Neural responses are modulated by brain state, which varies with arousal, attention, and behavior. In mice, running and whisking desynchronize the cortex and enhance sensory responses, but the quiescent periods between bouts of exploratory behaviors have not been well-studied. We found that these periods of “quiet wakefulness” were characterized by state fluctuations on a timescale of 1–2 seconds. Small fluctuations in pupil diameter tracked these state transitions in multiple cortical areas. During dilation, the intracellular membrane potential was desynchronized, sensory responses were enhanced, and population activity was less correlated. In contrast, constriction was characterized by increased low-frequency oscillations and higher ensemble correlations. Specific subtypes of cortical interneurons were differentially activated during dilation and constriction, consistent with their participation in the observed state changes. Pupillometry has been used to index attention and mental effort in humans, but the intracellular dynamics and differences in population activity underlying this phenomenon were previously unknown.

The state of the brain and body constantly varies on rapid and slow time scales. These variations contribute to the apparent noisiness of sensory responses at both the neural and behavioral level. Recent investigations of rapid state changes in awake, behaving animals have provided insight into the mechanisms by which optimal sensory encoding and behavioral performance are achieved. Fluctuations in state, as indexed by pupillometry, impact both the “signal” (sensory evoked response) and the “noise” (spontaneous activity) of cortical responses. By taking these fluctuations into account, neural response (co-)variability is significantly reduced, revealing the brain to be more reliable and predictable than previously thought.

Rapid variations in cortical state during wakefulness have a strong influence on neural and behavioural responses and are tightly coupled to changes in pupil size across species. However, the physiological processes linking cortical state and pupil variations are largely unknown. Here we demonstrate that these rapid variations, during both quiet waking and locomotion, are highly correlated with fluctuations in the activity of corticopetal noradrenergic and cholinergic projections. Rapid dilations of the pupil are tightly associated with phasic activity in noradrenergic axons, whereas longer-lasting dilations of the pupil, such as during locomotion, are accompanied by sustained activity in cholinergic axons. Thus, the pupil can be used to sensitively track the activity in multiple neuromodulatory transmitter systems as they control the state of the waking brain.

Despite the importance of the mammalian neocortex for complex cognitive processes, we still lack a comprehensive description of its cellular components. To improve the classification of neuronal cell types and the functional characterization of single neurons, we present Patch-seq, a method that combines whole-cell electrophysiological patch-clamp recordings, single-cell RNA-sequencing and morphological characterization. Following electrophysiological characterization, cell contents are aspirated through the patch-clamp pipette and prepared for RNA-sequencing. Using this approach, we generate electrophysiological and molecular profiles of 58 neocortical cells and show that gene expression patterns can be used to infer the morphological and physiological properties such as axonal arborization and action potential amplitude of individual neurons. Our results shed light on the molecular underpinnings of neuronal diversity and suggest that Patch-seq can facilitate the classification of cell types in the nervous system.

High-resolution optical imaging is critical to understanding brain function. We demonstrate that three-photon microscopy at 1,300-nm excitation enables functional imaging of GCaMP6s-labeled neurons beyond the depth limit of two-photon microscopy. We record spontaneous activity from up to 50 neurons in the hippocampal stratum pyramidale at ~1-mm depth within an intact mouse brain. our method creates opportunities for noninvasive recording of neuronal activity with high spatial and temporal resolution deep within scattering brain tissues.

Summary A fundamental challenge in calcium imaging has been to infer spike rates of neurons from the measured noisy fluorescence traces. We systematically evaluate different spike inference algorithms on a large benchmark dataset (>100.000 spikes) recorded from varying neural tissue (V1 and retina) using different calcium indicators (OGB-1 and GCaMP6). In addition, we introduce a new algorithm based on supervised learning in flexible probabilistic models and find that it performs better than other published techniques. Importantly, it outperforms other algorithms even when applied to entirely new datasets for which no simultaneously recorded data is available. Future data acquired in new experimental conditions can be used to further improve the spike prediction accuracy and generalization performance of the model. Finally, we show that comparing algorithms on artificial data is not informative about performance on real data, suggesting that benchmarking different methods with real-world datasets may greatly facilitate future algorithmic developments in neuroscience.

SUMMARY Beta oscillations (12-30Hz) in local field potentials are prevalent in the motor system, yet their functional role within the context of planning a movement is still debated. In this study, a human participant implanted with a multi-electrode array in the hand area of primary motor cortex (MI) was instructed to plan a movement using either the second or fourth of five sequentially presented instruction cues. The beta amplitude increased from the start of the trial until the informative (second or fourth) cue, and was diminished afterwards. Moreover, the beta amplitude peaked just prior to each instruction cue and the delta frequency (0.5-1.5Hz) entrained to the interval between the cues - but only until the informative cue. This result suggests that the beta amplitude and delta phase in MI reflect the subject’s engagement with the rhythmically-presented cues and work together to enhance sensitivity to predictable and task-relevant visual cues.

A variety of studies have shown that motor cortical areas can be activated by observation of familiar actions. Here, we describe singleneuron responses in monkey primary motor (MI) and dorsal premotor (PMd) cortices during passive observation and execution of a familiar task. We show that the spiking modulation, preferred directions, and encoded information of cells in MI and PMd remain consistent during both observation and movement. Furthermore, we find that the presence of a visual target is necessary to elicit this congruent neural activity during observation. These findings along with results from our analysis of the oscillatory power in the beta frequency of the local field potential are consistent with previous imaging and EEG studies that have suggested that congruence between observation and action is a general feature of the motor system, even outside of canonical "mirror" areas. Such congruent activity has proposed relevance to motor learning, mimicry, and communication and has practical applications for the development of motorcortical neuroprostheses in paralyzed patients.