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Children from lower income backgrounds tend to have poorer memory and language abilities than their wealthier peers. It has been proposed that these cognitive gaps reflect the effects of income-related stress on hippocampal structure, but the empirical evidence for this relationship has not been clear. Here, we examine how family income gaps in cognition relate to the anterior hippocampus, given its high sensitivity to stress, versus the posterior hippocampus. We find that anterior (but not posterior) hippocampal volumes positively correlate with family income up to an annual income of $75,000. Income-related differences in the anterior (but not posterior) hippocampus also predicted the strength of the gaps in memory and language. These findings add anatomical specificity to current theories by suggesting a stronger relationship between family income and anterior than posterior hippocampal volumes and offer a potential mechanism through which children from different income homes differ cognitively.
All participants underwent magnetic resonance (MR) scanning and 690 participants in the sample completed assessments of memory and vocabulary. We include episodic associative memory and vocabulary assessments in our investigation because both memory39,40 and the acquisition and use of new vocabulary20,21,23,24,41,42,43 are thought to depend on hippocampal binding. Individuals with hippocampal damage are impaired at learning the meaning of new words42,44, and studies demonstrate that language acquisition and vocabulary correlate with hippocampal activity21,24, and hippocampal volume in children45 and adults46. To test the specificity of the relationships between hippocampal volumes and cognition, we include performance on a processing speed task47 that is independent of the hippocampus39.
The large public dataset used here did not include a stress measure, so we were unable to directly assess the role that income-related stress played in our findings. Thus, while stress is a plausible mechanism, it is not the only factor that may influence the relations we observed. Indeed, many other factors, including access to material and nonmaterial resources3,7 correlate with SES and may play a role in our findings. For example, relative to families from lower SES backgrounds, higher SES families spend more time engaging children in reading activities51 and provide more access to educational resources52, which are thought to be important for cognitive and neural development53. These factors could boost anterior hippocampal volumes and cognitive performance among individuals from higher income backgrounds, and thus underlie the positive effects of income on cognition and anterior hippocampal volumes that we observed. It is our hope that our correlative findings will inspire future longitudinal research to directly measure stress to determine whether stress or other factors related to income can prospectively predict changes in anterior hippocampal volumes during development. Moreover, although not available in this dataset, future work investigating the effects of income should consider using an income-to-needs ratio (i.e., income divided by the national poverty threshold for a family of the same size), which would provide a more precise estimate of the amount of resources available to children than income alone.
To conclude, our findings are relevant to clinicians, educators, and policy makers, who are interested in promoting brain and cognitive health in children from lower income backgrounds. Moreover, our results add the much-needed anatomical specificity to current theories by showing that family income disproportionately affects the anterior hippocampus. Crucially, the present study also highlights that the anterior hippocampus may be a potential mediator of cognitive gaps between high- and low-income children. Given that the anterior and posterior hippocampus are involved in different cognitive processes27, the differential influence of income on the development of these hippocampal regions may have implications for understanding the types of cognitive processes that require more support in low-income children.
Parents were asked to report annual family income. In the case that parents did not accompany the participant to the lab, participants were asked to provide their parents combined income. Data were collected in bins that ranged from
In order to determine whether hippocampal volumes and income broadly correlate with cognition, or selectively correlate with cognitive abilities known to be supported by the hippocampus (e.g., memory and vocabulary), we also included a processing speed task47 which is thought to be independent of the hippocampus39,50.
Once automated segmentation of the whole hippocampus was complete, we combined the subfield labels (CA1, CA2-3, CA4-DG, subiculum, SRSLSM) into a single label for the left and right hippocampus. We combined the subfield labels because whole hippocampal volumes using this method are more reliable than those generated for the individual subfields63, and because we were particularly interested in examining the anterior and posterior hippocampus segments (rather than the subfields). After labels were generated, we visually inspected each to ensure that the label covered the hippocampus. Data were included if the segmentations covered the entire hippocampus on each slice that the hippocampus was visible, or the majority of the hippocampus on each slice that the hippocampus was visible. Otherwise, data were excluded. In the case of two labels, the segmentations only covered a few (3 or 4) slices of hippocampus. These two labels were excluded, leaving a total of 710 labels. To ensure objectivity for excluding these two labels, we selected a random subset of 100 labels among the 712 MR images (including the two labels that we decided to exclude due to poor segmentation). We then had a second blind rater successfully identify these two poor quality labels (and only these labels) for exclusion.
Finally, since patterns of age-related differences in hippocampal subregions are not well established, we assessed whether age influenced hippocampal subregion volumes more in the posterior than anterior hippocampus. We ran an interaction mixed effects model to test whether age had a more positive relationship on one subregion than another. For the interaction mixed effects model, since regions were nested within participants, we modeled random intercepts for each participant.
The volume management driver for Storage Virtualize family offers variousblock storage services. It provides OpenStack Compute instances with accessto IBM Storage Virtualize family storage products. These products include theSAN Volume Controller, Storwize and FlashSystem family members built with IBMStorage Virtualize (including FlashSystem 5xxx, 7xxx, 9xxx).
If using Fibre Channel (FC), each Storage Virtualize family node shouldhave at least one WWPN port configured. The driver uses all availableWWPNs to attach the volume to the instance. The driver obtains theWWPNs directly from the storage system. You do not need to providethese WWPNs directly to the driver.
If using iSCSI for data access and thestorwize_svc_iscsi_chap_enabled is set to True, the driver willassociate randomly-generated CHAP secrets with all hosts on the StorageVirtualize family. The compute nodes use these secrets when creatingiSCSI connections.
The IBM Storage Virtualize family driver can allocate volumes in multiplepools. The pools should be created in advance and be provided to the driverusing the storwize_svc_volpool_name configuration flag in the formof a comma-separated list.For the complete list of configuration flags, see Storage Virtualize family driver options in cinder.conf.
The driver requires access to the Storage Virtualize family systemmanagement interface. The driver communicates with the management usingSSH. The driver should be provided with the Storage Virtualize familymanagement IP using the san_ip flag, and the management port shouldbe provided by the san_ssh_port flag. By default, the port value isconfigured to be port 22 (SSH). Also, you can set the secondarymanagement IP using the storwize_san_secondary_ip flag.
To allow the driver to communicate with the Storage Virtualize familysystem, you must provide the driver with a user on the storage system.The driver has two authentication methods: password-based authenticationand SSH key pair authentication. The user should have an Administratorrole. It is suggested to create a new user for the management driver.Please consult with your storage and security administrator regardingthe preferred authentication method and how passwords or SSH keys shouldbe stored in a secure manner.
If using password authentication, assign a password to the user on theStorage Virtualize family system. The driver configuration flags for the userand password are san_login and san_password, respectively.
If you are using the SSH key pair authentication, create SSH private andpublic keys using the instructions below or by any other method.Associate the public key with the user by uploading the public key:select the choose file option in the Storage Virtualize familymanagement GUI under SSH public key. Alternatively, you mayassociate the SSH public key using the command-line interface; details canbe found in the Storage Virtualize family documentation. The private keyshould be provided to the driver using the san_private_key configurationflag.
The private key file should be provided to the driver using thesan_private_key configuration flag. The public key should beuploaded to the Storage Virtualize family system using the storagemanagement GUI or command-line interface.
The backend_id is a unique name of the remote storage, the san_ip,san_login, and san_password is authentication information for theremote storage. The pool_name is the pool name for the replicationtarget volume.
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