Division of labor among distinct subtypes of inhibitory neurons in a cortical microcircuit of working memory

The MIND diet, brain transcriptomic alterations, and dementia

INTRODUCTION

Dietary patterns are associated with dementia risk, but the underlying molecular mechanisms are largely unknown.

METHODS

We used RNA sequencing data from post mortem prefrontal cortex tissue and annual cognitive evaluations from 1204 participants in the Religious Orders Study and Memory and Aging Project. We identified a transcriptomic profile correlated with the MIND diet (Mediterranean-Dietary Approaches to Stop Hypertension Intervention for Neurodegenerative Delay) among 482 individuals who completed ante mortem food frequency questionnaires; and examined its associations with cognitive health in the remaining 722 participants.

RESULTS

We identified a transcriptomic profile, consisting of 50 genes, correlated with the MIND diet score (p = 0.001). Each standard deviation increase in the transcriptomic profile score was associated with a slower annual rate of decline in global cognition (β = 0.011, p = 0.003) and lower odds of dementia (odds ratio = 0.76, p = 0.0002). Expressions of several genes (including TCIM and IGSF5) appeared to mediate the association between MIND diet and dementia.

DISCUSSION

A brain transcriptomic profile for healthy diets revealed novel genes potentially associated with cognitive health.

HIGHLIGHTS

Why healthy dietary patterns are associated with lower dementia risk are unknown. We integrated dietary, brain transcriptomic, and cognitive data in older adults. Mediterranean-Dietary Approaches to Stop Hypertension Intervention for Neurodegenerative Delay (MIND) diet intake is correlated with a specific brain transcriptomic profile. This brain transcriptomic profile score is associated with better cognitive health. More data are needed to elucidate the causality and functionality of identified genes.

Flexible gating between subspaces in a neural network model of internally guided task switching

Behavioral flexibility relies on the brain's ability to switch rapidly between multiple tasks, even when the task rule is not explicitly cued but must be inferred through trial and error. The underlying neural circuit mechanism remains poorly understood. We investigated recurrent neural networks (RNNs) trained to perform an analog of the classic Wisconsin Card Sorting Test. The networks consist of two modules responsible for rule representation and sensorimotor mapping, respectively, where each module is comprised of a circuit with excitatory neurons and three major types of inhibitory neurons. We found that rule representation by self-sustained persistent activity across trials, error monitoring and gated sensorimotor mapping emerged from training. Systematic dissection of trained RNNs revealed a detailed circuit mechanism that is consistent across networks trained with different hyperparameters. The networks' dynamical trajectories for different rules resided in separate subspaces of population activity; the subspaces collapsed and performance was reduced to chance level when dendrite-targeting somatostatin-expressing interneurons were silenced, illustrating how a phenomenological description of representational subspaces is explained by a specific circuit mechanism.

Neuroanatomical Substrates of Circuit-Specific Cholinergic Modulation across the Primate Anterior Cingulate Cortex

Acetylcholine is a robust neuromodulator of the limbic system and a critical regulator of arousal and emotions. The anterior cingulate cortex (ACC) and the amygdala (AMY) are key limbic structures that are both densely innervated by cholinergic afferents and interact with each other for emotional regulation. The ACC is composed of functionally distinct dorsal (A24), rostral (A32), and ventral (A25) areas that differ in their connections with the AMY. The structural substrates of cholinergic modulation of distinct ACC microcircuits and outputs to AMY are thought to depend on the laminar and subcellular localization of cholinergic receptors. The present study examines the distribution of muscarinic acetylcholine receptors, m1 and m2, on distinct excitatory and inhibitory neurons and on AMY-targeting projection neurons within ACC areas, via immunohistochemistry and injections of neural tracers into the basolateral AMY in adult rhesus monkeys of both sexes. We found that laminar densities of m1+ and m2+ expressing excitatory and inhibitory neurons depended on area and cell type. Among the ACC areas, ventral subgenual ACC A25 exhibited greater m2+ localization on presynaptic inhibitory axon terminals and greater density of m1+ and m2+ expressing AMY-targeting (tracer+) pyramidal neurons. These patterns suggest robust cholinergic disinhibition and potentiation of amygdalar outputs from the limbic ventral ACC, which may be linked to the hyperexcitability of this subgenual ACC area in depression. These findings reveal the anatomical substrate of diverse cholinergic modulation of specific ACC microcircuits and amygdalar outputs that mediate cognitive-emotional integration and dysfunctions underlying stress and affective disorders.

Flexible gating between subspaces in a neural network model of internally guided task switching

Behavioral flexibility relies on the brain's ability to switch rapidly between multiple tasks, even when the task rule is not explicitly cued but must be inferred through trial and error. The underlying neural circuit mechanism remains poorly understood. We investigated recurrent neural networks (RNNs) trained to perform an analog of the classic Wisconsin Card Sorting Test. The networks consist of two modules responsible for rule representation and sensorimotor mapping, respectively, where each module is comprised of a circuit with excitatory neurons and three major types of inhibitory neurons. We found that rule representation by self-sustained persistent activity across trials, error monitoring and gated sensorimotor mapping emerged from training. Systematic dissection of trained RNNs revealed a detailed circuit mechanism that is consistent across networks trained with different hyperparameters. The networks' dynamical trajectories for different rules resided in separate subspaces of population activity; the subspaces collapsed and performance was reduced to chance level when dendrite-targeting somatostatin-expressing interneurons were silenced, illustrating how a phenomenological description of representational subspaces is explained by a specific circuit mechanism.

Neuronal activation sequences in lateral prefrontal cortex encode visuospatial working memory during virtual navigation

Working memory (WM) is the ability to maintain and manipulate information 'in mind'. The neural codes underlying WM have been a matter of debate. We simultaneously recorded the activity of hundreds of neurons in the lateral prefrontal cortex of male macaque monkeys during a visuospatial WM task that required navigation in a virtual 3D environment. Here, we demonstrate distinct neuronal activation sequences (NASs) that encode remembered target locations in the virtual environment. This NAS code outperformed the persistent firing code for remembered locations during the virtual reality task, but not during a classical WM task using stationary stimuli and constraining eye movements. Finally, blocking NMDA receptors using low doses of ketamine deteriorated the NAS code and behavioral performance selectively during the WM task. These results reveal the versatility and adaptability of neural codes supporting working memory function in the primate lateral prefrontal cortex.

The meso-connectomes of mouse, marmoset, and macaque: network organization and the emergence of higher cognition

The recent publications of the inter-areal connectomes for mouse, marmoset, and macaque cortex have allowed deeper comparisons across rodent vs. primate cortical organization. In general, these show that the mouse has very widespread, "all-to-all" inter-areal connectivity (i.e. a "highly dense" connectome in a graph theoretical framework), while primates have a more modular organization. In this review, we highlight the relevance of these differences to function, including the example of primary visual cortex (V1) which, in the mouse, is interconnected with all other areas, therefore including other primary sensory and frontal areas. We argue that this dense inter-areal connectivity benefits multimodal associations, at the cost of reduced functional segregation. Conversely, primates have expanded cortices with a modular connectivity structure, where V1 is almost exclusively interconnected with other visual cortices, themselves organized in relatively segregated streams, and hierarchically higher cortical areas such as prefrontal cortex provide top-down regulation for specifying precise information for working memory storage and manipulation. Increased complexity in cytoarchitecture, connectivity, dendritic spine density, and receptor expression additionally reveal a sharper hierarchical organization in primate cortex. Together, we argue that these primate specializations permit separable deconstruction and selective reconstruction of representations, which is essential to higher cognition.

Contributions of narrow- and broad-spiking prefrontal and parietal neurons on working memory tasks

Neurons that generate persistent activity in the primate dorsolateral prefrontal and posterior parietal cortex have been shown to be predictive of behavior in working memory tasks, though subtle differences between them have been observed in how information is represented. The role of different neuron types in each of these areas has not been investigated at depth. We thus compared the activity of neurons classified as narrow-spiking, putative interneurons, and broad-spiking, putative pyramidal neurons, recorded from the dorsolateral prefrontal and posterior parietal cortex of male monkeys, to analyze their role in the maintenance of working memory. Our results demonstrate that narrow-spiking neurons are active during a range of tasks and generate persistent activity during the delay period over which stimuli need to be maintained in memory. Furthermore, the activity of narrow-spiking neurons was predictive of the subject's recall no less than that of broad-spiking neurons, which are exclusively projection neurons in the cortex. Our results show that putative interneurons play an active role during the maintenance of working memory and shed light onto the fundamental neural circuits that determine subjects' memories and judgments.

The "psychiatric" neuron: the psychic neuron of the cerebral cortex, revisited

Nearly 25 years ago, Dr. Patricia Goldman-Rakic published her review paper, "The 'Psychic' Neuron of the Cerebral Cortex," outlining the circuit-level dynamics, neurotransmitter systems, and behavioral correlates of pyramidal neurons in the cerebral cortex, particularly as they relate to working memory. In the decades since the release of this paper, the existing literature and our understanding of the pyramidal neuron have increased tremendously, and research is still underway to better characterize the role of the pyramidal neuron in both healthy and psychiatric disease states. In this review, we revisit Dr. Goldman-Rakic's characterization of the pyramidal neuron, focusing on the pyramidal neurons of the prefrontal cortex (PFC) and their role in working memory. Specifically, we examine the role of PFC pyramidal neurons in the intersection of working memory and social function and describe how deficits in working memory may actually underlie the pathophysiology of social dysfunction in psychiatric disease states. We briefly describe the cortico-cortical and corticothalamic connections between the PFC and non-PFC brain regions, as well the microcircuit dynamics of the pyramidal neuron and interneurons, and the role of both these macro- and microcircuits in the maintenance of the excitatory/inhibitory balance of the cerebral cortex for working memory function. Finally, we discuss the consequences to working memory when pyramidal neurons and their circuits are dysfunctional, emphasizing the resulting social deficits in psychiatric disease states with known working memory dysfunction.

Aging or chronic stress impairs working memory and modulates GABA and glutamate gene expression in prelimbic cortex

The glucocorticoid (GC) hypothesis posits that effects of stress and dysregulated hypothalamic-pituitary-adrenal axis activity accumulate over the lifespan and contribute to impairment of neural function and cognition in advanced aging. The validity of the GC hypothesis is bolstered by a wealth of studies that investigate aging of the hippocampus and decline of associated mnemonic functions. The prefrontal cortex (PFC) mediates working memory which also decreases with age. While the PFC is susceptible to stress and GCs, few studies have formally assessed the application of the GC hypothesis to PFC aging and working memory. Using parallel behavioral and molecular approaches, we compared the effects of normal aging versus chronic variable stress (CVS) on working memory and expression of genes that encode for effectors of glutamate and GABA signaling in male F344 rats. Using an operant delayed match-to-sample test of PFC-dependent working memory, we determined that normal aging and CVS each significantly impaired mnemonic accuracy and reduced the total number of completed trials. We then determined that normal aging increased expression of Slc6a11, which encodes for GAT-3 GABA transporter expressed by astrocytes, in the prelimbic (PrL) subregion of the PFC. CVS increased PrL expression of genes associated with glutamatergic synapses: Grin2b that encodes the GluN2B subunit of NMDA receptor, Grm4 that encodes for metabotropic glutamate receptor 4 (mGluR4), and Plcb1 that encodes for phospholipase C beta 1, an intracellular signaling enzyme that transduces signaling of Group I mGluRs. Beyond the identification of specific genes that were differentially expressed between the PrL in normal aging or CVS, examination of Log2 fold-changes for all expressed glutamate and GABA genes revealed a positive association between molecular phenotypes of aging and CVS in the PrL but no association in the infralimbic subregion. Consistent with predictions of the GC hypothesis, PFC-dependent working memory and PrL glutamate/GABA gene expression demonstrate comparable sensitivity to aging and chronic stress. However, changes in expression of specific genes affiliated with regulation of extracellular GABA in normal aging vs. genes encoding for effectors of glutamatergic signaling during CVS suggest the presence of unique manifestations of imbalanced inhibitory and excitatory signaling in the PFC.

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.

Static and dynamic coding in distinct cell types during associative learning in the prefrontal cortex

The prefrontal cortex maintains information in memory through static or dynamic population codes depending on task demands, but whether the population coding schemes used are learning-dependent and differ between cell types is currently unknown. We investigate the population coding properties and temporal stability of neurons recorded from male macaques in two mapping tasks during and after stimulus-response associative learning, and then we use a Strategy task with the same stimuli and responses as control. We identify a heterogeneous population coding for stimuli, responses, and novel associations: static for putative pyramidal cells and dynamic for putative interneurons that show the strongest selectivity for all the variables. The population coding of learned associations shows overall the highest stability driven by cell types, with interneurons changing from dynamic to static coding after successful learning. The results support that prefrontal microcircuitry expresses mixed population coding governed by cell types and changes its stability during associative learning.

Diagnostic Specificity and Association With Cognition of Molecular Alterations in Prefrontal Somatostatin Neurons in Schizophrenia

Importance

Individuals with schizophrenia (SZ) exhibit pronounced deficits in somatostatin (SST) messenger RNA (mRNA) levels in the dorsolateral prefrontal cortex (DLPFC). Molecularly distinct subtypes of SST neurons, located in the superficial and deep zones of the DLPFC, are thought to contribute to different functional processes of this region; understanding the specificity of SST alterations in SZ across these zones could inform the functional consequences of those alterations, including cognitive impairments characteristic of SZ.

Objective

To quantify mRNA levels of SST and related neuropeptides in the DLPFC in individuals with SZ, bipolar disorder (BPD), or major depressive disorder (MDD) and unaffected comparison individuals.

Design, Setting, and Participants

This case-control study, conducted from January 20, 2020, to March 30, 2022, used postmortem brain tissue specimens previously obtained from individuals with SZ, MDD, or BPD and unaffected individuals from a community population through 2 medical examiners' offices. Demographic, clinical, and educational information was ascertained through psychological autopsies.

Exposures

Diagnosis of SZ, BPD, or MDD.

Main Outcome and Measures

The main outcome was levels of SST and related neuropeptide mRNA in 2 DLPFC zones, examined using laser microdissection and quantitative polymerase chain reaction or fluorescent in situ hybridization (FISH). Findings were compared using educational attainment as a proxy measure of premorbid cognition.

Results

A total of 200 postmortem brain specimens were studied, including 65 from unaffected comparison individuals (42 [65%] male; mean [SD] age, 49.2 [14.1] years); 54 from individuals with SZ (37 [69%] male; mean [SD] age, 47.5 [13.3] years); 42 from individuals with MDD (24 [57%] male; mean [SD] age, 45.6 [12.1] years); and 39 from individuals with BPD (23 [59%] male; mean (SD) age, 46.2 [12.5] years). Compared with unaffected individuals, levels of SST mRNA were lower in both superficial (Cohen d, 0.68; 95% CI, 0.23-1.13; P = .004) and deep (Cohen d, 0.60; 95% CI, 0.16-1.04; P = .02) DLPFC zones in individuals with SZ; findings were confirmed using FISH. Levels of SST were lower only in the superficial zone in the group with MDD (Cohen d, 0.58; 95% CI, 0.14-1.02; P = .12), but the difference was not significant; SST levels were not lower in either zone in the BPD group. Levels of neuropeptide Y and tachykinin 1 showed similar patterns. Neuropeptide alterations in the superficial, but not deep, zone were associated with lower educational attainment only in the group with SZ (superficial: adjusted odds ratio, 1.71 [95% CI, 1.11-2.69]; P = .02; deep: adjusted odds ratio, 1.08 [95% CI, 0.64-1.84]; P = .77).

Conclusions and Relevance

The findings revealed diagnosis-specific patterns of molecular alterations in SST neurons in the DLPFC, suggesting that distinct disease processes are reflected in the differential vulnerability of SST neurons in individuals with SZ, MDD, and BPD. In SZ, alterations specifically in the superficial zone may be associated with cognitive dysfunction.

Pattern of ventral temporal lobe interconnections in rhesus macaques

The entorhinal cortex (EC, A28) is linked through reciprocal pathways with nearby perirhinal and visual, auditory, and multimodal association cortices in the temporal lobe, in pathways associated with the flow of information for memory processing. The density and laminar organization of these pathways is not well understood in primates. We studied interconnections within the ventral temporal lobe in young adult rhesus monkeys of both sexes with the aid of neural tracers injected in temporal areas (Ts1, Ts2, TE1, area 36, temporal polar area TPro, and area 28) to determine the density and laminar distribution of projection neurons within the temporal lobe. These temporal areas can be categorized into three different cortical types based on their laminar architecture: the sensory association areas Ts1, Ts2, and TE1 have six layers (eulaminate); the perirhinal limbic areas TPro and area 36 have an incipient layer IV (dysgranular); and area 28 lacks layer IV (agranular). We found that (1) temporal areas that are similar in laminar architecture by cortical type are strongly interconnected, and (2) the laminar pattern of connections is dependent on the difference in cortical laminar structure between linked areas. Thus, agranular A28 is more strongly connected with other agranular/dysgranular areas than with eulaminate cortices. Further, A28 predominantly projected via feedback-like pathways that originated in the deep layers, and received feedforward-like projections from areas of greater laminar differentiation, which emanated from the upper layers. Our results are consistent with the Structural Model, which relates the density and laminar distribution of connections to the relationship of the laminar structure between the linked areas. These connections were viewed in the context of the inhibitory microenvironment of A28, which is the key recipient of pathways from the cortex and of the output of hippocampus. Our findings revealed a higher population of calretinin (CR)-expressing neurons in EC, with a significantly higher density in its lateral division. Medial EC had a higher density of CR neurons in the deep layers, particularly in layer Va. In contrast, parvalbumin (PV) neurons were more densely distributed in the deep layers of the lateral subdivisions of rostral EC, especially in layer Va, whereas the densities of calbindin (CB) neurons in the medial and lateral EC were comparable in all layers, except for layer IIIa, in which medial EC had a higher CB population than the lateral. The pattern of connections in the inhibitory microenvironment of EC, which sends and receives input from the hippocampus, may shed light on signal propagation in this network associated with diverse aspects of memory, and disruptions in neurologic and psychiatric diseases that affect this region.

Convergent Circuit Computation for Categorization in the Brains of Primates and Songbirds

Categorization is crucial for behavioral flexibility because it enables animals to group stimuli into meaningful classes that can easily be generalized to new circumstances. A most abstract quantitative category is set size, the number of elements in a set. This review explores how categorical number representations are realized by the operations of excitatory and inhibitory neurons in associative telencephalic microcircuits in primates and songbirds. Despite the independent evolution of the primate prefrontal cortex and the avian nidopallium caudolaterale, the neuronal computations of these associative pallial circuits show surprising correspondence. Comparing cellular functions in distantly related taxa can inform about the evolutionary principles of circuit computations for cognition in distinctly but convergently realized brain structures.

Distinct neuronal representation of small and large numbers in the human medial temporal lobe

Whether small numerical quantities are represented by a special subitizing system that is distinct from a large-number estimation system has been debated for over a century. Here we show that two separate neural mechanisms underlie the representation of small and large numbers. We performed single neuron recordings in the medial temporal lobe of neurosurgical patients judging numbers. We found a boundary in neuronal coding around number 4 that correlates with the behavioural transition from subitizing to estimation. In the subitizing range, neurons showed superior tuning selectivity accompanied by suppression effects suggestive of surround inhibition as a selectivity-increasing mechanism. In contrast, tuning selectivity decreased with increasing numbers beyond 4, characterizing a ratio-dependent number estimation system. The two systems with the coding boundary separating them were also indicated using decoding and clustering analyses. The identified small-number subitizing system could be linked to attention and working memory that show comparable capacity limitations.

Neural energy computations based on Hodgkin-Huxley models bridge abnormal neuronal activities and energy consumption patterns of major depressive disorder

Limited by the current experimental techniques and neurodynamical models, the dysregulation mechanisms of decision-making related neural circuits in major depressive disorder (MDD) are still not clear. In this paper, we proposed a neural coding methodology using energy to further investigate it, which has been proven to strongly complement the neurodynamical methodology. We augmented the previous neural energy calculation method, and applied it to our VTA-NAc-mPFC neurodynamical H-H models. We particularly focused on the peak power and energy consumption of abnormal ion channel (ionic) currents under different concentrations of dopamine input, and investigated the abnormal energy consumption patterns for the MDD group. The results revealed that the energy consumption of medium spiny neurons (MSNs) in the NAc region were lower in the MDD group than that of the normal control group despite having the same firing frequencies, peak action potentials, and average membrane potentials in both groups. Dopamine concentration was also positively correlated with the energy consumption of the pyramidal neurons, but the patterns of different interneuron types were distinct. Additionally, the ratio of mPFC's energy consumption to total energy consumption of the whole network in MDD group was lower than that in normal control group, revealing that the mPFC region in MDD group encoded less neural information, which matched the energy consumption patterns of BOLD-fMRI results. It was also in line with the behavioral characteristics that MDD patients demonstrated in the form of reward insensitivity during decision-making tasks. In conclusion, the model in this paper was the first neural network energy computational model for MDD, which showed success in explaining its dynamical mechanisms with an energy consumption perspective. To build on this, we demonstrated that energy consumption levels can be used as a potential indicator for MDD, which also showed a promising pipeline to use an energy methodology for studying other neuropsychiatric disorders.

γ And β Band Oscillation in Working Memory Given Sequential or Concurrent Multiple Items: A Spiking Network Model

Working memory (WM) can maintain sequential and concurrent information, and the load enhances the γ band oscillation during the delay period. To provide a unified account for these phenomena in working memory, we investigated a continuous network model consisting of pyramidal cells, high-threshold fast-spiking interneurons (FS), and low-threshold nonfast-spiking interneurons (nFS) for working memory of sequential and concurrent directional cues. Our model exhibits the γ (30-100 Hz) and β (10-30 Hz) band oscillation during the retention of both concurrent cues and sequential cues. We found that the β oscillation results from the interaction between pyramidal cells and nFS, whereas the γ oscillation emerges from the interaction between pyramidal cells and FS because of the strong excitation elicited by cue presentation, shedding light on the mechanism underlying the enhancement of γ power in many cognitive executions.

Laminar-Specific Alterations in Calbindin-Positive Boutons in the Prefrontal Cortex of Subjects With Schizophrenia

BACKGROUND

Cognitive deficits in schizophrenia are associated with altered GABA (gamma-aminobutyric acid) neurotransmission in the prefrontal cortex (PFC). GABA neurotransmission requires GABA synthesis by 2 isoforms of glutamic acid decarboxylase (GAD65 and GAD67) and packaging by the vesicular GABA transporter (vGAT). Current postmortem findings suggest that GAD67 messenger RNA is lower in a subset of the calbindin-expressing (CB+) class of GABA neurons in schizophrenia. Hence, we assessed if CB+ GABA neuron boutons are affected in schizophrenia.

METHODS

For 20 matched pairs of subjects with schizophrenia and unaffected comparison subjects, PFC tissue sections were immunolabeled for vGAT, CB, GAD67, and GAD65. The density of CB+ GABA boutons and levels of the 4 proteins per bouton were quantified.

RESULTS

Some CB+ GABA boutons contained both GAD65 and GAD67 (GAD65+/GAD67+), whereas others contained only GAD65 (GAD65+) or GAD67 (GAD67+). In schizophrenia, vGAT+/CB+/GAD65+/GAD67+ bouton density was not altered, vGAT+/CB+/GAD65+ bouton density was 86% higher in layers 2/superficial 3 (L2/3s), and vGAT+/CB+/GAD67+ bouton density was 36% lower in L5-6. Bouton GAD levels were differentially altered across bouton types and layers. In schizophrenia, the sum of GAD65 and GAD67 levels in vGAT+/CB+/GAD65+/GAD67+ boutons was 36% lower in L6, GAD65 levels were 51% higher in vGAT+/CB+/GAD65+ boutons in L2, and GAD67 levels in vGAT+/CB+/GAD67+ boutons were 30% to 46% lower in L2/3s-6.

CONCLUSIONS

These findings indicate that schizophrenia-associated alterations in the strength of inhibition from CB+ GABA neurons in the PFC differ across cortical layers and bouton classes, suggesting complex contributions to PFC dysfunction and cognitive impairments in schizophrenia.

The MIND diet, brain transcriptomic alterations, and dementia

Identifying novel mechanisms underlying dementia is critical to improving prevention and treatment. As an approach to mechanistic discovery, we investigated whether MIND diet (Mediterranean-DASH Diet Intervention for Neurodegenerative Delay), a consistent risk factor for dementia, is correlated with a specific profile of cortical gene expression, and whether such a transcriptomic profile is associated with dementia, in the Religious Orders Study (ROS) and Rush Memory and Aging Project (MAP). RNA sequencing (RNA-Seq) was conducted in postmortem dorsolateral prefrontal cortex tissue from 1,204 deceased participants; neuropsychological assessments were performed annually prior to death. In a subset of 482 participants, diet was assessed ~6 years before death using a validated food-frequency questionnaire; in these participants, using elastic net regression, we identified a transcriptomic profile, consisting of 50 genes, significantly correlated with MIND diet score (P=0.001). In multivariable analysis of the remaining 722 individuals, higher transcriptomic score of MIND diet was associated with slower annual rate of decline in global cognition (β=0.011 per standard deviation increment in transcriptomic profile score, P=0.003) and lower odds of dementia (odds ratio [OR] =0.76, P=0.0002). Cortical expression of several genes appeared to mediate the association between MIND diet and dementia, including TCIM, whose expression in inhibitory neurons and oligodendrocytes was associated with dementia in a subset of 424 individuals with single-nuclei RNA-seq data. In a secondary Mendelian randomization analysis, genetically predicted transcriptomic profile score was associated with dementia (OR=0.93, P=0.04). Our study suggests that associations between diet and cognitive health may involve brain molecular alterations at the transcriptomic level. Investigating brain molecular alterations related to diet may inform the identification of novel pathways underlying dementia.

Optogenetic manipulation of inhibitory interneurons can be used to validate a model of spatiotemporal sequence learning

The brain uses temporal information to link discrete events into memory structures supporting recognition, prediction, and a wide variety of complex behaviors. It is still an open question how experience-dependent synaptic plasticity creates memories including temporal and ordinal information. Various models have been proposed to explain how this could work, but these are often difficult to validate in a living brain. A recent model developed to explain sequence learning in the visual cortex encodes intervals in recurrent excitatory synapses and uses a learned offset between excitation and inhibition to generate precisely timed "messenger" cells that signal the end of an instance of time. This mechanism suggests that the recall of stored temporal intervals should be particularly sensitive to the activity of inhibitory interneurons that can be easily targeted in vivo with standard optogenetic tools. In this work we examined how simulated optogenetic manipulations of inhibitory cells modifies temporal learning and recall based on these mechanisms. We show that disinhibition and excess inhibition during learning or testing cause characteristic errors in recalled timing that could be used to validate the model in vivo using either physiological or behavioral measurements.

Predicted utility modulates working memory fidelity in the brain

The predicted utility of information stored in working memory (WM) is hypothesized to influence the strategic allocation of WM resources. Prior work has shown that when information is prioritized, it is remembered with greater precision relative to other remembered items. However, these paradigms often complicate interpretation of the effects of predicted utility on item fidelity due to a concurrent memory load. Likewise, no fMRI studies have examined whether the predicted utility of an item modulates fidelity in the neural representation of items during the memory delay without a concurrent load. In the current study, we used fMRI to investigate whether predicted utility influences fidelity of WM representations in the brain. Using a generative model multivoxel analysis approach to estimate the quality of remembered representations across predicted utility conditions, we observed that items with greater predicted utility are maintained in memory with greater fidelity, even when they are the only item being maintained. Further, we found that this pattern follows a parametric relationship where more predicted utility corresponded to greater fidelity. These precision differences could not be accounted for based on a redistribution of resources among already-remembered items. Rather, we interpret these results in terms of a gating mechanism that allows for pre-allocation of resources based on predicted value alone. This evidence supports a theoretical distinction between resource allocation that occurs as a result of load and resource pre-allocation that occurs as a result of predicted utility.

Functional architecture of executive control and associated event-related potentials in macaques

The medial frontal cortex (MFC) enables executive control by monitoring relevant information and using it to adapt behavior. In macaques performing a saccade countermanding (stop-signal) task, we simultaneously recorded electrical potentials over MFC and neural spiking across all layers of the supplementary eye field (SEF). We report the laminar organization of neurons enabling executive control by monitoring the conflict between incompatible responses, the timing of events, and sustaining goal maintenance. These neurons were a mix of narrow-spiking and broad-spiking found in all layers, but those predicting the duration of control and sustaining the task goal until the release of operant control were more commonly narrow-spiking neurons confined to layers 2 and 3 (L2/3). We complement these results with evidence for a monkey homolog of the N2/P3 event-related potential (ERP) complex associated with response inhibition. N2 polarization varied with error-likelihood and P3 polarization varied with the duration of expected control. The amplitude of the N2 and P3 were predicted by the spike rate of different classes of neurons located in L2/3 but not L5/6. These findings reveal features of the cortical microcircuitry supporting executive control and producing associated ERPs.

Age-dependent increased sag amplitude in human pyramidal neurons dampens baseline cortical activity

Aging involves various neurobiological changes, although their effect on brain function in humans remains poorly understood. The growing availability of human neuronal and circuit data provides opportunities for uncovering age-dependent changes of brain networks and for constraining models to predict consequences on brain activity. Here we found increased sag voltage amplitude in human middle temporal gyrus layer 5 pyramidal neurons from older subjects and captured this effect in biophysical models of younger and older pyramidal neurons. We used these models to simulate detailed layer 5 microcircuits and found lower baseline firing in older pyramidal neuron microcircuits, with minimal effect on response. We then validated the predicted reduced baseline firing using extracellular multielectrode recordings from human brain slices of different ages. Our results thus report changes in human pyramidal neuron input integration properties and provide fundamental insights into the neuronal mechanisms of altered cortical excitability and resting-state activity in human aging.

Cognitive Dysfunction and Prefrontal Cortical Circuit Alterations in Schizophrenia: Developmental Trajectories

Individuals with schizophrenia (SZ) exhibit cognitive performance below expected levels based on familial cognitive aptitude. One such cognitive process, working memory (WM), is robustly impaired in SZ. These WM impairments, which emerge over development during the premorbid and prodromal stages of SZ, appear to reflect alterations in the neural circuitry of the dorsolateral prefrontal cortex. Within the dorsolateral prefrontal cortex, a microcircuit formed by reciprocal connections between excitatory layer 3 pyramidal neurons and inhibitory parvalbumin basket cells (PVBCs) appears to be a key neural substrate for WM. Postmortem human studies indicate that both layer 3 pyramidal neurons and PVBCs are altered in SZ, suggesting that levels of excitation and inhibition are lower in the microcircuit. Studies in monkeys indicate that features of both cell types exhibit distinctive postnatal developmental trajectories. Together, the results of these studies suggest a model in which 1) genetic and/or early environmental insults to excitatory signaling in layer 3 pyramidal neurons give rise to cognitive impairments during the prodromal phase of SZ and evoke compensatory changes in inhibition that alter the developmental trajectories of PVBCs, and 2) synaptic pruning during adolescence further lowers excitatory activity to a level that exceeds the compensatory capacity of PVBC inhibition, leading to a failure of the normal maturational improvements in WM during the prodromal and early clinical stages of SZ. Findings that support as well as challenge this model are discussed.

Dopamine-Mediated Major Depressive Disorder in the Neural Circuit of Ventral Tegmental Area-Nucleus Accumbens-Medial Prefrontal Cortex: From Biological Evidence to Computational Models

Major depressive disorder (MDD) is a serious psychiatric disorder, with an increasing incidence in recent years. The abnormal dopaminergic pathways of the midbrain cortical and limbic system are the key pathological regions of MDD, particularly the ventral tegmental area- nucleus accumbens- medial prefrontal cortex (VTA-NAc-mPFC) neural circuit. MDD usually occurs with the dysfunction of dopaminergic neurons in VTA, which decreases the dopamine concentration and metabolic rate in NAc/mPFC brain regions. However, it has not been fully explained how abnormal dopamine concentration levels affect this neural circuit dynamically through the modulations of ion channels and synaptic activities. We used Hodgkin-Huxley and dynamical receptor binding model to establish this network, which can quantitatively explain neural activity patterns observed in MDD with different dopamine concentrations by changing the kinetics of some ion channels. The simulation replicated some important pathological patterns of MDD at the level of neurons and circuits with low dopamine concentration, such as the decreased action potential frequency in pyramidal neurons of mPFC with significantly reduced burst firing frequency. The calculation results also revealed that NaP and KS channels of mPFC pyramidal neurons played key roles in the functional regulation of this neural circuit. In addition, we analyzed the synaptic currents and local field potentials to explain the mechanism of MDD from the perspective of dysfunction of excitation-inhibition balance, especially the disinhibition effect in the network. The significance of this article is that we built the first computational model to illuminate the effect of dopamine concentrations for the NAc-mPFC-VTA circuit between MDD and normal groups, which can be used to quantitatively explain the results of existing physiological experiments, predict the results for unperformed experiments and screen possible drug targets.

Theory of the Multiregional Neocortex: Large-Scale Neural Dynamics and Distributed Cognition

The neocortex is a complex neurobiological system with many interacting regions. How these regions work together to subserve flexible behavior and cognition has become increasingly amenable to rigorous research. Here, I review recent experimental and theoretical work on the modus operandi of a multiregional cortex. These studies revealed several general principles for the neocortical interareal connectivity, low-dimensional macroscopic gradients of biological properties across cortical areas, and a hierarchy of timescales for information processing. Theoretical work suggests testable predictions regarding differential excitation and inhibition along feedforward and feedback pathways in the cortical hierarchy. Furthermore, modeling of distributed working memory and simple decision-making has given rise to a novel mathematical concept, dubbed bifurcation in space, that potentially explains how different cortical areas, with a canonical circuit organization but gradients of biological heterogeneities, are able to subserve their respective (e.g., sensory coding versus executive control) functions in a modularly organized brain.

Selective Inhibitory Circuit Dysfunction after Chronic Frontal Lobe Contusion

Traumatic brain injury (TBI) is a leading cause of neurologic disability; the most common deficits affect prefrontal cortex-dependent functions such as attention, working memory, social behavior, and mental flexibility. Despite this prevalence, little is known about the pathophysiology that develops in frontal cortical microcircuits after TBI. We investigated whether alterations in subtype-specific inhibitory circuits are associated with cognitive inflexibility in a mouse model of frontal lobe contusion in both male and female mice that recapitulates aberrant mental flexibility as measured by deficits in rule reversal learning. Using patch-clamp recordings and optogenetic stimulation, we identified selective vulnerability in the non-fast-spiking and somatostatin-expressing (SOM+) subtypes of inhibitory neurons in layer V of the orbitofrontal cortex 2 months after injury. These subtypes exhibited reduced intrinsic excitability and a decrease in their synaptic output onto pyramidal neurons, respectively. By contrast, the fast-spiking and parvalbumin-expressing interneurons did not show changes in intrinsic excitability or synaptic output, respectively. Impairments in non-fast-spiking/SOM+ inhibitory circuit function were also associated with network hyperexcitability. These findings provide evidence for selective disruptions within specific inhibitory microcircuits that may guide the development of novel therapeutics for TBI.SIGNIFICANCE STATEMENT TBI frequently leads to chronic deficits in cognitive and behavioral functions that involve the prefrontal cortex, yet the maladaptive changes that occur in these cortical microcircuits are unknown. Our data indicate that alterations in subtype-specific inhibitory circuits, specifically vulnerability in the non-fast-spiking/somatostatin-expressing interneurons, occurs in the orbitofrontal cortex in the context of chronic deficits in reversal learning. These neurons exhibit reduced excitability and synaptic output, whereas the other prominent inhibitory population in layer V, the fast-spiking/parvalbumin-expressing interneurons as well as pyramidal neurons are not affected. Our work offers mechanistic insight into the subtype-specific function of neurons that may contribute to mental inflexibility after TBI.

Functional alterations in large-scale resting-state networks of amyotrophic lateral sclerosis: A multi-site study across Canada and the United States

Amyotrophic lateral sclerosis (ALS) is a multisystem neurodegenerative disorder characterized by progressive degeneration of upper motor neurons and lower motor neurons, and frontotemporal regions resulting in impaired bulbar, limb, and cognitive function. Magnetic resonance imaging studies have reported cortical and subcortical brain involvement in the pathophysiology of ALS. The present study investigates the functional integrity of resting-state networks (RSNs) and their importance in ALS. Intra- and inter-network resting-state functional connectivity (Rs-FC) was examined using an independent component analysis approach in a large multi-center cohort. A total of 235 subjects (120 ALS patients; 115 healthy controls (HC) were recruited across North America through the Canadian ALS Neuroimaging Consortium (CALSNIC). Intra-network and inter-network Rs-FC was evaluated by the FSL-MELODIC and FSLNets software packages. As compared to HC, ALS patients displayed higher intra-network Rs-FC in the sensorimotor, default mode, right and left fronto-parietal, and orbitofrontal RSNs, and in previously undescribed networks including auditory, dorsal attention, basal ganglia, medial temporal, ventral streams, and cerebellum which negatively correlated with disease severity. Furthermore, ALS patients displayed higher inter-network Rs-FC between the orbitofrontal and basal ganglia RSNs which negatively correlated with cognitive impairment. In summary, in ALS there is an increase in intra- and inter-network functional connectivity of RSNs underpinning both motor and cognitive impairment. Moreover, the large multi-center CALSNIC dataset permitted the exploration of RSNs in unprecedented detail, revealing previously undescribed network involvement in ALS.

Neural circuit mechanisms of hierarchical sequence learning tested on large-scale recording data

The brain performs various cognitive functions by learning the spatiotemporal salient features of the environment. This learning requires unsupervised segmentation of hierarchically organized spike sequences, but the underlying neural mechanism is only poorly understood. Here, we show that a recurrent gated network of neurons with dendrites can efficiently solve difficult segmentation tasks. In this model, multiplicative recurrent connections learn a context-dependent gating of dendro-somatic information transfers to minimize error in the prediction of somatic responses by the dendrites. Consequently, these connections filter the redundant input features represented by the dendrites but unnecessary in the given context. The model was tested on both synthetic and real neural data. In particular, the model was successful for segmenting multiple cell assemblies repeating in large-scale calcium imaging data containing thousands of cortical neurons. Our results suggest that recurrent gating of dendro-somatic signal transfers is crucial for cortical learning of context-dependent segmentation tasks.

A Simplified Plasticity Model Based on Synaptic Tagging and Capture Theory: Simplified STC

The formation and consolidation of memory play a vital role for survival in an ever-changing environment. In the brain, the change and stabilization of potentiated and depressed synapses are the neural basis of memory formation and maintenance. These changes can be induced by rather short stimuli (only a few seconds or even less) but should then be stable for months or years. Recently, the neural mechanism of conversion from rapid change during the early phase of synaptic plasticity into a stable memory trace in the late phase of synaptic plasticity is more and more clear at the protein and molecular levels, among which synaptic tagging and capture (STC) theory is one of the most popular theories. According to the STC theory, the change and stabilization of synaptic efficiency mainly depend on three processes related to calcium concentration, including synaptic tagging, synthesis of plasticity-related product (PRP), and the capture of PRP by tagged synapse. Based on the STC theory, several computational models are proposed. However, these models hardly take simplicity and biological interpretability into account simultaneously. Here, we propose a simplified STC (SM-STC) model to address this issue. In the SM-STC model, the concentration of calcium ion in each neuronal compartment and synapse is first calculated, and then the tag state of synapse and PRP are updated, and the coupling effect of tagged synapse and PRP is further considered to determine the plasticity state of the synapse, either potentiation or depression. We simulated the Schaffer collaterals pathway of the hippocampus targeting a multicompartment CA1 neuron for several hours of biological time. The results show that the SM-STC model can produce a broad range of experimental phenomena known in the physiological experiments, including long-term potentiation induced by high-frequency stimuli, long-term depression induced by low-frequency stimuli, and cross-capture with two stimuli separated by a delay. Thus, the SM-STC model proposed in this study provides an effective learning rule for brain-like computation on the premise of ensuring biological plausibility and computational efficiency.

The prefrontal cortex, pathological anxiety, and anxiety disorders

Anxiety is experienced in response to threats that are distal or uncertain, involving changes in one's subjective state, autonomic responses, and behavior. Defensive and physiologic responses to threats that involve the amygdala and brainstem are conserved across species. While anxiety responses typically serve an adaptive purpose, when excessive, unregulated, and generalized, they can become maladaptive, leading to distress and avoidance of potentially threatening situations. In primates, anxiety can be regulated by the prefrontal cortex (PFC), which has expanded in evolution. This prefrontal expansion is thought to underlie primates' increased capacity to engage high-level regulatory strategies aimed at coping with and modifying the experience of anxiety. The specialized primate lateral, medial, and orbital PFC sectors are connected with association and limbic cortices, the latter of which are connected with the amygdala and brainstem autonomic structures that underlie emotional and physiological arousal. PFC pathways that interface with distinct inhibitory systems within the cortex, the amygdala, or the thalamus can regulate responses by modulating neuronal output. Within the PFC, pathways connecting cortical regions are poised to reduce noise and enhance signals for cognitive operations that regulate anxiety processing and autonomic drive. Specialized PFC pathways to the inhibitory thalamic reticular nucleus suggest a mechanism to allow passage of relevant signals from thalamus to cortex, and in the amygdala to modulate the output to autonomic structures. Disruption of specific nodes within the PFC that interface with inhibitory systems can affect the negative bias, failure to regulate autonomic arousal, and avoidance that characterize anxiety disorders.

Mechanisms underlying dorsolateral prefrontal cortex contributions to cognitive dysfunction in schizophrenia

Kraepelin, in his early descriptions of schizophrenia (SZ), characterized the illness as having "an orchestra without a conductor." Kraepelin further speculated that this "conductor" was situated in the frontal lobes. Findings from multiple studies over the following decades have clearly implicated pathology of the dorsolateral prefrontal cortex (DLPFC) as playing a central role in the pathophysiology of SZ, particularly with regard to key cognitive features such as deficits in working memory and cognitive control. Following an overview of the cognitive mechanisms associated with DLPFC function and how they are altered in SZ, we review evidence from an array of neuroscientific approaches addressing how these cognitive impairments may reflect the underlying pathophysiology of the illness. Specifically, we present evidence suggesting that alterations of the DLPFC in SZ are evident across a range of spatial and temporal resolutions: from its cellular and molecular architecture, to its gross structural and functional integrity, and from millisecond to longer timescales. We then present an integrative model based upon how microscale changes in neuronal signaling in the DLPFC can influence synchronized patterns of neural activity to produce macrocircuit-level alterations in DLPFC activation that ultimately influence cognition and behavior. We conclude with a discussion of initial efforts aimed at targeting DLPFC function in SZ, the clinical implications of those efforts, and potential avenues for future development.

Functional and pharmacological role of the dopamine D4 receptor and its polymorphic variants

The functional and pharmacological significance of the dopamine D₄ receptor (D₄R) has remained the least well understood of all the dopamine receptor subtypes. Even more enigmatic has been the role of the very prevalent human DRD4 gene polymorphisms in the region that encodes the third intracellular loop of the receptor. The most common polymorphisms encode a D₄R with 4 or 7 repeats of a proline-rich sequence of 16 amino acids (D_4.4R and D_4.7R). DRD4 polymorphisms have been associated with individual differences linked to impulse control-related neuropsychiatric disorders, with the most consistent associations established between the gene encoding D_4.7R and attention-deficit hyperactivity disorder (ADHD) and substance use disorders. The function of D₄R and its polymorphic variants is being revealed by addressing the role of receptor heteromerization and the relatively avidity of norepinephrine for D₄R. We review the evidence conveying a significant and differential role of D_4.4R and D_4.7R in the dopaminergic and noradrenergic modulation of the frontal cortico-striatal pyramidal neuron, with implications for the moderation of constructs of impulsivity as personality traits. This differential role depends on their ability to confer different properties to adrenergic α_2A receptor (α_2AR)-D₄R heteromers and dopamine D₂ receptor (D₂R)-D₄R heteromers, preferentially localized in the perisomatic region of the frontal cortical pyramidal neuron and its striatal terminals, respectively. We also review the evidence to support the D₄R as a therapeutic target for ADHD and other impulse-control disorders, as well as for restless legs syndrome.

Neural Substrates of Visual Perception and Working Memory: Two Sides of the Same Coin or Two Different Coins?

Visual perception occurs when a set of physical signals emanating from the environment enter the visual system and the brain interprets such signals as a percept. Visual working memory occurs when the brain produces and maintains a mental representation of a percept while the physical signals corresponding to that percept are not available. Early studies in humans and non-human primates demonstrated that lesions of the prefrontal cortex impair performance during visual working memory tasks but not during perceptual tasks. These studies attributed a fundamental role in working memory and a lesser role in visual perception to the prefrontal cortex. Indeed, single cell recording studies have found that neurons in the lateral prefrontal cortex of macaques encode working memory representations via persistent firing, validating the results of lesion studies. However, other studies have reported that neurons in some areas of the parietal and temporal lobe-classically associated with visual perception-similarly encode working memory representations via persistent firing. This prompted a line of enquiry about the role of the prefrontal and other associative cortices in working memory and perception. Here, we review evidence from single neuron studies in macaque monkeys examining working memory representations across different areas of the visual hierarchy and link them to studies examining the role of the same areas in visual perception. We conclude that neurons in early visual areas of both ventral (V1-V2-V4) and dorsal (V1-V3-MT) visual pathways of macaques mainly encode perceptual signals. On the other hand, areas downstream from V4 and MT contain subpopulations of neurons that encode both perceptual and/or working memory signals. Differences in cortical architecture (neuronal types, layer composition, and synaptic density and distribution) may be linked to the differential encoding of perceptual and working memory signals between early visual areas and higher association areas.

Sensory-motor cortices shape functional connectivity dynamics in the human brain

Large-scale biophysical circuit models provide mechanistic insights into the micro-scale and macro-scale properties of brain organization that shape complex patterns of spontaneous brain activity. We developed a spatially heterogeneous large-scale dynamical circuit model that allowed for variation in local synaptic properties across the human cortex. Here we show that parameterizing local circuit properties with both anatomical and functional gradients generates more realistic static and dynamic resting-state functional connectivity (FC). Furthermore, empirical and simulated FC dynamics demonstrates remarkably similar sharp transitions in FC patterns, suggesting the existence of multiple attractors. Time-varying regional fMRI amplitude may track multi-stability in FC dynamics. Causal manipulation of the large-scale circuit model suggests that sensory-motor regions are a driver of FC dynamics. Finally, the spatial distribution of sensory-motor drivers matches the principal gradient of gene expression that encompasses certain interneuron classes, suggesting that heterogeneity in excitation-inhibition balance might shape multi-stability in FC dynamics.

A dopamine gradient controls access to distributed working memory in the large-scale monkey cortex

Dopamine is required for working memory, but how it modulates the large-scale cortex is unknown. Here, we report that dopamine receptor density per neuron, measured by autoradiography, displays a macroscopic gradient along the macaque cortical hierarchy. This gradient is incorporated in a connectome-based large-scale cortex model endowed with multiple neuron types. The model captures an inverted U-shaped dependence of working memory on dopamine and spatial patterns of persistent activity observed in over 90 experimental studies. Moreover, we show that dopamine is crucial for filtering out irrelevant stimuli by enhancing inhibition from dendrite-targeting interneurons. Our model revealed that an activity-silent memory trace can be realized by facilitation of inter-areal connections and that adjusting cortical dopamine induces a switch from this internal memory state to distributed persistent activity. Our work represents a cross-level understanding from molecules and cell types to recurrent circuit dynamics underlying a core cognitive function distributed across the primate cortex.

50 years of mnemonic persistent activity: quo vadis?

Half a century ago persistent spiking activity in the neocortex was discovered to be a neural substrate of working memory. Since then scientists have sought to understand this core cognitive function across biological and computational levels. Studies are reviewed here that cumulatively lend support to a synaptic theory of recurrent circuits for mnemonic persistent activity that depends on various cellular and network substrates and is mathematically described by a multiple-attractor network model. Crucially, a mnemonic attractor state of the brain is consistent with temporal variations and heterogeneity across neurons in a subspace of population activity. Persistent activity should be broadly understood as a contrast to decaying transients. Mechanisms in the absence of neural firing ('activity-silent state') are suitable for passive short-term memory but not for working memory - which is characterized by executive control for filtering out distractors, limited capacity, and internal manipulation of information.

Emergence of prefrontal neuron maturation properties by training recurrent neural networks in cognitive tasks

Working memory and response inhibition are functions that mature relatively late in life, after adolescence, paralleling the maturation of the prefrontal cortex. The link between behavioral and neural maturation is not obvious, however, making it challenging to understand how neural activity underlies the maturation of cognitive function. To gain insights into the nature of observed changes in prefrontal activity between adolescence and adulthood, we investigated the progressive changes in unit activity of recurrent neural networks as they were trained to perform working memory and response inhibition tasks. These included increased delay period activity during working memory tasks and increased activation in antisaccade tasks. These findings reveal universal properties underlying the neuronal computations behind cognitive tasks and explicate the nature of changes that occur as the result of developmental maturation.

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Properties of RNN networks during training offer insights in prefrontal maturation

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Fully trained networks exhibit higher levels of activity in working memory tasks

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Trained networks also exhibit higher activation in antisaccade tasks

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Partially trained RNNs can generate accurate predictions of immature PFC activity

Working Memory: From Neural Activity to the Sentient Mind

Working memory (WM) is the ability to maintain and manipulate information in the conscious mind over a timescale of seconds. This ability is thought to be maintained through the persistent discharges of neurons in a network of brain areas centered on the prefrontal cortex, as evidenced by neurophysiological recordings in nonhuman primates, though both the localization and the neural basis of WM has been a matter of debate in recent years. Neural correlates of WM are evident in species other than primates, including rodents and corvids. A specialized network of excitatory and inhibitory neurons, aided by neuromodulatory influences of dopamine, is critical for the maintenance of neuronal activity. Limitations in WM capacity and duration, as well as its enhancement during development, can be attributed to properties of neural activity and circuits. Changes in these factors can be observed through training-induced improvements and in pathological impairments. WM thus provides a prototypical cognitive function whose properties can be tied to the spiking activity of brain neurons. © 2021 American Physiological Society. Compr Physiol 11:1-41, 2021.

Differential Excitability of PV and SST Neurons Results in Distinct Functional Roles in Inhibition Stabilization of Up States

Up states are the best studied example of an emergent neural dynamic regime. Computational models based on a single class of inhibitory neurons indicate that Up states reflect bistable dynamic systems in which positive feedback is stabilized by strong inhibition and predict a paradoxical effect in which increased drive to inhibitory neurons results in decreased inhibitory activity. To date, however, computational models have not incorporated empirically defined properties of parvalbumin (PV) and somatostatin (SST) neurons. Here we first experimentally characterized the frequency-current (F-I) curves of pyramidal (Pyr), PV, and SST neurons from mice of either sex, and confirmed a sharp difference between the threshold and slopes of PV and SST neurons. The empirically defined F-I curves were incorporated into a three-population computational model that simulated the empirically derived firing rates of pyramidal, PV, and SST neurons. Simulations revealed that the intrinsic properties were sufficient to predict that PV neurons are primarily responsible for generating the nontrivial fixed points representing Up states. Simulations and analytical methods demonstrated that while the paradoxical effect is not obligatory in a model with two classes of inhibitory neurons, it is present in most regimes. Finally, experimental tests validated predictions of the model that the Pyr ↔ PV inhibitory loop is stronger than the Pyr ↔ SST loop.SIGNIFICANCE STATEMENT Many cortical computations, such as working memory, rely on the local recurrent excitatory connections that define cortical circuit motifs. Up states are among the best studied examples of neural dynamic regimes that rely on recurrent excitatory excitation. However, this positive feedback must be held in check by inhibition. To address the relative contribution of PV and SST neurons, we characterized the intrinsic input-output differences between these classes of inhibitory neurons and, using experimental and theoretical methods, show that the higher threshold and gain of PV leads to a dominant role in network stabilization.

Deciphering how interneuron specific 3 cells control oriens lacunosum-moleculare cells to contribute to circuit function

The wide diversity of inhibitory cells across the brain makes them suitable to contribute to network dynamics in specialized fashions. However, the contributions of a particular inhibitory cell type in a behaving animal are challenging to untangle as one needs to both record cellular activities and identify the cell type being recorded. Thus, using computational modeling and theory to predict and hypothesize cell-specific contributions is desirable. Here, we examine potential contributions of interneuron-specific 3 (I-S3) cells - an inhibitory interneuron found in CA1 hippocampus that only targets other inhibitory interneurons - during simulated theta rhythms. We use previously developed multi-compartment models of oriens lacunosum-moleculare (OLM) cells, the main target of I-S3 cells, and explore how I-S3 cell inputs during in vitro and in vivo scenarios contribute to theta. We find that I-S3 cells suppress OLM cell spiking, rather than engender its spiking via post-inhibitory rebound mechanisms, and contribute to theta frequency spike resonance during simulated in vivo scenarios. To elicit recruitment similar to in vitro experiments, inclusion of disinhibited pyramidal cell inputs is necessary, implying that I-S3 cell firing broadens the window for pyramidal cell disinhibition. Using in vivo virtual networks, we show that I-S3 cells contribute to a sharpening of OLM cell recruitment at theta frequencies. Further, shifting the timing of I-S3 cell spiking due to external modulation shifts the timing of the OLM cell firing and thus disinhibitory windows. We propose a specialized contribution of I-S3 cells to create temporally precise coordination of modulation pathways.

Circuit mechanisms for cortical plasticity and learning

The cerebral cortex integrates sensory information with emotional states and internal representations to produce coherent percepts, form associations, and execute voluntary actions. For the cortex to optimize perception, its neuronal network needs to dynamically retrieve and encode new information. Over the last few decades, research has started to provide insight into how the cortex serves these functions. Building on classical Hebbian plasticity models, the latest hypotheses hold that throughout experience and learning, streams of feedforward, feedback, and modulatory information operate in selective and coordinated manners to alter the strength of synapses and ultimately change the response properties of cortical neurons. Here, we describe cortical plasticity mechanisms that involve the concerted action of feedforward and long-range feedback input onto pyramidal neurons as well as the implication of local disinhibitory circuit motifs in this process.

Inhibitory regulation of calcium transients in prefrontal dendritic spines is compromised by a nonsense Shank3 mutation

The SHANK3 gene encodes a postsynaptic scaffold protein in excitatory synapses, and its disruption is implicated in neurodevelopmental disorders such as Phelan-McDermid syndrome, autism spectrum disorder, and schizophrenia. Most studies of SHANK3 in the neocortex and hippocampus have focused on disturbances in pyramidal neurons. However, GABAergic interneurons likewise receive excitatory inputs and presumably would also be a target of constitutive SHANK3 perturbations. In this study, we characterize the prefrontal cortical microcircuit in awake mice using subcellular-resolution two-photon microscopy. We focused on a nonsense R1117X mutation, which leads to truncated SHANK3 and has been linked previously to cortical dysfunction. We find that R1117X mutants have abnormally elevated calcium transients in apical dendritic spines. The synaptic calcium dysregulation is due to a loss of dendritic inhibition via decreased NMDAR currents and reduced firing of dendrite-targeting somatostatin-expressing (SST) GABAergic interneurons. Notably, upregulation of the NMDAR subunit GluN2B in SST interneurons corrects the excessive synaptic calcium signals and ameliorates learning deficits in R1117X mutants. These findings reveal dendrite-targeting interneurons, and more broadly the inhibitory control of dendritic spines, as a key microcircuit mechanism compromised by the SHANK3 dysfunction.

Pyramidal cell subtype-dependent cortical oscillatory activity regulates motor learning

The cortex processes information through intricate circuitry and outputs to multiple brain areas by different sets of pyramidal cells (PCs). PCs form intra- and inter-laminar subnetworks, depending on PC projection subtypes. However, it remains unknown how individual PC subtypes are involved in cortical network activity and, thereby, in distinct brain functions. Here, we examined the effects of optogenetic manipulations of specific PC subtypes on network activity in the motor cortex. In layer V, the beta/gamma frequency band of oscillation was evoked by photostimulation, depending on PC subtypes. Our experimental and simulation results suggest that oscillatory activity is generated in reciprocal connections between pyramidal tract (PT) and fast-spiking cells. A similar frequency band was also observed in local field potentials during a pattern learning task. Manipulation of PT cell activity affected beta/gamma band power and learning. Our results suggest that PT cell-dependent oscillations play important roles in motor learning.

Otsuka and Kawaguchi investigate how manipulation of pyramidal cell subtypes in the motor cortex affects cortical network activity. Their findings suggest that pyramidal cell type cell-dependent oscillatory activity play an important role in motor learning.

Primate Spatial Memory Cells Become Tuned Early and Lose Tuning at Cell-Specific Times

Working memory, the ability to maintain and transform information, is critical for cognition. Spatial working memory is particularly well studied. The premier model for spatial memory is the continuous attractor network, which posits that cells maintain constant activity over memory periods. Alternative models propose complex dynamics that result in a variety of cell activity time courses. We recorded from neurons in the frontal eye fields and dorsolateral prefrontal cortex of 2 macaques during long (5-15 s) memory periods. We found that memory cells turn on early after stimulus presentation, sustain activity for distinct and fixed lengths of time, then turn off and stay off for the remainder of the memory period. These dynamics are more complex than the dynamics of a canonical bump attractor network model (either decaying or nondecaying) but more constrained than the dynamics of fully heterogeneous memory models. We speculate that memory may be supported by multiple attractor networks working in parallel, with each network having its own characteristic mean turn-off time such that mnemonic resources are gradually freed up over time.

Drifts in Prefrontal and Parietal Neuronal Activity Influence Working Memory Judgments

The dorsolateral prefrontal cortex (dlPFC) plays a critical role in spatial working memory and its activity predicts behavioral responses in delayed response tasks. Here, we addressed if this predictive ability extends to other working memory tasks and if it is present in other brain areas. We trained monkeys to remember the location of a stimulus and determine whether a second stimulus appeared at the same location or not. Neurophysiological recordings were performed in the dorsolateral prefrontal cortex and posterior parietal cortex (PPC). We hypothesized that random drifts causing the peak activity of the network to move away from the first stimulus location and toward the location of the second stimulus would result in categorical errors. Indeed, for both areas, in nonmatching trials, when the first stimulus appeared in a neuron's preferred location, the neuron showed significantly higher firing rates in correct than in error trials; and vice versa, when the first stimulus appeared at a nonpreferred location, activity in error trials was higher than in correct. The results indicate that the activity of both dlPFC and PPC neurons is predictive of categorical judgments of information maintained in working memory, and neuronal firing rate deviations are revealing of the contents of working memory.

A Connectomic Hypothesis for the Hominization of the Brain

Cognitive abilities of the human brain, including language, have expanded dramatically in the course of our recent evolution from nonhuman primates, despite only minor apparent changes at the gene level. The hypothesis we propose for this paradox relies upon fundamental features of human brain connectivity, which contribute to a characteristic anatomical, functional, and computational neural phenotype, offering a parsimonious framework for connectomic changes taking place upon the human-specific evolution of the genome. Many human connectomic features might be accounted for by substantially increased brain size within the global neural architecture of the primate brain, resulting in a larger number of neurons and areas and the sparsification, increased modularity, and laminar differentiation of cortical connections. The combination of these features with the developmental expansion of upper cortical layers, prolonged postnatal brain development, and multiplied nongenetic interactions with the physical, social, and cultural environment gives rise to categorically human-specific cognitive abilities including the recursivity of language. Thus, a small set of genetic regulatory events affecting quantitative gene expression may plausibly account for the origins of human brain connectivity and cognition.

Flexible Frequency Switching in Adult Mouse Visual Cortex Is Mediated by Competition Between Parvalbumin and Somatostatin Expressing Interneurons

Neuronal networks in rodent primary visual cortex (V1) can generate oscillations in different frequency bands depending on the network state and the level of visual stimulation. High-frequency gamma rhythms, for example, dominate the network's spontaneous activity in adult mice but are attenuated upon visual stimulation, during which the network switches to the beta band instead. The spontaneous local field potential (LFP) of juvenile mouse V1, however, mainly contains beta rhythms and presenting a stimulus does not elicit drastic changes in network oscillations. We study, in a spiking neuron network model, the mechanism in adult mice allowing for flexible switches between multiple frequency bands and contrast this to the network structure in juvenile mice that lack this flexibility. The model comprises excitatory pyramidal cells (PCs) and two types of interneurons: the parvalbumin-expressing (PV) and the somatostatinexpressing (SOM) interneuron. In accordance with experimental findings, the pyramidal-PV and pyramidal-SOM cell subnetworks are associated with gamma and beta oscillations, respectively. In our model, they are both generated via a pyramidal-interneuron gamma (PING) mechanism, wherein the PCs drive the oscillations. Furthermore, we demonstrate that large but not small visual stimulation activates SOM cells, which shift the frequency of resting-state gamma oscillations produced by the pyramidal-PV cell subnetwork so that beta rhythms emerge. Finally, we show that this behavior is obtained for only a subset of PV and SOM interneuron projection strengths, indicating that their influence on the PCs should be balanced so that they can compete for oscillatory control of the PCs. In sum, we propose a mechanism by which visual beta rhythms can emerge from spontaneous gamma oscillations in a network model of the mouse V1; for this mechanism to reproduce V1 dynamics in adult mice, balance between the effective strengths of PV and SOM cells is required.

Postnatal Development of Glutamate and GABA Transcript Expression in Monkey Visual, Parietal, and Prefrontal Cortices

Visuospatial working memory (vsWM) requires information transfer among multiple cortical regions, from primary visual (V1) to prefrontal (PFC) cortices. This information is conveyed via layer 3 glutamatergic neurons whose activity is regulated by gamma-aminobutyric acid (GABA)ergic interneurons. In layer 3 of adult human neocortex, molecular markers of glutamate neurotransmission were lowest in V1 and highest in PFC, whereas GABA markers had the reverse pattern. Here, we asked if these opposite V1-visual association cortex (V2)-posterior parietal cortex (PPC)-PFC gradients across the vsWM network are present in layer 3 of monkey neocortex, when they are established during postnatal development, and if they are specific to this layer. We quantified transcript levels of glutamate and GABA markers in layers 3 and 6 of four vsWM cortical regions in a postnatal developmental series of 30 macaque monkeys. In adult monkeys, glutamate transcript levels in layer 3 increased across V1-V2-PPC-PFC regions, whereas GABA transcripts showed the opposite V1-V2-PPC-PFC gradient. Glutamate transcripts established adult-like expression patterns earlier during postnatal development than GABA transcripts. These V1-V2-PPC-PFC gradients and developmental patterns were less evident in layer 6. These findings demonstrate that expression of glutamate and GABA transcripts differs across cortical regions and layers during postnatal development, revealing potential molecular substrates for vsWM functional maturation.

Pathways for Contextual Memory: The Primate Hippocampal Pathway to Anterior Cingulate Cortex

The anterior cingulate cortex (ACC) is one of the few prefrontal areas that receives robust direct hippocampal terminations. This pathway may enable current context and past experience to influence goal-directed actions and emotional regulation by prefrontal cortices. We investigated the still ill-understood organization of the pathway from anterior hippocampus to ACC (A24a, A25, A32) to identify laminar termination patterns and their postsynaptic excitatory and inhibitory targets from system to synapse in rhesus monkeys. The densest hippocampal terminations targeted posterior A25, a region that is involved in affective and autonomic regulation. Hippocampal terminations innervated mostly excitatory neurons (~90%), suggesting strong excitatory effects. Among the smaller fraction of inhibitory targets, hippocampal terminations in A25 preferentially innervated calretinin neurons, a pattern that differs markedly from rodents. Further, hippocampal terminations innervated spines with D1 receptors, particularly in the deep layers of A25, where D1 receptors are enriched in comparison with the upper layers. The proximity of hippocampal terminations to D1 receptors may enable dopamine to enhance information transfer from the hippocampus to A25 and contribute to dopaminergic influence downstream on goal-directed action and emotional control by prefrontal cortices, in processes that may be disrupted by excessive dopamine release during uncontrollable stress.