Sampling Properties of the Spectrum and Coherency of Sequences of Action Potentials

Jarvis, M. R.; Mitra, Partha P.

doi:10.1162/089976601300014312

Cited by 382 publications

(356 citation statements)

References 15 publications

Supporting

Mentioning

354

Contrasting

Order By: Relevance

“…Here, P rs denotes the stimulus-response cross spectrum, P ss is the power spectrum of the stimulus, and P rr is the power spectrum of the spike train. All spectral quantities were estimated using multitaper estimation techniques (Jarvis and Mitra, 2001). Note that the stimulus-response coherence directly relates to the mutual information measures we use in other papers (Chacron et al, 2005b;Ellis et al, 2007a), as: I(f) = −log2[1−C(f)] (in bits/s/Hz) (Borst and Theunissen, 1999).…”

Section: Discussionmentioning

confidence: 99%

Ionic and neuromodulatory regulation of burst discharge controls frequency tuning

Mehaffey

Ellis

Krahe

et al. 2008

Journal of Physiology-Paris

View full text Add to dashboard Cite

Sensory neurons encode natural stimuli by changes in firing rate or by generating specific firing patterns, such as bursts. Many neural computations rely on the fact that neurons can be tuned to specific stimulus frequencies. It is thus important to understand the mechanisms underlying frequency tuning. In the electrosensory system of the weakly electric fish, Apteronotus leptorhynchus, the primary processing of behaviourally relevant sensory signals occurs in pyramidal neurons of the electrosensory lateral line lobe (ELL). These cells encode low frequency prey stimuli with bursts of spikes and high frequency communication signals with single spikes. We describe here how bursting in pyramidal neurons can be regulated by intrinsic conductances in a cell subtype specific fashion across the sensory maps found within the ELL, thereby regulating their frequency tuning. Further, the neuromodulatory regulation of such conductances within individual cells and the consequences to frequency tuning are highlighted. Such alterations in the tuning of the pyramidal neurons may allow weakly electric fish to preferentially select for certain stimuli under various behaviourally relevant circumstances.

show abstract

Section: Discussionmentioning

confidence: 99%

Ionic and neuromodulatory regulation of burst discharge controls frequency tuning

Mehaffey

Ellis

Krahe

et al. 2008

Journal of Physiology-Paris

View full text Add to dashboard Cite

show abstract

“…Correlation functions are often estimated in the time domain to detect temporal structure but are well known to suffer serious problems of bias and variance which are exacerbated in the context of a behaving animal (Jarvis and Mitra, 2000). Attempts to overcome these limitations when estimating correlation functions by pooling observations across a large period of time during the experiment leads to a violation of the stationarity assumption and misinterpretation of the data (Brody, 1999).…”

Section: General Methodological Issue: Time and Frequencymentioning

confidence: 99%

Temporal structure in neuronal activity during working memory in macaque parietal cortex

et al. 2002

View full text Add to dashboard Cite

A number of cortical structures are reported to have elevated single unit firing rates sustained throughout the memory period of a working memory task. How the nervous system forms and maintains these memories is unknown but reverberating neuronal network activity is thought to be important. We studied the temporal structure of single unit (SU) activity and simultaneously recorded local field potential (LFP) activity from area LIP in the inferior parietal lobe of two awake macaques during a memory-saccade task. Using multitaper techniques for spectral analysis, which play an important role in obtaining the present results, we find elevations in spectral power in a 50-90Hz (gamma) frequency band during the memory period in both SU and LFP activity. The activity is tuned to the direction of the saccade providing evidence for temporal structure that codes for movement plans during working memory. We also find SU and LFP activity are coherent during the memory period in the 50-90Hz gamma band and no consistent relation is present during simple fixation. Finally, we find organized LFP activity in a 15-25Hz frequency band that may be related to movement execution and preparatory aspects of the task. Neuronal activity could be used to control a neural prosthesis but SU activity can be hard to isolate with cortical implants. As the LFP is easier to acquire than SU activity, our finding of rich temporal structure in LFP activity related to movement planning and execution may accelerate the development of this medical application.Keywords: parietal, prosthesis, local field potential, gamma band, coherence, temporal structure.Pesaran et. al. 3Working memory is a brain system requiring the temporary storage and manipulation of information necessary for the performance of complex cognitive tasks (Baddeley, 1992). The neurophysiological basis of working memory is studied in non-human primates by recording neural activity during delayed-response tasks (Fuster, 1995). Cue-selective elevated single unit firing rates have been recorded during the delay period in many brain areas during different versions of the task (Fuster and Jervey, 1982;Bruce and Goldberg, 1985;Gnadt and Andersen, 1988;Miyashita and Chang, 1988;Funahashi et al., 1989;Koch and Fuster, 1989;Miller et al., 1996;Zhou and Fuster, 1996). How this neural activity is sustained is unknown but may be important to understanding the neural basis of working memory (Goldman-Rakic, 1995). Converging evidence points to the importance of a distributed recurrent neuronal network (Goldman-Rakic, 1988) and reverberating network activity has long been suggested as a possible mechanism for short-term memory (Lorente de No, 1938;Hebb, 1949;Amit, 1995;Seung, 1996;Wang, 1999).Measures with the potential to capture correlated neural activity on a millisecond time scale may be needed to resolve reverberating memory activity. The dynamical structure of neuronal activity has been the source of much interest as a temporal code (for a review see Singer and Gray (1995) ) however ...

show abstract

“…The measure syn (F 1 , F 2 ͉ S) is zero if both features F 1 and F 2 convey independent information about the spikes S. To analyze prediction accuracy on different timescales, we used spectral coherence (Jarvis and Mitra 2001). Spectra were again estimated via a multitaper approach designed for point events (Jarvis and Mitra 2001).…”

Section: I͓smentioning

confidence: 99%

Inferring Spike Trains From Local Field Potentials

Rasch¹,

Gretton²,

Murayama³

et al. 2008

Journal of Neurophysiology

206

200

View full text Add to dashboard Cite

We investigated whether it is possible to infer spike trains solely on the basis of the underlying local field potentials (LFPs). Using support vector machines and linear regression models, we found that in the primary visual cortex (V1) of monkeys, spikes can indeed be inferred from LFPs, at least with moderate success. Although there is a considerable degree of variation across electrodes, the low-frequency structure in spike trains (in the 100-ms range) can be inferred with reasonable accuracy, whereas exact spike positions are not reliably predicted. Two kinds of features of the LFP are exploited for prediction: the frequency power of bands in the high ␥-range (40 -90 Hz) and information contained in lowfrequency oscillations (Ͻ10 Hz), where both phase and power modulations are informative. Information analysis revealed that both features code (mainly) independent aspects of the spike-to-LFP relationship, with the low-frequency LFP phase coding for temporally clustered spiking activity. Although both features and prediction quality are similar during seminatural movie stimuli and spontaneous activity, prediction performance during spontaneous activity degrades much more slowly with increasing electrode distance. The general trend of data obtained with anesthetized animals is qualitatively mirrored in that of a more limited data set recorded in V1 of non-anesthetized monkeys. In contrast to the cortical field potentials, thalamic LFPs (e.g., LFPs derived from recordings in the dorsal lateral geniculate nucleus) hold no useful information for predicting spiking activity.

show abstract

Sampling Properties of the Spectrum and Coherency of Sequences of Action Potentials

Cited by 382 publications

References 15 publications

Ionic and neuromodulatory regulation of burst discharge controls frequency tuning

Ionic and neuromodulatory regulation of burst discharge controls frequency tuning

Temporal structure in neuronal activity during working memory in macaque parietal cortex

Inferring Spike Trains From Local Field Potentials

Contact Info

Product

Resources

About