scholarly journals Laminar organization of encoding and memory reactivation in the parietal cortex

2017 ◽  
Author(s):  
Aaron Wilber ◽  
Ivan Skelin ◽  
Bruce L McNaughton
Keyword(s):  
Parietal Cortex ◽  
High Frequency ◽  
Neural Coding ◽  
Field Potential ◽  
Laminar Organization ◽  
Memory Reactivation ◽  
Local Clustering ◽  
Circular Platform ◽  
Self Motion ◽  
Spiking Activity

Egocentric neural coding has been observed in parietal cortex (PC), but its topographical and laminar organization is not well characterized. We used multi-site recording to look for evidence of local clustering and laminar consistency of linear and angular velocity encoding in multi-neuronal spiking activity (MUA) and in the high-frequency (300-900 Hz) component of the local field potential (HF-LFP), believed to reflect local spiking activity. Rats were trained to run many trials on a large circular platform, either to LED-cued goal locations or as a spatial sequence from memory. Tuning to specific self-motion states was observed consistently, and exhibited distinct cortical depth-invariant coding properties. These patterns of collective local and laminar activation during behavior were reactivated in compressed form during post-experience sleep, and temporally coupled to hippocampal sharp wave ripples. Thus, PC neuron motion encoding is consistent across cortical laminae, and this consistency is maintained during memory reactivation.

scholarly journals Laminar Organization of Encoding and Memory Reactivation in the Parietal Cortex

Neuron ◽  
2017 ◽  
Vol 95 (6) ◽  
pp. 1406-1419.e5 ◽  
Author(s):  
Aaron A. Wilber ◽  
Ivan Skelin ◽  
Wei Wu ◽  
Bruce L. McNaughton
Keyword(s):  
Parietal Cortex ◽  
Laminar Organization ◽  
Memory Reactivation

scholarly journals The Temporal Pattern of Spiking Activity of a Thalamic Neuron are Related to the Amplitude of the Cortical Local Field Potential

2021 ◽  
Author(s):  
Hiroshi Tamura
Keyword(s):  
Local Field ◽  
Local Field Potential ◽  
High Frequency ◽  
Temporal Pattern ◽  
Temporal Summation ◽  
Field Potential ◽  
Cortical Activation ◽  
Thalamic Neuron ◽  
Short Period ◽  
Spiking Activity

AbstractNeuron activity in the sensory cortices mainly depends on feedforward thalamic inputs. High-frequency activity of a thalamic input can be temporally integrated by a neuron in the sensory cortex and is likely to induce larger depolarization. However, feedforward inhibition (FFI) and depression of excitatory synaptic transmission in thalamocortical pathways attenuate depolarization induced by the latter part of high-frequency spiking activity and the temporal summation may not be effective. The spiking activity of a thalamic neuron in a specific temporal pattern may circumvent FFI and depression of excitatory synapses. The present study determined the relationship between the temporal pattern of spiking activity of a single thalamic neuron and the degree of cortical activation as well as that between the firing rate of spiking activity of a single thalamic neuron and the degree of cortical activation. Spiking activity of a thalamic neuron was recorded extracellularly from the lateral geniculate nucleus (LGN) in male Long-Evans rats. Degree of cortical activation was assessed by simultaneous recording of local field potential (LFP) from the visual cortex. A specific temporal pattern appearing in three consecutive spikes of an LGN neuron induced larger cortical LFP modulation than high-frequency spiking activity during a short period. These findings indicate that spiking activity of thalamic inputs is integrated by a synaptic mechanism sensitive to an input temporal pattern.Significance StatementSensory cortical activity depends on thalamic inputs. Despite the importance of thalamocortical transmission, how spiking activity of thalamic inputs is integrated by cortical neurons remains unclear. Feedforward inhibition and synaptic depression of excitatory transmission may not allow simple temporal summation of membrane potential induced by consecutive spiking activity of a thalamic neuron. A specific temporal pattern appearing in three consecutive spikes of a thalamic neuron induced larger cortical local field potential modulation than high-frequency spiking activity during a short period. The findings indicate the importance of the temporal pattern of spiking activity of a single thalamic neuron on cortical activation.

scholarly journals Ripples reflect a spectrum of synchronous spiking activity in human anterior temporal lobe

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Ai Phuong S Tong ◽  
Alex P Vaz ◽  
John H Wittig ◽  
Sara K Inati ◽  
Kareem A Zaghloul
Keyword(s):  
Temporal Lobe ◽  
High Frequency ◽  
Temporal Cortex ◽  
Field Potential ◽  
Human Memory ◽  
Dynamic Coordination ◽  
Macro Scale ◽  
High Frequency Activity ◽  
Fast Oscillations ◽  
Spiking Activity

Direct brain recordings have provided important insights into how high frequency activity captured through intracranial EEG (iEEG) supports human memory retrieval. The extent to which such activity is comprised of transient fluctuations that reflect the dynamic coordination of underlying neurons, however, remains unclear. Here, we simultaneously record iEEG, local field potential (LFP), and single unit activity in the human temporal cortex. We demonstrate that fast oscillations within the previously identified 80-120 Hz ripple band contribute to 70-200 Hz high frequency activity in the human cortex. These ripple oscillations exhibit a spectrum of amplitudes and durations related to the amount of underlying neuronal spiking. Ripples in the macro-scale iEEG are related to the number and synchrony of ripples in the micro-scale LFP, which in turn are related to the synchrony of neuronal spiking. Our data suggest that neural activity in the human temporal lobe is organized into transient bouts of ripple oscillations that reflect underlying bursts of spiking activity.

scholarly journals Sensory feedback-dependent coding of arm position in local field potentials of the posterior parietal cortex

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Paul VanGilder ◽  
Ying Shi ◽  
Gregory Apker ◽  
Christopher A. Buneo
Keyword(s):  
Local Field ◽  
Sensory Feedback ◽  
Posterior Parietal Cortex ◽  
Spectral Power ◽  
Field Potential ◽  
Beta Activity ◽  
Beta Band ◽  
Arm Position ◽  
Multisensory Interactions ◽  
Spiking Activity

AbstractAlthough multisensory integration is crucial for sensorimotor function, it is unclear how visual and proprioceptive sensory cues are combined in the brain during motor behaviors. Here we characterized the effects of multisensory interactions on local field potential (LFP) activity obtained from the superior parietal lobule (SPL) as non-human primates performed a reaching task with either unimodal (proprioceptive) or bimodal (visual-proprioceptive) sensory feedback. Based on previous analyses of spiking activity, we hypothesized that evoked LFP responses would be tuned to arm location but would be suppressed on bimodal trials, relative to unimodal trials. We also expected to see a substantial number of recording sites with enhanced beta band spectral power for only one set of feedback conditions (e.g. unimodal or bimodal), as was previously observed for spiking activity. We found that evoked activity and beta band power were tuned to arm location at many individual sites, though this tuning often differed between unimodal and bimodal trials. Across the population, both evoked and beta activity were consistent with feedback-dependent tuning to arm location, while beta band activity also showed evidence of response suppression on bimodal trials. The results suggest that multisensory interactions can alter the tuning and gain of arm position-related LFP activity in the SPL.

scholarly journals Superimposed gratings induce diverse response patterns of gamma oscillations in primary visual cortex

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Bin Wang ◽  
Chuanliang Han ◽  
Tian Wang ◽  
Weifeng Dai ◽  
Yang Li ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Field Potential ◽  
Gamma Oscillations ◽  
Neural Mechanisms ◽  
Model Parameters ◽  
Response Patterns ◽  
Region Difference ◽  
High Gamma ◽  
Spiking Activity

AbstractStimulus-dependence of gamma oscillations (GAMMA, 30–90 Hz) has not been fully understood, but it is important for revealing neural mechanisms and functions of GAMMA. Here, we recorded spiking activity (MUA) and the local field potential (LFP), driven by a variety of plaids (generated by two superimposed gratings orthogonal to each other and with different contrast combinations), in the primary visual cortex of anesthetized cats. We found two distinct narrow-band GAMMAs in the LFPs and a variety of response patterns to plaids. Similar to MUA, most response patterns showed that the second grating suppressed GAMMAs driven by the first one. However, there is only a weak site-by-site correlation between cross-orientation interactions in GAMMAs and those in MUAs. We developed a normalization model that could unify the response patterns of both GAMMAs and MUAs. Interestingly, compared with MUAs, the GAMMAs demonstrated a wider range of model parameters and more diverse response patterns to plaids. Further analysis revealed that normalization parameters for high GAMMA, but not those for low GAMMA, were significantly correlated with the discrepancy of spatial frequency between stimulus and sites’ preferences. Consistent with these findings, normalization parameters and diversity of high GAMMA exhibited a clear transition trend and region difference between area 17 to 18. Our results show that GAMMAs are also regulated in the form of normalization, but that the neural mechanisms for these normalizations might differ from those of spiking activity. Normalizations in different brain signals could be due to interactions of excitation and inhibitions at multiple stages in the visual system.

scholarly journals Outcome contingency selectively affects the neural coding of outcomes but not of tasks

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
David Wisniewski ◽  
Birte Forstmann ◽  
Marcel Brass
Keyword(s):  
Decision Making ◽  
Parietal Cortex ◽  
Neural Coding ◽  
Free Choice ◽  
Pattern Analysis ◽  
Maintenance Phase ◽  
Large Network ◽  
Multivariate Pattern Analysis ◽  
Multivariate Pattern

AbstractValue-based decision-making is ubiquitous in every-day life, and critically depends on the contingency between choices and their outcomes. Only if outcomes are contingent on our choices can we make meaningful value-based decisions. Here, we investigate the effect of outcome contingency on the neural coding of rewards and tasks. Participants performed a reversal-learning paradigm in which reward outcomes were contingent on trial-by-trial choices, and performed a ‘free choice’ paradigm in which rewards were random and not contingent on choices. We hypothesized that contingent outcomes enhance the neural coding of rewards and tasks, which was tested using multivariate pattern analysis of fMRI data. Reward outcomes were encoded in a large network including the striatum, dmPFC and parietal cortex, and these representations were indeed amplified for contingent rewards. Tasks were encoded in the dmPFC at the time of decision-making, and in parietal cortex in a subsequent maintenance phase. We found no evidence for contingency-dependent modulations of task signals, demonstrating highly similar coding across contingency conditions. Our findings suggest selective effects of contingency on reward coding only, and further highlight the role of dmPFC and parietal cortex in value-based decision-making, as these were the only regions strongly involved in both reward and task coding.

Pattern Filtering for Detection of Neural Activity, with Examples from HVc Activity During Sleep in Zebra Finches

2003 ◽  
Vol 15 (10) ◽  
pp. 2307-2337 ◽  
Author(s):  
Zhiyi Chi ◽  
Peter L. Rauske ◽  
Daniel Margoliash
Keyword(s):  
Neural Coding ◽  
Point Processes ◽  
Statistical Significance ◽  
Test Procedure ◽  
Surrogate Data ◽  
Likelihood Ratios ◽  
Alignment Procedure ◽  
Auditory Evoked Response ◽  
The Individual ◽  
Spiking Activity

The detection of patterned spiking activity is important in the study of neural coding. A pattern filtering approach is developed for pattern detection under the framework of point processes, which offers flexibility in combining temporal details and firing rates. The detection combines multiple steps of filtering in a coarse-to-fine manner. Under some conditional Poisson assumptions on the spiking activity, each filtering step is equivalent to classifying by likelihood ratios all the data segments as targets or as background sequences. Unlike previous studies, where global surrogate data were used to evaluate the statistical significance of the detected patterns, a localizedp-test procedure is developed, which better accounts for firing modulation and nonstationarity in spiking activity. Common temporal structures of patterned activity are learned using an entropy-based alignment procedure, without relying on metrics or pair-wise alignment. Applications of pattern filtering to single, presumptive interneurons recorded in the nucleus HVc of zebra finch are illustrated. These demonstrate a match between the auditory-evoked response to playback of the individual bird's own song and spontaneous activity during sleep. Small temporal compression or expansion, or both, is required for optimal matching of spontaneous patterns to stimulus-evoked activity.

Spike Timing of Lacunosom-Moleculare Targeting Interneurons and CA3 Pyramidal Cells During High-Frequency Network Oscillations In Vitro

2007 ◽  
Vol 98 (1) ◽  
pp. 96-104 ◽  
Author(s):  
Jay Spampanato ◽  
Istvan Mody
Keyword(s):  
High Frequency ◽  
Epileptiform Activity ◽  
Field Potential ◽  
Pyramidal Cells ◽  
Gamma Oscillations ◽  
Spike Timing ◽  
Network Activity ◽  
Network Oscillations ◽  
Ca3 Pyramidal Cells

Network activity in the 200- to 600-Hz range termed high-frequency oscillations (HFOs) has been detected in epileptic tissue from both humans and rodents and may underlie the mechanism of epileptogenesis in experimental rodent models. Slower network oscillations including theta and gamma oscillations as well as ripples are generated by the complex spike timing and interactions between interneurons and pyramidal cells of the hippocampus. We determined the activity of CA3 pyramidal cells, stratum oriens lacunosum-moleculare (O-LM) and s. radiatum lacunosum-moleculare (R-LM) interneurons during HFO in the in vitro low-Mg2+ model of epileptiform activity in GIN mice. In these animals, interneurons can be identified prior to cell-attached recordings by the expression of green-fluorescent protein (GFP). Simultaneous local field potential recordings from s. pyramidale and on-cell recordings of individual interneurons and principal cells revealed three primary firing behaviors of the active cells: 36% of O-LM interneurons and 60% of pyramidal cells fired action potentials at high frequencies during the HFO. R-LM interneurons were biphasic in that they fired at high frequency at the beginning of the HFO but stopped firing before its end. When considering only the highest frequency component of the oscillations most pyramidal cells fired on the rising phase of the oscillation. These data provide evidence for functional distinction during HFOs within otherwise homogeneous groups of O-LM interneurons and pyramidal cells.

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