Psychological Distortion of Space and Time

 

General factors affecting distortion of space and time:

o   Number of turns

o   Density of structures in environment

o   Familiarity of environment

o   Attention

o   Dynamic visual information (optic flow)


Relevant brain architecture

  • MTL (medial temporal lobe) region of the brain tracks distance to the goal during navigation:

o Entorhinal cortex activity correlates with ‘Euclidean distance’ (the straight line distance to the goal).

o Posterior hippocampal activity correlates with path distance to the goal.

o Hippocampal activity correlates with goal closeness and egocentric direction towards goal (at decision points) — activity greatest when goal was close and directly ahead, low when goal further away and on a path curved away from current heading direction — path geometry seems to alter the brain's representation of space.

  • Separate neural pathways may exist for the representation of spatial and temporal information in hippocampal-parahippocampal regions. Or, a single neural pathway exists that processes temporal and spatial information of an environment differently.

Distortion of Space

  • Brunec et al. (2017) found that when participants estimated the distance to travel towards a goal when circumnavigating different path-geometries (U-shaped or L-shaped), there was an overestimation of Euclidean distance to the goal. This was more apparent in the U-shaped paths. Therefore an expansion of estimated Euclidean distance.

  • Jafarpour and Spiers (2017) found that with increased space familiarity, the estimates of sketched space expanded. The paper suggests that the expansion of space is potentially due to an increase in grid cell spacing (less grid units per meter).

  • A study looking at the contributions of static visual cues, non-visual cues and optic flow on distance processing/estimation found that in tasks where visual information was present, participants would overestimate the distance for shorter distances (10m) and under-estimate the actual distance for longer distances (20m). They also found that dynamic visual information (optic flow) would lead participants to underestimate their movement, resulting in an overestimation of the distance travelled.

  • Routes within a space that contain fewer turns/angle changes are perceived as being metrically shorter. This has led to suggestions that buildings should have straighter more direct routes and less extreme angle turns, particularly greater than 90 degrees.


Distortion of Time

  • Brunec et al. (2017) found that participants would under-estimate the time it takes to travel to the goal when circumnavigating different path geometries (U-shaped or L-shaped) — a contraction in estimated travel time.

  • Jafarpour and Spiers (2017) found that the estimated travel time (ETA) for more familiar paths was shorter, consistent with past research that familiar environments travel-times are underestimated. Suggests that highly familiar paths may become schematized over time therefore retrieval/recall of them requires less detail and cognitive demand leading to a contraction in ETA.

  • The greater the time relevance of a journey, the more attentional resources used to track the time and therefore, a longer estimate of journey duration. Arriving to a goal/event tends to be more time relevant, while returning back is not, this results in the ‘return trip effect’ (the return journey seems shorter than the initial journey). Therefore estimated time of arrival (ETA) may be affected by attention.

  • Time perception is divided into two domains:

    • Prospective timing: This is where timing is an essential part of the task. Based on the attentional gate model, attention paid to duration closes a switch between an intrinsic pacemaker and pulse accumulator. Time is then estimated based on the pulses counted in the accumulator. Higher attentional resources used for processing temporal information results in a longer perceived duration of a task.

    • Retrospective timing: This is where you are asked unexpectedly the timing of an event retrospectively. Based on the contextual change model, memories of an event are segmented based on the number of contextual changes (defined as changes in cognitive processing) that occur in the event. We use these changes as temporal referents to estimate the perceived duration of the event. Segmentation of a memory determines the memory size. Therefore, the greater the segmentation of a memory, the greater the memory size and the longer the perceived duration of the event.


 
Josh Artus