Neural coding in the chick cochlear nucleus

Physiological recordings were made from single units in the two divisions of the chick cochlear nucleus-nucleus angularis (NA) and nucleus magnocellularis (NM). Sound evoked responses were obtained in an effort to quantify functional differences between the two nuclei. In particular, it was of interest to determine if nucleus angularis and magnocellularis code for separate features of sound stimuli, such as temporal and intensity information. The principal findings are: 1. Spontaneous activity patterns in the two nuclei are very different. Neurons in nucleus angularis tend to have low spontaneous discharge rates while magnocellular units have high levels of spontaneous firing. 2. Frequency tuning curves recorded in both nuclei are similar in form, although the best thresholds of NA units are about 10 dB more sensitive than their NM counterparts across the entire frequency range. A wide spread of neural thresholds is evident in both NA and NM. 3. Large driven increases in discharge rate are seen in both NA and NM. Rate intensity functions from NM units are all monotonic, while a substantial percentage (22%) of NA units respond to increased sound level in a nonmonotonic fashion. 4. Most NA units with characteristic frequencies (CF) above 1000 Hz respond to sound stimuli at CF as 'choppers', while units with CF's below 1000 Hz are 'primary-like'. Several 'onset' units are also seen in NA. In contrast, all NM units show 'primary-like' response. 5. Units in both nuclei with CF's below 1000 Hz show strong neural phase-locking to stimuli at their CF. Above 1000 Hz, few NA units are phase-locked, while phase-locking in NM extends to 2000 Hz. 6. These results are discussed with reference to the hypothesis that NM initiates a neural pathway which codes temporal information while NA is involved primarily with intensity coding, similar in principle to the segregation of function seen in the cochlear nucleus of the barn owl (Sullivan and Konishi 1984).     

Rates and rhythms: a synergistic view of frequency and temporal coding in neuronal networks

In the CNS, activity of individual neurons has a small but quantifiable relationship to sensory representations and motor outputs. Coactivation of a few 10s to 100s of neurons can code sensory inputs and behavioral task performance within psychophysical limits. However, in a sea of sensory inputs and demand for complex motor outputs how is the activity of such small subpopulations of neurons organized? Two theories dominate in this respect: increases in spike rate (rate coding) and sharpening of the coincidence of spiking in active neurons (temporal coding). Both have computational advantages and are far from mutually exclusive. Here, we review evidence for a bias in neuronal circuits toward temporal coding and the coexistence of rate and temporal coding during population rhythm generation. The coincident expression of multiple types of gamma rhythm in sensory cortex suggests a mechanistic substrate for combining rate and temporal codes?on the basis of stimulus strength.     

Temporal population code of concurrent vocal signals in the auditory midbrain

Unique patterns of spike activity across neuron populations have been implicated in the coding of complex sensory stimuli. Delineating the patterns of neural activity in response to varying stimulus parameters and their relationships to the tuning characteristics of individual neurons is essential to ascertaining the nature of population coding within the brain. Here, we address these points in the midbrain coding of concurrent vocal signals of a sound-producing fish, the plainfin midshipman. Midshipman produce multiharmonic vocalizations which frequently overlap to produce beats. We used multivariate statistical analysis from single-unit recordings across multiple animals to assess the presence of a temporal population code. Our results show that distinct patterns of temporal activity emerge among midbrain neurons in response to concurrent signals that vary in their difference frequency. These patterns can serve to code beat difference frequencies. The patterns directly result from the differential temporal coding of difference frequency by individual neurons. Difference frequency encoding, based on temporal patterns of activity, could permit the segregation of concurrent vocal signals on time scales shorter than codes requiring averaging. Given the ubiquity across vertebrates of auditory midbrain tuning to the temporal structure of acoustic signals, a similar temporal population code is likely present in other species.     

Localization of the preprosomatostatin-mRNA by in situ hybridization in the ewe hypothalamus

The peptidergic neurohormone somatostatin (SRIF) derives from a precursor called preprosomatostatin (PPS) by proteolysis. We have isolated by RT-PCR and sequenced a partial cDNA coding for the ovine PPS. It contains a 348 base pairs coding sequence that shares strong similarities with previously cloned mammalian cDNAs. The ovine cDNA was used to synthesize radiolabeled cRNA to probe the PPS mRNA in the ewe hypothalamus by in situ hybridization. The PPS mRNA-containing cells are widely distributed in the hypothalamus. According to the number of silver grains over a cell, they show various staining intensities. The distribution of the PPS mRNA is in good agreement with that of the peptide previously determined using immunohistochemistry. The strongest labeled areas include the periventricular region of the paraventricular nucleus and the lateral division of the ventromedial nucleus. The difference in labeling intensity observed in the diverse populations of labeled neurons could reflect various levels of neuronal activity.     

Coding processes involved in the cortical representation of complex tactile stimuli

To understand how information is coded in the primary somatosensory cortex (S1) we need to decipher the relationship between neural activity and tactile stimuli. Such a relationship can be formally measured by mutual information. The present study was designed to determine how S1 neuronal populations code for the multidimensional kinetic features (i.e. random, time-varying patterns of force) of complex tactile stimuli, applied at different locations of the rat forepaw. More precisely, the stimulus localization and feature extraction were analyzed as two independent processes, using both rate coding and temporal coding strategies. To model the process of stimulus kinetic feature extraction, multidimensional stimuli were projected onto lower dimensional subspace and then clustered according to their similarity. Different combinations of stimuli clustering were applied to differentiate each stimulus identification process. Information analyses show that both processes are synergistic, this synergy is enhanced within the temporal coding framework. The stimulus localization process is faster than the stimulus feature extraction process. The latter provides more information quantity with rate coding strategy, whereas the localization process maximizes the mutual information within the temporal coding framework. Therefore, combining mutual information analysis with robust clustering of complex stimuli provides a framework to study neural coding mechanisms related to complex stimuli discrimination.     

Processing of Auditory Midbrain Interspike Intervals by Model Neurons

A question central to sensory processing is how signal information is encoded and processed by single neurons. Stimulus features can be represented through rate coding (via firing rate), temporal coding (via firing synchronization to temporal periodicities), or temporal encoding (via intricate patterns of spike trains). Of the three, examples of temporal encoding are the least documented. One region in which temporal encoding is currently being explored is the auditory midbrain. Midbrain neurons in the plainfin midshipman generate different interspike interval (ISI) distributions depending on the frequencies of the concurrent vocal signals. However, these distributions differ only along certain lengths of ISIs, so that any neurons trying to distinguish the distributions would have to respond selectively to specific ISI ranges. We used this empirical observation as a realistic challenge with which to explore the plausibility of ISI-tuned neurons that could validate this form of temporal encoding. The resulting modeled cells—point neurons optimized through multidimensional searching—were successfully tuned to discriminate patterns in specific ranges of ISIs. Achieving this task, particularly with simplified neurons, strengthens the credibility of ISI coding in the brain and lends credence to its role in auditory processing.     

Enhanced visual temporal resolution in autism spectrum disorders

Cognitive functions that rely on accurate sequencing of events, such as action planning and execution, verbal and nonverbal communication, and social interaction rely on well-tuned coding of temporal event-structure. Visual temporal event-structure coding was tested in 17 high-functioning adolescents and adults with autism spectrum disorder (ASD) and mental- and chronological-age matched typically-developing (TD) individuals using a perceptual simultaneity paradigm. Visual simultaneity thresholds were lower in individuals with ASD compared to TD individuals, suggesting that autism may be characterised by increased parsing of temporal event-structure, with a decreased capability for integration over time. Lower perceptual simultaneity thresholds in ASD were also related to increased developmental communication difficulties. These results are linked to detail-focussed and local processing bias.     

Dual coding hypotheses for neural information representation

Information is represented and processed in neural systems in various ways. The rate coding, population coding, and temporal coding are typical examples of representation. It is a hot issue in neuroscience what kinds of coding is used in real neural systems. Different regions of the brain may resort to different coding strategies. Moreover, recent studies suggest the possibility of dual or multiple codes, in which different modes of information are embedded in one neural system. The present paper reviews various possibilities of neural codes focusing on dual codes.     

Perceptual learning reduces interneuronal correlations in macaque visual cortex

Responses of neurons in early visual cortex change little with training and appear insufficient to account for perceptual learning. Behavioral performance, however, relies on population activity, and the accuracy of a population code is constrained by correlated noise among neurons. We tested whether training changes interneuronal correlations in the dorsal medial superior temporal area, which is involved in multisensory heading perception. Pairs of single units were recorded simultaneously in two groups of subjects: animals trained extensively in a heading discrimination task, and "naive" animals that performed a passive fixation task. Correlated noise was significantly weaker in trained versus naive animals, which might be expected to improve coding efficiency. However, we show that the observed uniform reduction in noise correlations leads to little change in population coding efficiency when all neurons are decoded. Thus, global changes in correlated noise among sensory neurons may be insufficient to account for perceptual learning.     

Spatiotemporal burst coding for extracting features of spatiotemporally varying stimuli

Encoding features of spatiotemporally varying stimuli is quite important for understanding the neural mechanisms of various sensory coding. Temporal coding can encode features of time-varying stimulus, and population coding with temporal coding is adequate for encoding spatiotemporal correlation of stimulus features into spatiotemporal activity of neurons. However, little is known about how spatiotemporal features of stimulus are encoded by spatiotemporal property of neural activity. To address this issue, we propose here a population coding with burst spikes, called here spatiotemporal burst (STB) coding. In STB coding, the temporal variation of stimuli is encoded by the precise onset timing of burst spike, and the spatiotemporal correlation of stimuli is emphasized by one specific aspect of burst firing, or spike packet followed by silent interval. To show concretely the role of STB coding, we study the electrosensory system of a weakly electric fish. Weakly electric fish must perceive the information about an object nearby by analyzing spatiotemporal modulations of electric field around it. On the basis of well-characterized circuitry, we constructed a neural network model of the electrosensory system. Here we show that STB coding encodes well the information of object distance and size by extracting the spatiotemporal correlation of the distorted electric field. The burst activity of electrosensory neurons is also affected by feedback signals through synaptic plasticity. We show that the control of burst activity caused by the synaptic plasticity leads to extracting the stimulus features depending on the stimulus context. Our results suggest that sensory systems use burst spikes as a unit of sensory coding in order to extract spatiotemporal features of stimuli from spatially distributed stimuli.     

Live‐cell CRISPR imaging in plants reveals dynamic telomere movements

Elucidating the spatiotemporal organization of the genome inside the nucleus is imperative to our understanding of the regulation of genes and non‐coding sequences during development and environmental changes. Emerging techniques of chromatin imaging promise to bridge the long‐standing gap between sequencing studies, which reveal genomic information, and imaging studies that provide spatial and temporal information of defined genomic regions. Here, we demonstrate such an imaging technique based on two orthologues of the bacterial clustered regularly interspaced short palindromic repeats (CRISPR)–CRISPR associated protein 9 (Cas9). By fusing eGFP/mRuby2 to catalytically inactive versions of Streptococcus pyogenes and Staphylococcus aureus Cas9, we show robust visualization of telomere repeats in live leaf cells of Nicotiana benthamiana. By tracking the dynamics of telomeres visualized by CRISPR–dCas9, we reveal dynamic telomere movements of up to 2 μm over 30 min during interphase. Furthermore, we show that CRISPR–dCas9 can be combined with fluorescence‐labelled proteins to visualize DNA–protein interactions in vivo. By simultaneously using two dCas9 orthologues, we pave the way for the imaging of multiple genomic loci in live plants cells. CRISPR imaging bears the potential to significantly improve our understanding of the dynamics of chromosomes in live plant cells.     

Temporal coding in vision: coding by the spike arrival times leads to oscillations in the case of moving targets

The ‘oscillations’ which have been observed in the visual cortex of cats and monkeys in the case of moving targets are discussed in relation to a temporal coding based on the arrival times of spikes or bursts. A decoding process for this temporal coding is proposed in which neurons work in a correlator mode. In the case of motion analysis, periodic resetting is needed to avoid information jamming. This resetting is proposed to be responsible for the ‘oscillations’. Good initial synchronization is required for the decoding process to be performed efficiently. A diffusive process based on interdendritic ionic currents is proposed and shown to operate efficiently, without any loss of spatial and temporal resolving powers. Received: 2 June 1994 / Accepted in revised form: 23 January 1996     

Independent Component Analysis of Temporal Sequences Subject to Constraints by Lateral Geniculate Nucleus Inputs Yields All the Three Major Cell Types of the Primary Visual Cortex

Information maximization has long been suggested as the underlying coding strategy of the primary visual cortex (V1). Grouping image sequences into blocks has been shown by others to improve agreement between experiments and theory. We have studied the effect of temporal convolution on the formation of spatiotemporal filters—that is, the analogues of receptive fields—since this temporal feature is characteristic to the response function of lagged and nonlagged cells of the lateral geniculate nucleus. Concatenated input sequences were used to learn the linear transformation that maximizes the information transfer. Learning was accomplished by means of principal component analysis and independent component analysis. Properties of the emerging spatiotemporal filters closely resemble the three major types of V1 cells: simple cells with separable receptive field, simple cells with nonseparable receptive field, and complex cells.     

Synaptic integration gradients in single cortical pyramidal cell dendrites

Cortical pyramidal neurons receive thousands of synaptic inputs arriving at different dendritic locations with varying degrees of temporal synchrony. It is not known if different locations along single cortical dendrites integrate excitatory inputs in different ways. Here we have used two-photon glutamate uncaging and compartmental modeling to reveal a gradient of nonlinear synaptic integration in basal and apical oblique dendrites of cortical pyramidal neurons. Excitatory inputs to the proximal dendrite sum linearly and require precise temporal coincidence for effective summation, whereas distal inputs are amplified with high gain and integrated over broader time windows. This allows distal inputs to overcome their electrotonic disadvantage, and become surprisingly more effective than proximal inputs at influencing action potential output. Thus, single dendritic branches can already exhibit nonuniform synaptic integration, with the computational strategy shifting from temporal coding to rate coding along the dendrite.     

Noise-tolerant stimulus discrimination by synchronization with depressing synapses

 Some synapses between cortical pyramidal neurons exhibit a rapid depression of excitatory postsynaptic potentials for successive presynaptic spikes. Since depressing synapses do not transmit information on sustained presynaptic firing rates, it has been speculated that they are favorable for temporal coding. In this paper, we study the dynamical effects of depressing synapses on stimulus-induced transient synchronization in a simple network of inhibitory interneurons and excitatory neurons, assuming that the recurrent excitation is mediated by depressing synapses. This synchronization occurs in a temporal pattern which depends on a given stimulus. Since the presence of noise is always a potential hazard in temporal coding, we investigate the extent to which noise in stimuli influences the synchronization phenomena. It is demonstrated that depressing synapses greatly contribute to suppressing the influences of noise on the stimulus-specific temporal patterns of synchronous firing. The timing-based Hebbian learning revealed by physiological experiments is shown to stabilize the temporal patterns in cooperation with synaptic depression. Thus, the times at which synchronous firing occurs provides a reliable information representation in the presence of synaptic depression. Received: 5 July 2000 / Accepted in revised form: 12 January 2001     

A model of the relation of tonotopy and synchronization in the auditory system

Tonotopy and synchronization of spike discharges with the stimulus frequency are two modes of coding which are probably not independent. After defining an appropriate process of coding and a measure of temporal correlations between two neighbouring channels, we show that it is possible to build with these two fundamental features of the auditory system, a neurophysiologically plausible neural network which has properties of noise resistance and signal segmentation.     

Duration channels mediate human time perception

The task of deciding how long sensory events seem to last is one that the human nervous system appears to perform rapidly and, for sub-second intervals, seemingly without conscious effort. That these estimates can be performed within and between multiple sensory and motor domains suggest time perception forms one of the core, fundamental processes of our perception of the world around us. Given this significance, the current paucity in our understanding of how this process operates is surprising. One candidate mechanism for duration perception posits that duration may be mediated via a system of duration-selective 'channels', which are differentially activated depending on the match between afferent duration information and the channels' 'preferred' duration. However, this model awaits experimental validation. In the current study, we use the technique of sensory adaptation, and we present data that are well described by banks of duration channels that are limited in their bandwidth, sensory-specific, and appear to operate at a relatively early stage of visual and auditory sensory processing. Our results suggest that many of the computational principles the nervous system applies to coding visual spatial and auditory spectral information are common to its processing of temporal extent.     

Efficiency of information transmission by retinal ganglion cells

BACKGROUND: Different types of retinal ganglion cells convey different messages to the brain. Messages are in the form of spike patterns, and the number of possible patterns per second sets the coding capacity. We asked if different ganglion cell types make equally efficient use of their coding capacity or whether efficiency depends on the message conveyed. RESULTS: We recorded spike trains from retinal ganglion cells in an in vitro preparation of the guinea pig retina. By calculating, for the observed spike rate, the number of possible spike patterns per second, we calculated coding capacity, and by counting the actual number of patterns, we estimated information rate. Cells with "brisk" responses, i.e., high firing rates, and a general message transmitted information at high rates (21 +/- 9 bits s(-1)). Cells with "sluggish" responses, i.e., lower firing rates, and specific messages (direction of motion, local-edge) transmitted information at lower rates (13 +/- 7 bits s(-1)). Yet, for every type of ganglion cell examined, the information rate was about one-third of coding capacity. For every ganglion cell, information rate was very close (within 4%) to that predicted from Poisson noise and the cell's actual time-modulated rate. CONCLUSIONS: Different messages are transmitted with similar efficiency. Efficiency is limited by temporal correlations, but correlations may be essential to improve decoding in the presence of irreducible noise.     

Stochastic and Reduced Biophysical Models of Synaptic Transmission

Stochastic and reduced biophysical models of synaptictransmission are formulated and evaluated. Thesynaptic transmission involves presynapticfacilitation of neurotransmitter release, depletionand recovery of the presynaptic pool of readilyreleasable vesicles containing neurotransmittermolecules and saturation of postsynaptic receptors ofboth fast non-NMDA and slow NMDA types. The models areshown to display the principal dynamicalcharacteristics experimentally observed of synaptictransmission. The two main types of neural coding,i.e. rate and temporal coding, can be distinguished bymeans of different dynamical properties of synaptictransmission determined by initial neurotransmitterrelease probability and presynaptic firing rate. Fromthe temporal evolution of the postsynaptic membranepotential response to a train of presynaptic actionpotentials at a sustained firing rate, in particularthe steady-state amplitude and steady-state averagelevel of postsynaptic membrane potentials aredetermined as functions of both initial releaseprobability and presynaptic firing rate. The modelsare applicable to studies of the primary stages oflearning processes and can be extended to incorporateshort-term and long-term potentiation in memoryconsolidation processes.