Multiplexed Spike Coding and Adaptation in the Thalamus

Mease, Rebecca A.; Kuner, Thomas; Fairhall, Adrienne L.; Groh, Alexander

doi:10.1016/j.celrep.2017.04.050

Cited by 47 publications

(55 citation statements)

References 63 publications

(163 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Their activation drives thalamic cells to fire the characteristic low threshold calcium spike (LTS) and a burst of action potentials Llinas, 1984a, 1984b). The degree of t-type channel deinactivation is time-and voltage-dependent and determines the number of spikes transferred within a burst (Jahnsen and Llinas 1984a;Mease et al 2017) and thereby the quality and timing of thalamic spiking (Wolfart et al 2005;Mease et al 2014). It is important to note that in the in-vivo situation M1 L6 neurons mono-synaptically innervate excitatory neurons in VL as well as inhibitory neurons in the reticular thalamic nucleus (RTN), which in turn provide feed-forward inhibition to thalamo-cortical relay neurons (Yamawaki and Shepherd 2015).…”

Section: Discussionmentioning

confidence: 99%

Cerebello-Thalamic Spike Transfer via Temporal Coding and Cortical Adaptation

Schäfer

Gao

Zeeuw

et al. 2020

Preprint

View full text Add to dashboard Cite

Orchestrating the ensemble of muscle contractions necessary for coordinated movements requires the interaction of cerebellar, thalamic and cerebral structures, but the mechanisms underlying the integration of information remain largely unknown. Here we investigated how excitatory inputs from cerebellar nuclei (CN) and primary motor cortex layer VI (M1 L6) neurons may regulate together the activity of neurons in the mouse ventrolateral (VL) thalamus. Using dual-optogenetic stimulation and whole-cell recordings in vitro we were able to specifically activate the CN and M1 pathways and study their differential impact. We found that VL spiking probability is effectively determined by a pause in CN stimuli, whereas VL membrane potential can be modulated subthreshold by M1 L6 input. Upon mild depolarization of the VL membrane potential, repetitive CN stimulation evokes at best single action potential firing, whereas more negative membrane potentials increase VL spiking probability. Moreover, whereas high-frequency cerebellar activity attenuates thalamic spiking, pauses in cerebellar activity re-activate thalamic spiking. In contrast, facilitating inputs from cerebral cortex modulate thalamo-cortical spike transfer via fluctuations in the membrane potential. The fine-tuning by cerebellar and cerebral activity allows the motor thalamus to operate as a low-pass filter for cerebellar activity, generating sparse but precisely timed outputs for the cerebral cortex.

show abstract

Section: Discussionmentioning

confidence: 99%

Cerebello-Thalamic Spike Transfer via Temporal Coding and Cortical Adaptation

Schäfer

Gao

Zeeuw

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…This simultaneous representation of multiple stimulus features enables multiplexed information 312 coding, a mechanism that greatly increases the information transmission capacity [19,27,28]. 313…”

Section: Fig 7f Yellow Andmentioning

confidence: 99%

“…For example, in synaptic 343 transmission from the retina to the lateral geniculate nucleus (LGN), retinal spikes with ISIs of a 344 few milliseconds are much more effective in eliciting LGN spikes than those with ISIs of > ~20 345 ms [39][40][41][42][43][44][45]. Consistently, LGN burst ISIs are sensitive to the millisecond-scale structure of 346 current input [19]. Similar to synaptic connections from the retina to the LGN, those from the 347…”

Section: Implications For Visual Processing 340mentioning

confidence: 99%

“…In this regard, bursts are 49 believed to represent an important neuronal code [7,9,10]. Previous analyses of burst 50 information coding have suggested that the number of spikes within a burst [4,[11][12][13][14][15][16][17][18][19], the onset 51 timing of a burst [5,6,[20][21][22], and the duration of a burst [15,23] all carry information. 52…”

Section: Introduction 43mentioning

confidence: 99%

“…Such burst ISI coding should have significant effects on information transfer, 55 because the efficiency of synaptic transmission is sensitive to ISIs [24]. Consistent with this idea, 56 4 recent studies suggest that ISIs within bursts carry information [15,19,23,25]. Although these 57 studies have shown that the first ISI and average ISI within a burst carry information, interaction 58 among multiple ISIs has been unclear.…”

Section: Introduction 43mentioning

confidence: 99%

See 2 more Smart Citations

Interspike intervals within retinal spike bursts combinatorially encode multiple stimulus features

Ishii

Hosoya

2020

Preprint

View full text Add to dashboard Cite

13Neurons in various regions of the brain generate spike bursts. While the number of spikes within 14 a burst has been shown to carry information, information coding by interspike intervals (ISIs) is 15 less well understood. In particular, a burst with k spikes has k−1 intraburst ISIs, and these k−1 16ISIs could theoretically encode k−1 independent values. In this study, we demonstrate that such 17 combinatorial coding occurs for retinal bursts. By recording ganglion cell spikes from isolated 18 salamander retinae, we found that intraburst ISIs encode oscillatory light sequences that are 19 much faster than the light intensity modulation encoded by the number of spikes. When a burst 20 has three spikes, the two intraburst ISIs combinatorially encode the amplitude and phase of the 21 oscillatory sequence. Analysis of trial-to-trial variability suggested that intraburst ISIs are 22 regulated by two independent mechanisms responding to orthogonal oscillatory components, one 23 of which is common to bursts with different number of spikes. Therefore, the retina encodes 24 multiple stimulus features by exploiting all degrees of freedom of burst spike patterns, i.e., the 25 spike number and multiple intraburst ISIs. 26 Author Summary 27Neurons in various regions of the brain generate spike bursts. Bursts are typically composed of a 28 few spikes generated within dozens of milliseconds, and individual bursts are separated by much 29 longer periods of silence (~hundreds of milliseconds). Recent evidence indicates that the number 30 of spikes in a burst, the interspike intervals (ISIs), and the overall duration of a burst, as well as 31 the timing of burst onset, encode information. However, it remains unknown whether multiple 32ISIs within a single burst encode multiple independent information contents. Here we 33 demonstrate that such combinatorial ISI coding occurs for spike bursts in the retina. We recorded 34 3 ganglion cell spikes from isolated salamander retinae stimulated with computer-generated 35 movies. Visual response analyses indicated that multiple ISIs within a single burst 36 combinatorially encode the phase and amplitude of oscillatory light sequences, which are 37 different from the stimulus feature encoded by the spike number. The result demonstrates that the 38 retina encodes multiple stimulus features by exploiting all degrees of freedom of burst spike 39 patterns, i.e., the spike number and multiple intraburst ISIs. Because synaptic transmission in the 40 visual system is highly sensitive to ISIs, the combinatorial ISI coding must have a major impact 41 on visual information processing. 42

show abstract

Multiscale relevance and informative encoding in neuronal spike trains

2020

View full text Add to dashboard Cite

Neuronal responses to complex stimuli and tasks can encompass a wide range of time scales. Understanding these responses requires measures that characterize how the information on these response patterns are represented across multiple temporal resolutions. In this paper we propose a metric -which we call multiscale relevance (MSR) -to capture the dynamical variability of the activity of single neurons across different time scales. The MSR is a non-parametric, fully featureless indicator in that it uses only the time stamps of the firing activity without resorting to any a priori covariate or invoking any specific structure in the tuning curve for neural activity. When applied to neural data from the mEC and from the ADn and PoS regions of freely-behaving rodents, we found that neurons having low MSR tend to have low mutual information and low firing sparsity across the correlates that are believed to be encoded by the region of the brain where the recordings were made. In addition, neurons with high MSR contain significant information on spatial navigation and allow to decode spatial position or head direction as efficiently as those neurons whose firing activity has high mutual information with the covariate to be decoded and significantly better than the set of neurons with high local variations in their interspike intervals. Given these results, we propose that the MSR can be used as a measure to rank and select neurons for their information content without the need to appeal to any a priori covariate.

show abstract

Multiplexed Spike Coding and Adaptation in the Thalamus

Cited by 47 publications

References 63 publications

Cerebello-Thalamic Spike Transfer via Temporal Coding and Cortical Adaptation

Cerebello-Thalamic Spike Transfer via Temporal Coding and Cortical Adaptation

Interspike intervals within retinal spike bursts combinatorially encode multiple stimulus features

Multiscale relevance and informative encoding in neuronal spike trains

Contact Info

Product

Resources

About