10 Simple Rules for a Supportive Lab Environment.

The transition to principal investigator (PI), or lab leader, can be challenging, partially due to the need to fulfil new managerial and leadership responsibilities. One key aspect of this role, which is often not explicitly discussed, is creating a supportive lab environment. Here, we present ten simple rules to guide the new PI in the development of their own positive and thriving lab atmosphere. These rules were written and voted on collaboratively, by the students and mentees of Professor Mark Stokes, who inspired this piece.

Temporal prediction elicits rhythmic preactivation of relevant sensory cortices.

Being able to anticipate events before they happen facilitates stimulus processing. The anticipation of the contents of events is thought to be implemented by the elicitation of prestimulus templates in sensory cortex. In contrast, the anticipation of the timing of events is typically associated with entrainment of neural oscillations. It is so far unknown whether and in which conditions temporal expectations interact with feature-based expectations, and, consequently, whether entrainment modulates the generation of content-specific sensory templates. In this study, we investigated the role of temporal expectations in a sensory discrimination task. We presented participants with rhythmically interleaved visual and auditory streams of relevant and irrelevant stimuli while measuring neural activity using magnetoencephalography. We found no evidence that rhythmic stimulation induced prestimulus feature templates. However, we did observe clear anticipatory rhythmic preactivation of the relevant sensory cortices. This oscillatory activity peaked at behaviourally relevant, in-phase, intervals. Our results suggest that temporal expectations about stimulus features do not behave similarly to explicitly cued, nonrhythmic, expectations, yet elicit a distinct form of modality-specific preactivation.

Phasic modulation of visual representations during sustained attention.

Sustained attention has long been thought to benefit perception in a continuous fashion, but recent evidence suggests that it affects perception in a discrete, rhythmic way. Periodic fluctuations in behavioral performance over time, and modulations of behavioral performance by the phase of spontaneous oscillatory brain activity point to an attentional sampling rate in the theta or alpha frequency range. We investigated whether such discrete sampling by attention is reflected in periodic fluctuations in the decodability of visual stimulus orientation from magnetoencephalographic (MEG) brain signals. In this exploratory study, human subjects attended one of the two grating stimuli, while MEG was being recorded. We assessed the strength of the visual representation of the attended stimulus using a support vector machine (SVM) to decode the orientation of the grating (clockwise vs. counterclockwise) from the MEG signal. We tested whether decoder performance depended on the theta/alpha phase of local brain activity. While the phase of ongoing activity in the visual cortex did not modulate decoding performance, theta/alpha phase of activity in the frontal eye fields and parietal cortex, contralateral to the attended stimulus did modulate decoding performance. These findings suggest that phasic modulations of visual stimulus representations in the brain are caused by frequency-specific top-down activity in the frontoparietal attention network, though the behavioral relevance of these effects could not be established.

Scene Context Impairs Perception of Semantically Congruent Objects.

Visual scene context is well-known to facilitate the recognition of scene-congruent objects. Interestingly, however, according to predictive-processing accounts of brain function, scene congruency may lead to reduced (rather than enhanced) processing of congruent objects, compared with incongruent ones, because congruent objects elicit reduced prediction-error responses. We tested this counterintuitive hypothesis in two online behavioral experiments with human participants (N = 300). We found clear evidence for impaired perception of congruent objects, both in a change-detection task measuring response times and in a bias-free object-discrimination task measuring accuracy. Congruency costs were related to independent subjective congruency ratings. Finally, we show that the reported effects cannot be explained by low-level stimulus confounds, response biases, or top-down strategy. These results provide convincing evidence for perceptual congruency costs during scene viewing, in line with predictive-processing theory.

Hippocampal and Prefrontal Theta-Band Mechanisms Underpin Implicit Spatial Context Learning.

Humans can rapidly and seemingly implicitly learn to predict typical locations of relevant items when those items are encountered in familiar spatial contexts. Two important questions remain, however, concerning this type of learning: (1) which neural structures and mechanisms are involved in acquiring and exploiting such contextual knowledge? (2) Is this type of learning truly implicit and unconscious? We now answer both these questions after closely examining behavior and recording neural activity using MEG while observers (male and female) were acquiring and exploiting statistical regularities. Computational modeling of behavioral data suggested that, after repeated exposures to a spatial context, participants' behavior was marked by an abrupt switch to an exploitation strategy of the learnt regularities. MEG recordings showed that hippocampus and prefrontal cortex (PFC) were involved in the task and furthermore revealed a striking dissociation: only the initial learning phase was associated with hippocampal theta band activity, while the subsequent exploitation phase showed a shift in theta band activity to the PFC. Intriguingly, the behavioral benefit of repeated exposures to certain scenes was inversely related to explicit awareness of such repeats, demonstrating the implicit nature of the expectations acquired. Together, these findings demonstrate that (1a) hippocampus and PFC play complementary roles in the implicit, unconscious learning and exploitation of spatial statistical regularities; (1b) these mechanisms are implemented in the theta frequency band; and (2) contextual knowledge can indeed be acquired unconsciously, and awareness of such knowledge can even interfere with the exploitation thereof.SIGNIFICANCE STATEMENT Human visual perception is determined not just by the light that strikes our eyes, but also strongly by our prior knowledge and expectations. Such expectations, particularly about where to expect certain objects given scene context, might be learned implicitly and unconsciously, although this is hotly debated. Furthermore, it is unknown which brain mechanisms underpin this type of learning. We now show that, indeed, spatial prior expectations can be learned without awareness; in fact, strikingly, awareness seems to hinder the exploitation of the relevant knowledge. Furthermore, we demonstrate that one brain mechanism (hippocampal theta-band activity) is responsible for learning in these settings, whereas another mechanism (prefrontal theta-band activity) is involved in exploiting the learned associations.

Previously Reward-Associated Stimuli Capture Spatial Attention in the Absence of Changes in the Corresponding Sensory Representations as Measured with MEG.

Studies of selective attention typically consider the role of task goals or physical salience, but attention can also be captured by previously reward-associated stimuli, even if they are currently task irrelevant. One theory underlying this value-driven attentional capture (VDAC) is that reward-associated stimulus representations undergo plasticity in sensory cortex, thereby automatically capturing attention during early processing. To test this, we used magnetoencephalography to probe whether stimulus location and identity representations in sensory cortex are modulated by reward learning. We furthermore investigated the time course of these neural effects, and their relationship to behavioral VDAC. Male and female human participants first learned stimulus-reward associations. Next, we measured VDAC in a separate task by presenting these stimuli in the absence of reward contingency and probing their effects on the processing of separate target stimuli presented at different time lags. Using time-resolved multivariate pattern analysis, we found that learned value modulated the spatial selection of previously rewarded stimuli in posterior visual and parietal cortex from ∼260 ms after stimulus onset. This value modulation was related to the strength of participants' behavioral VDAC effect and persisted into subsequent target processing. Importantly, learned value did not influence cortical signatures of early processing (i.e., earlier than ∼200 ms); nor did it influence the decodability of stimulus identity. Our results suggest that VDAC is underpinned by learned value signals that modulate spatial selection throughout posterior visual and parietal cortex. We further suggest that VDAC can occur in the absence of changes in early visual processing in cortex.SIGNIFICANCE STATEMENT Attention is our ability to focus on relevant information at the expense of irrelevant information. It can be affected by previously learned but currently irrelevant stimulus-reward associations, a phenomenon termed "value-driven attentional capture" (VDAC). The neural mechanisms underlying VDAC remain unclear. It has been speculated that reward learning induces visual cortical plasticity, which modulates early visual processing to capture attention. Although we find that learned value modulates spatial signals in visual cortical areas, an effect that correlates with VDAC, we find no relevant signatures of changes in early visual processing in cortex.

Rapid invisible frequency tagging reveals nonlinear integration of auditory and visual information.

During communication in real-life settings, the brain integrates information from auditory and visual modalities to form a unified percept of our environment. In the current magnetoencephalography (MEG) study, we used rapid invisible frequency tagging (RIFT) to generate steady-state evoked fields and investigated the integration of audiovisual information in a semantic context. We presented participants with videos of an actress uttering action verbs (auditory; tagged at 61 Hz) accompanied by a gesture (visual; tagged at 68 Hz, using a projector with a 1,440 Hz refresh rate). Integration difficulty was manipulated by lower-order auditory factors (clear/degraded speech) and higher-order visual factors (congruent/incongruent gesture). We identified MEG spectral peaks at the individual (61/68 Hz) tagging frequencies. We furthermore observed a peak at the intermodulation frequency of the auditory and visually tagged signals (fvisual - fauditory = 7 Hz), specifically when lower-order integration was easiest because signal quality was optimal. This intermodulation peak is a signature of nonlinear audiovisual integration, and was strongest in left inferior frontal gyrus and left temporal regions; areas known to be involved in speech-gesture integration. The enhanced power at the intermodulation frequency thus reflects the ease of lower-order audiovisual integration and demonstrates that speech-gesture information interacts in higher-order language areas. Furthermore, we provide a proof-of-principle of the use of RIFT to study the integration of audiovisual stimuli, in relation to, for instance, semantic context.

Familiarity Increases Processing Speed in the Visual System.

Familiarity with a stimulus leads to an attenuated neural response to the stimulus. Alongside this attenuation, recent studies have also observed a truncation of stimulus-evoked activity for familiar visual input. One proposed function of this truncation is to rapidly put neurons in a state of readiness to respond to new input. Here, we examined this hypothesis by presenting human participants with target stimuli that were embedded in rapid streams of familiar or novel distractor stimuli at different speeds of presentation, while recording brain activity using magnetoencephalography and measuring behavioral performance. We investigated the temporal and spatial dynamics of signal truncation and whether this phenomenon bears relationship to participants' ability to categorize target items within a visual stream. Behaviorally, target categorization performance was markedly better when the target was embedded within familiar distractors, and this benefit became more pronounced with increasing speed of presentation. Familiar distractors showed a truncation of neural activity in the visual system. This truncation was strongest for the fastest presentation speeds and peaked in progressively more anterior cortical regions as presentation speeds became slower. Moreover, the neural response evoked by the target was stronger when this target was preceded by familiar distractors. Taken together, these findings demonstrate that item familiarity results in a truncated neural response, is associated with stronger processing of relevant target information, and leads to superior perceptual performance.

Stable and Dynamic Coding for Working Memory in Primate Prefrontal Cortex.

Working memory (WM) provides the stability necessary for high-level cognition. Influential theories typically assume that WM depends on the persistence of stable neural representations, yet increasing evidence suggests that neural states are highly dynamic. Here we apply multivariate pattern analysis to explore the population dynamics in primate lateral prefrontal cortex (PFC) during three variants of the classic memory-guided saccade task (recorded in four animals). We observed the hallmark of dynamic population coding across key phases of a working memory task: sensory processing, memory encoding, and response execution. Throughout both these dynamic epochs and the memory delay period, however, the neural representational geometry remained stable. We identified two characteristics that jointly explain these dynamics: (1) time-varying changes in the subpopulation of neurons coding for task variables (i.e., dynamic subpopulations); and (2) time-varying selectivity within neurons (i.e., dynamic selectivity). These results indicate that even in a very simple memory-guided saccade task, PFC neurons display complex dynamics to support stable representations for WM.SIGNIFICANCE STATEMENT Flexible, intelligent behavior requires the maintenance and manipulation of incoming information over various time spans. For short time spans, this faculty is labeled "working memory" (WM). Dominant models propose that WM is maintained by stable, persistent patterns of neural activity in prefrontal cortex (PFC). However, recent evidence suggests that neural activity in PFC is dynamic, even while the contents of WM remain stably represented. Here, we explored the neural dynamics in PFC during a memory-guided saccade task. We found evidence for dynamic population coding in various task epochs, despite striking stability in the neural representational geometry of WM. Furthermore, we identified two distinct cellular mechanisms that contribute to dynamic population coding.

The Neural Mechanisms of Prediction in Visual Search.

The speed of visual search depends on bottom-up stimulus features (e.g., we quickly locate a red item among blue distractors), but it is also facilitated by the presence of top-down perceptual predictions about the item. Here, we identify the nature, source, and neuronal substrate of the predictions that speed up resumed visual search. Human subjects were presented with a visual search array that was repeated up to 4 times, while brain activity was recorded using magnetoencephalography (MEG). Behaviorally, we observed a bimodal reaction time distribution for resumed visual search, indicating that subjects were extraordinarily rapid on a proportion of trials. MEG data demonstrated that these rapid-response trials were associated with a prediction of (1) target location, as reflected by alpha-band (8-12 Hz) lateralization; and (2) target identity, as reflected by beta-band (15-30 Hz) lateralization. Moreover, we show that these predictions are likely generated in a network consisting of medial superior frontal cortex and right temporo-parietal junction. These findings underscore the importance and nature of perceptual hypotheses for efficient visual search.

Local entrainment of α oscillations by visual stimuli causes cyclic modulation of perception.

Prestimulus oscillatory neural activity in the visual cortex has large consequences for perception and can be influenced by top-down control from higher-order brain regions. Making a causal claim about the mechanistic role of oscillatory activity requires that oscillations be directly manipulated independently of cognitive instructions. There are indications that a direct manipulation, or entrainment, of visual alpha activity is possible through visual stimulation. However, three important questions remain: (1) Can the entrained alpha activity be endogenously maintained in the absence of continuous stimulation?; (2) Does entrainment of alpha activity reflect a global or a local process?; and (3) Does the entrained alpha activity influence perception? To address these questions, we presented human subjects with rhythmic stimuli in one visual hemifield, and arhythmic stimuli in the other. After rhythmic entrainment, we found a periodic pattern in detection performance of near-threshold targets specific to the entrained hemifield. Using magnetoencephalograhy to measure ongoing brain activity, we observed strong alpha activity contralateral to the rhythmic stimulation outlasting the stimulation by several cycles. This entrained alpha activity was produced locally in early visual cortex, as revealed by source analysis. Importantly, stronger alpha entrainment predicted a stronger phasic modulation of detection performance in the entrained hemifield. These findings argue for a cortically focal entrainment of ongoing alpha oscillations by visual stimulation, with concomitant consequences for perception. Our results support the notion that oscillatory brain activity in the alpha band provides a causal mechanism for the temporal organization of visual perception.

The hippocampus and implicit memory (by any other name).

Is the hippocampus involved in implicit memory? I argue that contemporary views on hippocampal function, going beyond the classic dichotomy of explicit versus implicit, predict involvement of the hippocampus whenever flexible, predictive associations are rapidly encoded. This involvement is independent of conscious awareness. A paradigm case is statistical learning: the unconscious extraction of statistical regularities from the environment. In line with this, a substantial body of literature on contextual cueing in visual search has established hippocampal involvement in this form of implicit learning. To conclude, implicit memory (as such or by any other name) is associated with the hippocampus.

Magnetoencephalography recordings reveal the neural mechanisms of auditory contributions to improved visual detection.

Sounds enhance the detection of visual stimuli while concurrently biasing an observer's decisions. To investigate the neural mechanisms that underlie such multisensory interactions, we decoded time-resolved Signal Detection Theory sensitivity and criterion parameters from magneto-encephalographic recordings of participants that performed a visual detection task. We found that sounds improved visual detection sensitivity by enhancing the accumulation and maintenance of perceptual evidence over time. Meanwhile, criterion decoding analyses revealed that sounds induced brain activity patterns that resembled the patterns evoked by an actual visual stimulus. These two complementary mechanisms of audiovisual interplay differed in terms of their automaticity: Whereas the sound-induced enhancement in visual sensitivity depended on participants being actively engaged in a detection task, we found that sounds activated the visual cortex irrespective of task demands, potentially inducing visual illusory percepts. These results challenge the classical assumption that sound-induced increases in false alarms exclusively correspond to decision-level biases.

Cortical activity during naturalistic music listening reflects short-range predictions based on long-term experience.

Expectations shape our experience of music. However, the internal model upon which listeners form melodic expectations is still debated. Do expectations stem from Gestalt-like principles or statistical learning? If the latter, does long-term experience play an important role, or are short-term regularities sufficient? And finally, what length of context informs contextual expectations? To answer these questions, we presented human listeners with diverse naturalistic compositions from Western classical music, while recording neural activity using MEG. We quantified note-level melodic surprise and uncertainty using various computational models of music, including a state-of-the-art transformer neural network. A time-resolved regression analysis revealed that neural activity over fronto-temporal sensors tracked melodic surprise particularly around 200ms and 300-500ms after note onset. This neural surprise response was dissociated from sensory-acoustic and adaptation effects. Neural surprise was best predicted by computational models that incorporated long-term statistical learning-rather than by simple, Gestalt-like principles. Yet, intriguingly, the surprise reflected primarily short-range musical contexts of less than ten notes. We present a full replication of our novel MEG results in an openly available EEG dataset. Together, these results elucidate the internal model that shapes melodic predictions during naturalistic music listening.

No exploitation of temporal sequence context during visual search.

The human visual system can rapidly extract regularities from our visual environment, generating predictive context. It has been shown that spatial predictive context can be used during visual search. We set out to see whether observers can additionally exploit temporal predictive context based on sequence order, using an extended version of a contextual cueing paradigm. Though we replicated the contextual cueing effect, repeating search scenes in a structured order versus a random order yielded no additional behavioural benefit. This was also true when we looked specifically at participants who revealed a sensitivity to spatial predictive context. We argue that spatial predictive context during visual search is more readily learned and subsequently exploited than temporal predictive context, potentially rendering the latter redundant. In conclusion, unlike spatial context, temporal context is not automatically extracted and used during visual search.

A Bayesian and efficient observer model explains concurrent attractive and repulsive history biases in visual perception.

Human perceptual decisions can be repelled away from (repulsive adaptation) or attracted towards recent visual experience (attractive serial dependence). It is currently unclear whether and how these repulsive and attractive biases interact during visual processing and what computational principles underlie these history dependencies. Here we disentangle repulsive and attractive biases by exploring their respective timescales. We find that perceptual decisions are concurrently attracted towards the short-term perceptual history and repelled from stimuli experienced up to minutes into the past. The temporal pattern of short-term attraction and long-term repulsion cannot be captured by an ideal Bayesian observer model alone. Instead, it is well captured by an ideal observer model with efficient encoding and Bayesian decoding of visual information in a slowly changing environment. Concurrent attractive and repulsive history biases in perceptual decisions may thus be the consequence of the need for visual processing to simultaneously satisfy constraints of efficiency and stability.

The Importance of Single-Trial Analyses in Cognitive Neuroscience.

Theories of working memory typically assume that information is maintained via persistent neural activity. By contrast, Lundqvist et al. report that single-trial delay activity is actually 'bursty'; the classic profile of persistent activity is an artefact of trial-wise averaging. Tackling brain-behaviour relationships at the single-trial level is an important future direction for cognitive neuroscience.

Discriminating Valid from Spurious Indices of Phase-Amplitude Coupling.

Recently there has been a strong interest in cross-frequency coupling, the interaction between neuronal oscillations in different frequency bands. In particular, measures quantifying the coupling between the phase of slow oscillations and the amplitude of fast oscillations have been applied to a wide range of data recorded from animals and humans. Some of the measures applied to detect phase-amplitude coupling have been criticized for being sensitive to nonsinusoidal properties of the oscillations and thus spuriously indicate the presence of coupling. While such instances of spurious identification of coupling have been observed, in this commentary we give concrete examples illustrating cases when the identification of cross-frequency coupling can be trusted. These examples are based on control analyses and empirical observations rather than signal-processing tools. Finally, we provide concrete advice on how to determine when measures of phase-amplitude coupling can be considered trustworthy.

Decoding Rich Spatial Information with High Temporal Resolution.

New research suggests that magnetoencephalography (MEG) contains rich spatial information for decoding neural states. Even small differences in the angle of neighbouring dipoles generate subtle, but statistically separable field patterns. This implies MEG (and electroencephalography: EEG) is ideal for decoding neural states with high-temporal resolution in the human brain.

Hippocampal theta modulation of neocortical spike times and gamma rhythm: a biophysical model study.

The hippocampal theta and neocortical gamma rhythms are two prominent examples of oscillatory neuronal activity. The hippocampus has often been hypothesized to influence neocortical networks by its theta rhythm, and, recently, evidence for such a direct influence has been found. We examined a possible mechanism for this influence by means of a biophysical model study using conductance-based model neurons. We found, in agreement with previous studies, that networks of fast-spiking GABA-ergic interneurons, coupled with shunting inhibition, synchronize their spike activity at a gamma frequency and are able to impose this rhythm on a network of pyramidal cells to which they are coupled. When our model was supplied with hippocampal theta-modulated input fibres, the theta rhythm biased the spike timings of both the fast-spiking and pyramidal cells. Furthermore, both the amplitude and frequency of local field potential gamma oscillations were influenced by the phase of the theta rhythm. We show that the fast-spiking cells, not pyramidal cells, are essential for this latter phenomenon, thus highlighting their crucial role in the interplay between hippocampus and neocortex.