Modeling the effect of locus coeruleus firing on cortical state dynamics and single-trial sensory processing

Juxtacellular recordings from identified neurons in the mouse locus coeruleus

The locus coeruleus (LC) is the primary source of noradrenergic transmission in the mammalian central nervous system. This small pontine nucleus consists of a densely packed nuclear core-which contains the highest density of noradrenergic neurons-embedded within a heterogeneous surround of non-noradrenergic cells. This local heterogeneity, together with the small size of the LC, has made it particularly difficult to infer noradrenergic cell identity based on extracellular sampling of in vivo spiking activity. Moreover, the relatively high cell density, background activity and synchronicity of LC neurons have made spike identification and unit isolation notoriously challenging. In this study, we aimed at bridging these gaps by performing juxtacellular recordings from single identified neurons within the mouse LC complex. We found that noradrenergic neurons (identified by tyrosine hydroxylase, TH, expression; TH-positive) and intermingled putatively non-noradrenergic (TH-negative) cells displayed similar morphologies and responded to foot shock stimuli with excitatory responses; however, on average, TH-positive neurons exhibited more prominent foot shock responses and post-activation firing suppression. The two cell classes also displayed different spontaneous firing rates, spike waveforms and temporal spiking properties. A logistic regression classifier trained on spontaneous electrophysiological features could separate the two cell classes with 76% accuracy. Altogether, our results reveal in vivo electrophysiological correlates of TH-positive neurons, which can be useful for refining current approaches for the classification of LC unit activity.

Information flow between motor cortex and striatum reverses during skill learning

The coordination of neural activity across brain areas during a specific behavior is often interpreted as neural communication involved in controlling the behavior. However, whether information relevant to the behavior is actually transferred between areas is often untested. Here, we used information-theoretic tools to quantify how motor cortex and striatum encode and exchange behaviorally relevant information about specific reach-to-grasp movement features during skill learning in rats. We found a temporal shift in the encoding of behaviorally relevant information during skill learning, as well as a reversal in the primary direction of behaviorally relevant information flow, from cortex-to-striatum during naive movements to striatum-to-cortex during skilled movements. Standard analytical methods that quantify the evolution of overall neural activity during learning-such as changes in neural signal amplitude or the overall exchange of information between areas-failed to capture these behaviorally relevant information dynamics. Using these standard methods, we instead found a consistent coactivation of overall neural signals during movement production and a bidirectional increase in overall information propagation between areas during learning. Our results show that skill learning is achieved through a transformation in how behaviorally relevant information is routed across cortical and subcortical brain areas and that isolating the components of neural activity relevant to and informative about behavior is critical to uncover directional interactions within a coactive and coordinated network.

Age-dependent dysregulation of locus coeruleus firing in a transgenic rat model of Alzheimer's disease

Hyperphosphorylated tau in the locus coeruleus (LC) is ubiquitous in prodromal Alzheimer's disease (AD), and LC neurons degenerate as AD progresses. Hyperphosphorylated tau alters firing rates in other brain regions, but its effects on LC neurons are unknown. We assessed single unit LC activity in anesthetized wild-type (WT) and TgF344-AD rats at 6 months, which represents a prodromal stage when LC neurons are the only cells containing hyperphosphorylated tau in TgF344-AD animals, and at 15 months when amyloid-β (Aβ) and tau pathology are both abundant in the forebrain. At baseline, LC neurons from TgF344-AD rats were hypoactive at both ages compared to WT littermates but showed elevated spontaneous bursting properties. Differences in footshock-evoked LC firing depended on age, with 6-month TgF344-AD rats demonstrating aspects of hyperactivity, and 15-month transgenic rats showing hypoactivity. Early LC hyperactivity is consistent with appearance of prodromal neuropsychiatric symptoms and is followed by LC hypoactivity which contributes to cognitive impairment. These results support further investigation into disease stage-dependent noradrenergic interventions for AD.

Altered norepinephrine transmission after spatial learning impairs sleep-mediated memory consolidation in rats

The therapeutic use of noradrenergic drugs makes the evaluation of their effects on cognition of high priority. Norepinephrine (NE) is an important neuromodulator for a variety of cognitive processes and may importantly contribute to sleep-mediated memory consolidation. The NE transmission fluctuates with the behavioral and/or brain state and influences associated neural activity. Here, we assessed the effects of altered NE transmission after learning of a hippocampal-dependent task on neural activity and spatial memory in adult male rats. We administered clonidine (0.05 mg/kg, i.p.; n = 12 rats) or propranolol (10 mg/kg, i.p.; n = 11) after each of seven daily learning sessions on an 8-arm radial maze. Compared to the saline group (n = 9), the drug-treated rats showed lower learning rates. To assess the effects of drugs on cortical and hippocampal activity, we recorded prefrontal EEG and local field potentials from the CA1 subfield of the dorsal hippocampus for 2 h after each learning session or drug administration. Both drugs significantly reduced the number of hippocampal ripples for at least 2 h. An EEG-based sleep scoring revealed that clonidine made the sleep onset faster while prolonging quiet wakefulness. Propranolol increased active wakefulness at the expense of non-rapid eye movement (NREM) sleep. Clonidine reduced the occurrence of slow oscillations (SO) and sleep spindles during NREM sleep and altered the temporal coupling between SO and sleep spindles. Thus, pharmacological alteration of NE transmission produced a suboptimal brain state for memory consolidation. Our results suggest that the post-learning NE contributes to the efficiency of hippocampal-cortical communication underlying memory consolidation.

Sensory salience processing moderates attenuated gazes on faces in autism spectrum disorder: a case-control study

BACKGROUND

Attenuated social attention is a key marker of autism spectrum disorder (ASD). Recent neuroimaging findings also emphasize an altered processing of sensory salience in ASD. The locus coeruleus-norepinephrine system (LC-NE) has been established as a modulator of this sensory salience processing (SSP). We tested the hypothesis that altered LC-NE functioning contributes to different SSP and results in diverging social attention in ASD.

METHODS

We analyzed the baseline eye-tracking data of the EU-AIMS Longitudinal European Autism Project (LEAP) for subgroups of autistic participants (n = 166, age = 6-30 years, IQ = 61-138, gender [female/male] = 41/125) or neurotypical development (TD; n = 166, age = 6-30 years, IQ = 63-138, gender [female/male] = 49/117) that were matched for demographic variables and data quality. Participants watched brief movie scenes (k = 85) depicting humans in social situations (human) or without humans (non-human). SSP was estimated by gazes on physical and motion salience and a corresponding pupillary response that indexes phasic activity of the LC-NE. Social attention is estimated by gazes on faces via manual areas of interest definition. SSP is compared between groups and related to social attention by linear mixed models that consider temporal dynamics within scenes. Models are controlled for comorbid psychopathology, gaze behavior, and luminance.

RESULTS

We found no group differences in gazes on salience, whereas pupillary responses were associated with altered gazes on physical and motion salience. In ASD compared to TD, we observed pupillary responses that were higher for non-human scenes and lower for human scenes. In ASD, we observed lower gazes on faces across the duration of the scenes. Crucially, this different social attention was influenced by gazes on physical salience and moderated by pupillary responses.

LIMITATIONS

The naturalistic study design precluded experimental manipulations and stimulus control, while effect sizes were small to moderate. Covariate effects of age and IQ indicate that the findings differ between age and developmental subgroups.

CONCLUSIONS

Pupillary responses as a proxy of LC-NE phasic activity during visual attention are suggested to modulate sensory salience processing and contribute to attenuated social attention in ASD.

NMDA Enhances and Glutamate Attenuates Synchrony of Spontaneous Phase-Locked Locus Coeruleus Network Rhythm in Newborn Rat Brain Slices

Locus coeruleus (LC) neurons are controlled by glutamatergic inputs. Here, we studied in brain slices of neonatal rats NMDA and glutamate effects on phase-locked LC neuron spiking at ~1 Hz summating to ~0.2 s-lasting bell-shaped local field potential (LFP). NMDA: 10 μM accelerated LFP 1.7-fold, whereas 25 and 50 μM, respectively, increased its rate 3.2- and 4.6-fold while merging discrete events into 43 and 56% shorter oscillations. After 4–6 min, LFP oscillations stopped every 6 s for 1 s, resulting in ‘oscillation trains’. A dose of 32 μM depolarized neurons by 8.4 mV to cause 7.2-fold accelerated spiking at reduced jitter and enhanced synchrony with the LFP, as evident from cross-correlation. Glutamate: 25–50 μM made rhythm more irregular and the LFP pattern could transform into 2.7-fold longer-lasting multipeak discharge. In 100 μM, LFP amplitude and duration declined. In 25–50 μM, neurons depolarized by 5 mV to cause 3.7-fold acceleration of spiking that was less synchronized with LFP. Both agents: evoked ‘post-agonist depression’ of LFP that correlated with the amplitude and kinetics of V_m hyperpolarization. The findings show that accelerated spiking during NMDA and glutamate is associated with enhanced or attenuated LC synchrony, respectively, causing distinct LFP pattern transformations. Shaping of LC population discharge dynamics by ionotropic glutamate receptors potentially fine-tunes its influence on brain functions.

Increased fMRI connectivity upon chemogenetic inhibition of the mouse prefrontal cortex

While shaped and constrained by axonal connections, fMRI-based functional connectivity reorganizes in response to varying interareal input or pathological perturbations. However, the causal contribution of regional brain activity to whole-brain fMRI network organization remains unclear. Here we combine neural manipulations, resting-state fMRI and in vivo electrophysiology to probe how inactivation of a cortical node causally affects brain-wide fMRI coupling in the mouse. We find that chronic inhibition of the medial prefrontal cortex (PFC) via overexpression of a potassium channel increases fMRI connectivity between the inhibited area and its direct thalamo-cortical targets. Acute chemogenetic inhibition of the PFC produces analogous patterns of fMRI overconnectivity. Using in vivo electrophysiology, we find that chemogenetic inhibition of the PFC enhances low frequency (0.1–4 Hz) oscillatory power via suppression of neural firing not phase-locked to slow rhythms, resulting in increased slow and δ band coherence between areas that exhibit fMRI overconnectivity. These results provide causal evidence that cortical inactivation can counterintuitively increase fMRI connectivity via enhanced, less-localized slow oscillatory processes.

Pathological perturbation affects whole brain network activity. Here the authors show in mice that cortical inactivation unexpectedly results in increased fMRI connectivity between the manipulated regions and its direct axonal targets.

Functional Coupling of the Locus Coeruleus Is Linked to Successful Cognitive Control

The locus coeruleus (LC) is a brainstem structure that sends widespread efferent projections throughout the mammalian brain. The LC constitutes the major source of noradrenaline (NE), a modulatory neurotransmitter that is crucial for fundamental brain functions such as arousal, attention, and cognitive control. This role of the LC-NE is traditionally not believed to reflect functional influences on the frontoparietal network or the striatum, but recent advances in chemogenetic manipulations of the rodent brain have challenged this notion. However, demonstrations of LC-NE functional connectivity with these areas in the human brain are surprisingly sparse. Here, we close this gap. Using an established emotional stroop task, we directly compared trials requiring response conflict control with trials that did not require this, but were matched for visual stimulus properties, response modality, and controlled for pupil dilation differences across both trial types. We found that LC-NE functional coupling with the parietal cortex and regions of the striatum is substantially enhanced during trials requiring response conflict control. Crucially, the strength of this functional coupling was directly related to individual reaction time differences incurred by conflict resolution. Our data concur with recent rodent findings and highlight the importance of converging evidence between human and nonhuman neurophysiology to further understand the neural systems supporting adaptive and maladaptive behavior in health and disease.

Noradrenergic modulation of rhythmic neural activity shapes selective attention

During moments involving selective attention, the thalamus orchestrates the preferential processing of prioritized information by coordinating rhythmic neural activity within a distributed frontoparietal network. The timed release of neuromodulators from subcortical structures dynamically sculpts neural synchronization in thalamocortical networks to meet current attentional demands. In particular, noradrenaline modulates the balance of cortical excitation and inhibition, as reflected by thalamocortical alpha synchronization (~8-12 Hz). These neuromodulatory adjustments facilitate the selective processing of prioritized information. Thus, by disrupting effective rhythmic coordination in attention networks, age-related locus coeruleus (LC) degeneration can impair higher levels of neural processing. In sum, findings across different levels of analysis and modalities shed light on how the noradrenergic modulation of neural synchronization helps to shape selective attention.

State-Dependent Changes in Perception and Coding in the Mouse Somatosensory Cortex

An animal's behavioral state is reflected in the dynamics of cortical population activity and its capacity to process sensory information. To better understand the relationship between behavioral states and information processing, mice are trained to detect varying amplitudes of whisker-deflection under two-photon calcium imaging. Layer 2/3 neurons in the vibrissal primary somatosensory cortex are imaged across different behavioral states, defined based on detection performance (low to high-state) and pupil diameter. The neurometric curve in each behavioral state mirrors the corresponding psychometric performance, with calcium signals predictive of the animal's choice. High behavioral states are associated with lower network synchrony, extending over shorter cortical distances. The decrease in correlation across neurons in high state results in enhanced information transmission capacity at the population level. The observed state-dependent changes suggest that the coding regime within the first stage of cortical processing may underlie adaptive routing of relevant information through the sensorimotor system.

Modulation of Prefrontal Cortex Slow Oscillations by Phasic Activation of the Locus Coeruleus

Cortical slow rhythmic activity, a hallmark of deep sleep, is observed under urethane anesthesia. Synchronized fluctuations of the membrane excitability of a large neuronal population are reflected in the extracellular Local Field Potential (LFP), as high-amplitude slow (∼1 Hz) oscillations (SO). The SO-phase indicates the presence (Up) or absence (Down) of neuronal spiking. The cortical state is controlled by the input from thalamic and neuromodulatory centers, including the brainstem noradrenergic nucleus Locus Coeruleus (LC). The bidirectional modulation of neuronal excitability by noradrenaline (NA) is well known. We have previously shown that LC phasic activation caused transient excitability increase in the medial prefrontal cortex (mPFC). In the present study, we characterized the effect of LC phasic activation on the prefrontal population dynamics at a temporal scale of a single SO cycle. We applied short (0.2 s) trains of electric pulses (0.02-0.05 mA at 20-50 Hz) to the LC cell bodies and monitored a broadband (0.1 Hz-8 kHz) mPFC LFP in urethane-anesthetized rats. The direct electrical stimulation of LC (LC-DES), applied during the Up-phase, enhanced the firing probability in the mPFC by ∼20% and substantially prolonged Up-states in 56% of trials. The LC-DES applied during Down-phase caused a rapid Down-to-Up transition in 81.5% of trials. The LC-DES was more effective at a higher frequency, but not at a higher current. Our results suggest that transient NA release, coupled to SO, may promote synaptic plasticity and memory consolidation by sustaining a depolarized state in the mPFC neurons.

Synchronous spiking associated with prefrontal high γ oscillations evokes a 5-Hz rhythmic modulation of spiking in locus coeruleus

The brainstem noradrenergic locus coeruleus (LC) is reciprocally connected with the prefrontal cortex (PFC). Coupling between LC spiking and the depolarizing phase of slow (1-2 Hz) waves in PFC field potentials during sleep and anesthesia suggests that LC drives cortical state transition. Reciprocal LC-PFC connectivity should also allow interactions in the opposing (top-down) direction, but prior work has only studied prefrontal control over LC activity using electrical or optogenetic stimulation. Here, we describe the physiological characteristics of spontaneously occurring top-down LC-PFC interactions. We recorded LC multiunit activity (MUA) simultaneously with PFC single-unit and local field potential (LFP) activity in urethane-anesthetized rats. We observed cross-regional coupling between the phase of 5-Hz oscillations in LC-MUA and the power of PFC LFP 60-200 Hz high γ (hγ). Transient increases in PFC hγ power preceded peaks in the 5-Hz LC-MUA oscillation. Analysis of cross-regional transfer entropy demonstrated that the PFC hγ transients were predictive of a transient increase in LC-MUA. An ∼29 ms delay between these signals was consistent with the conduction velocity from the PFC to the LC. Finally, we showed that PFC hγ transients are associated with synchronized spiking of a subset (27%) of PFC single units. Our data suggest that PFC hγ transients may indicate the timing of the top-down excitatory input to LC, at least under conditions when LC neuronal population activity fluctuates rhythmically at 5 Hz. Synchronized PFC neuronal spiking that occurs during hγ transients may provide a previously unknown mode of top-down control over the LC.NEW & NOTEWORTHY The prefrontal cortex (PFC) is thought to control activity in the noradrenergic locus coeruleus (LC). Prior anatomical and prefrontal stimulation studies demonstrated the potential for PFC-LC interactions; however, it is unknown what types of PFC activity affect the LC. Here, we show that transient increases in PFC high γ power and associated changes in PFC unit-pair synchrony are a potential sign of top-down control over the LC.

Resting Brain Fluctuations Are Intrinsically Coupled to Visual Response Dynamics

How do intrinsic brain dynamics interact with processing of external sensory stimuli? We sought new insights using functional magnetic resonance imaging to track spatiotemporal activity patterns at the whole brain level in lightly anesthetized mice, during both resting conditions and visual stimulation trials. Our results provide evidence that quasiperiodic patterns (QPPs) are the most prominent component of mouse resting brain dynamics. These QPPs captured the temporal alignment of anticorrelation between the default mode (DMN)- and task-positive (TPN)-like networks, with global brain fluctuations, and activity in neuromodulatory nuclei of the reticular formation. Specifically, the phase of QPPs prior to stimulation could significantly stratify subsequent visual response magnitude, suggesting QPPs relate to brain state fluctuations. This is the first observation in mice that dynamics of the DMN- and TPN-like networks, and particularly their anticorrelation, capture a brain state dynamic that affects sensory processing. Interestingly, QPPs also displayed transient onset response properties during visual stimulation, which covaried with deactivations in the reticular formation. We conclude that QPPs appear to capture a brain state fluctuation that may be orchestrated through neuromodulation. Our findings provide new frontiers to understand the neural processes that shape functional brain states and modulate sensory input processing.

Brain dynamics for confidence-weighted learning

Learning in a changing, uncertain environment is a difficult problem. A popular solution is to predict future observations and then use surprising outcomes to update those predictions. However, humans also have a sense of confidence that characterizes the precision of their predictions. Bayesian models use a confidence-weighting principle to regulate learning: for a given surprise, the update is smaller when the confidence about the prediction was higher. Prior behavioral evidence indicates that human learning adheres to this confidence-weighting principle. Here, we explored the human brain dynamics sub-tending the confidence-weighting of learning using magneto-encephalography (MEG). During our volatile probability learning task, subjects’ confidence reports conformed with Bayesian inference. MEG revealed several stimulus-evoked brain responses whose amplitude reflected surprise, and some of them were further shaped by confidence: surprise amplified the stimulus-evoked response whereas confidence dampened it. Confidence about predictions also modulated several aspects of the brain state: pupil-linked arousal and beta-range (15–30 Hz) oscillations. The brain state in turn modulated specific stimulus-evoked surprise responses following the confidence-weighting principle. Our results thus indicate that there exist, in the human brain, signals reflecting surprise that are dampened by confidence in a way that is appropriate for learning according to Bayesian inference. They also suggest a mechanism for confidence-weighted learning: confidence about predictions would modulate intrinsic properties of the brain state to amplify or dampen surprise responses evoked by discrepant observations.

Learning in a changing and uncertain world is difficult. In this context, facing a discrepancy between my current belief and new observations may reflect random fluctuations (e.g. my commute train is unexpectedly late, but it happens sometimes), if so, I should ignore this discrepancy and not change erratically my belief. However, this discrepancy could also denote a profound change (e.g. the train company changed and is less reliable), in this case, I should promptly revise my current belief. Human learning is adaptive: we change how much we learn from new observations, in particular, we promote flexibility when facing profound changes. A mathematical analysis of the problem shows that we should increase flexibility when the confidence about our current belief is low, which occurs when a change is suspected. Here, I show that human learners entertain rational confidence levels during the learning of changing probabilities. This confidence modulates intrinsic properties of the brain state (oscillatory activity and neuromodulation) which in turn amplifies or reduces, depending on whether confidence is low or high, the neural responses to discrepant observations. This confidence-weighting mechanism could underpin adaptive learning.

Impaired Phasic Discharge of Locus Coeruleus Neurons Based on Persistent High Tonic Discharge-A New Hypothesis With Potential Implications for Neurodegenerative Diseases

The locus coeruleus (LC) is a small brainstem nucleus with widely distributed noradrenergic projections to the whole brain, and loss of LC neurons is a prominent feature of age-related neurodegenerative diseases, such as Alzheimer's disease (AD) and Parkinson's disease (PD). This article discusses the hypothesis that in early stages of neurodegenerative diseases, the discharge mode of LC neurons could be changed to a persistent high tonic discharge, which in turn might impair phasic discharge. Since phasic discharge of LC neurons is required for the release of high amounts of norepinephrine (NE) in the brain to promote anti-inflammatory and neuroprotective effects, persistent high tonic discharge of LC neurons could be a key factor in the progression of neurodegenerative diseases. Transcutaneous vagal stimulation (t-VNS), a non-invasive technique that potentially increases phasic discharge of LC neurons, could therefore provide a non-pharmacological treatment approach in specific disease stages. This article focuses on LC vulnerability in neurodegenerative diseases, discusses the hypothesis that a persistent high tonic discharge of LC neurons might affect neurodegenerative processes, and finally reflects on t-VNS as a potentially useful clinical tool in specific stages of AD and PD.

Increased ACh-Associated Immunoreactivity in Autonomic Centers in PTZ Kindling Model of Epilepsy

Experimental and clinical studies of cardiac pathology associated with epilepsy have demonstrated an impact on the autonomic nervous system (ANS). However, the underlying molecular mechanism has not been fully elucidated. Molecular investigation of the neurotransmitters related receptor and ion channel directing ANS might help in understanding the associated mechanism. In this paper, we investigated the role of acetylcholine (ACh), which demonstrates both sympathetic and parasympathetic roles in targeted expression in terms of the relevant receptor and ion channel. Inwardly rectifying potassium (Kir) channels play a significant role in maintaining the resting membrane potential and controlling cell excitability and are prominently expressed in both the excitable and non-excitable tissues. The immunoreactivity of ACh-activated Kir3.1 channel and muscarinic ACh receptors (M2) in autonomic centers such as the brainstem, vagus nerve (VN) and atria of heart was confirmed by both histological staining and pathological tissue analysis. Significant upregulations of Kir3.1 and M2 receptors were observed in pentylenetetrazol (PTZ)-kindled epileptic rats for all related tissues investigated, whereas no pathological difference was observed. These findings provide proof-of-concept that changes in ACh-associated immunoreactivity might be linked to the ANS dysfunctions associated with epilepsy.

Noradrenergic Responsiveness Supports Selective Attention across the Adult Lifespan

Selectively attending to relevant information while blocking out distractors is crucial for goal-directed behavior, yet with advancing age, deficits emerge in attentional selectivity. Decrements in attention have been associated with altered noradrenergic activity in animals. However, research linking noradrenergic functioning to attention in aging humans is scarce, likely reflecting long-standing methodological challenges in noninvasive assessments. We studied whether age-related differences in the noradrenergic system predict differences in attention. We measured pupil dilation, a noninvasive marker of arousal-related norepinephrine (NE) release, while concurrently recording the EEG of male younger (N = 39; 25.2 ± 3.2 years) and older adults (N = 38; 70.6 ± 2.7 years). Arousal was modulated on a trial-by-trial basis using fear-conditioned (CS⁺) stimuli. During conditioning, pupil and EEG markers related to heightened arousal were identified. Afterward, in a dichotic listening task, participants were cued to direct attention to either the left or right ear while highly similar syllable pairs were presented simultaneously to both ears. During the dichotic listening task, presentation of fear-conditioned stimuli reinstated the acquired arousal response, as reflected in pupil and EEG α-β band responses. Critically, pupil dilation to CS⁺ was correlated with stronger EEG α-β desynchronization, suggesting a common dependence on NE release. On a behavioral level, stronger arousal reactions were associated with better attention. In particular, structural equation modeling revealed that the responsiveness of the NE system is associated with attention on a latent construct level, measured by several indicator tasks. Overall, our results suggest that the responsiveness of the NE system supports attention across the lifespan.SIGNIFICANCE STATEMENT In old age, the ability to selectively process relevant aspects of the environment fades. Animal research suggests that the neuromodulator norepinephrine helps to maintain selective attention. We tested younger and older adults across a variety of attention tasks. In addition, we used arousing stimuli to experimentally activate participants' noradrenergic system while recording pupillometry and EEG to infer its functional capacity. Older adults showed compromised attention and reduced noradrenergic responsiveness as indicated by interrelated pupil and EEG markers. Crucially, in both age groups, a more responsive noradrenergic system was strongly associated with attention. Our findings link animal and human studies on the neural underpinning of attention in aging and underscore the importance of the noradrenergic system in late-life cognition.

Brainstem Modulation of Large-Scale Intrinsic Cortical Activity Correlations

Brain activity fluctuates continuously, even in the absence of changes in sensory input or motor output. These intrinsic activity fluctuations are correlated across brain regions and are spatially organized in macroscale networks. Variations in the strength, topography, and topology of correlated activity occur over time, and unfold upon a backbone of long-range anatomical connections. Subcortical neuromodulatory systems send widespread ascending projections to the cortex, and are thus ideally situated to shape the temporal and spatial structure of intrinsic correlations. These systems are also the targets of the pharmacological treatment of major neurological and psychiatric disorders, such as Parkinson's disease, depression, and schizophrenia. Here, we review recent work that has investigated how neuromodulatory systems shape correlations of intrinsic fluctuations of large-scale cortical activity. We discuss studies in the human, monkey, and rodent brain, with a focus on non-invasive recordings of human brain activity. We provide a structured but selective overview of this work and distil a number of emerging principles. Future efforts to chart the effect of specific neuromodulators and, in particular, specific receptors, on intrinsic correlations may help identify shared or antagonistic principles between different neuromodulatory systems. Such principles can inform models of healthy brain function and may provide an important reference for understanding altered cortical dynamics that are evident in neurological and psychiatric disorders, potentially paving the way for mechanistically inspired biomarkers and individualized treatments of these disorders.

Active High-Density Electrode Arrays: Technology and Applications in Neuronal Cell Cultures

Active high-density electrode arrays realized with complementary metal-oxide-semiconductor (CMOS) technology provide electrophysiological recordings from several thousands of closely spaced microelectrodes. This has drastically advanced the spatiotemporal recording resolution of conventional multielectrode arrays (MEAs). Thus, today's electrophysiology in neuronal cultures can exploit label-free electrical readouts from a large number of single neurons within the same network. This provides advanced capabilities to investigate the properties of self-assembling neuronal networks, to advance studies on neurotoxicity and neurodevelopmental alterations associated with human brain diseases, and to develop cell culture models for testing drug- or cell-based strategies for therapies.Here, after introducing the reader to this neurotechnology, we summarize the results of different recent studies demonstrating the potential of active high-density electrode arrays for experimental applications. We also discuss ongoing and possible future research directions that might allow for moving these platforms forward for screening applications.

Brainstem atrophy in focal epilepsy destabilizes brainstem-brain interactions: Preliminary findings

Background

MR Imaging has shown atrophy in brainstem regions that were linked to autonomic dysfunction in epilepsy patients. The brainstem projects to and modulates the activation state of several wide-spread cortical/subcortical regions. The goal was to investigate 1. Impact of brainstem atrophy on gray matter connectivity of cortical/subcortical structures and autonomic control. 2. Impact on the modulation of cortical/subcortical functional connectivity.

Methods

11 controls and 18 patients with non-lesional focal epilepsy (FE) underwent heart rate variability (HRV) measurements and a 3 T MRI (T1 in all subjects, task-free fMRI in 7 controls/ 12 FE). The brainstem was extracted, and atrophy assessed using deformation-based-morphometry. The age-corrected z-scores of the mean Jacobian determinants were extracted from 71 5x5x5 mm grids placed in brainstem regions associated with autonomic function. Cortical and non-brainstem subcortical gray matter atrophy was assessed with voxel-based-morphometry and mean age corrected z-scores of the modulated gray matter volumes extracted from 380 cortical/subcortical rois. The profile similarity index was used to characterize the impact of brainstem atrophy on gray matter connectivity. The fMRI was preprocessed in SPM12/Conn17 and the BOLD signal extracted from 398 ROIs (16 brainstem). A dynamic task-free analysis approach was used to identify activation states. Connectivity HRV relationship were assessed with Spearman rank correlations.

Results

HRV was negatively correlated with reduced brainstem right hippocampus/parahippocampus gray matter connectivity in controls (p < .05, FDR) and reduced brainstem to right parietal cortex, lingual gyrus, left hippocampus/amygdala, parahippocampus, temporal pole, and bilateral anterior thalamus connectivity in FE (p < .05, FDR). Dynamic task-free fMRI analysis identified 22 states. The strength of the functional brainstem/cortical connectivity of state 15 was negatively associated with HRV (r = −0.5, p = .03) and positively with decreased brainstem-cortical (0.49, p = .03) gray matter connectivity.

Conclusion

The findings of this small pilot study suggest that impaired brainstem-cortex gray matter connectivity in FE negatively affects the brainstem's ability to control cortical activation.

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Brainstem and cortical/subcortical gray matter (gm) connectivity is impaired in FE.

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FE is associated with an abnormal brain activation state in the interictal state.

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The severity of the gm impairment and of the abnormal brain state are correlated.

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GM connectivity impairment and abnormal brain activity affect HRV.

Adrenergic Modulation of Visually-Guided Behavior

Iontophoretic application of norepinephrine (NE) into the primary visual cortex (V1) in vivo reduces spontaneous and evoked activity, without changing the functional selectivity of cortical units. One possible consequence of this phenomenon is that adrenergic receptors (ARs) regulate the signal-to-noise ratio (SNR) of neural responses in this circuit. However, despite such strong inhibitory action of NE on neuronal firing patterns in V1, its specific action on visual behavior has not been studied. Furthermore, the majority of observations regarding cortical NE from in vivo recordings have been performed in anesthetized animals and have not been tested behaviorally. Here, we describe how micro-infusion of AR agonists/antagonists into mouse V1 influences visually-guided behavior at different contrasts and spatial frequencies. We found that cortical activation of α₁- and β-AR produced a substantial reduction in visual discrimination performance at high contrasts and low spatial frequencies, consistent with a divisive effect. This reduction was reversible and was accompanied by a rise in escape latencies as well as an increase in the group averaged choice variance as a function of stimulus contrast. We conclude that pharmacological activation of cortical AR regulates visual perception and adaptive behavior through a divisive gain control of visual responses.

Reaction Time Improvements by Neural Bistability

The often reported reduction of Reaction Time (RT) by Vision Training) is successfully replicated by 81 athletes across sports. This enabled us to achieve a mean reduction of RTs for athletes eye-hand coordination of more than 10%, with high statistical significance. We explain how such an observed effect of Sensorimotor systems' plasticity causing reduced RT can last in practice for multiple days and even weeks in subjects, via a proof of principle. Its mathematical neural model can be forced outside a previous stable (but long) RT into a state leading to reduced eye-hand coordination RT, which is, again, in a stable neural state.

TARP mediation of accelerated and more regular locus coeruleus network bursting in neonatal rat brain slices

Transmembrane AMPA receptor (AMPAR) regulatory proteins (TARP) increase neuronal excitability. However, it is unknown how TARP affect rhythmic neural network activity. Here we studied TARP effects on local field potential (LFP) bursting, membrane potential and cytosolic Ca²⁺ (Ca_i) in locus coeruleus neurons of newborn rat brain slices. LFP bursting was not affected by the unselective competitive ionotropic glutamate receptor antagonist kynurenic acid (2.5 mM). TARP-AMPAR complex activation with 25 μM CNQX accelerated LFP rhythm 2.2-fold and decreased its irregularity score from 63 to 9. Neuronal spiking was correspondingly 2.3-fold accelerated in association with a 2-5 mV depolarization and a modest Ca_i rise whereas Ca_i was unchanged in neighboring astrocytes. After blocking rhythmic activities with tetrodotoxin (1 μM), CNQX caused a 5-8 mV depolarization and also the Ca_i rise persisted. In tetrodotoxin, both responses were abolished by the non-competitive AMPAR antagonist GYKI 53655 (25 μM) which also reversed stimulatory CNQX effects in control solution. The CNQX-evoked Ca_i rise was blocked by the L-type voltage-activated Ca²⁺ channel inhibitor nifedipine (100 μM). The findings show that ionotropic glutamate receptor-independent neonatal locus coeruleus network bursting is accelerated and becomes more regular by activating a TARP-AMPAR complex. The associated depolarization-evoked L-type Ca²⁺ channel-mediated neuronal Ca_i rise may be pivotal to regulate locus coeruleus activity in cooperation with SK-type K⁺ channels. In summary, this is the first demonstration of TARP-mediated stimulation of neural network bursting. We hypothesize that TARP-AMPAR stimulation of rhythmic locus coeruleus output serves to fine-tune its control of multiple brain functions thus comprising a target for drug discovery.

Phasic locus coeruleus activity regulates cortical encoding of salience information

Phasic activation of locus coeruleus (LC)-norepinephrine (NE) neurons is associated with focused attention and behavioral responses to salient stimuli. We used cell-type-specific optogenetics and single-unit neurophysiology to identify how LC activity influences neural encoding of sensory information. We found that phasic, but not tonic, LC-NE photoactivation generated a distinct event-related potential (ERP) across cortical regions. Salient sensory stimuli (which innately trigger phasic LC activity) produced strong excitatory cortical responses during this ERP window. Application of weaker, nonsalient stimuli produced limited responses, but these responses were elevated to salient stimulus levels when they were temporally locked with phasic LC photoactivation. These results demonstrate that phasic LC activity enhances cortical encoding of salient stimuli by facilitating long-latency signals within target regions in response to stimulus intensity/salience. The LC-driven salience signal identified here provides a measure of phasic LC activity that can be used to investigate the LC's role in attentional processing across species.

Catecholaminergic manipulation alters dynamic network topology across cognitive states

The human brain is able to flexibly adapt its information processing capacity to meet a variety of cognitive challenges. Recent evidence suggests that this flexibility is reflected in the dynamic reorganization of the functional connectome. The ascending catecholaminergic arousal systems of the brain are a plausible candidate mechanism for driving alterations in network architecture, enabling efficient deployment of cognitive resources when the environment demands them. We tested this hypothesis by analyzing both resting-state and task-based fMRI data following the administration of atomoxetine, a noradrenaline reuptake inhibitor, compared with placebo, in two separate human fMRI studies. Our results demonstrate that the manipulation of central catecholamine levels leads to a reorganization of the functional connectome in a manner that is sensitive to ongoing cognitive demands.

There is emerging evidence that the flexible network structure of the brain is related to activity within the ascending arousal systems of the brain, such as the noradrenergic locus coeruleus. Here, we explored the role of catecholaminergic activity on network architecture by analyzing the graph structure of the brain measured using functional MRI following the administration of atomoxetine, a selective noradrenaline reuptake inhibitor. We estimated functional network topology in two double-blind, placebo-controlled datasets: one from the resting state and another from a parametric N-back task. Our results demonstrate that the nature of catecholaminergic network reconfiguration is differentially related to cognitive state and provide confirmatory evidence for the hypothesis that the functional network signature of the brain is sensitive to the ascending catecholaminergic arousal system.

The Locus Coeruleus Is a Complex and Differentiated Neuromodulatory System

Diffuse projections of locus coeruleus (LC) neurons and evidence of synchronous spiking have long been perceived as features of global neuromodulation. Recent studies demonstrated the possibility of targeted modulation by subsets of LC neurons. Non-global neuromodulation depends on target specificity and the differentiated spatiotemporal dynamics within LC. Here, we characterized interactions between 3,164 LC cell pairs in the rat LC under urethane anesthesia. Spike count correlations were near zero and only a small proportion of unit pairs had synchronized spontaneous (15%) or evoked (16%) discharge. We identified infra-slow (0.01-1 Hz) fluctuations of LC unit spike rate, which were also asynchronous across the population. Despite overall sparse population synchrony, we report the existence of LC ensembles and relate them to forebrain projection targets. We also show that spike waveform width was related to ensemble membership, propensity for synchronization, and interactions with cortex. Our findings suggest a partly differentiated and target-specific noradrenergic signal.

Surprise About Sensory Event Timing Drives Cortical Transients in the Beta Frequency Band

Learning the statistical structure of the environment is crucial for adaptive behavior. Humans and nonhuman decision-makers seem to track such structure through a process of probabilistic inference, which enables predictions about behaviorally relevant events. Deviations from such predictions cause surprise, which in turn helps improve inference. Surprise about the timing of behaviorally relevant sensory events drives phasic responses of neuromodulatory brainstem systems, which project to the cerebral cortex. Here, we developed a computational model-based magnetoencephalography (MEG) approach for mapping the resulting cortical transients across space, time, and frequency, in the human brain (N = 28, 17 female). We used a Bayesian ideal observer model to learn the statistics of the timing of changes in a simple visual detection task. This model yielded quantitative trial-by-trial estimates of temporal surprise. The model-based surprise variable predicted trial-by-trial variations in reaction time more strongly than the externally observable interval timings alone. Trial-by-trial variations in surprise were negatively correlated with the power of cortical population activity measured with MEG. This surprise-related power suppression occurred transiently around the behavioral response, specifically in the beta frequency band. It peaked in parietal and prefrontal cortices, remote from the motor cortical suppression of beta power related to overt report (button press) of change detection. Our results indicate that surprise about sensory event timing transiently suppresses ongoing beta-band oscillations in association cortex. This transient suppression of frontal beta-band oscillations might reflect an active reset triggered by surprise, and is in line with the idea that beta-oscillations help maintain cognitive sets.SIGNIFICANCE STATEMENT The brain continuously tracks the statistical structure of the environment to anticipate behaviorally relevant events. Deviations from such predictions cause surprise, which in turn drives neural activity in subcortical brain regions that project to the cerebral cortex. We used magnetoencephalography in humans to map out surprise-related modulations of cortical population activity across space, time, and frequency. Surprise was elicited by variable timing of visual stimulus changes requiring a behavioral response. Surprise was quantified by means of an ideal observer model. Surprise predicted behavior as well as a transient suppression of beta frequency-band oscillations in frontal cortical regions. Our results are in line with conceptual accounts that have linked neural oscillations in the beta-band to the maintenance of cognitive sets.

Monoaminergic Neuromodulation of Sensory Processing

All neuronal circuits are subject to neuromodulation. Modulatory effects on neuronal processing and resulting behavioral changes are most commonly reported for higher order cognitive brain functions. Comparatively little is known about how neuromodulators shape processing in sensory brain areas that provide the signals for downstream regions to operate on. In this article, we review the current knowledge about how the monoamine neuromodulators serotonin, dopamine and noradrenaline influence the representation of sensory stimuli in the mammalian sensory system. We review the functional organization of the monoaminergic brainstem neuromodulatory systems in relation to their role for sensory processing and summarize recent neurophysiological evidence showing that monoamines have diverse effects on early sensory processing, including changes in gain and in the precision of neuronal responses to sensory inputs. We also highlight the substantial evidence for complementarity between these neuromodulatory systems with different patterns of innervation across brain areas and cortical layers as well as distinct neuromodulatory actions. Studying the effects of neuromodulators at various target sites is a crucial step in the development of a mechanistic understanding of neuronal information processing in the healthy brain and in the generation and maintenance of mental diseases.

Apical Function in Neocortical Pyramidal Cells: A Common Pathway by Which General Anesthetics Can Affect Mental State

It has been argued that general anesthetics suppress the level of consciousness, or the contents of consciousness, or both. The distinction between level and content is important because, in addition to clarifying the mechanisms of anesthesia, it may help clarify the neural bases of consciousness. We assess these arguments in the light of evidence that both the level and the content of consciousness depend upon the contribution of apical input to the information processing capabilities of neocortical pyramidal cells which selectively amplify relevant signals. We summarize research suggesting that what neocortical pyramidal cells transmit information about can be distinguished from levels of arousal controlled by sub-cortical nuclei and from levels of prioritization specified by interactions within the thalamocortical system. Put simply, on the basis of the observations reviewed, we hypothesize that when conscious we have particular, directly experienced, percepts, thoughts, feelings and intentions, and that general anesthetics affect consciousness by interfering with the subcellular processes by which particular activities are selectively amplified when relevant to the current context.

State-dependent representation of stimulus-evoked activity in high-density recordings of neural cultures

Neuronal responses to external stimuli vary from trial to trial partly because they depend on continuous spontaneous variations of the state of neural circuits, reflected in variations of ongoing activity prior to stimulus presentation. Understanding how post-stimulus responses relate to the pre-stimulus spontaneous activity is thus important to understand how state dependence affects information processing and neural coding, and how state variations can be discounted to better decode single-trial neural responses. Here we exploited high-resolution CMOS electrode arrays to record simultaneously from thousands of electrodes in in-vitro cultures stimulated at specific sites. We used information-theoretic analyses to study how ongoing activity affects the information that neuronal responses carry about the location of the stimuli. We found that responses exhibited state dependence on the time between the last spontaneous burst and the stimulus presentation and that the dependence could be described with a linear model. Importantly, we found that a small number of selected neurons carry most of the stimulus information and contribute to the state-dependent information gain. This suggests that a major value of large-scale recording is that it individuates the small subset of neurons that carry most information and that benefit the most from knowledge of its state dependence.

The modulation of neural gain facilitates a transition between functional segregation and integration in the brain

Cognitive function relies on a dynamic, context-sensitive balance between functional integration and segregation in the brain. Previous work has proposed that this balance is mediated by global fluctuations in neural gain by projections from ascending neuromodulatory nuclei. To test this hypothesis in silico, we studied the effects of neural gain on network dynamics in a model of large-scale neuronal dynamics. We found that increases in neural gain directed the network through an abrupt dynamical transition, leading to an integrated network topology that was maximal in frontoparietal 'rich club' regions. This gain-mediated transition was also associated with increased topological complexity, as well as increased variability in time-resolved topological structure, further highlighting the potential computational benefits of the gain-mediated network transition. These results support the hypothesis that neural gain modulation has the computational capacity to mediate the balance between integration and segregation in the brain.

Back to Pupillometry: How Cortical Network State Fluctuations Tracked by Pupil Dynamics Could Explain Neural Signal Variability in Human Cognitive Neuroscience

The mammalian thalamocortical system generates intrinsic activity reflecting different states of excitability, arising from changes in the membrane potentials of underlying neuronal networks. Fluctuations between these states occur spontaneously, regularly, and frequently throughout awake periods and influence stimulus encoding, information processing, and neuronal and behavioral responses. Changes of pupil size have recently been identified as a reliable marker of underlying neuronal membrane potential and thus can encode associated network state changes in rodent cortex. This suggests that pupillometry, a ubiquitous measure of pupil dilation in cognitive neuroscience, could be used as an index for network state fluctuations also for human brain signals. Considering this variable may explain task-independent variance in neuronal and behavioral signals that were previously disregarded as noise.

Locus coeruleus phasic discharge is essential for stimulus-induced gamma oscillations in the prefrontal cortex

The locus coeruleus (LC) noradrenergic (NE) neuromodulatory system is critically involved in regulation of neural excitability via its diffuse ascending projections. Tonic NE release in the forebrain is essential for maintenance of vigilant states and increases the signal-to-noise ratio of cortical sensory responses. The impact of phasic NE release on cortical activity and sensory processing is less explored. We previously reported that LC microstimulation caused a transient desynchronization of population activity in the medial prefrontal cortex (mPFC), similar to noxious somatosensory stimuli. The LC receives nociceptive information from the medulla and therefore may mediate sensory signaling to its forebrain targets. Here we performed extracellular recordings in LC and mPFC while presenting noxious stimuli in urethane-anesthetized rats. A brief train of foot shocks produced a robust phasic response in the LC and a transient change in the mPFC power spectrum, with the strongest modulation in the gamma (30-90 Hz) range. The LC phasic response preceded prefrontal gamma power increase, and cortical modulation was proportional to the LC excitation. We also quantitatively characterized distinct cortical states and showed that sensory responses in both LC and mPFC depend on the ongoing cortical state. Finally, cessation of the LC firing by bilateral local iontophoretic injection of clonidine, an α₂-adrenoreceptor agonist, completely eliminated sensory responses in the mPFC without shifting cortex to a less excitable state. Together, our results suggest that the LC phasic response induces gamma power increase in the PFC and is essential for mediating sensory information along an ascending noxious pathway. NEW & NOTEWORTHY Our study shows linear relationships between locus coeruleus phasic excitation and the amplitude of gamma oscillations in the prefrontal cortex. Results suggest that the locus coeruleus phasic response is essential for mediating sensory information along an ascending noxious pathway.

Catecholaminergic Neuromodulation Shapes Intrinsic MRI Functional Connectivity in the Human Brain

The brain commonly exhibits spontaneous (i.e., in the absence of a task) fluctuations in neural activity that are correlated across brain regions. It has been established that the spatial structure, or topography, of these intrinsic correlations is in part determined by the fixed anatomical connectivity between regions. However, it remains unclear which factors dynamically sculpt this topography as a function of brain state. Potential candidate factors are subcortical catecholaminergic neuromodulatory systems, such as the locus ceruleus-norepinephrine system, which send diffuse projections to most parts of the forebrain. Here, we systematically characterized the effects of endogenous central neuromodulation on correlated fluctuations during rest in the human brain. Using a double-blind placebo-controlled crossover design, we pharmacologically increased synaptic catecholamine levels by administering atomoxetine, an NE transporter blocker, and examined the effects on the strength and spatial structure of resting-state MRI functional connectivity. First, atomoxetine reduced the strength of inter-regional correlations across three levels of spatial organization, indicating that catecholamines reduce the strength of functional interactions during rest. Second, this modulatory effect on intrinsic correlations exhibited a substantial degree of spatial specificity: the decrease in functional connectivity showed an anterior-posterior gradient in the cortex, depended on the strength of baseline functional connectivity, and was strongest for connections between regions belonging to distinct resting-state networks. Thus, catecholamines reduce intrinsic correlations in a spatially heterogeneous fashion. We conclude that neuromodulation is an important factor shaping the topography of intrinsic functional connectivity.

SIGNIFICANCE STATEMENT

The human brain shows spontaneous activity that is strongly correlated across brain regions. The factors that dynamically sculpt these inter-regional correlation patterns are poorly understood. Here, we test the hypothesis that they are shaped by the catecholaminergic neuromodulators norepinephrine and dopamine. We pharmacologically increased synaptic catecholamine levels and measured the resulting changes in intrinsic fMRI functional connectivity. At odds with common understanding of catecholamine function, we found (1) overall reduced inter-regional correlations across several levels of spatial organization; and (2) a remarkable spatial specificity of this modulatory effect. Our results identify norepinephrine and dopamine as important factors shaping intrinsic functional connectivity and advance our understanding of catecholamine function in the central nervous system.

Identification of biotypes in Attention-Deficit/Hyperactivity Disorder, a report from a randomized, controlled trial

Attention-Deficit/Hyperactivity Disorder (ADHD) is a heterogeneous disorder. Current subtypes lack longitudinal stability or prognostic utility. We aimed to identify data-driven biotypes using multiple cognitive measures, then to validate these biotypes using EEG, ECG, and clinical response to atomoxetine as external validators. Study design was a double-blind, randomized, placebo-controlled crossover trial of atomoxetine including 116 subjects ages 6 through 17 with diagnosis of ADHD and 56 typically developing controls. Initial features for unsupervised machine learning included a cognitive battery with 20 measures affected in ADHD. External validators included baseline mechanistic validators (using electroencephalogram/EEG and electrocardiogram/ECG) and clinical response (ADHD Rating Scale and correlation with cognitive change). One biotype, labeled impulsive cognition, was characterized by increased errors of commission and shorter reaction time, had greater EEG slow wave (theta/delta) power and greater resting heart rate. The second biotype, labeled inattentive cognition, was characterized by longer/more variable reaction time and errors of omission, had lower EEG fast wave (beta) power, resting heart rate that did not differ from controls, and a strong correlation (r = -0.447, p < 0.001) between clinical response to atomoxetine and improvement in verbal memory immediate recall. ADHD comprises at least two biotypes that cut across current subtype criteria and that may reflect distinct arousal mechanisms. The findings provide evidence that further investigation of cognitive subtypes may be at least as fruitful as symptom checklist-based subtypes for development of biologically-based diagnostics and interventions for ADHD.

State-Dependent Decoding Algorithms Improve the Performance of a Bidirectional BMI in Anesthetized Rats

Brain-machine interfaces (BMIs) promise to improve the quality of life of patients suffering from sensory and motor disabilities by creating a direct communication channel between the brain and the external world. Yet, their performance is currently limited by the relatively small amount of information that can be decoded from neural activity recorded form the brain. We have recently proposed that such decoding performance may be improved when using state-dependent decoding algorithms that predict and discount the large component of the trial-to-trial variability of neural activity which is due to the dependence of neural responses on the network's current internal state. Here we tested this idea by using a bidirectional BMI to investigate the gain in performance arising from using a state-dependent decoding algorithm. This BMI, implemented in anesthetized rats, controlled the movement of a dynamical system using neural activity decoded from motor cortex and fed back to the brain the dynamical system's position by electrically microstimulating somatosensory cortex. We found that using state-dependent algorithms that tracked the dynamics of ongoing activity led to an increase in the amount of information extracted form neural activity by 22%, with a consequently increase in all of the indices measuring the BMI's performance in controlling the dynamical system. This suggests that state-dependent decoding algorithms may be used to enhance BMIs at moderate computational cost.

Multiple Transient Signals in Human Visual Cortex Associated with an Elementary Decision

The cerebral cortex continuously undergoes changes in its state, which are manifested in transient modulations of the cortical power spectrum. Cortical state changes also occur at full wakefulness and during rapid cognitive acts, such as perceptual decisions. Previous studies found a global modulation of beta-band (12–30 Hz) activity in human and monkey visual cortex during an elementary visual decision: reporting the appearance or disappearance of salient visual targets surrounded by a distractor. The previous studies disentangled neither the motor action associated with behavioral report nor other secondary processes, such as arousal, from perceptual decision processing per se. Here, we used magnetoencephalography in humans to pinpoint the factors underlying the beta-band modulation. We found that disappearances of a salient target were associated with beta-band suppression, and target reappearances with beta-band enhancement. This was true for both overt behavioral reports (immediate button presses) and silent counting of the perceptual events. This finding indicates that the beta-band modulation was unrelated to the execution of the motor act associated with a behavioral report of the perceptual decision. Further, changes in pupil-linked arousal, fixational eye movements, or gamma-band responses were not necessary for the beta-band modulation. Together, our results suggest that the beta-band modulation was a top-down signal associated with the process of converting graded perceptual signals into a categorical format underlying flexible behavior. This signal may have been fed back from brain regions involved in decision processing to visual cortex, thus enforcing a “decision-consistent” cortical state.

SIGNIFICANCE STATEMENT Elementary visual decisions are associated with a rapid state change in visual cortex, indexed by a modulation of neural activity in the beta-frequency range. Such decisions are also followed by other events that might affect the state of visual cortex, including the motor command associated with the report of the decision, an increase in pupil-linked arousal, fixational eye movements, and fluctuations in bottom-up sensory processing. Here, we ruled out the necessity of these events for the beta-band modulation of visual cortex. We propose that the modulation reflects a decision-related state change, which is induced by the conversion of graded perceptual signals into a categorical format underlying behavior. The resulting decision signal may be fed back to visual cortex.

Could LC-NE-Dependent Adjustment of Neural Gain Drive Functional Brain Network Reorganization?

The locus coeruleus-norepinephrine (LC-NE) system is thought to act at synaptic, cellular, microcircuit, and network levels to facilitate cognitive functions through at least two different processes, not mutually exclusive. Accordingly, as a reset signal, the LC-NE system could trigger brain network reorganizations in response to salient information in the environment and/or adjust the neural gain within its target regions to optimize behavioral responses. Here, we provide evidence of the co-occurrence of these two mechanisms at the whole-brain level, in resting-state conditions following a pharmacological stimulation of the LC-NE system. We propose that these two mechanisms are interdependent such that the LC-NE-dependent adjustment of the neural gain inferred from the clustering coefficient could drive functional brain network reorganizations through coherence in the gamma rhythm. Via the temporal dynamic of gamma-range band-limited power, the release of NE could adjust the neural gain, promoting interactions only within the neuronal populations whose amplitude envelopes are correlated, thus making it possible to reorganize neuronal ensembles, functional networks, and ultimately, behavioral responses. Thus, our proposal offers a unified framework integrating the putative influence of the LC-NE system on both local- and long-range adjustments of brain dynamics underlying behavioral flexibility.

Small-world human brain networks: Perspectives and challenges

Modelling the human brain as a complex network has provided a powerful mathematical framework to characterize the structural and functional architectures of the brain. In the past decade, the combination of non-invasive neuroimaging techniques and graph theoretical approaches enable us to map human structural and functional connectivity patterns (i.e., connectome) at the macroscopic level. One of the most influential findings is that human brain networks exhibit prominent small-world organization. Such a network architecture in the human brain facilitates efficient information segregation and integration at low wiring and energy costs, which presumably results from natural selection under the pressure of a cost-efficiency balance. Moreover, the small-world organization undergoes continuous changes during normal development and ageing and exhibits dramatic alterations in neurological and psychiatric disorders. In this review, we survey recent advances regarding the small-world architecture in human brain networks and highlight the potential implications and applications in multidisciplinary fields, including cognitive neuroscience, medicine and engineering. Finally, we highlight several challenging issues and areas for future research in this rapidly growing field.

History-dependent variability in population dynamics during evidence accumulation in cortex

We studied how the posterior parietal cortex combined new information with ongoing activity dynamics as mice accumulated evidence during a virtual-navigation task. Using new methods to analyze population activity on single trials, we found that activity transitioned rapidly between different sets of active neurons. Each event in a trial — whether an evidence cue or a behavioral choice — caused seconds-long modifications to the probabilities that govern how one activity pattern transitions to the next, forming a short-term memory. A sequence of evidence cues triggered a chain of these modifications resulting in a signal for accumulated evidence. Multiple distinguishable activity patterns were possible for the same accumulated evidence because representations of ongoing events were influenced by previous within and across trial events. Therefore, evidence accumulation need not require the explicit competition between groups of neurons, as in winner-take-all models, but could instead emerge implicitly from general dynamical properties that instantiate short-term memory.

The Dynamics of Functional Brain Networks: Integrated Network States during Cognitive Task Performance

Higher brain function relies upon the ability to flexibly integrate information across specialized communities of brain regions; however, it is unclear how this mechanism manifests over time. In this study, we used time-resolved network analysis of fMRI data to demonstrate that the human brain traverses between functional states that maximize either segregation into tight-knit communities or integration across otherwise disparate neural regions. Integrated states enable faster and more accurate performance on a cognitive task, and are associated with dilations in pupil diameter, suggesting that ascending neuromodulatory systems may govern the transition between these alternative modes of brain function. Together, our results confirm a direct link between cognitive performance and the dynamic reorganization of the network structure of the brain.

The effects of arousal on apical amplification and conscious state

Neocortical pyramidal cells can integrate two classes of input separately and use one to modulate response to the other. Their tuft dendrites are electrotonically separated from basal dendrites and soma by the apical dendrite, and apical hyperpolarization-activated currents (Ih) further isolate subthreshold integration of tuft inputs. When apical depolarization exceeds a threshold, however, it can enhance response to the basal inputs that specify the cell's selective sensitivity. This process is referred to as apical amplification (AA). We review evidence suggesting that, by regulating Ih in the apical compartments, adrenergic arousal controls the coupling between apical and somatic integration zones thus modifying cognitive capabilities closely associated with consciousness. Evidence relating AA to schizophrenia, sleep, and anesthesia is reviewed, and we assess theories that emphasize the relevance of AA to consciousness. Implications for theories of neocortical computation that emphasize context-sensitive modulation are summarized. We conclude that the findings concerning AA and its regulation by arousal offer a new perspective on states of consciousness, the function and evolution of neocortex, and psychopathology. Many issues worthy of closer examination arise.

Multiscale modeling of brain dynamics: from single neurons and networks to mathematical tools

The extreme complexity of the brain naturally requires mathematical modeling approaches on a large variety of scales; the spectrum ranges from single neuron dynamics over the behavior of groups of neurons to neuronal network activity. Thus, the connection between the microscopic scale (single neuron activity) to macroscopic behavior (emergent behavior of the collective dynamics) and vice versa is a key to understand the brain in its complexity. In this work, we attempt a review of a wide range of approaches, ranging from the modeling of single neuron dynamics to machine learning. The models include biophysical as well as data-driven phenomenological models. The discussed models include Hodgkin-Huxley, FitzHugh-Nagumo, coupled oscillators (Kuramoto oscillators, Rössler oscillators, and the Hindmarsh-Rose neuron), Integrate and Fire, networks of neurons, and neural field equations. In addition to the mathematical models, important mathematical methods in multiscale modeling and reconstruction of the causal connectivity are sketched. The methods include linear and nonlinear tools from statistics, data analysis, and time series analysis up to differential equations, dynamical systems, and bifurcation theory, including Granger causal connectivity analysis, phase synchronization connectivity analysis, principal component analysis (PCA), independent component analysis (ICA), and manifold learning algorithms such as ISOMAP, and diffusion maps and equation-free techniques. WIREs Syst Biol Med 2016, 8:438-458. doi: 10.1002/wsbm.1348 For further resources related to this article, please visit the WIREs website.

Adaptive Spike Threshold Enables Robust and Temporally Precise Neuronal Encoding

Neural processing rests on the intracellular transformation of information as synaptic inputs are translated into action potentials. This transformation is governed by the spike threshold, which depends on the history of the membrane potential on many temporal scales. While the adaptation of the threshold after spiking activity has been addressed before both theoretically and experimentally, it has only recently been demonstrated that the subthreshold membrane state also influences the effective spike threshold. The consequences for neural computation are not well understood yet. We address this question here using neural simulations and whole cell intracellular recordings in combination with information theoretic analysis. We show that an adaptive spike threshold leads to better stimulus discrimination for tight input correlations than would be achieved otherwise, independent from whether the stimulus is encoded in the rate or pattern of action potentials. The time scales of input selectivity are jointly governed by membrane and threshold dynamics. Encoding information using adaptive thresholds further ensures robust information transmission across cortical states i.e. decoding from different states is less state dependent in the adaptive threshold case, if the decoding is performed in reference to the timing of the population response. Results from in vitro neural recordings were consistent with simulations from adaptive threshold neurons. In summary, the adaptive spike threshold reduces information loss during intracellular information transfer, improves stimulus discriminability and ensures robust decoding across membrane states in a regime of highly correlated inputs, similar to those seen in sensory nuclei during the encoding of sensory information.

A neuron is a tiny computer that transforms electrical inputs into electrical outputs. While neurons have been investigated and modeled for many decades, some aspects remain elusive. Recently, it was demonstrated that the membrane (voltage) state of a neuron determines its threshold to spiking. In the present study we asked, what are the consequences of this dependence for the computation the neuron performs. We find that this so called adaptive threshold allows neurons to be more focused on inputs which arrive close in time with other inputs. Also, it allows neurons to represent their information more robustly, such that a readout of their activity is less influenced by the state the brain is in. The present use of information theory provides a solid foundation for these results. We obtained the results primarily in detailed simulations, but performed neural recordings to verify these properties in real neurons. In summary, an adaptive spiking threshold allows neurons to specifically compute robustly with a focus on tight temporal correlations in their input.