This thesis addresses the hippocampal-orbitofrontal interactions underlying reality filtering of memories or, in other words, how a memory relates to the reality we live in.
Memories are encoded, stored and retrieved through the action of the medial temporal lobe (MTL) (Squire and Zola-Morgan, 1991). The memory trace then contains all the information that was available at the time of encoding and the hippocampus (HC) binds that information into a meaningful representation, which is the memory (Moscovitch et al., 2006). Because the HC is simply indexing information stored in the cortex, it does not contain any information about the current relevance of that representation. One might expect a separate mechanism to suppress representations not pertaining to the current reality from being activated (Nieuwenhuis and Takashima, 2011). In this chapter we will first discuss our findings suggesting that, while the memory trace is encoded through the MTL, it is also filtered rapidly after in the orbitofrontal cortex (OFC), a mechanism called orbitofrontal reality filtering (ORFi). We also argue that this interaction, which relates our thoughts to reality, could be the substrate for later differentiating events we experienced from events we only imagined. ORFi has been supported by findings from confabulating patients with lesion to the OFC, and to further corroborate the model we will discuss our findings from a group of patients with schizophrenia spectrum disorders3 thought to confuse reality despite no apparent lesions.
4.1 Encoding of the memory trace
The initial challenge presented by this thesis was the absence of a reliable electrophysiological marker for the encoding of the memory trace. Indeed, ORFi has a well-established surrogate marker, which is described in chapter 1.2.2.2. – an early frontal potential between 200 and 300 ms and emanating from the OFC (Schnider et al., 2002; Treyer et al., 2003; Schnider, 2008) – but there is no consensus for an equivalent electrophysiological marker of memory.
3 Schizophrenia spectrum disorders include schizophrenia, schizotypal, delusional, and other non-mood psychotic disorders. They are defined in the DSM-V in part by the presence, for a month, of at least two of the following five domains: delusions, hallucinations, disorganized speech, grossly disorganized behavior (including catatonia), and negative symptoms (American Psychiatric Association, 2013).
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46 Earlier studies have identified an electrophysiological dissociation between immediate and delayed memory encoding (Nielsen-Bohlman and Knight, 1994; Kim et al., 2001). As previously discussed in the Introduction chapter (see 1.1.4.), repetition of information improves retention of memories. In a continuous recognition task, information repeated apart in time is however better remembered than information presented in a massed fashion (i.e.
repeated immediately), a mechanism known as the Spacing Effect (Ebbinghaus, 1885;
Greene, 1989). James et al. (2009) found that, at the time of encoding, immediately repeated items induced a specific electrocortical response after 200-300 ms over frontal electrodes reflecting MTL activity. This was later confirmed with depth electrode recording in epileptic patients, which demonstrated hippocampal activity upon immediate repetitions (Nahum et al., 2011b).
In Thézé et al. (2016) we first replicated the results from James et al. (2009) in a different group of healthy subjects. Immediately repeated items elicited a positive frontal potential at about 300 ms associated with increased MTL activity, as determined with source localization. James et al. (2009) suggested that newly presented items initiated a consolidation process and that immediately repeated items benefited from facilitated activation of the memory trace (i.e. faster reaction time). Massed items were overall better remembered than items presented only once, although later recognition was poorer than for delayed items (James et al., 2009). The authors could not specify what neural mechanism the MTL activation reflected but they implied that it might reflect the encoding of the memory trace interfering with offline consolidation. Above all, and of interest to this thesis, it implies that the hippocampal activity during the encoding of the memory also has a surrogate electrophysiological marker.
Following on that hypothesis, Thézé et al. (2016) demonstrated that immediately repeated items were characterized with a transient increase of theta-band coherence in the MTL at 200-400 ms. This observation, congruent with the timing of the MTL activity measured in Thézé et al. (2016) and previous studies (James et al., 2009; Nahum et al., 2011b), also highlights new aspects.
Primarily, the phasic increase of coherence in the MTL was specific to the theta-band frequency. These oscillations, ranging between 3 to 7.5 Hz, are believed to result from cortico-hippocampal feedback loops (Klimesch, 1999; Miller, 2013) and to reflect long distance synchronization between large neuronal assemblies (Von Stein and Sarnthein, 2000).
Human studies have previously described theta oscillation in the MTL, and more particularly in the HC, as a mechanism for long-term memory encoding (Rutishauser et al., 2010;
47 Battaglia et al., 2011; Fell and Axmacher, 2011), but also for maintenance of visual information into working memory (Klimesch et al., 1997; Sauseng et al., 2005; Raghavachari et al., 2006; Fuentemilla et al., 2010). Animal studies also measured increased theta activity associated with long-term memory encoding (Benchenane et al., 2010; Brincat and Miller, 2015). Altogether those findings indicate that increase of theta coherence is reflecting an encoding process of the active memory trace.
James et al. (2009) suggested the MTL-generated potential evoked by immediately repeated stimuli reflects an interference of the consolidation process. This conclusion was drawn from the observation that later recognition of immediately repeated items is poorer than for delayed items, which suggests a less efficient encoding. Strikingly, the increase of coherence measured in Thézé et al. (2016) was significantly stronger in subjects who better remembered immediately repeated items. This increase of coherence also correlated positively with the activity generated in the MTL. Therefore, the MTL source activity and the co-occurring increase of coherence are likely part of a process potentiating memory rather than interfering with it.
It is arguable whether this signal is reflecting a process of encoding of the memory trace or simply its maintenance into short-term memory from the initial presentation. Van Strien et al. (2007) similarly recorded a group of subjects performing an equivalent continuous recognition task with word repetition. They reported an increase of theta power at 250-625 ms in response to immediately repeated stimuli, which were processed faster. They concluded the increase of theta power was reflecting the strength of the memory trace being maintained active in the short-term store. Their analyses were however limited to surface electrodes and thus the conclusions are equivocal (see chapter 2 for a complete explanation).
Moreover a measure of power increase is merely indicative of a larger number of neurons firing synchronously (Klimesch, 1999). In Thézé et al. (2016) we observed that the MTL increase of coherence was targeted at the parietal cortex at 200-400 ms. The parietal lobes have repeatedly been linked to memory retrieval (Cabeza et al., 2008) but more as a control mechanism of memory, notably with theta oscillation (Sauseng et al., 2010). In the presently discussed study (Thézé et al., 2016), coherence to the parietal cortex did not predict performance (i.e. coherence was not stronger if subjects better remembered immediately repeated items), although it correlated with current source density in the MTL. This further implies that the MTL increase of coherence is specifically reflecting the stabilization of the information held into working memory, that is, the encoding of the memory trace. The frontally evoked potential, originating in the MTL and identified by James (2009), thus
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48 reflects the encoding process. This is consistent with the observation that severely amnesic Wernicke-Korsakoff syndrome patients lack this potential (Nahum et al., 2015a).
Altogether, the frontal potential in response to immediately repeated stimuli likely reflects a process of encoding, or at least a process supporting encoding, in the MTL. While it would be desirable to corroborate this finding with a classical encoding paradigm, this potential is probably so far the best indicator of the encoding of a memory trace.
4.2. Memory encoding and orbitofrontal reality filtering
One aim of this thesis was to find a reliable marker of the encoding of the memory trace that was comparable to the surrogate marker of ORFi. Indeed the reality filtering theory has been supported by various studies (Schnider et al., 2000; Schnider et al., 2002; Treyer et al., 2003; Treyer et al., 2006; Wahlen et al., 2011; Bouzerda-Wahlen et al., 2015) with different sets of participants, and systematically identified an electrophysiological signature of what is believed to be the mechanism filtering our thoughts (see chapter 1.2.2.). In the previous chapter we discussed an electrophysiological signal bearing interesting similarities with the marker of ORFi, that is, a positive evoked potential over frontal electrodes at 200-300 ms. In Thézé et al. (2017a) our aim was to directly compare the timing during which the two mechanisms occurred and test the underlying neural interactions.
To do so, we designed a paradigm that combined the experimental tasks of both electrophysiological markers. In two runs of a continuous recognition task, subjects had to indicate the recurrence within an ongoing run of pictures presented again either immediately or after multiple occurrences. Immediate picture recurrence within the first run reflected the encoding of the memory trace and evoked a positive frontal potential at 200-300 ms, which originated in the MTL, as determined with source localization. For clarity purposes this signal will be further referred to as the encoding potential. Pictures first occurrences during the second run, on the other hand, reflected ORFi. Processing of such stimuli also triggered a frontal potential at 200-300 ms, although it was more of an absence of negativity rather than a positive potential. In source localization this potential was associated with OFC activation.
From now on it will be referred to as the ORFi potential.
In addition to replicating previous findings regarding respective potentials, Thézé et al.
(2017a) uncovered that, on average, the encoding potential preceded the ORFi potential by 35 ms, and it was a significant time difference. Corroborating this view, Catenoix et al. (2005) demonstrated that HC stimulation in epileptic patients produced reproducible evoked
49 potentials in the ipsilateral OFC. The latency was around 200 ms, which suggests an indirect polysynaptic pathway; although the authors admitted their method did not allow recordings of very short latencies (<20 ms) and it did not exclude the existence of a monosynaptic pathway.
Indeed, similar in vivo stimulation of rats’ hippocampal CA1 neurons triggered a response in prefrontal pyramidal neurons with a latency of 40 ms (Dégenètais et al., 2003). Moreover, the existence of a monosynaptic pathway going from the HC to the medial prefrontal cortex has been repeatedly demonstrated in the rats (Swanson, 1981; Ferino et al., 1987; Thierry et al., 2000). In fact, OFC is the prefrontal region that has the strongest links with the HC formation (Barbas and Blatt, 1995; Carmichael and Price, 1995; Cavada et al., 2000). Further supporting this idea, Thézé et al. (2017a) calculated inverse solutions of the encoding and ORFi potential at the time of maximum amplitude. The MTL and the OFC were respectively active at that time. In other words, as soon as the MTL was activated, possibly to deliver an encoding signal on the memory trace, the activation of OFC followed.
Evoked potentials and source localization however present arguably weak evidence for an actual interaction between the two regions of interest. Hence, in Thézé et al. (2017a) we calculated the functional connectivity within the brain in response to all stimuli of interest, that is, the stimuli respective to the memory potential and the ORFi potential. Based on the results from Thézé et al. (2016), we expected to find a MTL based increase of theta coherence upon immediately repeated stimuli. We hypothesized that this increase of coherence might be directed at the OFC, which would imply that both structures are firing synchronously.
Indeed, in Thézé et al. (2017a) we measured a significant coherence increase in the MTL area with the rest of the brain in the theta-band frequency range that was specific for immediately repeated items and transiently occurring around 200 ms. Moreover, the OFC was also marked with an increase of coherence with the rest of the brain in the theta frequency, around 200 ms, and specific to stimuli occurring for the first time in the second run (i.e.
stimuli of the ORFi potential). A seed analysis of the coherence showed that both the MTL and the OFC were mutual targets of the theta increase. This implies that both regions are highly synchronized with other regions of the brain when processing the respective stimuli.
To begin with, we shall consider that both regions displayed an increase of coherence in the theta frequency. In chapter 4.1. we already discussed that increase of theta coherence in the MTL has previously been associated with encoding and with maintenance in working memory not only in humans (Rutishauser et al., 2010; Battaglia et al., 2011; Fell and Axmacher, 2011; van Kesteren et al., 2012; Zeithamova et al., 2012) but also in monkeys (Lee et al., 2005). Theta oscillations have traditionally thought to be generated by
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50 hippocampal activity, although they have also been recorded in the prefrontal cortex (Hyman et al., 2005; Jones and Wilson, 2005; Tsujimoto et al., 2006; Benchenane et al., 2010), with a critical role for interaction of the prefrontal cortex with the HC. In fact, it was demonstrated (Siapas et al., 2005) in the rats that prefrontal neurons phase lock best to hippocampal theta rhythm with a delay of approximately 50 ms, which suggests directionality from HC toward PFC neurons, which further supports our findings from the evoked potentials.
In rodents, hippocampal-prefrontal interactions in the theta band coherence are critical for spatial working memory (Floresco et al., 1997; Jones and Wilson, 2005). The two regions, for instance, will be synchronized when evaluating possible rewarding outcomes out of the two possible choice arms in a maze (Johnson and Redish, 2007; Benchenane et al., 2010) where the HC will send contextual information to the prefrontal cortex, which in turn directs the retrieval of memories based on that information with a delay of 20-30 ms (Place et al., 2016). OFC most likely integrates information represented in separate areas of limbic system (Nieuwenhuis and Takashima, 2011) and OFC-MTL interaction illustrates binding of the reactivated memories with the current experience. Building integrated memories that relate to perception enables a predictive function for those memories and, consequently, inferential judgment regarding perception (Zeithamova et al., 2012).
In the rats, Lesburguères et al. (2011) demonstrated that memory encoding in the HC is followed by temporally graded changes in the OFC. When the authors inactivated the HC during the consolidation period, it prevented the development of dendritic spines on OFC neurons and led to impairment of early, but not remote, memories. The interaction of the HC with the OFC is thus crucial for the long-term encoding of the memory trace. It was demonstrated in rats again during spatial working memory tasks (Jones and Wilson, 2005) where theta coordination of both structure allowed for incorporating currently relevant spatial information during encoding. The interactions currently described may have strong implications on various cognitive functions such as reality monitoring, which was described in the introduction (see chapter 1.2.5.).
ORFi during encoding is thought to leave a memory trace, which, upon retrieval, can then be attributed to a real event or a fantasy. That is, encoding during ORFi today allows for reality monitoring tomorrow. It is the memory characteristics established at encoding that provide spatial and temporal contextual details (Johnson and Raye, 1981; Johnson et al., 1993; Mitchell and Johnson, 2009). Indeed, memory encoding is a critical variable for source monitoring capacities, such as reality monitoring, as suggested with functional MRI studies (Davachi et al., 2003; Gonsalves et al., 2004; Kensinger and Schacter, 2005; Sugimori et al.,
51 2014). Deficient ORFi may cause confabulating patients to perceive an event imagined during a discussion as a real event (Schnider et al., 2005b; Chapter 1 in Schnider, 2008). We suggest that MTL-conveyed encoding during OFC-mediated reality filtering provides an efficient explanation for source monitoring functions.
4.3. Orbitofrontal reality filtering and schizophrenia spectrum disorder
In the preceding chapter we explored the hippocampal-orbitofrontal interactions underlying the joint action of memory encoding and reality filtering, which may be crucial for having a sense of whether something we remember was real or was simply imagined, a process that relates to source monitoring. Deficits of monitoring have been described in schizophrenia disorders (Keefe et al., 1999; Brébion et al., 2002) with the positive symptomatology being referred to a default of self-monitoring (Frith, 1995). Brunelin et al.
(2006), for instance, tested hallucinating patients who misattributed words they imagined themselves as words said by the experimenter more frequently than non-hallucinating controls. Hallucinating patients also have more false positives than healthy controls when performing multiple runs of the paradigm used in ORFi studies (Waters et al., 2003; Michie et al., 2005). It suggests that these schizophrenic patients may express difficulties in filtering irrelevant memories, which we just demonstrated may be crucial for reality monitoring, and provide an explanation for symptoms of schizophrenia. Indeed, deficient ORFi, caused by lesions to the OFC, has been demonstrated to result in severe confusion of reality, characterized by confabulation and disorientation (Schnider et al., 2005a; Schnider, 2008).
Reality confusion is also a core feature in schizophrenia spectrum disorders, which are characterized, among other things, by hallucinations and delusions (Cullberg, 2014). These patients are believed to have lost touch with reality and, have been described as having a defect in filtering or gating sensory input (Andreasen et al., 1994). In Thézé et al. (2017b) we explored whether reality confusion in schizophrenic spectrum patients was also associated with disturbed ORFi.
The control group and its schizophrenic counterpart did not differ in their neuropsychological testing results, in the sense that the patient group did not present any substantial cognitive deficit, despite a diagnosis of psychosis for most of them. Both completed two runs of the recognition task testing for ORFi (Schnider et al., 2002) and performed equally well. The patient group, however, in comparison to the control group displayed a reduced frontal potential between 200-300 ms in response to ORFi stimuli.
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52 Failure in processing this kind of stimuli has been a reliable marker of reality confusion in patients with damage to the OFC or directly connected structures (Schnider et al., 1996b, 1996c; Schnider and Ptak, 1999; Nahum et al., 2012). In this study the electrophysiological potential marking ORFi in the patient group had significantly reduced amplitude compared to the control group, the magnitude of which predicted the diagnosis of the disorder: the less positive was the potential, the greater was the likelihood for the patients to be diagnosed with the disorder.
This is not without reminding of the P300, which is a potential evoked at about 300 ms during an auditory oddball paradigm (Polich, 2007; Javitt et al., 2008) or of the mismatch negativity (MMN), which is a negative deflection evoked at about 150-200 ms when a sequence of repetitive auditory stimuli is interrupted by a stimuli that does not relate to the more frequently presented stimuli (Turetsky et al., 2006). Deficits in both electrophysiological potentials are considered to be reliable markers of schizophrenia, which are expressed with reduced amplitude depending on the severity of the symptoms (Mathalon et al., 2000; Bramon et al., 2004; Umbricht and Krljes, 2005). MMN deficits have been linked to abnormalities in the dopaminergic system (Turetsky et al., 2006). The gene 22q is critical for metabolizing dopamine in the prefrontal cortex (Takarae et al., 2009) but mutations to this gene have been linked to risk factors for developing both schizophrenia (Bassett and Chow, 2008) and deficits of MMN (Baker et al., 2005). While the ORFi potential is unmistakably reflecting a different cognitive process from both the P300 and the MMN, it bears electrophysiological similarities to them which suggest a potential role for marking the disorder. Indeed, ORFi is also relying on the dopaminergic system (Schnider et al., 2010; Schnider, 2013). Simply put, reality filtering recurs on the extinction capacity of the OFC (see chapter 1.2.4.), that is, the OFC signals the absence of expected outcomes, a function modulated by the dopaminergic system (Schnider et al., 2000, Schnider, 2008 #377; Schnider et al., 2010) that triggers a frontal electrophysiological potential identical to the ORFi potential (Schnider, 2013). Thus, the dopaminergic abnormalities present in schizophrenia disorders may relate to the deficit
This is not without reminding of the P300, which is a potential evoked at about 300 ms during an auditory oddball paradigm (Polich, 2007; Javitt et al., 2008) or of the mismatch negativity (MMN), which is a negative deflection evoked at about 150-200 ms when a sequence of repetitive auditory stimuli is interrupted by a stimuli that does not relate to the more frequently presented stimuli (Turetsky et al., 2006). Deficits in both electrophysiological potentials are considered to be reliable markers of schizophrenia, which are expressed with reduced amplitude depending on the severity of the symptoms (Mathalon et al., 2000; Bramon et al., 2004; Umbricht and Krljes, 2005). MMN deficits have been linked to abnormalities in the dopaminergic system (Turetsky et al., 2006). The gene 22q is critical for metabolizing dopamine in the prefrontal cortex (Takarae et al., 2009) but mutations to this gene have been linked to risk factors for developing both schizophrenia (Bassett and Chow, 2008) and deficits of MMN (Baker et al., 2005). While the ORFi potential is unmistakably reflecting a different cognitive process from both the P300 and the MMN, it bears electrophysiological similarities to them which suggest a potential role for marking the disorder. Indeed, ORFi is also relying on the dopaminergic system (Schnider et al., 2010; Schnider, 2013). Simply put, reality filtering recurs on the extinction capacity of the OFC (see chapter 1.2.4.), that is, the OFC signals the absence of expected outcomes, a function modulated by the dopaminergic system (Schnider et al., 2000, Schnider, 2008 #377; Schnider et al., 2010) that triggers a frontal electrophysiological potential identical to the ORFi potential (Schnider, 2013). Thus, the dopaminergic abnormalities present in schizophrenia disorders may relate to the deficit