Measuring the spatiotemporal complexity of cortical responses to direct perturbations provides a reliable index of the brain's capacity for consciousness in humans under both physiological and pathological conditions. Upon loss of consciousness, the complex pattern of causal interactions observed during wakefulness collapses into a stereotypical slow wave, suggesting that cortical bistability may play a role. Bistability is mainly expressed in the form of slow oscillations, a default pattern of activity that emerges from cortical networks in conditions of functional or anatomical disconnection. Here, we employ an in vitro model to understand the relationship between bistability and complexity in cortical circuits. We adapted the perturbational complexity index applied in humans to electrically stimulated cortical slices under different neuromodulatory conditions. At this microscale level, we demonstrate that perturbational complexity can be effectively modulated by pharmacological reduction of bistability and, albeit to a lesser extent, by enhancement of excitability, providing mechanistic insights into the macroscale measurements performed in humans.

Establishing a reliable communication interface between the brain and electronic devices is of paramount importance for exploiting the full potential of neural prostheses [1][2][3][4] . Current microelectrode technologies for recording electrical activity, however, evidence important shortcomings, e.g. challenging high density integration. Solution-gated field-effect transistors (SGFETs), on the other hand, could overcome these shortcomings if a suitable transistor material were available. Graphene is particularly attractive due to its biocompatibility, chemical stability, flexibility, low intrinsic electronic noise and high charge carrier mobilities [5][6][7][8][9] . Here, we report on the use of an array of flexible graphene SGFETs for recording spontaneous slow waves, as well as visually evoked and also pre-epileptic activity in vivo in rats. The flexible array of graphene SGFETs allows mapping brain electrical activity with excellent signal-to-noise ratio (SNR), suggesting that this technology could lay the foundation for a future generation of in vivo recording implants.Recording brain activity with high fidelity and decoding the enclosed information could enable the development of a new generation of neuroprosthetic devices for control of artificial limbs and motor rehabilitation, as well as brain-machine interfaces for communication and speech prostheses 1,10,11 . A major challenge is still the need of high-density, small recording sites that provide high spatial resolution with adequate signal-to-noise ratio (SNR) recordings to obtain high fidelity data for decoding as much information as possible. The most extended technology for in vivo recordings today uses microelectrode arrays (MEAs), mainly based on metals such as Pt and PtIr 12 . However, using MEAs for high-density recordings presents important drawbacks. Since the electrode impedance and noise are inversely proportional to the electrode size, a trade-off

The understanding of brain processing requires monitoring and exogenous modulation of neuronal ensembles. To this end, it is critical to implement equipment that ideally provides highly accurate, low latency recording and stimulation capabilities, that is functional for different experimental preparations and that is highly compact and mobile. To address these requirements, we designed a small ultra-flexible multielectrode array and combined it with an ultra-compact electronic system. The device consists of a polyimide microelectrode array (8 µm thick and with electrodes measuring as low as 10 µm in diameter) connected to a miniaturized electronic board capable of amplifying, filtering and digitalizing neural signals and, in addition, of stimulating brain tissue. To evaluate the system, we recorded slow oscillations generated in the cerebral cortex network both from in vitro slices and from in vivo anesthetized animals, and we modulated the oscillatory pattern by means of electrical and visual stimulation. Finally, we established a preliminary closed-loop algorithm in vitro that exploits the low latency of the electronics (<0.5 ms), thus allowing monitoring and modulating emergent cortical activity in real time to a desired target oscillatory frequency.

39Non-invasive brain stimulation techniques, such as transcranial direct current 40 stimulation (tDCS), play a growing role in the treatment of neurological disorders. 41 However, the mechanisms by which electric fields modulate cortical network activity 42 are only partially understood. To explore the spatiotemporal modulation of cortical 43 activity by electric fields (DC fields), we exposed neocortical slices to constant fields of 44 varying intensity and direction and we measured their effect on the low (<1 Hz) and

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