Spike-phase coupling patterns reveal laminar identity in primate cortex

Propofol-mediated loss of consciousness disrupts predictive routing and local field phase modulation of neural activity

Predictive coding is a fundamental function of the cortex. The predictive routing model proposes a neurophysiological implementation for predictive coding. Predictions are fed back from the deep-layer cortex via alpha/beta (8 to 30 Hz) oscillations. They inhibit the gamma (40 to 100 Hz) and spiking that feed sensory inputs forward. Unpredicted inputs arrive in circuits unprepared by alpha/beta, resulting in enhanced gamma and spiking. To test the predictive routing model and its role in consciousness, we collected data from intracranial recordings of macaque monkeys during passive presentation of auditory oddballs before and after propofol-mediated loss of consciousness (LOC). In line with the predictive routing model, alpha/beta oscillations in the awake state served to inhibit the processing of predictable stimuli. Propofol-mediated LOC eliminated alpha/beta modulation by a predictable stimulus in the sensory cortex and alpha/beta coherence between sensory and frontal areas. As a result, oddball stimuli evoked enhanced gamma power, late period (>200 ms from stimulus onset) spiking, and superficial layer sinks in the sensory cortex. LOC also resulted in diminished decodability of pattern-level prediction error signals in the higher-order cortex. Therefore, the auditory cortex was in a disinhibited state during propofol-mediated LOC. However, despite these enhanced feedforward responses in the auditory cortex, there was a loss of differential spiking to oddballs in the higher-order cortex. This may be a consequence of a loss of within-area and interareal spike-field coupling in the alpha/beta and gamma frequency bands. These results provide strong constraints for current theories of consciousness.

Is there a ubiquitous spectrolaminar motif of local field potential power across primate neocortex?

Mendoza-Halliday, Major et al., 2024 ("The Paper")1 advocates a local field potential (LFP)-based approach to functional identification of cortical layers during "laminar" (simultaneous recordings from all cortical layers) multielectrode recordings in nonhuman primates (NHPs). The Paper describes a "ubiquitous spectrolaminar motif" in the primate neocortex: 1) 75-150 Hz power peaks in the supragranular layers, 2) 10-19 Hz power peaks in the infragranular layers and 3) the crossing point of their laminar power gradients identifies Layer 4 (L4). Identification of L4 is critical in general, but especially for The Paper as the "motif" discovery is couched within a framework whose central hypothesis is that gamma activity originates in the supragranular layers and reflects feedforward activity, while alpha-beta activity originates in the infragranular layers and reflects feedback activity. In an impressive scientific effort, The Paper analyzed laminar data from 14 cortical areas in 2 prior macaque studies and compared them to marmoset, mouse, and human data to further bolster the canonical nature of the motif. Identification of such canonical principles of brain operation is clearly a topic of broad scientific interest. Similarly, a reliable online method for L4 identification would be of broad scientific value for the rapidly increasing use of laminar recordings using numerous evolving technologies. Despite The Paper's strengths, and its potential for scientific impact, a series of concerns that are fundamental to the analysis and interpretation of laminar activity profile data in general, and local field potential (LFP) signals in particular, led us to question its conclusions. We thus evaluated the generality of The Paper's methods and findings using new sets of data comprised of stimulus-evoked laminar response profiles from primary and higher-order auditory cortices (A1 and belt cortex), and primary visual cortex (V1). The rationale for using these areas as a test bed for new methods is that their laminar anatomy and physiology have already been extensively characterized by prior studies, and there is general agreement across laboratories on key matters like L4 identification. Our analyses indicate that The Paper's findings do not generalize well to any of these cortical areas. In particular, we find The Paper's methods for L4 identification to be unreliable. Moreover, both methodological and statistical concerns, outlined below and in the supplement, question the stated prevalence of the motif in The Paper's published dataset. After summarizing our findings and related broader concerns, we briefly critique the evidence from biophysical modeling studies cited to support The Paper's conclusions. While our findings are at odds with the proposition of a ubiquitous spectrolaminar motif in the primate neocortex, The Paper already has, and will continue to spark debate and further experimentation. Hopefully this countervailing presentation will lead to robust collegial efforts to define optimal strategies for applying laminar recording methods in future studies.

Mixed selectivity: Cellular computations for complexity

The property of mixed selectivity has been discussed at a computational level and offers a strategy to maximize computational power by adding versatility to the functional role of each neuron. Here, we offer a biologically grounded implementational-level mechanistic explanation for mixed selectivity in neural circuits. We define pure, linear, and nonlinear mixed selectivity and discuss how these response properties can be obtained in simple neural circuits. Neurons that respond to multiple, statistically independent variables display mixed selectivity. If their activity can be expressed as a weighted sum, then they exhibit linear mixed selectivity; otherwise, they exhibit nonlinear mixed selectivity. Neural representations based on diverse nonlinear mixed selectivity are high dimensional; hence, they confer enormous flexibility to a simple downstream readout neural circuit. However, a simple neural circuit cannot possibly encode all possible mixtures of variables simultaneously, as this would require a combinatorially large number of mixed selectivity neurons. Gating mechanisms like oscillations and neuromodulation can solve this problem by dynamically selecting which variables are mixed and transmitted to the readout.

Acute Neuropixels Recordings in the Marmoset Monkey

High-density linear probes, such as Neuropixels, provide an unprecedented opportunity to understand how neural populations within specific laminar compartments contribute to behavior. Marmoset monkeys, unlike macaque monkeys, have a lissencephalic (smooth) cortex that enables recording perpendicular to the cortical surface, thus making them an ideal animal model for studying laminar computations. Here we present a method for acute Neuropixels recordings in the common marmoset (Callithrix jacchus). The approach replaces the native dura with an artificial silicon-based dura that grants visual access to the cortical surface, which is helpful in avoiding blood vessels, ensures perpendicular penetrations, and could be used in conjunction with optical imaging or optogenetic techniques. The chamber housing the artificial dura is simple to maintain with minimal risk of infection and could be combined with semichronic microdrives and wireless recording hardware. This technique enables repeated acute penetrations over a period of several months. With occasional removal of tissue growth on the pial surface, recordings can be performed for a year or more. The approach is fully compatible with Neuropixels probes, enabling the recording of hundreds of single neurons distributed throughout the cortical column.

A ubiquitous spectrolaminar motif of local field potential power across the primate cortex

The mammalian cerebral cortex is anatomically organized into a six-layer motif. It is currently unknown whether a corresponding laminar motif of neuronal activity patterns exists across the cortex. Here we report such a motif in the power of local field potentials (LFPs). Using laminar probes, we recorded LFPs from 14 cortical areas across the cortical hierarchy in five macaque monkeys. The laminar locations of recordings were histologically identified by electrolytic lesions. Across all areas, we found a ubiquitous spectrolaminar pattern characterized by an increasing deep-to-superficial layer gradient of high-frequency power peaking in layers 2/3 and an increasing superficial-to-deep gradient of alpha-beta power peaking in layers 5/6. Laminar recordings from additional species showed that the spectrolaminar pattern is highly preserved among primates-macaque, marmoset and human-but more dissimilar in mouse. Our results suggest the existence of a canonical layer-based and frequency-based mechanism for cortical computation.

Grouping cells in primate visual cortex

Our perception of how objects are laid out in visual scenes is remarkably stable, despite rapid shifts in the patterns of light that fall on the retina with each saccade. One mechanism that may help establish perceptual stability is border ownership assignment. Studies in macaque area V2 have identified border ownership neurons that signal which side of a border belongs to a foreground surface. This signal persists for hundreds of milliseconds after border ownership has been rendered ambiguous by deleting the stimulus features that distinguish foreground from background. Remarkably, this signal survives eye movements: border ownership neurons also exhibit border ownership signals de novo when an eye movement places the newly ambiguous border within their receptive field. The grouping cell hypothesis proposes the existence of hypothetical grouping cells in a downstream brain area. These cells would compute persistent proto-object representations and therefore have the properties to endow cells in upstream brain areas with selectivity for border ownership. Such grouping cells have been predicted to show a centripetal and persistent pattern of preferred side of ownership for a border placed parallel to the perimeter of their classical receptive field, and such a centripetal ownership preference pattern should also occur de novo in these same cells if an ambiguous border lands in their receptive field after a saccade. It is unknown if grouping cells exist. Here we used laminar multielectrodes in area V4 - the main source of feedback to V2 - of behaving macaques to determine whether such grouping cells exist. Consistent with the model prediction we find a substantial population of neurons with these properties, in all laminar compartments, and they exhibit a response latency that is short enough to act as the source that endows neurons in V2 with selectivity for border ownership. While grouping cell activity provides information about the location of foreground surfaces, these neurons are, counterintuitively, not as strongly tuned for luminance contrast polarity, a feature of those surfaces, as are border ownership cells. Our data suggest a division of labor in which these newly discovered grouping cells provide spatiotemporal continuity of segmented surfaces whereas border ownership cells link this location information with surface features such as luminance contrast.

Acute Neuropixels recordings in the marmoset monkey

High-density linear probes, like Neuropixels, provide an unprecedented opportunity to understand how neural populations within specific laminar compartments contribute to behavior. Marmoset monkeys, unlike macaque monkeys, have a lissencephalic (smooth) cortex that enables recording perpendicular to the cortical surface, thus making them an ideal animal model for studying laminar computations. Here we present a method for acute Neuropixels recordings in the common marmoset (Callithrix jacchus). The approach replaces the native dura with an artificial silicon-based dura that grants visual access to the cortical surface, which is helpful in avoiding blood vessels, ensures perpendicular penetrations, and could be used in conjunction with optical imaging or optogenetic techniques. The chamber housing the artificial dura is simple to maintain with minimal risk of infection and could be combined with semi-chronic microdrives and wireless recording hardware. This technique enables repeated acute penetrations over a period of several months. With occasional removal of tissue growth on the pial surface, recordings can be performed for a year or more. The approach is fully compatible with Neuropixels probes, enabling the recording of hundreds of single neurons distributed throughout the cortical column.

A sparse code for natural sound context in auditory cortex

Accurate sound perception can require integrating information over hundreds of milliseconds or even seconds. Spectro-temporal models of sound coding by single neurons in auditory cortex indicate that the majority of sound-evoked activity can be attributed to stimuli with a few tens of milliseconds. It remains uncertain how the auditory system integrates information about sensory context on a longer timescale. Here we characterized long-lasting contextual effects in auditory cortex (AC) using a diverse set of natural sound stimuli. We measured context effects as the difference in a neuron's response to a single probe sound following two different context sounds. Many AC neurons showed context effects lasting longer than the temporal window of a traditional spectro-temporal receptive field. The duration and magnitude of context effects varied substantially across neurons and stimuli. This diversity of context effects formed a sparse code across the neural population that encoded a wider range of contexts than any constituent neuron. Encoding model analysis indicates that context effects can be explained by activity in the local neural population, suggesting that recurrent local circuits support a long-lasting representation of sensory context in auditory cortex.

Propofol-mediated loss of consciousness disrupts predictive routing and local field phase modulation of neural activity

Predictive coding is a fundamental function of the cortex. The predictive routing model proposes a neurophysiological implementation for predictive coding. Predictions are fed back from deep-layer cortex via alpha/beta (8-30Hz) oscillations. They inhibit the gamma (40-100Hz) and spiking that feed sensory inputs forward. Unpredicted inputs arrive in circuits unprepared by alpha/beta, resulting in enhanced gamma and spiking. To test the predictive routing model and its role in consciousness, we collected data from intracranial recordings of macaque monkeys during passive presentation of auditory oddballs (e.g., AAAAB) before and after propofol-mediated loss of consciousness (LOC). In line with the predictive routing model, alpha/beta oscillations in the awake state served to inhibit the processing of predictable stimuli. Propofol-mediated LOC eliminated alpha/beta modulation by a predictable stimulus in sensory cortex and alpha/beta coherence between sensory and frontal areas. As a result, oddball stimuli evoked enhanced gamma power, late (> 200 ms from stimulus onset) period spiking, and superficial layer sinks in sensory cortex. Therefore, auditory cortex was in a disinhibited state during propofol-mediated LOC. However, despite these enhanced feedforward responses in auditory cortex, there was a loss of differential spiking to oddballs in higher order cortex. This may be a consequence of a loss of within-area and inter-area spike-field coupling in the alpha/beta and gamma frequency bands. These results provide strong constraints for current theories of consciousness.

Significance statement

Neurophysiology studies have found alpha/beta oscillations (8-30Hz), gamma oscillations (40-100Hz), and spiking activity during cognition. Alpha/beta power has an inverse relationship with gamma power/spiking. This inverse relationship suggests that gamma/spiking are under the inhibitory control of alpha/beta. The predictive routing model hypothesizes that alpha/beta oscillations selectively inhibit (and thereby control) cortical activity that is predictable. We tested whether this inhibitory control is a signature of consciousness. We used multi-area neurophysiology recordings in monkeys presented with tone sequences that varied in predictability. We recorded brain activity as the anesthetic propofol was administered to manipulate consciousness. Compared to conscious processing, propofol-mediated unconsciousness disrupted alpha/beta inhibitory control during predictive processing. This led to a disinhibition of gamma/spiking, consistent with the predictive routing model.

The double-drift illusion biases the marmoset oculomotor system

The double-drift illusion has two unique characteristics: The error between the perceived and physical position of the stimulus grows over time, and saccades to the moving target land much closer to the physical than the perceived location. These results suggest that the perceptual and saccade targeting systems integrate visual information over different time scales. Functional imaging studies in humans have revealed several potential cortical areas of interest, including the prefrontal cortex. However, we currently lack an animal model to study the neural mechanisms of location perception that underlie the double-drift illusion. To fill this gap, we trained two marmoset monkeys to fixate and then saccade to the double-drift stimulus. In line with human observers for radial double-drift trajectories with fast internal motion, we find that saccade endpoints show a significant bias that is, nevertheless, smaller than the bias seen in human perceptual reports. This bias is modulated by changes in the external and internal speeds of the stimulus. These results demonstrate that the saccade targeting system of the marmoset monkey is influenced by the double-drift illusion.

Spike-phase coupling patterns reveal laminar identity in primate cortex

The cortical column is one of the fundamental computational circuits in the brain. In order to understand the role neurons in different layers of this circuit play in cortical function it is necessary to identify the boundaries that separate the laminar compartments. While histological approaches can reveal ground truth they are not a practical means of identifying cortical layers in vivo. The gold standard for identifying laminar compartments in electrophysiological recordings is current-source density (CSD) analysis. However, laminar CSD analysis requires averaging across reliably evoked responses that target the input layer in cortex, which may be difficult to generate in less well-studied cortical regions. Further, the analysis can be susceptible to noise on individual channels resulting in errors in assigning laminar boundaries. Here, we have analyzed linear array recordings in multiple cortical areas in both the common marmoset and the rhesus macaque. We describe a pattern of laminar spike-field phase relationships that reliably identifies the transition between input and deep layers in cortical recordings from multiple cortical areas in two different non-human primate species. This measure corresponds well to estimates of the location of the input layer using CSDs, but does not require averaging or specific evoked activity. Laminar identity can be estimated rapidly with as little as a minute of ongoing data and is invariant to many experimental parameters. This method may serve to validate CSD measurements that might otherwise be unreliable or to estimate laminar boundaries when other methods are not practical.