Thalamic amplification of cortical connectivity sustains attentional control

Specific connectivity optimizes learning in thalamocortical loops

Thalamocortical loops have a central role in cognition and motor control, but precisely how they contribute to these processes is unclear. Recent studies showing evidence of plasticity in thalamocortical synapses indicate a role for the thalamus in shaping cortical dynamics through learning. Since signals undergo a compression from the cortex to the thalamus, we hypothesized that the computational role of the thalamus depends critically on the structure of corticothalamic connectivity. To test this, we identified the optimal corticothalamic structure that promotes biologically plausible learning in thalamocortical synapses. We found that corticothalamic projections specialized to communicate an efference copy of the cortical output benefit motor control, while communicating the modes of highest variance is optimal for working memory tasks. We analyzed neural recordings from mice performing grasping and delayed discrimination tasks and found corticothalamic communication consistent with these predictions. These results suggest that the thalamus orchestrates cortical dynamics in a functionally precise manner through structured connectivity.

Not Just a Mood Disorder─Is Depression a Neurodevelopmental, Cognitive Disorder? Focus on Prefronto-Thalamic Circuits

Depression is one of the most burdensome psychiatric disorders, affecting hundreds of millions of people worldwide. The disease is characterized not only by severe emotional and affective impairments, but also by disturbed vegetative and cognitive functions. Although many candidate mechanisms have been proposed to cause the disease, the pathophysiology of cognitive impairments in depression remains unclear. In this article, we aim to assess the link between cognitive alterations in depression and possible developmental changes in neuronal circuit wiring during critical periods of susceptibility. We review the existing literature and propose a role of serotonin signaling during development in shaping the functional states of prefrontal neuronal circuits and prefronto-thalamic loops. We discuss how early life insults affecting the serotonergic system could be important in the alterations of these local and long-range circuits, thus favoring the emergence of neurodevelopmental disorders, such as depression.

Atypical co-development of the thalamus and cortex in autism: Evidence from age-related white-gray contrast change

Recent studies have shown that white-gray contrast (WGC) of either cortical or subcortical gray matter provides for accurate predictions of age in typically developing (TD) children, and that, at least for the cortex, it changes differently with age in subjects with autism spectrum disorder (ASD) compared to their TD peers. Our previous study showed different patterns of contrast change between ASD and TD in sensorimotor and association cortices. While that study was confined to the cortex, we hypothesized that subcortical structures, particularly the thalamus, were involved in the observed cortical dichotomy between lower and higher processing. The current paper investigates that hypothesis using the WGC measures from the thalamus in addition to those from the cortex. We compared age-related WGC changes in the thalamus to those in the cortex. To capture the simultaneity of this change across the two structures, we devised a metric capturing the co-development of the thalamus and cortex (CoDevTC), proportional to the magnitude of cortical and thalamic age-related WGC change. We calculated this metric for each of the subjects in a large homogeneous sample taken from the Autism Brain Imaging Data Exchange (ABIDE) (N = 434). We used structural MRI data from the largest high-quality cross-sectional sample (NYU) as well as two other large high-quality sites, GU and OHSU, all three using Siemens 3T scanners. We observed that the co-development features in ASD and TD exhibit contrasting patterns; specifically, some higher-order thalamic nuclei, such as the lateral dorsal nucleus, exhibited reduction in codevelopment with most of the cortex in ASD compared to TD. Moreover, this difference in the CoDevTC pattern correlates with a number of behavioral measures across multiple cognitive and physiological domains. The results support previous notions of altered connectivity in autism, but add more specific evidence about the heterogeneity in thalamocortical development that elucidates the mechanisms underlying the clinical features of ASD.

Independent inhibitory control mechanisms for aggressive motivation and action

Social behaviors often consist of a motivational phase followed by action. Here we show that neurons in the ventromedial hypothalamus ventrolateral area (VMHvl) of mice encode the temporal sequence of aggressive motivation to action. The VMHvl receives local inhibitory input (VMHvl shell) and long-range input from the medial preoptic area (MPO) with functional coupling to neurons with specific temporal profiles. Encoding models reveal that during aggression, VMHvl shellvgat+ activity peaks at the start of an attack, whereas activity from the MPO-VMHvlvgat+ input peaks at specific interaction endpoints. Activation of the MPO-VMHvlvgat+ input promotes and prolongs a low motivation state, whereas activation of VMHvl shellvgat+ results in action-related deficits, acutely terminating attack. Moreover, stimulation of MPO-VMHvlvgat+ input is positively valenced and anxiolytic. Together, these data demonstrate how distinct inhibitory inputs to the hypothalamus can independently gate the motivational and action phases of aggression through a single locus of control.

Parvalbumin interneuron deficiency in the prefrontal and motor cortices of spontaneously hypertensive rats: an attention-deficit hyperactivity disorder animal model insight

Background

Attention deficit hyperactivity disorder (ADHD) is characterized by impairments in developmental-behavioral inhibition, resulting in impulsivity and hyperactivity. Recent research has underscored cortical inhibition deficiencies in ADHD via the gamma-aminobutyric acid (GABA)ergic system, which is crucial for maintaining excitatory-inhibitory balance in the brain. This study explored postnatal changes in parvalbumin (PV) immunoreactivity, indicating GABAergic interneuron types, in the prefrontal (PFC) and motor (MC) cortices of spontaneously hypertensive rats (SHRs), an ADHD animal model.

Methods

Examining PV- positive (PV+) cells associated with dopamine D2 receptors (D2) and the impact of dopamine on GABA synthesis, we also investigated changes in the immunoreactivity of D2 and tyrosine hydroxylase (TH). Brain sections from 4- to 10-week-old SHRs and Wistar Kyoto rats (WKYs) were immunohistochemically analyzed, comparing PV+, D2+ cells, and TH+ fiber densities across age-matched SHRs and WKYs in specific PFC/MC regions.

Results

The results revealed significantly reduced PV+ cell density in SHRs: prelimbic (~20% less), anterior cingulate (~15% less), primary (~15% less), and secondary motor (~17% less) cortices. PV+ deficits coincided with the upregulation of D2 in prepubertal SHRs and the downregulation of TH predominantly in pubertal/postpubertal SHRs.

Conclusion

Reduced PV+ cells in various PFC regions could contribute to inattention/behavioral alterations in ADHD, while MC deficits could manifest as motor hyperactivity. D2 upregulation and TH deficits may impact GABA synthesis, exacerbating behavioral deficits in ADHD. These findings not only shed new light on ADHD pathophysiology but also pave the way for future research endeavors.

Transgenic tools targeting the basal ganglia reveal both evolutionary conservation and specialization of neural circuits in zebrafish

The cortico-basal ganglia circuit mediates decision making. Here, we generated transgenic tools for adult zebrafish targeting specific subpopulations of the components of this circuit and utilized them to identify evolutionary homologs of the mammalian direct- and indirect-pathway striatal neurons, which respectively project to the homologs of the internal and external segment of the globus pallidus (dorsal entopeduncular nucleus [dEN] and lateral nucleus of the ventral telencephalic area [Vl]) as in mammals. Unlike in mammals, the Vl mainly projects to the dEN directly, not by way of the subthalamic nucleus. Further single-cell RNA sequencing analysis reveals two pallidal output pathways: a major shortcut pathway directly connecting the dEN with the pallium and the evolutionarily conserved closed loop by way of the thalamus. Our resources and circuit map provide the common basis for the functional study of the basal ganglia in a small and optically tractable zebrafish brain for the comprehensive mechanistic understanding of the cortico-basal ganglia circuit.

The mediodorsal thalamus in executive control

Executive control, the ability to organize thoughts and action plans in real time, is a defining feature of higher cognition. Classical theories have emphasized cortical contributions to this process, but recent studies have reinvigorated interest in the role of the thalamus. Although it is well established that local thalamic damage diminishes cognitive capacity, such observations have been difficult to inform functional models. Recent progress in experimental techniques is beginning to enrich our understanding of the anatomical, physiological, and computational substrates underlying thalamic engagement in executive control. In this review, we discuss this progress and particularly focus on the mediodorsal thalamus, which regulates the activity within and across frontal cortical areas. We end with a synthesis that highlights frontal thalamocortical interactions in cognitive computations and discusses its functional implications in normal and pathological conditions.

A Thalamocortical Perspective on Sleep Spindle Alterations in Neurodevelopmental Disorders

Purpose of Review

Neurodevelopmental disorders are a group of conditions that affect the development and function of the nervous system, typically arising early in life. These disorders can have various genetic, environmental, and/or neural underpinnings, which can impact the thalamocortical system. Sleep spindles, brief bursts of oscillatory activity that occur during NREM sleep, provide a unique in vivo measure of the thalamocortical system. In this manuscript, we review the development of the thalamocortical system and sleep spindles in rodent models and humans. We then utilize this as a foundation to discuss alterations in sleep spindle activity in four of the most pervasive neurodevelopmental disorders-intellectual disability, attention deficit hyperactivity disorder, autism, and schizophrenia.

Recent Findings

Recent work in humans has shown alterations in sleep spindles across several neurodevelopmental disorders. Simultaneously, rodent models have elucidated the mechanisms which may underlie these deficits in spindle activity. This review merges recent findings from these two separate lines of research to draw conclusions about the pathogenesis of neurodevelopmental disorders.

Summary

We speculate that deficits in the thalamocortical system associated with neurodevelopmental disorders are exquisitely reflected in sleep spindle activity. We propose that sleep spindles may represent a promising biomarker for drug discovery, risk stratification, and treatment monitoring.

Rule-based modulation of a sensorimotor transformation across cortical areas

Flexible responses to sensory stimuli based on changing rules are critical for adapting to a dynamic environment. However, it remains unclear how the brain encodes rule information and uses this information to guide behavioral responses to sensory stimuli. Here, we made single-unit recordings while head-fixed mice performed a cross-modal sensory selection task in which they switched between two rules in different blocks of trials: licking in response to tactile stimuli applied to a whisker while rejecting visual stimuli, or licking to visual stimuli while rejecting the tactile stimuli. Along a cortical sensorimotor processing stream including the primary (S1) and secondary (S2) somatosensory areas, and the medial (MM) and anterolateral (ALM) motor areas, the single-trial activity of individual neurons distinguished between the two rules both prior to and in response to the tactile stimulus. Variable rule-dependent responses to identical stimuli could in principle occur via appropriate configuration of pre-stimulus preparatory states of a neural population, which would shape the subsequent response. We hypothesized that neural populations in S1, S2, MM and ALM would show preparatory activity states that were set in a rule-dependent manner to cause processing of sensory information according to the current rule. This hypothesis was supported for the motor cortical areas by findings that (1) the current task rule could be decoded from pre-stimulus population activity in ALM and MM; (2) neural subspaces containing the population activity differed between the two rules; and (3) optogenetic disruption of pre-stimulus states within ALM and MM impaired task performance. Our findings indicate that flexible selection of an appropriate action in response to a sensory input can occur via configuration of preparatory states in the motor cortex.

Prefrontal projections modulate recurrent circuitry in the insular cortex to support short-term memory

Short-term memory (STM) maintains information during a short delay period. How long-range and local connections interact to support STM encoding remains elusive. Here, we tackle the problem focusing on long-range projections from the medial prefrontal cortex (mPFC) to the anterior agranular insular cortex (aAIC) in head-fixed mice performing an olfactory delayed-response task. Optogenetic and electrophysiological experiments reveal the behavioral importance of the two regions in encoding STM information. Spike-correlogram analysis reveals strong local and cross-region functional coupling (FC) between memory neurons encoding the same information. Optogenetic suppression of mPFC-aAIC projections during the delay period reduces behavioral performance, the proportion of memory neurons, and memory-specific FC within the aAIC, whereas optogenetic excitation enhances all of them. mPFC-aAIC projections also bidirectionally modulate the efficacy of STM-information transfer, measured by the contribution of FC spiking pairs to the memory-coding ability of following neurons. Thus, prefrontal projections modulate insular neurons' functional connectivity and memory-coding ability to support STM.

Enhancement of mediodorsal thalamus rescues aberrant belief dynamics in a mouse model with schizophrenia-associated mutation

Optimizing behavioral strategy requires belief updating based on new evidence, a process that engages higher cognition. In schizophrenia, aberrant belief dynamics may lead to psychosis, but the mechanisms underlying this process are unknown, in part, due to lack of appropriate animal models and behavior readouts. Here, we address this challenge by taking two synergistic approaches. First, we generate a mouse model bearing patient-derived point mutation in Grin2a (Grin2aY700X+/-), a gene that confers high-risk for schizophrenia and recently identified by large-scale exome sequencing. Second, we develop a computationally trackable foraging task, in which mice form and update belief-driven strategies in a dynamic environment. We found that Grin2aY700X+/- mice perform less optimally than their wild-type (WT) littermates, showing unstable behavioral states and a slower belief update rate. Using functional ultrasound imaging, we identified the mediodorsal (MD) thalamus as hypofunctional in Grin2aY700X+/- mice, and in vivo task recordings showed that MD neurons encoded dynamic values and behavioral states in WT mice. Optogenetic inhibition of MD neurons in WT mice phenocopied Grin2aY700X+/- mice, and enhancing MD activity rescued task deficits in Grin2aY700X+/- mice. Together, our study identifies the MD thalamus as a key node for schizophrenia-relevant cognitive dysfunction, and a potential target for future therapeutics.

The Associative Thalamus: A Switchboard for Cortical Operations and a Promising Target for Schizophrenia

Schizophrenia is a brain disorder that profoundly perturbs cognitive processing. Despite the success in treating many of its symptoms, the field lacks effective methods to measure and address its impact on reasoning, inference, and decision making. Prefrontal cortical abnormalities have been well documented in schizophrenia, but additional dysfunction in the interactions between the prefrontal cortex and thalamus have recently been described. This dysfunction may be interpreted in light of parallel advances in neural circuit research based on nonhuman animals, which show critical thalamic roles in maintaining and switching prefrontal activity patterns in various cognitive tasks. Here, we review this basic literature and connect it to emerging innovations in clinical research. We highlight the value of focusing on associative thalamic structures not only to better understand the very nature of cognitive processing but also to leverage these circuits for diagnostic and therapeutic development in schizophrenia. We suggest that the time is right for building close bridges between basic thalamic research and its clinical translation, particularly in the domain of cognition and schizophrenia.

Electrophysiological correlates of attention in the locus coeruleus-prelimbic cortex circuit during the rodent continuous performance test

Sustained attention, the ability to focus on an activity or stimulus over time, is significantly impaired in many psychiatric disorders, and there remains a major unmet need in treating impaired attention. Continuous performance tests (CPTs) were developed to measure sustained attention in humans, non-human primates, rats, and mice, and similar neural circuits are engaged across species during CPT performance, supporting their use in translational studies to identify novel therapeutics. Here, we identified electrophysiological correlates of attentional performance in a touchscreen-based rodent CPT (rCPT) in the locus coeruleus (LC) and prelimbic cortex (PrL), two inter-connected regions that are implicated in attentional processes. We used viral labeling and molecular techniques to demonstrate that neural activity is recruited in LC-PrL projections during the rCPT, and that this recruitment increases with cognitive demand. We implanted male mice with depth electrodes within the LC and PrL for local field potential (LFP) recordings during rCPT training, and identified an increase in PrL delta and theta power, and an increase in LC delta power during correct responses in the rCPT. We also found that the LC leads the PrL in theta frequencies during correct responses while the PrL leads the LC in gamma frequencies during incorrect responses. These findings may represent translational biomarkers that can be used to screen novel therapeutics for drug discovery in attention.

The role of the thalamus in modular functional networks in temporal lobe epilepsy with cognitive impairment

OBJECTIVE

Cognitive deficit is common in patients with temporal lobe epilepsy (TLE). Here, we aimed to investigate the modular architecture of functional networks associated with distinct cognitive states in TLE patients together with the role of the thalamus in modular networks.

METHODS

Resting-state functional magnetic resonance imaging scans were acquired from 53 TLE patients and 37 matched healthy controls. All patients received the Montreal Cognitive Assessment test and accordingly were divided into TLE patients with normal cognition (TLE-CN, n = 35) and TLE patients with cognitive impairment (TLE-CI, n = 18) groups. The modular properties of functional networks were calculated and compared including global modularity Q, modular segregation index, intramodular connections, and intermodular connections. Thalamic subdivisions corresponding to the modular networks were generated by applying a 'winner-take-all' strategy before analyzing the modular properties (participation coefficient and within-module degree z-score) of each thalamic subdivision to assess the contribution of the thalamus to modular functional networks. Relationships between network properties and cognitive performance were then further explored.

RESULTS

Both TLE-CN and TLE-CI patients showed lower global modularity, as well as lower modular segregation index values for the ventral attention network and the default mode network. However, different patterns of intramodular and intermodular connections existed for different cognitive states. In addition, both TLE-CN and TLE-CI patients exhibited anomalous modular properties of functional thalamic subdivisions, with TLE-CI patients presenting a broader range of abnormalities. Cognitive performance in TLE-CI patients was not related to the modular properties of functional network but rather to the modular properties of functional thalamic subdivisions.

CONCLUSIONS

The thalamus plays a prominent role in modular networks and potentially represents a key neural mechanism underlying cognitive impairment in TLE.

Propofol-mediated Unconsciousness Disrupts Progression of Sensory Signals through the Cortical Hierarchy

A critical component of anesthesia is the loss of sensory perception. Propofol is the most widely used drug for general anesthesia, but the neural mechanisms of how and when it disrupts sensory processing are not fully understood. We analyzed local field potential and spiking recorded from Utah arrays in auditory cortex, associative cortex, and cognitive cortex of nonhuman primates before and during propofol-mediated unconsciousness. Sensory stimuli elicited robust and decodable stimulus responses and triggered periods of stimulus-related synchronization between brain areas in the local field potential of Awake animals. By contrast, propofol-mediated unconsciousness eliminated stimulus-related synchrony and drastically weakened stimulus responses and information in all brain areas except for auditory cortex, where responses and information persisted. However, we found stimuli occurring during spiking Up states triggered weaker spiking responses than in Awake animals in auditory cortex, and little or no spiking responses in higher order areas. These results suggest that propofol's effect on sensory processing is not just because of asynchronous Down states. Rather, both Down states and Up states reflect disrupted dynamics.

White matter tracts and executive functions: a review of causal and correlation evidence

Executive functions are high-level cognitive processes involving abilities such as working memory/updating, set-shifting and inhibition. These complex cognitive functions are enabled by interactions among widely distributed cognitive networks, supported by white matter tracts. Executive impairment is frequent in neurological conditions affecting white matter; however, whether specific tracts are crucial for normal executive functions is unclear. We review causal and correlation evidence from studies that used direct electrical stimulation during awake surgery for gliomas, voxel-based and tract-based lesion-symptom mapping, and diffusion tensor imaging to explore associations between the integrity of white matter tracts and executive functions in healthy and impaired adults. The corpus callosum was consistently associated with all executive processes, notably its anterior segments. Both causal and correlation evidence showed prominent support of the superior longitudinal fasciculus to executive functions, notably to working memory. More specifically, strong evidence suggested that the second branch of the superior longitudinal fasciculus is crucial for all executive functions, especially for flexibility. Global results showed left lateralization for verbal tasks and right lateralization for executive tasks with visual demands. The frontal aslant tract potentially supports executive functions, however, additional evidence is needed to clarify whether its involvement in executive tasks goes beyond the control of language. Converging evidence indicates that a right-lateralized network of tracts connecting cortical and subcortical grey matter regions supports the performance of tasks assessing response inhibition, some suggesting a role for the right anterior thalamic radiation. Finally, correlation evidence suggests a role for the cingulum bundle in executive functions, especially in tasks assessing inhibition. We discuss these findings in light of current knowledge about the functional role of these tracts, descriptions of the brain networks supporting executive functions and clinical implications for individuals with brain tumours.

Efficient mapping of the thalamocortical monosynaptic connectivity in vivo by tangential insertions of high-density electrodes in the cortex

The thalamus provides the principal input to the cortex and therefore understanding the mechanisms underlying cortical integration of sensory inputs requires to characterize the thalamocortical connectivity in behaving animals. Here, we propose tangential insertions of high-density electrodes into mouse cortical layer 4 as a method to capture the activity of thalamocortical axons simultaneously with their synaptically connected cortical neurons. This technique can reliably monitor multiple parallel thalamic synaptic inputs to cortical neurons, providing an efficient approach to map thalamocortical connectivity in both awake and anesthetized mice.

Cell type-specific connectome predicts distributed working memory activity in the mouse brain

Recent advances in connectomics and neurophysiology make it possible to probe whole-brain mechanisms of cognition and behavior. We developed a large-scale model of the multiregional mouse brain for a cardinal cognitive function called working memory, the brain's ability to internally hold and process information without sensory input. The model is built on mesoscopic connectome data for interareal cortical connections and endowed with a macroscopic gradient of measured parvalbumin-expressing interneuron density. We found that working memory coding is distributed yet exhibits modularity; the spatial pattern of mnemonic representation is determined by long-range cell type-specific targeting and density of cell classes. Cell type-specific graph measures predict the activity patterns and a core subnetwork for memory maintenance. The model shows numerous attractor states, which are self-sustained internal states (each engaging a distinct subset of areas). This work provides a framework to interpret large-scale recordings of brain activity during cognition, while highlighting the need for cell type-specific connectomics.

The role of the mediodorsal thalamus in chemosensory preference and consummatory behavior in rats

Experience plays a pivotal role in determining our food preferences. Consuming food generates odor-taste associations that shape our perceptual judgements of chemosensory stimuli, such as their intensity, familiarity, and pleasantness. The process of making consummatory choices relies on a network of brain regions to integrate and process chemosensory information. The mediodorsal thalamus is a higher-order thalamic nucleus involved in many experience-dependent chemosensory behaviors, including olfactory attention, odor discrimination, and the hedonic perception of flavors. Recent research has shown that neurons in the mediodorsal thalamus represent the sensory and affective properties of experienced odors, tastes, and odor-taste mixtures. However, its role in guiding consummatory choices remains unclear. To investigate the influence of the mediodorsal thalamus in the consummatory choice for experienced odors, tastes, and odor-taste mixtures, we pharmacologically inactivated the mediodorsal thalamus during 2-bottle brief-access tasks. We found that inactivation altered the preference for specific odor-taste mixtures, significantly reduced consumption of the preferred taste and increased within-trial sampling of both chemosensory stimulus options. Our results show that the mediodorsal thalamus plays a crucial role in consummatory decisions related to chemosensory preference and attention.

Functional Connectivity Biomarkers in Schizophrenia

Schizophrenia is a debilitating neuropsychiatric disorder that affects approximately 1% of the population and poses a major public health problem. Despite over 100 years of study, the treatment for schizophrenia remains limited, partially due to the lack of knowledge about the neural mechanisms of the illness and how they relate to symptoms. The US Food and Drug Administration (FDA) and the National Institute of Health (NIH) have provided seven biomarker categories that indicate causes, risks, and treatment responses. However, no FDA-approved biomarkers exist for psychiatric conditions, including schizophrenia, highlighting the need for biomarker development. Over three decades, magnetic resonance imaging (MRI)-based studies have identified patterns of abnormal brain function in schizophrenia. By using functional connectivity (FC) data, which gauges how brain regions interact over time, these studies have differentiated patient subgroups, predicted responses to antipsychotic medication, and correlated neural changes with symptoms. This suggests FC metrics could serve as promising biomarkers. Here, we present a selective review of studies leveraging MRI-derived FC to study neural alterations in schizophrenia, discuss how they align with FDA-NIH biomarkers, and outline the challenges and goals for developing FC biomarkers in schizophrenia.

Perceived and Experienced Anti-Chinese Discrimination and Its Associated Psychological Impacts Among Chinese Canadians During the Wave 2 of the COVID-19 Pandemic

The current study examined the sociodemographic factors associated with perceived and experienced anti-Chinese discrimination and discrimination as a predictor of psychological distress and loneliness among Chinese Canadians. A cross-sectional online survey was conducted in early 2021 with a sample of 899 Chinese Canadians (i.e., immigrants, citizens, visitors, and international students) during the Wave 2 of the COVID-19 pandemic. Overall, anti-Chinese discrimination was generally associated with younger age and poor financial or health status. Christianity/Catholicism believers were less likely to report perceived discrimination, whereas being married/partnered and living with family reduced the incidences of experienced discrimination. Most importantly, hierarchical linear regression models showed that both perceived and experienced discrimination predicted higher psychological distress (βs = 4.90-7.57, ps ≤ .001) and loneliness (βs = .89-1.73, ps ≤ .003), before and after controlling for all related sociodemographic covariates. Additionally, older age, higher education, better financial or health status could all buffer psychological distress, whereas living with family or in a house and better financial or health status could mitigate feeling of loneliness. The results suggested that discrimination has a robust detrimental impact on mental health conditions among Chinese Canadians.

How deep is the brain? The shallow brain hypothesis

Deep learning and predictive coding architectures commonly assume that inference in neural networks is hierarchical. However, largely neglected in deep learning and predictive coding architectures is the neurobiological evidence that all hierarchical cortical areas, higher or lower, project to and receive signals directly from subcortical areas. Given these neuroanatomical facts, today's dominance of cortico-centric, hierarchical architectures in deep learning and predictive coding networks is highly questionable; such architectures are likely to be missing essential computational principles the brain uses. In this Perspective, we present the shallow brain hypothesis: hierarchical cortical processing is integrated with a massively parallel process to which subcortical areas substantially contribute. This shallow architecture exploits the computational capacity of cortical microcircuits and thalamo-cortical loops that are not included in typical hierarchical deep learning and predictive coding networks. We argue that the shallow brain architecture provides several critical benefits over deep hierarchical structures and a more complete depiction of how mammalian brains achieve fast and flexible computational capabilities.

The bidirectional effects between cognitive ability and brain morphology: A life course Mendelian randomization analysis

Introduction

Little is understood about the dynamic interplay between brain morphology and cognitive ability across the life course. Additionally, most existing research has focused on global morphology measures such as estimated total intracranial volume, mean thickness, and total surface area.

Methods

Mendelian randomization was used to estimate the bidirectional effects between cognitive ability, global and regional measures of cortical thickness and surface area, estimated total intracranial volume, total white matter, and the volume of subcortical structures (N=37,864). Analyses were stratified for developmental periods (childhood, early adulthood, mid-to-late adulthood; age range: 8-81 years).

Results

The earliest effects were observed in childhood and early adulthood in the frontoparietal lobes. A bidirectional relationship was identified between higher cognitive ability, larger estimated total intracranial volume (childhood, mid-to-late adulthood) and total surface area (all life stages). A thicker posterior cingulate cortex and a larger surface area in the caudal middle frontal cortex and temporal pole were associated with greater cognitive ability. Contrary, a thicker temporal pole was associated with lower cognitive ability.

Discussion

Stable effects of cognitive ability on brain morphology across the life course suggests that childhood is potentially an important window for intervention.

Modulation of prefrontal couplings by prior belief-related responses in ventromedial prefrontal cortex

Humans and other animals can maintain constant payoffs in an uncertain environment by steadily re-evaluating and flexibly adjusting current strategy, which largely depends on the interactions between the prefrontal cortex (PFC) and mediodorsal thalamus (MD). While the ventromedial PFC (vmPFC) represents the level of uncertainty (i.e., prior belief about external states), it remains unclear how the brain recruits the PFC-MD network to re-evaluate decision strategy based on the uncertainty. Here, we leverage non-linear dynamic causal modeling on fMRI data to test how prior belief-dependent activity in vmPFC gates the information flow in the PFC-MD network when individuals switch their decision strategy. We show that the prior belief-related responses in vmPFC had a modulatory influence on the connections from dorsolateral PFC (dlPFC) to both, lateral orbitofrontal (lOFC) and MD. Bayesian parameter averaging revealed that only the connection from the dlPFC to lOFC surpassed the significant threshold, which indicates that the weaker the prior belief, the less was the inhibitory influence of the vmPFC on the strength of effective connections from dlPFC to lOFC. These findings suggest that the vmPFC acts as a gatekeeper for the recruitment of processing resources to re-evaluate the decision strategy in situations of high uncertainty.

High-Resolution Tractography Protocol to Investigate the Pathways between Human Mediodorsal Thalamic Nucleus and Prefrontal Cortex

Animal studies have established that the mediodorsal nucleus (MD) of the thalamus is heavily and reciprocally connected with all areas of the prefrontal cortex (PFC). In humans, however, these connections are difficult to investigate. High-resolution imaging protocols capable of reliably tracing the axonal tracts linking the human MD with each of the PFC areas may thus be key to advance our understanding of the variation, development, and plastic changes of these important circuits, in health and disease. Here, we tested in adult female and male humans the reliability of a new reconstruction protocol based on in vivo diffusion MRI to trace, measure, and characterize the fiber tracts interconnecting the MD with 39 human PFC areas per hemisphere. Our protocol comprised the following three components: (1) defining regions of interest; (2) preprocessing diffusion data; and, (3) modeling white matter tracts and tractometry. This analysis revealed largely separate PFC territories of reciprocal MD-PFC tracts bearing striking resemblance with the topographic layout observed in macaque connection-tracing studies. We then examined whether our protocol could reliably reconstruct each of these MD-PFC tracts and their profiles across test and retest sessions. Results revealed that this protocol was able to trace and measure, in both left and right hemispheres, the trajectories of these 39 area-specific axon bundles with good-to-excellent test-retest reproducibility. This protocol, which has been made publicly available, may be relevant for cognitive neuroscience and clinical studies of normal and abnormal PFC function, development, and plasticity.SIGNIFICANCE STATEMENT Reciprocal MD-PFC interactions are critical for complex human cognition and learning. Reliably tracing, measuring and characterizing MD-PFC white matter tracts using high-resolution noninvasive methods is key to assess individual variation of these systems in humans. Here, we propose a high-resolution tractography protocol that reliably reconstructs 39 area-specific MD-PFC white matter tracts per hemisphere and quantifies structural information from diffusion MRI data. This protocol revealed a detailed mapping of thalamocortical and corticothalamic MD-PFC tracts in four different PFC territories (dorsal, medial, orbital/frontal pole, inferior frontal) showing structural connections resembling those observed in tracing studies with macaques. Furthermore, our automated protocol revealed high test-retest reproducibility and is made publicly available, constituting a step forward in mapping human MD-PFC circuits in clinical and academic research.

Functional alterations of the prefrontal circuit underlying cognitive aging in mice

Executive function is susceptible to aging. How aging impacts the circuit-level computations underlying executive function remains unclear. Using calcium imaging and optogenetic manipulation during memory-guided behavior, we show that working-memory coding and the relevant recurrent connectivity in the mouse medial prefrontal cortex (mPFC) are altered as early as middle age. Population activity in the young adult mPFC exhibits dissociable yet overlapping patterns between tactile and auditory modalities, enabling crossmodal memory coding concurrent with modality-dependent coding. In middle age, however, crossmodal coding remarkably diminishes while modality-dependent coding persists, and both types of coding decay in advanced age. Resting-state functional connectivity, especially among memory-coding neurons, decreases already in middle age, suggesting deteriorated recurrent circuits for memory maintenance. Optogenetic inactivation reveals that the middle-aged mPFC exhibits heightened vulnerability to perturbations. These findings elucidate functional alterations of the prefrontal circuit that unfold in middle age and deteriorate further as a hallmark of cognitive aging.

Altered Functional Connectivity Strength in Distinct Brain Networks of Children With Early-Onset Schizophrenia

BACKGROUND

Schizophrenia is regarded as a brain network or connectome disorder that is associated with neurodevelopment. Children with early-onset schizophrenia (EOS) provide an opportunity to evaluate the neuropathology of schizophrenia at a very early stage without potential confounding factors. But dysfunction in brain networks of schizophrenia is inconsistent.

PURPOSE

To identify abnormal functional connectivity (FC) in EOS patients and relationships with clinical symptoms, we aimed to reveal neuroimaging phenotypes of EOS.

STUDY TYPE

Prospective, cross-sectional.

POPULATION

Twenty-six female/22 male patients (age:14.3 ± 3.45 years) with first-episode EOS, 27 female/22 male age- and gender-matched healthy controls (HC) (age:14.1 ± 4.32).

FIELD STRENGTH/SEQUENCE

3-T, resting-state (rs) gradient-echo echo-planar imaging and three-dimensional magnetization-prepared rapid gradient-echo imaging.

ASSESSMENT

Intelligence quotient (IQ) was measured by the Wechsler Intelligence Scale-Fourth edition for Children (WISC-IV). The clinical symptoms were evaluated by the Positive and Negative Syndrome Scale (PANSS). FC strength (FCS) from rs functional MRI (rsfMRI) was used to investigate functional integrity of global brain regions. In addition, associations between regionally altered FCS and clinical symptoms in EOS patients were examined.

STATISTICAL TESTS

Two-sample t-test controlling for sample size, diagnostic method, brain volume algorithm, and age of the subjects, Bonferroni correction, Pearson's correlation analysis. A P-value <0.05 with a minimum cluster size of 50 voxels was considered statistically significant.

RESULTS

Compared with HC, EOS patients had significantly lower total IQ scores (IQ:91.5 ± 16.1), increased FCS in the bilateral precuneus, left dorsolateral prefrontal cortex, left thalamus, and left parahippocampus (paraHIP), and decreased FCS in the right cerebellum posterior lobe and right superior temporal gyrus. The PANSS total score of EOS patients (PANSS total score:74.30 ± 7.23) was found to be positively correlated to FCS in the left paraHIP (r = 0.45).

DATA CONCLUSION

Our study revealed that disrupted FC of brain hubs illustrate multiple abnormalities in brain networks in EOS patients.

EVIDENCE LEVEL

1 TECHNICAL EFFICACY STAGE: 2.

Dynorphin / kappa-opioid receptor regulation of excitation-inhibition balance toggles afferent control of prefrontal cortical circuits in a pathway-specific manner

The medial prefrontal cortex (mPFC) controls behavior via connections with limbic excitatory afferents that engage various inhibitory motifs to shape mPFC circuit function. The dynorphin (Dyn) / kappa-opioid receptor (KOR) system is highly enriched in the mPFC, and its dysregulation is implicated in neuropsychiatric disorders. However, it is unclear how the Dyn / KOR system modulates excitatory and inhibitory circuits that are integral for mPFC information processing and behavioral control. Here, we provide a circuit-based framework wherein mPFC Dyn / KOR signaling regulates excitation-inhibition balance by toggling which afferents drive mPFC neurons. Dyn / KOR regulation of afferent inputs is pathway-specific. Dyn acting on presynaptic KORs inhibits glutamate release from afferent inputs to the mPFC, including the basolateral amygdala (BLA), paraventricular nucleus of the thalamus, and contralateral cortex. The majority of excitatory synapses to mPFC neurons, including those from the ventral hippocampus (VH), do not express presynaptic KOR, rendering them insensitive to Dyn / KOR modulation. Dyn / KOR signaling also suppresses afferent-driven recruitment of specific inhibitory sub-networks, providing a basis for Dyn to disinhibit mPFC circuits. Specifically, Dyn / KOR signaling preferentially suppresses SST interneuron- relative to PV interneuron-mediated inhibition. Selective KOR action on afferents or within mPFC microcircuits gates how distinct limbic inputs drive spiking in mPFC neurons. Presynaptic Dyn / KOR signaling decreases KOR-positive input-driven (e.g. BLA) spiking of mPFC neurons. In contrast, KOR-negative input recruitment of mPFC neurons is enhanced by Dyn / KOR signaling via suppression of mPFC inhibitory microcircuits. Thus, by acting on distinct circuit elements, Dyn / KOR signaling shifts KOR-positive and negative afferent control of mPFC circuits, providing mechanistic insights into the role of neuropeptides in shaping mPFC function. Together, these findings highlight the utility of targeting the mPFC Dyn / KOR system as a means to treat neuropsychiatric disorders characterized by dysregulation in mPFC integration of long-range afferents with local inhibitory microcircuits.

Characterizing functional modules in the human thalamus: coactivation-based parcellation and systems-level functional decoding

The human thalamus relays sensory signals to the cortex and facilitates brain-wide communication. The thalamus is also more directly involved in sensorimotor and various cognitive functions but a full characterization of its functional repertoire, particularly in regard to its internal anatomical structure, is still outstanding. As a putative hub in the human connectome, the thalamus might reveal its functional profile only in conjunction with interconnected brain areas. We therefore developed a novel systems-level Bayesian reverse inference decoding that complements the traditional neuroinformatics approach towards a network account of thalamic function. The systems-level decoding considers the functional repertoire (i.e., the terms associated with a brain region) of all regions showing co-activations with a predefined seed region in a brain-wide fashion. Here, we used task-constrained meta-analytic connectivity-based parcellation (MACM-CBP) to identify thalamic subregions as seed regions and applied the systems-level decoding to these subregions in conjunction with functionally connected cortical regions. Our results confirm thalamic structure-function relationships known from animal and clinical studies and revealed further associations with language, memory, and locomotion that have not been detailed in the cognitive neuroscience literature before. The systems-level decoding further uncovered large systems engaged in autobiographical memory and nociception. We propose this novel decoding approach as a useful tool to detect previously unknown structure-function relationships at the brain network level, and to build viable starting points for future studies.

Emergence of cortical network motifs for short-term memory during learning

Learning of adaptive behaviors requires the refinement of coordinated activity across multiple brain regions. However, how neural communications develop during learning remains poorly understood. Here, using two-photon calcium imaging, we simultaneously recorded the activity of layer 2/3 excitatory neurons in eight regions of the mouse dorsal cortex during learning of a delayed-response task. Across learning, while global functional connectivity became sparser, there emerged a subnetwork comprising of neurons in the anterior lateral motor cortex (ALM) and posterior parietal cortex (PPC). Neurons in this subnetwork shared a similar choice code during action preparation and formed recurrent functional connectivity across learning. Suppression of PPC activity disrupted choice selectivity in ALM and impaired task performance. Recurrent neural networks reconstructed from ALM activity revealed that PPC-ALM interactions rendered choice-related attractor dynamics more stable. Thus, learning constructs cortical network motifs by recruiting specific inter-areal communication channels to promote efficient and robust sensorimotor transformation.

The right inferior frontal gyrus as pivotal node and effective regulator of the basal ganglia-thalamocortical response inhibition circuit

Background

The involvement of specific basal ganglia-thalamocortical circuits in response inhibition has been extensively mapped in animal models. However, the pivotal nodes and directed causal regulation within this inhibitory circuit in humans remains controversial.

Objective

The main aim of the present study was to determine the causal information flow and critical nodes in the basal ganglia-thalamocortical inhibitory circuits and also to examine whether these are modulated by biological factors (i.e. sex) and behavioral performance.

Methods

Here, we capitalize on the recent progress in robust and biologically plausible directed causal modeling (DCM-PEB) and a large response inhibition dataset (n = 250) acquired with concomitant functional magnetic resonance imaging to determine key nodes, their causal regulation and modulation via biological variables (sex) and inhibitory performance in the inhibitory circuit encompassing the right inferior frontal gyrus (rIFG), caudate nucleus (rCau), globus pallidum (rGP), and thalamus (rThal).

Results

The entire neural circuit exhibited high intrinsic connectivity and response inhibition critically increased causal projections from the rIFG to both rCau and rThal. Direct comparison further demonstrated that response inhibition induced an increasing rIFG inflow and increased the causal regulation of this region over the rCau and rThal. In addition, sex and performance influenced the functional architecture of the regulatory circuits such that women displayed increased rThal self-inhibition and decreased rThal to GP modulation, while better inhibitory performance was associated with stronger rThal to rIFG communication. Furthermore, control analyses did not reveal a similar key communication in a left lateralized model.

Conclusions

Together, these findings indicate a pivotal role of the rIFG as input and causal regulator of subcortical response inhibition nodes.

The spatial extent of anatomical connections within the thalamus varies across the cortical hierarchy in humans and macaques

Each cortical area has a distinct pattern of anatomical connections within the thalamus, a central subcortical structure composed of functionally and structurally distinct nuclei. Previous studies have suggested that certain cortical areas may have more extensive anatomical connections that target multiple thalamic nuclei, which potentially allows them to modulate distributed information flow. However, there is a lack of quantitative investigations into anatomical connectivity patterns within the thalamus. Consequently, it remains unknown if cortical areas exhibit systematic differences in the extent of their anatomical connections within the thalamus. To address this knowledge gap, we used diffusion magnetic resonance imaging (dMRI) to perform brain-wide probabilistic tractography for 828 healthy adults from the Human Connectome Project. We then developed a framework to quantify the spatial extent of each cortical area's anatomical connections within the thalamus. Additionally, we leveraged resting-state functional MRI, cortical myelin, and human neural gene expression data to test if the extent of anatomical connections within the thalamus varied along the cortical hierarchy. Our results revealed two distinct corticothalamic tractography motifs: 1) a sensorimotor cortical motif characterized by focal thalamic connections targeting posterolateral thalamus, associated with fast, feed-forward information flow; and 2) an associative cortical motif characterized by diffuse thalamic connections targeting anteromedial thalamus, associated with slow, feed-back information flow. These findings were consistent across human subjects and were also observed in macaques, indicating cross-species generalizability. Overall, our study demonstrates that sensorimotor and association cortical areas exhibit differences in the spatial extent of their anatomical connections within the thalamus, which may support functionally-distinct cortico-thalamic information flow.

Transthalamic input to higher-order cortex selectively conveys state information

Communication among different neocortical areas is largely thought to be mediated by long-range synaptic interactions between cortical neurons, with the thalamus providing only an initial relay of information from the sensory periphery. Higher-order thalamic nuclei receive strong synaptic inputs from the cortex and send robust projections back to other cortical areas, providing a distinct and potentially critical route for cortico-cortical communication. However, the relative contributions of corticocortical and thalamocortical inputs to higher-order cortical function remain unclear. Using imaging of cortical neurons and projection axon terminals in combination with optogenetic manipulations, we find that the higher-order visual thalamus of mice conveys a specialized stream of information to higher-order visual cortex. Whereas corticocortical projections from lower cortical areas convey robust visual information, higher-order thalamocortical projections convey strong behavioral state information. Together, these findings suggest a key role for higher-order thalamus in providing contextual signals that flexibly modulate sensory processing in higher-order cortex.

Neurocognitive outcomes in adult survivors of neuroblastoma: A report from the Childhood Cancer Survivor Study

BACKGROUND

Despite survival improvements, there is a paucity of data on neurocognitive outcomes in neuroblastoma survivors. This study addresses this literature gap.

METHODS

Neurocognitive impairments in survivors were compared to sibling controls from the Childhood Cancer Survivor Study (CCSS) using the CCSS Neurocognitive Questionnaire. Impaired emotional regulation, organization, task efficiency, and memory defined as scores ≥90th percentile of sibling norms. Modified Poisson regression models evaluated associations with treatment exposures, era of diagnosis, and chronic conditions. Analyses were stratified by age at diagnosis (≤1 and >1 year) as proxy for lower versus higher risk disease.

RESULTS

Survivors (N = 837; median [range] age, 25 [17-58] years, age diagnosed, 1 [0-21] years) were compared to sibling controls (N = 728; age, 32 [16-43] years). Survivors had higher risk of impaired task efficiency (≤1 year relative risk [RR], 1.48; 95% confidence interval [CI], 1.08-2.03; >1 year RR, 1.58; 95% CI, 1.22-2.06) and emotional regulation (≤1 year RR, 1.51; 95% CI, 1.07-2.12; >1 year RR, 1.44; 95% CI, 1.06-1.95). Impaired task efficiency associated with platinum exposure (≤1 year RR, 1.74; 95% CI, 1.01-2.97), hearing loss (≤1 year RR, 1.95; 95% CI, 1.26-3.00; >1 year RR, 1.56; 95% CI, 1.09-2.24), cardiovascular (≤1 year RR, 1.83; 95% CI, 1.15-2.89; >1 year RR, 1.74; 95% CI, 1.12-2.69), neurologic (≤1 year RR, 2.00; 95% CI, 1.32-3.03; >1 year RR, 2.29; 95% CI, 1.64-3.21), and respiratory (>1 year RR, 2.35; 95% CI, 1.60-3.45) conditions. Survivors ≤1 year; female sex (RR, 1.54; 95% CI, 1.02-2.33), cardiovascular (RR, 1.71; 95% CI, 1.08-2.70) and respiratory (RR, 1.99; 95% CI, 1.14-3.49) conditions associated impaired emotional regulation. Survivors were less likely to be employed full-time (p < .0001), graduate college (p = .035), and live independently (p < .0001).

CONCLUSIONS

Neuroblastoma survivors report neurocognitive impairment impacting adult milestones. Identified health conditions and treatment exposures can be targeted to improve outcomes.

PLAIN LANGUAGE SUMMARY

Survival rates continue to improve in patients with neuroblastoma. There is a lack of information regarding neurocognitive outcomes in neuroblastoma survivors; most studies examined survivors of leukemia or brain tumors. In this study, 837 adult survivors of childhood neuroblastoma were compared to siblings from the Childhood Cancer Survivorship Study. Survivors had a 50% higher risk of impairment with attention/processing speed (task efficiency) and emotional reactivity/frustration tolerance (emotional regulation). Survivors were less likely to reach adult milestones such as living independently. Survivors with chronic health conditions are at a higher risk of impairment. Early identification and aggressive management of chronic conditions may help mitigate the level of impairment.

Heterogeneous complement and microglia activation mediates stress-induced synapse loss

Spatially heterogeneous synapse loss is a characteristic of many psychiatric and neurological disorders, but the underlying mechanisms are unclear. Here, we show that spatially-restricted complement activation mediates stress-induced heterogeneous microglia activation and synapse loss localized to the upper layers of the mouse medial prefrontal cortex (mPFC). Single cell RNA sequencing also reveals a stress-associated microglia state marked by high expression of the apolipoprotein E gene (ApoE high ) localized to the upper layers of the mPFC. Mice lacking complement component C3 are protected from stress-induced layer-specific synapse loss, and the ApoE high microglia population is markedly reduced in the mPFC of these mice. Furthermore, C3 knockout mice are also resilient to stress-induced anhedonia and working memory behavioral deficits. Our findings suggest that region-specific complement and microglia activation can contribute to the disease-specific spatially restricted patterns of synapse loss and clinical symptoms found in many brain diseases.

Effects of hypertension on subcortical nucleus morphological alternations in patients with type 2 diabetes

Objectives

Type 2 diabetes mellitus(T2DM) and hypertension(HTN) are common comorbidities, and known to affect the brain. However, little is known about the effects of the coexisting HTN on brain in T2DM patients. So we aim to investigate the impact of HTN on the subcortical nucleus morphological alternations in T2DM patients.

Materials & methods

This work was registered by the clinicaltrials.gov (grant number NCT03564431). We recruited a total of 92 participants, comprising 36 only T2DM patients, 28 T2DM patients with HTN(T2DMH) and 28 healthy controls(HCs) in our study. All clinical indicators were assessed and brain image data was collected for each participant. Voxel-based morphometry(VBM), automatic volume and vertex-based shape analyses were used to determine the subcortical nucleus alternations from each participant's 3D-T1 brain images and evaluate the relationship between the alternations and clinical indicators.

Results

T2DMH patients exhibited volumetric reduction and morphological alterations in thalamus compared to T2DM patients, whereas T2DM patients did not demonstrate any significant subcortical alterations compared to HCs. Furthermore, negative correlations have been found between thalamic alternations and the duration of HTN in T2DMH patients.

Conclusion

Our results revealed that HTN may exacerbate subcortical nucleus alternations in T2DM patients, which highlighted the importance of HTN management in T2DM patients to prevent further damage to the brain health.

Opportunities and challenges in drug discovery targeting the orphan receptor GPR12

G-protein-coupled receptor 12 (GPR12) is a brain-specific expression orphan G-protein-coupled receptor (oGPCR) that regulates various physiological processes. It is an emerging therapeutic target for central nervous system (CNS) disorders, including Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD), attention deficit hyperactivity disorder (ADHD), and schizophrenia, as well as other human diseases, such as cancer, obesity, and metabolic disorders. GPR12 remains a less extensively investigated oGPCR, particularly in terms of its biological functions, signaling pathways, and ligand discovery. The discovery of drug-like small-molecule modulators to probe the brain functions of GPR12 or to act as a potential drug candidates, as well as the identification of reliable biomarkers, are vital to elucidate the roles of this receptor in various human diseases and develop novel target-based therapeutics.

Modeling the role of the thalamus in resting-state functional connectivity: Nature or structure

The thalamus is a central brain structure that serves as a relay station for sensory inputs from the periphery to the cortex and regulates cortical arousal. Traditionally, it has been regarded as a passive relay that transmits information between brain regions. However, recent studies have suggested that the thalamus may also play a role in shaping functional connectivity (FC) in a task-based context. Based on this idea, we hypothesized that due to its centrality in the network and its involvement in cortical activation, the thalamus may also contribute to resting-state FC, a key neurological biomarker widely used to characterize brain function in health and disease. To investigate this hypothesis, we constructed ten in-silico brain network models based on neuroimaging data (MEG, MRI, and dwMRI), and simulated them including and excluding the thalamus, and raising the noise into thalamus to represent the afferences related to the reticular activating system (RAS) and the relay of peripheral sensory inputs. We simulated brain activity and compared the resulting FC to their empirical MEG counterparts to evaluate model's performance. Results showed that a parceled version of the thalamus with higher noise, able to drive damped cortical oscillators, enhanced the match to empirical FC. However, with an already active self-oscillatory cortex, no impact on the dynamics was observed when introducing the thalamus. We also demonstrated that the enhanced performance was not related to the structural connectivity of the thalamus, but to its higher noisy inputs. Additionally, we highlighted the relevance of a balanced signal-to-noise ratio in thalamus to allow it to propagate its own dynamics. In conclusion, our study sheds light on the role of the thalamus in shaping brain dynamics and FC in resting-state and allowed us to discuss the general role of criticality in the brain at the mesoscale level.

A Deep-Learning Enabled Automatic Fetal Thalamus Diameter Measurement Algorithm

The analysis of maternal factors that impact the normal development of the fetal thalamus is an emerging field of research and requires the retrospective measurement of fetal thalamus diameter (FTD). Unfortunately, FTD is not measured in routine 2D ultrasound (2D-US) screenings of fetuses. Manual measurement of FTD is a laborious, difficult, and error-prone process because the thalamus lacks well-defined boundaries in 2D-US images of the fetal brain as it has a similar echogenicity to the surrounding brain tissue. Traditional methods based on statistical shape models (SSMs) perform poorly in measuring FTD due to the noisy textures and fuzzy edges of the fetal thalamus in 2D-US images of the fetal brain. To overcome these difficulties, we propose a deep learning-based automatic FTD measurement algorithm, FTDNet. FTDNet measures FTD by learning to directly detect the measurement landmarks through supervised learning. The algorithm first detects the region of the brain that contains the thalamus structure, and then focuses on processing that region for FTD landmark detection. Our FTD dataset, developed through a consensus between two ultrasonographers, contains 1,111 pairs of landmark coordinates for measuring FTD and verified bounding boxes surrounding the fetal thalamus. To assess FTDNet's measurement consistency compared to the ground truth, we used the intraclass correlation coefficient (ICC). FTDNet achieved an ICC score of 0.734, significantly outperforming the prior SSM method and other baseline comparison methods. Our findings are an important step forward in understanding the maternal factors which influence fetal brain development.Clinical relevance- This work proposes an end-to-end thalamus detection and measurement algorithm for measuring fetal thalamus diameter. Our work represents a significant step in the research of how maternal factors can impact fetal thalamus development. The development of an automatic and accurate method for measuring FTD through deep learning has the potential to greatly advance this field of study.

Spiking Recurrent Neural Networks Represent Task-Relevant Neural Sequences in Rule-Dependent Computation

Background

Prefrontal cortical neurons play essential roles in performing rule-dependent tasks and working memory-based decision making.

Methods

Motivated by PFG recordings of task-performing mice, we developed an excitatory-inhibitory spiking recurrent neural network (SRNN) to perform a rule-dependent two-alternative forced choice (2AFC) task. We imposed several important biological constraints onto the SRNN, and adapted spike frequency adaptation (SFA) and SuperSpike gradient methods to train the SRNN efficiently.

Results

The trained SRNN produced emergent rule-specific tunings in single-unit representations, showing rule-dependent population dynamics that resembled experimentally observed data. Under varying test conditions, we manipulated the SRNN parameters or configuration in computer simulations, and we investigated the impacts of rule-coding error, delay duration, recurrent weight connectivity and sparsity, and excitation/inhibition (E/I) balance on both task performance and neural representations.

Conclusions

Overall, our modeling study provides a computational framework to understand neuronal representations at a fine timescale during working memory and cognitive control, and provides new experimentally testable hypotheses in future experiments.

The impact of the human thalamus on brain-wide information processing

The thalamus is a small, bilateral structure in the diencephalon that integrates signals from many areas of the CNS. This critical anatomical position allows the thalamus to influence whole-brain activity and adaptive behaviour. However, traditional research paradigms have struggled to attribute specific functions to the thalamus, and it has remained understudied in the human neuroimaging literature. Recent advances in analytical techniques and increased accessibility to large, high-quality data sets have brought forth a series of studies and findings that (re-)establish the thalamus as a core region of interest in human cognitive neuroscience, a field that otherwise remains cortico-centric. In this Perspective, we argue that using whole-brain neuroimaging approaches to investigate the thalamus and its interaction with the rest of the brain is key for understanding systems-level control of information processing. To this end, we highlight the role of the thalamus in shaping a range of functional signatures, including evoked activity, interregional connectivity, network topology and neuronal variability, both at rest and during the performance of cognitive tasks.

Spontaneous variations in arousal modulate subsequent visual processing and local field potential dynamics in the ferret during quiet wakefulness

Behavioral states affect neuronal responses throughout the cortex and influence visual processing. Quiet wakefulness (QW) is a behavioral state during which subjects are quiescent but awake and connected to the environment. Here, we examined the effects of pre-stimulus arousal variability on post-stimulus neural activity in the primary visual cortex and posterior parietal cortex in awake ferrets, using pupil diameter as an indicator of arousal. We observed that the power of stimuli-induced alpha (8-12 Hz) decreases when the arousal level increases. The peak of alpha power shifts depending on arousal. High arousal increases inter- and intra-areal coherence. Using a simplified model of laminar circuits, we show that this connectivity pattern is compatible with feedback signals targeting infragranular layers in area posterior parietal cortex and supragranular layers in V1. During high arousal, neurons in V1 displayed higher firing rates at their preferred orientations. Broad-spiking cells in V1 are entrained to high-frequency oscillations (>80 Hz), whereas narrow-spiking neurons are phase-locked to low- (12-18 Hz) and high-frequency (>80 Hz) rhythms. These results indicate that the variability and sensitivity of post-stimulus cortical responses and coherence depend on the pre-stimulus behavioral state and account for the neuronal response variability observed during repeated stimulation.

Bimodal modulation of L1 interneuron activity in anterior cingulate cortex during fear conditioning

The anterior cingulate cortex (ACC) plays a crucial role in encoding, consolidating and retrieving memories related to emotionally salient experiences, such as aversive and rewarding events. Various studies have highlighted its importance for fear memory processing, but its circuit mechanisms are still poorly understood. Cortical layer 1 (L1) of the ACC might be a particularly important site of signal integration, since it is a major entry point for long-range inputs, which is tightly controlled by local inhibition. Many L1 interneurons express the ionotropic serotonin receptor 3a (5HT3aR), which has been implicated in post-traumatic stress disorder and in models of anxiety. Hence, unraveling the response dynamics of L1 interneurons and subtypes thereof during fear memory processing may provide important insights into the microcircuit organization regulating this process. Here, using 2-photon laser scanning microscopy of genetically encoded calcium indicators through microprisms in awake mice, we longitudinally monitored over days the activity of L1 interneurons in the ACC in a tone-cued fear conditioning paradigm. We observed that tones elicited responses in a substantial fraction of the imaged neurons, which were significantly modulated in a bidirectional manner after the tone was associated to an aversive stimulus. A subpopulation of these neurons, the neurogliaform cells (NGCs), displayed a net increase in tone-evoked responses following fear conditioning. Together, these results suggest that different subpopulations of L1 interneurons may exert distinct functions in the ACC circuitry regulating fear learning and memory.

Primary somatosensory cortex bidirectionally modulates sensory gain and nociceptive behavior in a layer-specific manner

The primary somatosensory cortex (S1) is a hub for body sensation of both innocuous and noxious signals, yet its role in somatosensation versus pain is debated. Despite known contributions of S1 to sensory gain modulation, its causal involvement in subjective sensory experiences remains elusive. Here, in mouse S1, we reveal the involvement of cortical output neurons in layers 5 (L5) and 6 (L6) in the perception of innocuous and noxious somatosensory signals. We find that L6 activation can drive aversive hypersensitivity and spontaneous nocifensive behavior. Linking behavior to neuronal mechanisms, we find that L6 enhances thalamic somatosensory responses, and in parallel, strongly suppresses L5 neurons. Directly suppressing L5 reproduced the pronociceptive phenotype induced by L6 activation, suggesting an anti-nociceptive function for L5 output. Indeed, L5 activation reduced sensory sensitivity and reversed inflammatory allodynia. Together, these findings reveal a layer-specific and bidirectional role for S1 in modulating subjective sensory experiences.

Spatial Attention Modulates Neuronal Interactions between Simple and Complex Cells in V1

Visual perception is profoundly modulated by spatial attention, which can selectively prioritize goal-related information. Previous studies found spatial attention facilitated the efficacy of neuronal communication between visual cortices with hierarchical organizations. In the primary visual cortex (V1), there is also a hierarchical connection between simple (S) and complex (C) cells. We wonder whether and how spatial attention modulates neuronal communication within V1, especially for neuronal pairs with heterogeneous visual input. We simultaneously recorded the pairs' activity from macaque monkeys when they performed a spatial-attention-involved task, then applied likelihood-based Granger causality analysis to explore attentional modulation of neuronal interactions. First, a significant attention-related decrease in Granger causality was found in S-C pairs, which primarily displayed in the S-to-C feedforward connection. Second, the interaction strength of the feedforward connection was significantly higher than that of the feedback under attend toward (AT) conditions. Although information flow did not alter as the attentional focus shifted, the strength of communications between target- and distractor-stimuli-covered neurons differed only when attending to complex cells' receptive fields (RFs). Furthermore, pairs' communications depended on the attentional modulation of neurons' firing rates. Our findings demonstrate spatial attention does not induce specific information flow but rather amplifies directed communication within V1.

Long-range inhibition synchronizes and updates prefrontal task activity

Changes in patterns of activity within the medial prefrontal cortex enable rodents, non-human primates and humans to update their behaviour to adapt to changes in the environment-for example, during cognitive tasks1-5. Parvalbumin-expressing inhibitory neurons in the medial prefrontal cortex are important for learning new strategies during a rule-shift task6-8, but the circuit interactions that switch prefrontal network dynamics from maintaining to updating task-related patterns of activity remain unknown. Here we describe a mechanism that links parvalbumin-expressing neurons, a new callosal inhibitory connection, and changes in task representations. Whereas nonspecifically inhibiting all callosal projections does not prevent mice from learning rule shifts or disrupt the evolution of activity patterns, selectively inhibiting only callosal projections of parvalbumin-expressing neurons impairs rule-shift learning, desynchronizes the gamma-frequency activity that is necessary for learning8 and suppresses the reorganization of prefrontal activity patterns that normally accompanies rule-shift learning. This dissociation reveals how callosal parvalbumin-expressing projections switch the operating mode of prefrontal circuits from maintenance to updating by transmitting gamma synchrony and gating the ability of other callosal inputs to maintain previously established neural representations. Thus, callosal projections originating from parvalbumin-expressing neurons represent a key circuit locus for understanding and correcting the deficits in behavioural flexibility and gamma synchrony that have been implicated in schizophrenia and related conditions9,10.

Towards a pluralistic neurobiological understanding of consciousness

Theories of consciousness are often based on the assumption that a single, unified neurobiological account will explain different types of conscious awareness. However, recent findings show that, even within a single modality such as conscious visual perception, the anatomical location, timing, and information flow of neural activity related to conscious awareness vary depending on both external and internal factors. This suggests that the search for generic neural correlates of consciousness may not be fruitful. I argue that consciousness science requires a more pluralistic approach and propose a new framework: joint determinant theory (JDT). This theory may be capable of accommodating different brain circuit mechanisms for conscious contents as varied as percepts, wills, memories, emotions, and thoughts, as well as their integrated experience.

Electrophysiological correlates of attention in the locus coeruleus - anterior cingulate cortex circuit during the rodent continuous performance test

Sustained attention, the ability to focus on an activity or stimulus over time, is significantly impaired in many psychiatric disorders, and there remains a major unmet need in treating impaired attention. Continuous performance tests (CPTs) were developed to measure sustained attention in humans, non-human primates, rats, and mice, and similar neural circuits are engaged across species during CPT performance, supporting their use in translational studies to identify novel therapeutics. Here, we identified electrophysiological correlates of attentional performance in a touchscreen-based rodent CPT (rCPT) in the locus coeruleus (LC) and anterior cingulate cortex (ACC), two inter-connected regions that are implicated in attentional processes. We used viral labeling and molecular techniques to demonstrate that neural activity is recruited in LC-ACC projections during the rCPT, and that this recruitment increases with cognitive demand. We implanted male mice with depth electrodes within the LC and ACC for local field potential (LFP) recordings during rCPT training, and identified an increase in ACC delta and theta power, and an increase in LC delta power during correct responses in the rCPT. We also found that the LC leads the ACC in theta frequencies during correct responses while the ACC leads the LC in gamma frequencies during incorrect responses. These findings may represent translational biomarkers that can be used to screen novel therapeutics for drug discovery in attention.

Distinguishing between bipolar depression and unipolar depression based on the reward circuit activities and clinical characteristics: A machine learning analysis

BACKGROUND

Differentiating bipolar depression (BD) from unipolar depression (UD) is a major clinical challenge. Identifying the potential classifying biomarkers between these two diseases is vital to optimize personalized management of depressed individuals.

METHODS

Here, we aimed to integrate neuroimaging and clinical data with machine learning method to classify BD and UD at the individual level. Data were collected from 31 healthy controls (HC group) and 80 depressive patients with an average follow-up period of 7.51 years. Of these patients, 32 got diagnosis conversion from major depressive disorder (MDD) to BD (BD group) and 48 remain persistent diagnosis of MDD (MDD group). Using graph theory and functional connectivity (FC) analysis, we investigated the differences in reward circuit properties among three groups. Then we applied a support vector machine and leave-one-out cross-validation methods to classify BD and UD patients based on neuroimaging and clinical data.

RESULTS

Compared with MDD and HC, BD showed decreased degree centrality of right mediodorsal thalamus (MD) and nodal efficiency (NE) of left ventral pallidum. Compared with BD and HC, MDD showed decreased NE of right MD and increased FC between right MD and bilateral dorsolateral prefrontal cortex and left ventromedial prefrontal cortex. Notably, the classifier obtained high classification accuracies (87.50 %) distinguishing BD and UD patients based on reward circuit properties and clinical features.

LIMITATIONS

The classifying model requires out-of-sample replication analysis.

CONCLUSION

The reward circuit dysfunction can not only provide additional information to assist clinical differential diagnosis, but also in turn informed treatment decision of depressive patients.