scholarly journals Spontaneous dynamics of neural networks in deep layers of prefrontal cortex

2017 ◽  
Vol 117 (4) ◽  
pp. 1581-1594 ◽  
Author(s):  
Andrew S. Blaeser ◽  
Barry W. Connors ◽  
Arto V. Nurmikko
Keyword(s):  
Prefrontal Cortex ◽  
Spontaneous Activity ◽  
Calcium Imaging ◽  
Cortical Neurons ◽  
Rhythmic Activity ◽  
Network Activity ◽  
Local Networks ◽  
Spatiotemporal Scale ◽  
Deep Layers ◽  
Delta Oscillations

Cortical systems maintain and process information through the sustained activation of recurrent local networks of neurons. Layer 5 is known to have a major role in generating the recurrent activation associated with these functions, but relatively little is known about its intrinsic dynamics at the mesoscopic level of large numbers of neighboring neurons. Using calcium imaging, we measured the spontaneous activity of networks of deep-layer medial prefrontal cortical neurons in an acute slice model. Inferring the simultaneous activity of tens of neighboring neurons, we found that while the majority showed only sporadic activity, a subset of neurons engaged in sustained delta frequency rhythmic activity. Spontaneous activity under baseline conditions was weakly correlated between pairs of neurons, and rhythmic neurons showed little coherence in their oscillations. However, we consistently observed brief bouts of highly synchronous activity that must be attributed to network activity. NMDA-mediated stimulation enhanced rhythmicity, synchrony, and correlation within these local networks. These results characterize spontaneous prefrontal activity at a previously unexplored spatiotemporal scale and suggest that medial prefrontal cortex can act as an intrinsic generator of delta oscillations. NEW & NOTEWORTHY Using calcium imaging and a novel analytic framework, we characterized the spontaneous and NMDA-evoked activity of layer 5 prefrontal cortex at a largely unexplored spatiotemporal scale. Our results suggest that the mPFC microcircuitry is capable of intrinsically generating delta oscillations and sustaining synchronized network activity that is potentially relevant for understanding its contribution to cognitive processes.

scholarly journals Rapid Temporal Modulation of Synchrony by Competition in Cortical Interneuron Networks

2004 ◽  
Vol 16 (2) ◽  
pp. 251-275 ◽  
Author(s):  
P.H.E. Tiesinga ◽  
T. J. Sejnowski
Keyword(s):  
Cortical Neurons ◽  
Pyramidal Neurons ◽  
Background Activity ◽  
Pyramidal Cells ◽  
Spike Timing ◽  
Network Activity ◽  
Local Networks ◽  
Rapid Changes ◽  
Asynchronous State ◽  
The Impact

The synchrony of neurons in extrastriate visual cortex is modulated by selective attention even when there are only small changes in firing rate (Fries, Reynolds, Rorie, & Desimone, 2001). We used Hodgkin-Huxley type models of cortical neurons to investigate the mechanism by which the degree of synchrony can be modulated independently of changes in firing rates. The synchrony of local networks of model cortical interneurons interacting through GABAA synapses was modulated on a fast timescale by selectively activating a fraction of the interneurons. The activated interneurons became rapidly synchronized and suppressed the activity of the other neurons in the network but only if the network was in a restricted range of balanced synaptic background activity. During stronger background activity, the network did not synchronize, and for weaker background activity, the network synchronized but did not return to an asynchronous state after synchronizing. The inhibitory output of the network blocked the activity of pyramidal neurons during asynchronous network activity, and during synchronous network activity, it enhanced the impact of the stimulus-related activity of pyramidal cells on receiving cortical areas (Salinas & Sejnowski, 2001). Synchrony by competition provides a mechanism for controlling synchrony with minor alterations in rate, which could be useful for information processing. Because traditional methods such as cross-correlation and the spike field coherence require several hundred milliseconds of recordings and cannot measure rapid changes in the degree of synchrony, we introduced a new method to detect rapid changes in the degree of coincidence and precision of spike timing.

scholarly journals Common coding of expected value and value uncertainty memories in the prefrontal cortex and basal ganglia output

2021 ◽  
Vol 7 (20) ◽  
pp. eabe0693
Author(s):  
Ali Ghazizadeh ◽  
Okihide Hikosaka
Keyword(s):  
Prefrontal Cortex ◽  
Basal Ganglia ◽  
Cortical Neurons ◽  
Expected Value ◽  
Common Coding ◽  
Repetition Suppression ◽  
Free Viewing ◽  
Gaze Bias ◽  
Single Unit Recordings ◽  
Value Preferences

Recent evidence implicates both basal ganglia and ventrolateral prefrontal cortex (vlPFC) in encoding value memories. However, comparative roles of cortical and basal nodes in value memory are not well understood. Here, single-unit recordings in vlPFC and substantia nigra reticulata (SNr), within macaque monkeys, revealed a larger value signal in SNr that was nevertheless correlated with and had a comparable onset to the vlPFC value signal. The value signal was maintained for many objects (>90) many weeks after reward learning and was resistant to extinction in both regions and to repetition suppression in vlPFC. Both regions showed comparable granularity in encoding expected value and value uncertainty, which was paralleled by enhanced gaze bias during free viewing. The value signal dynamics in SNr could be predicted by combining responses of vlPFC neurons according to their value preferences consistent with a scheme in which cortical neurons reached SNr via direct and indirect pathways.

scholarly journals Altered network properties in C9ORF72 repeat expansion cortical neurons are due to synaptic dysfunction

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Emma M. Perkins ◽  
Karen Burr ◽  
Poulomi Banerjee ◽  
Arpan R. Mehta ◽  
Owen Dando ◽  
...  
Keyword(s):  
Synaptic Plasticity ◽  
Synaptic Vesicle ◽  
Cortical Neurons ◽  
Electrode Array ◽  
Repeat Expansion ◽  
Cortical Network ◽  
Synaptic Function ◽  
Network Activity ◽  
Cortical Function ◽  
Network Function

Abstract Background Physiological disturbances in cortical network excitability and plasticity are established and widespread in amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) patients, including those harbouring the C9ORF72 repeat expansion (C9ORF72RE) mutation – the most common genetic impairment causal to ALS and FTD. Noting that perturbations in cortical function are evidenced pre-symptomatically, and that the cortex is associated with widespread pathology, cortical dysfunction is thought to be an early driver of neurodegenerative disease progression. However, our understanding of how altered network function manifests at the cellular and molecular level is not clear. Methods To address this we have generated cortical neurons from patient-derived iPSCs harbouring C9ORF72RE mutations, as well as from their isogenic expansion-corrected controls. We have established a model of network activity in these neurons using multi-electrode array electrophysiology. We have then mechanistically examined the physiological processes underpinning network dysfunction using a combination of patch-clamp electrophysiology, immunocytochemistry, pharmacology and transcriptomic profiling. Results We find that C9ORF72RE causes elevated network burst activity, associated with enhanced synaptic input, yet lower burst duration, attributable to impaired pre-synaptic vesicle dynamics. We also show that the C9ORF72RE is associated with impaired synaptic plasticity. Moreover, RNA-seq analysis revealed dysregulated molecular pathways impacting on synaptic function. All molecular, cellular and network deficits are rescued by CRISPR/Cas9 correction of C9ORF72RE. Our study provides a mechanistic view of the early dysregulated processes that underpin cortical network dysfunction in ALS-FTD. Conclusion These findings suggest synaptic pathophysiology is widespread in ALS-FTD and has an early and fundamental role in driving altered network function that is thought to contribute to neurodegenerative processes in these patients. The overall importance is the identification of previously unidentified defects in pre and postsynaptic compartments affecting synaptic plasticity, synaptic vesicle stores, and network propagation, which directly impact upon cortical function.

scholarly journals A supervised machine learning approach to characterize spinal network function

2019 ◽  
Vol 121 (6) ◽  
pp. 2001-2012 ◽  
Author(s):  
A. N. Dalrymple ◽  
S. A. Sharples ◽  
N. Osachoff ◽  
A. P. Lognon ◽  
P. J. Whelan
Keyword(s):  
Machine Learning ◽  
Spinal Cord ◽  
Nervous System ◽  
Spontaneous Activity ◽  
Machine Learning Algorithms ◽  
Supervised Machine Learning ◽  
Network Activity ◽  
Multilayer Perceptrons ◽  
Network Development ◽  
Newborn Mice

Spontaneous activity is a common feature of immature neuronal networks throughout the central nervous system and plays an important role in network development and consolidation. In postnatal rodents, spontaneous activity in the spinal cord exhibits complex, stochastic patterns that have historically proven challenging to characterize. We developed a software tool for quickly and automatically characterizing and classifying episodes of spontaneous activity generated from developing spinal networks. We recorded spontaneous activity from in vitro lumbar ventral roots of 16 neonatal [postnatal day (P)0–P3] mice. Recordings were DC coupled and detrended, and episodes were separated for analysis. Amplitude-, duration-, and frequency-related features were extracted from each episode and organized into five classes. Paired classes and features were used to train and test supervised machine learning algorithms. Multilayer perceptrons were used to classify episodes as rhythmic or multiburst. We increased network excitability with potassium chloride and tested the utility of the tool to detect changes in features and episode class. We also demonstrate usability by having a novel experimenter use the program to classify episodes collected at a later time point (P5). Supervised machine learning-based classification of episodes accounted for changes that traditional approaches cannot detect. Our tool, named SpontaneousClassification, advances the detail in which we can study not only developing spinal networks, but also spontaneous networks in other areas of the nervous system.NEW & NOTEWORTHY Spontaneous activity is important for nervous system network development and consolidation. Our software uses machine learning to automatically and quickly characterize and classify episodes of spontaneous activity in the spinal cord of newborn mice. It detected changes in network activity following KCl-enhanced excitation. Using our software to classify spontaneous activity throughout development, in pathological models, or with neuromodulation, may offer insight into the development and organization of spinal circuits.

Aldolase C/Zebrin II is Released to the Extracellular Space after Stroke and Inhibits the Network Activity of Cortical Neurons

2006 ◽  
Vol 31 (11) ◽  
pp. 1297-1303 ◽  
Author(s):  
Stephanie Linke ◽  
Philipp Goertz ◽  
Stephan L. Baader ◽  
Volkmar Gieselmann ◽  
Mario Siebler ◽  
...  
Keyword(s):  
Cortical Neurons ◽  
Extracellular Space ◽  
Network Activity ◽  
Aldolase C ◽  
Zebrin Ii

scholarly journals The NKCC1 antagonist bumetanide mitigates interneuronopathy associated with ethanol exposure in utero

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Alexander GJ Skorput ◽  
Stephanie M Lee ◽  
Pamela WL Yeh ◽  
Hermes H Yeh
Keyword(s):  
Prefrontal Cortex ◽  
Cortical Neurons ◽  
Fetal Alcohol Spectrum Disorders ◽  
Behavioral Flexibility ◽  
Ethanol Exposure ◽  
Embryonic Mouse ◽  
Form And Function ◽  
Tangential Migration ◽  
And Function

Prenatal exposure to ethanol induces aberrant tangential migration of corticopetal GABAergic interneurons, and long-term alterations in the form and function of the prefrontal cortex. We have hypothesized that interneuronopathy contributes significantly to the pathoetiology of fetal alcohol spectrum disorders (FASD). Activity-dependent tangential migration of GABAergic cortical neurons is driven by depolarizing responses to ambient GABA present in the cortical enclave. We found that ethanol exposure potentiates the depolarizing action of GABA in GABAergic cortical interneurons of the embryonic mouse brain. Pharmacological antagonism of the cotransporter NKCC1 mitigated ethanol-induced potentiation of GABA depolarization and prevented aberrant patterns of tangential migration induced by ethanol in vitro. In a model of FASD, maternal bumetanide treatment prevented interneuronopathy in the prefrontal cortex of ethanol exposed offspring, including deficits in behavioral flexibility. These findings position interneuronopathy as a mechanism of FASD symptomatology, and posit NKCC1 as a pharmacological target for the management of FASD.

scholarly journals Oxytocin shapes spontaneous activity patterns in the developing visual cortex by activating somatostatin interneurons

2019 ◽  
Author(s):  
Paloma P Maldonado ◽  
Alvaro Nuno-Perez ◽  
Jan Kirchner ◽  
Elizabeth Hammock ◽  
Julijana Gjorgjieva ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Spontaneous Activity ◽  
Sensory Processing ◽  
Activity Patterns ◽  
Network Activity ◽  
Synaptic Connections ◽  
Pairwise Correlations ◽  
Early Brain Development

SummarySpontaneous network activity shapes emerging neuronal circuits during early brain development, however how neuromodulation influences this activity is not fully understood. Here, we report that the neuromodulator oxytocin powerfully shapes spontaneous activity patterns. In vivo, oxytocin strongly decreased the frequency and pairwise correlations of spontaneous activity events in visual cortex (V1), but not in somatosensory cortex (S1). This differential effect was a consequence of oxytocin only increasing inhibition in V1 and increasing both inhibition and excitation in S1. The increase in inhibition was mediated by the depolarization and increase in excitability of somatostatin+ (SST) interneurons specifically. Accordingly, silencing SST+ neurons pharmacogenetically fully blocked oxytocin’s effect on inhibition in vitro as well its effect on spontaneous activity patterns in vivo. Thus, oxytocin decreases the excitatory/inhibitory ratio and modulates specific features of V1 spontaneous activity patterns that are crucial for refining developing synaptic connections and sensory processing later in life.

Sign in / Sign up

Export Citation Format

Share Document