Journal of Cognitive Neuroscience

Many cognitive processes depend on integrating information as it becomes available to construct meaningful interpretations. Prior work has shown graded and incremental context effects, especially in language, but it remains less clear whether contextual integration exhibits a comparable temporal profile across symbolic domains when structured input is examined within congruent sequences. Twenty-seven participants processed congruent four-element sequences designed to be structurally comparable across lexical, algebraic, and graphical domains while event-related potentials were recorded. In the 250-500 ms interval, mean amplitudes increased systematically with sequence position within a predefined centro-parietal region of interest (p < .001). The Domain x Position interaction did not reach significance (p = .056), although modest domain-related differences in the buildup profile cannot be ruled out. A follow-up analysis showed that the increase to the response-relevant final position was larger than earlier increases (p < .001). Additional analyses indicated maximal amplitudes over parietal sites and the clearest graded increase over central sites. These findings indicate that context-sensitive activity was progressive but not uniform across sequence positions, with the strongest increase occurring when the sequence reached its final, response-relevant completion point. The presence of position-related increases across lexical, algebraic, and graphical domains is consistent with the view that centro-parietal ERP activity in the 250-500 ms window tracks the progressive buildup of contextual integration during structured sequence processing. HighlightsO_LIContext-sensitive ERP activity increased across sequence position. C_LIO_LIThe strongest increase occurred at the final completion point. C_LIO_LIMaximal amplitudes were observed over parietal electrodes. C_LIO_LICentral sites best captured graded position-related modulation. C_LIO_LIPosition-related buildup was observed across symbolic domains. C_LI

Prevailing models propose that sustained focus is a product of top-down control that amplifies task-relevant representations while suppressing distraction. We challenge this view, demonstrating that the neural signatures of mental focus differ across cognitive modes. In two neuroimaging studies, we used a paradigm that creates conflict between external task goals and self-generated thought, to identify the neural correlates of task focus in contexts varying in memory engagement. In Study 1, arithmetic and comprehension tasks were associated with distinct neural architectures of task focus: arithmetic-related focus recruited visual-motor regions, while comprehension-related focus was characterized by the recruitment of memory systems and reduced activation of control regions. Study 2 extended these findings, with both externally directed comprehension and internal memory retrieval associated with a shared neural profile of reduced control engagement, despite reliance on distinct memory systems. Furthermore, focus covaried with activity in heteromodal semantic regions across both reading and listening, suggesting semantic engagement is a primary marker of being on task during comprehension. Our findings indicate that sustained focus during memory-guided cognition is characterized by mutual disengagement between control and memory networks. This discovery motivates a departure from traditional executive-control accounts, since task focus in meaningful contexts is associated with the recruitment of representational structures in long-term memory rather than active top-down supervision. Significance StatementDoes concentration always require effort? While traditional models suggest that sustained focus is a product of top-down executive supervision, we show that the brain employs fundamentally different architectures for focus depending on the cognitive mode. In two neuroimaging studies, focus was associated with distinct neural profiles - reduced engagement of memory systems in arithmetic, and control deactivation alongside the activation of distinct memory systems in comprehension and autobiographical recall. Heteromodal semantic regions were associated with focus during reading and listening, consistent with an association between semantic network engagement and task focus during comprehension. These findings indicate that sustained attention occurs across multiple neural configurations linked to different cognitive modes, challenging the view that top-down supervision is a universal requirement.

Past work has indicated that expectation can modulate neural responses to visual stimuli, but it is unclear whether these effects remain consistent across different types of unexpected stimuli. Here, we measured and compared neural prediction effects associated with semantic category and presentation frequency-based expectations in real-world object stimuli. Participants (n = 35) viewed real-world object images in rapid serial visual presentation (RSVP) streams. Semantically unexpected stimuli occurred when a stimulus was presented in a semantically incongruent stream. Low-frequency violations occurred when a rarely presented stimulus was displayed in a semantically congruent stream. Multivariate pattern analysis of electroencephalography (EEG) was used to quantify and compare the degree of information represented in neural activity for stimuli in different prediction conditions. Semantically expected stimuli yielded lower decoding accuracy relative to random (unpredictable) stimuli (125-313 ms post-onset) while semantically unexpected stimuli exhibited increased decoding accuracy (199-238 ms & 523-559 ms). Low-frequency violations yielded decoding accuracy which was not significantly different from semantically expected stimuli. Exploratory analyses indicated that dissimilarity between expected and presented stimuli quantified in terms of higher-level stimulus features, but not low-level visual features, modulated the observed neural prediction effects. These results demonstrate that different types of prediction violations have distinct modulatory effects on neural responses, providing novel insight into the neural implementation of predictive processing.

How the brain constructs meaning across extended contexts remains poorly understood. While neural responses to words and sentences are well characterized, much less is known about the brain mechanisms supporting narrative comprehension. Sentence-level studies suggest that neural activation increases as word meanings are integrated into sentence meaning. At the discourse level, theories propose that narratives depend on situation models, possibly engaging networks beyond core language regions, including the default mode network. Because narrative comprehension unfolds over longer timescales, processing time may be a bottleneck. In this MEG study, we tested how representation size and presentation rate shape neural responses by varying linguistic structure (words, sentences, stories) and the speed of visual text in 1-4-word chunks. We found an early bilateral story effect in visual cortex, followed by a spatiotemporal progression of activity along the temporal lobes that culminated in a three-way contrast among word lists, sentence lists, and stories. Faster presentation altered this pattern: the left-lateralized story effect disappeared, and the right-lateralized effect became more spatially restricted. Under Fast presentation, significant effects were limited to left lateral language cortex distinguishing coherent inputs from word lists, and to two right-hemisphere story effects in extended language regions. We also observed a context effect in the Slow Story condition, with neural responses remaining constant as the narrative unfolded while they increased in the SentenceList and WordList conditions. This effect was absent under Fast presentation, suggesting story-specific comprehension that is temporally constrained. Together, the findings identify temporal constraints as a key determinant of the neural signatures of narrative processing.

Given the limited capacity of working memory (WM), prioritization is essential for efficient information processing. Whether prioritization acts primarily at encoding, or dynamically shapes representations during maintenance, is currently unclear. Here, we employed a two-item delayed-match-to-sample task and compared prioritization conditions in which the testing order of items was either known in advance or not. Behaviorally, prioritization selectively reduced guess rates, without affecting precision. Using multivariate pattern analysis, we decoded stimulus information from EEG voltage and indexed internal attention using alpha-band patterns. Prioritization did not alter decodable representations during encoding. During maintenance, however, prioritization enhanced both voltage-based decodability and alpha power-based decodability for the currently prioritized item. Mediation analyses further indicated that alpha-based attentional signals influenced behavior indirectly, via voltage-based representational strength, which is consistent with the idea that internal attention supports performance by strengthening prioritized representations during memory maintenance. Significance StatementWM is capacity-limited, requiring the prioritization of information most relevant to current task demands. Whether prioritization is established at encoding or emerges during maintenance, and how it improves working memory performance, remains unclear. Comparing conditions with and without advance priority knowledge, we found that prioritization occurred primarily during maintenance rather than encoding. We also found that prioritization improved performance by directing internal attention to prioritized items, strengthening their neural representations and increasing their accessibility. This finding provides insight into the flexibility of working memory in the updating of already-encoded information.

Salient distractors capture attention, but whether momentary cortical state modulates capture -- and whether this depends on attentional filtering routines -- remains unclear. Using fMRI during visual search in human participants (N = 34), we examined how pre-stimulus global signal (GS) interacts with dimension-specific capture and location-based suppression learning. Same-dimension distractors activated frontoparietal regions (FEF, IPS/SPL, SMA) and produced robust capture, whereas different-dimension distractors produced little behavioral or neural capture, consistent with dimension-selective gating. Pre-stimulus GS negatively modulated capture-related brain activation. Behaviorally, however, GS effects diverged by learning history: GS predicted slower responses in participants who learned location-based suppression for same-dimension distractors (SS group), but faster responses in participants whose spatial learning involved different-dimension distractors (DS group). Thus, the state indexed by GS did not have uniform behavioral consequences. Instead, the findings suggest that the impact of cortical state depends on the control demands and the filtering routine engaged, consistent with broader views that arousal-related effects on performance vary with processing mode and task utility.

Attention is a coherent state, in which multiple brain regions converge to represent selected features of a focal object or event. Lateral prefrontal cortex (LPFC), with its flexible coding of multiple task features and their conjunctions, is widely believed to play a key role in this process. While much research has investigated biased competition between features within a brain region, and cofluctuations of activity between regions, less is known about the representational dynamics through which a coherent neural state emerges. Here, we examine directed mutual information concerning multiple feature-specific population codes, between dorsal and ventral LPFC, across three phases of an attentional selection task. We find bidirectional convergence of information regarding multiple task features, but specifically following the period of selection from the visual display. The results show that neural processes driving inter-region coherence are especially salient during a period of cued object selection, despite comparable local information representation during other task phases. Significance statementIn the primate brain, lateral prefrontal cortex (LPFC) is thought to play a key role in selective attention, which is fundamental to goal-directed behaviour, and implies inter-region convergence towards a coherent neural state. Combining electrophysiological recordings, multivariate decoding, and analysis of information dynamics, we find population representations of multiple task features during multiple task phases, in both dorsal and ventral regions of LPFC, with inter-region representational coherence triggered by attentional selection. Results show that information convergence between these regions is bidirectional, sustained, and reflects multiple features of a chosen object, but, unlike local information representation, is highly specific to the choice phase of the task.

The natural environment is spatiotemporally structured, and the brain exploits this regularity to predict and prepare for upcoming sensory stimuli. Such predictive processing is thought to increase neural efficiency by reducing metabolic expenditure and altering the fidelity with which newly encountered stimuli are encoded. Competing theoretical frameworks propose this is achieved either through sharpening, whereby expected events are encoded more precisely, or dampening, whereby expected events are suppressed and encoded less precisely. Despite clear, opposing predictions, evidence in humans for each account remains mixed due to methodological and analytical inconsistencies. Here we addressed these issues using probabilistic visual paradigm combined with functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). We used population receptive field (pRF) mapping of fMRI data and inverted encoding of EEG data to compare the fidelity and timecourse of activity in visual areas in response to expected, unexpected, and random stimuli. Both methods produced a consistent pattern of results. Post hoc analysis of EEG data revealed that the apparent effect of expectancy was better explained by local spatiotemporal stimulus properties than the global expectancy manipulation. Although this pattern resembled sensory adaptation, it was more consistent with an expectation of temporal stability combined with dampening, in which both the aggregate response to expected features and their representational fidelity are suppressed. Taken together, our findings suggest that predictive processing may operate through dampening, with ecological advantages for high-fidelity encoding of unexpected sensory events.

Across contemplative traditions, deeper states of meditation are described as states of heightened clarity, vividness, and stillness of mind, yet what this clarity corresponds to in the brain has remained difficult to specify. The functional signal-to-noise ratio (f-SNR) framework frames mental clarity as a measurable property of neural signals: the degree to which brain activity tracks the causes of sensory signals rather than endogenous, irrelevant fluctuations. It predicts that deepening meditation should raise f-SNR, expressing sensory events more faithfully in neural signals against ongoing background activity. We tested this prediction across different levels of meditative depth. Twenty-nine experienced Vipassana practitioners meditated while auditory tones were presented, periodically reporting their depth of meditation. f-SNR was quantified from event-related potentials (ERPs) in a fronto-central P3 window and from single-trial decodability of auditory tone-evoked activity against no-tone background EEG. High-depth states were associated with greater ERP signal-to-noise ratio, stronger single-trial signal consistency, and improved decodability of auditory tones. These results suggest that meditative depth is expressed in the reproducibility and stimulus-background separability of sensory responses, consistent with deep meditation enhancing the brain's functional signal-to-noise ratio by improving the clarity of sensory signals and reducing endogenous noise.

Sentence comprehension requires the incremental construction of syntactic structure and semantic interpretation. Prior neural work (Nelson et al., 2017) identified key neural events at major phrase boundaries during sentence comprehension. To investigate a behavioral correlation of these processes, we used self-paced reading to examine the impact of syntactic phase boundaries, semantic congruence, and sentence structure on sentence processing. Participants read object-relative, subject-relative, and canonical control sentences one word at a time and a subsequent comprehension task. Reading times were analyzed relative to phrase boundaries, node-closing operations, and semantic congruence. Object-relative sentences produced the greatest processing difficulty, demonstrated by increased reading times and decreased comprehension accuracy. Reading times peaked at the phrase boundaries, indicating that processing costs are tied to constituent completion rather than individual lexical categories. Reading times also increased with the number of syntactic constituents completed at a phrase boundary. Agent-patient semantic congruence produced its largest effects in object-relative sentences, suggesting that semantic information interacts with syntactic computations when processing demands are greatest. These findings demonstrate that self-paced reading is sensitive to the incremental processing associated with syntactic constituent completion. Processing costs are tied more closely to phrase completion than to individual lexical categories, scale with the amount of syntactic structure completed at a boundary and interact with agent-patient semantic interpretation during object-relative sentence comprehension. Together, these findings support a view of sentence comprehension in which syntactic structure building and semantic interpretation proceed incrementally and interact continuously throughout online language processing.

The binding of perception and action features into common representations, so-called event files, is a core mechanism supporting goal-directed behavior. Recent work using electroencephalography has presented correlational evidence linking the maintenance of perception-action representations to oscillatory activity in the {beta}-frequency range. Here, we used transcranial alternating current stimulation (tACS) to test whether {beta}-oscillations play a causal role in event-file maintenance. Participants performed a distractor-response binding task with a sequential prime-probe structure while receiving either active {beta}-tACS over the left occipito-parietal cortex or a novel shunt stimulation designed to produce comparable sensory effects but substantially weaker cortical stimulation. Prime-probe intervals were varied to manipulate event-file maintenance. {beta}-tACS did not modulate behavioral binding effects during stimulation. However, we observed a significant aftereffect on behavioral distractor-response binding after stimulation. This effect was restricted to short prime-probe intervals, where event files are typically still available, and was absent at longer intervals, where event files commonly decay. These findings provide causal evidence that {beta}-oscillations contribute to the stabilization of perception-action representations over time. More broadly, they support the view that {beta}-oscillations help maintain the current cognitive-motor state and preserve the status-quo in action control.

Human long-term memory for visual scenes is remarkably robust, yet the neural mechanisms supporting memory encoding and retrieval remain poorly understood when both processes must operate at the same time. For instance, this might happen when we encounter a familiar place while simultaneously forming new memories of this encounter. We investigated electrophysiological correlates of visual recognition memory using a continuous recognition task (CRT), in which participants judged a continuous stream of scene photographs as previously seen or new, such that encoding and retrieval occurred in parallel on every trial. To make recognition particularly demanding, stimuli were drawn from only four scene categories. Thirty-one participants performed the task while EEG was recorded, and we analyzed canonical ERP markers of retrieval (mid-frontal FN400, 300-550 ms; late parietal effect, LPE, 550-800 ms) and encoding (subsequent memory effect, SME) as a function of stimulus repetition and lag between consecutive presentations. FN400 showed robust old/new effects for both repetitions, whereas LPE differences emerged only at the second repetition. While FN400 amplitude was insensitive to lag, LPE amplitude decreased systematically with increasing lag, mirroring the behavioral pattern of declining accuracy and slower responses. A significant SME emerged selectively for images subsequently recognized on both repetitions, indicating that the SME in continuous recognition is specific for the most robustly encoded items and reflects the strength of encoding. Together, these findings show that canonical ERP markers of recognition memory are preserved even when encoding and retrieval operate concurrently, but their expression depends on how often and how recently an item has previously been encoded - parameters that can be flexibly manipulated within the CRT. This demonstrates that the CRT is sensitive to fine-grained temporal dynamics of memory formation and retrieval that could be missed under standard single-repetition designs.

The perception of timing has been investigated across short and long timescales, with the latter usually underrepresented. Previous accounts of supra-second timing have often emphasised dedicated neural signals, yet whether timing performance over longer durations reflects specialised temporal mechanisms or domain-general neural excitability remains unclear. We examined this question in an interval reproduction task (2 to 4 s) using EEG, decomposing neural activity into oscillatory (alpha, theta) and aperiodic components and relating both to behavioural performance. At the neural level, separate analyses were performed on the interval encoding epoch and the following delay period. Time-resolved analyses revealed a coordinated decrease in posterior alpha power and aperiodic offset during interval encoding. In contrast, interval duration did not produce consistent modulation of oscillatory or aperiodic activity during the delay period, providing limited support for a workload-based account of time duration. Across participants, higher baseline alpha power and aperiodic offset were associated with better timing accuracy, whereas trial-by-trial fluctuations in aperiodic activity, and to a lesser extent alpha power, predicted single-trial reproductions. The results suggest that temporal behaviour in the supra-second range is shaped by domain-general neural activity sustaining goal-directed task engagement, with oscillatory and aperiodic dynamics serving as complementary indices of this broader excitability state.

Previous research on the brain correlates of working memory using functional magnetic resonance imaging (fMRI) and multivariate pattern analysis (MVPA) have shown that neural activity related to information currently needed to respond on a test is considered to be in the focus of attention (FoA). An ongoing controversy pertains to the neural representation of information in working memory that is not needed for the upcoming test but possibly for a subsequent one, which is considered to reside in an activated portion of long-term memory (aLTM). The key theoretical issue regarding aLTM is whether it corresponds solely to an activity-silent neural state. Here, by using a retrospective cuing task in which two arrays of stimuli from different categories were presented in succession on the same trial, and a pattern classifier trained on the first-presented category during the presentation of the second, we provide evidence that aLTM is associated with an active neural state. Specifically, the aLTM effect was demonstrated to be dissociable in direction from that related to the FoA, there was considerable overlap between brain regions representing information in a stronger form in the FoA and a weaker form in aLTM, and the two states appeared to be differentially subject to flexible cognitive control versus natural decay.

Pupil diameter is widely used as an index of arousal and brain state, yet it remains unclear whether slow pupil-linked state fluctuations systematically modulate the effective capacity of temporal attention. Here, we tested this question using an auditory attentional blink paradigm, in which participants were required to detect the first (T1) and second (T2) targets. In Experiment 1, trial-by-trial analyses revealed that successful T2 detection, given correct T1 detection (T2|T1), was associated with smaller baseline pupil size. Furthermore, analyses focusing on slow pupil fluctuations (< 0.2 Hz) revealed that the T2|T1 detection accuracy increased during the pupil dilation phase occurring 0-2 seconds after pupil constriction. In Experiment 2, we used real-time pupillometry to trigger stimulus presentation during predefined phases of ongoing slow pupil dynamics. This closed-loop manipulation produced reliable phase-dependent differences in T2|T1 detection accuracy. Critically, the effect of pupil phase remained significant in a linear mixed-effects model that included baseline pupil size as a covariate, indicating that it cannot be explained by baseline pupil size alone. Together, these findings demonstrate that temporal attentional capacity is shaped not only by arousal level but also by the phase of slow pupil-linked brain-state fluctuations. Our results suggest that the attentional blink reflects a dynamically regulated, state-dependent limitation rather than a fixed processing bottleneck.

The sensory content and temporal structure of stimuli have been shown to consistently bias duration perception. Temporal intervals filled with continuous sensory input ("filled intervals"), are often perceived as lasting longer than intervals marked only by their onset and offset ("empty intervals"). Despite this robust behavioral finding, it remains unclear whether filled and empty intervals rely on similar or distinct neural mechanisms and, more generally, how sensory format shapes the neural processing of millisecond time. To address this question, we asked twenty-one healthy participants to reproduce visual durations across different stimulus configurations while high-density scalp EEG was recorded. Behavioral results revealed differences in performance across stimulus configurations. Event-related potentials (ERPs) recorded at occipito-parietal and fronto-central electrodes between 0.1 and 0.4 s after duration offset were modulated in amplitude by both stimulus duration and format. These modulations scaled with the sensory load of the stimulus and its duration, suggesting a common underlying mechanism. A Representational Similarity Analysis (RSA) of the ERP data showed that perceived time was represented more strongly than physical time particularly at occipito-parietal electrodes, but only within the 0.2-0.3 s post-offset window, where stimulus format exerted a pronounced effect on the ERP signal. These findings highlight the role of sensory processing in shaping duration perception and its neural coding, and reveal an early neural signature of perceived time in occipito-parietal electrodes. 1 Significance statementOur perception of subsecond durations is distorted by the sensory content of stimuli. Here, we investigated how stimulus configuration shapes the neural correlates of visual duration perception. Specifically, we asked whether temporal intervals filled with continuous sensory input are processed differently from those lacking such content. We found that, between 0.2 and 0.3 s after interval offset, ERP amplitudes were modulated by stimulus content, and in this same temporal window the EEG signal reflected the perceptual bias. These findings support the view that duration processing and perception are deeply rooted in sensory processing.

Eye blinks are among the largest physiological artefacts in electroencephalography and are typically removed from neural recordings. Yet their timing may carry information about cognition. Here, we asked whether the temporal distribution of spontaneous blinks across trials provides a time-resolved behavioural signature of internal attentional focusing in working memory. In Experiment 1, blink-locked EEG analyses showed that blink timing was aligned with neural activity reflecting attentional focusing on a relevant internal representation. In Experiment 2, participants remembered the same visual information across conditions, but the relevant item was revealed either early, by a cue before report, or later, at report. Blink-frequency profiles shifted accordingly, increasing after the cue when selection was possible early and after the probe when selection was delayed. Post-cue blinks in the early-selection condition were also associated with better memory performance. Thus, more generally, spontaneous blinks provide an unobtrusive chronometric signal for tracking latent cognitive processing.

Working memory unfolds over time, yet how different working memory operations are temporally coordinated remains unclear. Building on prior links between low-frequency neural oscillations and working memory maintenance and retrieval, as well as evidence that low-frequency oscillations help coordinate cognitive functions, we tested whether low-frequency neural oscillations bridge and/or differentiate distinct working memory operations. Specifically, we tested whether low-frequency phase was linked to memory accuracy and event-related neural responses across three operations: (i) encoding, (ii) retrieval, and (iii) distractor processing during maintenance. Using EEG in human participants, we found that encoding and retrieval were most strongly linked to memory accuracy through theta phase ([~]4-7 Hz), measured just prior to each task event. Pre-encoding theta phase also modulated the neural response to memory item onset, suggesting that theta phase influences encoding strength. Critically, the theta phase associated with better memory accuracy differed significantly between encoding and retrieval, consistent with temporally distinct and functionally specific states supporting each working memory operation. In contrast, the influence of distractors on memory accuracy was linked to alpha phase ([~]8-10 Hz), with distractor occurrence also appearing to re-engage theta-dependent processes associated with encoding and retrieval. Together, these findings suggest that low-frequency neural oscillations provide a temporal framework that bridges multiple operations of working memory. SignificanceWorking memory (WM) relies on multiple operations that must be coordinated over time, yet how these processes are temporally organized remains unclear. Neural oscillations have been proposed as a timing mechanism for cognition, yet evidence linking distinct oscillatory phases to distinct WM operations remains limited. Here, we show that memory accuracy depends on the phase of low-frequency neural activity, with encoding and retrieval linked to opposing theta phases ([~]4-7 Hz), and distractor interference during maintenance linked to alpha phase ([~]8-10 Hz). These findings indicate that distinct WM operations are temporally coordinated within oscillatory cycles, providing evidence that low-frequency neural activity both coordinates and segregates cognitive processes over time.

Inhibition of return (IOR) refers to the slowing of response times (RTs) for stimuli presented at previously inspected locations relative to novel locations. However, the exact processing stage(s) at which IOR occurs, and its nature across different response modalities, remain debated. By reanalyzing RT data from a target-target IOR paradigm with a single noisy accumulator model, we tested whether IOR could occur at sensory or attentional stages of processing, or at later stages of decision and action selection. We considered IOR under two conditions: manual and saccadic responses. The within-trial Gaussian noise parameter best explained both manual and saccadic IOR, suggesting that in both modalities, IOR may result from a more fluctuating accumulation of evidence for repeated locations. These results support the hypothesis that target-target IOR may primarily involve attentional-level mechanisms. Significance statementWe respond more slowly to a stimulus that is presented within a short interval in the same location ("inhibition of return"), a bias thought to promote efficient visual exploration. Using evidence-accumulation modeling of manual and eye-movement reaction times from two previous studies, we found that the key change linked to inhibition of return is greater within-trial variability (noise) in evidence accumulation, not a higher decision threshold. Understanding which processing stage is affected can help connect behavioral effects to the brain networks that support attention and orienting.

Regions within ventral occipito-temporal cortex exhibit category-selective BOLD responses during episodic encoding and retrieval of visual information. How these regions interact with other brain areas during successful encoding and retrieval, and whether these interactions relate to memory performance, remains unclear. The present study examined category-selective functional connectivity using psychophysiological interaction (PPI) analyses in younger and older adults during the encoding and retrieval of word-image associations. Seed regions comprised three scene-selective regions - the parahippocampal place area, medial place area, and occipital place area - and one object-selective region, the lateral occipital complex (LOC). During encoding, scene-selective regions exhibited greater connectivity with posterior occipital and occipitotemporal regions during scene relative to object encoding, whereas the LOC exhibited less extensive connectivity with similar posterior regions during object encoding. During retrieval, both scene- and object-selective regions demonstrated increased connectivity with left lateral prefrontal and parietal cortices during the retrieval of their preferred category. Age differences in scene-selective connectivity were evident at both phases. Moreover, associations between source memory performance and scene-selective connectivity were significant only in younger adults. These findings suggest that scene- and object-selective regions exhibit convergent patterns of functional connectivity during encoding and retrieval which, for scenes, vary with age.