Neocortical Layer 1: An Elegant Solution to Top-Down and Bottom-Up Integration

Microglial TNFα controls daily changes in synaptic GABAARs and sleep slow waves

Microglia sense the changes in their environment. How microglia actively translate these changes into suitable cues to adapt brain physiology is unknown. We reveal an activity-dependent regulation of cortical inhibitory synapses by microglia, driven by purinergic signaling acting on P2RX7 and mediated by microglia-derived TNFα. We demonstrate that sleep induces microglia-dependent synaptic enrichment of GABAARs in a manner dependent on microglial TNFα and P2RX7. We further show that microglia-specific depletion of TNFα alters slow waves during NREM sleep and blunt memory consolidation in sleep-dependent learning tasks. Together, our results reveal that microglia orchestrate sleep-intrinsic plasticity of synaptic GABAARs, sculpt sleep slow waves, and support memory consolidation.

Expression and function of nicotinic acetylcholine receptors in specific neuronal populations: Focus on striatal and prefrontal circuits

Nicotinic acetylcholine receptors (nAChRs) are widely expressed in the central nervous system and play an important role in the control of neural functions including neuronal activity, transmitter release and synaptic plasticity. Although the common subtypes of nAChRs are abundantly expressed throughout the brain, their expression in different brain regions and by individual neuronal types is not homogeneous or incidental. In recent years, several studies have emerged showing that particular subtypes of nAChRs are expressed by specific neuronal populations in which they have major influence on the activity of local circuits and behavior. It has been demonstrated that even nAChRs expressed by relatively rare neuronal types can induce significant changes in behavior and contribute to pathological processes. Depending on the identity and connectivity of the particular nAChRs-expressing neuronal populations, the activation of nAChRs can have distinct or even opposing effects on local neuronal signaling. In this review, we will summarize the available literature describing the expression of individual nicotinic subunits by different neuronal types in two crucial brain regions, the striatum and the prefrontal cortex. The review will also briefly discuss nicotinic expression in non-neuronal, glial cells, as they cannot be ignored as potential targets of nAChRs-modulating drugs. The final section will discuss options that could allow us to target nAChRs in a neuronal-type-specific manner, not only in the experimental field, but also eventually in clinical practice.

Dysfunctions of cellular context-sensitivity in neurodevelopmental learning disabilities

Pyramidal neurons have a pivotal role in the cognitive capabilities of neocortex. Though they have been predominantly modeled as integrate-and-fire point processors, many of them have another point of input integration in their apical dendrites that is central to mechanisms endowing them with the sensitivity to context that underlies basic cognitive capabilities. Here we review evidence implicating impairments of those mechanisms in three major neurodevelopmental disabilities, fragile X, Down syndrome, and fetal alcohol spectrum disorders. Multiple dysfunctions of the mechanisms by which pyramidal cells are sensitive to context are found to be implicated in all three syndromes. Further deciphering of these cellular mechanisms would lead to the understanding of and therapies for learning disabilities beyond any that are currently available.

Layer 1 NDNF interneurons are specialized top-down master regulators of cortical circuits

Diverse types of inhibitory interneurons (INs) impart computational power and flexibility to neocortical circuits. Whereas markers for different IN types in cortical layers 2-6 (L2-L6) have been instrumental for generating a wealth of functional insights, only the recent identification of a selective marker (neuron-derived neurotrophic factor [NDNF]) has opened comparable opportunities for INs in L1 (L1INs). However, at present we know very little about the connectivity of NDNF L1INs with other IN types, their input-output conversion, and the existence of potential NDNF L1IN subtypes. Here, we report pervasive inhibition of L2/3 INs (including parvalbumin INs and vasoactive intestinal peptide INs) by NDNF L1INs. Intersectional genetics revealed similar physiology and connectivity in the NDNF L1IN subpopulation co-expressing neuropeptide Y. Finally, NDNF L1INs prominently and selectively engage in persistent firing, a physiological hallmark disconnecting their output from the current input. Collectively, our work therefore identifies NDNF L1INs as specialized master regulators of superficial neocortex according to their pervasive top-down afferents.

Organization of corticocortical and thalamocortical top-down inputs in the primary visual cortex

Unified visual perception requires integration of bottom-up and top-down inputs in the primary visual cortex (V1), yet the organization of top-down inputs in V1 remains unclear. Here, we used optogenetics-assisted circuit mapping to identify how multiple top-down inputs from higher-order cortical and thalamic areas engage V1 excitatory and inhibitory neurons. Top-down inputs overlap in superficial layers yet segregate in deep layers. Inputs from the medial secondary visual cortex (V2M) and anterior cingulate cortex (ACA) converge on L6 Pyrs, whereas ventrolateral orbitofrontal cortex (ORBvl) and lateral posterior thalamic nucleus (LP) inputs are processed in parallel in Pyr-type-specific subnetworks (Pyr←ORBvl and Pyr←LP) and drive mutual inhibition between them via local interneurons. Our study deepens understanding of the top-down modulation mechanisms of visual processing and establishes that V2M and ACA inputs in L6 employ integrated processing distinct from the parallel processing of LP and ORBvl inputs in L5.

Ndnf Interneuron Excitability Is Spared in a Mouse Model of Dravet Syndrome

Dravet syndrome (DS) is a neurodevelopmental disorder characterized by epilepsy, developmental delay/intellectual disability, and features of autism spectrum disorder, caused by heterozygous loss-of-function variants in SCN1A encoding the voltage-gated sodium channel α subunit Nav1.1. The dominant model of DS pathogenesis is the "interneuron hypothesis," whereby GABAergic interneurons (INs) express and preferentially rely on Nav1.1-containing sodium channels for action potential (AP) generation. This has been shown for three of the major subclasses of cerebral cortex GABAergic INs: those expressing parvalbumin (PV), somatostatin, and vasoactive intestinal peptide. Here, we define the function of a fourth major subclass of INs expressing neuron-derived neurotrophic factor (Ndnf) in male and female DS (Scn1a+/-) mice. Patch-clamp electrophysiological recordings of Ndnf-INs in brain slices from Scn1a+/â mice and WT controls reveal normal intrinsic membrane properties, properties of AP generation and repetitive firing, and synaptic transmission across development. Immunohistochemistry shows that Nav1.1 is strongly expressed at the axon initial segment (AIS) of PV-expressing INs but is absent at the Ndnf-IN AIS. In vivo two-photon calcium imaging demonstrates that Ndnf-INs in Scn1a+/â mice are recruited similarly to WT controls during arousal. These results suggest that Ndnf-INs are the only major IN subclass that does not prominently rely on Nav1.1 for AP generation and thus retain their excitability in DS. The discovery of a major IN subclass with preserved function in the Scn1a+/â mouse model adds further complexity to the "interneuron hypothesis" and highlights the importance of considering cell-type heterogeneity when investigating mechanisms underlying neurodevelopmental disorders.

Cellular mechanisms of cooperative context-sensitive predictive inference

We argue that prediction success maximization is a basic objective of cognition and cortex, that it is compatible with but distinct from prediction error minimization, that neither objective requires subtractive coding, that there is clear neurobiological evidence for the amplification of predicted signals, and that we are unconvinced by evidence proposed in support of subtractive coding. We outline recent discoveries showing that pyramidal cells on which our cognitive capabilities depend usually transmit information about input to their basal dendrites and amplify that transmission when input to their distal apical dendrites provides a context that agrees with the feedforward basal input in that both are depolarizing, i.e., both are excitatory rather than inhibitory. Though these intracellular discoveries require a level of technical expertise that is beyond the current abilities of most neuroscience labs, they are not controversial and acclaimed as groundbreaking. We note that this cellular cooperative context-sensitivity greatly enhances the cognitive capabilities of the mammalian neocortex, and that much remains to be discovered concerning its evolution, development, and pathology.

Layer 6b controls brain state via apical dendrites and the higher-order thalamocortical system

The deepest layer of the cortex (layer 6b [L6b]) contains relatively few neurons, but it is the only cortical layer responsive to the potent wake-promoting neuropeptide orexin/hypocretin. Can these few neurons significantly influence brain state? Here, we show that L6b-photoactivation causes a surprisingly robust enhancement of attention-associated high-gamma oscillations and population spiking while abolishing slow waves in sleep-deprived mice. To explain this powerful impact on brain state, we investigated L6b's synaptic output using optogenetics, electrophysiology, and monoCaTChR ex vivo. We found powerful output in the higher-order thalamus and apical dendrites of L5 pyramidal neurons, via L1a and L5a, as well as in superior colliculus and L6 interneurons. L6b subpopulations with distinct morphologies and short- and long-term plasticities project to these diverse targets. The L1a-targeting subpopulation triggered powerful NMDA-receptor-dependent spikes that elicited burst firing in L5. We conclude that orexin/hypocretin-activated cortical neurons form a multifaceted, fine-tuned circuit for the sustained control of the higher-order thalamocortical system.

An operating principle of the cerebral cortex, and a cellular mechanism for attentional trial-and-error pattern learning and useful classification extraction

A feature of the brains of intelligent animals is the ability to learn to respond to an ensemble of active neuronal inputs with a behaviorally appropriate ensemble of active neuronal outputs. Previously, a hypothesis was proposed on how this mechanism is implemented at the cellular level within the neocortical pyramidal neuron: the apical tuft or perisomatic inputs initiate "guess" neuron firings, while the basal dendrites identify input patterns based on excited synaptic clusters, with the cluster excitation strength adjusted based on reward feedback. This simple mechanism allows neurons to learn to classify their inputs in a surprisingly intelligent manner. Here, we revise and extend this hypothesis. We modify synaptic plasticity rules to align with behavioral time scale synaptic plasticity (BTSP) observed in hippocampal area CA1, making the framework more biophysically and behaviorally plausible. The neurons for the guess firings are selected in a voluntary manner via feedback connections to apical tufts in the neocortical layer 1, leading to dendritic Ca2+ spikes with burst firing, which are postulated to be neural correlates of attentional, aware processing. Once learned, the neuronal input classification is executed without voluntary or conscious control, enabling hierarchical incremental learning of classifications that is effective in our inherently classifiable world. In addition to voluntary, we propose that pyramidal neuron burst firing can be involuntary, also initiated via apical tuft inputs, drawing attention toward important cues such as novelty and noxious stimuli. We classify the excitations of neocortical pyramidal neurons into four categories based on their excitation pathway: attentional versus automatic and voluntary/acquired versus involuntary. Additionally, we hypothesize that dendrites within pyramidal neuron minicolumn bundles are coupled via depolarization cross-induction, enabling minicolumn functions such as the creation of powerful hierarchical "hyperneurons" and the internal representation of the external world. We suggest building blocks to extend the microcircuit theory to network-level processing, which, interestingly, yields variants resembling the artificial neural networks currently in use. On a more speculative note, we conjecture that principles of intelligence in universes governed by certain types of physical laws might resemble ours.

Context association in pyramidal neurons through local synaptic plasticity in apical dendrites

The unique characteristics of neocortical pyramidal neurons are thought to be crucial for many aspects of information processing and learning in the brain. Experimental data suggests that their segregation into two distinct compartments, the basal dendrites close to the soma and the apical dendrites branching out from the thick apical dendritic tuft, plays an essential role in cortical organization. A recent hypothesis states that layer 5 pyramidal cells associate top-down contextual information arriving at their apical tuft with features of the sensory input that predominantly arrives at their basal dendrites. It has however remained unclear whether such context association could be established by synaptic plasticity processes. In this work, we formalize the objective of such context association learning through a mathematical loss function and derive a plasticity rule for apical synapses that optimizes this loss. The resulting plasticity rule utilizes information that is available either locally at the synapse, through branch-local NMDA spikes, or through global Ca2+events, both of which have been observed experimentally in layer 5 pyramidal cells. We show in computer simulations that the plasticity rule enables pyramidal cells to associate top-down contextual input patterns with high somatic activity. Furthermore, it enables networks of pyramidal neuron models to perform context-dependent tasks and enables continual learning by allocating new dendritic branches to novel contexts.

Layer 1 neocortex: Gating and integrating multidimensional signals

Layer 1 (L1) of the neocortex acts as a nexus for the collection and processing of widespread information. By integrating ascending inputs with extensive top-down activity, this layer likely provides critical information regulating how the perception of sensory inputs is reconciled with expectation. This is accomplished by sorting, directing, and integrating the complex network of excitatory inputs that converge onto L1. These signals are combined with neuromodulatory afferents and gated by the wealth of inhibitory interneurons that either are embedded within L1 or send axons from other cortical layers. Together, these interactions dynamically calibrate information flow throughout the neocortex. This review will primarily focus on L1 within the primary sensory cortex and will use these insights to understand L1 in other cortical areas.

STalign: Alignment of spatial transcriptomics data using diffeomorphic metric mapping

Spatial transcriptomics (ST) technologies enable high throughput gene expression characterization within thin tissue sections. However, comparing spatial observations across sections, samples, and technologies remains challenging. To address this challenge, we develop STalign to align ST datasets in a manner that accounts for partially matched tissue sections and other local non-linear distortions using diffeomorphic metric mapping. We apply STalign to align ST datasets within and across technologies as well as to align ST datasets to a 3D common coordinate framework. We show that STalign achieves high gene expression and cell-type correspondence across matched spatial locations that is significantly improved over landmark-based affine alignments. Applying STalign to align ST datasets of the mouse brain to the 3D common coordinate framework from the Allen Brain Atlas, we highlight how STalign can be used to lift over brain region annotations and enable the interrogation of compositional heterogeneity across anatomical structures. STalign is available as an open-source Python toolkit at https://github.com/JEFworks-Lab/STalign and as Supplementary Software with additional documentation and tutorials available at https://jef.works/STalign .

Generation and characterization of a knock-in mouse model for spastic tetraplegia, thin corpus callosum, and progressive microcephaly (SPATCCM)

Solute carrier family 1 member 4 (SLC1A4), also referred to as Alanine/Serine/Cysteine/Threonine-preferring Transporter 1 (ASCT1), is a sodium-dependent neutral amino acid transporter. It is expressed in many tissues, including the brain, where it is expressed primarily on astrocytes and plays key roles in neuronal differentiation and development, maintaining neurotransmitter homeostasis, and N-methyl-D-aspartate neurotransmission, through regulation of L- and D-serine. Mutations in SLC1A4 are associated with the rare autosomal recessive neurodevelopmental disorder spastic tetraplegia, thin corpus callosum, and progressive microcephaly (SPATCCM, OMIM 616657). Psychomotor development and speech are significantly impaired in these patients, and many develop seizures. We generated and characterized a knock-in mouse model for the most common mutant allele, which results in a single amino acid change (p.Glu256Lys, or E256K). Homozygous mutants had increased D-serine uptake in the brain, microcephaly, and thin corpus callosum and cortex layer 1. While p.E256K homozygotes showed some significant differences in exploratory behavior relative to wildtype mice, their performance in assays for motor coordination, endurance, learning, and memory was normal, and they showed no significant differences in long-term potentiation. Taken together, these results indicate that the impact of the p.E256K mutation on cognition and motor function is minimal in mice, but other aspects of SLC1A4 function in the brain are conserved. Mice homozygous for p.E256K may be a good model for understanding the developmental basis of the corpus callosum and microcephaly phenotypes observed in SPATCCM patients and assessing whether they are rescued by serine supplementation.

Layer 1 of somatosensory cortex: an important site for input to a tiny cortical compartment

Neocortical layer 1 has been proposed to be at the center for top-down and bottom-up integration. It is a locus for interactions between long-range inputs, layer 1 interneurons, and apical tuft dendrites of pyramidal neurons. While input to layer 1 has been studied intensively, the level and effect of input to this layer has still not been completely characterized. Here we examined the input to layer 1 of mouse somatosensory cortex with retrograde tracing and optogenetics. Our assays reveal that local input to layer 1 is predominantly from layers 2/3 and 5 pyramidal neurons and interneurons, and that subtypes of local layers 5 and 6b neurons project to layer 1 with different probabilities. Long-range input from sensory-motor cortices to layer 1 of somatosensory cortex arose predominantly from layers 2/3 neurons. Our optogenetic experiments showed that intra-telencephalic layer 5 pyramidal neurons drive layer 1 interneurons but have no effect locally on layer 5 apical tuft dendrites. Dual retrograde tracing revealed that a fraction of local and long-range neurons was both presynaptic to layer 5 neurons and projected to layer 1. Our work highlights the prominent role of local inputs to layer 1 and shows the potential for complex interactions between long-range and local inputs, which are both in position to modify the output of somatosensory cortex.

Morphoelectric and transcriptomic divergence of the layer 1 interneuron repertoire in human versus mouse neocortex

Neocortical layer 1 (L1) is a site of convergence between pyramidal-neuron dendrites and feedback axons where local inhibitory signaling can profoundly shape cortical processing. Evolutionary expansion of human neocortex is marked by distinctive pyramidal neurons with extensive L1 branching, but whether L1 interneurons are similarly diverse is underexplored. Using Patch-seq recordings from human neurosurgical tissue, we identified four transcriptomic subclasses with mouse L1 homologs, along with distinct subtypes and types unmatched in mouse L1. Subclass and subtype comparisons showed stronger transcriptomic differences in human L1 and were correlated with strong morphoelectric variability along dimensions distinct from mouse L1 variability. Accompanied by greater layer thickness and other cytoarchitecture changes, these findings suggest that L1 has diverged in evolution, reflecting the demands of regulating the expanded human neocortical circuit.

C4 induces pathological synaptic loss by impairing AMPAR trafficking

During development, activation of the complement pathway, an extracellular proteolytic cascade, results in microglia-dependent synaptic elimination via complement receptor 3 (CR3). Here, we report that decreased connectivity caused by overexpression of C4 (C4-OE), a schizophrenia-associated gene, is CR3 independent. Instead, C4-OE triggers GluR1 degradation through an intracellular mechanism involving endosomal trafficking protein SNX27, resulting in pathological synaptic loss. Moreover, the connectivity deficits associated with C4-OE were rescued by increasing levels of SNX27, linking excessive complement activity to an intracellular endolysosomal recycling pathway affecting synapses.

Neural decoding reveals specialized kinematic tuning after an abrupt cortical transition

The primary motor cortex (M1) exhibits a protracted period of development, including the development of a sensory representation long before motor outflow emerges. In rats, this representation is present by postnatal day (P) 8, when M1 activity is "discontinuous." Here, we ask how the representation changes upon the transition to "continuous" activity at P12. We use neural decoding to predict forelimb movements from M1 activity and show that a linear decoder effectively predicts limb movements at P8 but not at P12; instead, a nonlinear decoder better predicts limb movements at P12. The altered decoder performance reflects increased complexity and uniqueness of kinematic information in M1. We next show that M1's representation at P12 is more susceptible to "lesioning" of inputs and "transplanting" of M1's encoding scheme from one pup to another. Thus, the emergence of continuous M1 activity signals the developmental onset of more complex, informationally sparse, and individualized sensory representations.

How 'visual' is the visual cortex? The interactions between the visual cortex and other sensory, motivational and motor systems as enabling factors for visual perception

The definition of the visual cortex is primarily based on the evidence that lesions of this area impair visual perception. However, this does not exclude that the visual cortex may process more information than of retinal origin alone, or that other brain structures contribute to vision. Indeed, research across the past decades has shown that non-visual information, such as neural activity related to reward expectation and value, locomotion, working memory and other sensory modalities, can modulate primary visual cortical responses to retinal inputs. Nevertheless, the function of this non-visual information is poorly understood. Here we review recent evidence, coming primarily from studies in rodents, arguing that non-visual and motor effects in visual cortex play a role in visual processing itself, for instance disentangling direct auditory effects on visual cortex from effects of sound-evoked orofacial movement. These findings are placed in a broader framework casting vision in terms of predictive processing under control of frontal, reward- and motor-related systems. In contrast to the prevalent notion that vision is exclusively constructed by the visual cortical system, we propose that visual percepts are generated by a larger network-the extended visual system-spanning other sensory cortices, supramodal areas and frontal systems. This article is part of the theme issue 'Decision and control processes in multisensory perception'.

Structure and function of neocortical layer 6b

Cortical layer 6b is considered by many to be a remnant of the subplate that forms during early stages of neocortical development, but its role in the adult is not well understood. Its neuronal complement has only recently become the subject of systematic studies, and its axonal projections and synaptic input structures have remained largely unexplored despite decades of research into neocortical function. In recent years, however, layer 6b (L6b) has attracted increasing attention and its functional role is beginning to be elucidated. In this review, I will attempt to provide an overview of what is currently known about the excitatory and inhibitory neurons in this layer, their pre- and postsynaptic connectivity, and their functional implications. Similarities and differences between different cortical areas will be highlighted. Finally, layer 6b neurons are highly responsive to several neuropeptides such as orexin/hypocretin, neurotensin and cholecystokinin, in some cases exclusively. They are also strongly controlled by neurotransmitters such as acetylcholine and norepinephrine. The interaction of these neuromodulators with L6b microcircuitry and its functional consequences will also be discussed.

Id2 GABAergic interneurons comprise a neglected fourth major group of cortical inhibitory cells

Cortical GABAergic interneurons (INs) represent a diverse population of mainly locally projecting cells that provide specialized forms of inhibition to pyramidal neurons and other INs. Most recent work on INs has focused on subtypes distinguished by expression of Parvalbumin (PV), Somatostatin (SST), or Vasoactive Intestinal Peptide (VIP). However, a fourth group that includes neurogliaform cells (NGFCs) has been less well characterized due to a lack of genetic tools. Here, we show that these INs can be accessed experimentally using intersectional genetics with the gene Id2. We find that outside of layer 1 (L1), the majority of Id2 INs are NGFCs that express high levels of neuropeptide Y (NPY) and exhibit a late-spiking firing pattern, with extensive local connectivity. While much sparser, non-NGFC Id2 INs had more variable properties, with most cells corresponding to a diverse group of INs that strongly expresses the neuropeptide CCK. In vivo, using silicon probe recordings, we observed several distinguishing aspects of NGFC activity, including a strong rebound in activity immediately following the cortical down state during NREM sleep. Our study provides insights into IN diversity and NGFC distribution and properties, and outlines an intersectional genetics approach for further study of this underappreciated group of INs.

NMDA-driven dendritic modulation enables multitask representation learning in hierarchical sensory processing pathways

While sensory representations in the brain depend on context, it remains unclear how such modulations are implemented at the biophysical level, and how processing layers further in the hierarchy can extract useful features for each possible contextual state. Here, we demonstrate that dendritic N-Methyl-D-Aspartate spikes can, within physiological constraints, implement contextual modulation of feedforward processing. Such neuron-specific modulations exploit prior knowledge, encoded in stable feedforward weights, to achieve transfer learning across contexts. In a network of biophysically realistic neuron models with context-independent feedforward weights, we show that modulatory inputs to dendritic branches can solve linearly nonseparable learning problems with a Hebbian, error-modulated learning rule. We also demonstrate that local prediction of whether representations originate either from different inputs, or from different contextual modulations of the same input, results in representation learning of hierarchical feedforward weights across processing layers that accommodate a multitude of contexts.

Developmental emergence of cortical neurogliaform cell diversity

GABAergic interneurons are key regulators of cortical circuit function. Among the dozens of reported transcriptionally distinct subtypes of cortical interneurons, neurogliaform cells (NGCs) are unique: they are recruited by long-range excitatory inputs, are a source of slow cortical inhibition and are able to modulate the activity of large neuronal populations. Despite their functional relevance, the developmental emergence and diversity of NGCs remains unclear. Here, by combining single-cell transcriptomics, genetic fate mapping, and electrophysiological and morphological characterization, we reveal that discrete molecular subtypes of NGCs, with distinctive anatomical and molecular profiles, populate the mouse neocortex. Furthermore, we show that NGC subtypes emerge gradually through development, as incipient discriminant molecular signatures are apparent in preoptic area (POA)-born NGC precursors. By identifying NGC developmentally conserved transcriptional programs, we report that the transcription factor Tox2 constitutes an identity hallmark across NGC subtypes. Using CRISPR-Cas9-mediated genetic loss of function, we show that Tox2 is essential for NGC development: POA-born cells lacking Tox2 fail to differentiate into NGCs. Together, these results reveal that NGCs are born from a spatially restricted pool of Tox2+ POA precursors, after which intra-type diverging molecular programs are gradually acquired post-mitotically and result in functionally and molecularly discrete NGC cortical subtypes.

The Spatial Precision of Contextual Feedback Signals in Human V1

Neurons in the primary visual cortex (V1) receive sensory inputs that describe small, local regions of the visual scene and cortical feedback inputs from higher visual areas processing the global scene context. Investigating the spatial precision of this visual contextual modulation will contribute to our understanding of the functional role of cortical feedback inputs in perceptual computations. We used human functional magnetic resonance imaging (fMRI) to test the spatial precision of contextual feedback inputs to V1 during natural scene processing. We measured brain activity patterns in the stimulated regions of V1 and in regions that we blocked from direct feedforward input, receiving information only from non-feedforward (i.e., feedback and lateral) inputs. We measured the spatial precision of contextual feedback signals by generalising brain activity patterns across parametrically spatially displaced versions of identical images using an MVPA cross-classification approach. We found that fMRI activity patterns in cortical feedback signals predicted our scene-specific features in V1 with a precision of approximately 4 degrees. The stimulated regions of V1 carried more precise scene information than non-stimulated regions; however, these regions also contained information patterns that generalised up to 4 degrees. This result shows that contextual signals relating to the global scene are similarly fed back to V1 when feedforward inputs are either present or absent. Our results are in line with contextual feedback signals from extrastriate areas to V1, describing global scene information and contributing to perceptual computations such as the hierarchical representation of feature boundaries within natural scenes.

Laminar and dorsoventral organization of layer 1 interneuronal microcircuitry in superficial layers of the medial entorhinal cortex

Layer 1 (L1) interneurons (INs) participate in various brain functions by gating information flow in the neocortex, but their role in the medial entorhinal cortex (MEC) is still unknown, largely due to scant knowledge of MEC L1 microcircuitry. Using simultaneous triple-octuple whole-cell recordings and morphological reconstructions, we comprehensively depict L1IN networks in the MEC. We identify three morphologically distinct types of L1INs with characteristic electrophysiological properties. We dissect intra- and inter-laminar cell-type-specific microcircuits of L1INs, showing connectivity patterns different from those in the neocortex. Remarkably, motif analysis reveals transitive and clustered features of L1 networks, as well as over-represented trans-laminar motifs. Finally, we demonstrate the dorsoventral gradient of L1IN microcircuits, with dorsal L1 neurogliaform cells receiving fewer intra-laminar inputs but exerting more inhibition on L2 principal neurons. These results thus present a more comprehensive picture of L1IN microcircuitry, which is indispensable for deciphering the function of L1INs in the MEC.

Granular retrosplenial cortex layer 2/3 generates high-frequency oscillations coupled with hippocampal theta and gamma in online states or sharp-wave ripples in offline states

Neuronal oscillations support information transfer by temporally aligning the activity of anatomically distributed 'writer' and 'reader' cell assemblies. High-frequency oscillations (HFOs) such as hippocampal CA1 sharp-wave ripples (SWRs; 100-250 Hz) are sufficiently fast to initiate synaptic plasticity between assemblies and are required for memory consolidation. HFOs are observed in parietal and midline cortices including granular retrosplenial cortex (gRSC). In 'offline' brain states (e.g. quiet wakefulness) gRSC HFOs co-occur with CA1 SWRs, while in 'online' states (e.g. ambulation) HFOs persist with the emergence of theta oscillations. The mechanisms of gRSC HFO oscillations, specifically whether the gRSC can intrinsically generate HFOs, and which layers support HFOs across states, remain unclear. We addressed these issues in behaving mice using optogenetic excitation in individual layers of the gRSC and high density silicon-probe recordings across gRSC layers and hippocampus CA1. Optogenetically induced HFOs (iHFOs) could be elicited by depolarizing excitatory neurons with 100 ms half-sine wave pulses in layer 2/3 (L2/3) or layer 5 (L5) though L5 iHFOs were of lower power than in L2/3. Critically, spontaneous HFOs were only observed in L2/3 and never in L5. Intra-laminar monosynaptic connectivity between excitatory and inhibitory neurons was similar across layers, suggesting other factors restrict HFOs to L2/3. To compare HFOs in online versus offline states we analyzed, separately, HFOs that did or did not co-occur with CA1 SWRs. Using current-source density analysis we found uniform synaptic inputs to L2/3 during all gRSC HFOs, suggesting layer-specific inputs may dictate the localization of HFOs to L2/3. HFOs occurring without SWRs were aligned with the descending phase of both gRSC and CA1 theta oscillations and were coherent with CA1 high frequency gamma oscillations (50-80 Hz). These results demonstrate that gRSC can internally generate HFOs without rhythmic inputs and that HFOs occur exclusively in L2/3, coupled to distinct hippocampal oscillations in online versus offline states.

Inhibitory top-down projections from zona incerta mediate neocortical memory

Top-down projections convey a family of signals encoding previous experiences and current aims to the sensory neocortex, where they converge with external bottom-up information to enable perception and memory. Whereas top-down control has been attributed to excitatory pathways, the existence, connectivity, and information content of inhibitory top-down projections remain elusive. Here, we combine synaptic two-photon calcium imaging, circuit mapping, cortex-dependent learning, and chemogenetics in mice to identify GABAergic afferents from the subthalamic zona incerta as a major source of top-down input to the neocortex. Incertocortical transmission undergoes robust plasticity during learning that improves information transfer and mediates behavioral memory. Unlike excitatory pathways, incertocortical afferents form a disinhibitory circuit that encodes learned top-down relevance in a bidirectional manner where the rapid appearance of negative responses serves as the main driver of changes in stimulus representation. Our results therefore reveal the distinctive contribution of long-range (dis)inhibitory afferents to the computational flexibility of neocortical circuits.

Quantitative Fluorescence Analysis Reveals Dendrite-Specific Thalamocortical Plasticity in L5 Pyramidal Neurons during Learning

High-throughput anatomic data can stimulate and constrain new hypotheses about how neural circuits change in response to experience. Here, we use fluorescence-based reagents for presynaptic and postsynaptic labeling to monitor changes in thalamocortical synapses onto different compartments of layer 5 (L5) pyramidal (Pyr) neurons in somatosensory (barrel) cortex from mixed-sex mice during whisker-dependent learning (Audette et al., 2019). Using axonal fills and molecular-genetic tags for synapse identification in fixed tissue from Rbp4-Cre transgenic mice, we found that thalamocortical synapses from the higher-order posterior medial thalamic nucleus showed rapid morphologic changes in both presynaptic and postsynaptic structures at the earliest stages of sensory association training. Detected increases in thalamocortical synaptic size were compartment specific, occurring selectively in the proximal dendrites onto L5 Pyr and not at inputs onto their apical tufts in L1. Both axonal and dendritic changes were transient, normalizing back to baseline as animals became expert in the task. Anatomical measurements were corroborated by electrophysiological recordings at different stages of training. Thus, fluorescence-based analysis of input- and target-specific synapses can reveal compartment-specific changes in synapse properties during learning.SIGNIFICANCE STATEMENT Synaptic changes underlie the cellular basis of learning, experience, and neurologic diseases. Neuroanatomical methods to assess synaptic plasticity can provide critical spatial information necessary for building models of neuronal computations during learning and experience but are technically and fiscally intensive. Here, we describe a confocal fluorescence microscopy-based analytical method to assess input, cell type, and dendritic location-specific synaptic plasticity in a sensory learning assay. Our method not only confirms prior electrophysiological measurements but allows us to predict functional strength of synapses in a pathway-specific manner. Our findings also indicate that changes in primary sensory cortices are transient, occurring during early learning. Fluorescence-based synapse identification can be an efficient and easily adopted approach to study synaptic changes in a variety of experimental paradigms.

Cortical Representation of Movement Across the Developmental Transition to Continuous Neural Activity

Primary motor cortex (M1) exhibits a protracted period of development that includes the establishment of a somatosensory map long before motor outflow emerges. In rats, the sensory representation is established by postnatal day (P) 8 when cortical activity is still "discontinuous." Here, we ask how the representation survives the sudden transition to noisy "continuous" activity at P12. Using neural decoding to predict forelimb movements based solely on M1 activity, we show that a linear decoder is sufficient to predict limb movements at P8, but not at P12; in contrast, a nonlinear decoder effectively predicts limb movements at P12. The change in decoder performance at P12 reflects an increase in both the complexity and uniqueness of kinematic information available in M1. We next show that the representation at P12 is more susceptible to the deleterious effects of "lesioning" inputs and to "transplanting" M1's encoding scheme from one pup to another. We conclude that the emergence of continuous cortical activity signals the developmental onset in M1 of more complex, informationally sparse, and individualized sensory representations.

Where is the error? Hierarchical predictive coding through dendritic error computation

Top-down feedback in cortex is critical for guiding sensory processing, which has prominently been formalized in the theory of hierarchical predictive coding (hPC). However, experimental evidence for error units, which are central to the theory, is inconclusive and it remains unclear how hPC can be implemented with spiking neurons. To address this, we connect hPC to existing work on efficient coding in balanced networks with lateral inhibition and predictive computation at apical dendrites. Together, this work points to an efficient implementation of hPC with spiking neurons, where prediction errors are computed not in separate units, but locally in dendritic compartments. We then discuss the correspondence of this model to experimentally observed connectivity patterns, plasticity, and dynamics in cortex.

Probing top-down information in neocortical layer 1

Accurate perception of the environment is a constructive process that requires integration of external bottom-up sensory signals with internally generated top-down information. Decades of work have elucidated how sensory neocortex processes physical stimulus features. By contrast, examining how top-down information is encoded and integrated with bottom-up signals has been challenging using traditional neuroscience methods. Recent technological advances in functional imaging of brain-wide afferents in behaving mice have enabled the direct measurement of top-down information. Here, we review the emerging literature on encoding of these internally generated signals by different projection systems enriched in neocortical layer 1 during defined brain functions, including memory, attention, and predictive coding. Moreover, we identify gaps in current knowledge and highlight future directions for this rapidly advancing field.

Contrast polarity-specific mapping improves efficiency of neuronal computation for collision detection

Neurons receive information through their synaptic inputs, but the functional significance of how those inputs are mapped on to a cell's dendrites remains unclear. We studied this question in a grasshopper visual neuron that tracks approaching objects and triggers escape behavior before an impending collision. In response to black approaching objects, the neuron receives OFF excitatory inputs that form a retinotopic map of the visual field onto compartmentalized, distal dendrites. Subsequent processing of these OFF inputs by active membrane conductances allows the neuron to discriminate the spatial coherence of such stimuli. In contrast, we show that ON excitatory synaptic inputs activated by white approaching objects map in a random manner onto a more proximal dendritic field of the same neuron. The lack of retinotopic synaptic arrangement results in the neuron's inability to discriminate the coherence of white approaching stimuli. Yet, the neuron retains the ability to discriminate stimulus coherence for checkered stimuli of mixed ON/OFF polarity. The coarser mapping and processing of ON stimuli thus has a minimal impact, while reducing the total energetic cost of the circuit. Further, we show that these differences in ON/OFF neuronal processing are behaviorally relevant, being tightly correlated with the animal's escape behavior to light and dark stimuli of variable coherence. Our results show that the synaptic mapping of excitatory inputs affects the fine stimulus discrimination ability of single neurons and document the resulting functional impact on behavior.

A Comparison of Partial Information Decompositions Using Data from Real and Simulated Layer 5b Pyramidal Cells

Partial information decomposition allows the joint mutual information between an output and a set of inputs to be divided into components that are synergistic or shared or unique to each input. We consider five different decompositions and compare their results using data from layer 5b pyramidal cells in two different studies. The first study was on the amplification of somatic action potential output by apical dendritic input and its regulation by dendritic inhibition. We find that two of the decompositions produce much larger estimates of synergy and shared information than the others, as well as large levels of unique misinformation. When within-neuron differences in the components are examined, the five methods produce more similar results for all but the shared information component, for which two methods produce a different statistical conclusion from the others. There are some differences in the expression of unique information asymmetry among the methods. It is significantly larger, on average, under dendritic inhibition. Three of the methods support a previous conclusion that apical amplification is reduced by dendritic inhibition. The second study used a detailed compartmental model to produce action potentials for many combinations of the numbers of basal and apical synaptic inputs. Decompositions of the entire data set produce similar differences to those in the first study. Two analyses of decompositions are conducted on subsets of the data. In the first, the decompositions reveal a bifurcation in unique information asymmetry. For three of the methods, this suggests that apical drive switches to basal drive as the strength of the basal input increases, while the other two show changing mixtures of information and misinformation. Decompositions produced using the second set of subsets show that all five decompositions provide support for properties of cooperative context-sensitivity—to varying extents.

From Analog to Digital Computing: Is Homo sapiens’ Brain on Its Way to Become a Turing Machine?

The abstract basis of modern computation is the formal description of a finite state machine, the Universal Turing Machine, based on manipulation of integers and logic symbols. In this contribution to the discourse on the computer-brain analogy, we discuss the extent to which analog computing, as performed by the mammalian brain, is like and unlike the digital computing of Universal Turing Machines. We begin with ordinary reality being a permanent dialog between continuous and discontinuous worlds. So it is with computing, which can be analog or digital, and is often mixed. The theory behind computers is essentially digital, but efficient simulations of phenomena can be performed by analog devices; indeed, any physical calculation requires implementation in the physical world and is therefore analog to some extent, despite being based on abstract logic and arithmetic. The mammalian brain, comprised of neuronal networks, functions as an analog device and has given rise to artificial neural networks that are implemented as digital algorithms but function as analog models would. Analog constructs compute with the implementation of a variety of feedback and feedforward loops. In contrast, digital algorithms allow the implementation of recursive processes that enable them to generate unparalleled emergent properties. We briefly illustrate how the cortical organization of neurons can integrate signals and make predictions analogically. While we conclude that brains are not digital computers, we speculate on the recent implementation of human writing in the brain as a possible digital path that slowly evolves the brain into a genuine (slow) Turing machine.

Dynamic interplay between thalamic activity and Cajal-Retzius cells regulates the wiring of cortical layer 1

Cortical wiring relies on guidepost cells and activity-dependent processes that are thought to act sequentially. Here, we show that the construction of layer 1 (L1), a main site of top-down integration, is regulated by crosstalk between transient Cajal-Retzius cells (CRc) and spontaneous activity of the thalamus, a main driver of bottom-up information. While activity was known to regulate CRc migration and elimination, we found that prenatal spontaneous thalamic activity and NMDA receptors selectively control CRc early density, without affecting their demise. CRc density, in turn, regulates the distribution of upper layer interneurons and excitatory synapses, thereby drastically impairing the apical dendrite activity of output pyramidal neurons. In contrast, postnatal sensory-evoked activity had a limited impact on L1 and selectively perturbed basal dendrites synaptogenesis. Collectively, our study highlights a remarkable interplay between thalamic activity and CRc in L1 functional wiring, with major implications for our understanding of cortical development.

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Prenatal thalamic waves of activity regulate CRc density in L1

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Prenatal and postnatal CRc manipulations alter specific interneuron populations

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Postnatal CRc shape L5 apical dendrite structural and functional properties

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Early sensory activity selectively regulates L5 basal dendrite spine formation

Fan cells in lateral entorhinal cortex directly influence medial entorhinal cortex through synaptic connections in layer 1

Standard models for spatial and episodic memory suggest that the lateral entorhinal cortex (LEC) and medial entorhinal cortex (MEC) send parallel independent inputs to the hippocampus, each carrying different types of information. Here, we evaluate the possibility that information is integrated between divisions of the entorhinal cortex prior to reaching the hippocampus. We demonstrate that, in mice, fan cells in layer 2 (L2) of LEC that receive neocortical inputs, and that project to the hippocampal dentate gyrus, also send axon collaterals to layer 1 (L1) of the MEC. Activation of inputs from fan cells evokes monosynaptic glutamatergic excitation of stellate and pyramidal cells in L2 of the MEC, typically followed by inhibition that contains fast and slow components mediated by GABA_A and GABA_B receptors, respectively. Inputs from fan cells also directly activate interneurons in L1 and L2 of MEC, with synaptic connections from L1 interneurons accounting for slow feedforward inhibition of L2 principal cell populations. The relative strength of excitation and inhibition following fan cell activation differs substantially between neurons and is largely independent of anatomical location. Our results demonstrate that the LEC, in addition to directly influencing the hippocampus, can activate or inhibit major hippocampal inputs arising from the MEC. Thus, local circuits in the superficial MEC may combine spatial information with sensory and higher order signals from the LEC, providing a substrate for integration of 'what' and 'where' components of episodic memories.

Evidence for Layer-Specific Connectional Heterogeneity in the Mouse Auditory Corticocollicular System

The auditory cortex (AC) sends long-range projections to virtually all subcortical auditory structures. One of the largest and most complex of these-the projection between AC and inferior colliculus (IC; the corticocollicular pathway)-originates from layer 5 and deep layer 6. Though previous work has shown that these two corticocollicular projection systems have different physiological properties and network connectivities, their functional organization is poorly understood. Here, using a combination of traditional and viral tracers combined with in vivo imaging in both sexes of the mouse, we observed that layer 5 and layer 6 corticocollicular neurons differ in their areas of origin and termination patterns. Layer 5 corticocollicular neurons are concentrated in primary AC, while layer 6 corticocollicular neurons emanate from broad auditory and limbic areas in the temporal cortex. In addition, layer 5 sends dense projections of both small and large (>1 µm2 area) terminals to all regions of nonlemniscal IC, while layer 6 sends small terminals to the most superficial 50-100 µm of the IC. These findings suggest that layer 5 and 6 corticocollicular projections are optimized to play distinct roles in corticofugal modulation. Layer 5 neurons provide strong, rapid, and unimodal feedback to the nonlemniscal IC, while layer 6 neurons provide heteromodal and limbic modulation diffusely to the nonlemniscal IC. Such organizational diversity in the corticocollicular pathway may help to explain the heterogeneous effects of corticocollicular manipulations and, given similar diversity in corticothalamic pathways, may be a general principle in top-down modulation.SIGNIFICANCE STATEMENT We demonstrate that a major descending system in the brain is actually two systems. That is, the auditory corticocollicular projection, which exerts considerable influence over the midbrain, comprises two projections: one from layer 5 and the other from layer 6. The layer 6 projection is diffusely organized, receives multisensory inputs, and ends in small terminals; while the layer 5 projection is derived from a circumscribed auditory cortical area and ends in large terminals. These data suggest that the varied effects of cortical manipulations on the midbrain may be related to effects on two disparate systems. These findings have broader implications because other descending systems derive from two layers. Therefore, a duplex organization may be a common motif in descending control.

A new role for visual experience in top-down cortical development

In this issue of Neuron, Ibrahim et al. (2021) examine the rules by which top-down connections are made on visual cortical layer 1 interneurons, discovering activity-dependent cooperative interactions with visual input that are specific to neurogliaform cells and anterior cingulate cortex.

Bottom-up inputs are required for establishment of top-down connectivity onto cortical layer 1 neurogliaform cells

Higher-order projections to sensory cortical areas converge on layer 1 (L1), the primary site for integration of top-down information via the apical dendrites of pyramidal neurons and L1 GABAergic interneurons. Here we investigated the contribution of early thalamic inputs onto L1 interneurons for establishment of top-down connectivity in the primary visual cortex. We find that bottom-up thalamic inputs predominate during L1 development and preferentially target neurogliaform cells. We show that these projections are critical for the subsequent strengthening of top-down inputs from the anterior cingulate cortex onto L1 neurogliaform cells. Sensory deprivation or selective removal of thalamic afferents blocked this phenomenon. Although early activation of the anterior cingulate cortex resulted in premature strengthening of these top-down afferents, this was dependent on thalamic inputs. Our results demonstrate that proper establishment of top-down connectivity in the visual cortex depends critically on bottom-up inputs from the thalamus during postnatal development.

Memories off the top of your head

[Figure: see text].

Apical amplification-a cellular mechanism of conscious perception?

We present a theoretical view of the cellular foundations for network-level processes involved in producing our conscious experience. Inputs to apical synapses in layer 1 of a large subset of neocortical cells are summed at an integration zone near the top of their apical trunk. These inputs come from diverse sources and provide a context within which the transmission of information abstracted from sensory input to their basal and perisomatic synapses can be amplified when relevant. We argue that apical amplification enables conscious perceptual experience and makes it more flexible, and thus more adaptive, by being sensitive to context. Apical amplification provides a possible mechanism for recurrent processing theory that avoids strong loops. It makes the broadcasting hypothesized by global neuronal workspace theories feasible while preserving the distinct contributions of the individual cells receiving the broadcast. It also provides mechanisms that contribute to the holistic aspects of integrated information theory. As apical amplification is highly dependent on cholinergic, aminergic, and other neuromodulators, it relates the specific contents of conscious experience to global mental states and to fluctuations in arousal when awake. We conclude that apical dendrites provide a cellular mechanism for the context-sensitive selective amplification that is a cardinal prerequisite of conscious perception.

Corticothalamic Pathways From Layer 5: Emerging Roles in Computation and Pathology

Large portions of the thalamus receive strong driving input from cortical layer 5 (L5) neurons but the role of this important pathway in cortical and thalamic computations is not well understood. L5-recipient "higher-order" thalamic regions participate in cortico-thalamo-cortical (CTC) circuits that are increasingly recognized to be (1) anatomically and functionally distinct from better-studied "first-order" CTC networks, and (2) integral to cortical activity related to learning and perception. Additionally, studies are beginning to elucidate the clinical relevance of these networks, as dysfunction across these pathways have been implicated in several pathological states. In this review, we highlight recent advances in understanding L5 CTC networks across sensory modalities and brain regions, particularly studies leveraging cell-type-specific tools that allow precise experimental access to L5 CTC circuits. We aim to provide a focused and accessible summary of the anatomical, physiological, and computational properties of L5-originating CTC networks, and outline their underappreciated contribution in pathology. We particularly seek to connect single-neuron and synaptic properties to network (dys)function and emerging theories of cortical computation, and highlight information processing in L5 CTC networks as a promising focus for computational studies.

The Emergence of Network Activity Patterns in the Somatosensory Cortex - An Early Window to Autism Spectrum Disorders

Across mammalian species, patterned activity in neural populations is a prominent feature of developing sensory cortices. Numerous studies have long appreciated the diversity of these patterns, characterizing their differences in spatial and temporal dynamics. In the murine somatosensory cortex, neuronal co-activation is thought to guide the formation of sensory maps and prepare the cortex for sensory processing after birth. While pioneering studies deftly utilized slice electrophysiology and unit recordings to characterize correlated activity, a detailed understanding of the underlying circuits remains poorly understood. More recently, advances in in vivo calcium imaging in awake mouse pups and increasing genetic tractability of neuronal types have allowed unprecedented manipulation of circuit components at select developmental timepoints. These novel approaches have proven fundamental in uncovering the identity of neurons engaged in correlated activity during development. In particular, recent studies have highlighted interneurons as key in refining the spatial extent and temporal progression of patterned activity. Here, we discuss how emergent synchronous activity across the first postnatal weeks is shaped by underlying gamma aminobutyric acid (GABA)ergic contributors in the somatosensory cortex. Further, the importance of participation in specific activity patterns per se for neuronal maturation and perdurance will be of particular highlight in this survey of recent literature. Finally, we underscore how aberrant neuronal synchrony and disrupted inhibitory interneuron activity underlie sensory perturbations in neurodevelopmental disorders, particularly Autism Spectrum Disorders (ASDs), emphasizing the importance of future investigative approaches that incorporate the spatiotemporal features of patterned activity alongside the cellular components to probe disordered circuit assembly.