Synchronous chaos and broad band gamma rhythm in a minimal multi-layer model of primary visual cortex

Visually induced neuronal activity in V1 displays a marked gamma-band component which is modulated by stimulus properties. It has been argued that synchronized oscillations contribute to these gamma-band activity [... however,] even when oscillations are observed, they undergo temporal decorrelation over very few cycles. This is not easily accounted for in previous network modeling of gamma oscillations. We argue here that interactions between cortical layers can be responsible for this fast decorrelation. We study a model of a V1 hypercolumn, embedding a simplified description of the multi-layered structure of the cortex. When the stimulus contrast is low, the induced activity is only weakly synchronous and the network resonates transiently without developing collective oscillations. When the contrast is high, on the other hand, the induced activity undergoes synchronous oscillations with an irregular spatiotemporal structure expressing a synchronous chaotic state. As a consequence the population activity undergoes fast temporal decorrelation, with concomitant rapid damping of the oscillations in LFPs autocorrelograms and peak broadening in LFPs power spectra. [...] Finally, we argue that the mechanism underlying the emergence of synchronous chaos in our model is in fact very general. It stems from the fact that gamma oscillations induced by local delayed inhibition tend to develop chaos when coupled by sufficiently strong excitation.Comment: 49 pages, 11 figures, 7 table

25th Annual Computational Neuroscience Meeting: CNS-2016

Abstracts of the 25th Annual Computational Neuroscience Meeting: CNS-2016 Seogwipo City, Jeju-do, South Korea. 2–7 July 201

Stimulus and task-dependent gamma activity in monkey V1

The single unit doctrine proposes that each one of our percepts and sensations is represented by the activity of specialized high-level cells in the brain. A common criticism applied to this proposal is the one referred to as the "combinatorial problem". We are constantly confronted with unlimited combinations of elements and features, and yet we face no problem in recognizing patterns and objects present in visual scenes. Are there enough neurons in the brain to singly code for each one of our percepts? Or is it the case that perceptions are represented by the distributed activity of different neuronal ensembles? We lack a general theory capable of explaining how distributed information can be efficiently integrated into single percepts. The working hypothesis here is that distributed neuronal ensembles signal relations present in the stimulus by selectively synchronizing their spiking responses. Synchronization is generally associated with oscillatory activity in the brain. Gamma oscillations in particular have been linked to various integrative processes in the visual system. Studies in anesthetized animals have shown a conspicuous increase in power for the gamma frequency band (30 to 60 Hz) in response to visual stimuli. Recently, these observations have been extended to behavioral studies which addressed the role of gamma activity in cognitive processes demanding selective attention. The initial motivation for carrying out this work was to test if the binding-by-synchronization (BBS) hypothesis serves as a neuronal mechanism for perceptual grouping in the visual system. To this aim we used single and superimposed grating stimuli. Superimposed gratings (plaids) are bi-stable stimuli capable of eliciting different percepts depending on their physical characteristics. In this way, plaids can be perceived either as a single moving surface (pattern plaids), or as two segregated surfaces drifting in different directions (component plaids). While testing the BBS hypothesis, we performed various experiments which addressed the role of both stimulus and cortical architecture on the properties of gamma oscillations in the primary visual cortex (V1) of monkeys. Additionally, we investigated whether gamma activity could also be modulated by allocating attention in time. Finally, we report on gamma-phase shifts in area V1, and how they depend on the level of neuronal activation. ...Einleitung: Die visuelle Hirnforschung hat eine große Informationsmenge über die analytischen Fähigkeiten des Nervensystems zusammengetragen. Die Einführung von Einzelzellableitungen ermöglichte eine detaillierte Beschreibung der Eigenschaften rezeptiver Felder im Sehsystem. Konzentrische rezeptive Felder in der Netzhaut antworten optimal auf einen Luminanzkontrast in ihren On- und Off-Regionen. Antworteigenschaften entwickeln sich schrittweise entlang der Sehbahn, indem zunehmend komplexere Eigenschaften des visuellen Reizes extrahiert werden. Die Pionierarbeiten von David Hubel und Torsten Wiesel beschrieben zunächst Orientierung- und Richtungsselektivität von Neuronen in frühen visuellen Kortexarealen. Später fand man Einzelzellen im medialen Temporallappen, die auf komplexe Objekte wie Hände und Gesichter antworten. Die Hirnforschung ist daher lange davon ausgegangen, dass die Repräsentation komplexer Objekte eine natürliche Entfaltung von Konvergenz entlang der Sehbahn darstellt. Zellen, welche auf elementare Merkmale des Stimulus antworteten, bildeten so durch ihr Muster anatomischer Verbindungen schrittweise die spezialisierten Neurone in höheren visuellen Arealen. Diese Sichtweise zeigt allerdings Limitationen auf. Eine beständige Kritik, die an der "Einzelzelldoktrin" geübt wird, ist das sogenannte kombinatorische Problem. Obwohl wir ständig mit einer unbegrenzten Fülle an Kombinationen verschiedener Elemente und Merkmale konfrontiert sind, laufen wir selten Gefahr, Muster und Objekte in einer visuellen Szene nicht zu erkennen. Ist es überhaupt möglich, dass jedes unserer möglichen Perzepte durch die Antwort eines einzelnen hoch spezialisierten Neurons im Hirn kodiert wird? Falls nicht, welcher Mechanismus könnte einen relationalen Code darstellen, der es ermöglicht, die Aktivität verschiedener neuronaler Ensembles zu integrieren? Die Anforderungen an einen solchen Mechanismus treten besonders hervor, wenn man sich die verteilte Struktur der visuellen Verarbeitung verdeutlicht. Die Merkmalsextraktion entlang der Sehbahn führt unvermeidbar zu einer räumlich verstreuten Repräsentation eines visuellen Reizes. Zusätzlich kommen parallele Bahnen neuronaler Verarbeitung im Hirn häufig vor. Es fehlt eine universale Theorie darüber, wie die verteilte Information effizient in eine einzige Wahrnehmung integriert wird. Die Arbeitshypothese hier lautet, dass das Hirn die Zeitdomäne benutzt, um visuelle Informationen zu integrieren und zu verarbeiten. Konkret würden neuronale Ensemble die aus dem Stimulus hervorgehenden Beziehungen durch eine selektive Synchronisation ihrer Aktionspotenziale signalisieren. Synchronisation ist normalerweise mit oszillatorischer Hirnaktivität assoziiert. Besonders die Oszillationen im Gamma Frequenzband sind mit verschiedensten integrativen Prozessen im Sehsystem in Verbindung gebracht worden. Arbeiten an anästhesierten Tieren haben einen auffälligen Anstieg von Energie im Gamma Frequenzband (30-60 Hz) unter visueller Stimulation gezeigt. Kürzlich sind diese Beobachtungen auf Verhaltensstudien ausgeweitet worden, welche die Rolle von Gamma Aktivität bei der für kognitive Prozesse erforderlichen gerichteten Aufmerksamkeit untersuchen. Die ursprüngliche Motivation dieser Arbeit war es, die von Wolf Singer und Mitarbeitern formulierte "binding-bysynchronization (BBS)" Hypothese zu testen. Dies wurde durch die Ableitung neuronaler Antworten in V1 bei Darbietung eines Paars übereinander gelegter Balkengitter ("Plaid" Stimulus) angegangen. Physikalische Manipulationen der Luminanz in Unterregionen des Plaid-Stimulus können die Wahrnehmung zugunsten der Bewegung der Einzelkomponenten (zwei Objekte, die sich übereinander schieben) oder der Bewegung des Gesamtmusters (ein einziges sich in eine gemeinsame Richtung bewegendes Objekt) beeinflussen. Die gleichzeitige Ableitung von zwei Neuronen, die jeweils nur selektiv auf eines der beiden Balkengitter antworteten, ermöglichte es uns, zwei Vorhersagen der BBS Hypothese zu testen. Falls beide V1 Neurone auf dasselbe Balkengitter antworteten, sollten sie ihre Aktivität unabhängig davon, ob das Plaid in Einzelkomponenten oder als Gesamtmuster wahrgenommen würde, synchronisieren. Der Grund dafür wäre, dass beide Neurone auf dasselbe Objekt reagierten. Im zweiten Fall antworten beide Ableitstellen auf jeweils eine der beiden Balkengitterkomponenten. Hier sagt die BBS Hypothese voraus, dass beide ihre Aktivität nur bei Gesamtmusterbewegung synchronisieren würden, da sie nur in dieser Bedingung auf dasselbe Objekt antworten würden. ..

Exact neural mass model for synaptic-based working memory

A synaptic theory of Working Memory (WM) has been developed in the last decade as a possible alternative to the persistent spiking paradigm. In this context, we have developed a neural mass model able to reproduce exactly the dynamics of heterogeneous spiking neural networks encompassing realistic cellular mechanisms for short-term synaptic plasticity. This population model reproduces the macroscopic dynamics of the network in terms of the firing rate and the mean membrane potential. The latter quantity allows us to get insight on Local Field Potential and electroencephalographic signals measured during WM tasks to characterize the brain activity. More specifically synaptic facilitation and depression integrate each other to efficiently mimic WM operations via either synaptic reactivation or persistent activity. Memory access and loading are associated to stimulus-locked transient oscillations followed by a steady-state activity in the $\beta-\gamma$ band, thus resembling what observed in the cortex during vibrotactile stimuli in humans and object recognition in monkeys. Memory juggling and competition emerge already by loading only two items. However more items can be stored in WM by considering neural architectures composed of multiple excitatory populations and a common inhibitory pool. Memory capacity depends strongly on the presentation rate of the items and it maximizes for an optimal frequency range. In particular we provide an analytic expression for the maximal memory capacity. Furthermore, the mean membrane potential turns out to be a suitable proxy to measure the memory load, analogously to event driven potentials in experiments on humans. Finally we show that the $\gamma$ power increases with the number of loaded items, as reported in many experiments, while $\theta$ and $\beta$ power reveal non monotonic behaviours.Comment: 47 pages, 14 figure

A model of delta frequency neuronal network activity and theta-gamma interactions in rat sensorimotor cortex in vitro

In recent decades, advances in electrophysiological techniques have enabled understanding of neuronal network activity, with in vitro brain slices providing insights into the mechanisms underlying oscillations at various frequency ranges. Understanding the electrical and neuro-pharmacological properties of brain networks using selective receptor modulators in native tissue allows to compare such properties with those in disease models (e.g. epilepsy and Parkinson’s). In vivo and in vitro studies have implicated M1 in execution of voluntary movements and, from both local network in vitro and whole brain in vivo perspectives. M1 has been shown to generate oscillatory activity at various frequencies, including beta frequency and nested theta and gamma oscillations similar to those of rat hippocampus. In vivo studies also confirmed slow wave oscillations in somatosensory cortex including delta and theta band activity. However, despite these findings, non-thalamic mechanisms underlying cortical delta oscillations remain almost unexplored. Therefore, we determined to explore these oscillations in vitro in M1 and S1. Using a modified sagittal plane slice preparation with aCSF containing neuroprotectants, we have greatly improved brain slice viability, enabling the generation and study of dual rhythms (theta and gamma oscillations) in deep layers (LV) of the in vitro sensorimotor slice (M1 and S1) in the presence of KA and CCh. We found that theta-gamma activity in M1 is led by S1 and that the amplitude of gamma oscillations was (phase-amplitude) coupled to theta phase in both regions. Oscillations were dependent on GABAAR, AMPAR and NMDAR and were augmented by DAR activation. Experiments using cut/reduced slices showed both M1 and S1 could be intrinsic generators of oscillatory activity. Delta oscillations were induced in M1 and S1 by maintaining a neuromodulatory state mimicking deep sleep, characterised by low dopaminergic and low cholinergic tone, achieved using DAR blockade and low CCh. Delta activity depends on GABAAR, GABABR and AMPAR but not NMDAR, and once induced was not reversible. Unlike theta-gamma activity, delta was led by M1, and activity took >20mins to develop in S1 after establishement of peak power in M1. Unlike M1, S1 alone was unable to support delta activity. Dopamine modulates network activity in M1 and it is known that fast-spiking interneurons are the pacemakers of network rhythmogenesis. Recent studies reported that dopamine (DA) controled Itonic in medium spiny, ventrobasal thalamus and nucleus accumbens neurons by modulation of GABARs or cation channels. In the current study, voltage-clamp whole cell recordings were performed in fast spiking interneurons (FS cells) in Layer V of M1. These recordings revealed tonic and phasic GABAAR inhibition and when DA was bath applied, a slow inward current (IDA) was induced. IDA was mediated by non-specific cationic TRPC channels following D2R-like receptor activation. Overall, my studies show the strong interdependence of theta-gamma rhythmogenesis between M1 and S1, dominanace of M1 at delta frequency and the crucial role of dopamine in controlling FS cell activity. Further exploration of these rhythms in models of pathological conditions such as Parkinson`s disease and Epilepsy may provide insights into network changes underlying these disease conditions