Biology subjects

Woolgar, A.

Publications and source records attributed to Woolgar, A..

36 records · Page 2Linked to original sources

bioRxiv2021

Adaptive coding of stimulus information in human fronto-parietal cortex during visual classification

The neural mechanisms of how frontal and parietal brain regions support flexible adaptation of behavior remain poorly understood. Here, we used functional magnetic resonance imaging (fMRI) and model-based representational similarity analysis (RSA) to investigate frontoparietal representations of stimulus information during visual classification under varying task demands. Based on prior research, we predicted that increasing perceptual task difficulty should lead to more categorical coding of stimulus information, and that exemplar-level stimulus coding would be restricted to posterior, sensory brain regions. Counter to our expectations, however, we found frontoparietal regions encoded exemplar-level stimulus information. Interestingly, the anterior intraparietal sulcus (aIPS) encoded stimuli equally well regardless of perceptual difficulty, and these representations were directly related to choice behavior (proportion of guessing). Overall, these findings reveal unexpected exemplar-level stimulus coding in frontoparietal cortex, and highlight the role of aIPS in supporting adaptive behavior.

neuroscience↗

bioRxiv2021

Caveats and nuances of model-based and model-free representational connectivity analysis

Brain connectivity analyses have conventionally relied on statistical relationship between one-dimensional summaries of activation in different brain areas. However, summarising activation patterns within each area to a single dimension ignores the potential statistical dependencies between their multi-dimensional activity patterns. Representational Connectivity Analyses (RCA) is a method that quantifies the relationship between multi-dimensional patterns of activity without reducing the dimensionality of the data. We consider two variants of RCA. In model-free RCA, the goal is to quantify the shared information for two brain regions. In model-based RCA, one tests whether two regions have shared information about a specific aspect of the stimuli/task, as defined by a model. However, this is a new approach and the potential caveats of model-free and model-based RCA are still understudied. We first explain how model-based RCA detects connectivity through the lens of models, and then present three scenarios where model-based and model-free RCA give discrepant results. These conflicting results complicate the interpretation of functional connectivity. We highlight the challenges in three scenarios: complex intermediate models, common patterns across regions and transformation of representational structure across brain regions. The paper is accompanied by scripts that reproduce the results. In each case, we suggest potential ways to mitigate the difficulties caused by inconsistent results. The results of this study shed light on some understudied aspects of RCA, and allow researchers to use the method more effectively.

neuroscience↗

bioRxiv2021

When the whole is less than the sum of its parts: maximum object category information and behavioral prediction in multiscale activation patterns

Neural codes are reflected in complex, temporally and spatially specific patterns of activation. One popular approach to decode neural codes in electroencephalography (EEG) is multivariate decoding. This approach examines the discriminability of activity patterns across experimental conditions to test if EEG contains information about those conditions. However, conventional decoding analyses ignore aspects of neural activity which are informative. Specifically, EEG data can be decomposed into a large number of mathematically distinct features (e.g., entropy, Fourier and Wavelet coefficients) which can reflect different aspects of neural activity. We previously compared 30 such features of EEG data, and found that visual category, and participant behavior, can be more accurately predicted using multiscale spatiotemporally sensitive Wavelet coefficients than mean amplitude (Karimi-Rouzbahani et al., 2021b). Here, we considered that even this larger set of features may only partially capture the underlying neural code, because the brain could use a combination of encoding protocols within a single trial which is not reflected in any one mathematical feature alone. To check, we combined those mathematical features using state-of-the-art supervised and unsupervised feature selection procedures (n = 17). Across 3 datasets, we compared decoding of visual object category between these 17 sets of combined features, and between combined and individual features. Object category could be robustly decoded using the combined features from all of the 17 algorithms. However, the combination of features, which were equalized in dimension to the individual features, were outperformed in most of the time points by the most informative individual feature (Wavelet coefficients). Moreover, the Wavelet coefficients also explained the behavioral performance more accurately than the combined features. These results suggest that a single but multiscale encoding protocol may capture the neural code better than any combination of features. Our findings put new constraints on the models of neural information encoding in EEG.

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bioRxiv2021

Now you see it, now you don't: optimal parameters for interslice stimulation in concurrent TMS-fMRI

The powerful combination of transcranial magnetic stimulation (TMS) concurrent with functional magnetic resonance imaging (fMRI) provides rare insights into the causal relationships between brain activity and behaviour. Despite a recent resurgence in popularity, TMS-fMRI remains technically challenging. Here we examined the feasibility of applying TMS during short gaps between fMRI slices to avoid incurring artefacts in the fMRI data. We quantified signal dropout and changes in temporal signal-to-noise ratio (tSNR) for TMS pulses presented at timepoints from 100ms before to 100ms after slice onset. Up to 3 pulses were delivered per volume using MagVentures MR-compatible TMS coil. We used a spherical phantom, two 7-channel TMS-dedicated surface coils, and a multiband (MB) sequence (factor=2) with interslice gaps of 100ms and 40ms, on a Siemens 3T Prisma-fit scanner. For comparison we repeated a subset of parameters with a more standard single-channel TxRx (birdcage) coil, and with a human participant and surface coil set up. We found that, even at 100% stimulator output, pulses applied at least - 40ms/+50ms from the onset of slice readout avoid incurring artifacts. This was the case for all three setups. Thus, an interslice protocol can be achieved with a frequency of up to ~10 Hz, using a standard EPI sequence (slice acquisition time: 62.5ms, interslice gap: 40ms). Faster stimulation frequencies would require shorter slice acquisition times, for example using in-plane acceleration. Interslice TMS-fMRI protocols provide a promising avenue for retaining flexible timing of stimulus delivery without incurring TMS artifacts.

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bioRxiv2021

Linking the brain with behaviour: the neural dynamics of success and failure in goal-directed behaviour

The human brain is extremely flexible and capable of rapidly selecting relevant information in accordance with task goals. Regions of frontoparietal cortex flexibly represent relevant task information such as task rules and stimulus features when participants perform tasks successfully, but less is known about how information processing breaks down when participants make mistakes. This is important for understanding whether and when information coding recorded with neuroimaging is directly meaningful for behaviour. Here, we used magnetoencephalography (MEG) to assess the temporal dynamics of information processing, and linked neural responses with goal-directed behaviour by analysing how they changed on behavioural error. Participants performed a difficult stimulus-response task using two stimulus-response mapping rules. We used time-resolved multivariate pattern analysis to characterise the progression of information coding from perceptual information about the stimulus, cue and rule coding, and finally, motor response. Response-aligned analyses revealed a ramping up of perceptual information prior to a correct response, suggestive of internal evidence accumulation. Strikingly, when participants made a stimulus-related error, and not when they made other types of errors, patterns of activity initially reflected the stimulus presented, but later reversed, and accumulated towards a representation of the incorrect stimulus. This suggests that the patterns recorded at later timepoints reflect an internally generated stimulus representation that was used to make the (incorrect) decision. These results illustrate the orderly and overlapping temporal dynamics of information coding in perceptual decision-making and show a clear link between neural patterns in the late stages of processing and behaviour.

neuroscience↗

bioRxiv2021

Neural coding of visual objects rapidly reconfigures to reflect sub-trial shifts in attentional focus

Every day, we respond to the dynamic world around us by flexibly choosing actions to meet our goals. This constant problem solving, in familiar settings and in novel tasks, is a defining feature of human behaviour. Flexible neural populations are thought to support this process by adapting to prioritise task-relevant information, driving coding in specialised brain regions toward stimuli and actions that are important for our goal. Accordingly, human fMRI shows that activity patterns in frontoparietal cortex contain more information about visual features when they are task-relevant. However, if this preferential coding drives momentary focus, for example to solve each part of a task, it must reconfigure more quickly than we can observe with fMRI. Here we used MVPA with MEG to test for rapid reconfiguration of stimulus information when a new feature becomes relevant within a trial. Participants saw two displays on each trial. They attended to the shape of a first target then the colour of a second, or vice versa, and reported the attended features at a choice display. We found evidence of preferential coding for the relevant features in both trial phases, even as participants shifted attention mid-trial, commensurate with fast sub-trial reconfiguration. However, we only found this pattern of results when the task was difficult, and the stimulus displays contained multiple objects, and not in a simpler task with the same structure. The data suggest that adaptive coding in humans can operate on a fast, sub-trial timescale, suitable for supporting periods of momentary focus when complex tasks are broken down into simpler ones, but may not always do so.

neuroscience↗

bioRxiv2021

Undivided attention: The temporal effects of attention dissociated from decision, memory, and expectation

Selective attention prioritises relevant information amongst competing sensory input. Time-resolved electrophysiological studies have shown stronger representation of attended compared to unattended stimuli, which has been interpreted as an effect of attention on information coding. However, because attention is often manipulated by making only the attended stimulus a target to be remembered and/or responded to, many reported attention effects have been confounded with target-related processes such as visual short-term memory or decision-making. In addition, the effects of attention could be influenced by temporal expectation. The aim of this study was to investigate the dynamic effect of attention on visual processing using multivariate pattern analysis of electroencephalography (EEG) data, while 1) controlling for target-related confounds, and 2) directly investigating the influence of temporal expectation. Participants viewed rapid sequences of overlaid oriented grating pairs at fixation while detecting a "target" grating of a particular orientation. We manipulated attention, one grating was attended and the other ignored, and temporal expectation, with stimulus onset timing either predictable or not. We controlled for target-related processing confounds by only analysing non-target trials. Both attended and ignored gratings were initially coded equally in the pattern of responses across EEG sensors. An effect of attention, with preferential coding of the attended stimulus, emerged approximately 230ms after stimulus onset. This attention effect occurred even when controlling for target-related processing confounds, and regardless of stimulus onset predictability. These results provide insight into the effect of attention on the dynamic processing of competing visual information, presented at the same time and location.

neuroscience↗

bioRxiv2021

Selective attention and decision-making have separable neural bases in space and time

Attention and decision-making processes are fundamental to cognition. However, they are usually experimentally confounded, making it difficult to link neural observations to specific processes. Here we separated the effects of selective attention from the effects of decision-making on human brain activity, using a two-stage task where the attended stimulus and decision were orthogonal and separated in time. Multivariate pattern analyses of multimodal neuroimaging data revealed the dynamics of perceptual and decision-related information coding through time (magnetoencephalography (MEG)), space (functional Magnetic Resonance Imaging (fMRI)), and their combination (MEG-fMRI fusion). Our MEG results showed an effect of attention before decision-making could begin, and fMRI results showed an attention effect in early visual and frontoparietal regions. Model-based MEG-fMRI fusion suggested that attention boosted stimulus information in frontoparietal and early visual regions before decision-making was possible. Together, our results suggest that attention affects neural stimulus representations in frontoparietal regions independent of decision-making.

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bioRxiv2020

Word detection in individual subjects is difficult to probe with fast periodic visual stimulation

Measuring cognition in single subjects presents unique challenges. Yet individually sensitive measurements offer extraordinary opportunities, from informing theoretical models to enabling truly individualised clinical assessment. Here, we test the robustness of fast, periodic, visual stimulation (FPVS), an emerging method proposed to elicit detectable responses to written words in the electroencephalogram (EEG) of individual subjects. The method is non-invasive, passive, and requires only a few minutes of testing, making it a potentially powerful tool to test comprehension in those who do not speak or who struggle with long testing procedures. In an initial study, Lochy et al. (2015) used FPVS to detect word processing in 8 out of 10 fluent French readers. Here, we attempted to replicate their study in a new sample of ten fluent English readers. Participants viewed rapid streams of pseudo-words with words embedded at regular intervals, while we recorded their EEG. Based on Lochy et al., we expected that words would elicit a steady-state response at the word-presentation frequency (2 Hz) over parieto-occipital electrode sites. However, across 40 datasets (10 participants, two conditions, and two regions of interest - ROIs), only four datasets met the criteria for a unique response to words. This corresponds to a 10% detection rate. We conclude that FPVS should be developed further before it can serve as an individually-sensitive measure of written word processing.

animal behavior and cognition↗

bioRxiv2020

Perceptual difficulty modulates the direction of information flow in familiar face recognition

Humans are fast and accurate when they recognize familiar faces. Previous neurophysiological studies have shown enhanced representations for the dichotomy of familiar vs. unfamiliar faces. As familiarity is a spectrum, however, any neural correlate should reflect graded representations for more vs. less familiar faces along the spectrum. By systematically varying familiarity across stimuli, we show a neural familiarity spectrum using electroencephalography. We then evaluated the spatiotemporal dynamics of familiar face recognition across the brain. Specifically, we developed a novel informational connectivity method to test whether peri-frontal brain areas contribute to familiar face recognition. Results showed that feed-forward flow dominates for the most familiar faces and top-down flow was only dominant when sensory evidence was insufficient to support face recognition. These results demonstrate that perceptual difficulty and the level of familiarity influence the neural representation of familiar faces and the degree to which peri-frontal neural networks contribute to familiar face recognition.

neuroscience↗

bioRxiv2020

Vigilance decrements in the brain: neural signatures can predict behavioural errors before they happen

There are now many environments in which humans need to monitor moving displays and only rarely act, such as train control and driving autonomous vehicles; lapses of attention in these circumstances can have tragic consequences. Problematically, we know that it is difficult to sustain attention under these monitoring or vigilance conditions and performance drops: when target events are rare, we tend to miss them, or are slower to respond. This rare target effect becomes more marked with longer tasks, known as a vigilance decrement. Despite the importance, we still have limited understanding of how the brain processes information during monitoring, particularly with dynamic stimuli, and how this processing changes when attention lapses. Here, we designed a multiple-object monitoring (MOM) paradigm that required sustained attention to dynamic stimuli, and used multivariate analyses of magnetoencephalography (MEG) data to examine how the neural representation of the information in the display varied with target frequency and time on the task. Behavioural performance decreased over time for the rare target (monitoring) condition, but not for the frequent target (active) condition. This change was mirrored in the neural results: under monitoring conditions, there was weaker coding of the critical distance between objects during time periods when vigilance decrements in performance occurred. There was also weaker informational connectivity between peri-occipital and peri-frontal brain areas in rare versus frequent target conditions. We developed a new analysis which used the strength of information decoding to predict whether the participant was going to miss the target on a given trial. We could predict behavioural errors more than a second before they occurred. This provides a first step in developing methods to predict and pre-empt behavioural errors due to lapses in attention and provides new insight into how vigilance decrements are reflected in information coding in the brain.

neuroscience↗

bioRxiv2020

Concurrent neuroimaging and neurostimulation reveals a causal role for dlPFC in coding of task-relevant information

The way in which the brain prioritises processing of information relevant for our current goals is widely contested. Many studies implicate the dorsolateral prefrontal cortex (dlPFC), and propose that it drives brain-wide focus by biasing processing in favour of relevant information. An alternative, however, is that dlPFC is involved in the inhibition of irrelevant information. Here, we address this longstanding debate using the inferentially powerful approach of applying transcranial magnetic stimulation during functional magnetic resonance imaging (concurrent TMS-fMRI) and testing for changes in information coding using multivariate pattern analysis (MVPA). We ask whether dlPFC plays a causal role in prioritising information processing, and whether this is through selection of relevant information or inhibition of irrelevant information. Participants attended to one object feature whilst ignoring another feature of the same object. We reasoned that, if dlPFC is necessary for selection, active (disruptive) TMS should decrease coding of attended information compared to the low intensity (control) condition. Conversely, if right dlPFC is crucial for inhibition, active TMS should increase coding of irrelevant information relative to the control condition. The results showed that active TMS decreased coding of relevant information throughout the frontoparietal multiple demand regions, and that this impact was significantly stronger than the effect of TMS on irrelevant information coding, which was not statistically detectable. These data provide causal evidence for a specific role of dlPFC in supporting the representation of task-relevant information and demonstrate the crucial insights into high level cognitive-neural mechanisms possible with the combination of TMS-fMRI and MVPA.

neuroscience↗

bioRxiv2019

Finding hidden treasures: a child-friendly neural test of task-following in individuals using functional transcranial Doppler ultrasound

Despite growing interest in the mental life of individuals who cannot communicate verbally, objective and non-invasive tests of covert cognition are still sparse. In this study, we assessed the ability of neurotypical children to understand and follow task instructions by measuring neural responses through functional transcranial Doppler ultrasound (fTCD). We recorded blood flow velocity for the two brain hemispheres of twenty children (aged 9 to 12) while they performed either a language task or a visuospatial memory task, on identical visual stimuli. We extracted measures of neural lateralisation for the two tasks separately to investigate lateralisation, and we compared the left-minus-right pattern of activation across tasks to assess task-following. At the group level, we found that neural responses were left-lateralised when children performed the language task, and not when they performed the visuospatial task. However, with statistically robust analyses and controlled paradigms, significant lateralisation in individual children was less frequent than expected from the literature. Nonetheless, the pattern of hemispheric activation for the two tasks allowed us to confirm task-following in the group of participants, as well as in over half of the individuals. This provides a promising avenue for a covert and inexpensive test of children’s ability to covertly follow task instructions and perform different mental tasks on identical stimuli.Competing Interest StatementThe authors have declared no competing interest.View Full Text

animal behavior and cognition↗

bioRxiv2019

Even neurotypical children are heterogeneous: using multivariate decoding to improve individual subject analysis of lexico-semantic EEG data

In conditions such as minimally-verbal autism, standard assessments of language comprehension are often unreliable. Given the known heterogeneity within the autistic population, it is crucial to design tests of semantic comprehension that are sensitive in individuals. Recent efforts to develop neural signals of language comprehension have focused on the N400, a robust marker of lexical-semantic violation at the group level. However, homogeneity of response in individual neurotypical children has not been established. Here, we presented 20 neurotypical children with congruent and incongruent visual animations and spoken sentences while measuring their neural response using EEG. Despite robust group-level responses, we found high inter-individual variability in response to lexico-semantic anomalies. To overcome this, we analysed our data using temporally and spatially unconstrained MVPA, supplemented by descriptive analyses to examine the timecourse, topography, and strength of the effect. Our results show that neurotypical children exhibit heterogenous responses to lexical-semantic violation, implying that any application to heterogenous disorders such as ASD will require individual-subject analyses that are robust to variation in topology and timecourse of neural responses.Competing Interest StatementThe authors have declared no competing interest.View Full Text

animal behavior and cognition↗

bioRxiv2019

Foveal feedback supports peripheral perception of both object color and form

Evidence from neuroimaging and brain stimulation studies suggest that visual information about objects in the periphery is fed back to foveal retinotopic cortex in a separate representation that is essential for peripheral perception. The characteristics of this phenomenon has important theoretical implications for the role fovea-specific feedback might play in perception. In this work, we employed a recently developed behavioral paradigm to explore whether late disruption to central visual space impaired perception of color. First, participants performed a shape discrimination task on colored novel objects in the periphery while fixating centrally. Consistent with the results from previous work, a visual distractor presented at fixation ~100ms after presentation of the peripheral stimuli impaired sensitivity to differences in peripheral shapes more than a visual distractor presented at other stimulus onset asynchronies. In a second experiment, participants performed a color discrimination task on the same colored objects. In a third experiment, we further tested for the foveal distractor effect with stimuli restricted to a low-level feature by using homogenous color patches. These two latter experiments resulted in a similar pattern of behavior: a central distractor presented at the critical stimulus onset asynchrony impaired sensitivity to peripheral color differences, but, importantly, the magnitude of the effect depended on whether peripheral objects contained complex shape information. These results taken together suggest that feedback to the foveal confluence is a component of visual processing supporting perception of both object form and color.

neuroscience↗

bioRxiv2019

Meaningful patterns of information in the brain revealed through analysis of errors

Great excitement has surrounded our ability to decode task information from human brain activity patterns, reinforcing the dominant view of the brain as an information processor. We tested a fundamental but overlooked assumption: that such decodable information is actually used by the brain to generate cognition and behaviour. Participants performed a challenging stimulus-response task during fMRI. Our novel analyses trained a pattern classifier on data from correct trials, and used it to examine stimulus and rule coding on error trials. There was a striking interaction in which frontoparietal cortex systematically represented incorrect rule but correct stimulus information when participants used the wrong rule, and incorrect stimulus but correct rule information on other types of errors. Visual cortex, by contrast, did not code correct or incorrect information on error. Thus behaviour was tightly linked to coding in frontoparietal cortex and only weakly linked to coding in visual cortex. Human behaviour may indeed result from information-like patterns of activity in the brain, but this relationship is stronger in some brain regions than in others. Testing for information coding on error can help establish which patterns constitute behaviourally-meaningful information.

neuroscience↗

bioRxiv2019

Towards an individualised neural assessment of receptive language in children

PurposeWe aimed to develop a non-invasive neural test of language comprehension to use with non-speaking children for whom standard behavioural testing is unreliable (e.g., minimally-verbal autism). Our aims were three-fold. First, we sought to establish the sensitivity of two auditory paradigms to elicit neural responses in individual neurotypical children. Second, we aimed to validate the use of a portable and accessible electroencephalography (EEG) system, by comparing its recordings to those of a research-grade system. Third, in light of substantial inter-individual variability in individuals neural responses, we assessed whether multivariate decoding methods could improve sensitivity. MethodsWe tested the sensitivity of two child-friendly covert N400 paradigms. Thirty-one typically developing children listened to identical spoken words that were either strongly predicted by the preceding context or violated lexical-semantic expectations. Context was given by a cue word (Experiment 1) or sentence frame (Experiment 2) and participants either made an overall judgement on word relatedness or counted lexical-semantic violations. We measured EEG concurrently from a research-grade system, Neuroscans SynAmps2, and an adapted gaming system, Emotivs EPOC+. ResultsWe found substantial inter-individual variability in the timing and topology of N400-like effects. For both paradigms and EEG systems, traditional N400 effects at the expected sensors and time points were statistically significant in around 50% of individuals. Using multivariate analyses, detection rate increased to 88% of individuals for the research-grade system in the sentences paradigm, illustrating the robustness of this method in the face of inter-individual variations in topography. ConclusionsThere was large inter-individual variability in neural responses, suggesting inter-individual variation in either the cognitive response to lexical-semantic violations, and/or the neural substrate of that response. Around half of our neurotypical participants showed the expected N400 effect at the expected location and time point. A low-cost, accessible EEG system provided comparable data for univariate analysis but was not well suited to multivariate decoding. However, multivariate analyses with a research-grade EEG system increased our detection rate to 88% of individuals. This approach provides a strong foundation to establish a neural index of language comprehension in children with limited communication.

animal behavior and cognition↗

bioRxiv2019

Spatial and feature-selective attention have distinct effects on population-level tuning.

Attention is a fundamental brain process by which we selectively prioritize relevant information in our environment. Cognitively, we can employ different methods for selecting visual information for further processing, but the extent to which these are implemented by similar or different neural processes remains unclear. Spatial and feature-selective attention both change the stimulus related information signaled by single-cells and neural populations, but relatively few studies have directly compared the effects of these distinct types of attention. We scanned participants (n=20) using MEG, while they covertly attended to an object on the left or the right of fixation (spatial attention manipulation) and reported the objects shape or color (feature-selective attention manipulation). We used multivariate pattern classification to measure population stimulus-coding in occipital and frontal areas, for attended and non-attended stimulus features, at attended and non-attended locations. In occipital cortex, we show that both spatial and feature-selective attention enhanced object representations, and the effects of these two attention types interacted multiplicatively. We also found that spatial and feature-selective attention induced qualitatively different patterns of enhancement in occipital cortex for the encoding of stimulus color. Specifically, feature-based attention primarily enhanced small color differences, while spatial attention produced greater enhancement for larger differences. We demonstrate that principles of response-gain and tuning curve sharpening that have been applied to describe the effects of attention at the level of a single neuron can account for these differences. An information flow analysis suggested that these attentional effects may be driven by feedback from frontal areas.

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