Unraveling Brain Functional Connectivity of encoding and retrieval in the context of education
Introduction
The importance of memory cannot be understated since our very survival depends on our ability to remember who we are, who others are, our past experiences, what is dangerous, what is safe, etc. Atkinson–Shiffrin model (Bjork & Whitten, 1974) remains the most popular model for studying memory which describes memory as a sequence of three stages, from sensory to short-term to long term memory, rather than as a unitary process. All aspects of memory, can be viewed as the activation of network memory, that is, the increased firing of the cortical neurons making up a memory network (Joaquı́n M. Fuster, 1997). Networks remain open-ended throughout life, subject to expansion and recombination by new experience. The networks of perceptual and motor memory appear hierarchically organized on a foundation of phyletic memory-that is, primary sensory and motor cortex (Joaquı́n M. Fuster, 1997). Short-term memory is represented in a network involving the prefrontal and posterior sensory cortices. The prefrontal cortex controls subsidiary posterior cortices, enabling retention of short-lived information relevant to ongoing goal-directed behavior. Long-term declarative memory is also represented in the cerebral cortex in a domain-specific fashion. For instance, in the inferior temporal cortex, which is involved in object recognition, some neurons encode stimulus repetition, while others learn to encode an elemental semantic-like association between visual images. (T. Fukushima, 2003). The process of encoding varies with the levels of shallow and deep processing (Craik & Tulving, 1975). The retrieval is influenced by cues, encoding specificity, state-dependent learning and transfer-appropriate processing. Neurobiology of memory involves connection, cognition, compartmentalization, and consolidation (Milner, Squire, and Kandel, 1998; Eichenbaum, 2011).
With the developments in the field of functional MRI (fMRI) a very high level of integrative real time understanding of working memory is now possible as we are able to see brain in real time as functionally defined set of networks that transiently interact to perform a particular neural function. Accumulating studies on functional connectivity now see brain as a complex dynamic unit with positively and negatively correlated networks in perfect coherence during a task (Chanraud et al., 2011, Esposito et al., 2009, Fox et al., 2009, Hampson et al., 2006, Mayer et al., 2010, Meda et al., 2009, Sala-Llonch et al., 2012, Van den Bosch et al., 2012). Task-positive networks are regions that are simultaneously activated during active cognitive processing. Frontoparietal network is a prominent task positive working memory network (Champod and Petrides, 2010, Deiber et al., 1997, Iidaka et al., 2006, LaBar et al., 1999). Dorsolateral prefrontal cortex is considered as hub for many networks especially in the context memory and education (Champod and Petrides, 2007, Collette et al., 1999, Gerton et al., 2004, Sun et al., 2005). Task-negative networks (resting-related networks) are those which are active during passive or stimulus-independent thought, and are subsequently deactivated during active processing. One of the well documented resting related networks is DMN. This network comprises a set of highly functionally connected regions such as medial prefrontal cortex (MPFC), posterior cingulate cortex (PCC), lateral and medial temporal lobes and posterior inferior parietal lobule (Greicius et al., 2009, Raichle et al., 2001, Uddin et al., 2009; Fransson, 2005, Damoiseaux et al., 2006, Fox and Raichle, 2007, Buckner et al., 2008, Johnson et al., 2012). The negative correlation between regions in the DMN during a cognitive task suggests that the circuit interferes with or distracts from cognitive processing and facilitates cognitive performance. In prior studies, a negative correlation between working memory performance and task-irrelevant mental processing was reported (Chanraud et al., 2011, Esposito et al., 2009, Fox et al., 2005, Fox et al., 2009, Hampson et al., 2006, Mayer et al., 2010, Meda et al., 2009, Michels et al., 2010, Sala-Llonch et al., 2012, Van den Bosch et al., 2012). A recent study observed and found that not only there is negative correlation between the DMN and cognitive tasks but the degree is proportionally related with the demands of the cognitive function (Sala-Llonch et al., 2012). Further study confirmed that the relative extent of the anterior and posterior midline spots within the DMN was negatively correlated in the PCC with the level of task difficulty. The study concluded that the working-memory function is related to a spatial re-configuration of the DMN functional connectivity which could function as a novel predictor of the working-memory efficiency (Esposito et al., 2009). From the perspective of development, Van den Bosch et al. studied the brain connectivity during verbal working memory in children and adolescents. They noted children have higher task-related connectivity at lower loads, but they tend to equalize with the adolescents with higher loads and non-load related network involving the orbital frontal and anterior cingulate cortices showed less connectivity in children (Van den Bosch et al., 2012). In a study done by Champod and Petrides (2007), it was noted that the PCC is centrally involved in manipulation processes, whereas activation of the DLFC is related to the monitoring of the information that is being manipulated and their relative contribution to working memory. Brain deactivation patterns during working memory and visual attention tasks was noted in task fMRI (Tomasi, Ernst, Caparelli, & Chang, 2006). Mayer et al. noted task induced brain deactivation in DMN region in visual working memory and attention task. They reported task-induced deactivations within regions of the DMN with a segregation of areas that were additively deactivated by an increase in the demands on both attention and WM. Attention selective deactivations appeared in the left ventrolateral and medial prefrontal cortex and the left lateral temporal cortex. Conversely, WM selective deactivations were reported in the right hemisphere including the medial-parietal, the lateral temporo-parietal, and the medial prefrontal cortex. Moreover they also reported, during WM encoding deactivated regions showed task specific functional connectivity. Their findings demonstrate that task induced deactivations within parts of the DMN depend on the specific characteristics of the cognitive process (Mayer et al., 2010). Recently an EEG-fMRI study found that low frequency band (theta and alpha) activity negatively correlated with the BOLD signal during the retention phase of a WM task. They found negative BOLD signal correlations with lower frequency of EEG (theta band) in the MPFC, posterior parietal cortex (PPC), and cingulate cortex (ACC and PCC). For alpha1, positive correlations with the BOLD signal were found in ACC, MPFC, and PCC; negative correlations were observed in DLPFC, PPC, and inferior frontal gyrus (IFG). Beta and gamma showed positive correlations with BOLD in DLPFC, MPFC and IFG (Michels et al., 2010).
Connectivity analysis could be either task independent (resting state) based connectivity or task based functional connectivity. Task based functional connectivity could be superior in understanding dynamic changes involved in network in relation to a task (Greicius et al., 2003, Mayer et al., 2010, Wang et al., 2013).
Cognitive reserve (CR) hypothesis emphasizes inter-individual differences in the effective recruitment of neural networks and cognitive processes to compensate for age related effects or pathology. Under the reserve hypothesis (Stern, 2002), education is being considered as one of the main proxy of reserve, although other factors (i.e. intelligence quotient (IQ), occupation, social and physical activities, complex mental activities) may also be considered (Satz et al., 2011). Functional studies during memory tasks showed functional reorganization of brain networks (compensation) in healthy elders with higher education compared to young individuals (Scarmeas et al., 2003), and more efficient or optimal patterns of brain activation in elders with higher reserve proxies compared to elders with lower reserve proxies (Bosch et al., 2010; Solé-Padullés et al., 2009). According to C. Bastin et al., 2012, for tasks of low to moderate difficulty, high cognitive reserve will take the form of reduced – more efficient activation of the network for an equivalent or even greater success in the task and for high-demanding tasks, individuals with high cognitive reserve will have a greater capacity, so that they can show greater increase in network activation to cope with increasing task difficulty.
With the insights gained from these studies we aimed to understand the coherence of positively and negatively correlated networks during a working memory task as we strongly believe that brain is better understood as a balanced network resonating in harmony during task performance. Education being a main proxy for cognitive reserve we also aimed at understanding the effect of education on the harmony of these networks.
Section snippets
Sample
Written informed consent was sought from all the participants as per the institute Ethics Committee. Sixty right handed educated healthy volunteers from both the genders (32 females and 28 males) in the age range of 18–40 years were recruited and segregated into two groups of 30 each as school educated (SE < 10 years of education) and college educated (CE > 10 years of education) on the basis of education acquired in years. School educated participants’ inability to pursue further years of education
Preprocessing
The functional and structural MRI pre analysis was performed using statistical parametric mapping (Friston, Ashburner, Kiebel, Nichols, & Penny, 2011) (SPM8; Welcome Department of Cognitive Neurology, London). The data was realigned for motion correction by registration to the mean image. The images were then normalized to the Montreal Neurological Institute (MNI) space. Finally images were smoothed with a Gaussian kernel of 8 mm at full-width half maximum. In addition to these steps, the
Behavioral results
Performance scores (d prime) and reaction times (RTs) at the time of retrieval were noted for both the CE and SE group. All the subjects performed well (greater than 80% correct response) during the scanning session across the group. A Mann–Whitney U test was used to evaluate their difference in behavioral preferences. CE showed significantly higher performance scores and shorter RTs in retrieval. d Prime values are significantly different between the CE (3.045 ± 0.4917, median = 3.16) and SE (1.443
Discussion
Brain regions simultaneously activated during any cognitive process are functionally connected, forming large-scale networks. These functional networks can be examined during task performance and rest states and such analysis is being widely used. The aim of our study was to examine brain networks connectivity for encoding and retrieval in the context of education. Sixty healthy young school educated and college educated subjects were selected to study the visual encoding and retrieval using
Acknowledgments
This research work was funded by the Department of Science and Technology. We thank our radiographers, (Dept. Neuroimaging and Interventional Radiology (NIIR), NIMHANS, India) for their technical support and data collection. Special thanks to Mr. Deepak Ulal (Senior Technician, Dept. of Clinical Psychology) and Ms. Saranya VR (Radiographer, Dept. NIIR).
References (59)
- et al.
Prefrontal and hippocampal contributions to the generation and binding of semantic associations during successful encoding
Neuroimage
(2006) - et al.
Cognitive reserve impacts on inter-individual variability in resting-state cerebral metabolism in normal aging
NeuroImage
(2012) - et al.
A component based noise correction method (CompCor) for BOLD and perfusion based fMRI
Neuroimage
(2007) - et al.
Recency-sensitive retrieval processes in long-term free recall
Cognitive Psychology
(1974) - et al.
Cognitive reserve modulates task-induced activations and deactivations in healthy elders, amnestic mild cognitive impairment and mild Alzheimer's disease
Cortex
(2010) - et al.
Functional–anatomic study of episodic retrieval using fMRI
Neuroimage
(1998) - et al.
Regional brain activity during tasks devoted to the central executive of working memory
Cognitive Brain Research
(1999) Network memory
Trends in neurosciences
(1997)- et al.
Shared and distinct neurophysiological components of the digits forward and backward tasks as revealed by functional neuroimaging
Neuropsychologia
(2004) - et al.
Alteration of brain default network in subacute phase of injury in concussed individuals: Resting-state fMRI study
Neuroimage
(2012)
Hemispheric specialization in human dorsal frontal cortex and medial temporal lobe for verbal and nonverbal memory encoding
Neuron-Cambridge MA-
Neuroanatomic overlap of working memory and spatial attention networks: A functional MRI comparison within subjects
Neuroimage
Cognitive neuroscience review and the study of memory
Neuron
Levels of processing versus transfer appropriate processing
Journal of Verbal Learning and Verbal Behavior
Neural correlates of cognitive efficiency
Neuroimage
Brain connectivity during resting state and subsequent working memory task predicts behavioural performance
Cortex
Brain structure and function related to cognitive reserve variables in normal aging, mild cognitive impairment and Alzheimer's disease
Neurobiology of aging
Age-dependent brain activation during forward and backward digit recall revealed by fMRI
Neuroimage
Functional resting-state networks are differentially affected in schizophrenia
Schizophrenia Research
The brain’s default network
Annals of the New York Academy of Sciences
Functional anatomic studies of memory retrieval for auditory words and visual pictures
The Journal of Neuroscience
Dissociable roles of the posterior parietal and the prefrontal cortex in manipulation and monitoring processes
Proceedings of the National Academy of Sciences
Dissociation within the frontoparietal network in verbal working memory: A parametric functional magnetic resonance imaging study
The Journal of Neuroscience
Disruption of functional connectivity of the default-mode network in alcoholism
Cerebral Cortex
Depth of processing and the retention of words in episodic memory
Journal of Experimental Psychology: General
Consistent resting-state networks across healthy subjects
Proceedings of the national academy of sciences
Frontal and parietal networks for conditional motor learning: A positron emission tomography study
Journal of Neurophysiology
The cognitive neuroscience of memory: An introduction
Does the default-mode functional connectivity of the brain correlate with working-memory performances?
Archives Italiennes de Biologie
Cited by (9)
Frontoparietal hyperconnectivity during cognitive regulation in obsessive-compulsive disorder followed by reward valuation inflexibility
2021, Journal of Psychiatric ResearchCitation Excerpt :OCD patients had lower education than controls (Mann-Whitney test U = 174.0, p = 0.002, Cohen's effect size d = 1.3 [large effect]) but no statistically significant differences were found for age (U = 129.0, p = 0.304, d = 0.4 [small effect]) and gender ratio (Chi-squared test ꭕ2(1)<0.1, p = 0.893, d < 0.1 [no effect]). The education level was used as a covariate in the further statistical analyses because FC in networks associated with cognitive regulation and cognitive functioning depends on educational attainment (Panda et al., 2014; Shen et al., 2018). We measured weight and height to determine the body mass index (BMI) in our sample.
Psychophysiological mechanisms for learning tasks solving of different complexity
2020, E3S Web of ConferencesEffects of body mass index and education on verbal and nonverbal memory
2017, Aging, Neuropsychology, and Cognition