Looking for the roots of cortical sensory computation in three-layered cortices

Transcriptomic Correlates of State Modulation in GABAergic Interneurons: A Cross-Species Analysis

GABAergic inhibitory interneurons comprise many subtypes that differ in their molecular, anatomical, and functional properties. In mouse visual cortex, they also differ in their modulation with an animal's behavioral state, and this state modulation can be predicted from the first principal component (PC) of the gene expression matrix. Here, we ask whether this link between transcriptome and state-dependent processing generalizes across species. To this end, we analysed seven single-cell and single-nucleus RNA sequencing datasets from mouse, human, songbird, and turtle forebrains. Despite homology at the level of cell types, we found clear differences between transcriptomic PCs, with greater dissimilarities between evolutionarily distant species. These dissimilarities arise from two factors: divergence in gene expression within homologous cell types and divergence in cell-type abundance. We also compare the expression of cholinergic receptors, which are thought to causally link transcriptome and state modulation. Several cholinergic receptors predictive of state modulation in mouse interneurons are differentially expressed between species. Circuit modelling and mathematical analyses suggest conditions under which these expression differences could translate into functional differences.

Can we gain translational insights into the functional roles of cerebral cortex from acortical rodent and naturally acortical zebrafish models?

Cerebral cortex is found only in mammals and is particularly prominent and developed in humans. Various rodent models with fully or partially ablated cortex are commonly used to probe the role of cortex in brain functions and its multiple subcortical projections, including pallium, thalamus and the limbic system. Various rodent models are traditionally used to study the role of cortex in brain functions. A small teleost fish, the zebrafish (Danio rerio), has gained popularity in neuroscience research, and albeit (like other fishes) lacking cortex, its brain performs well some key functions (e.g., memory, consciousness and motivation) with complex, context-specific and well-defined behaviors. Can rodent and zebrafish models help generate insights into the role of cortex in brain functions, and dissect its cortex-specific (vs. non-cortical) functions? To address this conceptual question, here we evaluate brain functionality in intact vs. decorticated rodents and further compare it in the zebrafish, a naturally occurring acortical species. Overall, comparing cortical and acortical rodent models with naturally acortical zebrafish reveals both distinct and overlapping contributions of neocortex and 'precortical' zebrafish telencephalic regions to higher brain functions. Albeit morphologically different, mammalian neocortex and fish pallium may possess more functional similarities than it is presently recognized, calling for further integrative research utilizing both cortical and decorticated/acortical vertebrate model organisms.

The emergence of enhanced intelligence in a brain-inspired cognitive architecture

The Causal Cognitive Architecture is a brain-inspired cognitive architecture developed from the hypothesis that the navigation circuits in the ancestors of mammals duplicated to eventually form the neocortex. Thus, millions of neocortical minicolumns are functionally modeled in the architecture as millions of "navigation maps." An investigation of a cognitive architecture based on these navigation maps has previously shown that modest changes in the architecture allow the ready emergence of human cognitive abilities such as grounded, full causal decision-making, full analogical reasoning, and near-full compositional language abilities. In this study, additional biologically plausible modest changes to the architecture are considered and show the emergence of super-human planning abilities. The architecture should be considered as a viable alternative pathway toward the development of more advanced artificial intelligence, as well as to give insight into the emergence of natural human intelligence.

Patterning the cerebral cortex into distinct functional domains during development

The cerebral cortex is compartmentalized into multiple regions, including the newly evolved neocortex and evolutionarily older paleocortex and archicortex. These broad cortical regions can be further subdivided into different functional domains, each with its own unique cytoarchitecture and distinct set of input and output projections to perform specific functions. While many excitatory projection neurons show region-specific gene expression profiles, the cells are derived from the seemingly uniform progenitors in the dorsal telencephalon. Much progress has been made in defining the genetic mechanisms involved in generating the morphological and functional diversity of the central nervous system. In this review, we summarize the current knowledge of mouse corticogenesis and discuss key events involved in cortical patterning during early developmental stages.

Single spikes drive sequential propagation and routing of activity in a cortical network

Single spikes can trigger repeatable firing sequences in cortical networks. The mechanisms that support reliable propagation of activity from such small events and their functional consequences remain unclear. By constraining a recurrent network model with experimental statistics from turtle cortex, we generate reliable and temporally precise sequences from single spike triggers. We find that rare strong connections support sequence propagation, while dense weak connections modulate propagation reliability. We identify sections of sequences corresponding to divergent branches of strongly connected neurons which can be selectively gated. Applying external inputs to specific neurons in the sparse backbone of strong connections can effectively control propagation and route activity within the network. Finally, we demonstrate that concurrent sequences interact reliably, generating a highly combinatorial space of sequence activations. Our results reveal the impact of individual spikes in cortical circuits, detailing how repeatable sequences of activity can be triggered, sustained, and controlled during cortical computations.

What Is It Like to Be a Bass? Red Herrings, Fish Pain and the Study of Animal Sentience

Debates around fishes' ability to feel pain concern sentience: do reactions to tissue damage indicate evaluative consciousness (conscious affect), or mere nociception? Thanks to Braithwaite's discovery of trout nociceptors, and concerns that current practices could compromise welfare in countless fish, this issue's importance is beyond dispute. However, nociceptors are merely necessary, not sufficient, for true pain, and many measures held to indicate sentience have the same problem. The question of whether fish feel pain - or indeed anything at all - therefore stimulates sometimes polarized debate. Here, we try to bridge the divide. After reviewing key consciousness concepts, we identify "red herring" measures that should not be used to infer sentience because also present in non-sentient organisms, notably those lacking nervous systems, like plants and protozoa (P); spines disconnected from brains (S); decerebrate mammals and birds (D); and humans in unaware states (U). These "S.P.U.D. subjects" can show approach/withdrawal; react with apparent emotion; change their reactivity with food deprivation or analgesia; discriminate between stimuli; display Pavlovian learning, including some forms of trace conditioning; and even learn simple instrumental responses. Consequently, none of these responses are good indicators of sentience. Potentially more valid are aspects of working memory, operant conditioning, the self-report of state, and forms of higher order cognition. We suggest new experiments on humans to test these hypotheses, as well as modifications to tests for "mental time travel" and self-awareness (e.g., mirror self-recognition) that could allow these to now probe sentience (since currently they reflect perceptual rather than evaluative, affective aspects of consciousness). Because "bullet-proof" neurological and behavioral indicators of sentience are thus still lacking, agnosticism about fish sentience remains widespread. To end, we address how to balance such doubts with welfare protection, discussing concerns raised by key skeptics in this debate. Overall, we celebrate the rigorous evidential standards required by those unconvinced that fish are sentient; laud the compassion and ethical rigor shown by those advocating for welfare protections; and seek to show how precautionary principles still support protecting fish from physical harm.

Neural architectures in the light of comparative connectomics

Since the Cambrian, animals diversified from a few body forms or bauplans, into many extinct and all extant species. A characteristic neural architecture serves each bauplan. How the connectome of each animal differs from that of closely related species or whether it converged into an optimal architecture shared with more distant ones is unknown. Recent technological innovations in molecular biology, microscopy, digital data storage and processing, and computational neuroscience have lowered the barriers for whole-brain connectomics. Comparative connectomics of suitable, relatively small, representative species across the phylogenetic tree can infer the archetypal neural architecture of each bauplan and identify any circuits that possibly converged onto a shared and potentially optimal, structure.

Mechanisms, development, and comparative perspectives on experience-dependent plasticity in social behavior

Revealing the mechanisms underlying experience-dependent plasticity is a hallmark of behavioral neuroscience. While the study of social behavior has focused primarily on the neuroendocrine and neural control of social behaviors, the plasticity of these innate behaviors has received relatively less attention. Here, we review studies on mating-dependent changes to social behavior and neural circuitry across mammals, birds, and reptiles. We provide an overview of species similarities and differences in the effects of mating experiences on motivational and performative aspects of sexual behaviors, on sensory processing and preferences, and on the experience-dependent consolidation of sexual behavior. We also discuss recent insights into the neural mechanisms of and developmental influences on mating-dependent changes and outline promising approaches to investigate evolutionary parallels and divergences in experience-dependent plasticity.

Finding the Brain in the Nose

Olfaction is fundamentally distinct from other sensory modalities. Natural odor stimuli are complex mixtures of volatile chemicals that interact in the nose with a receptor array that, in rodents, is built from more than 1,000 unique receptors. These interactions dictate a peripheral olfactory code, which in the brain is transformed and reformatted as it is broadcast across a set of highly interconnected olfactory regions. Here we discuss the problems of characterizing peripheral population codes for olfactory stimuli, of inferring the specific functions of different higher olfactory areas given their extensive recurrence, and of ultimately understanding how odor representations are linked to perception and action. We argue that, despite the differences between olfaction and other sensory modalities, addressing these specific questions will reveal general principles underlying brain function.

Cell assembly formation and structure in a piriform cortex model

The piriform cortex is rich in recurrent excitatory synaptic connections between pyramidal neurons. We asked how such connections could shape cortical responses to olfactory lateral olfactory tract (LOT) inputs. For this, we constructed a computational network model of anterior piriform cortex with 2000 multicompartment, multiconductance neurons (500 semilunar, 1000 layer 2 and 500 layer 3 pyramids; 200 superficial interneurons of two types; 500 deep interneurons of three types; 500 LOT afferents), incorporating published and unpublished data. With a given distribution of LOT firing patterns, and increasing the strength of recurrent excitation, a small number of firing patterns were observed in pyramidal cell networks: first, sparse firings; then temporally and spatially concentrated epochs of action potentials, wherein each neuron fires one or two spikes; then more synchronized events, associated with bursts of action potentials in some pyramidal neurons. We suggest that one function of anterior piriform cortex is to transform ongoing streams of input spikes into temporally focused spike patterns, called here "cell assemblies", that are salient for downstream projection areas.

Principles of odor coding in vertebrates and artificial chemosensory systems

The biological olfactory system is the sensory system responsible for the detection of the chemical composition of the environment. Several attempts to mimic biological olfactory systems have led to various artificial olfactory systems using different technical approaches. Here we provide a parallel description of biological olfactory systems and their technical counterparts. We start with a presentation of the input to the systems, the stimuli, and treat the interface between the external world and the environment where receptor neurons or artificial chemosensors reside. We then delineate the functions of receptor neurons and chemosensors as well as their overall I-O relationships. Up to this point, our account of the systems goes along similar lines. The next processing steps differ considerably: while in biology the processing step following the receptor neurons is the "integration" and "processing" of receptor neuron outputs in the olfactory bulb, this step has various realizations in electronic noses. For a long period of time, the signal processing stages beyond the olfactory bulb, i.e., the higher olfactory centers were little studied. Only recently there has been a marked growth of studies tackling the information processing in these centers. In electronic noses, a third stage of processing has virtually never been considered. In this review, we provide an up-to-date overview of the current knowledge of both fields and, for the first time, attempt to tie them together. We hope it will be a breeding ground for better information, communication, and data exchange between very related but so far little connected fields.

An Evolutionary Microcircuit Approach to the Neural Basis of High Dimensional Sensory Processing in Olfaction

Odor stimuli consist of thousands of possible molecules, each molecule with many different properties, each property a dimension of the stimulus. Processing these high dimensional stimuli would appear to require many stages in the brain to reach odor perception, yet, in mammals, after the sensory receptors this is accomplished through only two regions, the olfactory bulb and olfactory cortex. We take a first step toward a fundamental understanding by identifying the sequence of local operations carried out by microcircuits in the pathway. Parallel research provided strong evidence that processed odor information is spatial representations of odor molecules that constitute odor images in the olfactory bulb and odor objects in olfactory cortex. Paleontology provides a unique advantage with evolutionary insights providing evidence that the basic architecture of the olfactory pathway almost from the start ∼330 million years ago (mya) has included an overwhelming input from olfactory sensory neurons combined with a large olfactory bulb and olfactory cortex to process that input, driven by olfactory receptor gene duplications. We identify a sequence of over 20 microcircuits that are involved, and expand on results of research on several microcircuits that give the best insights thus far into the nature of the high dimensional processing.

Circuit-Specific Dendritic Development in the Piriform Cortex

Dendritic geometry is largely determined during postnatal development and has a substantial impact on neural function. In sensory processing, postnatal development of the dendritic tree is affected by two dominant circuit motifs, ascending sensory feedforward inputs and descending and local recurrent connections. In the three-layered anterior piriform cortex (aPCx), neurons in the sublayers 2a and 2b display vertical segregation of these two circuit motifs. Here, we combined electrophysiology, detailed morphometry, and Ca²⁺ imaging in acute mouse brain slices and modeling to study circuit-specific aspects of dendritic development. We observed that determination of branching complexity, dendritic length increases, and pruning occurred in distinct developmental phases. Layer 2a and layer 2b neurons displayed developmental phase-specific differences between their apical and basal dendritic trees related to differences in circuit incorporation. We further identified functional candidate mechanisms for circuit-specific differences in postnatal dendritic growth in sublayers 2a and 2b at the mesoscale and microscale levels. Already in the first postnatal week, functional connectivity of layer 2a and layer 2b neurons during early spontaneous network activity scales with differences in basal dendritic growth. During the early critical period of sensory plasticity in the piriform cortex, our data are consistent with a model that proposes a role for dendritic NMDA-spikes in selecting branches for survival during developmental pruning in apical dendrites. The different stages of the morphologic and functional developmental pattern differences between layer 2a and layer 2b neurons demonstrate the complex interplay between dendritic development and circuit specificity.

Reliable Sequential Activation of Neural Assemblies by Single Pyramidal Cells in a Three-Layered Cortex

Recent studies reveal the occasional impact of single neurons on surround firing statistics and even simple behaviors. Exploiting the advantages of a simple cortex, we examined the influence of single pyramidal neurons on surrounding cortical circuits. Brief activation of single neurons triggered reliable sequences of firing in tens of other excitatory and inhibitory cortical neurons, reflecting cascading activity through local networks, as indicated by delayed yet precisely timed polysynaptic subthreshold potentials. The evoked patterns were specific to the pyramidal cell of origin, extended over hundreds of micrometers from their source, and unfolded over up to 200 ms. Simultaneous activation of pyramidal cell pairs indicated balanced control of population activity, preventing paroxysmal amplification. Single cortical pyramidal neurons can thus trigger reliable postsynaptic activity that can propagate in a reliable fashion through cortex, generating rapidly evolving and non-random firing sequences reminiscent of those observed in mammalian hippocampus during "replay" and in avian song circuits.

Neuron Names: A Gene- and Property-Based Name Format, With Special Reference to Cortical Neurons

Precision in neuron names is increasingly needed. We are entering a new era in which classical anatomical criteria are only the beginning toward defining the identity of a neuron as carried in its name. New criteria include patterns of gene expression, membrane properties of channels and receptors, pharmacology of neurotransmitters and neuropeptides, physiological properties of impulse firing, and state-dependent variations in expression of characteristic genes and proteins. These gene and functional properties are increasingly defining neuron types and subtypes. Clarity will therefore be enhanced by conveying as much as possible the genes and properties in the neuron name. Using a tested format of parent-child relations for the region and subregion for naming a neuron, we show how the format can be extended so that these additional properties can become an explicit part of a neuron's identity and name, or archived in a linked properties database. Based on the mouse, examples are provided for neurons in several brain regions as proof of principle, with extension to the complexities of neuron names in the cerebral cortex. The format has dual advantages, of ensuring order in archiving the hundreds of neuron types across all brain regions, as well as facilitating investigation of a given neuron type or given gene or property in the context of all its properties. In particular, we show how the format is extensible to the variety of neuron types and subtypes being revealed by RNA-seq and optogenetics. As current research reveals increasingly complex properties, the proposed approach can facilitate a consensus that goes beyond traditional neuron types.

Neuron Names: A Gene- and Property-Based Name Format, With Special Reference to Cortical Neurons

Precision in neuron names is increasingly needed. We are entering a new era in which classical anatomical criteria are only the beginning toward defining the identity of a neuron as carried in its name. New criteria include patterns of gene expression, membrane properties of channels and receptors, pharmacology of neurotransmitters and neuropeptides, physiological properties of impulse firing, and state-dependent variations in expression of characteristic genes and proteins. These gene and functional properties are increasingly defining neuron types and subtypes. Clarity will therefore be enhanced by conveying as much as possible the genes and properties in the neuron name. Using a tested format of parent-child relations for the region and subregion for naming a neuron, we show how the format can be extended so that these additional properties can become an explicit part of a neuron's identity and name, or archived in a linked properties database. Based on the mouse, examples are provided for neurons in several brain regions as proof of principle, with extension to the complexities of neuron names in the cerebral cortex. The format has dual advantages, of ensuring order in archiving the hundreds of neuron types across all brain regions, as well as facilitating investigation of a given neuron type or given gene or property in the context of all its properties. In particular, we show how the format is extensible to the variety of neuron types and subtypes being revealed by RNA-seq and optogenetics. As current research reveals increasingly complex properties, the proposed approach can facilitate a consensus that goes beyond traditional neuron types.

Sodium and potassium conductances in principal neurons of the mouse piriform cortex: a quantitative description

KEY POINTS

The primary olfactory (or piriform) cortex is a promising model system for understanding how the cerebral cortex processes sensory information, although an investigation of the piriform cortex is hindered by a lack of detailed information about the intrinsic electrical properties of its component neurons. In the present study, we quantify the properties of voltage-dependent sodium currents and voltage- and calcium-dependent potassium currents in two important classes of excitatory neurons in the main input layer of the piriform cortex. We identify several classes of these currents and show that their properties are similar to those found in better-studied cortical regions. Our detailed quantitative descriptions of these currents will be valuable to computational neuroscientists who aim to build models that explain how the piriform cortex encodes odours.

ABSTRACT

The primary olfactory cortex (or piriform cortex, PC) is an anatomically simple palaeocortex that is increasingly used as a model system for investigating cortical sensory processing. However, little information is available on the intrinsic electrical conductances in neurons of the PC, hampering efforts to build realistic computational models of this cortex. In the present study, we used nucleated macropatches and whole-cell recordings to rigorously quantify the biophysical properties of voltage-gated sodium (Na_V ), voltage-gated potassium (K_V ) and calcium-activated potassium (K_Ca ) conductances in two major classes of glutamatergic neurons in layer 2 of the PC, semilunar (SL) cells and superficial pyramidal (SP) cells. We found that SL and SP cells both express a fast-inactivating Na_V current, two types of K_V current (A-type and delayed rectifier-type) and three types of K_Ca current (fast-, medium- and slow-afterhyperpolarization currents). The kinetic and voltage-dependent properties of the Na_V and K_V conductances were, with some exceptions, identical in SL and SP cells and similar to those found in neocortical pyramidal neurons. The K_Ca conductances were also similar across the different types of neurons. Our results are summarized in a series of empirical equations that should prove useful to computational neuroscientists seeking to model the PC. More broadly, our findings indicate that, at the level of single-cell electrical properties, this palaeocortex is not so different from the neocortex, vindicating efforts to use the PC as a model of cortical sensory processing in general.

Big data and the industrialization of neuroscience: A safe roadmap for understanding the brain?

New technologies in neuroscience generate reams of data at an exponentially increasing rate, spurring the design of very-large-scale data-mining initiatives. Several supranational ventures are contemplating the possibility of achieving, within the next decade(s), full simulation of the human brain.

Coupling of synaptic inputs to local cortical activity differs among neurons and adapts after stimulus onset

Cortical activity contributes significantly to the high variability of sensory responses of interconnected pyramidal neurons, which has crucial implications for sensory coding. Yet, largely because of technical limitations of in vivo intracellular recordings, the coupling of a pyramidal neuron's synaptic inputs to the local cortical activity has evaded full understanding. Here we obtained excitatory synaptic conductance ( g) measurements from putative pyramidal neurons and local field potential (LFP) recordings from adjacent cortical circuits during visual processing in the turtle whole brain ex vivo preparation. We found a range of g-LFP coupling across neurons. Importantly, for a given neuron, g-LFP coupling increased at stimulus onset and then relaxed toward intermediate values during continued visual stimulation. A model network with clustered connectivity and synaptic depression reproduced both the diversity and the dynamics of g-LFP coupling. In conclusion, these results establish a rich dependence of single-neuron responses on anatomical, synaptic, and emergent network properties. NEW & NOTEWORTHY Cortical neurons are strongly influenced by the networks in which they are embedded. To understand sensory processing, we must identify the nature of this influence and its underlying mechanisms. Here we investigate synaptic inputs to cortical neurons, and the nearby local field potential, during visual processing. We find a range of neuron-to-network coupling across cortical neurons. This coupling is dynamically modulated during visual processing via biophysical and emergent network properties.

Neocortical Lamination: Insights from Neuron Types and Evolutionary Precursors

The neocortex is characterized by lamination of its neuron cell bodies in six layers, but there are few clues as to how this comes about and what is its function. Recent studies provide evidence that evolution from simple three-layer cortex may give insight into this problem. Three-layer cortex arose in the olfactory, hippocampal and dorsal cortex of the early amniote forebrain based on a cortical module of excitatory and inhibitory inputs to an intratelencephalic (IT) type of pyramidal neuron with feedback excitation and inhibition and related interneurons. We summarize recent evidence suggesting the hypothesis that the developmental program of three-layer olfactory cortex was co-opted to form six-layer mammalian neocortex, elaborating IT cortical units in layers 2-6 while adding layer 4 stellate cells, layer 5B pyramidal tract (PT) cells and layer 6 corticothalamic (CT) cells.

The turtle visual system mediates a complex spatiotemporal transformation of visual stimuli into cortical activity

The three-layered visual cortex of turtle is characterized by extensive intracortical axonal projections and receives non-retinotopic axonal projections from lateral geniculate nucleus. What spatiotemporal transformation of visual stimuli into cortical activity arises from such tangle of malleable cortical inputs and intracortical connections? To address this question, we obtained band-pass filtered extracellular recordings of neural activity in turtle dorsal cortex during visual stimulation of the retina. We discovered important spatial and temporal features of stimulus-modulated cortical local field potential (LFP) recordings. Spatial receptive fields span large areas of the visual field, have an intricate internal structure, and lack directional tuning. The receptive field structure varies across recording sites in a distant-dependent manner. Such composite spatial organization of stimulus-modulated cortical activity is accompanied by an equally multifaceted temporal organization. Cortical visual responses are delayed, persistent, and oscillatory. Further, prior cortical activity contributes globally to adaptation in turtle visual cortex. In conclusion, these results demonstrate convoluted spatiotemporal transformations of visual stimuli into stimulus-modulated cortical activity that, at present, largely evade computational frameworks.

The Lamprey Pallium Provides a Blueprint of the Mammalian Layered Cortex

The basic architecture of the mammalian neocortex is remarkably similar across species. Pallial structures in the reptilian brain are considered amniote precursors of mammalian neocortex, whereas pallia of anamniotes ("lower" vertebrates) have been deemed largely insignificant with respect to homology. Here, we examine the cytoarchitecture of the lateral pallium in the lamprey, the phylogenetically oldest group of extant vertebrates. We reveal a three-layered structure with similar excitatory cell types as in the mammalian cortex and GABAergic interneurons. The ventral parts are sensory areas receiving monosynaptic thalamic input that can be activated from the optic nerve, whereas the dorsal parts contain motor areas with efferent projections to the brainstem, receiving oligosynaptic thalamic input. Both regions receive monosynaptic olfactory input. This three-layered "primordial" lamprey lateral pallium has evolved most features of the three-layered reptilian cortices and is thereby a precursor of the six-layered "neo" cortex with a long-standing evolutionary precedent (some 500 million years ago).

Network activity influences the subthreshold and spiking visual responses of pyramidal neurons in the three-layer turtle cortex

A primary goal of systems neuroscience is to understand cortical function, typically by studying spontaneous and stimulus-modulated cortical activity. Mounting evidence suggests a strong and complex relationship exists between the ongoing and stimulus-modulated cortical state. To date, most work in this area has been based on spiking in populations of neurons. While advantageous in many respects, this approach is limited in scope: it records the activity of a minority of neurons and gives no direct indication of the underlying subthreshold dynamics. Membrane potential recordings can fill these gaps in our understanding, but stable recordings are difficult to obtain in vivo. Here, we recorded subthreshold cortical visual responses in the ex vivo turtle eye-attached whole brain preparation, which is ideally suited for such a study. We found that, in the absence of visual stimulation, the network was "synchronous"; neurons displayed network-mediated transitions between hyperpolarized (Down) and depolarized (Up) membrane potential states. The prevalence of these slow-wave transitions varied across turtles and recording sessions. Visual stimulation evoked similar Up states, which were on average larger and less reliable when the ongoing state was more synchronous. Responses were muted when immediately preceded by large, spontaneous Up states. Evoked spiking was sparse, highly variable across trials, and mediated by concerted synaptic inputs that were, in general, only very weakly correlated with inputs to nearby neurons. Together, these results highlight the multiplexed influence of the cortical network on the spontaneous and sensory-evoked activity of individual cortical neurons.NEW & NOTEWORTHY Most studies of cortical activity focus on spikes. Subthreshold membrane potential recordings can provide complementary insight, but stable recordings are difficult to obtain in vivo. Here, we recorded the membrane potentials of cortical neurons during ongoing and visually evoked activity. We observed a strong relationship between network and single-neuron evoked activity spanning multiple temporal scales. The membrane potential perspective of cortical dynamics thus highlights the influence of intrinsic network properties on visual processing.

Adaptation modulates correlated subthreshold response variability in visual cortex

Cortical sensory responses are highly variable across stimulus presentations. This variability can be correlated across neurons (due to some combination of dense intracortical connectivity, cortical activity level, and cortical state), with fundamental implications for population coding. Yet the interpretation of correlated response variability (or "noise correlation") has remained fraught with difficulty, in part because of the restriction to extracellular neuronal spike recordings. Here, we measured response variability and its correlation at the most microscopic level of electrical neural activity, the membrane potential, by obtaining dual whole cell recordings from pairs of cortical pyramidal neurons during visual processing in the turtle whole brain ex vivo preparation. We found that during visual stimulation, correlated variability adapts toward an intermediate level and that this correlation dynamic is likely mediated by intracortical mechanisms. A model network with external inputs, synaptic depression, and structure reproduced the observed dynamics of correlated variability. These results suggest that intracortical adaptation self-organizes cortical circuits toward a balanced regime at which correlated variability is maintained at an intermediate level.NEW & NOTEWORTHY Correlated response variability has profound implications for stimulus encoding, yet our understanding of this phenomenon is based largely on spike data. Here, we investigate the dynamics and mechanisms of membrane potential-correlated variability (CC) in visual cortex with a combined experimental and computational approach. We observe a visually evoked increase in CC, followed by a fast return to baseline. Our results further suggest a link between this observation and the adaptation-mediated dynamics of emergent network phenomena.

Adaptation towards scale-free dynamics improves cortical stimulus discrimination at the cost of reduced detection

Fundamental to the function of nervous systems is the ability to reorganize to cope with changing sensory input. Although well-studied in single neurons, how such adaptive versatility manifests in the collective population dynamics and function of cerebral cortex remains unknown. Here we measured population neural activity with microelectrode arrays in turtle visual cortex while visually stimulating the retina. First, we found that, following the onset of stimulation, adaptation tunes the collective population dynamics towards a special regime with scale-free spatiotemporal activity, after an initial large-scale transient response. Concurrently, we observed an adaptive tradeoff between two important aspects of population coding-sensory detection and discrimination. As adaptation tuned the cortex toward scale-free dynamics, stimulus discrimination was enhanced, while stimulus detection was reduced. Finally, we used a network-level computational model to show that short-term synaptic depression was sufficient to mechanistically explain our experimental results. In the model, scale-free dynamics emerge only when the model operates near a special regime called criticality. Together our model and experimental results suggest unanticipated functional benefits and costs of adaptation near criticality in visual cortex.

Orientation selectivity in the visual cortex of the nine-banded armadillo

Orientation selectivity in primary visual cortex (V1) has been proposed to reflect a canonical computation performed by the neocortical circuitry. Although orientation selectivity has been reported in all mammals examined to date, the degree of selectivity and the functional organization of selectivity vary across mammalian clades. The differences in degree of orientation selectivity are large, from reports in marsupials that only a small subset of neurons are selective to studies in carnivores, in which it is rare to find a neuron lacking selectivity. Furthermore, the functional organization in cortex varies in that the primate and carnivore V1 is characterized by an organization in which nearby neurons share orientation preference while other mammals such as rodents and lagomorphs either lack or have only extremely weak clustering. To gain insight into the evolutionary emergence of orientation selectivity, we examined the nine-banded armadillo, a species within the early placental clade Xenarthra. Here we use a combination of neuroimaging, histological, and electrophysiological methods to identify the retinofugal pathways, locate V1, and for the first time examine the functional properties of V1 neurons in the armadillo (Dasypus novemcinctus) V1. Individual neurons were strongly sensitive to the orientation and often the direction of drifting gratings. We uncovered a wide range of orientation preferences but found a bias for horizontal gratings. The presence of strong orientation selectivity in armadillos suggests that the circuitry responsible for this computation is common to all placental mammals.NEW & NOTEWORTHY The current study shows that armadillo primary visual cortex (V1) neurons share the signature properties of V1 neurons of primates, carnivorans, and rodents. Furthermore, these neurons exhibit a degree of selectivity for stimulus orientation and motion direction similar to that found in primate V1. Our findings in armadillo visual cortex suggest that the functional properties of V1 neurons emerged early in the mammalian lineage, near the time of the divergence of marsupials.

Spontaneous activity in the piriform cortex extends the dynamic range of cortical odor coding

Neurons in the neocortex exhibit spontaneous spiking activity in the absence of external stimuli, but the origin and functions of this activity remain uncertain. Here, we show that spontaneous spiking is also prominent in a sensory paleocortex, the primary olfactory (piriform) cortex of mice. In the absence of applied odors, piriform neurons exhibit spontaneous firing at mean rates that vary systematically among neuronal classes. This activity requires the participation of NMDA receptors and is entirely driven by bottom-up spontaneous input from the olfactory bulb. Odor stimulation produces two types of spatially dispersed, odor-distinctive patterns of responses in piriform cortex layer 2 principal cells: Approximately 15% of cells are excited by odor, and another approximately 15% have their spontaneous activity suppressed. Our results show that, by allowing odor-evoked suppression as well as excitation, the responsiveness of piriform neurons is at least twofold less sparse than currently believed. Hence, by enabling bidirectional changes in spiking around an elevated baseline, spontaneous activity in the piriform cortex extends the dynamic range of odor representation and enriches the coding space for the representation of complex olfactory stimuli.

Development and Organization of the Evolutionarily Conserved Three-Layered Olfactory Cortex

The olfactory cortex is part of the mammalian cerebral cortex together with the neocortex and the hippocampus. It receives direct input from the olfactory bulbs and participates in odor discrimination, association, and learning (Bekkers and Suzuki, 2013). It is thought to be an evolutionarily conserved paleocortex, which shares common characteristics with the three-layered general cortex of reptiles (Aboitiz et al., 2002). The olfactory cortex has been studied as a “simple model” to address sensory processing, though little is known about its precise cell origin, diversity, and identity. While the development and the cellular diversity of the six-layered neocortex are increasingly understood, the olfactory cortex remains poorly documented in these aspects. Here is a review of current knowledge of the development and organization of the olfactory cortex, keeping the analogy with those of the neocortex. The comparison of olfactory cortex and neocortex will allow the opening of evolutionary perspectives on cortical development.

Optogenetic Mapping of Intracortical Circuits Originating from Semilunar Cells in the Piriform Cortex

Despite its comparatively simple trilaminar architecture, the primary olfactory (piriform) cortex of mammals is capable of performing sophisticated sensory processing, an ability that is thought to depend critically on its extensive associational (intracortical) excitatory circuits. Here, we used a novel transgenic mouse model and optogenetics to measure the connectivity of associational circuits that originate in semilunar (SL) cells in layer 2a of the anterior piriform cortex (aPC). We generated a mouse line (48L) in which channelrhodopsin-2 (ChR) could be selectively expressed in a subset of SL cells. Light-evoked excitatory postsynaptic currents (EPSCs) could be evoked in superficial pyramidal cells (17.4% of n = 86 neurons) and deep pyramidal cells (33.3%, n = 9) in the aPC, but never in ChR- SL cells (0%, n = 34). Thus, SL cells monosynaptically excite pyramidal cells, but not other SL cells. Light-evoked EPSCs were also selectively elicited in 3 classes of GABAergic interneurons in layer 3 of the aPC. Our results show that SL cells are specialized for providing feedforward excitation of specific classes of neurons in the aPC, confirming that SL cells comprise a functionally distinctive input layer.

Brain Computation Is Organized via Power-of-Two-Based Permutation Logic

There is considerable scientific interest in understanding how cell assemblies—the long-presumed computational motif—are organized so that the brain can generate intelligent cognition and flexible behavior. The Theory of Connectivity proposes that the origin of intelligence is rooted in a power-of-two-based permutation logic (N = 2ⁱ–1), producing specific-to-general cell-assembly architecture capable of generating specific perceptions and memories, as well as generalized knowledge and flexible actions. We show that this power-of-two-based permutation logic is widely used in cortical and subcortical circuits across animal species and is conserved for the processing of a variety of cognitive modalities including appetitive, emotional and social information. However, modulatory neurons, such as dopaminergic (DA) neurons, use a simpler logic despite their distinct subtypes. Interestingly, this specific-to-general permutation logic remained largely intact although NMDA receptors—the synaptic switch for learning and memory—were deleted throughout adulthood, suggesting that the logic is developmentally pre-configured. Moreover, this computational logic is implemented in the cortex via combining a random-connectivity strategy in superficial layers 2/3 with nonrandom organizations in deep layers 5/6. This randomness of layers 2/3 cliques—which preferentially encode specific and low-combinatorial features and project inter-cortically—is ideal for maximizing cross-modality novel pattern-extraction, pattern-discrimination and pattern-categorization using sparse code, consequently explaining why it requires hippocampal offline-consolidation. In contrast, the nonrandomness in layers 5/6—which consists of few specific cliques but a higher portion of more general cliques projecting mostly to subcortical systems—is ideal for feedback-control of motivation, emotion, consciousness and behaviors. These observations suggest that the brain’s basic computational algorithm is indeed organized by the power-of-two-based permutation logic. This simple mathematical logic can account for brain computation across the entire evolutionary spectrum, ranging from the simplest neural networks to the most complex.

Toward an Integration of Deep Learning and Neuroscience

Neuroscience has focused on the detailed implementation of computation, studying neural codes, dynamics and circuits. In machine learning, however, artificial neural networks tend to eschew precisely designed codes, dynamics or circuits in favor of brute force optimization of a cost function, often using simple and relatively uniform initial architectures. Two recent developments have emerged within machine learning that create an opportunity to connect these seemingly divergent perspectives. First, structured architectures are used, including dedicated systems for attention, recursion and various forms of short- and long-term memory storage. Second, cost functions and training procedures have become more complex and are varied across layers and over time. Here we think about the brain in terms of these ideas. We hypothesize that (1) the brain optimizes cost functions, (2) the cost functions are diverse and differ across brain locations and over development, and (3) optimization operates within a pre-structured architecture matched to the computational problems posed by behavior. In support of these hypotheses, we argue that a range of implementations of credit assignment through multiple layers of neurons are compatible with our current knowledge of neural circuitry, and that the brain's specialized systems can be interpreted as enabling efficient optimization for specific problem classes. Such a heterogeneously optimized system, enabled by a series of interacting cost functions, serves to make learning data-efficient and precisely targeted to the needs of the organism. We suggest directions by which neuroscience could seek to refine and test these hypotheses.

Theory of Connectivity: Nature and Nurture of Cell Assemblies and Cognitive Computation

Richard Semon and Donald Hebb are among the firsts to put forth the notion of cell assembly—a group of coherently or sequentially-activated neurons—to represent percept, memory, or concept. Despite the rekindled interest in this century-old idea, the concept of cell assembly still remains ill-defined and its operational principle is poorly understood. What is the size of a cell assembly? How should a cell assembly be organized? What is the computational logic underlying Hebbian cell assemblies? How might Nature vs. Nurture interact at the level of a cell assembly? In contrast to the widely assumed randomness within the mature but naïve cell assembly, the Theory of Connectivity postulates that the brain consists of the developmentally pre-programmed cell assemblies known as the functional connectivity motif (FCM). Principal cells within such FCM is organized by the power-of-two-based mathematical principle that guides the construction of specific-to-general combinatorial connectivity patterns in neuronal circuits, giving rise to a full range of specific features, various relational patterns, and generalized knowledge. This pre-configured canonical computation is predicted to be evolutionarily conserved across many circuits, ranging from these encoding memory engrams and imagination to decision-making and motor control. Although the power-of-two-based wiring and computational logic places a mathematical boundary on an individual’s cognitive capacity, the fullest intellectual potential can be brought about by optimized nature and nurture. This theory may also open up a new avenue to examining how genetic mutations and various drugs might impair or improve the computational logic of brain circuits.

From sauropsids to mammals and back: New approaches to comparative cortical development

Evolution of the mammalian neocortex (isocortex) has been a persisting problem in neurobiology. While recent studies have attempted to understand the evolutionary expansion of the human neocortex from rodents, similar approaches have been used to study the changes between reptiles, birds, and mammals. We review here findings from the past decades on the development, organization, and gene expression patterns in various extant species. This review aims to compare cortical cell numbers and neuronal cell types to the elaboration of progenitor populations and their proliferation in these species. Several progenitors, such as the ventricular radial glia, the subventricular intermediate progenitors, and the subventricular (outer) radial glia, have been identified but the contribution of each to cortical layers and cell types through specific lineages, their possible roles in determining brain size or cortical folding, are not yet understood. Across species, larger, more diverse progenitors relate to cortical size and cell diversity. The challenge is to relate the radial and tangential expansion of the neocortex to the changes in the proliferative compartments during mammalian evolution and with the changes in gene expression and lineages evident in various sectors of the developing brain. We also review the use of recent lineage tracing and transcriptomic approaches to revisit theories and to provide novel understanding of molecular processes involved in specification of cortical regions.

Role of ortho-retronasal olfaction in mammalian cortical evolution

Fossils of mammals and their extinct relatives among cynodonts give evidence of correlated transformations affecting olfaction as well as mastication, head movement, and ventilation, and suggest evolutionary coupling of these seemingly separate anatomical regions into a larger integrated system of ortho-retronasal olfaction. Evidence from paleontology and physiology suggests that ortho-retronasal olfaction played a critical role at three stages of mammalian cortical evolution: early mammalian brain development was driven in part by ortho-retronasal olfaction; the bauplan for neocortex had higher-level association functions derived from olfactory cortex; and human cortical evolution was enhanced by ortho-retronasal smell.

Turtle Dorsal Cortex Pyramidal Neurons Comprise Two Distinct Cell Types with Indistinguishable Visual Responses

A detailed inventory of the constituent pieces in cerebral cortex is considered essential to understand the principles underlying cortical signal processing. Specifically, the search for pyramidal neuron subtypes is partly motivated by the hypothesis that a subtype-specific division of labor could create a rich substrate for computation. On the other hand, the extreme integration of individual neurons into the collective cortical circuit promotes the hypothesis that cellular individuality represents a smaller computational role within the context of the larger network. These competing hypotheses raise the important question to what extent the computational function of a neuron is determined by its individual type or by its circuit connections. We created electrophysiological profiles from pyramidal neurons within the sole cellular layer of turtle visual cortex by measuring responses to current injection using whole-cell recordings. A blind clustering algorithm applied to these data revealed the presence of two principle types of pyramidal neurons. Brief diffuse light flashes triggered membrane potential fluctuations in those same cortical neurons. The apparently network driven variability of the visual responses concealed the existence of subtypes. In conclusion, our results support the notion that the importance of diverse intrinsic physiological properties is minimized when neurons are embedded in a synaptic recurrent network.

Olfaction, navigation, and the origin of isocortex

There are remarkable similarities between the brains of mammals and birds in terms of microcircuit architecture, despite obvious differences in gross morphology and development. While in reptiles and birds the most expanding component (the dorsal ventricular ridge) displays an overall nuclear shape and derives from the lateral and ventral pallium, in mammals a dorsal pallial, six-layered isocortex shows the most remarkable elaboration. Regardless of discussions about possible homologies between mammalian and avian brains, a main question remains in explaining the emergence of the mammalian isocortex, because it represents a unique phenotype across amniotes. In this article, we propose that the origin of the isocortex was driven by behavioral adaptations involving olfactory driven goal-directed and navigating behaviors. These adaptations were linked with increasing sensory development, which provided selective pressure for the expansion of the dorsal pallium. The latter appeared as an interface in olfactory-hippocampal networks, contributing somatosensory information for navigating behavior. Sensory input from other modalities like vision and audition were subsequently recruited into this expanding region, contributing to multimodal associative networks.

Functional constraints in the evolution of brain circuits

Regardless of major anatomical and neurodevelopmental differences, the vertebrate isocortex shows a remarkably well-conserved organization. In the isocortex, reciprocal connections between excitatory and inhibitory neurons are distributed across multiple layers, encompassing modular, dynamical and recurrent functional networks during information processing. These dynamical brain networks are often organized in neuronal assemblies interacting through rhythmic phase relationships. Accordingly, these oscillatory interactions are observed across multiple brain scale levels, and they are associated with several sensory, motor, and cognitive processes. Most notably, oscillatory interactions are also found in the complete spectrum of vertebrates. Yet, it is unknown why this functional organization is so well conserved in evolution. In this perspective, we propose some ideas about how functional requirements of the isocortex can account for the evolutionary stability observed in microcircuits across vertebrates. We argue that isocortex architectures represent canonical microcircuits resulting from: (i) the early selection of neuronal architectures based on the oscillatory excitatory-inhibitory balance, which lead to the implementation of compartmentalized oscillations and (ii) the subsequent emergence of inferential coding strategies (predictive coding), which are able to expand computational capacities. We also argue that these functional constraints may be the result of several advantages that oscillatory activity contributes to brain network processes, such as information transmission and code reliability. In this manner, similarities in mesoscale brain circuitry and input-output organization between different vertebrate groups may reflect evolutionary constraints imposed by these functional requirements, which may or may not be traceable to a common ancestor.

A hypothesis for the evolution of the upper layers of the neocortex through co-option of the olfactory cortex developmental program

The neocortex is unique to mammals and its evolutionary origin is still highly debated. The neocortex is generated by the dorsal pallium ventricular zone, a germinative domain that in reptiles give rise to the dorsal cortex. Whether this latter allocortical structure contains homologs of all neocortical cell types it is unclear. Recently we described a population of DCX+/Tbr1+ cells that is specifically associated with the layer II of higher order areas of both the neocortex and of the more evolutionary conserved piriform cortex. In a reptile similar cells are present in the layer II of the olfactory cortex and the DVR but not in the dorsal cortex. These data are consistent with the proposal that the reptilian dorsal cortex is homologous only to the deep layers of the neocortex while the upper layers are a mammalian innovation. Based on our observations we extended these ideas by hypothesizing that this innovation was obtained by co-opting a lateral and/or ventral pallium developmental program. Interestingly, an analysis in the Allen brain atlas revealed a striking similarity in gene expression between neocortical layers II/III and piriform cortex. We thus propose a model in which the early neocortical column originated by the superposition of the lateral olfactory and dorsal cortex. This model is consistent with the fossil record and may account not only for the topological position of the neocortex, but also for its basic cytoarchitectural and hodological features. This idea is also consistent with previous hypotheses that the peri-allocortex represents the more ancient neocortical part. The great advances in deciphering the molecular logic of the amniote pallium developmental programs will hopefully enable to directly test our hypotheses in the next future.