Biology subjects

Honey, C. J.

Publications and source records attributed to Honey, C. J..

11 recordsLinked to original sources

bioRxiv2024

Neural dynamics of spontaneous memory recall and future thinking in the continuous flow of thoughts

The human brain constantly recalls past experiences and anticipates future events, generating a continuous flow of thoughts. However, the neural mechanisms underlying the natural transitions and trajectories of thoughts during spontaneous memory recall and future thinking remain underexplored. To address this gap, we conducted a functional magnetic resonance imaging study using a think-aloud paradigm, where participants verbalize their uninterrupted stream of thoughts during rest. We found that transitions between thoughts, particularly those involving significant shifts in semantic content, activate the brains default and control networks. These neural responses to internally generated thought boundaries produce activation patterns resembling those triggered by external event boundaries. Moreover, interactions within and between these networks shape the overall semantic structure of thought trajectories: stronger functional connectivity within the medial temporal subsystem of the default network predicts greater variability in thoughts, while stronger connectivity between the control and core default networks is associated with reduced variability. Together, our findings highlight how the default and control networks guide the dynamic transitions and structure of naturally arising memory and future thinking.

neuroscience↗

bioRxiv2022

On the automaticity of visual statistical learning

Humans can extract regularities from their environment, enabling them to recognize and predict sequences of events. The process of regularity extraction is called statistical learning and is generally thought to occur rapidly and automatically; that is, regularities are extracted from repeated stimulus presentations, without intent or awareness, as long as the stimuli are attended. We hypothesized that visual statistical learning is not entirely automatic, even when stimuli are attended, and that the learning depends on the extent to which viewers process the relationships between stimuli. To test this, we measured statistical learning performance across seven conditions in which participants (N=774) viewed image sequences. As task instructions across conditions increasingly required participants to attend to relationships between stimuli, their learning performance increased from chance to robust levels. We conclude that the learning observed in visual statistical learning paradigms is, for the most part, not automatic and requires more than passively attending to stimuli.

neuroscience↗

bioRxiv2021

Social-affective features drive human representations of observed actions

Humans observe actions performed by others in many different visual and social settings. What features do we extract and attend when we view such complex scenes, and how are they processed in the brain? To answer these questions, we curated two large-scale sets of naturalistic videos of everyday actions and estimated their perceived similarity in two behavioral experiments. We normed and quantified a large range of visual, action-related and social-affective features across the stimulus sets. Using a cross-validated variance partitioning analysis, we found that social-affective features predicted similarity judgments better than, and independently of, visual and action features in both behavioral experiments. Next, we conducted an electroencephalography (EEG) experiment, which revealed a sustained correlation between neural responses to videos and their behavioral similarity. Visual, action, and social-affective features predicted neural patterns at early, intermediate and late stages respectively during this behaviorally relevant time window. Together, these findings show that social-affective features are important for perceiving naturalistic actions, and are extracted at the final stage of a temporal gradient in the brain.

neuroscience↗

bioRxiv2021

The Similarity Structure of Real-World Memories

How do we mentally organize our memories of life events? Two episodes may be connected because they share a similar location, time period, activity, spatial environment, or social and emotional content. However, we lack an understanding of how each of these dimensions contributes to the perceived similarity of two life memories. We addressed this question with a data-driven approach, eliciting pairs of real-life memories from participants. Participants annotated the social, purposive, spatial, temporal, and emotional characteristics of their memories. We found that the overall similarity of memories was influenced by all of these factors, but to very different extents. Emotional features were the most consistent single predictor of overall memory similarity. Memories with different emotional tone were reliably perceived to be dissimilar, even when they occurred at similar times and places and involved similar people; conversely, memories with a shared emotional tone were perceived as similar even when they occurred at different times and places, and involved different people. A predictive model explained over half of the variance in memory similarity, using only information about (i) the emotional properties of events and (ii) the primary action or purpose of events. Emotional features may make an outsized contribution to event similarity because they provide compact summaries of an events goals and self-related outcomes, which are critical information for future planning and decision making. Thus, in order to understand and improve real-world memory function, we must account for the strong influence of emotional and purposive information on memory organization and memory search. SignificanceOur brains enable us to understand and act within the present, informed by previous, related life experience. But how are our life experiences organized so that one event can be related to another? Theories have suggested that we use spatiotemporal, social, causal, purposive, and emotional dimensions to inter-relate our memories; however, these organizing principles are usually studied using impersonal laboratory stimuli. Here, we mapped and modeled the connections between peoples own annotated life memories. We found that life events are linked by a variety of factors, but are predominantly connected in memory by their primary activity and emotional character. This highlights a need for theories of memory organization and retrieval to better account for the role of high-level actions and emotions.

animal behavior and cognition↗

bioRxiv2020

Narratives: fMRI data for evaluating models of naturalistic language comprehension

The "Narratives" collection aggregates a variety of functional MRI datasets collected while human subjects listened to naturalistic spoken stories. The current release includes 345 subjects, 891 functional scans, and 27 diverse stories of varying duration totaling ~4.6 hours of unique stimuli (~43,000 words). This data collection is well-suited for naturalistic neuroimaging analysis, and is intended to serve as a benchmark for models of language and narrative comprehension. We provide standardized MRI data accompanied by rich metadata, preprocessed versions of the data ready for immediate use, and the spoken story stimuli with time-stamped phoneme- and word-level transcripts. All code and data are publicly available with full provenance in keeping with current best practices in transparent and reproducible neuroimaging.

neuroscience↗

bioRxiv2019

Constructing and Forgetting Temporal Context in the Human Cerebral Cortex

How does information from seconds earlier affect neocortical responses to new input? Here, we used empirical measurements and computational modeling to study the integration and forgetting of prior information. We found that when two groups of participants heard the same sentence in a narrative, preceded by different contexts, the neural responses of each group were initially different, but gradually fell into alignment. We observed a hierarchical gradient: sensory cortices aligned most quickly, followed by mid-level regions, while higher-order cortical regions aligned last. In some higher order regions, responses to the same sentence took more than 10 seconds to align. What kinds of computations can explain this hierarchical organization of contextual alignment? Passive linear integration models predict that regions which are slower to integrate new information should also be slower to forget old information. However, we found that higher order regions could rapidly forget prior context. The data were better captured by a model composed of hierarchical autoencoders in time (HAT). In HAT, cortical regions maintain a temporal context representation which is actively integrated with input at each moment, and this integration is gated by prediction error. These data and models suggest that sequences of information are combined throughout the cortical hierarchy using an active and gated integration process.

neuroscience↗

bioRxiv2019

Temporal integration of narrative information in a hippocampal amnesic patient

Default network regions appear to integrate information over time windows of 30 seconds or more during narrative listening. Does this long-timescale capability require the hippocampus? Amnesic behavior suggests that the hippocampus may not be needed for online processing when input is continuous and semantically rich: amnesics can participate in conversations and tell stories spanning minutes, and when tested immediately on recently heard prose their performance is relatively preserved. We hypothesized that default network regions can integrate the semantically coherent information of a narrative across long time windows, even in the absence of the hippocampus. To test this prediction, we measured BOLD activity in the brain of a hippocampal amnesic patient (D. A.) and healthy control participants while they listened to a seven-minute narrative. The narrative was played either in its intact form, or as a paragraph-scrambled version, which has been previously shown to interfere with the long-range temporal dependencies in default network activity. In the intact story condition, D. A.s moment-by-moment BOLD activity spatial patterns were similar to those of controls in low-level auditory cortex as well as in some high-level default network regions (including lateral and medial posterior parietal cortex). Moreover, as in controls, D. A.s response patterns in medial and lateral posterior parietal cortex were disrupted when paragraphs of the story were presented in a shuffled order, suggesting that activity in these areas did depend on information from 30 seconds or more in the past. Together, these results suggest that some default network cortical areas can integrate information across long timescales, even in the absence of the hippocampus.

neuroscience↗

bioRxiv2018

Transformation of Speech Sequences in Human Sensorimotor Circuits

After we listen to a series of words, we can silently replay them in our mind. Does this mental replay involve a re-activation of our original perceptual representations? We recorded electrocorticographic (ECoG) activity across the lateral cerebral cortex as people heard and then mentally rehearsed spoken sentences. For each region, we tested whether silent rehearsal of sentences involved reactivation of sentence-specific representations established during perception or transformation to a distinct representation. In sensorimotor and premotor cortex, we observed reliable and temporally precise responses to speech; these patterns transformed to distinct sentence-specific representations during mental rehearsal. In contrast, we observed slower and less reliable responses in prefrontal and temporoparietal cortex; these higher-order representations, which were sensitive to sentence semantics, were shared across perception and rehearsal. The mental rehearsal of natural speech involves the transformation of time-resolved speech representations in sensorimotor and premotor cortex, combined with diffuse reactivation of higher-order semantic representations.\n\nConflict of interestThe authors declare no competing financial interests.

neuroscience↗

bioRxiv2018

Electrocorticographic responses to time-compressed speech vary across the cortical auditory hierarchy

Human listeners understand spoken language across a variety of rates, but when speech is presented three times or more faster than its usual rate, it becomes unintelligible. How the brain achieves such tolerance and why speech becomes unintelligible above certain rates is still unclear. We addressed these questions using electrocorticography (ECoG) recordings in 7 epileptic patients (two female). Patients rated the intelligibility of sentences presented at the original rate (100%), speeded rates (33% or 66% of the original sentence duration) and a slowed rate (150%). We then examined which parameters of the neural response covary with the transition from intelligible to unintelligible speech. Specifically, we asked whether neural responses: 1) track the acoustic envelope of the incoming speech; 2) \"scale\" with speech rate, i.e. whether neural responses elicited by slowed and speeded sentences can be linearly scaled to match the responses to the original sentence. Behaviorally, intelligibility was at ceiling for speech rates of 66% and above, but dropped significantly for the 33% rate. At the neural level, Superior Temporal Gyrus regions (STG) in close proximity to A1 ( low-level) tracked the acoustic envelope and linearly scaled with the input across all speech rates, irrespective of intelligibility. In contrast, secondary auditory areas in the STG as well as the inferior frontal gyrus and angular gyrus ( high-level) tracked the acoustic envelope and linearly scaled with input only for intelligible speech. These results help reconcile seemingly contradictory previous findings and provide better understanding of how information processing unfolds along the cortical auditory hierarchy.

neuroscience↗

bioRxiv2017

Elucidating relations between fMRI, ECoG and EEG through a common natural stimulus

Human brain mapping relies heavily on fMRI, ECoG and EEG, which capture different physiological signals. Relationships between these signals have been established in the context of specific tasks or during resting state, often using spatially confined concurrent recordings in animals. But it is not certain whether these correlations generalize to other contexts relevant for human cognitive neuroscience. Here, we address the case of complex naturalistic stimuli and ask two basic questions. First, how reliable are the responses evoked by a naturalistic audio-visual stimulus in each of these imaging methods, and second, how similar are stimulus-related responses across methods? To this end, we investigated a wide range of brain regions and frequency bands. We presented the same movie clip twice to three different cohorts of subjects (NEEG = 45, NfMRI = 11, NECoG = 5) and assessed stimulus-driven correlations across viewings and between imaging methods, thereby ruling out task-irrelevant confounds. All three imaging methods had similar repeat-reliability across viewings when fMRI and EEG data were averaged across subjects, highlighting the potential to achieve large signal-to-noise ratio by leveraging large sample sizes. The fMRI signal correlated positively with high-frequency ECoG power across multiple task-related cortical structures but positively with low-frequency EEG and ECoG power. In contrast to previous studies, these correlations were as strong for low-frequency as for high frequency ECoG. We also observed links between fMRI and infra-slow EEG voltage fluctuations. These results extend previous findings to the case of natural stimulus processing.

neuroscience↗

bioRxiv2017

Serial dependence transfers between perceptual objects

Judgments of the present visual world are affected by what came before. When judgments of visual properties such as orientation are biased in the direction of preceding stimuli, this is called visual serial dependence. Visual serial dependence is thought to arise from mechanisms that support perceptual continuity: because physical properties of an object usually vary smoothly in time, perception might be accurately stabilized by smoothing the perceived features in time. However, mechanisms that support perceptual continuity should be object-specific, because the orientation of one object is more related to its own past than to the past of a distinct object. Thus, we tested the perceptual continuity explanation by comparing the magnitude of serial dependence between objects and within objects. Across three experiments, we manipulated objecthood by varying the color, the location, and both the color and the location of Gabor patches. We observed a serial dependence effect in every experiment but did not observe an effect of objecthood in any experiment. We further observed serial dependence even when the orientations of two successive stimuli were nearly orthogonal. These data are inconsistent with explanations of serial dependence based on visual continuity. We hypothesize that serial dependence arises from a combination of perceptual features and internal response variables, which interact within a common task or decisional context.

neuroscience↗