Evidence for spatiotemporal firing patterns within the auditory thalamus of the cat

doi:10.1016/0006-8993(90)90558-S

Brain Research

Volume 509, Issue 2, 19 February 1990, Pages 325-327

https://doi.org/10.1016/0006-8993(90)90558-S Get rights and content

Abstract

Multiple spike trains were recorded in the auditory thalamus of cats. Each unit was studied before, during and after cooling of the ipsilateral primary auditory cortex, during spontaneous activity and acoustically evoked activity. The search for spatiotemporal firing patterns provided evidence that excess of patterns does exist and that the acoustical stimulation increased their number. Cortical cooling did not affect the probability of finding the firing pattern.

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Expressive power of first-order recurrent neural networks determined by their attractor dynamics
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Hence, the activation of functional cell assemblies in distributed networks might be induced by transmissions of complex patterns of activity [1]. In fact, various experimental studies suggest that specific attractor dynamics [20,21,56] as well as spatiotemporal pattern of discharges (i.e., ordered and precise interspike interval relationships) [2,49,51,53,54,57] are likely to be significantly involved in the processing and coding of information in the brain. Moreover, the association between attractor dynamics and repeating firing patterns has been demonstrated in nonlinear dynamical systems [3,4] and in simulations of large scale neuronal networks [28,29].
We provide a characterization of the expressive powers of several models of deterministic and nondeterministic first-order recurrent neural networks according to their attractor dynamics. The expressive power of neural nets is expressed as the topological complexity of their underlying neural ω-languages, and refers to the ability of the networks to perform more or less complicated classification tasks via the manifestation of specific attractor dynamics. In this context, we prove that most neural models under consideration are strictly more powerful than Muller Turing machines. These results provide new insights into the computational capabilities of recurrent neural networks.
On the precision of neural computation with interaural level differences in the lateral superior olive
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Furthermore, spike timing must be conveyed accurately from the auditory afferents to the LSO so that no additional noise is introduced into the spike trains. This assumption is realistic as it is known that, for example, spike times are precisely phase locked to the sound frequency or to subharmonic components of the stimulus not only in the LSO circuit, but also in the inferior colliculus (Poon and Chiu, 2000) and elsewhere in other higher relays of the auditory pathway (Villa and Abeles, 1990). In addition, one has to bear in mind that LSO cells hardly behave as ideal detectors; the theoretical values derived here may thus be worsened by suboptimal output of neurons.
Interaural level difference (ILD) is one of the basic binaural clues in the spatial localization of a sound source. Due to the acoustic shadow cast by the head, a sound source out of the medial plane results in an increased sound level at the nearer ear and a decreased level at the distant ear. In the mammalian auditory brainstem, the ILD is processed by a neuronal circuit of binaural neurons in the lateral superior olive (LSO). These neurons receive major excitatory projections from the ipsilateral side and major inhibitory projections from the contralateral side. As the sound level is encoded predominantly by the neuronal discharge rate, the principal function of LSO neurons is to estimate and encode the difference between the discharge rates of the excitatory and inhibitory inputs. Two general mechanisms of this operation are biologically plausible: (1) subtraction of firing rates integrated over longer time intervals, and (2) detection of coincidence of individual spikes within shorter time intervals. However, the exact mechanism of ILD evaluation is not known. Furthermore, given the stochastic nature of neuronal activity, it is not clear how the circuit achieves the remarkable precision of ILD assessment observed experimentally. We employ a probabilistic model and complementary computer simulations to investigate whether the two general mechanisms are capable of the desired performance. Introducing the concept of an ideal observer, we determine the theoretical ILD accuracy expressed by means of the just-noticeable difference (JND) in dependence on the statistics of the interacting spike trains, the overall firing rate, detection time, the number of converging fibers, and on the neural mechanism itself. We demonstrate that the JNDs rely on the precision of spike timing; however, with an appropriate parameter setting, the lowest theoretical values are similar or better than the experimental values. Furthermore, a mechanism based on excitatory and inhibitory coincidence detection may give better results than the subtraction of firing rates.
This article is part of a Special Issue entitled Neural Coding 2012.
Neural codes in the thalamocortical auditory system: From artificial stimuli to communication sounds
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The authors show that the identified patterns can better decode modulation frequency than single neurons and more importantly, that the information carried by these patterns is not utterly redundant with single electrode firings. However, it can be misleading to promote the idea that the anatomical particularities of cortical networks generate these patterns: Complex patterns of firing were also found in auditory thalamus (some patterns even included neurons located in the auditory sector of the reticular nucleus) and they were still present during cortical cooling (Villa and Abeles, 1990). These recurrent neuronal coordinations likely represent another aspect of neuronal coding that need to be considered, even if its behavioral significance remains to be investigated.
Over the last 15 years, an increasing number of studies have described the responsiveness of thalamic and cortical neurons to communication sounds. Whereas initial studies have simply looked for neurons exhibiting higher firing rate to conspecific vocalizations over their modified, artificially synthesized versions, more recent studies determine the relative contribution of “rate coding” and “temporal coding” to the information transmitted by spike trains. In this article, we aim at reviewing the different strategies employed by thalamic and cortical neurons to encode information about acoustic stimuli, from artificial to natural sounds. Considering data obtained with simple stimuli, we first illustrate that different facets of temporal code, ranging from a strict correspondence between spike-timing and stimulus temporal features to more complex coding strategies, do already exist with artificial stimuli. We then review lines of evidence indicating that spike-timing provides an efficient code for discriminating communication sounds from thalamus, primary and non-primary auditory cortex up to frontal areas. As the neural code probably developed, and became specialized, over evolution to allow precise and reliable processing of sounds that are of survival value, we argue that spike-timing based coding strategies might set the foundations of our perceptive abilities.
Recurrent spatiotemporal firing patterns in large spiking neural networks with ontogenetic and epigenetic processes
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Neural development and differentiation are characterized by an overproduction of cells and a transient exuberant number of connections followed by cell death and selective synaptic pruning. We simulated large spiking neural networks (10,000 units at its maximum size) with and without an ontogenetic process corresponding to a brief initial phase of apoptosis driven by an excessive firing rate mimicking cell death due to glutamatergic neurotoxicity and glutamate-triggered apoptosis. This phase was followed by the onset of spike timing dependent synaptic plasticity (STDP), driven by spatiotemporal patterns of stimulation. Despite the reduction in cell counts the apoptosis tended to increase the excitatory/inhibitory ratio because the inhibitory cells were affected at first. Recurrent spatiotemporal firing patterns emerged in both developmental condition but they differed in dynamics. They were less numerous but repeated more often after apoptosis. The results suggest that initial cell death may be necessary for the emergence of stable cell assemblies, able to sustain and process temporal information, from the initially randomly connected networks.
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Citation Excerpt :
With these premises, the question arises whether precise temporal information conveyed to a neuron may be somehow transmitted through a neural network, without losing its original content. Recurrent temporal patterns of spikes, often referred to as precise firing sequences, consist of occurrences of higher order spike intervals with high temporal accuracy (in the order of few milliseconds), repeating more often than expected by chance (Abeles & Gerstein, 1988; Dayhoff & Gerstein, 1983; Prut et al., 1998; Tetko & Villa, 2001b; Villa & Abeles, 1990). Such temporal patterns of spikes have been observed in a large set of experimental preparations, and have been shown to be associated to sensorimotor and cognitive processes (Shmiel et al., 2005; Villa, 2005; Villa, Tetko, Hyland, & Najem, 1999).
Precise spatiotemporal sequences of neuronal discharges (i.e., intervals between epochs repeating more often than expected by chance), have been observed in a large set of experimental electrophysiological recordings. Sensitivity to temporal information, by itself, does not demonstrate that dynamics embedded in spike trains can be transmitted through a neural network. This study analyzes how synaptic transmission through three archetypical types of neurons (regular-spiking, thalamo-cortical and resonator), simulated by a simple spiking model, can affect the transmission of precise timings generated by a nonlinear deterministic system (i.e., the Zaslavskii mapping in the present study). The results show that cells with subthreshold oscillations (resonators) are very sensitive to stochastic inputs, and are not a good candidate for transmitting temporally coded information. Thalamo-cortical neurons may transmit very well temporal patterns in the absence of background activity, but jitter accumulates along the synaptic chain. Conversely, we observed that cortical regular-spiking neurons can propagate filtered temporal information in a reliable way through the network, and with high temporal accuracy. We discuss the results in the general framework of neural dynamics and brain theories.

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: This research was partially supported by grants from the Holderbank Stiftung, 5113 Holderbank (Switzerland), Fondation du 450ème anniversaire de l'Universitéde Lausanne and by Grant No. 86-269 from the United States-Israel Binational Science Foundation, Jerusalem, Israel.

^†: The authors wish to thank Drs. F. de Ribaupierre, Y. de Ribaupierre, E.M. Rouiller and G.M. Simm, P. Zurita and C. Eriksson for taking part in the experiments reported here. A.E.P. Villa has worked on this study as IBRO Fellow at the Hebrew University of Jerusalem.

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Evidence for spatiotemporal firing patterns within the auditory thalamus of the cat

Abstract

Brain Research

Neurosci. Lett.

Local Cortical Circuits: an Electrophysiological Study

Neural codes for higher brain functions

Detection of single unit responses which are loosely time-locked to a stimulus

IEEE Trans. Syst., Man, Cybern.

Detecting spatio-temporal firing patterns among simultaneously recorded single neurons

J. Neurophysiol.

The efferent projections of the central nucleus and the pericentral nucleus of the inferior colliculus in the cat

J. Comp. Neurol.

Organization of the thalamo-cortical auditory system in the cat

Annu. Rev. Neurosci.