Electronics that are capable of intimate, non-invasive integration with the soft, curvilinear surfaces of biological tissues offer important opportunities for diagnosing and treating disease and for improving brain-machine interfaces. This paper describes a material strategy for a type of biointerfaced system that relies on ultrathin electronics supported by bioresorbable substrates of silk fibroin. Mounting such devices on tissue and then allowing the silk to dissolve and resorb initiates a spontaneous, conformal wrapping process driven by capillary forces at the biotic/abiotic interface. Specialized mesh designs and ultrathin forms for the electronics ensure minimal stresses on the tissue and highly conformal coverage, even for complex curvilinear surfaces, as confirmed by experimental and theoretical studies. In vivo, neural mapping experiments on feline animal

Arrays of electrodes for recording and stimulating the brain are used throughout clinical medicine and basic neuroscience research, yet are unable to sample large areas of the brain while maintaining high spatial resolution because of the need to individually wire each passive sensor at the electrode-tissue interface. To overcome this constraint, we have developed new devices integrating ultrathin and flexible silicon nanomembrane transistors into the electrode array, enabling new dense arrays of thousands of amplified and multiplexed sensors connected using many fewer wires. We used this system to record novel spatial properties of brain activity in vivo, including sleep spindles, single-trial visual evoked responses, and electrographic seizures. Our electrode array allowed us to discover that seizures may manifest as recurrent spiral waves which propagate in the neocortex. The developments reported here herald a new generation of diagnostic and therapeutic brain-machine interface (BMI) devices. KeywordsMultielectrode array; electrode array; flexible electronics; multiplexed electrode; cortical surface electrode; foldable electrode; ECoG; μECoG; brain machine interface; high temporal resolution; high spatial resolution; spindle; visual neuroscience; spiral wave; epilepsy; seizure; epileptiform spike; interhemispheric fissure; silicon nanoribbonThe utility of high-resolution neural recordings from the cortical surface for basic research and clinical medicine has been shown for a wide range of applications. Spatial spectral analysis of electrocorticograms (ECoG) from the superior temporal gyrus and motor cortex demonstrate that electrode spacing should be 1.25 mm or closer in humans to sufficiently capture the rich spatial information available 1 . Motor control signals 2 and spoken words 3 can be decoded with substantially improved performance utilizing electrodes spaced 1 mm apart or less. In occipital cortex, arrays with 500 μm spacing have demonstrated micro-field evoked potentials that can distinguish ocular dominance columns 4 . The spatial scale for some pathologic signals is also submillimeter, based on observations of microseizures, microdischarges and high frequency oscillations in epileptic brain 5,6 .Yet the subdural electrodes in use clinically, for example, in the diagnosis and treatment of epilepsy, are much larger (~3 mm diameter) and have large interspacing (~10mm) because of the clinical need to record from large areas of the brain surface (80 mm × 80 mm) in order to accurately localize seizure generating brain regions. Large area electrode arrays with high spatial resolution are also needed in BMI applications to account for variability in the location of brain functions, which can vary by ~5mm across subjects [7][8][9][10] . High-resolution interface over a large area has previously been impossible due to the infeasibility of connecting thousands of wires in the small intracranial space. Author Manuscript Author ManuscriptAuthor Manuscript Author ManuscriptMuch of the existing researc...

The highly interconnected networks of the mammalian forebrain can generate a wide variety of synchronized activities, including those underlying epileptic seizures, which often appear as a transformation of otherwise normal brain rhythms. The cerebral cortex and hippocampus are particularly prone to the generation of the large, synchronized bursts of activity underlying many forms of seizures owing to strong recurrent excitatory connections, the presence of intrinsically burst-generating neurons, ephaptic interactions among closely spaced neurons, and synaptic plasticity. The simplest form of epileptiform activity in these structures is the interictal spike, a synchronized burst of action potentials generated by recurrent excitation, followed by a period of hyperpolarization, in a localized pool of pyramidal neurons. Seizures can also be generated in response to a loss of balance between excitatory and inhibitory influences and can take the form of either tonic depolarizations or repetitive, rhythmic burst discharges, either as clonic or spike-wave activity, again mediated both by intrinsic membrane properties and synaptic interactions. The interaction of the cerebral cortex and the thalamus, in conjunction with intrathalamic communication, can also generate spike waves similar to those occurring during human absence seizure discharges. Although epileptic syndromes and their causes are diverse, the cellular mechanisms of seizure generation appear to fall into only two categories: rhythmic or tonic "runaway" excitation or the synchronized and rhythmic interplay between excitatory and inhibitory neurons and membrane conductances.

As most afferent axons to the thalamus originate in the cerebral cortex, we assumed that the slow (< 1 Hz) cortical oscillation described in the two companion articles is reflected in reticular (RE) thalamic and thalamocortical cells. We hypothesized that the cortically generated slow rhythm would appear in the thalamus in conjunction with delta and spindle oscillations arising from intrinsic and network properties of thalamic neurons. Intracellular recordings have been obtained in anesthetized cats from RE (n = 51) and cortically projecting (n = 240) thalamic neurons. RE cells were physiologically identified by cortically evoked high-frequency spike bursts and depolarizing spindle oscillations. Thalamocortical cells were recognized by backfiring from appropriate neocortical areas, spindle-related cyclic IPSPs, and hyperpolarization-activated delta oscillation consisting of rhythmic low-threshold spikes (LTSs) alternating with afterhyperpolarizing potentials (AHPs). The slow rhythm (0.3-0.5 Hz) was recorded in 65% of RE neurons. In approximately 90% of oscillating cells, the rhythm consisted of prolonged depolarizations giving rise to trains of single action potentials. DC hyperpolarization increased the synaptic noise and, in a few cells, suppressed the long-lasting depolarizing phase of the slow rhythm, without blocking the fast EPSPs. In approximately 10% of oscillating neurons, the hyperpolarizing phase of the oscillation was much more pronounced, thus suggesting that the slow rhythm was produced by inhibitory sculpturing of the background firing. The slow oscillation was associated with faster rhythms (4-8 Hz) in the same RE neuron. The slow rhythm of RE neurons was closely related to EEG wave complexes recurring with the same frequency, and its strong dependency upon a synchronized state of cortical EEG was observed during shifts in EEG patterns at different levels of anesthesia. In 44% of thalamocortical cells the slow rhythm of depolarizing sequences was apparent and it could coexist with delta or spindle oscillations in the same neuron. The occurrence of the slowly recurring depolarizing envelopes was delayed by the hyperpolarizing spindle sequences or by the LTS-AHP sequences of delta oscillation. The hyperpolarization-activated delta potentials that tended to dampen after a few cycles were grouped in sequences recurring with the slow rhythm. We finally propose a unified scenario of the genesis of the three major sleep rhythms: slow, delta, and spindle oscillations.