In this article we develop the concept that the hippocampus and the midbrain dopaminergic neurons of the ventral tegmental area (VTA) form a functional loop. Activation of the loop begins when the hippocampus detects newly arrived information that is not already stored in its long-term memory. The resulting novelty signal is conveyed through the subiculum, accumbens, and ventral pallidum to the VTA where it contributes (along with salience and goal information) to the novelty-dependent firing of these cells. In the upward arm of the loop, dopamine (DA) is released within the hippocampus; this produces an enhancement of LTP and learning. These findings support a model whereby the hippocampal-VTA loop regulates the entry of information into long-term memory.

Long-term potentiation (LTP) in the CA1 region of the hippocampus has been the primary model by which to study the cellular and molecular basis of memory. Calcium/calmodulin-dependent protein kinase II (CaMKII) is necessary for LTP induction, is persistently activated by stimuli that elicit LTP, and can, by itself, enhance the efficacy of synaptic transmission. The analysis of CaMKII autophosphorylation and dephosphorylation indicates that this kinase could serve as a molecular switch that is capable of long-term memory storage. Consistent with such a role, mutations that prevent persistent activation of CaMKII block LTP, experience-dependent plasticity and behavioural memory. These results make CaMKII a leading candidate in the search for the molecular basis of memory.

Theta and gamma frequency oscillations occur in the same brain regions and interact with each other, a process called cross-frequency coupling. Here, we review evidence for the following hypothesis: that the dual oscillations form a code for representing multiple items in an ordered way. This form of coding has been most clearly demonstrated in the hippocampus, where different spatial information is represented in different gamma subcycles of a theta cycle. Other experiments have tested the functional importance of oscillations and their coupling. These involve correlation of oscillatory properties with memory states, correlation with memory performance, and effects of disrupting oscillations on memory. Recent work suggests that this coding scheme coordinates communication between brain regions and is involved in sensory as well as memory processes.

Psychophysical measurements indicate that human subjects can store approximately seven short-term memories. Physiological studies suggest that short-term memories are stored by patterns of neuronal activity. Here it is shown that activity patterns associated with multiple memories can be stored in a single neural network that exhibits nested oscillations similar to those recorded from the brain. Each memory is stored in a different high-frequency ("40 hertz") subcycle of a low-frequency oscillation. Memory patterns repeat on each low-frequency (5 to 12 hertz) oscillation, a repetition that relies on activity-dependent changes in membrane excitability rather than reverberatory circuits. This work suggests that brain oscillations are a timing mechanism for controlling the serial processing of short-term memories.

Long-term potentiation (LTP) of synaptic strength occurs during learning and can last for long periods, making it a probable mechanism for memory storage. LTP induction results in calcium entry, which activates calcium–calmodulin-dependent protein kinase II (CaMKII). CaMKII subsequently translocates to the synapse, where it binds to the NMDA-type glutamate receptors and produces potentiation by phosphorylating principal and auxiliary subunits of AMPA-type glutamate receptors. These processes all are localized to stimulated spines and account for the synapse specificity of LTP. In the later stages of LTP, CaMKII has a structural role in enlarging and strengthening the synapse.

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Many risk genes interact synergistically to produce schizophrenia and many neurotransmitter interactions have been implicated. We have developed a circuit-based framework for understanding gene and neurotransmitter interactions. NMDAR hypofunction has been implicated in schizophrenia because NMDAR antagonists reproduce symptoms of the disease. One action of antagonists is to reduce the excitation of fast-spiking interneurons, resulting in disinhibition of pyramidal cells. Overactive pyramidal cells, notably those in the hippocampus, can drive a hyperdopaminergic state that produces psychosis. Additional aspects of interneuron function can be understood in this framework, as follows. (i) In animal models, NMDAR antagonists reduce parvalbumin and GAD67, as found in schizophrenia. These changes produce further disinhibition and can be viewed as the aberrant response of a homeostatic system having a faulty activity sensor (the NMDAR). (ii) Disinhibition decreases the power of gamma oscillation and might thereby produce negative and cognitive symptoms. (iii) Nicotine enhances the output of interneurons, and might thereby contribute to its therapeutic effect in schizophrenia.

In a previous paper, a model was presentedshowing how the group of Ca2+/calmodulin-dependent protein kinase II molecules contained within a postsynaptic density could stably store a graded synaptic weight. This paper completes the model by showing how bidirectional control of synaptic weight could be achieved. It is proposed that the quantitative level of the activity-dependent rise in postsynaptic Ca2' determines whether the synaptic weight will increase or decrease. It is further proposed that reduction of synaptic weight is governed by protein phosphatase 1, an enzyme indirectly controlled by Ca2+ through reactions involving phosphatase inhibitor 1, cAMP-dependent protein kinase, calcineurin, and adenylate cyclase. Modeling of this biochemical system shows that it can function as an analog computer that can store a synaptic weight and modify it in accord with the Hebb and anti-Hebb learning rules.In many types of neural network models, learning occurs by the bidirectional modification of synaptic weights according to simple activity-dependent rules that resemble the Hebb and anti-Hebb rules described below. Such networks can store multiple memories (1), develop selectivity for input patterns (2), find optimum solutions (3), and organize topographic maps (4). These theoretical results suggest that understanding how synaptic weights are stored and modified is important for understanding brain function in general, and learning and memory in particular.The best experimental evidence for activity-dependent changes in synaptic weight comes from work in the hippocampus (5) demonstrating that high-frequency stimulation of a group of excitatory synaptic inputs leads to a long-term potentiation (LTP) of the synaptic efficacy of the stimulated synapses. Analysis (6) of LTP in the CA1 region of the hippocampus has shown that the process is governed by the Hebb rule (7); the synaptic weight of a synapse increases when there is both presynaptic activity at that synapse and a critical level of postsynaptic depolarization. Induction of LTP involves the N-methyl-D-aspartate (NMDA) class of glutamate-activated channels in the postsynaptic membrane (8). These channels open only if there is both presynaptic release of glutamate and substantial postsynaptic depolarization (9, 10). Opening of the NMDA channel leads to an influx of Ca2+ (11,12) that triggers the increase in synaptic weight (13,14). The final expression of the increase in synaptic weight is enhancement of the synaptic current carried by the non-NMDA class of glutamate-activated channels (15).Fundamental questions about how synaptic weights are stored and modified remain unanswered. Theoretical considerations suggest that there must be processes that decrease synaptic weight (16) when presynaptic and postsynaptic activity do not occur together. Such processes have in fact been observed experimentally (see below) and have been labeled "anti-Hebb" processes (17), but almost nothing is known about their mechanism. Furthermore, the central problem of memory stora...