Martin Vinck

Arousal and Locomotion Make Distinct Contributions to Cortical Activity Patterns and Visual Encoding

Spontaneous and sensory-evoked cortical activity is highly state-dependent, yet relatively little is known about transitions between distinct waking states. Patterns of activity in mouse V1 differ dramatically between quiescence and locomotion, but this difference could be explained by either motor feedback or a change in arousal levels. We recorded single cells and local field potentials from area V1 in mice head-fixed on a running wheel and monitored pupil diameter to assay arousal. Using naturally occurring and induced state transitions, we dissociated arousal and locomotion effects in V1. Arousal suppressed spontaneous firing and strongly altered the temporal patterning of population activity. Moreover, heightened arousal increased the signal-to-noise ratio of visual responses and reduced noise correlations. In contrast, increased firing in anticipation of and during movement was attributable to locomotion effects. Our findings suggest complementary roles of arousal and locomotion in promoting functional flexibility in cortical circuits.

Waking State: Rapid Variations Modulate Neural and Behavioral Responses

The state of the brain and body constantly varies on rapid and slow timescales. These variations contribute to the apparent noisiness of sensory responses at both the neural and the 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.

Stimulus repetition modulates gamma-band synchronization in primate visual cortex

Significance When a visual stimulus repeats multiple times, visual cortical neurons show decreasing firing rate responses, yet neither perception nor stimulus-related behavior is compromised. We show that stimulus repetition leads to increased neuronal gamma-band (∼40–90 Hz) synchronization within and between early and higher visual areas. The enhanced gamma-band synchronization likely maintains effective stimulus signaling in the face of dwindling firing rates. We also show that synchronization to the gamma rhythm increases for spikes in general and for those of putative interneurons, whereas it decreases for spikes of putative excitatory neurons if they are not strongly stimulus-driven. Thus, inhibitory interneurons might create increasingly precise gamma-band synchronization, and thereby prune the stimulus representation by pyramidal cells to be sparser and more efficient. When a sensory stimulus repeats, neuronal firing rate and functional MRI blood oxygen level-dependent responses typically decline, yet perception and behavioral performance either stay constant or improve. An additional aspect of neuronal activity is neuronal synchronization, which can enhance the impact of neurons onto their postsynaptic targets independent of neuronal firing rates. We show that stimulus repetition leads to profound changes of neuronal gamma-band (∼40–90 Hz) synchronization. Electrocorticographic recordings in two awake macaque monkeys demonstrated that repeated presentations of a visual grating stimulus resulted in a steady increase of visually induced gamma-band activity in area V1, gamma-band synchronization between areas V1 and V4, and gamma-band activity in area V4. Microelectrode recordings in area V4 of two additional monkeys under the same stimulation conditions allowed a direct comparison of firing rates and gamma-band synchronization strengths for multiunit activity (MUA), as well as for isolated single units, sorted into putative pyramidal cells and putative interneurons. MUA and putative interneurons showed repetition-related decreases in firing rate, yet increases in gamma-band synchronization. Putative pyramidal cells showed no repetition-related firing rate change, but a decrease in gamma-band synchronization for weakly stimulus-driven units and constant gamma-band synchronization for strongly driven units. We propose that the repetition-related changes in gamma-band synchronization maintain the interareal stimulus signaling and sharpen the stimulus representation by gamma-synchronized pyramidal cell spikes.

Theta-band phase locking of orbitofrontal neurons during reward expectancy

The expectancy of a rewarding outcome following actions and cues is coded by a network of brain structures including the orbitofrontal cortex. Thus far, predicted reward was considered to be coded by time-averaged spike rates of neurons. However, besides firing rate, the precise timing of action potentials in relation to ongoing oscillations in local field potentials is thought to be of importance for effective communication between brain areas. We performed multineuron and field potential recordings in orbitofrontal cortex of rats performing olfactory discrimination learning to study the temporal structure of coding predictive of outcome. After associative learning, field potentials were marked by theta oscillations, both in advance and during delivery of reward. Orbitofrontal neurons, especially those coding information about upcoming reward with their firing rate, phase locked to these oscillations in anticipation of reward. When established associations were reversed, phase locking collapsed in the anticipatory task phase, but returned when reward became predictable again after relearning. Behaviorally, the outcome anticipation phase was marked by licking responses, but the frequency of lick responses was dissociated from the strength of theta-band phase locking. The strength of theta-band phase locking by orbitofrontal neurons robustly follows the dynamics of associative learning as measured by behavior and correlates with the rats current outcome expectancy. Theta-band phase locking may facilitate communication of outcome-related information between reward-related brain areas and offers a novel mechanism for coding value signals during reinforcement learning.

How to detect the Granger-causal flow direction in the presence of additive noise?

Granger-causality metrics have become increasingly popular tools to identify directed interactions between brain areas. However, it is known that additive noise can strongly affect Granger-causality metrics, which can lead to spurious conclusions about neuronal interactions. To solve this problem, previous studies have proposed the detection of Granger-causal directionality, i.e. the dominant Granger-causal flow, using either the slope of the coherency (Phase Slope Index; PSI), or by comparing Granger-causality values between original and time-reversed signals (reversed Granger testing). We show that for ensembles of vector autoregressive (VAR) models encompassing bidirectionally coupled sources, these alternative methods do not correctly measure Granger-causal directionality for a substantial fraction of VAR models, even in the absence of noise. We then demonstrate that uncorrelated noise has fundamentally different effects on directed connectivity metrics than linearly mixed noise, where the latter may result as a consequence of electric volume conduction. Uncorrelated noise only weakly affects the detection of Granger-causal directionality, whereas linearly mixed noise causes a large fraction of false positives for standard Granger-causality metrics and PSI, but not for reversed Granger testing. We further show that we can reliably identify cases where linearly mixed noise causes a large fraction of false positives by examining the magnitude of the instantaneous influence coefficient in a structural VAR model. By rejecting cases with strong instantaneous influence, we obtain an improved detection of Granger-causal flow between neuronal sources in the presence of additive noise. These techniques are applicable to real data, which we demonstrate using actual area V1 and area V4 LFP data, recorded from the awake monkey performing a visual attention task.

Gamma or no gamma, that is the question

Numerous studies suggest that gamma-band synchronization is central to visual processing, yet most of them have used artificial stimuli. A new study using electrocorticography (ECoG) in humans reported finding no gamma for many natural images and for visual noise. However, we highlight that sensitive metrics can reveal clear gamma not only for natural images, but for noise stimuli and even during the absence of visual stimuli. This shows the importance of using appropriate metrics for detecting rhythmic synchronization and investigating the function of gamma during natural viewing.

Mapping of Functionally Characterized Cell Classes onto Canonical Circuit Operations in Primate Prefrontal Cortex

Microcircuits are composed of multiple cell classes that likely serve unique circuit operations. But how cell classes map onto circuit functions is largely unknown, particularly for primate prefrontal cortex during actual goal-directed behavior. One difficulty in this quest is to reliably distinguish cell classes in extracellular recordings of action potentials. Here we surmount this issue and report that spike shape and neural firing variability provide reliable markers to segregate seven functional classes of prefrontal cells in macaques engaged in an attention task. We delineate an unbiased clustering protocol that identifies four broad spiking (BS) putative pyramidal cell classes and three narrow spiking (NS) putative inhibitory cell classes dissociated by how sparse, bursty, or regular they fire. We speculate that these functional classes map onto canonical circuit functions. First, two BS classes show sparse, bursty firing, and phase synchronize their spiking to 3–7 Hz (theta) and 12–20 Hz (beta) frequency bands of the local field potential (LFP). These properties make cells flexibly responsive to network activation at varying frequencies. Second, one NS and two BS cell classes show regular firing and higher rate with only marginal synchronization preference. These properties are akin to setting tonically the excitation and inhibition balance. Finally, two NS classes fired irregularly and synchronized to either theta or beta LFP fluctuations, tuning them potentially to frequency-specific subnetworks. These results suggest that a limited set of functional cell classes emerges in macaque prefrontal cortex (PFC) during attentional engagement to not only represent information, but to subserve basic circuit operations.

Cell-Type and State-Dependent Synchronization among Rodent Somatosensory, Visual, Perirhinal Cortex, and Hippocampus CA1

Beta and gamma rhythms have been hypothesized to be involved in global and local coordination of neuronal activity, respectively. Here, we investigated how cells in rodent area S1BF are entrained by rhythmic fluctuations at various frequencies within the local area and in connected areas, and how this depends on behavioral state and cell type. We performed simultaneous extracellular field and unit recordings in four connected areas of the freely moving rat (S1BF, V1M, perirhinal cortex, CA1). S1BF spiking activity was strongly entrained by both beta and gamma S1BF oscillations, which were associated with deactivations and activations, respectively. We identified multiple classes of fast spiking and excitatory cells in S1BF, which showed prominent differences in rhythmic entrainment and in the extent to which phase locking was modulated by behavioral state. Using an additional dataset acquired by whole-cell recordings in head-fixed mice, these cell classes could be compared with identified phenotypes showing gamma rhythmicity in their membrane potential. We next examined how S1BF cells were entrained by rhythmic fluctuations in connected brain areas. Gamma-synchronization was detected in all four areas, however we did not detect significant gamma coherence among these areas. Instead, we only found long-range coherence in the theta-beta range among these areas. In contrast to local S1BF synchronization, we found long-range S1BF-spike to CA1–LFP synchronization to be homogeneous across inhibitory and excitatory cell types. These findings suggest distinct, cell-type contributions of low and high-frequency synchronization to intra- and inter-areal neuronal interactions.

Respiration phase-locks to fast stimulus presentations: Implications for the interpretation of posterior midline “deactivations”

The posterior midline region (PMR)—considered a core of the default mode network—is deactivated during successful performance in different cognitive tasks. The extent of PMR‐deactivations is correlated with task‐demands and associated with successful performance in various cognitive domains. In the domain of episodic memory, functional MRI (fMRI) studies found that PMR‐deactivations reliably predict learning (successful encoding). Yet it is unclear what explains this relation. One intriguing possibility is that PMR‐deactivations are partially mediated by respiratory artifacts. There is evidence that the fMRI signal in PMR is particularly prone to respiratory artifacts, because of its large surrounding blood vessels. As respiratory fluctuations have been shown to track changes in attention, it is critical for the general interpretation of fMRI results to clarify the relation between respiratory fluctuations, cognitive performance, and fMRI signal. Here, we investigated this issue by measuring respiration during word encoding, together with a breath‐holding condition during fMRI‐scanning. Stimulus‐locked respiratory analyses showed that respiratory fluctuations predicted successful encoding via a respiratory phase‐locking mechanism. At the same time, the fMRI analyses showed that PMR‐deactivations associated with learning were reduced during breath‐holding and correlated with individual differences in the respiratory phase‐locking effect during normal breathing. A left frontal region—used as a control region—did not show these effects. These findings indicate that respiration is a critical factor in explaining the link between PMR‐deactivation and successful cognitive performance. Further research is necessary to demonstrate whether our findings are restricted to episodic memory encoding, or also extend to other cognitive domains. Hum Brain Mapp 35:4932–4943, 2014.

Developmental Dysfunction of VIP Interneurons Impairs Cortical Circuits

GABAergic interneurons play important roles in cortical circuit development. However, there are multiple populations of interneurons and their respective developmental contributions remain poorly explored. Neuregulin 1 (NRG1) and its interneuron-specific receptor ERBB4 are critical genes for interneuron maturation. Using a conditional ErbB4 deletion, we tested the role of vasoactive intestinal peptide (VIP)-expressing interneurons in the postnatal maturation of cortical circuits inxa0vivo. ErbB4 removal from VIP interneurons during development leads to changes inxa0their activity, along with severe dysregulation of cortical temporal organization and state dependence. These alterations emerge during adolescence, and mature animals in which VIP interneurons lack ErbB4 exhibit reduced cortical responses to sensory stimuli and impaired sensory learning. Our data support a key role for VIP interneurons in cortical circuit development and suggest a possible contribution to pathophysiology in neurodevelopmental disorders. These findings provide a new perspective on the role of GABAergic interneuron diversity in cortical development. VIDEO ABSTRACT.