Non-Gaussian Membrane Potential Dynamics Imply Sparse, Synchronous Activity in Auditory Cortex

DeWeese, Michael R.; Zador, Anthony M.

doi:10.1523/jneurosci.2813-06.2006

Cited by 148 publications

(163 citation statements)

References 95 publications

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“…The experimentally observed spike patterns in the lateral geniculate nucleus correspond at the population level to synchronous volleys. Taken together with experimental results from other sensory modalities 48,100 , this suggests that the output of SSCs might also consist of spike volleys.…”

Section: Gated Temporal Information Transfer Between Cortical Layer 4supporting

confidence: 70%

Section: Gated Temporal Information Transfer Between Cortical Layer 4mentioning

confidence: 96%

“…Nevertheless, because rapid whisker deflections caused synchronous thalamocortical spikes, the SSC spiked reliably (FIG. 7b) 48,100 , this suggests that the output of SSCs might also consist of spike volleys.In the cat primary visual cortex, the response of thalamocortical cells to a briefly flashed square was compared to the response of layer 4 and layer 2/3 cortical cells 101 . The layer 4 response was reliable, but the layer 2/3 response was less reliable.…”

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confidence: 96%

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Regulation of spike timing in visual cortical circuits

2008

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A train of action potentials (a spike train) can carry information in both the average firing rate and the pattern of spikes in the train. But can such a spike-pattern code be supported by cortical circuits? Neurons in vitro produce a spike pattern in response to the injection of a fluctuating current. However, cortical neurons in vivo are modulated by local oscillatory neuronal activity and by top-down inputs. In a cortical circuit, precise spike patterns thus reflect the interaction between internally generated activity and sensory information encoded by input spike trains. We review the evidence for precise and reliable spike timing in the cortex and discuss its computational role.Reliability and precision are two different quantities. When you make an appointment with your friend, she can either keep the appointment or not show up at all. If she does show up, she might or might not be on time. The former uncertainty is related to reliability, whereas the latter is related to precision. When the same stimulus waveform is repeatedly injected at the soma of a neuron in vitro (FIG. 1a), a similar spike train is obtained on each trial 1,2 (FIG. 1b). When approximately the same number of spikes occur on each trial the neuron is said to be reliable, whereas when the spikes occur almost at the same time across trials it is said to be precise (FIG. 1c). For a single neuron, the potential information content of precise and reliable spike times is many times larger than that which is contained in the firing rate, which is averaged across a typical interval of a hundred milliseconds [3][4][5][6] . The information contained in spike timing is available immediately, rather than after an averaging period. Furthermore, the timing of patterns of spikes can potentially transmit even more information than the timing of the individual constituent spikes 3,7 . The potential relevance of spike patterns becomes apparent when we consider neurons at the population level: when a group of similar neurons (a 'pool') produces precise and reliable spike trains, the neurons they project to receive volleys of synchronous spikes 8,9 . This opens up the possibility of communicating between different cortical areas through synchronous spike volleys.In contrast to the in vitro situation described above, in the intact cortex most excitatory synaptic inputs arrive at the dendrites rather than at the soma (FIG. 1d), and synaptic transmission is typically unreliable [10][11][12][13] . Furthermore, most of these dendritic inputs are not directly related to ongoing sensory stimulation; rather, they reflect spatiotemporally structured internal activity. Therefore, when the same stimulus is presented repeatedly, the resulting spike trains are usually neither precise nor reliable when they are aligned to the stimulus onset 6 . Instead, HHMI Author ManuscriptHHMI Author Manuscript HHMI Author Manuscript neural activity in vivo might be dominated by internally generated complex reverberations or rhythmic oscillations, and precise and reliable sp...

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Section: Gated Temporal Information Transfer Between Cortical Layer 4supporting

confidence: 70%

Section: Gated Temporal Information Transfer Between Cortical Layer 4mentioning

confidence: 96%

mentioning

confidence: 96%

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Regulation of spike timing in visual cortical circuits

2008

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“…Up and down states have not been previously described in auditory cortex (DeWeese and Zador, 2006). Our data presented above are consistent with a predominance of brief voltage excursions, with only occasional long up-states.…”

Section: Up and Down States In The Cerebral Cortexsupporting

confidence: 91%

“…grooming), etc.These events typically lead to a decrease in kurtosis because they smear out the peak in the mean of the voltage histogram near the resting potential (DeWeese and Zador, 2006).…”

Section: Kurtosis Analysismentioning

confidence: 99%

Representation of Sounds in Auditory Cortex of Awake Rats (Dissertation)

Hromádka

2008

Nature Precedings

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Organization of the gymnotiform fish pallium in relation to learning and memory: III. Intrinsic connections

Giassi

Ellis

Maler

2012

J of Comparative Neurology

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The present article reports on the telencephalic connections of regions of the dorsal telencephalon of the weakly electric fish Apteronotus leptorhynchus and Gymnotus sp. that are involved in learning and memory: the lateral (DL), central (DC), and dorsal (DD) regions of the pallium and the intermediate region between DL and DC (Dx). We find that the main route of transmission consists of diencephalic (preglomerular complex; PG) glutamatergic input to DL; glutamatergic projections from DL to DC and Dx; and glutamatergic output from DC/Dx to di-, mes-, and rhombencephalic nuclei. Although PG efferents to DL are spatially organized, the projection from DL to DC appears to be diffuse. The connections of DD are entirely intrinsic to the pallium: DL projects to DD (glutamatergic) and DD feeds back to DL (glutamatergic); DD also projects to DC and has strong contralateral connections. In addition, DL and DD receive input from subpallial regions; we suggest that these are associated with the previously identified γ-aminobutyric acid (GABA)-ergic, dopaminergic, and somatostatin-positive input to these regions. The DL/DD connections are very complex, because DL projects to and receives input from different subdivisions of DD. These subdivisions are linked by circuitry intrinsic to DD itself. DL and DD both contain recurrent putatively excitatory (glutamatergic) connections as well as local putatively inhibitory (GABAergic) interneurons. In contrast, recurrent excitatory connections appears to be absent in DC, and local inhibition is also barely present. Finally, we speculate on the implications of this pattern of connectivity for theories of short-term memory and long-term associative memory.

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Non-Gaussian Membrane Potential Dynamics Imply Sparse, Synchronous Activity in Auditory Cortex

Cited by 148 publications

References 95 publications

Regulation of spike timing in visual cortical circuits

Regulation of spike timing in visual cortical circuits

Representation of Sounds in Auditory Cortex of Awake Rats (Dissertation)

Organization of the gymnotiform fish pallium in relation to learning and memory: III. Intrinsic connections

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