Rapid Changes in Thalamic Firing Synchrony during Repetitive Whisker Stimulation

Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15261, USA.
The Journal of Neuroscience : The Official Journal of the Society for Neuroscience (Impact Factor: 6.75). 11/2008; 28(44):11153-64. DOI: 10.1523/JNEUROSCI.1586-08.2008
Source: PubMed

ABSTRACT Thalamic firing synchrony is thought to ensure selective transmission of relevant sensory information to the recipient cortical neurons by rendering them more responsive to temporally correlated input spikes. However, direct evidence for a synchrony code in the thalamus is limited. Here, we directly measure thalamic firing synchrony and its stimulus-induced modulation over time, using simultaneous single unit recordings from individual thalamic barreloids in the rat somatosensory whisker/barrel system. Employing whisker deflections varying in velocity or frequency and a cross-correlation approach, we find systematic changes in both time course and strength of thalamic firing synchrony as a function of stimulus parameters and sensory adaptation. Synchrony develops faster and is greater with higher velocity deflections. Greater firing synchrony reflects stimulus-dependent increases in instantaneous firing rates, greater spike time precision relative to stimulus onset as well as common input that likely arises from divergent trigeminothalamic and corticothalamic neurons. With adaptation, synchrony decreases and takes longer to develop but is more dependent on the cells' common inputs. Rapid, sharp increases in thalamic synchrony mirroring quick increases in whisker velocity occur also during ongoing random, high-frequency whisker vibrations. Together, results demonstrate millisecond by millisecond changes in thalamic near-synchronous firing during complex patterns of ongoing vibrissa movements that may ensure transmission of preferred sensory information in local thalamocortical circuits during whisking and active touch.

Download full-text


Available from: Simona Temereanca, Mar 22, 2014
  • Source
    • "Second, we find that our formulation partly obviates the use of the correction techniques introduced in (Haslinger et al., 2010) for goodness-of-fit assessment using the time-rescaling theorem and discrete-time approximations to the CIF. We demonstrate our claims on simulated data, as well as real data from rat thalamic neurons recorded in response to periodic whisker deflections varying in velocity (Temereanca et al., 2008). These data are characterized by high mean and instantaneous firing rates, on the order of 20 and 200 Hz respectively. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Likelihood-based encoding models founded on point processes have received significant attention in the literature because of their ability to reveal the information encoded by spiking neural populations. We propose an approximation to the likelihood of a point-process model of neurons that holds under assumptions about the continuous time process that are physiologically reasonable for neural spike trains: the presence of a refractory period, the predictability of the conditional intensity function, and its integrability. These are properties that apply to a large class of point processes arising in applications other than neuroscience. The proposed approach has several advantages over conventional ones. In particular, one can use standard fitting procedures for generalized linear models based on iteratively reweighted least squares while improving the accuracy of the approximation to the likelihood and reducing bias in the estimation of the parameters of the underlying continuous-time model. As a result, the proposed approach can use a larger bin size to achieve the same accuracy as conventional approaches would with a smaller bin size. This is particularly important when analyzing neural data with high mean and instantaneous firing rates. We demonstrate these claims on simulated and real neural spiking activity. By allowing a substantive increase in the required bin size, our algorithm has the potential to lower the barrier to the use of point-process methods in an increasing number of applications.
    Neural Computation 11/2013; 26(2). DOI:10.1162/NECO_a_00548 · 1.69 Impact Factor
  • Source
    • "(B) is modified from Hong et al. (2012). Neuron 78, June 5, 2013 ª2013 Elsevier Inc. 761 Neuron Perspective 2005; Temereanca et al., 2008), consistent with synchronyencoded signals being successfully transmitted to the cortex. Requirement 3 is satisfied insofar as synchrony-encoded signals are decodable depending on which type of cells carries the message. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Neural networks are more than the sum of their parts, but the properties of those parts are nonetheless important. For instance, neuronal properties affect the degree to which neurons receiving common input will spike synchronously, and whether that synchrony will propagate through the network. Stimulus-evoked synchrony can help or hinder network coding depending on the type of code. In this Perspective, we describe how spike initiation dynamics influence neuronal input-output properties, how those properties affect synchronization, and how synchronization affects network coding. We propose that synchronous and asynchronous spiking can be used to multiplex temporal (synchrony) and rate coding and discuss how pyramidal neurons would be well suited for that task.
    Neuron 06/2013; 78(5):758-772. DOI:10.1016/j.neuron.2013.05.030 · 15.98 Impact Factor
  • Source
    • "The mean number of spikes used was 1800 per orientation of the drifting gratings, with a minimum of 100 and maximum of 6258. Synchrony was defined as the central area under the cross-correlogram within a synchrony window (Temereanca et al., 2008; Q. Wang et al., 2010), and was relatively robust to the number of spikes used in the correlogram estimate. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Thalamic neurons respond to visual scenes by generating synchronous spike trains on the timescale of 10-20 ms that are very effective at driving cortical targets. Here we demonstrate that this synchronous activity contains unexpectedly rich information about fundamental properties of visual stimuli. We report that the occurrence of synchronous firing of cat thalamic cells with highly overlapping receptive fields is strongly sensitive to the orientation and the direction of motion of the visual stimulus. We show that this stimulus selectivity is robust, remaining relatively unchanged under different contrasts and temporal frequencies (stimulus velocities). A computational analysis based on an integrate-and-fire model of the direct thalamic input to a layer 4 cortical cell reveals a strong correlation between the degree of thalamic synchrony and the nonlinear relationship between cortical membrane potential and the resultant firing rate. Together, these findings suggest a novel population code in the synchronous firing of neurons in the early visual pathway that could serve as the substrate for establishing cortical representations of the visual scene.
    The Journal of Neuroscience : The Official Journal of the Society for Neuroscience 06/2012; 32(26):9073-88. DOI:10.1523/JNEUROSCI.4968-11.2012 · 6.75 Impact Factor
Show more