Functional impact of interneuronal inhibition in the cerebral cortex of behaving animals

The calculating brain

The human brain possesses neural networks and mechanisms enabling the representation of numbers, basic arithmetic operations, and mathematical reasoning. Without the ability to represent numerical quantity and perform calculations, our scientifically and technically advanced culture would not exist. However, the origins of numerical abilities are grounded in an intuitive understanding of quantity deeply rooted in biology. Nevertheless, more advanced symbolic arithmetic skills require a cultural background with formal mathematical education. In the past two decades, cognitive neuroscience has seen significant progress in understanding the workings of the calculating brain through various methods and model systems. This review begins by exploring the mental and neuronal representations of nonsymbolic numerical quantity and then progresses to symbolic representations acquired in childhood. During arithmetic operations (addition, subtraction, multiplication, and division), these representations are processed and transformed according to arithmetic rules and principles, leveraging different mental strategies and types of arithmetic knowledge that can be dissociated in the brain. Although it was once believed that number processing and calculation originated from the language faculty, it is now evident that mathematical and linguistic abilities are primarily processed independently in the brain. Understanding how the healthy brain processes numerical information is crucial for gaining insights into debilitating numerical disorders, including acquired conditions like acalculia and learning-related calculation disorders such as developmental dyscalculia.

Filtered Point Processes Tractably Capture Rhythmic And Broadband Power Spectral Structure in Neural Electrophysiological Recordings

Neural electrophysiological recordings arise from interacting rhythmic (oscillatory) and broadband (aperiodic) biological subprocesses. Both rhythmic and broadband processes contribute to the neural power spectrum, which decomposes the variance of a neural recording across frequencies. Although an extensive body of literature has successfully studied rhythms in various diseases and brain states, researchers only recently have systematically studied the characteristics of broadband effects in the power spectrum. Broadband effects can generally be categorized as 1) shifts in power across all frequencies, which correlate with changes in local firing rates and 2) changes in the overall shape of the power spectrum, such as the spectral slope or power law exponent. Shape changes are evident in various conditions and brain states, influenced by factors such as excitation to inhibition balance, age, and various diseases. It is increasingly recognized that broadband and rhythmic effects can interact on a sub-second timescale. For example, broadband power is time-locked to the phase of <1 Hz rhythms in propofol induced unconsciousness. Modeling tools that explicitly deal with both rhythmic and broadband contributors to the power spectrum and that capture their interactions are essential to help improve the interpretability of power spectral effects. Here, we introduce a tractable stochastic forward modeling framework designed to capture both narrowband and broadband spectral effects when prior knowledge or theory about the primary biophysical processes involved is available. Population-level neural recordings are modeled as the sum of filtered point processes (FPPs), each representing the contribution of a different biophysical process such as action potentials or postsynaptic potentials of different types. Our approach builds on prior neuroscience FPP work by allowing multiple interacting processes and time-varying firing rates and by deriving theoretical power spectra and cross-spectra. We demonstrate several properties of the models, including that they divide the power spectrum into frequency ranges dominated by rhythmic and broadband effects, and that they can capture spectral effects across multiple timescales, including sub-second cross-frequency coupling. The framework can be used to interpret empirically observed power spectra and cross-frequency coupling effects in biophysical terms, which bridges the gap between theoretical models and experimental results.

Infralimbic parvalbumin neural activity facilitates cued threat avoidance

The infralimbic cortex (IL) is essential for flexible behavioral responses to threatening environmental events. Reactive behaviors such as freezing or flight are adaptive in some contexts, but in others a strategic avoidance behavior may be more advantageous. IL has been implicated in avoidance, but the contribution of distinct IL neural subtypes with differing molecular identities and wiring patterns is poorly understood. Here, we study IL parvalbumin (PV) interneurons in mice as they engage in active avoidance behavior, a behavior in which mice must suppress freezing in order to move to safety. We find that activity in inhibitory PV neurons increases during movement to avoid the shock in this behavioral paradigm, and that PV activity during movement emerges after mice have experienced a single shock, prior to learning avoidance. PV neural activity does not change during movement toward cued rewards or during general locomotion in the open field, behavioral paradigms where freezing does not need to be suppressed to enable movement. Optogenetic suppression of PV neurons increases the duration of freezing and delays the onset of avoidance behavior, but does not affect movement toward rewards or general locomotion. These data provide evidence that IL PV neurons support strategic avoidance behavior by suppressing freezing.

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

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

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

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

Amodal population clock in the primate medial premotor system for rhythmic tapping

The neural substrate for beat extraction and response entrainment to rhythms is not fully understood. Here we analyze the activity of medial premotor neurons in monkeys performing isochronous tapping guided by brief flashing stimuli or auditory tones. The population dynamics shared the following properties across modalities: the circular dynamics of the neural trajectories form a regenerating loop for every produced interval; the trajectories converge in similar state space at tapping times resetting the clock; and the tempo of the synchronized tapping is encoded in the trajectories by a combination of amplitude modulation and temporal scaling. Notably, the modality induces displacement in the neural trajectories in the auditory and visual subspaces without greatly altering the time-keeping mechanism. These results suggest that the interaction between the medial premotor cortex's amodal internal representation of pulse and a modality-specific external input generates a neural rhythmic clock whose dynamics govern rhythmic tapping execution across senses.

Inferring light responses of primate retinal ganglion cells using intrinsic electrical signatures

Objective. Retinal implants are designed to stimulate retinal ganglion cells (RGCs) in a way that restores sight to individuals blinded by photoreceptor degeneration. Reproducing high-acuity vision with these devices will likely require inferring the natural light responses of diverse RGC types in the implanted retina, without being able to measure them directly. Here we demonstrate an inference approach that exploits intrinsic electrophysiological features of primate RGCs.Approach.First, ON-parasol and OFF-parasol RGC types were identified using their intrinsic electrical features in large-scale multi-electrode recordings from macaque retina. Then, the electrically inferred somatic location, inferred cell type, and average linear-nonlinear-Poisson model parameters of each cell type were used to infer a light response model for each cell. The accuracy of the cell type classification and of reproducing measured light responses with the model were evaluated.Main results.A cell-type classifier trained on 246 large-scale multi-electrode recordings from 148 retinas achieved 95% mean accuracy on 29 test retinas. In five retinas tested, the inferred models achieved an average correlation with measured firing rates of 0.49 for white noise visual stimuli and 0.50 for natural scenes stimuli, compared to 0.65 and 0.58 respectively for models fitted to recorded light responses (an upper bound). Linear decoding of natural images from predicted RGC activity in one retina showed a mean correlation of 0.55 between decoded and true images, compared to an upper bound of 0.81 using models fitted to light response data.Significance.These results suggest that inference of RGC light response properties from intrinsic features of their electrical activity may be a useful approach for high-fidelity sight restoration. The overall strategy of first inferring cell type from electrical features and then exploiting cell type to help infer natural cell function may also prove broadly useful to neural interfaces.

PMd and action preparation: bridging insights between TMS and single neuron research

Transcranial magnetic stimulation (TMS) research has furthered understanding of human dorsal premotor cortex (PMd) function due to its unrivalled ability to measure the inhibitory and facilitatory influences of PMd over the primary motor cortex (M1) in a temporally precise manner. TMS research indicates that PMd transiently modulates inhibitory output to effector representations within M1 during motor preparation, with the direction of modulation depending on which effectors are selected for response, and the timing of modulations co-varying with task selection demands. In this review, we critically assess this literature in the context of a dynamical systems approach used to model nonhuman primate (NHP) PMd/M1 single-neuron recordings during action preparation. Through this process, we identify gaps in the literature and propose future experiments.

Analogies of human speech and bird song: From vocal learning behavior to its neural basis

Vocal learning is a complex acquired social behavior that has been found only in very few animals. The process of animal vocal learning requires the participation of sensorimotor function. By accepting external auditory input and cooperating with repeated vocal imitation practice, a stable pattern of vocal information output is eventually formed. In parallel evolutionary branches, humans and songbirds share striking similarities in vocal learning behavior. For example, their vocal learning processes involve auditory feedback, complex syntactic structures, and sensitive periods. At the same time, they have evolved the hierarchical structure of special forebrain regions related to vocal motor control and vocal learning, which are organized and closely associated to the auditory cortex. By comparing the location, function, genome, and transcriptome of vocal learning-related brain regions, it was confirmed that songbird singing and human language-related neural control pathways have certain analogy. These common characteristics make songbirds an ideal animal model for studying the neural mechanisms of vocal learning behavior. The neural process of human language learning may be explained through similar neural mechanisms, and it can provide important insights for the treatment of language disorders.

Cell-type specific pallial circuits shape categorical tuning responses in the crow telencephalon

The nidopallium caudolaterale (NCL), an integration centre in the telencephalon of birds, plays a crucial role in representing and maintaining abstract categories and concepts. However, the computational principles allowing pallial microcircuits consisting of excitatory and inhibitory neurons to shape the tuning to abstract categories remain elusive. Here we identified the major pallial cell types, putative excitatory projection cells and inhibitory interneurons, by characterizing the waveforms of action potentials recorded in crows performing a cognitively demanding numerical categorization task. Both cell types showed clear differences in their capacity to encode categorical information. Nearby and functionally coupled putative projection neurons generally exhibited similar tuning, whereas putative interneurons showed mainly opposite tuning. The results favour feedforward mechanisms for the shaping of categorical tuning in microcircuits of the NCL. Our findings help to decipher the workings of pallial microcircuits in birds during complex cognition and to compare them vis-a-vis neocortical processes in mammals.

Neural recordings from the caudolateral nidopallium in crows during a numerosity task suggest there are two subsets of projection neurons and inhibitory interneurons involved in complex cognition.

Non-linear dimensionality reduction on extracellular waveforms reveals cell type diversity in premotor cortex

Cortical circuits are thought to contain a large number of cell types that coordinate to produce behavior. Current in vivo methods rely on clustering of specified features of extracellular waveforms to identify putative cell types, but these capture only a small amount of variation. Here, we develop a new method (WaveMAP) that combines non-linear dimensionality reduction with graph clustering to identify putative cell types. We apply WaveMAP to extracellular waveforms recorded from dorsal premotor cortex of macaque monkeys performing a decision-making task. Using WaveMAP, we robustly establish eight waveform clusters and show that these clusters recapitulate previously identified narrow- and broad-spiking types while revealing previously unknown diversity within these subtypes. The eight clusters exhibited distinct laminar distributions, characteristic firing rate patterns, and decision-related dynamics. Such insights were weaker when using feature-based approaches. WaveMAP therefore provides a more nuanced understanding of the dynamics of cell types in cortical circuits.

Roles of Motor Cortex Neuron Classes in Reach-Related Modulation for Hemiparkinsonian Rats

Disruption of the function of the primary motor cortex (M1) is thought to play a critical role in motor dysfunction in Parkinson's disease (PD). Detailed information regarding the specific aspects of M1 circuits that become abnormal is lacking. We recorded single units and local field potentials (LFPs) of M1 neurons in unilateral 6-hydroxydopamine (6-OHDA) lesion rats and control rats to assess the impact of dopamine (DA) cell loss during rest and a forelimb reaching task. Our results indicated that M1 neurons can be classified into two groups (putative pyramidal neurons and putative interneurons) and that 6-OHDA could modify the activity of different M1 subpopulations to a large extent. Reduced activation of putative pyramidal neurons during inattentive rest and reaching was observed. In addition, 6-OHDA intoxication was associated with an increase in certain LFP frequencies, especially those in the beta range (broadly defined here as any frequency between 12 and 35 Hz), which become pathologically exaggerated throughout cortico-basal ganglia circuits after dopamine depletion. Furthermore, assessment of different spike-LFP coupling parameters revealed that the putative pyramidal neurons were particularly prone to being phase-locked to ongoing cortical oscillations at 12-35 Hz during reaching. Conversely, putative interneurons were neither hypoactive nor synchronized to ongoing cortical oscillations. These data collectively demonstrate a neuron type-selective alteration in the M1 in hemiparkinsonian rats. These alterations hamper the ability of the M1 to contribute to motor conduction and are likely some of the main contributors to motor impairments in PD.

Chronic intermittent hypoxia transiently increases hippocampal network activity in the gamma frequency band and 4-Aminopyridine-induced hyperexcitability in vitro

Chronic intermittent hypoxia (CIH) is the most distinct feature of obstructive sleep apnea (OSA), a common breathing and sleep disorder that leads to several neuropathological consequences, including alterations in the hippocampal network and in seizure susceptibility. However, it is currently unknown whether these alterations are permanent or remit upon normal oxygenation. Here, we investigated the effects of CIH on hippocampal spontaneous network activity and hyperexcitability in vitro and explored whether these alterations endure or fade after normal oxygenation. Results showed that applying CIH for 21 days to adult rats increases gamma-band hippocampal network activity and aggravates 4-Aminopyridine-induced epileptiform activity in vitro. Interestingly, these CIH-induced alterations remit after 30 days of normal oxygenation. Our findings indicate that hippocampal network alterations and increased seizure susceptibility induced by CIH are not permanent and can be spontaneously reverted, suggesting that therapeutic interventions against OSA in patients with epilepsy, such as surgery or continuous positive airway pressure (CPAP), could be favorable for seizure control.

Role of paroxysmal depolarization in focal seizure activity

We analyze the role of inhibition in sustaining focal epileptic seizure activity. We review ongoing seizure activity at the mesoscopic scale that can be observed with microelectrode arrays as well as at the macroscale of standard clinical EEG. We provide clinical, experimental, and modeling data to support the hypothesis that paroxysmal depolarization (PD) is a critical component of the ictal machinery. We present dual-patch recordings in cortical cultures showing reduced synaptic transmission associated with presynaptic occurrence of PD, and we find that the PD threshold is cell size related. We further find evidence that optically evoked PD activity in parvalbumin neurons can promote propagation of neuronal excitation in neocortical networks in vitro. Spike sorting results from microelectrode array measurements around ictal wave propagation in human focal seizures demonstrate a strong increase in putative inhibitory firing with an approaching excitatory wave, followed by a sudden reduction of firing at passage. At the macroscopic level, we summarize evidence that this excitatory ictal wave activity is strongly correlated with oscillatory activity across a centimeter-sized cortical network. We summarize Wilson-Cowan-type modeling showing how inhibitory function is crucial for this behavior. Our findings motivated us to develop a network motif of neurons in silico, governed by a reduced version of the Hodgkin-Huxley formalism, to show how feedforward, feedback, PD, and local failure of inhibition contribute to observed dynamics across network scales. The presented multidisciplinary evidence suggests that the PD not only is a cellular marker or epiphenomenon but actively contributes to seizure activity.NEW & NOTEWORTHY We present mechanisms of ongoing focal seizures across meso- and macroscales of microelectrode array and standard clinical recordings, respectively. We find modeling, experimental, and clinical evidence for a dual role of inhibition across these scales: local failure of inhibition allows propagation of a mesoscopic ictal wave, whereas inhibition elsewhere remains intact and sustains macroscopic oscillatory activity. We present evidence for paroxysmal depolarization as a mechanism behind this dual role of inhibition in shaping ictal activity.

Somatostatin-Positive Gamma-Aminobutyric Acid Interneuron Deficits in Depression: Cortical Microcircuit and Therapeutic Perspectives

The functional integration of external and internal signals forms the basis of information processing and is essential for higher cognitive functions. This occurs in finely tuned cortical microcircuits whose functions are balanced at the cellular level by excitatory glutamatergic pyramidal neurons and inhibitory gamma-aminobutyric acidergic (GABAergic) interneurons. The balance of excitation and inhibition, from cellular processes to neural network activity, is characteristically disrupted in multiple neuropsychiatric disorders, including major depressive disorder (MDD), bipolar disorder, anxiety disorders, and schizophrenia. Specifically, nearly 3 decades of research demonstrate a role for reduced inhibitory GABA level and function across disorders. In MDD, recent evidence from human postmortem and animal studies suggests a selective vulnerability of GABAergic interneurons that coexpress the neuropeptide somatostatin (SST). Advances in cell type-specific molecular genetics have now helped to elucidate several important roles for SST interneurons in cortical processing (regulation of pyramidal cell excitatory input) and behavioral control (mood and cognition). Here, we review evidence for altered inhibitory function arising from GABAergic deficits across disorders and specifically in MDD. We then focus on properties of the cortical microcircuit, where SST-positive GABAergic interneuron deficits may disrupt functioning in several ways. Finally, we discuss the putative origins of SST cell deficits, as informed by recent research, and implications for therapeutic approaches. We conclude that deficits in SST interneurons represent a contributing cellular pathology and therefore a promising target for normalizing altered inhibitory function in MDD and other disorders with reduced SST cell and GABA functions.

Visual Receptive Field Heterogeneity and Functional Connectivity of Adjacent Neurons in Primate Frontoparietal Association Cortices

The basic organization principles of the primary visual cortex (V1) are commonly assumed to also hold in the association cortex such that neurons within a cortical column share functional connectivity patterns and represent the same region of the visual field. We mapped the visual receptive fields (RFs) of neurons recorded at the same electrode in the ventral intraparietal area (VIP) and the lateral prefrontal cortex (PFC) of rhesus monkeys. We report that the spatial characteristics of visual RFs between adjacent neurons differed considerably, with increasing heterogeneity from VIP to PFC. In addition to RF incongruences, we found differential functional connectivity between putative inhibitory interneurons and pyramidal cells in PFC and VIP. These findings suggest that local RF topography vanishes with hierarchical distance from visual cortical input and argue for increasingly modified functional microcircuits in noncanonical association cortices that contrast V1.SIGNIFICANCE STATEMENT Our visual field is thought to be represented faithfully by the early visual brain areas; all the information from a certain region of the visual field is conveyed to neurons situated close together within a functionally defined cortical column. We examined this principle in the association areas, PFC, and ventral intraparietal area of rhesus monkeys and found that adjacent neurons represent markedly different areas of the visual field. This is the first demonstration of such noncanonical organization of these brain areas.

From the motor cortex to the movement and back again

The motor cortex controls motor behaviors by generating movement-specific signals and transmitting them through spinal cord circuits and motoneurons to the muscles. Precise and well-coordinated muscle activation patterns are necessary for accurate movement execution. Therefore, the activity of cortical neurons should correlate with movement parameters. To investigate the specifics of such correlations among activities of the motor cortex, spinal cord network and muscles, we developed a model for neural control of goal-directed reaching movements that simulates the entire pathway from the motor cortex through spinal cord circuits to the muscles controlling arm movements. In this model, the arm consists of two joints (shoulder and elbow), whose movements are actuated by six muscles (4 single-joint and 2 double-joint flexors and extensors). The muscles provide afferent feedback to the spinal cord circuits. Cortical neurons are defined as cortical "controllers" that solve an inverse problem based on a proposed straight-line trajectory to a target position and a predefined bell-shaped velocity profile. Thus, the controller generates a motor program that produces a task-specific activation of low-level spinal circuits that in turn induce the muscle activation realizing the intended reaching movement. Using the model, we describe the mechanisms of correlation between cortical and motoneuronal activities and movement direction and other movement parameters. We show that the directional modulation of neuronal activity in the motor cortex and the spinal cord may result from direction-specific dynamics of muscle lengths. Our model suggests that directional modulation first emerges at the level of muscle forces, augments at the motoneuron level, and further increases at the level of the motor cortex due to the dependence of frictional forces in the joints, contractility of the muscles and afferent feedback on muscle lengths and/or velocities.

Temporal Processing by Intrinsic Neural Network Dynamics

It is becoming more apparent that there are rich contributions to temporal processing across the brain. Temporal dynamics have been found from lower brain structures all the way to cortical regions. Specifically,in vitrocortical preparations have been extremely useful in understanding how local circuits can time. While many of these results depict vastly different processing than a traditional central clock metaphor they still leave questions as to how this information is integrated. We therefore review evidence to place the results pertaining to local circuit timers into the larger context of temporal perception and generalization.

Recording extracellular neural activity in the behaving monkey using a semichronic and high-density electrode system

We describe a technique to semichronically record the cortical extracellular neural activity in the behaving monkey employing commercial high-density electrodes. After the design and construction of low cost microdrives that allow varying the depth of the recording locations after the implantation surgery, we recorded the extracellular unit activity from pools of neurons at different depths in the presupplementary motor cortex (pre-SMA) of a rhesus monkey trained in a tapping task. The collected data were processed to classify cells as putative pyramidal cells or interneurons on the basis of their waveform features. We also demonstrate that short time cross-correlogram occasionally yields unit pairs with high short latency (<5 ms), narrow bin (<3 ms) peaks, indicative of monosynaptic spike transmission from pre- to postsynaptic neurons. These methods have been verified extensively in rodents. Finally, we observed that the pattern of population activity was repetitive over distinct trials of the tapping task. These results show that the semichronic technique is a viable option for the large-scale parallel recording of local circuit activity at different depths in the cortex of the macaque monkey and other large species.

The neuronal code for number

Humans and non-human primates share an elemental quantification system that resides in a dedicated neural network in the parietal and frontal lobes. In this cortical network, 'number neurons' encode the number of elements in a set, its cardinality or numerosity, irrespective of stimulus appearance across sensory motor systems, and from both spatial and temporal presentation arrays. After numbers have been extracted from sensory input, they need to be processed to support goal-directed behaviour. Studying number neurons provides insights into how information is maintained in working memory and transformed in tasks that require rule-based decisions. Beyond an understanding of how cardinal numbers are encoded, number processing provides a window into the neuronal mechanisms of high-level brain functions.

High Stimulus-Related Information in Barrel Cortex Inhibitory Interneurons

The manner in which populations of inhibitory (INH) and excitatory (EXC) neocortical neurons collectively encode stimulus-related information is a fundamental, yet still unresolved question. Here we address this question by simultaneously recording with large-scale multi-electrode arrays (of up to 128 channels) the activity of cell ensembles (of up to 74 neurons) distributed along all layers of 3–4 neighboring cortical columns in the anesthetized adult rat somatosensory barrel cortex in vivo. Using two different whisker stimulus modalities (location and frequency) we show that individual INH neurons – classified as such according to their distinct extracellular spike waveforms – discriminate better between restricted sets of stimuli (≤6 stimulus classes) than EXC neurons in granular and infra-granular layers. We also demonstrate that ensembles of INH cells jointly provide as much information about such stimuli as comparable ensembles containing the ~20% most informative EXC neurons, however presenting less information redundancy – a result which was consistent when applying both theoretical information measurements and linear discriminant analysis classifiers. These results suggest that a consortium of INH neurons dominates the information conveyed to the neocortical network, thereby efficiently processing incoming sensory activity. This conclusion extends our view on the role of the inhibitory system to orchestrate cortical activity.

Perception of the environment relies on neuronal computation in the cerebral cortex. However, the exact algorithms by which cortical neuronal networks process relevant information from the inputs of sensory organs are only poorly understood. To address this problem we stimulated distinct whiskers and recorded the neuronal responses from identified cortical whisker representations of the rat using multi-site electrodes. For rodents the whisker system is one main sensory input channel, offering the unique property that for each whisker an identified cortical area ("barrel-related column") represents its main cortical input station. In the present study we were able to demonstrate that the action potential firing of single inhibitory neurons provides more information about behaviorally relevant qualities of whisker stimulation (identity of the stimulated whisker and frequency of stimulation) than excitatory neurons. In addition, information about stimulation qualities was encoded with less redundancy in inhibitory neurons. In summary, the results of our study suggest that inhibitory neurons carry substantial information about the sensory environment and can thereby adequately orchestrate neuronal activity in sensory cortices.

Finding the beat: a neural perspective across humans and non-human primates

Humans possess an ability to perceive and synchronize movements to the beat in music ('beat perception and synchronization'), and recent neuroscientific data have offered new insights into this beat-finding capacity at multiple neural levels. Here, we review and compare behavioural and neural data on temporal and sequential processing during beat perception and entrainment tasks in macaques (including direct neural recording and local field potential (LFP)) and humans (including fMRI, EEG and MEG). These abilities rest upon a distributed set of circuits that include the motor cortico-basal-ganglia-thalamo-cortical (mCBGT) circuit, where the supplementary motor cortex (SMA) and the putamen are critical cortical and subcortical nodes, respectively. In addition, a cortical loop between motor and auditory areas, connected through delta and beta oscillatory activity, is deeply involved in these behaviours, with motor regions providing the predictive timing needed for the perception of, and entrainment to, musical rhythms. The neural discharge rate and the LFP oscillatory activity in the gamma- and beta-bands in the putamen and SMA of monkeys are tuned to the duration of intervals produced during a beat synchronization-continuation task (SCT). Hence, the tempo during beat synchronization is represented by different interval-tuned cells that are activated depending on the produced interval. In addition, cells in these areas are tuned to the serial-order elements of the SCT. Thus, the underpinnings of beat synchronization are intrinsically linked to the dynamics of cell populations tuned for duration and serial order throughout the mCBGT. We suggest that a cross-species comparison of behaviours and the neural circuits supporting them sets the stage for a new generation of neurally grounded computational models for beat perception and synchronization.

Functional network overlap as revealed by fMRI using sICA and its potential relationships with functional heterogeneity, balanced excitation and inhibition, and sparseness of neuron activity

Functional magnetic resonance imaging (fMRI) studies traditionally use general linear model-based analysis (GLM-BA) and regularly report task-related activation, deactivation, or no change in activation in separate brain regions. However, several recent fMRI studies using spatial independent component analysis (sICA) find extensive overlap of functional networks (FNs), each exhibiting different task-related modulation (e.g., activation vs. deactivation), different from the dominant findings of GLM-BA. This study used sICA to assess overlap of FNs extracted from four datasets, each related to a different cognitive task. FNs extracted from each dataset overlapped with each other extensively across most or all brain regions and showed task-related concurrent increases, decreases, or no changes in activity. These findings indicate that neural substrates showing task-related concurrent but different modulations in activity intermix with each other and distribute across most of the brain. Furthermore, spatial correlation analyses found that most FNs were highly consistent in spatial patterns across different datasets. This finding indicates that these FNs probably reflect large-scale patterns of task-related brain activity. We hypothesize that FN overlaps as revealed by sICA might relate to functional heterogeneity, balanced excitation and inhibition, and population sparseness of neuron activity, three fundamental properties of the brain. These possibilities deserve further investigation.

Physiological properties of supragranular cortical inhibitory interneurons expressing retrograde persistent firing

Neurons are polarized functional units. The somatodendritic compartment receives and integrates synaptic inputs while the axon relays relevant synaptic information in form of action potentials (APs) across long distance. Despite this well accepted notion, recent research has shown that, under certain circumstances, the axon can also generate APs independent of synaptic inputs at axonal sites distal from the soma. These ectopic APs travel both toward synaptic terminals and antidromically toward the soma. This unusual form of neuronal communication seems to preferentially occur in cortical inhibitory interneurons following a period of intense neuronal activity and might have profound implications for neuronal information processing. Here we show that trains of ectopically generated APs can be induced in a large portion of neocortical layer 2/3 GABAergic interneurons following a somatic depolarization inducing hundreds of APs. Sparsely occurring ectopic spikes were also observed in a large portion of layer 1 interneurons even in absence of prior somatic depolarization. Remarkably, we found that interneurons which produce ectopic APs display specific membrane and morphological properties significantly different from the remaining GABAergic cells and may therefore represent a functionally unique interneuronal subpopulation.

Axon initial segment-associated microglia

Microglia are the brain's resident immune cells and function as the main defense against pathogens or injury. However, in the absence of disease, microglia have other functions in the normal brain. For example, previous studies showed that microglia contribute to circuit refinement and synaptic plasticity in the developing and adult brain, respectively. Thus, microglia actively participate in regulating neuronal excitability and function. Here, we report that in the cortex, but not other brain regions, a subset of microglia extend a single process that specifically associates and overlaps with the axon initial segment (AIS), the site where action potentials are generated. Similar associations were not observed with dendrites or distal axons. Microglia-AIS interactions appear early in development, persist throughout adulthood, and are conserved across species including mice, rats, and primates. However, these interactions are lost after microglial activation following brain injury, suggesting that such interactions may be part of healthy brain function. Loss of microglial CX3CR1 receptors, or the specialized extracellular matrix surrounding the AIS, did not disrupt the interaction. However, loss of AIS proteins by the neuron-specific deletion of the master AIS scaffold AnkyrinG disrupted microglia-AIS interactions. These results reveal a unique population of microglia that specifically interact with the AIS in the adult cortex.

Multiple blocks of intermittent and continuous theta-burst stimulation applied via transcranial magnetic stimulation differently affect sensory responses in rat barrel cortex

KEY POINTS

Theta-burst stimulation (TBS) applied via transcranial magnetic stimulation is able to modulate human cortical excitability. Here we investigated in a rat model how two different forms of TBS, intermittent (iTBS) and continuous (cTBS), affect sensory responses in rat barrel cortex. We found that iTBS but less cTBS promoted late (>18 ms) sensory response components while not affecting the earliest response (8-18 ms). The effect increased with each of the five iTBS blocks applied. cTBS somewhat reduced the early response component after the first block but had a similar effect as iTBS after four to five blocks. We conclude that iTBS primarly modulates the activity of (inhibitory) cortical interneurons while cTBS may first reduce general neuronal excitability with a single block but reverse to iTBS-like effects with application of several blocks.

ABSTRACT

Cortical sensory processing varies with cortical state and the balance of inhibition to excitation. Repetitive transcranial magnetic stimulation (rTMS) has been shown to modulate human cortical excitability. In a rat model, we recently showed that intermittent theta-burst stimulation (iTBS) applied to the corpus callosum, to activate primarily supragranular cortical pyramidal cells but fewer subcortical neurons, strongly reduced the cortical expression of parvalbumin (PV), indicating reduced activity of fast-spiking interneurons. Here, we used the well-studied rodent barrel cortex system to test how iTBS and continuous TBS (cTBS) modulate sensory responses evoked by either single or double stimuli applied to the principal (PW) and/or adjacent whisker (AW) in urethane-anaesthetized rats. Compared to sham stimulation, iTBS but not cTBS particularly enhanced late (>18 ms) response components of multi-unit spiking and local field potential responses in layer 4 but not the very early response (<18 ms). Similarly, only iTBS diminished the suppression of the second response evoked by paired PW or AW-PW stimulation at 20 ms intervals. The effects increased with each of the five iTBS blocks applied. With cTBS a mild effect similar to that of iTBS was first evident after 4-5 stimulation blocks. Enhanced cortical c-Fos and zif268 expression but reduced PV and GAD67 expression was found only after iTBS, indicating increased cortical activity due to lowered inhibition. We conclude that iTBS but less cTBS may primarily weaken a late recurrent-type cortical inhibition mediated via a subset of PV+ interneurons, enabling stronger late response components believed to contribute to the perception of sensory events.

Some predictions of Rafael Lorente de Nó 80 years later

Rafael Lorente de Nó, the youngest of Santiago Ramón y Cajal disciples, was one of the last Century's more influential researches in neuroscience. This assay highlights two fundamental contributions of Rafael Lorente de Nó to neurobiology: the intrinsic organization of the mammalian cerebral cortex and the basic physiology of the neuron processes.

A guide to in vivo single-unit recording from optogenetically identified cortical inhibitory interneurons

A major challenge in neurophysiology has been to characterize the response properties and function of the numerous inhibitory cell types in the cerebral cortex. We here share our strategy for obtaining stable, well-isolated single-unit recordings from identified inhibitory interneurons in the anesthetized mouse cortex using a method developed by Lima and colleagues. Recordings are performed in mice expressing Channelrhodopsin-2 (ChR2) in specific neuronal subpopulations. Members of the population are identified by their response to a brief flash of blue light. This technique - termed "PINP", or Photostimulation-assisted Identification of Neuronal Populations - can be implemented with standard extracellular recording equipment. It can serve as an inexpensive and accessible alternative to calcium imaging or visually-guided patching, for the purpose of targeting extracellular recordings to genetically-identified cells. Here we provide a set of guidelines for optimizing the method in everyday practice. We refined our strategy specifically for targeting parvalbumin-positive (PV+) cells, but have found that it works for other interneuron types as well, such as somatostatin-expressing (SOM+) and calretinin-expressing (CR+) interneurons.

Focal cortical lesions induce bidirectional changes in the excitability of fast spiking and non fast spiking cortical interneurons

A physiological brain function requires neuronal networks to operate within a well-defined range of activity. Indeed, alterations in neuronal excitability have been associated with several pathological conditions, ranging from epilepsy to neuropsychiatric disorders. Changes in inhibitory transmission are known to play a key role in the development of hyperexcitability. However it is largely unknown whether specific interneuronal subpopulations contribute differentially to such pathological condition. In the present study we investigated functional alterations of inhibitory interneurons embedded in a hyperexcitable cortical circuit at the border of chronically induced focal lesions in mouse visual cortex. Interestingly, we found opposite alterations in the excitability of non fast-spiking (Non Fs) and fast-spiking (Fs) interneurons in acute cortical slices from injured animals. Non Fs interneurons displayed a depolarized membrane potential and a higher frequency of spontaneous excitatory postsynaptic currents (sEPSCs). In contrast, Fs interneurons showed a reduced sEPSCs amplitude. The observed downscaling of excitatory synapses targeting Fs interneurons may prevent the recruitment of this specific population of interneurons to the hyperexcitable network. This mechanism is likely to seriously affect neuronal network function and to exacerbate hyperexcitability but it may be important to protect this particular vulnerable population of GABAegic neurons from excitotoxicity.

Oscillatory multiplexing of neural population codes for interval timing and working memory

Interval timing and working memory are critical components of cognition that are supported by neural oscillations in prefrontal-striatal-hippocampal circuits. In this review, the properties of interval timing and working memory are explored in terms of behavioral, anatomical, pharmacological, and neurophysiological findings. We then describe the various neurobiological theories that have been developed to explain these cognitive processes - largely independent of each other. Following this, a coupled excitatory - inhibitory oscillation (EIO) model of temporal processing is proposed to address the shared oscillatory properties of interval timing and working memory. Using this integrative approach, we describe a hybrid model explaining how interval timing and working memory can originate from the same oscillatory processes, but differ in terms of which dimension of the neural oscillation is utilized for the extraction of item, temporal order, and duration information. This extension of the striatal beat-frequency (SBF) model of interval timing (Matell and Meck, 2000, 2004) is based on prefrontal-striatal-hippocampal circuit dynamics and has direct relevance to the pathophysiological distortions observed in time perception and working memory in a variety of psychiatric and neurological conditions.

Neural mechanisms of auditory categorization: from across brain areas to within local microcircuits

Categorization enables listeners to efficiently encode and respond to auditory stimuli. Behavioral evidence for auditory categorization has been well documented across a broad range of human and non-human animal species. Moreover, neural correlates of auditory categorization have been documented in a variety of different brain regions in the ventral auditory pathway, which is thought to underlie auditory-object processing and auditory perception. Here, we review and discuss how neural representations of auditory categories are transformed across different scales of neural organization in the ventral auditory pathway: from across different brain areas to within local microcircuits. We propose different neural transformations across different scales of neural organization in auditory categorization. Along the ascending auditory system in the ventral pathway, there is a progression in the encoding of categories from simple acoustic categories to categories for abstract information. On the other hand, in local microcircuits, different classes of neurons differentially compute categorical information.

Information processing in the primate basal ganglia during sensory-guided and internally driven rhythmic tapping

Gamma (γ) and beta (β) oscillations seem to play complementary functions in the cortico-basal ganglia-thalamo-cortical circuit (CBGT) during motor behavior. We investigated the time-varying changes of the putaminal spiking activity and the spectral power of local field potentials (LFPs) during a task where the rhythmic tapping of monkeys was guided by isochronous stimuli separated by a fixed duration (synchronization phase), followed by a period of internally timed movements (continuation phase). We found that the power of both bands and the discharge rate of cells showed an orderly change in magnitude as a function of the duration and/or the serial order of the intervals executed rhythmically. More LFPs were tuned to duration and/or serial order in the β- than the γ-band, although different values of preferred features were represented by single cells and by both bands. Importantly, in the LFPs tuned to serial order, there was a strong bias toward the continuation phase for the β-band when aligned to movements, and a bias toward the synchronization phase for the γ-band when aligned to the stimuli. Our results suggest that γ-oscillations reflect local computations associated with stimulus processing, whereas β-activity involves the entrainment of large putaminal circuits, probably in conjunction with other elements of CBGT, during internally driven rhythmic tapping.

Competitive interactions in sensorimotor cortex: oscillations express separation between alternative movement targets

Choice behavior is influenced by factors such as reward and number of alternatives but also by physical context, for instance, the relative position of alternative movement targets. At small separation, speeded eye or hand movements are more likely to land between targets (spatial averaging) than at larger separation. Neurocomputational models explain such behavior in terms of cortical activity being preshaped by the movement environment. Here, we manipulate target separation, as a determinant of motor cortical activity in choice behavior, to address neural mechanisms of response selection. Specifically, we investigate whether context-induced changes in the balance of cooperative and competitive interactions between competing groups of neurons are expressed in the power spectrum of sensorimotor rhythms. We recorded magnetoencephalography while participants were precued to two possible movement target locations at different angles of separation (30, 60, or 90°). After a delay, one of the locations was cued as the target for a joystick pointing movement. We found that late delay-period movement-preparatory activity increased more strongly for alternative targets at 30 than at 60 or 90° of separation. This nonlinear pattern was evident in slow event-related fields as well as in beta- and low-gamma-band suppression. A comparable pattern was found within an earlier window for theta-band synchronization. We interpret the late delay effects in terms of increased movement-preparatory activity when there is greater overlap and hence less competition between groups of neurons encoding two response alternatives. Early delay-period theta-band synchronization may reflect covert response activation relevant to behavioral spatial averaging effects.

Neurophysiology of timing in the hundreds of milliseconds: multiple layers of neuronal clocks in the medial premotor areas

The precise quantification of time in the subsecond scale is critical for many complex behaviors including music and dance appreciation/execution, speech comprehension/articulation, and the performance of many sports. Nevertheless, its neural underpinnings are largely unknown. Recent neurophysiological experiments from our laboratory have shown that the cell activity in the medial premotor areas (MPC) of macaques can represent different aspects of temporal processing during a synchronization-continuation tapping task (SCT). In this task the rhythmic behavior of monkeys was synchronized to a metronome of isochronous stimuli in the hundreds of milliseconds range (synchronization phase), followed by a period where animals internally temporalized their movements (continuation phase). Overall, we found that the time-keeping mechanism in MPC is governed by different layers of neural clocks. Close to the temporal control of movements are two separate populations of ramping cells that code for elapsed or remaining time for a tapping movement during the SCT. Thus, the sensorimotor loops engaged during the task may depend on the cyclic interplay between two neuronal chronometers that quantify in their instantaneous discharge rate the time passed and the remaining time for an action. In addition, we found MPC neurons that are tuned to the duration of produced intervals during the rhythmic task, showing an orderly variation in the average discharge rate as a function of duration. All the tested durations in the subsecond scale were represented in the preferred intervals of the cell population. Most of the interval-tuned cells were also tuned to the ordinal structure of the six intervals produced sequentially in the SCT. Hence, this next level of temporal processing may work as the notes of a musical score, providing information to the timing network about what duration and ordinal element of the sequence are being executed. Finally, we describe how the timing circuit can use a dynamic neural representation of the passage of time and the context in which the intervals are executed by integrating the time-varying activity of populations of cells. These neural population clocks can be defined as distinct trajectories in the multidimensional cell response-space. We provide a hypothesis of how these different levels of neural clocks can interact to constitute a coherent timing machine that controls the rhythmic behavior during the SCT.

Interval tuning in the primate medial premotor cortex as a general timing mechanism

The precise quantification of time during motor performance is critical for many complex behaviors, including musical execution, speech articulation, and sports; however, its neural mechanisms are primarily unknown. We found that neurons in the medial premotor cortex (MPC) of behaving monkeys are tuned to the duration of produced intervals during rhythmic tapping tasks. Interval-tuned neurons showed similar preferred intervals across tapping behaviors that varied in the number of produced intervals and the modality used to drive temporal processing. In addition, we found that the same population of neurons is able to multiplex the ordinal structure of a sequence of rhythmic movements and a wide range of durations in the range of hundreds of milliseconds. Our results also revealed a possible gain mechanism for encoding the total number of intervals in a sequence of temporalized movements, where interval-tuned cells show a multiplicative effect of their activity for longer sequences of intervals. These data suggest that MPC is part of a core timing network that uses interval tuning as a signal to represent temporal processing in a variety of behavioral contexts where time is explicitly quantified.

A cytological and experimental study of the neuropil and primary olfactory afferences to the piriform cortex

The microscopic organization of the piriform cortex (PC) was studied in normal and experimental material from adult albino rats. In rapid-Golgi specimens a set of collaterals from the lateral olfactory tract (i.e., sublayer Ia) to the neuropil of the Layer II (LII) was identified. Specimens from experimental animals that received electrolytic lesion of the main olfactory bulb three days before sacrificing, were further processed for pre-embedding immunocytochemistry to the enzyme glutamic acid decarboxylase 67 (GAD 67). This novel approach permitted a simultaneous visualization at electron microscopy of both synaptic degeneration and GAD67-immunoreactive (GAD-I) sites. Degenerating and GAD-I synapses were separately found in the neuropil of Layers I and II of the PC. Previously overlooked patches of neuropil were featured in sublayer Ia. These areas consisted of dendritic and axonal processes including four synaptic types. Tridimensional reconstructions from serial thin sections from LI revealed the external appearance of the varicose and tubular dendrites as well as the synaptic terminals therein. The putative source(s) of processes to the neuropil of sublayer Ia is discussed in the context of the internal circuitry of the PC and an alternative model is introduced.

The roles of monkey M1 neuron classes in movement preparation and execution

The motor cortices exhibit substantial activity while preparing movements, yet the arm remains still during preparation. We investigated whether a subpopulation of presumed inhibitory neurons in primary motor cortex (M1) might be involved in “gating” motor output during preparation, while permitting output during movement. This hypothesis predicts a release of inhibition just before movement onset. In data from M1 of two monkeys, we did not find evidence for this hypothesis: few neurons exhibited a clear pause during movement, and these were at the tail end of a broad distribution. We then identified a subpopulation likely to be enriched for inhibitory interneurons, using their waveform shapes. We found that the firing rates of this subpopulation tended to increase during movement instead of decreasing as predicted by the M1 gating model. No clear subset that might implement an inhibitory gate was observed. Together with previous evidence against upstream inhibitory mechanisms in premotor cortex, this provides evidence against an inhibitory “gate” for motor output in cortex. Instead, it appears that some other mechanism must likely exist.

Motor directional tuning across brain areas: directional resonance and the role of inhibition for directional accuracy

Motor directional tuning (Georgopoulos et al., 1982) has been found in every brain area in which it has been sought for during the past 30-odd years. It is typically broad, with widely distributed preferred directions and a population signal that predicts accurately the direction of an upcoming reaching movement or isometric force pulse (Georgopoulos et al., 1992). What is the basis for such ubiquitous directional tuning? How does the tuning come about? What are the implications of directional tuning for understanding the brain mechanisms of movement in space? This review addresses these questions in the light of accumulated knowledge in various sub-fields of neuroscience and motor behavior. It is argued (a) that direction in space encompasses many aspects, from vision to muscles, (b) that there is a directional congruence among the central representations of these distributed “directions” arising from rough but orderly topographic connectivities among brain areas, (c) that broad directional tuning is the result of broad excitation limited by recurrent and non-recurrent (i.e., direct) inhibition within the preferred direction loci in brain areas, and (d) that the width of the directional tuning curve, modulated by local inhibitory mechanisms, is a parameter that determines the accuracy of the directional command.

Role of cerebral cortex in the neuropathology of Huntington's disease

An expansion of glutamine repeats in the N-terminal domain of the huntingtin protein leads to Huntington's disease (HD), a neurodegenerative condition characterized by the presence of involuntary movements, dementia, and psychiatric disturbances. Evaluation of postmortem HD tissue indicates that the most prominent cell loss occurs in cerebral cortex and striatum, forebrain regions in which cortical pyramidal neurons (CPNs) and striatal medium spiny neurons (MSNs) are the most affected. Subsequent evidence obtained from HD patients and especially from transgenic mouse models of HD indicates that long before neuronal death, patterns of communication between CPNs and MSNs become dysfunctional. In fact, electrophysiological signaling in transgenic HD mice is altered even before the appearance of the HD behavioral phenotype, suggesting that dysfunctional cortical input to the striatum sets the stage for the emergence of HD neurological signs. Striatal MSNs, moreover, project back to cortex via multi-synaptic connections, allowing for even further disruptions in cortical processing. An effective therapeutic strategy for HD, therefore, may lie in understanding the synaptic mechanisms by which it dysregulates the corticostriatal system. Here, we review literature evaluating the molecular, morphological, and physiological alterations in the cerebral cortex, a key component of brain circuitry controlling motor behavior, as they occur in both patients and transgenic HD models.

Towards a circuit mechanism for movement tuning in motor cortex

The firing rates of neurons in primate motor cortex have been related to multiple parameters of voluntary movement. This finding has been corroborated by stimulation-based studies that have mapped complex movements in rodent and primate motor cortex. However, it has been difficult to link the movement tuning of a neuron with its role within the cortical microcircuit. In sensory cortex, neuronal tuning is largely established by afferents delivering information from tuned receptors in the periphery. Motor cortex, which lacks the granular input layer, may be better understood by analyzing its efferent projections. As a primary source of cortical output, layer 5 neurons represent an ideal starting point for this line of experimentation. It is in these deep output layers that movements can most effectively be evoked by intracortical microstimulation and recordings can obtain the most useful signals for the control of motor prostheses. Studies focused on layer 5 output neurons have revealed that projection identity is a fundamental property related to the laminar position, receptive field and ion channel complement of these cells. Given the variety of brain areas targeted by layer 5 output neurons, knowledge of a neuron's downstream connectivity may provide insight into its movement tuning. Future experiments that relate motor behavior to the activity of neurons with a known projection identity will yield a more detailed understanding of the function of cortical microcircuits.