Using whole brain centrality metrics in a multivariate framework, we were able to show that ketamine induces a robust, predictable change in the functional connectivity pattern in the human brain, producing a shift from a cortically centred to a sub-cortically centred brain state. Risperidone pre-treatment significantly modulated the ketamine-induced centrality changes; however, lamotrigine did not. The distinct modulatory effects of these two compounds on ketamine-induced DC changes stands in contrast to their similar effects in attenuating the ketamine-induced BOLD amplitude changes.

Ketamine infusion

Consistent with previous work, during a task-free acute ketamine challenge, a distributed pattern of functional connectivity changes were observed across the brain. On contrasting ketamine with placebo, nodes in the basal ganglia and cerebellum were predominantly weighted in favour of the ketamine group whilst nodes in the frontal, occipital, parietal, temporal and medial temporal lobe regions were weighted for the placebo state. Post hoc univariate tests confirm the directionality of these effects, revealing decreasing cortical centrality and an increase in centrality of the cerebellum and basal ganglia in the ketamine state relative to the control.

Previous studies have revealed findings consistent with observations from this study. An overall increase in “global connectivity” as a result of ketamine infusion was observed in healthy volunteers (Driesen et al. 2013). Regions exhibiting the greatest increase in this global connectivity for ketamine included the thalamus, parietal regions and cerebellum. Whilst our analysis is multivariate, it is noteworthy that the same regions are present in the pattern of features describing ketamine and have increased degree centrality in relation to placebo. Our analysis extends these previous works, revealing the pattern on changes across the whole brain between groups.

Ketamine has also been reported to strongly affect the connectivity of cerebellar, visual, auditory, somatosensory and subcortical regions in relation to pre-defined networks of interest (Niesters et al. 2012). The cerebellum was shown to have increased connectivity in relation to visual networks as well as the intra-network connectivity of the visual cortex when under the influence of ketamine. Furthermore, the thalamus, PFC, temporal cortex and cingulum were shown to have decreasing connectivity in relation to the auditory and somatosensory network.

The multivariate results presented here provide an alternative perspective on the effect of acute ketamine on whole-brain connectivity. The task-free connectivity organisation of the brain is radically altered by acute ketamine with both increases and decreases in the centrality pattern of the brain. This is supported by previous studies demonstrating ketamine administration can cause long-range decoupling of neural population activity in mouse neocortical slices and has been shown to cause both increases and decreases in connectivity, e.g. (Dawson et al. 2013). We can summarise the observed effects of acute ketamine in humans as a shifting of the pattern of connectivity from a cortically centred state to a sub-cortically centred state. It is possible that cortical regions have a global reduction in connectivity with the rest of the brain, resulting in a reduction in the connectivity of cortical hubs; alternatively, it is possible that dominant regional couplings are reduced, resulting in a more equally distributed connectivity. Both mechanisms would result in the DC pattern observed under ketamine. The presented methodology is not designed to identify changes in individual connections; instead, we reveal consistent patterns of DC change across the whole brain which reveals a subcortical contribution for the ketamine connectivity pattern.

The observed pattern of disconnectivity of the cortical hubs is consistent with many of the experiential effects observed with ketamine; interruption of connectivity between cortical hubs would be predicted to result in a reduction contextual processing, impaired memory, spatial representation and sensorimotor processing. Whilst not a phenocopy of the disorder, ketamine has been used as pharmacological model for schizophrenia which has been shown to exhibit similar alterations in connectivity, notably a reduction in high DC cortical hubs (Rubinov et al. 2009) and wide spread disconnections across the brain (Liang et al. 2006; Lynall et al. 2010).

The main effects of ketamine at sub-anaesthetic doses are typically attributed to its blockade of the NMDA receptor (Driesen et al. 2013). It has high affinity for NMDA and D 2 receptor sites as well as a slightly lower affinity for the 5-HT 2A receptor, muscarinic and opioid receptors although these are thought to have notable effects at higher doses only (Hirota et al. 1999; Narita et al. 2001). A possible mechanism by which ketamine effects connectivity changes is through interruption of NMDAR-mediated transmission, namely the known cortical microcircuit effects where parvalbumin-positive GABAergic interneurons disinhibited by ketamine (Homayoun and Moghaddam 2007). Microdialysis confirms the NMDA antagonists PCP and MK-801 increase extracellular GABA levels. These interneurons inhibit pyramidal cells and synchronise their oscillations (Homayoun and Moghaddam 2007). The disinhibition of these GABAergic interneurons may result in impaired pyramidal synchrony and hence in decreased connectivity of cortical nodes, leading to the observed pattern of centrality. It is suggested that the lateral posterior pulvinar in the thalamus may strongly contribute to pyramidal synchrony (Shumikhina and Molotchnikoff 1999) which may explain its inclusion in the pattern for ketamine exhibiting increased centrality. Alternatively, if ketamine increases cortical connectivity globally whilst reducing strong regional connections, this may also result in increased centrality of the basal ganglia and cerebellum whilst reducing cortical centrality.

The radical alteration of the pattern of centrality during a task-free ketamine infusion has not been demonstrated previously and suggests a complex network reorganisation underpinning the effect of ketamine, even at the low dose administered in this study. This reorganisation is a plausible candidate for the variety of effects produced by ketamine, such as perceptual distortion (via parietal and visual regions as well as cerebellar and basal ganglia timing nodes), cognitive disorganisation (via fronto-patietal nodes) and anhedonia (via striatal and ventromedial nodes). The important contribution of the current study is to inform on the reorganisation of brain networks by ketamine and to what degree these can be pharmacologically modulated by different pharmacological mechanisms. In order to facilitate multiple administrations of ketamine, doses were kept relatively low; as such, we did not observe any strong and consistent subjective effects. Furthermore, the sparseness and inconsistencies of participant subjective responses, which were collected, prohibited investigation of correlation between functional connectivity effects and subjective ratings. Replication using higher doses producing stronger subjective changes in all participants would be important and also allow testing of the relationship between the multivariate changes in network patterns with the profiles of changes in subjective reporting of drug effects.

Lamotrigine treatment

Lamotrigine causes a reduction in glutamate release primarily through Na+ channel modulation; we hypothesised that this would partially counter the downstream glutamatergic effects of ketamine, thus attenuating any ketamine-induced changes in functional connectivity. Indeed, it has been demonstrated that lamotrigine pre-treatment attenuates the ketamine BOLD effect (Deakin et al. 2008; Doyle et al. 2013a; b). Furthermore, it has been suggested that ketamine’s effect on functional connectivity may reflect glutamatergic modulation (Duncan et al. 2011). In contrast to our previous findings on the ketamine-induced BOLD signal, we found no significant effects of lamotrigine on the pattern of DC in the brain. The administered dose of lamotrigine (300 mg) is clinically effective and the data analysed is the same as that used in our previous study (Doyle et al. 2013a; b) where clear effects on the local BOLD signal were demonstrated. Instead, our combined results show that lamotrigine induces an amplitude change in signal rather than affecting the coupling between regions; although we cannot preclude more subtle, localised changes in connectivity which our method which interrogates whole brain DC patterns would be insensitive. This lack of DC modulation by lamotrigine is further supported by the ordinal regression of saline, lamotrigine + ketamine and ketamine conditions, where we did not observe an ordinal progression between classes. This is consistent with our conclusion that lamotrigine does not attenuate the ketamine-induced pattern of DC. The strong confusion between the lamotrigine + ketamine and ketamine conditions as observed using binary classification whereby the discrimination between the lamotrigine + ketamine conditions was not significant (Table 3) and for ordinal regression (Table 5) whereby ~41 % of the lamotrigine + ketamine cases were classified as ketamine.

These results have important mechanistic implications for the ketamine-induced connectivity response and support the conclusion that lamotrigine pre-treatment has a similar effect to placebo on ketamine-induced DC. Furthermore, since lamotrigine, which block glutamate release, does not significantly modulate the ketamine-induced effects then this suggests that the observed pattern of hub connectivity induced by ketamine reflects NMDAR antagonism per se rather than downstream glutamatergic effects at non-NMDA sites. Instead, this would favour the NMDA blockade of ketamine as responsible for the observed connectivity changes. This proposal could be confirmed in preclinical experiments using specific NMDA subunit antagonists and non-NMDA antagonists for the AMPA and kainate receptors.

Risperidone treatment

Risperidone (2 mg) is expected to achieve high occupancy of 5-HT 2A and D 2 receptors (Nyberg et al. 1999) and reduces glutamate levels downstream through 5-HT 2A antagonism. Furthermore, risperidone has also been reported to potentiate NMDAR function directly (Konradsson et al. 2006). Given this profile, we expected that risperidone pre-treatment would attenuate the pattern of DC induced by ketamine.

Indeed, our observations indicate that, in contrast to lamotrigine, risperidone modulates the effect of ketamine resulting in a pattern of DC distinct to both ketamine and saline. The classification maps for ketamine compared to saline and ketamine compared to ris + ketamine also reveal a strong overlap in the spatial distribution, but not amplitude, of weights with the exception of occipital regions. This is consistent with risperidone pre-treatment reversing the ketamine-induced node strength changes. Comparing the pre- and post-infusion conditions for ketamine pre-treated with risperidone reveal risperidone effects some more subtle changes that did not achieve statistical significance. Direct comparison of the ketamine and ris + ketamine states reveal strong effects of the risperidone pre-treatment on the ketamine-induced pattern of DC which appear to oppose the ketamine effect. Furthermore, the ORGP results suggest risperidone does not attenuate the ketamine DC response in an ordinal manner; instead, the combined results support the conclusion that risperidone may have an opposing effect on the ketamine response.

We theorise that it is the twofold mechanism of risperidone acting upon ketamine that is responsible for the observed DC effects. It is likely that the potentiation of the NMDAR is the primary mechanism due to the dissimilarity in resultant effects between risperidone and lamotrigine pre-treatment. Our results are suggestive that risperidone may interact with, and in opposition to, the ketamine resulting in a pattern of DC dissimilar to that of ketamine; the dissimilarity from the saline state and ordinal regression results preclude a linear attenuation effect of risperidone on ketamine. These observations may be predominantly due to serotonergic effects; however, further work is required using a compound with selective 5-HT 2A binding.

In addition to the NMDA receptor, ketamine also has affinity for other receptors including dopamine, D2 and opioid receptors, particularly at high doses, effects can also be elicited through downstream serotonergic and muscarinic receptors (Hirota et al. 1999; Narita et al. 2001). Whilst we cannot preclude effects at other receptors contributing to our findings, we would favour a major contribution from glutamatergic effects. The opposing effects of ketamine and risperidone in the striatum may conceivably be related to their opposing effects at the D2 receptor, where risperidone acts as an antagonist and ketamine an agonist. The use of selective compounds would be required to understand the contribution of individual receptor types to the observed pattern of effects.

Stability of pattern recognition method in the absence of pharmacological intervention

Importantly, our methodology did not detect changes in connectivity pattern when no pharmacological stimulus was applied. Comparisons between pre-infusion scans from the two oral placebo sessions (PLA + SAL vs. PLA + KET), as well as between the pre- and post-infusion scans from the saline infusion session (PLA + SAL), both revealed no significant differences with classification accuracies approximating chance level. This test-retest stability provides confidence in our interpretation of the effects of ketamine and its modulation by risperidone and lamotrigine as reflecting the pharmacological action of these interventions.

Limitations

The results presented here provide an informative insight into the mechanisms of effect of ketamine on the human brain; however, the limitations of this analysis must also be considered. The use of graph theory combined with machine learning is a novel approach; it provides a principled means of investigation pharmacological compounds on the human brain. The use of centrality, whilst providing an intuitive measure of regional connectedness and providing an elegant solution to the interpreting spatial patterns of discrimination, prohibits investigation into specific regional coupling. As such, this methodology is insensitive to subtle changes in regional coupling which may be induced by the administered compounds. Univariate methods (Niesters et al. 2012) are available for testing hypotheses about specific connections, but these might also be more sensitive to non-pharmacological effects. Our choice of examining the patterns of change across the brain was motivated by the widespread expression of NMDA receptors.

The use of a single connectivity metric and temporal scale is a further limitation. The use of correlation allows for the identification of positive and negative synchronous relationships between regions, however, is naive to phase-delayed and non-linear relationships between regions which are likely to exist in a complex biological system such as the brain. By comparing the results of analysis using both correlation and a phase insensitive measures such as coherence, it may be possible to infer the effects of ketamine on BOLD signal synchronisation between regions. It is likely that analysis performed using different windowing scales would provide further insight into the effects of ketamine on the dynamics of connectivity in the human brain.

The use of degree centrality provides an initial investigation into the connectivity effects of ketamine in the brain. However, in order to generate a complete view of the connectivity effects of ketamine, a range comprehensive range of measures should be compared. Several graph theory metrics exist informing differential aspects of function connectivity; however, many of these measures are highly correlated and present challenges in biological interpretation. Further investigation is required in order to identify an optimal set of orthonormal connectivity measure suitable for use in connectivity analysis which provides a broad overview of connectivity effects.