Cortical cell assemblies and their underlying connectivity: An in silico study.

Recent developments in experimental techniques have enabled simultaneous recordings from thousands of neurons, enabling the study of functional cell assemblies. However, determining the patterns of synaptic connectivity giving rise to these assemblies remains challenging. To address this, we developed a complementary, simulation-based approach, using a detailed, large-scale cortical network model. Using a combination of established methods we detected functional cell assemblies from the stimulus-evoked spiking activity of 186,665 neurons. We studied how the structure of synaptic connectivity underlies assembly composition, quantifying the effects of thalamic innervation, recurrent connectivity, and the spatial arrangement of synapses on dendrites. We determined that these features reduce up to 30%, 22%, and 10% of the uncertainty of a neuron belonging to an assembly. The detected assemblies were activated in a stimulus-specific sequence and were grouped based on their position in the sequence. We found that the different groups were affected to different degrees by the structural features we considered. Additionally, connectivity was more predictive of assembly membership if its direction aligned with the temporal order of assembly activation, if it originated from strongly interconnected populations, and if synapses clustered on dendritic branches. In summary, reversing Hebb's postulate, we showed how cells that are wired together, fire together, quantifying how connectivity patterns interact to shape the emergence of assemblies. This includes a qualitative aspect of connectivity: not just the amount, but also the local structure matters; from the subcellular level in the form of dendritic clustering to the presence of specific network motifs.

Genetic and environmental influence on resting state networks in young male and female adults: a cartographer mapping study.

We propose a unique, minimal assumption, approach based on variance analyses (compared with standard approaches) to investigate genetic influence on individual differences on the functional connectivity of the brain using 65 monozygotic and 65 dizygotic healthy young adult twin pairs' low-frequency oscillation resting state functional Magnetic Resonance Imaging (fMRI) data from the Human Connectome Project. Overall, we found high number of genetically-influenced functional (GIF) connections involving posterior to posterior brain regions (occipital/temporal/parietal) implicated in low-level processes such as vision, perception, motion, categorization, dorsal/ventral stream visuospatial, and long-term memory processes, as well as high number across midline brain regions (cingulate) implicated in attentional processes, and emotional responses to pain. We found low number of GIF connections involving anterior to anterior/posterior brain regions (frontofrontal > frontoparietal, frontotemporal, frontooccipital) implicated in high-level processes such as working memory, reasoning, emotional judgment, language, and action planning. We found very low number of GIF connections involving subcortical/noncortical networks such as basal ganglia, thalamus, brainstem, and cerebellum. In terms of sex-specific individual differences, individual differences in males were more genetically influenced while individual differences in females were more environmentally influenced in terms of the interplay of interactions of Task positive networks (brain regions involved in various task-oriented processes and attending to and interacting with environment), extended Default Mode Network (a central brain hub for various processes such as internal monitoring, rumination, and evaluation of self and others), primary sensorimotor systems (vision, audition, somatosensory, and motor systems), and subcortical/noncortical networks. There were >8.5-19.1 times more GIF connections in males than females. These preliminary (young adult cohort-specific) findings suggest that individual differences in the resting state brain may be more genetically influenced in males and more environmentally influenced in females; furthermore, standard approaches may suggest that it is more substantially nonadditive genetics, rather than additive genetics, which contribute to the differences in sex-specific individual differences based on this young adult (male and female) specific cohort. Finally, considering the preliminary cohort-specific results, based on standard approaches, environmental influences on individual differences may be substantially greater than that of genetics, for either sex, frontally and brain-wide. [Correction added on 10 May 2023, after first online publication: added: functional Magnetic Resonance Imaging. Added: individual differences in, twice. Added statement between furthermore … based on standard approaches.].

Neural dissociation of the acoustic and cognitive representation of voice identity.

Recognising a speaker's identity by the sound of their voice is important for successful interaction. The skill depends on our ability to discriminate minute variations in the acoustics of the vocal signal. Performance on voice identity assessments varies widely across the population. The neural underpinnings of this ability and its individual differences, however, remain poorly understood. Here we provide critical tests of a theoretical framework for the neural processing stages of voice identity and address how individual differences in identity discrimination mediate activation in this neural network. We scanned 40 individuals on an fMRI adaptation task involving voices drawn from morphed continua between two personally familiar identities. Analyses dissociated neuronal effects induced by repetition of acoustically similar morphs from those induced by a switch in perceived identity. Activation in temporal voice-sensitive areas decreased with acoustic similarity between consecutive stimuli. This repetition suppression effect was mediated by the performance on an independent voice assessment and this result highlights an important functional role of adaptive coding in voice expertise. Bilateral anterior insulae and medial frontal gyri responded to a switch in perceived voice identity compared to an acoustically equidistant switch within identity. Our results support a multistep model of voice identity perception.

Depressive symptoms reduce when dorsolateral prefrontal cortex-precuneus connectivity normalizes after functional connectivity neurofeedback.

Depressive disorders contribute heavily to global disease burden; This is possibly because patients are often treated homogeneously, despite having heterogeneous symptoms with differing underlying neural mechanisms. A novel treatment that can directly influence the neural circuit relevant to an individual patient's subset of symptoms might more precisely and thus effectively aid in the alleviation of their specific symptoms. We tested this hypothesis in a proof-of-concept study using fMRI functional connectivity neurofeedback. We targeted connectivity between the left dorsolateral prefrontal cortex/middle frontal gyrus and the left precuneus/posterior cingulate cortex, because this connection has been well-established as relating to a specific subset of depressive symptoms. Specifically, this connectivity has been shown in a data-driven manner to be less anticorrelated in patients with melancholic depression than in healthy controls. Furthermore, a posterior cingulate dominant state-which results in a loss of this anticorrelation-is expected to specifically relate to an increase in rumination symptoms such as brooding. In line with predictions, we found that, with neurofeedback training, the more a participant normalized this connectivity (restored the anticorrelation), the more related (depressive and brooding symptoms), but not unrelated (trait anxiety), symptoms were reduced. Because these results look promising, this paradigm next needs to be examined with a greater sample size and with better controls. Nonetheless, here we provide preliminary evidence for a correlation between the normalization of a neural network and a reduction in related symptoms. Showing their reproducibility, these results were found in two experiments that took place several years apart by different experimenters. Indicative of its potential clinical utility, effects of this treatment remained one-two months later.Clinical trial registration: Both experiments reported here were registered clinical trials (UMIN000015249, jRCTs052180169).

Cerebral cortical processing time is elongated in human brain evolution.

An increase in number of neurons is presumed to underlie the enhancement of cognitive abilities in brain evolution. The evolution of human cognition is then expected to have accompanied a prolongation of net neural-processing time due to the accumulation of processing time of individual neurons over an expanded number of neurons. Here, we confirmed this prediction and quantified the amount of prolongation in vivo, using noninvasive measurements of brain responses to sounds in unanesthetized human and nonhuman primates. Latencies of the N1 component of auditory-evoked potentials recorded from the scalp were approximately 40, 50, 60, and 100 ms for the common marmoset, rhesus monkey, chimpanzee, and human, respectively. Importantly, the prominent increase in human N1 latency could not be explained by the physical lengthening of the auditory pathway, and therefore reflected an extended dwell time for auditory cortical processing. A longer time window for auditory cortical processing is advantageous for analyzing time-varying acoustic stimuli, such as those important for speech perception. A novel hypothesis concerning human brain evolution then emerges: the increase in cortical neuronal number widened the timescale of sensory cortical processing, the benefits of which outweighed the disadvantage of slow cognition and reaction.

Dissection of brain-wide resting-state and functional somatosensory circuits by fMRI with optogenetic silencing.

To further advance functional MRI (fMRI)-based brain science, it is critical to dissect fMRI activity at the circuit level. To achieve this goal, we combined brain-wide fMRI with neuronal silencing in well-defined regions. Since focal inactivation suppresses excitatory output to downstream pathways, intact input and suppressed output circuits can be separated. Highly specific cerebral blood volume-weighted fMRI was performed with optogenetic stimulation of local GABAergic neurons in mouse somatosensory regions. Brain-wide spontaneous somatosensory networks were found mostly in ipsilateral cortical and subcortical areas, which differed from the bilateral homotopic connections commonly observed in resting-state fMRI data. The evoked fMRI responses to somatosensory stimulation in regions of the somatosensory network were successfully dissected, allowing the relative contributions of spinothalamic (ST), thalamocortical (TC), corticothalamic (CT), corticocortical (CC) inputs, and local intracortical circuits to be determined. The ventral posterior thalamic nucleus receives ST inputs, while the posterior medial thalamic nucleus receives CT inputs from the primary somatosensory cortex (S1) with TC inputs. The secondary somatosensory cortex (S2) receives mostly direct CC inputs from S1 and a few TC inputs from the ventral posterolateral nucleus. The TC and CC input layers in cortical regions were identified by laminar-specific fMRI responses with a full width at half maximum of <150 µm. Long-range synaptic inputs in cortical areas were amplified approximately twofold by local intracortical circuits, which is consistent with electrophysiological recordings. Overall, whole-brain fMRI with optogenetic inactivation revealed brain-wide, population-based, long-range circuits, which could complement data typically collected in conventional microscopic functional circuit studies.

Functional connectome of arousal and motor brainstem nuclei in living humans by 7 Tesla resting-state fMRI.

Brainstem nuclei play a pivotal role in many functions, such as arousal and motor control. Nevertheless, the connectivity of arousal and motor brainstem nuclei is understudied in living humans due to the limited sensitivity and spatial resolution of conventional imaging, and to the lack of atlases of these deep tiny regions of the brain. For a holistic comprehension of sleep, arousal and associated motor processes, we investigated in 20 healthy subjects the resting-state functional connectivity of 18 arousal and motor brainstem nuclei in living humans. To do so, we used high spatial-resolution 7 Tesla resting-state fMRI, as well as a recently developed in-vivo probabilistic atlas of these nuclei in stereotactic space. Further, we verified the translatability of our brainstem connectome approach to conventional (e.g. 3 Tesla) fMRI. Arousal brainstem nuclei displayed high interconnectivity, as well as connectivity to the thalamus, hypothalamus, basal forebrain and frontal cortex, in line with animal studies and as expected for arousal regions. Motor brainstem nuclei showed expected connectivity to the cerebellum, basal ganglia and motor cortex, as well as high interconnectivity. Comparison of 3 Tesla to 7 Tesla connectivity results indicated good translatability of our brainstem connectome approach to conventional fMRI, especially for cortical and subcortical (non-brainstem) targets and to a lesser extent for brainstem targets. The functional connectome of 18 arousal and motor brainstem nuclei with the rest of the brain might provide a better understanding of arousal, sleep and accompanying motor functions in living humans in health and disease.

Cerebello-Thalamo-Cortical Hyperconnectivity Classifies Patients and Predicts Long-Term Treatment Outcome in First-Episode Schizophrenia.

It has previously been shown that cerebello-thalamo-cortical (CTC) hyperconnectivity is likely a state-independent neural signature for psychosis. However, the potential clinical utility of this change has not yet been evaluated. Here, using fMRI and clinical data acquired from 214 untreated first-episode patients with schizophrenia (62 of whom were clinically followed-up at least once at the 12th and 24th months after treatment initiation) and 179 healthy controls, we investigated whether CTC hyperconnectivity would serve as an individualized biomarker for diagnostic classification and prediction of long-term treatment outcome. Cross-validated LASSO regression was conducted to estimate the accuracy of baseline CTC connectivity for patient-control classification, with the generalizability of classification performance tested in an independent sample including 42 untreated first-episode patients and 65 controls. Associations between baseline CTC connectivity and clinical outcomes were evaluated using linear mixed model and leave-one-out cross validation. We found significantly increased baseline CTC connectivity in patients (P = .01), which remained stable after treatment. Measures of CTC connectivity discriminated patients from controls with moderate classification accuracy (AUC = 0.68, P < .001), and the classification model had good generalizability in the independent sample (AUC = 0.70, P < .001). Higher CTC connectivity at baseline significantly predicted poorer long-term symptom reduction in negative symptoms (R = 0.31, P = .01) but not positive or general symptoms. These findings provide initial evidence for the putative "CTC hyperconnectivity" anomaly as an individualized diagnostic and prognostic biomarker for schizophrenia, and highlight the potential of this measure in precision psychiatry.

A hypothalamomedullary network for physiological responses to environmental stresses.

Various environmental stressors, such as extreme temperatures (hot and cold), pathogens, predators and insufficient food, can threaten life. Remarkable progress has recently been made in understanding the central circuit mechanisms of physiological responses to such stressors. A hypothalamomedullary neural pathway from the dorsomedial hypothalamus (DMH) to the rostral medullary raphe region (rMR) regulates sympathetic outflows to effector organs for homeostasis. Thermal and infection stress inputs to the preoptic area dynamically alter the DMH → rMR transmission to elicit thermoregulatory, febrile and cardiovascular responses. Psychological stress signalling from a ventromedial prefrontal cortical area to the DMH drives sympathetic and behavioural responses for stress coping, representing a psychosomatic connection from the corticolimbic emotion circuit to the autonomic and somatic motor systems. Under starvation stress, medullary reticular neurons activated by hunger signalling from the hypothalamus suppress thermogenic drive from the rMR for energy saving and prime mastication to promote food intake. This Perspective presents a combined neural network for environmental stress responses, providing insights into the central circuit mechanism for the integrative regulation of systemic organs.

Circadian Rhythms in the Neuronal Network Timing the Luteinizing Hormone Surge.

For billions of years before electric light was invented, life on Earth evolved under the pattern of light during the day and darkness during the night. Through evolution, nearly all organisms internalized the temporal rhythm of Earth's 24-hour rotation and evolved self-sustaining biological clocks with a ~24-hour rhythm. These internal rhythms are called circadian rhythms, and the molecular constituents that generate them are called molecular circadian clocks. Alignment of molecular clocks with the environmental light-dark rhythms optimizes physiology and behavior. This phenomenon is particularly true for reproductive function, in which seasonal breeders use day length information to time yearly changes in fertility. However, it is becoming increasingly clear that light-induced disruption of circadian rhythms can negatively impact fertility in nonseasonal breeders as well. In particular, the luteinizing hormone surge promoting ovulation is sensitive to circadian disruption. In this review, we will summarize our current understanding of the neuronal networks that underlie circadian rhythms and the luteinizing hormone surge.

Methodological aspects of studying the mechanisms of consciousness.

There are at least two approaches to the definition of consciousness. In the first case, certain aspects of consciousness, called qualia, are considered inaccessible for research from a third person and can only be described through subjective experience. This approach is inextricably linked with the so-called "hard problem of consciousness", that is, the question of why consciousness has qualia or how any physical changes in the environment can generate subjective experience. With this approach, some aspects of consciousness, by definition, cannot be explained on the basis of external observations and, therefore, are outside the scope of scientific research. In the second case, a priori constraints do not constrain the field of scientific investigation, and the best explanation of the experience in the first person is included as a possible subject of empirical research. Historically, in the study of cause-and-effect relationships in biology, it was customary to distinguish between proximate causation and ultimate causation existing in biological systems. Immediate causes are based on the immediate influencing factors [1]. Proximate causation has evolutionary explanations. When studying biological systems themselves, such an approach is undoubtedly justified, but it often seems insufficient when studying the interaction of consciousness and the brain [2,3]. Current scientific communities proceed from the assumption that the physical substrate for the generation of consciousness is a neural network that unites various types of neurons located in various brain structures. Many neuroscientists attach a key role in this process to the cortical and thalamocortical neural networks. This question is directly related to experimental and clinical research in the field of disorder of consciousness. Progress in this area of medicine depends on advances in neuroscience in this area and is also a powerful source of empirical information. In this area of consciousness research, a large amount of experimental data has been accumulated, and in this review an attempt was made to generalize and systematize.

Distinct neural-behavioral correspondence within face processing and attention networks for the composite face effect.

The composite face effect (CFE) is recognized as a hallmark for holistic face processing, but our knowledge remains sparse about its cognitive and neural loci. Using functional magnetic resonance imaging with independent localizer and complete composite face task, we here investigated its neural-behavioral correspondence within face processing and attention networks. Complementing classical comparisons, we adopted a dimensional reduction approach to explore the core cognitive constructs of the behavioral CFE measurement. Our univariate analyses found an alignment effect in regions associated with both the extended face processing network and attention networks. Further representational similarity analyses based on Euclidian distances among all experimental conditions were used to identify cortical regions with reliable neural-behavioral correspondences. Multidimensional scaling and hierarchical clustering analyses for neural-behavioral correspondence data revealed two principal components underlying the behavioral CFE effect, which fit best to the neural responses in the bilateral insula and medial frontal gyrus. These findings highlight the distinct neurocognitive contributions of both face processing and attentional networks to the behavioral CFE outcome, which bridge the gaps between face recognition and attentional control models.

Language Recovery after Brain Injury: A Structural Network Control Theory Study.

Aphasia recovery after stroke depends on the condition of the remaining, extralesional brain network. Network control theory (NCT) provides a unique, quantitative approach to assess the interaction between brain networks. In this longitudinal, large-scale, whole-brain connectome study, we evaluated whether controllability measures of language-related regions are associated with treated aphasia recovery. Using probabilistic tractography and controlling for the effects of structural lesions, we reconstructed whole-brain diffusion tensor imaging (DTI) connectomes from 68 individuals (20 female, 48 male) with chronic poststroke aphasia who completed a three-week language therapy. Applying principles of NCT, we computed regional (1) average and (2) modal controllability, which decode the ability of a region to (1) spread control input through the brain network and (2) to facilitate brain state transitions. We tested the relationship between pretreatment controllability measures of 20 language-related left hemisphere regions and improvements in naming six months after language therapy using multiple linear regressions and a parsimonious elastic net regression model with cross-validation. Regional controllability of the inferior frontal gyrus (IFG) pars opercularis, pars orbitalis, and the anterior insula were associated with treatment outcomes independently of baseline aphasia severity, lesion volume, age, education, and network size. Modal controllability of the IFG pars opercularis was the strongest predictor of treated aphasia recovery with cross-validation and outperformed traditional graph theory, lesion load, and demographic measures. Regional NCT measures can reflect the status of the residual language network and its interaction with the remaining brain network, being able to predict language recovery after aphasia treatment.SIGNIFICANCE STATEMENT Predicting and understanding language recovery after brain injury remains a challenging, albeit a fundamental aspect of human neurology and neuroscience. In this study, we applied network control theory (NCT) to fully harness the concept of brain networks as dynamic systems and to evaluate their interaction. We studied 68 stroke survivors with aphasia who underwent imaging and longitudinal behavioral assessments coupled with language therapy. We found that the controllability of the inferior frontal regional network significantly predicted recovery in language production six months after treatment. Importantly, controllability outperformed traditional demographic, lesion, and graph-theoretical measures. Our findings shed light on the neurobiological basis of human language and can be translated into personalized rehabilitation approaches.

The interplay between glutamatergic circuits and oxytocin neurons in the hypothalamus and its relevance to neurodevelopmental disorders.

Oxytocin (OXT) neurons of the hypothalamus are at the center of several physiological functions, including milk ejection, uterus contraction, and maternal and social behavior. In lactating females, OXT neurons show a pattern of burst firing and inter-neuron synchronization during suckling that leads to pulsatile release of surges of OXT into the bloodstream to stimulate milk ejection. This pattern of firing and population synchronization may be facilitated in part by hypothalamic glutamatergic circuits, as has been observed in vitro using brain slices obtained from male rats and neonates. However, it remains unknown how hypothalamic glutamatergic circuits influence OXT cell activity outside the context of lactation. In this review, we summarize the in vivo and in vitro studies that describe the synchronized burst firing pattern of OXT neurons and the implication of hypothalamic glutamate in this pattern of firing. We also make note of the few studies that have traced glutamatergic afferents to the hypothalamic paraventricular and supraoptic nuclei. Finally, we discuss the genetic findings implicating several glutamatergic genes in neurodevelopmental disorders, including autism spectrum disorder, thus underscoring the need for future studies to investigate the impact of these mutations on hypothalamic glutamatergic circuits and the OXT system.

Inducing neuroplasticity through intracranial θ-burst stimulation in the human sensorimotor cortex.

The progress of therapeutic neuromodulation greatly depends on improving stimulation parameters to most efficiently induce neuroplasticity effects. Intermittent θ-burst stimulation (iTBS), a form of electrical stimulation that mimics natural brain activity patterns, has proved to efficiently induce such effects in animal studies and rhythmic transcranial magnetic stimulation studies in humans. However, little is known about the potential neuroplasticity effects of iTBS applied through intracranial electrodes in humans. This study characterizes the physiological effects of intracranial iTBS in humans and compare them with α-frequency stimulation, another frequently used neuromodulatory pattern. We applied these two stimulation patterns to well-defined regions in the sensorimotor cortex, which elicited contralateral hand muscle contractions during clinical mapping, in patients with epilepsy implanted with intracranial electrodes. Treatment effects were evaluated using oscillatory coherence across areas connected to the treatment site, as defined with corticocortical-evoked potentials. Our results show that iTBS increases coherence in the ß-frequency band within the sensorimotor network indicating a potential neuroplasticity effect. The effect is specific to the sensorimotor system, the ß band, and the stimulation pattern and outlasted the stimulation period by ∼3 min. The effect occurred in four out of seven subjects depending on the buildup of the effect during iTBS treatment and other patterns of oscillatory activity related to ceiling effects within the ß band and to preexistent coherence within the α band. By characterizing the neurophysiological effects of iTBS within well-defined cortical networks, we hope to provide an electrophysiological framework that allows clinicians/researchers to optimize brain stimulation protocols which may have translational value.NEW & NOTEWORTHY θ-Burst stimulation (TBS) protocols in transcranial magnetic stimulation studies have shown improved treatment efficacy in a variety of neuropsychiatric disorders. The optimal protocol to induce neuroplasticity in invasive direct electrical stimulation approaches is not known. We report that intracranial TBS applied in human sensorimotor cortex increases local coherence of preexistent ß rhythms. The effect is specific to the stimulation frequency and the stimulated network and outlasts the stimulation period by ∼3 min.

Neuropsychological evidence of multi-domain network hubs in the human thalamus.

Hubs in the human brain support behaviors that arise from brain network interactions. Previous studies have identified hub regions in the human thalamus that are connected with multiple functional networks. However, the behavioral significance of thalamic hubs has yet to be established. Our framework predicts that thalamic subregions with strong hub properties are broadly involved in functions across multiple cognitive domains. To test this prediction, we studied human patients with focal thalamic lesions in conjunction with network analyses of the human thalamocortical functional connectome. In support of our prediction, lesions to thalamic subregions with stronger hub properties were associated with widespread deficits in executive, language, and memory functions, whereas lesions to thalamic subregions with weaker hub properties were associated with more limited deficits. These results highlight how a large-scale network model can broaden our understanding of thalamic function for human cognition.

Regulatory Mechanism for Absence Seizures in Bidirectional Interactive Thalamocortical Model via Different Targeted Therapy Schemes.

Recent clinical practice has found that the spike-wave discharge (SWD) scopes of absence seizures change from small cortical region to large thalamocortical networks, which has also been proved by theoretical simulation. The best biophysics explanation is that there are interactions between coupled cortico-thalamic and thalamocortical circuits. To agree with experiment results and describe the phenomena better, we constructed a coupled thalamocortical model with bidirectional channel (CTMBC) to account for the causes of absence seizures which are connected by the principle of two-way communication of neural pathways. By adjusting the coupling strength of bidirectional pathways, the spike-wave discharges are reproduced. Regulatory mechanism for absence seizures is further applied to CTMBC via four different targeted therapy schemes, such as deep brain stimulation (DBS), charge-balanced biphasic pulse (CBBP), coordinated reset stimulation (CRS) 1 : 0, and (CRS) 3 : 2. The new CTMBC model shows that neurodiversity in bidirectional interactive channel could supply theory reference for the bidirectional communication mode of thalamocortical networks and the hypothesis validation of pathogenesis.

Protocol for targeting the magnocellular neuroendocrine cell ensemble via retrograde tracing from the posterior pituitary.

The hypothalamic magnocellular neuroendocrine cells (MNCs) project to the posterior pituitary (PPi), regulating reproduction and fluid homeostasis. It has been challenging to selectively label and manipulate MNCs, as they are intermingled with parvocellular neuroendocrine cells projecting to the median eminence. Here, we provide a step-by-step protocol for specifically targeting the MNCs by infusing retrograde viral tracers into the PPi. When combined with optogenetics, chemogenetics, and transgenic animals, this approach allows cell-type-specific manipulation of MNCs in multiple sites for functional dissection. For complete details on the use and execution of this protocol, please refer to Zhang et al. (2021) and Tang et al. (2020).

Increased Functional Connectivity of the Intraparietal Sulcus Underlies the Attenuation of Numerosity Estimations for Self-Generated Words.

Previous studies have shown that self-generated stimuli in auditory, visual, and somatosensory domains are attenuated, producing decreased behavioral and neural responses compared with the same stimuli that are externally generated. Yet, whether such attenuation also occurs for higher-level cognitive functions beyond sensorimotor processing remains unknown. In this study, we assessed whether cognitive functions such as numerosity estimations are subject to attenuation in 56 healthy participants (32 women). We designed a task allowing the controlled comparison of numerosity estimations for self-generated (active condition) and externally generated (passive condition) words. Our behavioral results showed a larger underestimation of self-generated compared with externally generated words, suggesting that numerosity estimations for self-generated words are attenuated. Moreover, the linear relationship between the reported and actual number of words was stronger for self-generated words, although the ability to track errors about numerosity estimations was similar across conditions. Neuroimaging results revealed that numerosity underestimation involved increased functional connectivity between the right intraparietal sulcus and an extended network (bilateral supplementary motor area, left inferior parietal lobule, and left superior temporal gyrus) when estimating the number of self-generated versus externally generated words. We interpret our results in light of two models of attenuation and discuss their perceptual versus cognitive origins.SIGNIFICANCE STATEMENT We perceive sensory events as less intense when they are self-generated compared with when they are externally generated. This phenomenon, called attenuation, enables us to distinguish sensory events from self and external origins. Here, we designed a novel fMRI paradigm to assess whether cognitive processes such as numerosity estimations are also subject to attenuation. When asking participants to estimate the number of words they had generated or passively heard, we found bigger underestimation in the former case, providing behavioral evidence of attenuation. Attenuation was associated with increased functional connectivity of the intraparietal sulcus, a region involved in numerosity processing. Together, our results indicate that the attenuation of self-generated stimuli is not limited to sensory consequences but is also impact cognitive processes such as numerosity estimations.

Central 5-HTR2C in the Control of Metabolic Homeostasis.

The 5-hydroxytryptamine 2C receptor (5-HTR2C) is a class G protein-coupled receptor (GPCR) enriched in the hypothalamus and the brain stem, where it has been shown to regulate energy homeostasis, including feeding and glucose metabolism. Accordingly, 5-HTR2C has been the target of several anti-obesity drugs, though the associated side effects greatly curbed their clinical applications. Dissecting the specific neural circuits of 5-HTR2C-expressing neurons and the detailed molecular pathways of 5-HTR2C signaling in metabolic regulation will help to develop better therapeutic strategies towards metabolic disorders. In this review, we introduced the regulatory role of 5-HTR2C in feeding behavior and glucose metabolism, with particular focus on the molecular pathways, neural network, and its interaction with other metabolic hormones, such as leptin, ghrelin, insulin, and estrogens. Moreover, the latest progress in the clinical research on 5-HTR2C agonists was also discussed.