Analysis of Cultured Neuronal Networks Using Intraburst Firing Characteristics

It is an open question whether neuronal networks, cultured on multielectrode arrays, retain any capability to usefully process information (learning and memory). A necessary prerequisite for learning is that stimulation can induce lasting changes in the network. To observe these changes, one needs a method to describe the network in sufficient detail, while stable in normal circumstances. We analyzed the spontaneous bursting activity that is encountered in dissociated cultures of rat neocortical cells. Burst profiles (BPs) were made by estimating the instantaneous array-wide firing frequency. The shape of the BPs was found to be stable on a time scale of hours. Spatiotemporal detail is provided by analyzing the instantaneous firing frequency per electrode. The resulting phase profiles (PPs) were estimated by aligning BPs to their peak spiking rate over a period of 15 min. The PPs reveal a stable spatiotemporal pattern of activity during bursts over a period of several hours, making them useful for plasticity and learning studies. We also show that PPs can be used to estimate conditional firing probabilities. Doing so, yields an approach in which network bursting behavior and functional connectivity can be studied

Inhomogeneous cortical synchronization and partial epileptic seizures

Objective: Interictal synchronization clusters have recently been described in several publications using diverse techniques, including neurophysiological recordings and fMRI, in patients suffering from epilepsy. However, little is known about the role of these hypersynchronous areas during seizures. In this work, we report an analysis of synchronization clusters jointly with several network measures during seizure activity; we then discuss our findings in the context of prior literature.Methods: Subdural activity was recorded by electrocorticography (with 60 electrodesplaced at temporal and parietal lobe locations) in a patient with temporal lobe epilepsywith partial seizures with and without secondary generalization (SG). Both interictal andictal activities (during four seizures) were investigated and characterized using local synchronization and complex network methodology. The modularity, density of links, average clustering coefficient, and average path lengthswere calculated to obtain information about the dynamics of the global network. Functional connectivity changes during the seizures were compared with the time evolution of highly synchronized areas.Results: Our findings reveal temporal changes in local synchronization areas during seizuresand a tight relationship between the cortical locations of these areas and the patterns oftheir evolution over time. Seizure evolution and SG appear to be driven by two differentunderlying mechanisms.Fil: Vega Zelaya, Lorena. Hospital Universitario la Princesa; EspañaFil: Pastor, Jesús Eduardo. Hospital Universitario la Princesa; EspañaFil: García de Sola, Rafael. Hospital Universitario la Princesa; EspañaFil: Ortega, Guillermo José. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Quilmes; Argentin

The interplay between long- and short-range temporal correlations shapes cortex dynamics across vigilance states

Increasing evidence suggests that cortical dynamics during wake exhibits long-range temporal correlations suitable to integrate inputs over extended periods of time to increase the signal-to-noise ratio in decision-making and working memory tasks. Accordingly, sleep has been suggested as a state characterized by a breakdown of long-range correlations; detailed measurements of neuronal timescales that support this view, however, have so far been lacking. Here we show that the long timescales measured at the individual neuron level in freely-behaving rats during the awake state are abrogated during non-REM (NREM) sleep. We provide evidence for the existence of two distinct states in terms of timescale dynamics in cortex: one which is characterized by long timescales which dominate during wake and REM sleep, and a second one characterized by the absence of long-range temporal correlations which characterizes NREM sleep. We observe that both timescale regimes can co-exist and, in combination, lead to an apparent gradual decline of long timescales during extended wake which is restored after sleep. Our results provide a missing link between the observed long timescales in individual neuron fluctuations during wake and the reported absence of long-term correlations during deep sleep in EEG and fMRI studies. They furthermore suggest a network-level function of sleep, to reorganize cortical networks towards states governed by slow cortex dynamics to ensure optimal function for the time awake

Dwelling Quietly in the Rich Club: Brain Network Determinants of Slow Cortical Fluctuations

For more than a century, cerebral cartography has been driven by investigations of structural and morphological properties of the brain across spatial scales and the temporal/functional phenomena that emerge from these underlying features. The next era of brain mapping will be driven by studies that consider both of these components of brain organization simultaneously -- elucidating their interactions and dependencies. Using this guiding principle, we explored the origin of slowly fluctuating patterns of synchronization within the topological core of brain regions known as the rich club, implicated in the regulation of mood and introspection. We find that a constellation of densely interconnected regions that constitute the rich club (including the anterior insula, amygdala, and precuneus) play a central role in promoting a stable, dynamical core of spontaneous activity in the primate cortex. The slow time scales are well matched to the regulation of internal visceral states, corresponding to the somatic correlates of mood and anxiety. In contrast, the topology of the surrounding "feeder" cortical regions show unstable, rapidly fluctuating dynamics likely crucial for fast perceptual processes. We discuss these findings in relation to psychiatric disorders and the future of connectomics.Comment: 35 pages, 6 figure

A Systematic Review of The Potential Use of Neurofeedback in Patients with Schizophrenia.

Schizophrenia (SCZ) is a neurodevelopmental disorder characterized by positive symptoms (hallucinations and delusions), negative symptoms (anhedonia, social withdrawal) and marked cognitive deficits (memory, executive function, and attention). Current mainstays of treatment, including medications and psychotherapy, do not adequately address cognitive symptoms, which are essential for everyday functioning. However, recent advances in computational neurobiology have rekindled interest in neurofeedback (NF), a form of self-regulation or neuromodulation, in potentially alleviating cognitive symptoms in patients with SCZ. Therefore, we conducted a systematic review of the literature for NF studies in SCZ to identify lessons learned and to identify steps to move the field forward. Our findings reveal that NF studies to date consist mostly of case studies and small sample, single-group studies. Despite few randomized clinical trials, the results suggest that NF is feasible and that it leads to measurable changes in brain function. These findings indicate early proof-of-concept data that needs to be followed up by larger, randomized clinical trials, testing the efficacy of NF compared to well thought out placebos. We hope that such an undertaking by the field will lead to innovative solutions that address refractory symptoms and improve everyday functioning in patients with SCZ

State-Dependent and -Independent Effects of Dialyzing Excitatory Neuromodulator Receptor Antagonists into the Ventral Respiratory Column

Unilateral dialysis of the broad-spectrum muscarinic receptor antagonist atropine (50 mM) into the ventral respiratory column [(VRC) including the pre-Bötzinger complex region] of awake goats increased pulmonary ventilation (V̇i) and breathing frequency (f), conceivably due to local compensatory increases in serotonin (5-HT) and substance P (SP) measured in effluent mock cerebral spinal fluid (mCSF). In contrast, unilateral dialysis of a triple cocktail of antagonists to muscarinic (atropine; 5 mM), neurokinin-1, and 5-HT receptors does not alter V̇i or f, but increases local SP. Herein, we tested hypotheses that 1) local compensatory 5-HT and SP responses to 50 mM atropine dialyzed into the VRC of goats will not differ between anesthetized and awake states; and 2) bilateral dialysis of the triple cocktail of antagonists into the VRC of awake goats will not alter V̇i or f, but will increase local excitatory neuromodulators. Through microtubules implanted into the VRC of goats, probes were inserted to dialyze mCSF alone (time control), 50 mM atropine, or the triple cocktail of antagonists. We found 1) equivalent increases in local 5-HT and SP with 50 mM atropine dialysis during wakefulness compared with isoflurane anesthesia, but V̇i and f only increased while awake; and 2) dialyses of the triple cocktail of antagonists increased V̇i, f, 5-HT, and SP