Morpho-electric diversity of human hippocampal CA1 pyramidal neurons.

Hippocampal pyramidal neuron activity underlies episodic memory and spatial navigation. Although extensively studied in rodents, extremely little is known about human hippocampal pyramidal neurons, even though the human hippocampus underwent strong evolutionary reorganization and shows lower theta rhythm frequencies. To test whether biophysical properties of human Cornu Amonis subfield 1 (CA1) pyramidal neurons can explain observed rhythms, we map the morpho-electric properties of individual CA1 pyramidal neurons in human, non-pathological hippocampal slices from neurosurgery. Human CA1 pyramidal neurons have much larger dendritic trees than mouse CA1 pyramidal neurons, have a large number of oblique dendrites, and resonate at 2.9 Hz, optimally tuned to human theta frequencies. Morphological and biophysical properties suggest cellular diversity along a multidimensional gradient rather than discrete clustering. Across the population, dendritic architecture and a large number of oblique dendrites consistently boost memory capacity in human CA1 pyramidal neurons by an order of magnitude compared to mouse CA1 pyramidal neurons.

Lateral hypothalamic GABAergic neurons encode alcohol memories.

In alcohol use disorder, the alcohol memories persist during abstinence, and exposure to stimuli associated with alcohol use can lead to relapse. This highlights the importance of investigating the neural substrates underlying not only relapse but also encoding and expression of alcohol memories. GABAergic neurons in the lateral hypothalamus (LH-GABA) have been shown to be critical for food-cue memories and motivation; however, the extent to which this role extends to alcohol-cue memories and motivations remains unexplored. In this study, we aimed to describe how alcohol-related memories are encoded and expressed in LH GABAergic neurons. Our first step was to monitor LH-GABA calcium transients during acquisition, extinction, and reinstatement of an alcohol-cue memory using fiber photometry. We trained the rats on a Pavlovian conditioning task, where one conditioned stimulus (CS+) predicted alcohol (20% EtOH) and another conditioned stimulus (CS-) had no outcome. We then extinguished this association through non-reinforced presentations of the CS+ and CS- and finally, in two different groups, we measured relapse under non-primed and alcohol-primed induced reinstatement. Our results show that initially both cues caused increased LH-GABA activity, and after learning only the alcohol cue increased LH-GABA activity. After extinction, this activity decreases, and we found no differences in LH-GABA activity during reinstatement in either group. Next, we inhibited LH-GABA neurons with optogenetics to show that activity of these neurons is necessary for the formation of an alcohol-cue association. These findings suggest that LH-GABA might be involved in attentional processes modulated by learning.

Human voltage-gated Na+ and K+ channel properties underlie sustained fast AP signaling.

Human cortical pyramidal neurons are large, have extensive dendritic trees, and yet have unexpectedly fast input-output properties: Rapid subthreshold synaptic membrane potential changes are reliably encoded in timing of action potentials (APs). Here, we tested whether biophysical properties of voltage-gated sodium (Na+) and potassium (K+) currents in human pyramidal neurons can explain their fast input-output properties. Human Na+ and K+ currents exhibited more depolarized voltage dependence, slower inactivation, and faster recovery from inactivation compared with their mouse counterparts. Computational modeling showed that despite lower Na+ channel densities in human neurons, the biophysical properties of Na+ channels resulted in higher channel availability and contributed to fast AP kinetics stability. Last, human Na+ channel properties also resulted in a larger dynamic range for encoding of subthreshold membrane potential changes. Thus, biophysical adaptations of voltage-gated Na+ and K+ channels enable fast input-output properties of large human pyramidal neurons.

Structural and functional specializations of human fast-spiking neurons support fast cortical signaling.

Fast-spiking interneurons (FSINs) provide fast inhibition that synchronizes neuronal activity and is critical for cognitive function. Fast synchronization frequencies are evolutionary conserved in the expanded human neocortex despite larger neuron-to-neuron distances that challenge fast input-output transfer functions of FSINs. Here, we test in human neurons from neurosurgery tissue, which mechanistic specializations of human FSINs explain their fast-signaling properties in human cortex. With morphological reconstructions, multipatch recordings, and biophysical modeling, we find that despite threefold longer dendritic path, human FSINs maintain fast inhibition between connected pyramidal neurons through several mechanisms: stronger synapse strength of excitatory inputs, larger dendrite diameter with reduced complexity, faster AP initiation, and faster and larger inhibitory output, while Na+ current activation/inactivation properties are similar. These adaptations underlie short input-output delays in fast inhibition of human pyramidal neurons through FSINs, explaining how cortical synchronization frequencies are conserved despite expanded and sparse network topology of human cortex.

Genes associated with cognitive ability and HAR show overlapping expression patterns in human cortical neuron types.

GWAS have identified numerous genes associated with human cognition but their cell type expression profiles in the human brain are unknown. These genes overlap with human accelerated regions (HARs) implicated in human brain evolution and might act on the same biological processes. Here, we investigated whether these gene sets are expressed in adult human cortical neurons, and how their expression relates to neuronal function and structure. We find that these gene sets are preferentially expressed in L3 pyramidal neurons in middle temporal gyrus (MTG). Furthermore, neurons with higher expression had larger total dendritic length (TDL) and faster action potential (AP) kinetics, properties previously linked to intelligence. We identify a subset of genes associated with TDL or AP kinetics with predominantly synaptic functions and high abundance of HARs.

Aquaporin-4 and GPRC5B: old and new players in controlling brain oedema.

Brain oedema is a life-threatening complication of various neurological conditions. Understanding molecular mechanisms of brain volume regulation is critical for therapy development. Unique insight comes from monogenic diseases characterized by chronic brain oedema, of which megalencephalic leukoencephalopathy with subcortical cysts (MLC) is the prototype. Variants in MLC1 or GLIALCAM, encoding proteins involved in astrocyte volume regulation, are the main causes of MLC. In some patients, the genetic cause remains unknown. We performed genetic studies to identify novel gene variants in MLC patients, diagnosed by clinical and MRI features, without MLC1 or GLIALCAM variants. We determined subcellular localization of the related novel proteins in cells and in human brain tissue. We investigated functional consequences of the newly identified variants on volume regulation pathways using cell volume measurements, biochemical analysis and electrophysiology. We identified a novel homozygous variant in AQP4, encoding the water channel aquaporin-4, in two siblings, and two de novo heterozygous variants in GPRC5B, encoding the orphan G protein-coupled receptor GPRC5B, in three unrelated patients. The AQP4 variant disrupts membrane localization and thereby channel function. GPRC5B, like MLC1, GlialCAM and aquaporin-4, is expressed in astrocyte endfeet in human brain. Cell volume regulation is disrupted in GPRC5B patient-derived lymphoblasts. GPRC5B functionally interacts with ion channels involved in astrocyte volume regulation. In conclusion, we identify aquaporin-4 and GPRC5B as old and new players in genetic brain oedema. Our findings shed light on the protein complex involved in astrocyte volume regulation and identify GPRC5B as novel potentially druggable target for treating brain oedema.

A novel role for MLC1 in regulating astrocyte-synapse interactions.

Loss of function of the astrocyte membrane protein MLC1 is the primary genetic cause of the rare white matter disease Megalencephalic Leukoencephalopathy with subcortical Cysts (MLC), which is characterized by disrupted brain ion and water homeostasis. MLC1 is prominently present around fluid barriers in the brain, such as in astrocyte endfeet contacting blood vessels and in processes contacting the meninges. Whether the protein plays a role in other astrocyte domains is unknown. Here, we show that MLC1 is present in distal astrocyte processes, also known as perisynaptic astrocyte processes (PAPs) or astrocyte leaflets, which closely interact with excitatory synapses in the CA1 region of the hippocampus. We find that the PAP tip extending toward excitatory synapses is shortened in Mlc1-null mice. This affects glutamatergic synaptic transmission, resulting in a reduced rate of spontaneous release events and slower glutamate re-uptake under challenging conditions. Moreover, while PAPs in wildtype mice retract from the synapse upon fear conditioning, we reveal that this structural plasticity is disturbed in Mlc1-null mice, where PAPs are already shorter. Finally, Mlc1-null mice show reduced contextual fear memory. In conclusion, our study uncovers an unexpected role for the astrocyte protein MLC1 in regulating the structure of PAPs. Loss of MLC1 alters excitatory synaptic transmission, prevents normal PAP remodeling induced by fear conditioning and disrupts contextual fear memory expression. Thus, MLC1 is a new player in the regulation of astrocyte-synapse interactions.

Retraction of Astrocyte Leaflets From the Synapse Enhances Fear Memory.

BACKGROUND: The formation and retrieval of fear memories depends on orchestrated synaptic activity of neuronal ensembles within the hippocampus, and it is becoming increasingly evident that astrocytes residing in the environment of these synapses play a central role in shaping cellular memory representations. Astrocyte distal processes, known as leaflets, fine-tune synaptic activity by clearing neurotransmitters and limiting glutamate diffusion. However, how astroglial synaptic coverage contributes to mnemonic processing of fearful experiences remains largely unknown. METHODS: We used electron microscopy to observe changes in astroglial coverage of hippocampal synapses during consolidation of fear memory in mice. To manipulate astroglial synaptic coverage, we depleted ezrin, an integral leaflet-structural protein, from hippocampal astrocytes using CRISPR (clustered regularly interspaced short palindromic repeats)/Cas9 gene editing. Next, a combination of Föster resonance energy transfer analysis, genetically encoded glutamate sensors, and whole-cell patch-clamp recordings was used to determine whether the proximity of astrocyte leaflets to the synapse is critical for synaptic integrity and function. RESULTS: We found that consolidation of a recent fear memory is accompanied by a transient retraction of astrocyte leaflets from hippocampal synapses and increased activation of NMDA receptors. Accordingly, astrocyte-specific depletion of ezrin resulted in shorter astrocyte leaflets and reduced astrocyte contact with the synaptic cleft, which consequently boosted extrasynaptic glutamate diffusion and NMDA receptor activation. Importantly, after fear conditioning, these cellular phenotypes translated to increased retrieval-evoked activation of CA1 pyramidal neurons and enhanced fear memory expression. CONCLUSIONS: Together, our data show that withdrawal of astrocyte leaflets from the synaptic cleft is an experience-induced, temporally regulated process that gates the strength of fear memories.

Strong and reliable synaptic communication between pyramidal neurons in adult human cerebral cortex.

Synaptic transmission constitutes the primary mode of communication between neurons. It is extensively studied in rodent but not human neocortex. We characterized synaptic transmission between pyramidal neurons in layers 2 and 3 using neurosurgically resected human middle temporal gyrus (MTG, Brodmann area 21), which is part of the distributed language circuitry. We find that local connectivity is comparable with mouse layer 2/3 connections in the anatomical homologue (temporal association area), but synaptic connections in human are 3-fold stronger and more reliable (0% vs 25% failure rates, respectively). We developed a theoretical approach to quantify properties of spinous synapses showing that synaptic conductance and voltage change in human dendritic spines are 3-4-folds larger compared with mouse, leading to significant NMDA receptor activation in human unitary connections. This model prediction was validated experimentally by showing that NMDA receptor activation increases the amplitude and prolongs decay of unitary excitatory postsynaptic potentials in human but not in mouse connections. Since NMDA-dependent recurrent excitation facilitates persistent activity (supporting working memory), our data uncovers cortical microcircuit properties in human that may contribute to language processing in MTG.

Prediction of Behavioral Improvement Through Resting-State Electroencephalography and Clinical Severity in a Randomized Controlled Trial Testing Bumetanide in Autism Spectrum Disorder.

BACKGROUND: Mechanism-based treatments such as bumetanide are being repurposed for autism spectrum disorder. We recently reported beneficial effects on repetitive behavioral symptoms that might be related to regulating excitation-inhibition (E/I) balance in the brain. Here, we tested the neurophysiological effects of bumetanide and the relationship to clinical outcome variability and investigated the potential for machine learning-based predictions of meaningful clinical improvement. METHODS: Using modified linear mixed models applied to intention-to-treat population, we analyzed E/I-sensitive electroencephalography (EEG) measures before and after 91 days of treatment in the double-blind, randomized, placebo-controlled Bumetanide in Autism Medication and Biomarker study. Resting-state EEG of 82 subjects out of 92 participants (7-15 years) were available. Alpha frequency band absolute and relative power, central frequency, long-range temporal correlations, and functional E/I ratio treatment effects were related to the Repetitive Behavior Scale-Revised (RBS-R) and the Social Responsiveness Scale 2 as clinical outcomes. RESULTS: We observed superior bumetanide effects on EEG, reflected in increased absolute and relative alpha power and functional E/I ratio and in decreased central frequency. Associations between EEG and clinical outcome change were restricted to subgroups with medium to high RBS-R improvement. Using machine learning, medium and high RBS-R improvement could be predicted by baseline RBS-R score and EEG measures with 80% and 92% accuracy, respectively. CONCLUSIONS: Bumetanide exerts neurophysiological effects related to clinical changes in more responsive subsets, in whom prediction of improvement was feasible through EEG and clinical measures.

The hibernation-derived compound SUL-138 shifts the mitochondrial proteome towards fatty acid metabolism and prevents cognitive decline and amyloid plaque formation in an Alzheimer's disease mouse model.

BACKGROUND: Alzheimer's disease (AD) is the most prevalent neurodegenerative disease worldwide and remains without effective cure. Increasing evidence is supporting the mitochondrial cascade hypothesis, proposing that loss of mitochondrial fitness and subsequent ROS and ATP imbalance are important contributors to AD pathophysiology. METHODS: Here, we tested the effects of SUL-138, a small hibernation-derived molecule that supports mitochondrial bioenergetics via complex I/IV activation, on molecular, physiological, behavioral, and pathological outcomes in APP/PS1 and wildtype mice. RESULTS: SUL-138 treatment rescued long-term potentiation and hippocampal memory impairments and decreased beta-amyloid plaque load in APP/PS1 mice. This was paralleled by a partial rescue of dysregulated protein expression in APP/PS1 mice as assessed by mass spectrometry-based proteomics. In-depth analysis of protein expression revealed a prominent effect of SUL-138 in APP/PS1 mice on mitochondrial protein expression. SUL-138 increased the levels of proteins involved in fatty acid metabolism in both wildtype and APP/PS1 mice. Additionally, in APP/PS1 mice only, SUL-138 increased the levels of proteins involved in glycolysis and amino acid metabolism pathways, indicating that SUL-138 rescues mitochondrial impairments that are typically observed in AD. CONCLUSION: Our study demonstrates a SUL-138-induced shift in metabolic input towards the electron transport chain in synaptic mitochondria, coinciding with increased synaptic plasticity and memory. In conclusion, targeting mitochondrial bioenergetics might provide a promising new way to treat cognitive impairments in AD and reduce disease progression.

Intellectually able adults with autism spectrum disorder show typical resting-state EEG activity.

There is broad interest in discovering quantifiable physiological biomarkers for psychiatric disorders to aid diagnostic assessment. However, finding biomarkers for autism spectrum disorder (ASD) has proven particularly difficult, partly due to high heterogeneity. Here, we recorded five minutes eyes-closed rest electroencephalography (EEG) from 186 adults (51% with ASD and 49% without ASD) and investigated the potential of EEG biomarkers to classify ASD using three conventional machine learning models with two-layer cross-validation. Comprehensive characterization of spectral, temporal and spatial dimensions of source-modelled EEG resulted in 3443 biomarkers per recording. We found no significant group-mean or group-variance differences for any of the EEG features. Interestingly, we obtained validation accuracies above 80%; however, the best machine learning model merely distinguished ASD from the non-autistic comparison group with a mean balanced test accuracy of 56% on the entirely unseen test set. The large drop in model performance between validation and testing, stress the importance of rigorous model evaluation, and further highlights the high heterogeneity in ASD. Overall, the lack of significant differences and weak classification indicates that, at the group level, intellectually able adults with ASD show remarkably typical resting-state EEG.

Prefrontal Cortical to Mediodorsal Thalamus Projection Neurons Regulate Posterror Adaptive Control of Behavior.

Adaptive control is the online adjustment of behavior to guide and optimize responses after errors or conflict. The neural circuits involved in monitoring and adapting behavioral performance following error are poorly understood. The prefrontal cortex (PFC) plays a critical role in this form of control. However, these brain areas are densely connected with many other regions, and it is unknown which projections are critical for adaptive behavior. Here, we tested the involvement of four distinct dorsal and ventral prefrontal cortical projections to striatal and thalamic target areas in adaptive control. We re-analyzed data from published experiments, using trial-by-trial analyses of behavior in an operant task for attention and impulsivity. We find that male rats slow their responses and perform worse following errors. Moreover, by combining retrograde labeling and chemogenetic silencing, we find that dorsomedial prefrontal pyramidal neurons that project to the lateral nucleus of the mediodorsal thalamus (MDL) are involved in posterror performance and timing of responses, specifically with unpredictable delays until stimulus presentation. Together, these data show that dorsal medial PFC (mPFC) projection neurons targeting the lateral MDT regulate adaptive control to flexibly optimize behavioral responses in goal-directed behavior.

Improved Manual Annotation of EEG Signals through Convolutional Neural Network Guidance.

The development of validated algorithms for automated handling of artifacts is essential for reliable and fast processing of EEG signals. Recently, there have been methodological advances in designing machine-learning algorithms to improve artifact detection of trained professionals who usually meticulously inspect and manually annotate EEG signals. However, validation of these methods is hindered by the lack of a gold standard as data are mostly private and data annotation is time consuming and error prone. In the effort to circumvent these issues, we propose an iterative learning model to speed up and reduce errors of manual annotation of EEG. We use a convolutional neural network (CNN) to train on expert-annotated eyes-open and eyes-closed resting-state EEG data from typically developing children (n = 30) and children with neurodevelopmental disorders (n = 141). To overcome the circular reasoning of aiming to develop a new algorithm and benchmarking to a manually-annotated gold standard, we instead aim to improve the gold standard by revising the portion of the data that was incorrectly learned by the network. When blindly presented with the selected signals for re-assessment (23% of the data), the two independent expert-annotators changed the annotation in 25% of the cases. Subsequently, the network was trained on the expert-revised gold standard, which resulted in improved separation between artifacts and nonartifacts as well as an increase in balanced accuracy from 74% to 80% and precision from 59% to 76%. These results show that CNNs are promising to enhance manual annotation of EEG artifacts and can be improved further with better gold-standard data.

Mesodiencephalic junction GABAergic inputs are processed separately from motor cortical inputs in the basilar pons.

The basilar pontine nuclei (bPN) are known to receive excitatory input from the entire neocortex and constitute the main source of mossy fibers to the cerebellum. Various potential inhibitory afferents have been described, but their origin, synaptic plasticity, and network function have remained elusive. Here we identify the mesodiencephalic junction (MDJ) as a prominent source of monosynaptic GABAergic inputs to the bPN. We found no evidence that these inputs converge with motor cortex (M1) inputs at the single neuron or at the local network level. Tracing the inputs to GABAergic MDJ neurons revealed inputs to these neurons from neocortical areas. Additionally, we observed little short-term synaptic facilitation or depression in afferents from the MDJ, enabling MDJ inputs to carry sign-inversed neocortical inputs. Thus, our results show a prominent source of GABAergic inhibition to the bPN that could enrich input to the cerebellar granule cell layer.

Bumetanide Effects on Resting-State EEG in Tuberous Sclerosis Complex in Relation to Clinical Outcome: An Open-Label Study.

Neuronal excitation-inhibition (E/I) imbalances are considered an important pathophysiological mechanism in neurodevelopmental disorders. Preclinical studies on tuberous sclerosis complex (TSC), suggest that altered chloride homeostasis may impair GABAergic inhibition and thereby E/I-balance regulation. Correction of chloride homeostasis may thus constitute a treatment target to alleviate behavioral symptoms. Recently, we showed that bumetanide-a chloride-regulating agent-improved behavioral symptoms in the open-label study Bumetanide to Ameliorate Tuberous Sclerosis Complex Hyperexcitable Behaviors trial (BATSCH trial; Eudra-CT: 2016-002408-13). Here, we present resting-state EEG as secondary analysis of BATSCH to investigate associations between EEG measures sensitive to network-level changes in E/I balance and clinical response to bumetanide. EEGs of 10 participants with TSC (aged 8-21 years) were available. Spectral power, long-range temporal correlations (LRTC), and functional E/I ratio (fE/I) in the alpha-frequency band were compared before and after 91 days of treatment. Pre-treatment measures were compared against 29 typically developing children (TDC). EEG measures were correlated with the Aberrant Behavioral Checklist-Irritability subscale (ABC-I), the Social Responsiveness Scale-2 (SRS-2), and the Repetitive Behavior Scale-Revised (RBS-R). At baseline, TSC showed lower alpha-band absolute power and fE/I than TDC. Absolute power increased through bumetanide treatment, which showed a moderate, albeit non-significant, correlation with improvement in RBS-R. Interestingly, correlations between baseline EEG measures and clinical outcomes suggest that most responsiveness might be expected in children with network characteristics around the E/I balance point. In sum, E/I imbalances pointing toward an inhibition-dominated network are present in TSC. We established neurophysiological effects of bumetanide although with an inconclusive relationship with clinical improvement. Nonetheless, our results further indicate that baseline network characteristics might influence treatment response. These findings highlight the possible utility of E/I-sensitive EEG measures to accompany new treatment interventions for TSC. Clinical Trial Registration: EU Clinical Trial Register, EudraCT 2016-002408-13 (www.clinicaltrialsregister.eu/ctr-search/trial/2016-002408-13/NL). Registered 25 July 2016.

Role of anterior insula cortex in context-induced relapse of nicotine-seeking.

Tobacco use is the leading cause of preventable death worldwide, and relapse during abstinence remains the critical barrier to successful treatment of tobacco addiction. During abstinence, environmental contexts associated with nicotine use can induce craving and contribute to relapse. The insular cortex (IC) is thought to be a critical substrate of nicotine addiction and relapse. However, its specific role in context-induced relapse of nicotine-seeking is not fully known. In this study, we report a novel rodent model of context-induced relapse to nicotine-seeking after punishment-imposed abstinence, which models self-imposed abstinence through increasing negative consequences of excessive drug use. Using the neuronal activity marker Fos we find that the anterior (aIC), but not the middle or posterior IC, shows increased activity during context-induced relapse. Combining Fos with retrograde labeling of aIC inputs, we show projections to aIC from contralateral aIC and basolateral amygdala exhibit increased activity during context-induced relapse. Next, we used fiber photometry in aIC and observed phasic increases in aIC activity around nicotine-seeking responses during self-administration, punishment, and the context-induced relapse tests. Next, we used chemogenetic inhibition in both male and female rats to determine whether activity in aIC is necessary for context-induced relapse. We found that chemogenetic inhibition of aIC decreased context-induced nicotine-seeking after either punishment- or extinction-imposed abstinence. These findings highlight the critical role nicotine-associated contexts play in promoting relapse, and they show that aIC activity is critical for this context-induced relapse following both punishment and extinction-imposed abstinence.

Long-Range Amplitude Coupling Is Optimized for Brain Networks That Function at Criticality.

Brain function depends on segregation and integration of information processing in brain networks often separated by long-range anatomic connections. Neuronal oscillations orchestrate such distributed processing through transient amplitude and phase coupling, yet surprisingly, little is known about local network properties facilitating these functional connections. Here, we test whether criticality, a dynamical state characterized by scale-free oscillations, optimizes the capacity of neuronal networks to couple through amplitude or phase, and transfer information. We coupled in silico networks which exhibit oscillations in the α band (8-16 Hz), and varied excitatory and inhibitory connectivity. We found that phase coupling of oscillations emerges at criticality, and that amplitude coupling, as well as information transfer, are maximal when networks are critical. Importantly, regulating criticality through modulation of synaptic gain showed that critical dynamics, as opposed to a static ratio of excitatory and inhibitory connections, optimize network coupling and information transfer. Our data support the idea that criticality is important for local and global information processing and may help explain why brain disorders characterized by local alterations in criticality also exhibit impaired long-range synchrony, even before degeneration of axonal connections.SIGNIFICANCE STATEMENT To perform adaptively in a changing environment, our brains dynamically coordinate activity across distant areas. Empirical evidence suggests that long-range amplitude and phase coupling of oscillations are systems-level mechanisms enabling transient formation of spatially distributed functional networks on the backbone of a relatively static structural connectome. However, surprisingly little is known about the local network properties that optimize coupling and information transfer. Here, we show that criticality, a dynamical state characterized by scale-free oscillations and a hallmark of neuronal network activity, optimizes the capacity of neuronal networks to couple through amplitude or phase and transfer information.

Extinction of Cocaine Memory Depends on a Feed-Forward Inhibition Circuit Within the Medial Prefrontal Cortex.

BACKGROUND: Cocaine-associated environments (i.e., contexts) evoke persistent memories of cocaine reward and thereby contribute to the maintenance of addictive behavior in cocaine users. From a therapeutic perspective, enhancing inhibitory control over cocaine-conditioned responses is of pivotal importance but requires a more detailed understanding of the neural circuitry that can suppress context-evoked cocaine memories, e.g., through extinction learning. The ventral medial prefrontal cortex (vmPFC) and dorsal medial prefrontal cortex (dmPFC) are thought to bidirectionally regulate responding to cocaine cues through their projections to other brain regions. However, whether these mPFC subregions interact to enable adaptive responding to cocaine-associated contextual stimuli has remained elusive. METHODS: We used antero- and retrograde tracing combined with chemogenetic intervention to examine the role of vmPFC-to-dmPFC projections in extinction of cocaine-induced place preference in mice. In addition, electrophysiological recordings and optogenetics were used to determine whether parvalbumin-expressing inhibitory interneurons and pyramidal neurons in the dmPFC are innervated by vmPFC projections. RESULTS: We found that vmPFC-to-dmPFC projecting neurons are activated during unreinforced re-exposure to a cocaine-associated context, and selective suppression of these cells impairs extinction learning. Parvalbumin-expressing inhibitory interneurons in the dmPFC receive stronger monosynaptic excitatory input from vmPFC projections than local dmPFC pyramidal neurons, consequently resulting in disynaptic inhibition of pyramidal neurons. In line with this, we show that chemogenetic suppression of dmPFC parvalbumin-expressing inhibitory interneurons impairs extinction learning. CONCLUSIONS: Our data reveal that vmPFC projections mediate extinction of a cocaine-associated contextual memory through recruitment of feed-forward inhibition in the dmPFC, thereby providing a novel neuronal substrate that promotes extinction-induced inhibitory control.

Cellular Substrates of Functional Network Integration and Memory in Temporal Lobe Epilepsy.

Temporal lobe epilepsy (TLE) patients are at risk of memory deficits, which have been linked to functional network disturbances, particularly of integration of the default mode network (DMN). However, the cellular substrates of functional network integration are unknown. We leverage a unique cross-scale dataset of drug-resistant TLE patients (n = 31), who underwent pseudo resting-state functional magnetic resonance imaging (fMRI), resting-state magnetoencephalography (MEG) and/or neuropsychological testing before neurosurgery. fMRI and MEG underwent atlas-based connectivity analyses. Functional network centrality of the lateral middle temporal gyrus, part of the DMN, was used as a measure of local network integration. Subsequently, non-pathological cortical tissue from this region was used for single cell morphological and electrophysiological patch-clamp analysis, assessing integration in terms of total dendritic length and action potential rise speed. As could be hypothesized, greater network centrality related to better memory performance. Moreover, greater network centrality correlated with more integrative properties at the cellular level across patients. We conclude that individual differences in cognitively relevant functional network integration of a DMN region are mirrored by differences in cellular integrative properties of this region in TLE patients. These findings connect previously separate scales of investigation, increasing translational insight into focal pathology and large-scale network disturbances in TLE.