There is an interesting recent paper (see citation) on visual memory. The researchers’ intent is to map and areas and causal directions between them for a particular process in healthy individuals so that sufferers showing lost of that process can be studied in the same way and the areas/connections which are faulty identified. In this study they were looking at encoding of vision for memory.
40 healthy subjects were examined. “… participants were presented with stimuli that represented a balanced mixture of indoor (50%) and outdoor (50%) scenes that included both images of inanimate objects as well as pictures of people and faces with neutral expressions. Attention to the task was monitored by asking participants to indicate whether the scene was indoor or outdoor using a button
box held in the right hand. Participants were also instructed to memorize all scenes for later memory testing. During the control condition, participants viewed pairs of scrambled images and were asked to indicate using the same button box whether both images in each pair were the same or not (50% of pairs contained the same images). Use of the control condition allowed for subtraction of visuo-perceptual, decision-making, and motor aspects of the task, with a goal of improved isolation of the memory encoding aspect of the active condition.” All the subjects performed well on both tasks and on later recognition of the scene they were asked to remember. “Thirty-two ICA components were identified. Of these, 10 were determined to be task-related (i.e., not representing noise or components related to the control condition) and were included in further analyses and model generation. Each retained component was attributed to a particular network based on previously published data. ” Granger causality analysis was carried out on each pair of the 10 components.
The authors give a description of the many functions that have been attributed to their 10 areas (independent components) which is interesting reading. But not very significant because the areas are on the large size and because it is reasonable to argue from a specific function to an active area but not from an active area to a specific function. The information does have a bearing on some theories and models. The fact that this work does not itself produce a model does not make it less useful in studying abnormal visual memory encoding.
The involvement of the ‘what’ visual stream rather than the stream used for motor actions is expected, as is the involvement of working memory. There is clearly a major importance of attention in this process. The involvement of language/concepts is interesting. “Episodic memory is defined as the ability to consciously recall dated information and spatiotemporal relations from previous experiences, while semantic memory consists of stored information about features and attributes that define concepts. The visual encoding of a scene in order to remember and recognize it later (i.e., visual memory encoding) engages both episodic and semantic memory, and an efficient retrieval system is needed for later recall.” The data is likely to be useful in evaluating theoretical ideas. The author mention support for the hemispheric encoding/retrieval asymmetry model.
“Memory encoding engages multiple concurrent and sequential processes. While the individual processes involved in successful encoding have been examined in many studies, a sequence of events and the importance of modules associated with memory encoding has not been established. For this reason, we sought to perform a comprehensive examination of the network for memory encoding using data driven methods and to determine the directionality of the information flow in order to build a viable model of visual memory encoding. Forty healthy controls ages 19–59 performed a visual scene encoding task. FMRI data were preprocessed using SPM8 and then processed using independent component analysis (ICA) with the reliability of the identified components confirmed using ICASSO as implemented in GIFT. The directionality of the information flow was examined using Granger causality analyses (GCA). All participants performed the fMRI task well above the chance level (.90% correct on both active and control conditions) and the post-fMRI testing recall revealed correct memory encoding at 86.3365.83%. ICA identified involvement of components of five different networks in the process of memory encoding, and the GCA allowed for the directionality of the information flow to be assessed, from visual cortex via ventral stream to the attention network and then to the default mode network (DMN). Two additional networks involved in this process were the cerebellar and the auditory-insular network. This study provides evidence that successful visual memory encoding is dependent on multiple modules that are part of other networks that are only indirectly related to the main process. This model may help to identify the node(s) of the network that are affected by a specific disease processes and explain the presence of memory encoding difficulties in patients in whom focal or global network dysfunction exists. ”
Nenert, R., Allendorfer, J., & Szaflarski, J. (2014). A Model for Visual Memory Encoding PLoS ONE, 9 (10) DOI: 10.1371/journal.pone.0107761