RESUMEN
BACKGROUND: Direct electrical stimulation of the amygdala can enhance declarative memory for specific events. An unanswered question is what underlying neurophysiological changes are induced by amygdala stimulation. OBJECTIVE: To leverage interpretable machine learning to identify the neurophysiological processes underlying amygdala-mediated memory, and to develop more efficient neuromodulation technologies. METHOD: Patients with treatment-resistant epilepsy and depth electrodes placed in the hippocampus and amygdala performed a recognition memory task for neutral images of objects. During the encoding phase, 160 images were shown to patients. Half of the images were followed by brief low-amplitude amygdala stimulation. For local field potentials (LFPs) recorded from key medial temporal lobe structures, feature vectors were calculated by taking the average spectral power in canonical frequency bands, before and after stimulation, to train a logistic regression classification model with elastic net regularization to differentiate brain states. RESULTS: Classifying the neural states at the time of encoding based on images subsequently remembered versus not-remembered showed that theta and slow-gamma power in the hippocampus were the most important features predicting subsequent memory performance. Classifying the post-image neural states at the time of encoding based on stimulated versus unstimulated trials showed that amygdala stimulation led to increased gamma power in the hippocampus. CONCLUSION: Amygdala stimulation induced pro-memory states in the hippocampus to enhance subsequent memory performance. Interpretable machine learning provides an effective tool for investigating the neurophysiological effects of brain stimulation.
Asunto(s)
Epilepsia del Lóbulo Temporal , Memoria , Amígdala del Cerebelo/fisiología , Hipocampo/fisiología , Humanos , Aprendizaje Automático , Memoria/fisiologíaRESUMEN
Recently we provided data showing that amygdala stimulation can ameliorate spatial memory impairments in rats with lesion in the fimbria-fornix (FF). The mechanisms for this improvement involve early gene expression and synthesis of BDNF, MAP-2, and GAP43 in the hippocampus and prefrontal cortex. Now we have studied which brain structures are activated by the amygdala using c-Fos as a marker of neural activation. First, we studied neuronal activation after tetanic stimulation to the amygdala in intact rats. We then carried out a second study in FF-lesioned rats in which the amygdala was stimulated 15 min after daily spatial memory training in the water maze. Our results showed that amygdala stimulation produces widespread brain activation, that includes cortical, thalamic, and brain stem structures. Activation was particularly intense in the dentate gyrus and the prefrontal cortex. Training in the water maze increased c-Fos positive nuclei in the dentate gyrus of the hippocampus and in medial prefrontal cortex. Amygdala stimulation to trained FF-lesioned rats induced an increase of neural activity in the dentate gyrus and medial prefrontal cortex relative to the FF-lesioned, but not stimulated group, like the c-Fos activity seen in trained control rats. Based on these and previous results we explain the mechanisms of amygdala reinforcement of neural plasticity and the partial recovery of spatial memory deficits.