional MRI methods, we investigated brain networks for performing rhythmic movements paced by auditory cues. Musically trained participants performed rhythmic movements at 2 and 3 Hz either at a 1:1 on-the-beat or with a 3:2 or a 2:3 stimulus-movement structure. Due to their prior musical experience, participants performed the 3:2 or 2:3 rhythmic movements automatically. Both the isorhythmic 1:1 and the polyrhythmic 3:2 or 2:3 movements yielded the expected activation in contralateral primary motor cortex and related motor areas and ipsilateral cerebellum. Direct comparison of functional MRI signals obtained during 3:2 or 2:3 and on-the-beat rhythms indicated activation differences bilaterally in the supplementary motor area, ipsilaterally in the supramarginal gyrus and caudate-putamen and contralaterally in the cerebellum.

CONCLUSIONS/SIGNIFICANCE

The activated brain areas suggest the existence of an interconnected brain network specific for complex sensory-motor rhythmic integration that might have specificity for elaboration of musical abilities.

Structure of spontaneous UP and DOWN transitions self-organizing in a cortical network model

Synaptic plasticity is considered to play a crucial role in the experience-dependent self-organization of local cortical networks. In the absence of sensory stimuli, cerebral cortex exhibits spontaneous membrane potential transitions between an UP and a DOWN state. To reveal how cortical networks develop spontaneous activity, or conversely, how spontaneous activity structures cortical networks, we analyze the self-organization of a recurrent network model of excitatory and inhibitory neurons, which is realistic enough to replicate UP-DOWN states, with spike-timing-dependent plasticity (STDP). The individual neurons in the self-organized network exhibit a variety of temporal patterns in the two-state transitions. In addition, the model develops a feed-forward network-like structure that produces a diverse repertoire of precise sequences of the UP state. Our model shows that the self-organized activity well resembles the spontaneous activity of cortical networks if STDP is accompanied by the pruning of weak synapses. These results suggest that the two-state membrane potential transitions play an active role in structuring local cortical circuits.

Comparative analyses of song complexity and song-control nuclei in fourteen oscine species

Most studies on the relationship between measures of song behavior and the sizes of song control nuclei have focused on one or two oscine species, and often show inconsistent results. To address this issue, we first measured four variables for song complexity, i.e., song repertoire size, syllable repertoire size, the mean number of syllables per phrase (MNS) and the number of syllables in the longest phrase (NSLP), and the sizes of three song control nuclei, i.e., HVC, RA (the robust nucleus of the arcopallium), and Area X in 14 oscine species from eight families. To tackle the problem of statistical non-independence that probably existed among the closely related species, we reconstructed the phylogeny of the species studied using mitochondrial cytochrome b DNA sequences from GenBank. By using the methods adopted in most previous reports, we tested the relationship between song complexity and the sizes of the song control nuclei. We found that: 1) the absolute sizes of RA and Area X, but not of HVC, were positively correlated to the three measures of song complexity, but that only the residual size of RA in regard to telencephalon size was significantly correlated to the song measures; 2) independent contrasts analysis showed RA and Area X to be significantly associated with NSLP. Our results indicated that the relationship between song behavior and its neural structures varied among song nuclei, suggesting that each song control nucleus may play a different role in song behavior.

Pathophysiology of tinnitus

Guided by findings from neural imaging and population responses in humans, where tinnitus is well characterized, several morphological and physiological substrates of tinnitus in animal studies are reviewed. These include changes in ion channels, receptor systems, single unit firing rate, and population responses. Most findings in humans can be interpreted as resulting from increased neural synchrony.

Neural representation of spectral and temporal features of song in the auditory forebrain of zebra finches as revealed by functional MRI

Song perception in songbirds, just as music and speech perception in humans, requires processing the spectral and temporal structure found in the succession of song-syllables. Using functional magnetic resonance imaging and synthetic songs that preserved exclusively either the temporal or the spectral structure of natural song, we investigated how vocalizations are processed in the avian forebrain. We found bilateral and equal activation of the primary auditory region, field L. The more ventral regions of field L showed depressed responses to the synthetic songs that lacked spectral structure. These ventral regions included subarea L3, medial-ventral subarea L and potentially the secondary auditory region caudal medial nidopallium. In addition, field L as a whole showed unexpected increased responses to the temporally filtered songs and this increase was the largest in the dorsal regions. These dorsal regions included L1 and the dorsal subareas L and L2b. Therefore, the ventral region of field L appears to be more sensitive to the preservation of both spectral and temporal information in the context of song processing. We did not find any differences in responses to playback of the bird's own song vs other familiar conspecific songs. We also investigated the effect of three commonly used anaesthetics on the blood oxygen level-dependent response: medetomidine, urethane and isoflurane. The extent of the area activated and the stimulus selectivity depended on the type of anaesthetic. We discuss these results in the context of what is known about the locus of action of the anaesthetics, and reports of neural activity measured in electrophysiological experiments.

Functional connectivity between auditory areas field L and CLM and song system nucleus HVC in anesthetized zebra finches

A key discovery that has emerged from studies of the vocal system in songbirds is that neurons in these regions respond preferentially to playback of the bird's own song (BOS). This BOS selectivity is not a general property of neurons in primary and secondary auditory forebrain regions, field L and caudolateral mesopallium (CLM). Moreover, anatomical studies have been unable to conclusively define a direct projection from field L and/or CLM to HVC, a central structure for integrating sensory and motor information in the vocal system. To examine the communication between these regions, we used simultaneous dual-electrode recording in anesthetized male zebra finches and cross-correlation analysis to estimate the functional connectivity between auditory areas, field L and CLM, and HVC. We found that >or=18% of neurons in field L and 33% of neurons in CLM are functionally connected to HVC, most with auditory forebrain leading-HVC latencies ranging from 0.5 to 15 ms. These results indicate that field L and CLM communicate extensively with HVC through both direct and indirect anatomical connections. To further explore the role of the auditory forebrain cells that are functionally connected with HVC, we assessed their responsiveness and selectivity for a variety of natural and synthetic auditory stimuli. We found that field L and CLM neurons that are functionally connected to HVC exhibit generic auditory forebrain properties including the lack of BOS selectivity. This finding puts further constraints on the neural architecture and the nature of the nonlinearity that leads to BOS-selective auditory responses in the vocal control nuclei.

Neural Correlations Increase Between Consecutive Processing Levels in the Auditory System of Locusts

Nervous systems may encode information about sensory stimuli using the temporal relations in spiking patterns between neurons. By conducting simultaneous intracellular recordings on pairs of auditory neurons we measured the strength of correlations between elements of the first three processing levels in the metathoracic auditory network of the locust. We quantified the degree of spike synchronization and rate covariations that occur among auditory neurons during acoustic stimulation. In addition to the acoustic stimulation, current pulses were injected into both neurons to study the connectivity within this network. Our findings support the view that the metathoracic auditory system is a hierarchically organized feedforward network. Strong synaptic connections were observed only between consecutive processing levels, whereas there was no indication for strong connections between elements of the same processing level. Both spike synchronization and rate covariations were increased among neurons on higher processing levels. We further investigated the consequences that correlations may have on the common estimates of neuronal variability. For example, rate covariations caused by strong synaptic coupling between two neurons may lead to an overestimation if the variability is measured trial by trial with respect to only single neurons. For the vast majority of cell pairs tested, however, no strong synaptic coupling could be demonstrated. Thus we could show that in most cases no serious errors are made if one determines variability by following the usual procedure on the basis of single-cell recordings.

Local cortical circuit model inferred from power-law distributed neuronal avalanches

How cortical neurons process information crucially depends on how their local circuits are organized. Spontaneous synchronous neuronal activity propagating through neocortical slices displays highly diverse, yet repeatable, activity patterns called "neuronal avalanches". They obey power-law distributions of the event sizes and lifetimes, presumably reflecting the structure of local circuits developed in slice cultures. However, the explicit network structure underlying the power-law statistics remains unclear. Here, we present a neuronal network model of pyramidal and inhibitory neurons that enables stable propagation of avalanche-like spiking activity. We demonstrate a neuronal wiring rule that governs the formation of mutually overlapping cell assemblies during the development of this network. The resultant network comprises a mixture of feedforward chains and recurrent circuits, in which neuronal avalanches are stable if the former structure is predominant. Interestingly, the recurrent synaptic connections formed by this wiring rule limit the number of cell assemblies embeddable in a neuron pool of given size. We investigate how the resultant power laws depend on the details of the cell-assembly formation as well as on the inhibitory feedback. Our model suggests that local cortical circuits may have a more complex topological design than has previously been thought.

Correlated neural activity as the driving force for functional changes in auditory cortex

The functional role of neural synchrony is reflected in cortical tonotopic map reorganization and in the emergence of pathological phenomena such as tinnitus. First of all experimenter-centered and subject-centered views of neural activity will be contrasted; this argues against the use of stimulus-correction procedures and favors the use of a correction procedure based on neural activity without reference to stimulus timing. Within a cortical column neurons fired synchronously with on average about 6% of their spikes in a 1 ms bin and occasionally showing 30% or more of such coincident spikes. For electrode separations exceeding 200 microm the average peak correlation strength only occasionally reached 3%. The experimental evidence for coincidence of neural activity, neural correlation and neural synchrony shows that horizontal fibers activity can induce strong neural correlations. Cortico-cortical connections for a large part connect cell groups with characteristic frequencies differing by more than one octave. Such neurons have generally non-overlapping receptive fields but still can have sizeable peak cross-correlations. Correlated neural activity and heterotopic neural interconnections are presented as the substrates for cortical reorganization; increased neural synchrony and tonotopic map reorganization go hand in hand. This links cortical reorganization with hypersynchrony that can be considered as an important driving force underlying tinnitus.

Sleep-related spike bursts in HVC are driven by the nucleus interface of the nidopallium

The function and the origin of replay of motor activity during sleep are currently unknown. Spontaneous activity patterns in the nucleus robustus of the arcopallium (RA) and in HVC (high vocal center) of the sleeping songbird resemble premotor patterns in these areas observed during singing. We test the hypothesis that the nucleus interface of the nidopallium (NIf) has an important role for initiating and shaping these sleep-related activity patterns. In head-fixed, sleeping zebra finches we find that injections of the GABA(A)-agonist muscimol into NIf lead to transient abolishment of premotor-like bursting activity in HVC neurons. Using antidromic activation of NIf neurons by electrical stimulation in HVC, we are able to distinguish a class of HVC-projecting NIf neurons from a second class of NIf neurons. Paired extracellular recordings in NIf and HVC show that NIf neurons provide a strong bursting drive to HVC. In contrast to HVC neurons, whose bursting activity waxes and wanes in burst epochs, individual NIf projection neurons are nearly continuously bursting and tend to burst only once on the timescale of song syllables. Two types of HVC projection neurons-premotor and striatal projecting-respond differently to the NIf drive, in agreement with notions of HVC relaying premotor signals to RA and an anticipatory copy thereof to areas of a basal ganglia pathway.

Properties of Correlated Neural Activity Clusters in Cat Auditory Cortex Resemble Those of Neural Assemblies

Spiking activity was recorded from cat auditory cortex using multi-electrode arrays. Cross-correlograms were calculated for spikes recorded on separate microelectrodes. The pair-wise cross-correlation matrix was constructed for the peak values of the correlograms. Hierarchical clustering was performed on the cross-correlation matrix for six stimulus conditions. These were silence, three multi-tone stimulus ensembles with different spectral densities, low-pass amplitude-modulated noise, and Poisson-distributed click trains that each lasted 15 min. The resulting neuron clusters reflect patches in cortex of up to several mm2 in size that expand and contract in response to different stimuli. Cluster positions and size were very similar for spontaneous activity and multi-tone stimulus-evoked activity but differed between those conditions and the noise and click stimuli. Cluster size was significantly larger in posterior auditory field (PAF) compared with primary auditory cortex (AI), whereas the fraction of common spikes (within a 10-ms window) across all electrode activity participating in a cluster was significantly higher in AI compared with PAF. Clusters crossed area boundaries in <5% of the cases were simultaneous recording were made in AI and PAF. Clusters are therefore similar to but not synonymous with the traditional view of neural assemblies. Common-spike spectrotemporal receptive fields (STRFs) were obtained for common-spike activity and all-spike activity within a cluster. Common-spike STRFs had higher signal-to-noise ratio than all-spike STRFs and showed generally spectral and temporal sharpening. The coincident and noncoincident output of the clusters could potentially act in parallel and may serve different modes of stimulus coding.

Neural circuitry for recognizing interspike interval sequences

Sensory systems present environmental information to central nervous system as sequences of action potentials or spikes. How do animals recognize these sequences carrying information about their world? We present a biologically inspired neural circuit designed to enable spike pattern recognition. This circuit is capable of training itself on a given interspike interval (ISI) sequence and is then able to respond to presentations of the same sequence. The essential ingredients of the recognition circuit are (a) a tunable time delay circuit, (b) a spike selection unit, and (c) a tuning mechanism using spike timing dependent plasticity of inhibitory synapses. We have investigated this circuit using Hodgkin-Huxley neuron models connected by realistic excitatory and inhibitory synapses. It is robust in the presence of noise represented as jitter in the spike times of the ISI sequence.

Synaptic interactions underlying song-selectivity in the avian nucleus HVC revealed by dual intracellular recordings

Stimulus-dependent synaptic interactions underlying selective sensory representations in neural circuits specialized for sensory processing and sensorimotor integration remain poorly understood. The songbird telencephalic nucleus HVC is a sensorimotor area essential to learned vocal control with one projection neuron (PN) type (HVC(RA)) innervating a song premotor pathway, another PN (HVC(X)) innervating a basal ganglia pathway essential to vocal plasticity, and interneurons (HVC(Int)). Playback of the bird's own song (BOS), but not other songs, evokes action potential bursts from both PNs, but HVC(RA) and HVC(X) display distinct BOS-evoked subthreshold responses. To characterize synaptic interactions underlying HVC's BOS-selective responses and assess stimulus-evoked changes in functional interactions between HVC neurons, we made simultaneous in vivo intracellular recordings from various HVC neuron pairs in urethan-anesthetized zebra finches. Spike-triggered averaging revealed that all HVC neuron types receive common excitation and that the onset of this excitation occurs during a narrower time window in projection neurons during BOS playback. To distinguish local from extrinsic contributions to HVC subthreshold response patterns, we inactivated the HVC local circuit with GABA or occluded inhibition in single HVC(X) cells. After either treatment, BOS-evoked responses in HVC(X) neurons became purely depolarizing and subthreshold responses of HVC(X) and HVC(RA) cells became remarkably similar to one another while retaining BOS selectivity. Therefore both PN types receive a common extrinsic source of BOS-selective excitation, and local inhibition specifically alters processing of auditory information in HVC(X) cells. In HVC, excitatory and inhibitory synaptic interactions are recruited in a stimulus-dependent fashion, affecting auditory representations of the BOS locally and in other song nuclei important to song learning and production.

Sleep-related neural activity in a premotor and a basal-ganglia pathway of the songbird

During singing, neurons in premotor nucleus RA (robust nucleus of the arcopallium) of the zebra finch produce complex temporal sequences of bursts that are recapitulated during sleep. RA receives input from nucleus HVC via the premotor pathway, and also from the lateral magnocellular nucleus of the anterior nidopallium (LMAN), part of a basal ganglia-related circuit essential for vocal learning. We explore the propagation of sleep-related spike patterns in these two pathways and their influences on RA activity. We promote sleep in head-fixed birds by injections of melatonin and make single-neuron recordings from the three major classes of neurons in HVC: RA-projecting neurons, Area X-projecting neurons, and interneurons. We also record LMAN neurons that project to RA. In paired recordings, spike trains from identified HVC neuron types are strongly coherent with spike trains in RA neurons, whereas LMAN projection neurons on average exhibit only a weak coherency with neurons in HVC and RA. We further examine the relative roles of HVC and LMAN in generating RA burst sequences with reversible inactivation. Lidocaine inactivation of HVC completely abolishes bursting in RA, whereas inactivation of LMAN has no effect on burst rates in RA. In combination, our data suggest that in adult birds, RA burst sequences in sleep are driven via the premotor pathway from HVC. We present a simple generative model of spike trains in HVC, RA, and LMAN neurons that is able to qualitatively reproduce observed coherency functions. We propose that commonly observed coherency peaks at positive and negative time lags are caused by sequentially correlated HVC activity.

Correlated firing in a feedforward network with Mexican-hat-type connectivity

We report on deterministic and stochastic evolutions of firing states through a feedforward neural network with Mexican-hat-type connectivity. The prevalence of columnar structures in a cortex implies spatially localized connectivity between neural pools. Although feedforward neural network models with homogeneous connectivity have been intensively studied within the context of the synfire chain, the effect of local connectivity has not yet been studied so thoroughly. When a neuron fires independently, the dynamics of macroscopic state variables (a firing rate and spatial eccentricity of a firing pattern) is deterministic from the law of large numbers. Possible stable firing states, which are derived from deterministic evolution equations, are uniform, localized, and nonfiring. The multistability of these three states is obtained where the excitatory and inhibitory interactions among neurons are balanced. When the presynapse-dependent variance in connection efficacies is incorporated into the network, the variance generates common noise. Then the evolution of the macroscopic state variables becomes stochastic, and neurons begin to fire in a correlated manner due to the common noise. The correlation structure that is generated by common noise exhibits a nontrivial bimodal distribution. The development of a firing state through neural layers does not converge to a certain fixed point but keeps on fluctuating.

Dynamics of learning in coupled oscillators tutored with delayed reinforcements

In this work we analyze the solutions of a simple system of coupled phase oscillators in which the connectivity is learned dynamically. The model is inspired by the process of learning of birdsongs by oscine birds. An oscillator acts as the generator of a basic rhythm and drives slave oscillators which are responsible for different motor actions. The driving signal arrives at each driven oscillator through two different pathways. One of them is a direct pathway. The other one is a reinforcement pathway, through which the signal arrives delayed. The coupling coefficients between the driving oscillator and the slave ones evolve in time following a Hebbian-like rule. We discuss the conditions under which a driven oscillator is capable of learning to lock to the driver. The resulting phase difference and connectivity are a function of the delay of the reinforcement. Around some specific delays, the system is capable of generating dramatic changes in the phase difference between the driver and the driven systems. We discuss the dynamical mechanism responsible for this effect and possible applications of this learning scheme.

Unitary IPSPs drive precise thalamic spiking in a circuit required for learning

Song learning in birds requires a basal ganglia-thalamo-pallial loop that contains a calyceal GABAergic synapse in the thalamus. Information processing within this circuit is critical for proper song development; however, it is unclear whether activation of the inhibitory output of the basal ganglia structure Area X can drive sustained activity in its thalamic target, the medial portion of the dorsolateral thalamic nucleus (DLM). We show that high-frequency, random activation of this GABAergic synapse can drive precisely timed firing in DLM neurons in brain slices in the absence of excitatory input. Complex IPSP trains, including spike trains recorded in vivo, drive spiking in slices with high reproducibility, even between animals. Using a simple model, we can predict much of DLM's response to natural stimulus trains. These data elucidate basic rules by which thalamic relay neurons translate IPSPs into suprathreshold output and demonstrate extrathalamic GABAergic activation of thalamus.

Timing and prediction the code from basal ganglia to thalamus

When is an inhibitory synapse not inhibitory? In this issue of Neuron, Person and Perkel demonstrate that thalamic neurons can translate extrinsic GABAergic input from the basal ganglia into highly precise patterns of sustained spiking in a circuit that is essential for vocal learning in songbirds. Postinhibitory rebound serves as a mechanism that preserves precise spike timing information, enabling reliable propagation of activity throughout this pathway. The results have broad implications for basic mechanisms of functional processing in both thalamus and basal ganglia and serve to increase our understanding of how acoustic units of vocal sounds are transformed into motor gestures during the sensitive period for song learning.

Different functional loops between cerebral cortex and the subthalmic area in Parkinson's disease

We investigate the extent to which functional circuits coupling cortical and subthalamic activity are multiple and segregated by frequency in untreated Parkinson's disease (PD). To this end, we recorded EEG and local field potentials (LFPs) from macroelectrodes inserted into the subthalamic nucleus area (SA) in nine awake patients following functional neurosurgery for PD. Patients were studied after overnight withdrawal of medication. Coherence between EEG and SA LFPs was apparent in the theta (3-7 Hz), alpha (8-13 Hz), lower beta (14-20 Hz) and upper beta (21-32 Hz) bands, although activity in the alpha and upper beta bands dominated. Theta coherence predominantly involved mesial and lateral areas, alpha and lower beta coherence the mesial and ipsilateral motor areas, and upper beta coherence the midline cortex. SA LFPs led EEG in the theta band. In contrast, EEG led the depth LFP in the lower and upper beta bands. SA LFP activity in the alpha band could either lead or lag EEG. Thus there are several functional sub-loops between the subthalamic area and cerebral cortical motor regions, distinguished by their frequency, cortical topography and temporal relationships. Tuning to distinct frequencies may provide a means of marking and segregating related processing, over and above any anatomical segregation of processing streams.

Neural circuitry of judgment and decision mechanisms

Tracing the neural circuitry of decision formation is a critical step in the understanding of higher cognitive function. To make a decision, the primate brain coordinates dynamic interactions between several cortical and subcortical areas that process sensory, cognitive, and reward information. In selecting the optimal behavioral response, decision mechanisms integrate the accumulating evidence with reward expectation and knowledge from prior experience, and deliberate about the choice that matches the expected outcome. Linkages between sensory input and behavioral output responsible for response selection are shown in the neural activity of structures from the prefrontal-basal ganglia-thalamo-cortical loop. The deliberation process can be best described in terms of sensitivity, selection bias, and activation threshold. Here, we show a systems neuroscience approach of the visual saccade decision circuit and the interaction between its components during decision formation.

Dynamical model of birdsong maintenance and control

The neuroethology of song learning, production, and maintenance in songbirds presents interesting similarities to human speech. We have developed a biophysical model of the manner in which song could be maintained in adult songbirds. This model may inform us about the human counterpart to these processes. In songbirds, signals generated in nucleus High Vocal center (HVc) follow a direct route along a premotor pathway to the robust nucleus of the archistriatum (RA) as well as an indirect route to RA through the anterior forebrain pathway (AFP): the neurons of RA are innervated from both sources. HVc expresses very sparse bursts of spikes having interspike intervals of about 2 ms. The expressions of these bursts arrive at the RA with a time difference DeltaT approximately equal to 50+/-10 ms between the two pathways. The observed combination of AMPA and NMDA receptors at RA projection neurons suggests that long-term potentiation and long-term depression can both be induced by spike timing plasticity through the pairing of the HVc and AFP signals. We present a dynamical model that stabilizes this synaptic plasticity through a feedback from the RA to the AFP using known connections. The stabilization occurs dynamically and is absent when the RA-->AFP connection is removed. This requires a dynamical selection of DeltaT. The model does this, and DeltaT lies within the observed range. Our model represents an illustration of a functional consequence of activity-dependent plasticity directly connected with neuroethological observations. Within the model the parameters of the AFP, and thus the magnitude of DeltaT, can also be tuned to an unstable regime. This means that destabilization might be induced by neuromodulation of the AFP.

The neural basis of temporal processing

A complete understanding of sensory and motor processing requires characterization of how the nervous system processes time in the range of tens to hundreds of milliseconds (ms). Temporal processing on this scale is required for simple sensory problems, such as interval, duration, and motion discrimination, as well as complex forms of sensory processing, such as speech recognition. Timing is also required for a wide range of motor tasks from eyelid conditioning to playing the piano. Here we review the behavioral, electrophysiological, and theoretical literature on the neural basis of temporal processing. These data suggest that temporal processing is likely to be distributed among different structures, rather than relying on a centralized timing area, as has been suggested in internal clock models. We also discuss whether temporal processing relies on specialized neural mechanisms, which perform temporal computations independent of spatial ones. We suggest that, given the intricate link between temporal and spatial information in most sensory and motor tasks, timing and spatial processing are intrinsic properties of neural function, and specialized timing mechanisms such as delay lines, oscillators, or a spectrum of different time constants are not required. Rather temporal processing may rely on state-dependent changes in network dynamics.

Cellular, circuit, and synaptic mechanisms in song learning

Songbirds, much like humans, learn their vocal behavior, and must be able to hear both themselves and others to do so. Studies of the brain areas involved in singing and song learning could reveal the underlying neural mechanisms. Here we describe experiments that explore the properties of the songbird anterior forebrain pathway (AFP), a basal ganglia-forebrain circuit known to be critical for song learning and for adult modification of vocal output. First, neural recordings in anesthetized, juvenile birds show that auditory AFP neurons become selectively responsive to the song stimuli that are compared during sensorimotor learning. Individual AFP neurons develop tuning to the bird's own song (BOS), and in many cases to the tutor song as well, even when these stimuli are manipulated to be very different from each other. Such dual selectivity could be useful in the BOS-tutor song comparison critical to song learning. Second, simultaneous neural recordings from the AFP and its target nucleus in the song motor pathway in anesthetized adult birds reveal correlated activity that is preserved through multiple steps of the circuits for song, including the AFP. This suggests that the AFP contains highly functionally interconnected neurons, an architecture that can preserve information about the timing of firing of groups of neurons. Finally, in vitro studies show that recurrent synapses between neurons in the AFP outflow nucleus, which are expected to contribute importantly to AFP correlation, can undergo activity-dependent and timing-sensitive strengthening. This synaptic enhancement appears to be restricted to birds in the sensory critical and early sensorimotor phases of learning. Together, these studies show that the AFP contains cells that reflect learning of both BOS and tutor song, as well as developmentally regulated synaptic and circuit mechanisms well-suited to create temporally organized assemblies of such cells. Such experience-dependent sensorimotor assemblies are likely to be critical to the AFP's role in song learning. Moreover, studies of such mechanisms in this basal ganglia circuit specialized for song may shed light more generally on how basal ganglia circuits function in guiding motor learning using sensory feedback signals.

Spike timing and synaptic plasticity in the premotor pathway of birdsong

The neural circuits of birdsong appear to utilize specific time delays in their operation. In particular, the anterior forebrain pathway (AFP) is implicated in an approximately 40- to 50- ms time delay, DeltaT, playing a role in the relative timing of premotor signals from the nucleus HVc to the nucleus robust nucleus of the archistratium (RA) and control/learning signals from the nucleus lateral magnocellular nucleus of the anterior neostratium (lMAN) to RA. Using a biophysical model of synaptic plasticity based on experiments on mammalian hippocampal and neocortical pyramidal neurons, we propose an understanding of this approximately 40- to 50- ms delay. The biophysical model describes the influence of Ca2+ influx into the postsynaptic RA cells through NMDA and AMPA receptors and the induction of LTP and LTD through complex metabolic pathways. The delay, DeltaT, between HVc --> RA premotor signals and lMAN --> RA control/learning signals plays an essential role in determining if synaptic plasticity is induced by signaling from each pathway into RA. If DeltaT is substantially larger than 40 ms, no plasticity is induced. If DeltaT is much less than 40 ms, only potentiation is expected. If DeltaT approximately 40 ms, the sign of synaptic plasticity is sensitive to DeltaT. Our results suggest that changes in DeltaT may influence learning and maintenance of birdsong. We investigate the robustness of this result to noise and to the removal of the Ca2+ contribution from lMAN --> RA NMDA receptors.

Neural mechanism underlying complex receptive field properties of motion-sensitive interneurons

In many species, neurons responding to visual motion at higher processing stages are often specifically tuned to particular flow fields; however, the neural circuitry that leads to this selectivity is not yet understood. Here we have studied this problem in 'vertical system' (VS) cells of the blowfly lobula plate. These neurons possess distinctive local preferred directions in different parts of their receptive field. Dual recordings from pairs of VS cells show that they are electrically coupled. This coupling is responsible for the elongated horizontal extent of their receptive fields. VS cells with a lateral receptive field have additional connections to a VS cell with a frontal receptive field and to the horizontal system, tuning these cells to rotational flow fields. In summary, the receptive field of these cells consists of two components: one that they receive from local motion detectors on their dendrite, and one that they import from other large-field neurons.

Basal forebrain cholinergic modulation of auditory activity in the zebra finch song system

The cholinergic basis of auditory "gating" in the sensorimotor nucleus HVc and its efferent target robustus archistriatalis (RA) was investigated in anesthetized zebra finches. Injections of cholinergic agonists carbachol or muscarine into HVc strongly affected discharge rates and diminished auditory responsiveness in both HVc and its target RA, changes toward an awake-like condition. HVc nicotine injections produced similar strong effects in HVc, but weaker and inconsistent effects in RA. Stimulation of basal forebrain (BF) produced an initial transient network shutdown followed by diminished auditory responsiveness in HVc and RA. All stimulation effects were blocked when preceded by HVc injections of nicotinic or muscarinic antagonists. Thus, BF cholinergic modulation of song system auditory activity acting via functionally distinct HVc circuits can contribute to auditory gating. We hypothesize that wakeful BF activity levels block sensory input to motor systems and adaptively change during behavior to allow sensorimotor feedback such as auditory feedback during singing.