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 오렌지 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 그리고 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 그리고 confort, 포함 gamme of options and 오렌지 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.

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 QC 결과를 연구팀 및 잠재적 offres 프로토콜 개선을 위해. 조용한 기간 동안(낮은 케이던스 등) 정기 점검을 계획하세요. nuit) 혼란을 최소화합니다. 추적 locations 컨텍스트를 실행하고(예:) 1월 세션)을 통해 환경이 데이터 품질에 미치는 영향을 파악합니다. 간단하고 실행 가능한 임계값을 유지하고 팀을 장려합니다. rejoindre 긍정적인 데이터 품질 문화를 유지하면서 지속적인 개선을 위한 피드백.

이 워크플로우를 적용함으로써 Massy-Palaiseau 데이터 스트림은 신뢰할 수 있는 전처리와 강력한 QC를 달성하여, 범주 선택적 피질에서 친숙한 얼굴과 장소의 시각적 이미지에 대한 더 광범위한 연구에 대한 자신감 있는 활성화 분석과 원활한 통합을 가능하게 합니다.

FFA 및 PPA에서 시각적 이미지와 기억 및 인식을 연결하기 위한 활성화 맵 해석

권장 사항: FFA 및 PPA에서 이미지 유발 활성화를 기억 결과와 연결하는 주제별 프로토콜을 사용하십시오. 각 평가판마다 생생함과 인식 결과를 수집하십시오. 교차 검증된 MVPA를 적용하여 활성화 패턴에서 기억 결과를 예측하고 hanover 및 royaume-uni 참가자를 포함하여 여러 평가판 및 코호트에서 효과 크기를 보고하십시오. 이 접근 방식은 저장된 경험에 대한 추억을 제공하고 신경 신호를 행동으로 변환하는 moyens을 제공하여 범주 선택적 회로가 이미지 기반 기억을 어떻게 지원하는지 명확히합니다.

분석적 프레임워크

기능 지도와 해부학적 랜드마크에 고정된 FFA 및 PPA에서 주제별 ROI를 정의합니다. RSA 및 MVPA를 사용하여 이미지 패턴이 얼굴 대 장소 템플릿과 어떻게 일치하는지 정량화하고, 이미지가 생성될 때 나타나는 동적 시그니처를 검사합니다. 검색 역학을 포착하기 위해 진폭과 타이밍을 추적합니다. FFA, PPA 및 회상을 뒷받침하는 해마 회로에서 활성화가 어떻게 이동하는지 기록합니다. 여러 세션과 하노버 및 영국과 같은 사이트에서 패턴 증거와 메모리 메트릭을 연관시킵니다. 각 사이트 내에서 장소와 얼굴을 비교하여 피질 표현의 제곱에서 메모리 신호의 목적지를 밝히고 이미지를 사용하는 동안 몰입도와 편안함이 디코딩 안정성에 미치는 영향을 평가합니다. 연결 분석을 사용하여 해마가 익숙한 장소와 역사적 맥락의 이미지화 동안 FFA–PPA 상호 작용을 조절하는지 테스트합니다. 피험자가 장면을 상상할 때 패턴은 역사적 맥락과 이미지의 생생함을 반영하여 메모리-이미지 링크의 컴팩트한 표현을 지원할 것으로 예상합니다.

실질적인 영향

실험 및 교육을 위한 실행 가능한 지침으로 결과를 번역합니다. 편향을 피하기 위해 얼굴과 장소의 균형을 맞추는 간결한 자극 세트를 설계하고, 피험자 내에서 빠른 복제가 가능한 시험 구조를 구현합니다. 인지적 확신도를 기록하고 관련성을 유지하기 위해 vélos 지원 몰입에 대한 편안함을 감시하고 응답이 회상된 장면의 여왕과 일치하는지 포화점까지 기록합니다. 하노버 및 royaume-uni 코호트 간 일관성을 보장하기 위해 사이트 전체 체크리스트(사이트, 판매, 목적지)를 통합하는 것을 고려합니다. 이미지가 주도하는 인식을 카테고리 수준 회로 및 기념품과 관련된 기억의 기능으로 구성하는 동시에 몰입을 향상시키고 목적지 지향적 회상을 강화하는 사용자 친화적인 인터페이스에 집중합니다.