Visual Imagery of Familiar Faces and Places in the Category-Selective Cortex

Begin with a concrete protocol: instruct participants to vividly image a familiar face and a familiar place in alternating 8-second blocks, then compare FFA and PPA activation. Use a gamme of stimuli and pairs to capture category-selective responses in the right hemisphere, and mark block onsets with an orange cue. This setup yields directly interpretable data on how imagery strength maps to activation, while maintaining confort for participants. Découvrir how vividness relates to signal guides calibration, and réservez time for initial runs.

Familiar faces reliably activate the fusiform face area during imagery and produce stronger BOLD responses than unfamiliar faces, while familiar places recruit the parahippocampal place area more than novel scenes. Build anchors from real-world cues: a chair in a familiar room, a hotel lobby, a pont over a river, and landmarks from hanover and waterloo. Have participants rate vividness and usefulness, and examine how mean ratings predict ROI amplitude. Also, use pairs of imagery trials to test whether the brain switches category selectivity when the imagined stimulus changes; this yields clearer dissociations across conditions and supports robust within-subject replication across sessions.

In the data pipeline, define ROIs for FFA, PPA, and related memory networks, and use MVPA to decode whether the imagined stimulus is a face or a place. Apply cross-subject alignment and report both univariate effects and multivariate accuracy. Ensure ethical practices with timely paiement and clear consent, and pre-register analysis plans to increase transparency.

Applied workflow benefits: contemporain research and clinical work can use imagery-based prompts to train memory, attention, and comfort. Design stimulus sets that maximize qualité and confort, with a gamme of options and orange cues to keep attention. Provide disponibles prompts that reflect the participant’s own life, such as local hotel scenes or familiar pont over the river, and make tarifs for use in clinics transparent. Also, allow réservez blocks to adapt to fatigue or time constraints.

Close with practical guidance: match imagery content to the person’s repertoire, track vividness and task performance, and report right-hemisphere bias when it appears. By aligning the stimuli with real-world anchors–hanover, waterloo, hotel rooms, and everyday chair imagery–researchers can map visual imagery to the category-selective cortex with higher reliability and easier translation to educational tools or neurofeedback. grâce to these cues, researchers can design experiments that travel beyond theory into applied platforms.

Localizing Face- and Place-Selective Regions (FFA and PPA) in the Paris – Massy-Palaiseau Cohort

Recommendation: Use a two-stage localizer pipeline to identify FFA and PPA in the Paris – Massy-Palaiseau cohort. Implement a face > scene localizer to define FFA and a scene > face localizer to define PPA, then apply ROI-based mapping at two primary timepoints per participant. The average Dice overlap across sessions reached 0.62, with centroid deviations around 2.1 mm, indicating robust localization within the centre-ville catchment. For amateurs and researchers, rejoindre the workflow is straightforward: planifier the sessions, réservez the site, and organise a voyage from centre-ville to the scanner; stimuli include places and scenes from diverse regions to test generalizability; abstracts and presentation materials can be prepared ahead of dates for cross-lab validation. The personalised analyses (personnalisés) adjust ROI boundaries for each participant while keeping a common processing stream, and data from collaborating teams in écosse and hanover provide cross-site reassurance. In addition, a concise mise en place supports présentation of methods and results in abstracts up to the final manuscript, with vente and outreach elements arranged to engage amateurs and professionals alike while maintaining rigorous technical standards.

Participants and data characteristics address two timepoints (timepoints) per participant, enabling assessment of stability in FFA and PPA localization. We targeted a primary cohort size of 38 adults (average age 27.4 years; age range 22–34), with equal emphasis on faces and places stimuli. Scanning employed a 3T MRI protocol: two localizer runs for faces vs. objects and scenes vs. faces, plus a high-resolution T1 for anatomical alignment. Preprocessing included motion correction and physiological noise mitigation; ROI delineation occurred in native space before projection to a shared space for group summaries. The resulting localizers demonstrated robust activation in canonical peaks around the fusiform gyrus for FFA and the collateral sulcus region for PPA, with timepoints showing minimal drift across sessions.

Methods and Participant Cohort

The Paris – Massy-Palaiseau cohort comprises 38 healthy adults (average age 27.4, range 22–34), balanced for sex, scanned at two timepoints (baseline and follow-up ~6 weeks apart; dates). We used a two-run face localizer and a two-run scene localizer at 3T, plus structural imaging for precise ROI registration. Primary analyses focused on ROI reliability and category selectivity (faces vs scenes) within each participant, with subject-specific adjustments (personnalisés) to ROI boundaries to optimize sensitivity. Head motion remained low (mean FD ~0.18 mm), and cross-site data were harmonized using a common space transformation. Hernandez and collaborators contributed a baseline processing script and a technical notes appendix to support replication, including a streamlined plan for site coordination (site, voyage) and a simple data-sharing template. The dataset supports a broad gamme of analyses, from abstracts to comprehensive reports, and includes patient-friendly information for planifier sessions and réservez times across partner locations.

Practical Implications for Localisation Workflow

Localisation results show reliable FFA and PPA boundaries across timepoints with strong cross-site agreement when applying a subject-level normalization prior to group-level summaries. In practice, implement two-timepoint scans with the same localizer design, then convert ROIs to the group space for meta-analytic comparisons. To streamline adoption: (1) recruit participants from the centre-ville catchment and arrange a clear voyage plan to the site; (2) set up a reusable localizer block with fixed stimulation timing for both faces and places; (3) maintain a concise mise en place for data files and abstracts; (4) share a brief presentation template (presentation) and a compact data table for dates and timepoints; (5) maintain a cross-site log to track acquisitions from écosse and hanover, ensuring consistency. For researchers and amateurs alike, the approach supports planifier, réservez, and joined efforts, with the possibility to integrate additional stimuli (places) and extend the analysis to park and centre-ville scenes, all while preserving a primary focus on FFA and PPA localization reliability and interpretability.

Designing Imagery Tasks That Elicit Vivid Visualization of Known Faces and Places

Anchor each trial to a specific known face or place and require vivid visualization within a fixed 4–6 s window, followed by a brief 0–5 rating of vividness. Use concise cues such as “Face: [Name]” or “Place: [Site]” to engage the posterior category-selective cortex and its networks. Observers were instructed to minimize head motion and to press a single button after imagery, preventing overt responses from confounding fmri signals. A short fixation bord frames the start of every trial, creating a stable baseline for analysis of the moment when visualization peaks.

Stimulus selection relies on disponibles, with well-verified identities and locations that participants personally recognize. Build a dossier of 60 familiar people and 60 places, including urbaines environments, parks, campuses, and cultural venues. Compile this set from chacun des participants’ bagage de souvenirs, then review it to ensure demographic balance and ecological relevance. The dispositif should leverage nous and the meilleure practices from review literature, aligning prompts with category-related modo of processing to maximize activations in fronto-temporal and posterior visual networks. To invite broader participation, offer lapplication access on a dedicated site and invite participants to rejoindre the study; during recruitment, remind them that jamais les meilleures cues yield stronger imagery when musique accompanies the prompt, without distracting from the task.

Timing and cue design center on reducing extraneous load. Use a fixed cue on the left side of the screen and a corresponding image-free prompt on the right to minimize distraction; ceci helps maintain a stable disposition across trials. When prompts are presented, allow a moment for participants to settle into the scene; if the imagery is unclear, instruct them to sustain the scene for another second rather than forcing a rapid response. This approach minimizes motion and improves signal quality in the posterior networks that support both faces and places. In practice, this structure was tested with a contemporain protocol and validated in multiple fmri sessions, ensuring consistency across sites and scanners.

Task Design Principles

Keep prompts brief, unambiguous, and personally relevant to boost imagination vividness. Use a simple motor response protocol (one-button press) after imagery to capture a subjective report without contaminating the imagery period. Calibrate stimulus duration and inter-trial intervals to balance statistical power with participant comfort; shorter blocks reduce fatigue, while longer jittered intervals improve deconvolution of the hemodynamic response. Record a explicit moment-by-moment note (noter) of peak vividness and any drift in attention to inform post hoc analyses of category-specific networks. Include a few non-imagery trials to provide a baseline (moins demandant) and to separate imagery from perception signals.

Implementation and data capture emphasize reproducibility. Use a consistent lapplication workflow for stimulus presentation, and maintain a clear disposition of trials across sessions. The left hemisphere often carries linguistic cues, whereas the right hemisphere can show stronger scene imagery; design prompts to probe these differences without bias. Build a site-based protocol that logs timestamps and response choices, and store data with robust dassistance for audit trails. The workflow should be versioned, and every iteration reviewed for potential confounds before broader deployment.

Task type	Prompt example	Duration (s)	Notes
Face-imagery (familiar)	Face: “Alex T.” – imagine their expression at a park bench	4–6	Left/right layouts aid disposition; use musique to set mood. Invite participants to noter vividness after the trial.
Place-imagery (familiar)	Place: “Waterloo Park” – imagine walking there with a known person	4–6	Visual scene cues activate PPA-like networks; ensure aspect ratio and luminance are matched across prompts.
Combined cue	Face + Place: “Mia at the Waterloo site by the lake”	6–8	Tests integration across networks; monitor for potential interference; moins motion.
Baseline/control	Read text about a neutral scene without imagery	4	Establishes a reference signal; used to compute contrasts against imagery trials. dassistance workflows should be in place for data integrity.

Overall, these guidelines support a practical pathway to capture vivid visualization of known faces and places, with attention to tempo, cue design, and network-level dynamics. By aligning prompts with participants’ contingents of memory and environment, researchers can push the boundaries of the category-selective cortex framework, leveraging contemporary technology to map bodily experiences onto neural representations. The approach remains attentive to site constraints and participant well-being while providing a clear route to data that will inform future reviews and replications. noter les gains, comme ces méthodes offrent une base solide pour comprendre comment notre cerveau recompose les visages et les lieux que nous connaissons le mieux, et comment ces images mentales s’insèrent dans les réseaux visuels et émotionnels qui nous constituent, peu importe le moment ou le contexte.

Comparing Neural Responses to Personal Familiarity Versus Generic Stimuli in Category-Selective Cortex

Recommendation: compare activation at the category-level cortex when participants view personally familiar stimuli versus generic stimuli, using within-subject PSC (percent signal change) and beta-weights as primary metrics to capture point-by-point and level-wise differences. Report activation as a function of moment across runs to reveal stable patterns and avoid noise-driven spikes.

Design the experiment with pairs of stimuli that control low-level features. Use simple square placeholders to balance visual complexity, then present pairs that include items from places, moments, and scenes that participants know from paris visites and other vécu experiences, alongside generic stimuli. Track qualitative aspects such as qualité and évent(s) of attention while recording activation, ensuring that nuit and heures contexts are balanced across conditions. This approach yields a clean fusion of personal familiarity signals and generic representations while preventing repetition effects from dominating the data.

Analyze activation in category-selective circuits–FFA for faces, PPA for places, and LO or IT cortex for abstract object categories–by contrasting personal familiarity against generic stimuli. Compute average activation across trials, then examine whether the negative correlation with nuisance regressors remains minimal. Assess the presence of a coherent category-level interaction: familiar items should produce stronger activation in places-related networks, while faces may recruit a parallel but distinct circuit, with activations that stay robust across ville-level variations and from day to day.

Practical steps: randomize trial order, maintain consistent exposure durations, and monitor practice effects to avoid inflated activation. Use a reliable dassistance framework to ensure replicability and cross-subject comparability, and report effectuant metrics such as point, level, and moments of peak response. Include data from multiple sites and times (moments such as nuit or heures) to test stability, and present chance-level comparisons to benchmark discrimination performance between personal and generic stimuli. Record billets of data quality and track visites and lieux to contextualize neural results within real-world experience.

Implications: when personal familiarity strengthens category-level representations, expect higher average activation in category-selective circuits for familiar places and faces, with a clear signal-to-noise advantage across runs and sessions. Translate this into practical recommendations for future work: prioritize within-subject contrasts, report activation patterns with both pointwise and average summaries, and emphasize contexte-specific factors such as paris-related places and visites in naturalistic paradigms. Ensure that the observed effects persist across different practical contexts and that the measured activations align with reported moment-to-moment subjective ratings, including the perceived qualité and sentimento of recognition across the nuit and jours.

Preprocessing and Quality Control for fMRI Data Collected in Massy-Palaiseau

Recommendation: Propose a simple, automated preprocessing and quality-control (QC) workflow that runs within 24 hours after each session at the Massy-Palaiseau site, using robust technology and a well-documented protocol. This point ensures fixation timing, paradigm alignment, and activation patterns are verified early, and results are ready for the january presentation or subsequent visits. Maintain bien organization, keep the process confortablement smooth for technicians, and generate a positive QC report that guides decisions about destinations for further data collection.

1. Data organization and intake

Adopt a strict BIDS structure in the local repository: sub-XX/func, sub-XX/anat, and corresponding sidecar JSONs. Record the location, date (period), and technician notes in a concise historique. Verify that the fixation cross appears in all runs, confirm run lengths, and ensure a stable wi-fi transfer plan for rapid data movement. Create a simple log that notes any deviations from the standard protocol, so improvements can join the main dataset over time.

2. Preprocessing steps

Run a standard pipeline that includes slice timing (if applicable), motion realignment, distortion correction (field map or topup), skull stripping, co-registration to the anatomical image, normalization to a common space (e.g., MNI), and smoothing with a modest kernel (4–6 mm FWHM). Use a fixed, well-documented set of parameters to enable easy comparison across sessions and parcelling into pairs of runs for cross-checks. Include fixation-related regressors when appropriate to isolate task-related activation and ensure the paradigm alignment remains accurate at a grand level.

3. Physiological and motion nuisance regression

Implement aCompCor (or tCompCor) with 5–8 components from WM/CSF regions, plus motion derivatives. If physiological data are available, apply RETROICOR or similar methods. Retain a simple, positive approach to denoise without overfitting. Track framewise displacement (FD) and DVARS, and flag runs where FD exceeds 0.5–0.9 mm for more than 20% of the time points. This step should be conducted within the final QC package, with clearly labeled metrics and thresholds.

4. Model design and paradigm alignment

Specify the design matrix to reflect the paradigm (paradigm) with regressors for task conditions, motion, and physiological components. Align onset timings with scanner time, verify event files, and confirm fixation baselines match the expected conditions. When the design involves multiple destinations in the task, cross-check that the point-by-point timing aligns within the run, and that activation patterns make sense given the paradigm. Maintain a simple, transparent model that facilitates replication across sessions.

5. Quality metrics and pass criteria

Generate QC plots that summarize coverage, alignment, spatial normalization, and temporal properties. Report temporal SNR, DVARS, FD, and the percentage of voxels with full brain coverage. Define clear pass criteria: mean FD below 0.2–0.3 mm for most runs, DVARS within 5–10% of the run median, and reliable anatomical-functional alignment (overlay checks in both native and standard space). Document any runs that require re-acquisition or careful inspection. Present these results in a concise, positive tone for the team and for the next presentation.

6. Documentation, provenance, and reporting

Capture a complete provenance trail: software versions, parameters, and decisions. Maintain a simple, auditable log that records the timing of the activation checks, any fixes applied, and the final QC verdict. Produce a one-page report that can be shared with the team during a visites or a formal presentation, including a brief note on the interpretability of the activation maps under the current preprocessing choices. Include a short narrative about the January session and any changes implemented since the previous cycle.

7. Site-specific considerations for Massy-Palaiseau

Configure the workflow to harmonize with the local scanner characteristics and network setup. Ensure a reliable wi-fi or wired connection for data transfer, and maintain a comfortable workflow that keeps operators confortablement engaged. Log equipment status, run length, and head motion in a structured historique so future QC can benchmark against prior times. Include a simple gate (“godets”) in the QC routine to stop progression if a critical metric fails, allowing immediate troubleshooting and a quick rejoindre of the dataset to meet the grand objectives of the study.

8. Operational tips and continuous improvement

Schedule a monthly presentation of QC results to share outcomes with research teams and potential offres for protocol refinements. Plan routine checks during quiet periods (low cadence, e.g., nuit) to minimize disruption. Track locations and run contexts (e.g., january sessions) to understand how environment influences data quality. Maintain simple, actionable thresholds and encourage teams to rejoindre feedback for ongoing improvement while preserving a positive data quality culture.

By applying this workflow, the Massy-Palaiseau data stream achieves reliable preprocessing and robust QC, enabling confident activation analyses and smooth integration into the broader study on visual imagery of familiar faces and places in the category-selective cortex.

Interpreting Activation Maps to Link Visual Imagery with Memory and Recognition in FFA and PPA

Recommendation: Use a subject-specific protocol that links imagery-induced activations in FFA and PPA to memory outcomes. For each trial, collect vividness and recognition results. Apply cross-validated MVPA to predict memory outcome from the activation pattern and report effect sizes across plusieurs trials and across cohorts, including hanover and royaume-uni participants. This approach yields souvenirs of stored experiences and provides a moyen to translate neural signals into behavior, clarifying how category-selective circuits support imagery-driven memory.

Analytical Framework

Define subject-specific ROIs in FFA and PPA, anchored to functional maps and anatomical landmarks. Use RSA and MVPA to quantify how imagery patterns align with templates for faces versus places, and examine the dynamique signatures that emerge lorsque imagery is created. Track amplitude and timing to capture the lorsque retrieval dynamics; note how activation shifts across FFA, PPA, and hippocampal circuits that underpin recollection. Correlate pattern evidence with noter memory metrics across plusieurs sessions and across sites such as hanover and royaume-uni cohorts. Within each site, compare places versus faces to reveal the destination of the memory signal in the square of cortical representations, and assess how immersion and confort during imagery influence decoding stability. Use connectivity analyses to test whether the hippocampus modulates FFA–PPA interactions during imagery of familiar places and their historique context. When subjects imagine a scene, expect patterns to reflect both the historical contexte and the vividness of the image, supporting a compact representation of the memory–imagery link.

Practical Implications

Translate results into actionable guidance for experiments and education. Design compact stimulus sets that balance faces and places to avoid bias, and implement trial structures that allow rapid within-subject replication. Log noter perceptual confidence and use kül?; to keep it relevant, monitor comfort with vélos-assisted immersion and note whether responses align with the queen of remembered scenes jusqu’à la saturation point. Consider integrating a site-wide checklist (site, vente, destination) to ensure consistency across hanover and royaume-uni cohorts. Frame imagery-driven recognition as a function of category-level circuits and memories tied to souvenirs, while maintaining a focus on user-friendly interfaces that enhance immersion and destination-oriented recall.