The Computational Memory Lab uses mathematical modeling and computational techniques to study human memory. We apply these quantitative methods both to data from laboratory studies of human memory and from electrophysiological studies done on patients with implanted electrodes.
Our research is focused on neurocomputational mechanisms of human episodic and spatial memory. Episodic memory refers to memory for events that are embedded in a temporal context. This includes both memory for significant life events and memory for common daily activities. In the laboratory, episodic memory is investigated by presenting lists of words for study, and then asking participants to recall the words. Using conditional probability and latency analyses (Kahana, M. J., 1996) one can quantify the way in which people transition from one recalled word to the next (see Fig. 1).
|Fig. 1: The contiguity effect in free recall. This curve shows the probability of making a recall to serial position i+lag immediately following recall of serial position i---that is, the conditional-response probability (CRP) as a function of lag.|
To explain the recency and contiguity effects in free recall, Howard, M. W. and Kahana, M. J. (2002) developed the Temporal Context Model of episodic memory. TCM is a distributed memory model that specifies the mechanisms of contextual drift and contextual retrieval. Through the drift mechanism, TCM describes how a temporal code is created by the integration of recently retrieved contextual states. As such, TCM represents the first formal model of how memories become 'episodic' (linked to the time when they occurred). TCM also provides an alternative explanation for associative tendencies in recall. Rather than resulting from co-occurrence in short-term memory (the standard earlier view), TCM suggests that these tendencies appear because recall of an item recovers the temporal context for the item, which in turn cues recall of subsequent items. Similarly, recency effects appear because the temporal context at the time of the memory test is most similar to the temporal context associated with recent items. Unlike short-term memory based models, TCM predicts that recency and associative effects should be approximately time-scale invariant (Howard, M. W. and Kahana, M. J., 1999, Sederberg et al., 2008).
In addition to behavioral and theoretical analyses of episodic memory, we also explore the neurophysiology of episodic memory with both scalp and intracranial electroencephalographic (iEEG) recordings. Intracranial recordings can be obtained from epilepsy patients who have had electrodes surgically implanted on the cortical surface of the brain or through the medial temporal lobes (including hippocampus) as part of the clinical process of localizing seizure foci. One focus of this research is to determine the oscillatory correlates of successful episodic memory formation. Our lab has found that 44-100 Hz (gamma) brain oscillations increase while participants are studying words that they will successfully, as opposed to unsuccessfully, recall (Sederberg et al., 2006). The same distribution of gamma activity across both hippocampus and neocortex is reactivated just prior to recalling an item, with higher levels of gamma predicting whether or not the recalled item was actually studied (Sederberg et al., 2007; see Fig. 2).
Our lab is also interested in the neural mechanisms underlying human spatial cognition. In this work, we use virtual reality computer games (Fig. 1) in which participants learn the locations of landmarks in virtual environments. To download a sample of a YellowCab session, click <<ExtLink(/files/misc/yc2_movie.mov,here)>>. Using this approach, we have documented the existence and character of the 4-8 Hz theta rhythm in the human brain as participants learned to navigate through complex virtual environments (Kahana et al., 1999; Caplan et al., 2001; Caplan et al., 2003; Ekstrom et al., 2005; Jacobs et al., Submitted). Recording individual neurons during virtual navigation, we have discovered "place cells" in the human brain. These cells, which are found primarily in the human hippocampus, become active when a given spatial location is being traversed Ekstrom et al. (2003). We also identified several other cellular responses during navigation: cells that become active in response to viewing a salient landmark (from any location), cells that become active when searching for a particular goal location (irrespective of location or view), cells that respond when traveling in a given direction (bearing/heading), and cells that respond along a particular route or path.<<html(
|Fig. 4: Firing-rate map of a right hippocampal cell showing significant place selectivity. Lettered squares (SA,SB,SC) indicate target store locations, white boxes indicate non-target buildings, red lines indicate the subject's trajectory, and the red square indicates regions of significantly high firing rate (all examples, p < 0.01).|