Biology subjects

Westerberg, J. A.

Publications and source records attributed to Westerberg, J. A..

12 recordsLinked to original sources

bioRxiv2026

Visual cortical dynamics supporting predictable attentional capture

Visual behavior depends on the ability to prioritize relevant sensory information while filtering out distractions. Predictable sensory contexts enable more efficient behavior by altering sensory processing. Using laminar neurophysiology in macaque visual cortex measuring population spiking during a feature-based pop-out visual search task, we examined how predictable visual routines influence cortical columnar processing of sensory information. By manipulating predictability through attentional priming, we found improved behavioral performance with predictable stimulus arrays. These behavioral changes were supported by earlier neuronal attentional target selection driven by reduced variability in the sensory response to the predictable target stimulus and more homogeneous feedforward processing dynamics across the cortical column. More effective distractor suppression was driven by adapted feedforward processing of the more frequent distractor stimulus. Together, these changes implicate independent mechanisms for target enhancement and distractor suppression. Our results highlight how predictions from experience alter visual columnar processing to optimize attentional selection through streamlining feedforward signaling. HighlightsO_LIBoth target enhancement and distractor suppression are independently observable in visual cortex with different profiles of modulation as a function of predictability. C_LIO_LIPredictions produce stronger, more reliable feedforward responses to attention-capturing targets across the visual cortical layers. C_LIO_LIBetter distractor suppression with stimulus predictability is driven by adapted sensory representations, not top-down inhibition. C_LI SignificanceHow do predictions help determine what catches our attention? It is well known that when primates repeatedly perform visuomotor tasks, they become more proficient. Using neural recordings across the layers of the visual cortex, Groot et al. demonstrate that more efficient feedforward processing of sensory information contributes to improved visual behavior under predictable sensory conditions. These findings highlight the crucial role of predictions in proactively shaping sensory representations to facilitate efficient attentive behavior.

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bioRxiv2025

V1 interlaminar coherence decreases with interocular conflict

Resolving conflicting input from the two eyes is a fundamental challenge for the visual system. In the primary visual cortex (V1), such interocular conflict induces modest suppression of single neuron spiking, but the accompanying population-level dynamics remain poorly understood. Here we examined laminar multi-unit activity and interlaminar local field potential (LFP) coherence in macaque V1 during dichoptic stimulation and binocular rivalry flash suppression (BRFS). From laminar microelectrode recordings, we found that interocular conflict reliably reduces interlaminar coherence, particularly between granular and infragranular layers, suggesting altered temporal coordination across the cortical column. Strikingly, during BRFS, coherence remained reduced even when firing rates were unchanged. Moreover, interlaminar coherence is higher for perceptually dominant BRFS stimuli, indicating that coherence across V1 layers covaries with perceptual outcome in the absence of significant firing-rate differences. These findings show that the temporal dynamics of population coherence are a more stable signal of interocular conflict than spike rate modulation. SIGNIFICANCE STATEMENTThese findings suggest that V1 processes interocular conflict not only through modest rate changes but also through temporal coordination of population activity across cortical layers. Interlaminar coherence therefore offers a complementary perspective on V1s role during binocular rivalry, providing insight into population dynamics that may shape how visual signals are relayed to subsequent stages of visual processing.

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bioRxiv2025

Ubiquitous predictive processing in the spectral domain of sensory cortex

The appearance at the anatomical level of a canonical laminar microcircuit suggests that each six-layer column of granular cortex may mediate a canonical computation. Hypotheses for such computations include predictive coding, predictive routing, efficient coding, and others. However, single-neuron recordings capture only the individual elements of the hypothesized laminar microcircuit, while local field potentials (LFPs) from a laminar probe offer insight into the broader population activity. Through the Allen Institutes OpenScope Brain Observatory, data in mice performing a visual oddball task during multi-area laminar recording was used to test predictive processing hypotheses in the spectral domain. Histological labeling of the cortical laminae enabled a fine-grained examination of their roles in the task, and frequency bands capturing both feedforward and feedback effects were analyzed. {gamma}-band local-field potential (LFP) oscillations conveyed feedforward prediction errors in lower sensory areas of cortex; /{beta}-band oscillations weakened in unpredictable conditions compared to predictable ones; and {theta}-band oscillations additionally signalled slower, longer-scale temporal prediction errors. In combination with the previous findings, predictive routing explains these experiments where neither ubiquitous predictive coding nor feedforward adaptation can. SignificanceCortical columns robustly signal perceptual features through the firing rates of spiking neurons. In accordance with this rate coding, predictive processing theories hypothesized that neuronal firing rates ubiquitously signal surprise. However, a recent large-scale study of spike rates did not support this conjecture. An alternate model, predictive routing, suggests that neuronal oscillations rather than spike rates could encode surprise. These neuronal oscillations, which can affect the timing but not rate of spiking, formed coherent {gamma} rhythms which consistently signaled both simpler and more complex forms of surprise in mouse visual cortex. Together with the findings on spike-rates in the same experiment, our findings suggest that cortical circuits encode surprise in the rhythmic timing of spikes rather than in their rate.

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bioRxiv2024

Stimulus history, not expectation, drives sensory prediction errors in mammalian cortex

Hierarchical predictive coding (HPC) models have recently flourished in neuroscience1-9. Feedforward and feedback processing are at the heart of HPC models. Previous experimental studies using fMRI, EEG/MEG, and LFP9-11 do not reliably resolve feedback modulation from local computations and feedforward outputs. Here, using open-science8, multi-species, multi-area, high-density12, laminar neurophysiology13, we empirically test whether hierarchical predictive coding is a key component shaping cortical processing of visual stimuli. To isolate visual information processing and eliminate motor/reward confounders9-11, we use a no-report task. Our task leveraged so-called global oddballs (GO) as unpredictable, deviant stimuli that circumvent low-level adaptation. We examined their responses relative to local oddballs (LO) that we habituated into highly predictable priors. Four surprising findings in this dataset challenge many existing hierarchical predictive coding models. First, GO responses were exclusive to higher-order, more cognitive areas rather than early-to-mid visual cortex. Second, inhibitory interneuron-targeted optogenetics in primates and mice and waveform shape analysis in primates revealed no evidence that predictive suppression was implemented via these interneurons. Third, highly predictable LO responses dominated in over 50% of all neurons, including in higher-order cortex, which should have anticipated them, indicating limited evidence for predictive suppression. Lastly, prediction error responses evoked by GOs did not evoke feedforward processing. These results reveal circuit dynamics that govern how prediction shapes visual processing, motivating more neurally constrained predictive processing models.

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bioRxiv2024

The laminar organization of cell types in macaque cortex and its relationship to neuronal oscillations

The canonical microcircuit (CMC) has been hypothesized to be the fundamental unit of information processing in cortex. Each CMC unit is thought to be an interconnected column of neurons with specific connections between excitatory and inhibitory neurons across layers. Recently, we identified a conserved spectrolaminar motif of oscillatory activity across the primate cortex that may be the physiological consequence of the CMC. The spectrolaminar motif consists of local field potential (LFP) gamma-band power (40-150 Hz) peaking in superficial layers 2 and 3 and alpha/beta-band power (8-30 Hz) peaking in deep layers 5 and 6. Here, we investigate whether specific conserved cell types may produce the spectrolaminar motif. We collected laminar histological and electrophysiological data in 11 distinct cortical areas spanning the visual hierarchy: V1, V2, V3, V4, TEO, MT, MST, LIP, 8A/FEF, PMD, and LPFC (area 46), and anatomical data in DP and 7A. We stained representative slices for the three main inhibitory subtypes, Parvalbumin (PV), Calbindin (CB), and Calretinin (CR) positive neurons, as well as pyramidal cells marked with Neurogranin (NRGN). We found a conserved laminar structure of PV, CB, CR, and pyramidal cells. We also found a consistent relationship between the laminar distribution of inhibitory subtypes with power in the local field potential. PV interneuron density positively correlated with gamma (40-150 Hz) power. CR and CB density negatively correlated with alpha (8-12 Hz) and beta (13-30 Hz) oscillations. The conserved, layer-specific pattern of inhibition and excitation across layers is therefore likely the anatomical substrate of the spectrolaminar motif. Significance StatementNeuronal oscillations emerge as an interplay between excitatory and inhibitory neurons and underlie cognitive functions and conscious states. These oscillations have distinct expression patterns across cortical layers. Does cellular anatomy enable these oscillations to emerge in specific cortical layers? We present a comprehensive analysis of the laminar distribution of the three main inhibitory cell types in primate cortex (Parvalbumin, Calbindin, and Calretinin positive) and excitatory pyramidal cells. We found a canonical relationship between the laminar anatomy and electrophysiology in 11 distinct primate areas spanning from primary visual to prefrontal cortex. The laminar anatomy explained the expression patterns of neuronal oscillations in different frequencies. Our work provides insight into the cortex-wide cellular mechanisms that generate neuronal oscillations in primates.

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bioRxiv2023

Near-field potentials index local neural computations more accurately than population spiking

Local field potentials (LFP) are low-frequency extracellular voltage fluctuations thought to primarily arise from synaptic activity. However, unlike highly localized neuronal spiking, LFP is spatially less specific. LFP measured at one location is not entirely generated there due to far-field contributions that are passively conducted across volumes of neural tissue. We sought to quantify how much information within the locally generated, near-field low-frequency activity (nfLFP) is masked by volume-conducted far-field signals. To do so, we measured laminar neural activity in primary visual cortex (V1) of monkeys viewing sequences of multifeatured stimuli. We compared information content of regular LFP and nfLFP that was mathematically stripped of volume-conducted far-field contributions. Information content was estimated by decoding stimulus properties from neural responses via spatiotemporal multivariate pattern analysis. Volume-conducted information differed from locally generated information in two important ways: (1) for stimulus features relevant to V1 processing (orientation and eye-of-origin), nfLFP contained more information. (2) in contrast, the volume-conducted signal was more informative regarding temporal context (relative stimulus position in a sequence), a signal likely to be coming from elsewhere. Moreover, LFP and nfLFP differed both spectrally as well as spatially, urging caution regarding the interpretations of individual frequency bands and/or laminar patterns of LFP. Most importantly, we found that population spiking of local neurons was less informative than either the LFP or nfLFP, with nfLFP containing most of the relevant information regarding local stimulus processing. These findings suggest that the optimal way to read out local computational processing from neural activity is to decode the local contributions to LFP, with significant information loss hampering both regular LFP and local spiking. Authors ContributionsConceptualization, D.A.T., J.A.W, and A.M.; Data Collection, J.A.W., M.A.C., K.D.; Formal Analysis, D.A.T. and J.A.W.; Data Visualization, D.A.T. and J.A.W.; Original Draft, D.A.T., J.A.W., and A.M.; Revisions and Final Draft, D.A.T., J.A.W., M.A.C., K.D., M.T.W., A.M.B., and A.M. Competing InterestsThe authors declare no conflicts of interest.

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bioRxiv2022

Cortical Contributions to Medial Frontal β-Bursts during Executive Control

EEG {beta}-bursts observed over the medial frontal cortex are claimed to mediate response inhibition despite their infrequent occurrence. The weak association with stopping behavior is supposed to be a by-product of the low signal-to-noise ratio of EEG recordings. We tested the premise that {beta}-bursts are more common within the cerebral cortex and more directly associated with response inhibition. We sampled simultaneously EEG and intracortical local field potentials (LFP) within the medial frontal cortex (MFC) of two macaque monkeys performing a response inhibition task. Intracortical {beta}-bursts were just as infrequent as those in EEG and did not parallel the likelihood of canceling a planned response. Cortical {beta}-bursts were more prevalent in upper layers but were not synchronized across a cortical column or with EEG {beta}-bursts. These findings contradict claims for a causal contribution of {beta}-bursts during response inhibition, provide important constraints for biophysical and cortical circuit models, and invite further considerations of {beta}-burst function in cognitive control.

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bioRxiv2022

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 exists across the cortex. Here, we report such a motif in the power of local field potentials (LFP). We implanted multicontact laminar probes in five macaque monkeys and recorded activity across layers in 14 cortical areas at various hierarchical processing stages in all cortical lobes. The anatomical laminar locations of recordings were histologically identified via electrolytic lesions. In all areas, we found a common spectrolaminar pattern characterized by an increasing deep-to-superficial layer gradient of gamma frequency LFP power peaking in layers 2/3, and an increasing superficial-to-deep gradient of alpha-beta power peaking in layers 5/6. Our results show an electrophysiological dissociation between superficial and deep layers that is preserved across the cortex, suggesting a ubiquitous layer and frequency-based mechanism for cortical computation.

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bioRxiv2022

Feedforward attentional selection in sensory cortex

Salient objects stand out (pop-out) from their surroundings, grabbing our attention. Whether this phenomenon is a consequence of bottom-up sensory processing or predicated on top-down influence is debated. We show that the neural computation of attentional pop-out is embedded in the earliest cortical sensory response, seemingly void of feedback from higher-level areas. We measured synaptic and spiking activity across cortical columns in mid-level area V4 of monkeys searching for an attention-grabbing stimulus. Indexed by reaction times and behavioral accuracy, attention was captured at variable times. This moment of attentional capture occurred within the earliest feedforward response, both in terms of timing and spatial location. Moreover, the magnitude of the earliest sensory response predicted reaction times. Crucially, errant attentional selection and consequent behavior was associated with errant selection in sensory cortex. Together, these findings demonstrate a dominant role for feedforward activation of sensory cortex for dictating attentional priority and subsequent behavior. In briefWhy do certain objects stand out from their surroundings and seemingly grab our attention? In this study, Westerberg et al. determine that attentional selection for salient objects in our environment is computed in sensory cortex as soon as sensory information arrives. HighlightsO_LIEarly sensory responses in V4 predict attentional selection and behavioral responses C_LIO_LIErrant attentional selection in sensory cortex precedes errant behavior C_LIO_LITonic modulation of sensory cortex can regulate attentional selection C_LI

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bioRxiv2022

Resolving the mesoscopic missing link: Biophysical modeling of EEG from cortical columns in primates

Event-related potentials (ERP) are among the most widely measured indices for studying human cognition. While their timing and magnitude provide valuable insights, their usefulness is limited by our understanding of their neural generators at the circuit level. Inverse source localization offers insights into such generators, but their solutions are not unique. To address this problem, scientists have assumed the source space generating such signals comprises a set of discrete equivalent current dipoles, representing the activity of small cortical regions. Based on this notion, theoretical studies have employed forward modeling of scalp potentials to understand how changes in circuit-level dynamics translate into macroscopic ERPs. However, experimental validation is lacking because it requires in vivo measurements of intracranial brain sources. Laminar local field potentials (LFP) offer a mechanism for estimating intracranial current sources. Yet, a theoretical link between LFPs and intracranial brain sources is missing. Here, we present a forward modeling approach for estimating mesoscopic intracranial brain sources from LFPs and predict their contribution to macroscopic ERPs. We evaluate the accuracy of this LFP-based representation of brain sources utilizing synthetic laminar neurophysiological measurements and then demonstrate the power of the approach in vivo to clarify the source of a representative cognitive ERP component. To that end, LFP was measured across the cortical layers of visual area V4 in macaque monkeys performing an attention demanding task. We show that area V4 generates dipoles through layer-specific transsynaptic currents that biophysically recapitulate the ERP component through the detailed forward modeling. The constraints imposed on EEG production by this method also revealed an important dissociation between computational and biophysical contributors. As such, this approach represents an important bridge from the mesoscopic activity of cortical columns to the patterns of EEG we measure at the scalp. HighlightsO_LICognitive EEG production was accurately modeled from empirically measured cortical activity in awake macaques. C_LIO_LIV4 laminar activity plausibly generates the attention-related signal indexed by the EEG. C_LIO_LIModels demonstrate the importance of biophysical geometry in cognitive EEG production. C_LI

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bioRxiv2021

Laminar microcircuitry of visual cortex producing attention-associated electric fields

Cognitive operations are widely studied by measuring electric fields through EEG and ECoG. However, despite their widespread use, the component neural circuitry giving rise to these signals remains unknown. Specifically, the functional architecture of cortical columns which results in attention-associated electric fields has not been explored. Here we detail the laminar cortical circuitry underlying an attention-associated electric field often measured over posterior regions of the brain in humans and monkeys. First, we identified visual cortical area V4 as one plausible contributor to this attention-associated electric field through inverse modeling of cranial EEG in macaque monkeys performing a visual attention task. Next, we performed laminar neurophysiological recordings on the prelunate gyrus and identified the electric-field-producing dipoles as synaptic activity in distinct cortical layers of area V4. Specifically, activation in the extragranular layers of cortex resulted in the generation of the attention-associated dipole. Feature selectivity of a given cortical column determined the overall contribution to this electric field. Columns selective for the attended feature contributed more to the electric field than columns selective for a different feature. Lastly, the laminar profile of synaptic activity generated by V4 was sufficient to produce an attention-associated signal measurable outside of the column. These findings suggest that the top-down recipient cortical layers produce an attention-associated electric field capable of being measured extracranially and the relative contribution of each column depends upon the underlying functional architecture.

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bioRxiv2019

Stimulus-specific information flow across the canonical cortical microcircuit

The vast majority of mammalian neocortex consists of a stereotypical microcircuit, the canonical cortical microcircuit (CCM), consisting of a granular input layer, positioned between superficial and deep layers. Due to this uniform layout, neuronal activation tends to follow a similar laminar sequence, with unique information extracted at each step. For example, the primate primary visual cortex (V1) combines the two eyes signals, extracts stimulus orientation and modulates its activity depending on stimulus history. Several theories have been proposed on when and where these processes happen within the CCMs laminar activation sequence, but it has been methodologically challenging to test these hypotheses. Here, we use time-resolved multivariate pattern analysis (MVPA) to decode information regarding the eye-of-origin, stimulus orientation and stimulus repetition from simultaneously measured spiking responses across V1s laminar microcircuit. We find that eye-of-origin information was decodable for the entire duration of stimulus presentation, but diminished in the deepest layers of V1, consistent with the notion that two eyes signals are combined within the upper layers. Conversely, orientation information was transient and equally pronounced across the microcircuit, in line with the idea that this information is relayed to other areas for further processing. Moreover, when stimuli were repeated, information regarding orientation was enhanced at the expense of eye-of origin information, suggesting that V1 modulates information flow to optimize specific stimulus dimensions. Taken together, these findings provide empirical evidence that adjudicates between long-standing hypotheses and reveals how information transfer within the CCM supports unique cortical functions.\n\nSignificance StatementDespite the brains daunting complexity, there are common organizing principles across brain areas. For example, neocortical activation follows a stereotypical pattern that spreads from input layers towards layers above and below. While this activation pattern is well known, it has been challenging to ascertain how unique types of information are extracted within this common sequence in different brain areas. Here we use machine learning to track the flow of stimulus-specific information across the layers of visual cortex. We found that information regarding several separate stimulus dimensions was routed uniquely within the common activation sequence in a manner that confirmed prior model predictions. This finding demonstrates how differences in information flow within the stereotypical neocortical activation sequence shape area-specific functions.

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