Development, learning and memory in large random networks of cortical neurons: lessons beyond anatomy

2002 ◽  
Vol 35 (1) ◽  
pp. 63-87 ◽  
Author(s):  
Shimon Marom ◽  
Goded Shahaf
Keyword(s):  
Functional Connectivity ◽  
Spontaneous Activity ◽  
Learning And Memory ◽  
Cortical Neurons ◽  
Ex Vivo ◽  
Adaptive Responses ◽  
Cortical Networks ◽  
Neural Learning ◽  
Wide Range ◽  
Activity Dependent

1. Introduction 631.1 Outline 631.2 Universals versus realizations in the study of learning and memory 642. Large random cortical networks developing ex vivo 652.1 Preparation 652.2 Measuring electrical activity 673. Spontaneous development 693.1 Activity 693.2 Connectivity 704. Consequences of spontaneous activity: pharmacological manipulations 724.1 Structural consequences 724.2 Functional consequences 735. Effects of stimulation 745.1 Response to focal stimulation 745.2 Stimulation-induced changes in connectivity 746. Embedding functionality in real neural networks 776.1 Facing the physiological definition of ‘reward’: two classes of theories 786.2 Closing the loop 797. Concluding remarks 848. Acknowledgments 859. References 85The phenomena of learning and memory are inherent to neural systems that differ from each other markedly. The differences, at the molecular, cellular and anatomical levels, reflect the wealth of possible instantiations of two neural learning and memory universals: (i) an extensive functional connectivity that enables a large repertoire of possible responses to stimuli; and (ii) sensitivity of the functional connectivity to activity, allowing for selection of adaptive responses. These universals can now be fully realized in ex-vivo developing neuronal networks due to advances in multi-electrode recording techniques and desktop computing. Applied to the study of ex-vivo networks of neurons, these approaches provide a unique view into learning and memory in networks, over a wide range of spatio-temporal scales. In this review, we summarize experimental data obtained from large random developing ex-vivo cortical networks. We describe how these networks are prepared, their structure, stages of functional development, and the forms of spontaneous activity they exhibit (Sections 2–4). In Section 5 we describe studies that seek to characterize the rules of activity-dependent changes in neural ensembles and their relation to monosynaptic rules. In Section 6, we demonstrate that it is possible to embed functionality into ex-vivo networks, that is, to teach them to perform desired firing patterns in both time and space. This requires ‘closing a loop’ between the network and the environment. Section 7 emphasizes the potential of ex-vivo developing cortical networks in the study of neural learning and memory universals. This may be achieved by combining closed loop experiments and ensemble-defined rules of activity-dependent change.

scholarly journals Quantitative differences in developmental profiles of spontaneous activity in cortical and hippocampal cultures

2014 ◽  
Author(s):  
Paul Charlesworth ◽  
Ellese Cotterill ◽  
Andrew Morton ◽  
Seth Grant ◽  
Stephen Eglen
Keyword(s):  
Spontaneous Activity ◽  
Cortical Neurons ◽  
Activity Patterns ◽  
Machine Learning Techniques ◽  
Multielectrode Arrays ◽  
Cortical Networks ◽  
Hippocampal Cultures ◽  
Hippocampal Networks ◽  
Cultured Networks

Background: Neural circuits can spontaneously generate complex spatiotemporal firing patterns during development. This spontaneous activity is thought to help guide development of the nervous system. In this study, we had two aims. First, to characterise the changes in spontaneous activity in cultures of developing networks of either hippocampal or cortical neurons dissociated from mouse. Second, to assess whether there are any functional differences in the patterns of activity in hippocampal and cortical networks. Results: We used multielectrode arrays to record the development of spontaneous activity in cultured networks of either hippocampal or cortical neurons every two or three days for the first month after plating. Within a few days of culturing, networks exhibited spontaneous activity. This activity strengthened and then stabilised typically around 21 days in vitro. We quantified the activity patterns in hippocampal and cortical networks using eleven features. Three out of eleven features showed striking differences in activity between hippocampal and cortical networks. 1: Interburst intervals are less variable in spike trains from hippocampal cultures. 2: Hippocampal networks have higher correlations. 3: Hippocampal networks generate more robust theta bursting patterns. Machine learning techniques confirmed that these differences in patterning are sufficient to reliably classify recordings at any given age as either hippocampal or cortical networks. Conclusions: Although cultured networks of hippocampal and cortical networks both generate spontaneous activity that changes over time, at any given time we can reliably detect differences in the activity patterns. We anticipate that this quantitative framework could have applications in many areas, including neurotoxicity testing and for characterising phenotype of different mutant mice. All code and data relating to this report are freely available for others to use.

scholarly journals On the Use of Dynamic Bayesian Networks in Reconstructing Functional Neuronal Networks from Spike Train Ensembles

2010 ◽  
Vol 22 (1) ◽  
pp. 158-189 ◽  
Author(s):  
Seif Eldawlatly ◽  
Yang Zhou ◽  
Rong Jin ◽  
Karim G. Oweiss
Keyword(s):  
Bayesian Networks ◽  
Spike Train ◽  
Cortical Neurons ◽  
Effective Connectivity ◽  
Dynamic Bayesian Networks ◽  
Time Varying ◽  
Cortical Networks ◽  
Highly Nonlinear ◽  
Wide Range ◽  
High Level

Coordination among cortical neurons is believed to be a key element in mediating many high-level cortical processes such as perception, attention, learning, and memory formation. Inferring the structure of the neural circuitry underlying this coordination is important to characterize the highly nonlinear, time-varying interactions between cortical neurons in the presence of complex stimuli. In this work, we investigate the applicability of dynamic Bayesian networks (DBNs) in inferring the effective connectivity between spiking cortical neurons from their observed spike trains. We demonstrate that DBNs can infer the underlying nonlinear and time-varying causal interactions between these neurons and can discriminate between mono- and polysynaptic links between them under certain constraints governing their putative connectivity. We analyzed conditionally Poisson spike train data mimicking spiking activity of cortical networks of small and moderately large size. The performance was assessed and compared to other methods under systematic variations of the network structure to mimic a wide range of responses typically observed in the cortex. Results demonstrate the utility of DBN in inferring the effective connectivity in cortical networks.

scholarly journals Comparative AAV-eGFP Transgene Expression Using Vector Serotypes 1–9, 7m8, and 8b in Human Pluripotent Stem Cells, RPEs, and Human and Rat Cortical Neurons

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Thu T. Duong ◽  
James Lim ◽  
Vidyullatha Vasireddy ◽  
Tyler Papp ◽  
Hung Nguyen ◽  
...  
Keyword(s):  
Cortical Neurons ◽  
Transgene Expression ◽  
Fluorescent Protein ◽  
Ex Vivo ◽  
Cell Types ◽  
Egfp Expression ◽  
Cell Type ◽  
Egfp Gene ◽  
Rat Cortical Neurons

Recombinant adeno-associated virus (rAAV), produced from a nonpathogenic parvovirus, has become an increasing popular vector for gene therapy applications in human clinical trials. However, transduction and transgene expression of rAAVs can differ acrossin vitroand ex vivo cellular transduction strategies. This study compared 11 rAAV serotypes, carrying one reporter transgene cassette containing a cytomegalovirus immediate-early enhancer (eCMV) and chicken beta actin (CBA) promoter driving the expression of an enhanced green-fluorescent protein (eGFP) gene, which was transduced into four different cell types: human iPSC, iPSC-derived RPE, iPSC-derived cortical, and dissociated embryonic day 18 rat cortical neurons. Each cell type was exposed to three multiplicity of infections (MOI: 1E4, 1E5, and 1E6 vg/cell). After 24, 48, 72, and 96 h posttransduction, GFP-expressing cells were examined and compared across dosage, time, and cell type. Retinal pigmented epithelium showed highest AAV-eGFP expression and iPSC cortical the lowest. At an MOI of 1E6 vg/cell, all serotypes show measurable levels of AAV-eGFP expression; moreover, AAV7m8 and AAV6 perform best across MOI and cell type. We conclude that serotype tropism is not only capsid dependent but also cell type plays a significant role in transgene expression dynamics.

scholarly journals Long-Lasting Hyperexcitability Induced by Depolarization in the Absence of Detectable Ca2+ Signals

2009 ◽  
Vol 101 (3) ◽  
pp. 1351-1360 ◽  
Author(s):  
Kumud K. Kunjilwar ◽  
Harvey M. Fishman ◽  
Dario J. Englot ◽  
Roger G. O'Neil ◽  
Edgar T. Walters
Keyword(s):  
Protein Synthesis ◽  
Neuronal Injury ◽  
Adaptive Responses ◽  
Neuronal Responses ◽  
Local Protein Synthesis ◽  
Neuronal Viability ◽  
Nerve Ganglion ◽  
Dissociated Cell Culture ◽  
Activity Dependent

Learning and memory depend on neuronal alterations induced by electrical activity. Most examples of activity-dependent plasticity, as well as adaptive responses to neuronal injury, have been linked explicitly or implicitly to induction by Ca2+ signals produced by depolarization. Indeed, transient Ca2+ signals are commonly assumed to be the only effective transducers of depolarization into adaptive neuronal responses. Nevertheless, Ca2+-independent depolarization-induced signals might also trigger plastic changes. Establishing the existence of such signals is a challenge because procedures that eliminate Ca2+ transients also impair neuronal viability and tolerance to cellular stress. We have taken advantage of nociceptive sensory neurons in the marine snail Aplysia, which exhibit unusual tolerance to extreme reduction of extracellular and intracellular free Ca2+ levels. The axons of these neurons exhibit a depolarization-induced memory-like hyperexcitability that lasts a day or longer and depends on local protein synthesis for induction. Here we show that transient localized depolarization of these axons in an excised nerve–ganglion preparation or in dissociated cell culture can induce short- and intermediate-term axonal hyperexcitability as well as long-term protein synthesis–dependent hyperexcitability under conditions in which Ca2+ entry is prevented (by bathing in nominally Ca2+ -free solutions containing EGTA) and detectable Ca2+ transients are eliminated (by adding BAPTA-AM). Disruption of Ca2+ release from intracellular stores by pretreatment with thapsigargin also failed to affect induction of axonal hyperexcitability. These findings suggest that unrecognized Ca2+-independent signals exist that can transduce intense depolarization into adaptive cellular responses during neuronal injury, prolonged high-frequency activity, or other sustained depolarizing events.

scholarly journals A Putative Cro-Like Repressor Contributes to Arylomycin Resistance in Staphylococcus aureus

2015 ◽  
Vol 59 (6) ◽  
pp. 3066-3074 ◽  
Author(s):  
Arryn Craney ◽  
Floyd E. Romesberg
Keyword(s):  
Staphylococcus Aureus ◽  
Ex Vivo ◽  
Transcriptional Regulator ◽  
Signal Peptidase ◽  
Health Concern ◽  
Resistant Bacteria ◽  
Type I ◽  
Wall Teichoic Acid ◽  
Content Type ◽  
Wide Range

ABSTRACTAntibiotic-resistant bacteria are a significant public health concern and motivate efforts to develop new classes of antibiotics. One such class of antibiotics is the arylomycins, which target type I signal peptidase (SPase), the enzyme responsible for the release of secreted proteins from their N-terminal leader sequences. Despite the essentiality, conservation, and relative accessibility of SPase, the activity of the arylomycins is limited against some bacteria, including the important human pathogenStaphylococcus aureus. To understand the origins of the limited activity againstS. aureus, we characterized the susceptibility of a panel of strains to two arylomycin derivatives, arylomycin A-C16and its more potent analog arylomycin M131. We observed a wide range of susceptibilities to the two arylomycins and found that resistant strains were sensitized by cotreatment with tunicamycin, which inhibits the first step of wall teichoic acid synthesis. To further understand howS. aureusresponds to the arylomycins, we profiled the transcriptional response ofS. aureusNCTC 8325 to growth-inhibitory concentrations of arylomycin M131 and found that it upregulates the cell wall stress stimulon (CWSS) and an operon consisting of a putative transcriptional regulator and three hypothetical proteins. Interestingly, we found that mutations in the putative transcriptional regulator are correlated with resistance, and selection for resistanceex vivodemonstrated that mutations in this gene are sufficient for resistance. The results begin to elucidate howS. aureuscopes with secretion stress and how it evolves resistance to the inhibition of SPase.

scholarly journals Ketamine decreases neuronally released glutamate via retrograde stimulation of presynaptic adenosine A1 receptors

2021 ◽  
Author(s):  
Vesna Lazarevic ◽  
Yunting Yang ◽  
Ivana Flais ◽  
Per Svenningsson
Keyword(s):  
Cortical Neurons ◽  
Intracellular Signaling ◽  
Ex Vivo ◽  
Forced Swim Test ◽  
Glutamate Release ◽  
Neuronal Cultures ◽  
Extracellular Glutamate ◽  
Primary Neuronal Cultures ◽  
Adenosine A1 Receptors ◽  
Adenosine A1

AbstractKetamine produces a rapid antidepressant response in patients with major depressive disorder (MDD), but the underlying mechanisms appear multifaceted. One hypothesis, proposes that by antagonizing NMDA receptors on GABAergic interneurons, ketamine disinhibits afferens to glutamatergic principal neurons and increases extracellular glutamate levels. However, ketamine seems also to reduce rapid glutamate release at some synapses. Therefore, clinical studies in MDD patients have stressed the need to identify mechanisms whereby ketamine decreases presynaptic activity and glutamate release. In the present study, the effect of ketamine and its antidepressant metabolite, (2R,6R)-HNK, on neuronally derived glutamate release was examined in rodents. We used FAST methodology to measure depolarization-evoked extracellular glutamate levels in vivo in freely moving or anesthetized animals, synaptosomes to detect synaptic recycling ex vivo and primary cortical neurons to perform functional imaging and to examine intracellular signaling in vitro. In all these versatile approaches, ketamine and (2R,6R)-HNK reduced glutamate release in a manner which could be blocked by AMPA receptor antagonism. Antagonism of adenosine A1 receptors, which are almost exclusively expressed at nerve terminals, also counteracted ketamine’s effect on glutamate release and presynaptic activity. Signal transduction studies in primary neuronal cultures demonstrated that ketamine reduced P-T286-CamKII and P-S9-Synapsin, which correlated with decreased synaptic vesicle recycling. Moreover, systemic administration of A1R antagonist counteracted the antidepressant-like actions of ketamine and (2R,6R)-HNK in the forced swim test. To conclude, by studying neuronally released glutamate, we identified a novel retrograde adenosinergic feedback mechanism that mediate inhibitory actions of ketamine on glutamate release that may contribute to its rapid antidepressant action.

Monaural inhibition in cat auditory cortex

1995 ◽  
Vol 73 (5) ◽  
pp. 1876-1891 ◽  
Author(s):  
M. B. Calford ◽  
M. N. Semple
Keyword(s):  
Auditory Cortex ◽  
Lateral Inhibition ◽  
Cortical Neurons ◽  
Frequency Tuning ◽  
Inhibitory Response ◽  
Forward Masking ◽  
Excitatory Response ◽  
Rate Level ◽  
Wide Range ◽  
Response Area

1. Several studies of auditory cortex have examined the competitive inhibition that can occur when appropriate sounds are presented to each ear. However, most cortical neurons also show both excitation and inhibition in response to presentation of stimuli at one ear alone. The extent of such inhibition has not been described. Forward masking, in which a variable masking stimulus was followed by a fixed probe stimulus (within the excitatory response area), was used to examine the extent of monaural inhibition for neurons in primary auditory cortex of anesthetized cats (barbiturate or barbiturate-ketamine). Both the masking and probe stimuli were 50-ms tone pips presented to the contralateral ear. Most cortical neurons showed significant forward masking at delays beyond which masking effects in the auditory nerve are relatively small compared with those seen in cortical neurons. Analysis was primarily concerned with such components. Standard rate-level functions were also obtained and were examined for nonmonotonicity, an indication of level-dependent monaural inhibition. 2. Consistent with previous reports, a wide range of frequency tuning properties (excitatory response area shapes) was found in cortical neurons. This was matched by a wide range of forward-masking-derived inhibitory response areas. At the most basic level of analysis, these were classified according to the presence of lateral inhibition, i.e., where a probe tone at a neuron's characteristic frequency was masked by tones outside the limits of the excitatory response area. Lateral inhibition was a property of 38% of the sampled neurons. Such neurons represented 77% of those with nonmonotonic rate-level functions, indicating a strong correlation between the two indexes of monaural inhibition; however, the shapes of forward masking inhibitory response areas did not usually correspond with those required to account for the "tuning" of a neuron. In addition, it was found that level-dependent inhibition was not added to by forward masking inhibition. 3. Analysis of the discharges to individual stimulus pair presentations, under conditions of partial masking, revealed that discharges to the probe occurred independently of discharges to the preceding masker. This indicates that even when the masker is within a neuron's excitatory response area, forward masking is not a postdischarge habituation phenomenon. However, for most neurons the degree of masking summed over multiple stimulus presentations appears determined by the same stimulus parameters that determine the probability of response to the masker.(ABSTRACT TRUNCATED AT 400 WORDS)

Gustatory neural coding in the monkey cortex: stimulus quality

1991 ◽  
Vol 66 (4) ◽  
pp. 1156-1165 ◽  
Author(s):  
V. L. Smith-Swintosky ◽  
C. R. Plata-Salaman ◽  
T. R. Scott
Keyword(s):  
Cortical Neurons ◽  
Neural Coding ◽  
Monosodium Glutamate ◽  
Stimulus Array ◽  
Cortical Region ◽  
Stimulus Similarity ◽  
Somatosensory Stimulation ◽  
Wide Range ◽  
Response Profiles ◽  
Stimulation Of

1. Extracellular action potentials were recorded from 50 single neurons in the insular-opercular cortex of two alert cynomolgus monkeys during gustatory stimulation of the tongue and palate. 2. Sixteen stimuli, including salts, sugars, acids, alkaloids, monosodium glutamate, and aspartame, were chosen to represent a wide range of taste qualities. Concentrations were selected to elicit a moderate gustatory response, as determined by reference to previous electrophysiological data or to the human psychophysical literature. 3. The cortical region over which taste-evoked activity could be recorded included the frontal operculum and anterior insula, an area of approximately 75 mm3. Taste-responsive cells constituted 50 (2.7%) of the 1,863 neurons tested. Nongustatory cells responded to mouth movement (20.7%), somatosensory stimulation of the tongue (9.6%), stimulus approach or anticipation (1.7%), and tongue extension (0.6%). The sensitivities of 64.6% of these cortical neurons could not be identified by our stimulation techniques. 4. Taste cells had low spontaneous activity levels (3.7 +/- 3.0 spikes/s, mean +/- SD) and showed little inhibition. They were moderately broadly tuned, with a mean entropy coefficient of 0.76 +/- 0.17. Excitatory responses were typically not robust. 5. Hierarchical cluster analysis was used to determine whether neurons could be divided into discrete types, as defined by their response profiles to the entire stimulus array. There was an apparent division of response profiles into four general categories, with primary sensitivities to sodium (n = 18), glucose (n = 15), quinine (n = 12), and acid (n = 5). However, these categories were not statistically independent. Therefore the notion of functionally distinct neuron types was not supported by an analysis of the distribution of response profiles. It was the case, however, that neurons in the sodium category could be distinguished from other neurons by their relative specificity. 6. The similarity among the taste qualities represented by this stimulus array was assessed by calculating correlations between the activity profiles they elicited from these 50 neurons. The results generally confirmed expectations derived from human psychophysical studies. In a multidimensional representation of stimulus similarity, there were groups that contained acids, sodium salts, and chemicals that humans label bitter and sweet. 7. The small proportion of insular-opercular neurons that are taste sensitive and the low discharge rates that taste stimuli are able to evoke from them suggest a wider role for this cortical area than just gustatory coding.(ABSTRACT TRUNCATED AT 400 WORDS)

scholarly journals Generalized Integrate-and-Fire Models of Neuronal Activity Approximate Spike Trains of a Detailed Model to a High Degree of Accuracy

2004 ◽  
Vol 92 (2) ◽  
pp. 959-976 ◽  
Author(s):  
Renaud Jolivet ◽  
Timothy J. Lewis ◽  
Wulfram Gerstner
Keyword(s):  
Cortical Neurons ◽  
Direct Reduction ◽  
Spike Trains ◽  
Model Parameters ◽  
Detailed Model ◽  
Fire Model ◽  
Integrate And Fire ◽  
Fire Models ◽  
Wide Range ◽  
Simple Models

We demonstrate that single-variable integrate-and-fire models can quantitatively capture the dynamics of a physiologically detailed model for fast-spiking cortical neurons. Through a systematic set of approximations, we reduce the conductance-based model to 2 variants of integrate-and-fire models. In the first variant (nonlinear integrate-and-fire model), parameters depend on the instantaneous membrane potential, whereas in the second variant, they depend on the time elapsed since the last spike [Spike Response Model (SRM)]. The direct reduction links features of the simple models to biophysical features of the full conductance-based model. To quantitatively test the predictive power of the SRM and of the nonlinear integrate-and-fire model, we compare spike trains in the simple models to those in the full conductance-based model when the models are subjected to identical randomly fluctuating input. For random current input, the simple models reproduce 70–80 percent of the spikes in the full model (with temporal precision of ±2 ms) over a wide range of firing frequencies. For random conductance injection, up to 73 percent of spikes are coincident. We also present a technique for numerically optimizing parameters in the SRM and the nonlinear integrate-and-fire model based on spike trains in the full conductance-based model. This technique can be used to tune simple models to reproduce spike trains of real neurons.

scholarly journals Functional connectivity of fMRI using differential covariance predicts structural connectivity and behavioral reaction times

2021 ◽  
Author(s):  
Yusi Chen ◽  
Qasim Bukhari ◽  
Tiger Wutu Lin ◽  
Terrence J Sejnowski
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Functional Connectivity ◽  
Resting State ◽  
Structural Connectivity ◽  
Reaction Times ◽  
Resonance Imaging ◽  
Brain Areas ◽  
Human Connectome Project ◽  
Wide Range

Recordings from resting state functional magnetic resonance imaging (rs-fMRI) reflect the influence of pathways between brain areas. A wide range of methods have been proposed to measure this functional connectivity (FC), but the lack of ''ground truth'' has made it difficult to systematically validate them. Most measures of FC produce connectivity estimates that are symmetrical between brain areas. Differential covariance (dCov) is an algorithm for analyzing FC with directed graph edges. Applied to synthetic datasets, dCov-FC was more effective than covariance and partial correlation in reducing false positive connections and more accurately matching the underlying structural connectivity. When we applied dCov-FC to resting state fMRI recordings from the human connectome project (HCP) and anesthetized mice, dCov-FC accurately identified strong cortical connections from diffusion Magnetic Resonance Imaging (dMRI) in individual humans and viral tract tracing in mice. In addition, those HCP subjects whose rs-fMRI were more integrated, as assessed by a graph-theoretic measure, tended to have shorter reaction times in several behavioral tests. Thus, dCov-FC was able to identify anatomically verified connectivity that yielded measures of brain integration causally related to behavior.

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