1 Division of Neurosurgery and , 2 Department of Psychiatry & Biobehavioral Sciences, UCLA School of Medicine, Los Angeles, CA 90095, USA and , 3 Functional Neurosurgery Unit, Tel-Aviv Medical Center and Sackler School of Medicine, Tel-Aviv University, Tel-Aviv, Israel
Itzhak Fried, Division of Neurosurgery, Box 957039, UCLA School of Medicine, Los Angeles, CA 90095-7039, USA. Email: ifried{at}mednet.ucla.edu.
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Abstract |
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Introduction |
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In this study we examined the activity of neurons in the human hippocampus, amygdala and entorhinal cortex during encoding and retrieval of complex visual stimuli. We utilized a rare opportunity to perform single unit recordings in awake and conscious subjects who were able to declare their memories. We asked the following questions: Are there differences in the firing characteristics of single neurons during encoding compared with recognition and are there differences among the hippo-campus, amygdala and entorhinal cortex with respect to the neuronal activity during these memory processes? In this study we show that an important clue can be found in the distribution of excitatory and inhibitory responses of single neurons in the various regions of the MTL.
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Materials and Methods |
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We conducted single unit recording in 20 patients with intractable epilepsy who underwent implantation of intracranial electrodes in order to identify the seizure focus for possible surgical resection. All patients except one were right-handed. Twelve patients underwent the sodium amobarbital test (Wada and Rasmussen, 1960). Two were found to have right-sided dominance for language (including the left-handed patient), nine had left-hemisphere dominance for language and one had bilateral representation of language function. All eight patients who did not have the Wada test were right-handed, and for comparison of neurons in the dominant versus nondominant hemisphere it was assumed that in these patients the left hemisphere was dominant for language function.
Electrode Placement
The technique of electrode placement and single unit recordings in these patients has been described in detail in previous publications (Fried et al., 1997, 1999
; Kreiman et al., 2000a
,b
). The sites of electrode implantation were selected based exclusively on clinical criteria. Electrodes were placed stereotactically, guided by magnetic resonance imaging (MRI) and cerebral angiography. Targets included the hippocampus, entorhinal cortex and the basolateral nuclear group of the amygdala (Fig. 1
). Each electrode consisted of a flexible polyurethane probe containing nine 40 µm platinumiridium microwires protruding ~4 mm into the tissue beyond the tip of the electrode. Following electrode placement the patient was monitored on the ward for a period of 13 weeks until a sufficient number of spontaneous seizures had been recorded. MRI confirmed the locations of the electrodes (Fig. 1
).
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Subjects underwent two sessions of memory testing (Fig. 2). In the first session (encoding) faces and objects were presented to be remembered. The faces were those of eight actors each depicting seven different emotional expressions (Eckmann and Friesen, 1976
). Objects were single common household items. Fifty-six faces and 42 objects were presented in an intermixed fashion in a single list that was presented once (in four patients) or twice (in 16 patients). Each stimulus was presented for a duration of 1 s, with an interstimulus delay of 45 s. One to 12 h later subjects underwent a recognition session where they were shown a series of 165 stimuli (94 faces and 71 objects), which included previously presented stimuli as well as novel faces and objects. Each stimulus was presented for 1 s before a question mark appeared below the picture, signaling the subject to respond with a key press (yes vs no) whether they had seen the face or object during the encoding session (Fried et al., 1997
). The research was conducted according to protocol approved by an Institutional Review Board, with subject informed consent.
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Data from each of the recorded microwires were amplified and high-pass filtered (300 Hz to 10 kHz), A/D converted and stored for spike sorting using Experiment Workbench data acquisition software (Datawave, Denver, CO, USA). Spike sorting was carried out off-line as previously described (Fried et al., 1997, 1999
). Spikes from single neurons were discriminated from the extracellular recordings based on action potential amplitude, duration, slope and other parameters of waveform morphology, using a manual cluster cutting method implemented in Datawave. Nevertheless, it should be pointed out that some units could possibly have had signals from more than one cell.
It is important to note that the recognition task was carried out 112 h after the encoding task. It is therefore likely that some cells recorded during encoding were lost, and other cells that were not detected during encoding became active during the recognition task. We therefore made no assumption of recording from any neuron during both encoding and recognition. Also, our technique picks up only stimulus-related changes and not task-specific changes, which would require direct comparison of encoding versus recognition in the same neuron. Such direct comparison requires different paradigms (Cameron et al., 2001).
Data Analysis
For data analysis, spike counts were obtained for 100 ms bins and collapsed across 1 s episodes: the second preceding stimulus onset (T0), the second of stimulus presentation (T1), and the following second (T2). The choice of 1 s is based on long-term potentiation (LTP) and episode formation timescale as discussed by Trevis and Rolls (Trevis and Rolls, 1994). We have previously shown that stimulus-selective responses of medial temporal neurons can be discerned beyond the duration of stimulus presentation (Fried et al., 1997
). The response of each cell to a stimulus during a specific task condition was evaluated by a two-tailed t-test comparing the spike counts during T1 or T2 against the preceding baseline (T0). A criterion level of P = 0.05 was used. The response was termed excitatory when it was significantly higher than the prestimulus baseline, and inhibitory when it was lower.
A neuron was considered selective for a particular stimulus category (i.e. faces or objects) if (i) the activity during T1 or T2 was significantly different from baseline activity, (ii) the neuron's activity in response to the other category was not significantly different from baseline (in the same direction), and (iii) the response to the preferred category was significantly different from the response to the other stimulus category (by a two-tailed t-test).
For each unit, the responses to faces (discharge rate during T1 or T2, corrected for the preceding 1 s baseline) were subjected to analysis of variance (ANOVA) to evaluate the relationship between the response and stimulus features, i.e. emotional expression and gender of faces. We considered a unit discriminant if one of the factors (i.e. gender or expression) or their interaction was significant (P < 0.05) during T1 and/or T2. The inclusion of T2 data was based on the observation that MTL neurons respond to specific stimulus features well beyond the first 1000 ms of stimulus presentation (Fried et al., 1997).
To evaluate the relationship between discharge rate and recognition performance, the data for each stimulus were segregated into one of two bins: correct recognition and incorrect recognition. For neuronal activity during retrieval this simply meant looking at the activity of the neuron during correct or incorrect recognition. For activity during encoding, the responses had to be classified into one of two bins: responses to stimuli that were later successfully recognized (during retrieval) and responses to those stimuli that were not subsequently recognized. A separate repeated measure ANOVA was carried out to evaluate the relationship between discharge rate (during encoding or recognition) and the performance during recognition (i.e. correct vs incorrect key responses). The relationship between firing rate and performance was considered significant if performance or its interaction with stimulus type (faces or objects) and/or time was significant. A neuron was considered performance-selective during recognition if (i) the response (during T1 and/or T2) of the neuron during correct performance was different from the response during incorrect performance and (ii) the response of the neuron was significant either during correct retrieval or during incorrect retrieval, or during both if the responses were of opposite sign. For the neuron to be considered performance selective during encoding (i.e. performance predictive) we applied these same criteria for the activity of the neuron during stimulus encoding based on the subsequent performance of recognizing those stimuli during retrieval.
The proportion of units in a region showing relevant responses were compared across regions, stimuli or tasks, using chi-square methods with exact permutational P values (Statxact, Cytel Inc., Cambridge, MA, USA). McNemar's test was used to compute P values for paired comparisons. For partially paired comparisons, a logistic model allowing correlations was used (SAS procedure GENMOD, SAS Inc., Cary, NC, USA).
It should be pointed out that generalization about normal neuronal function from recordings in patients with epilepsy is a potential limitation; however, most of the units recorded in this study (91.5%) were contralateral to or outside the focus of seizure onset. For responsive neurons (to faces), spontaneous firing rates were compared between the hemisphere with the epileptogenic region and the contralateral hemisphere, and there were no significant differences (2.9 and 4.2 Hz for the epileptogenic and normal hemispheres respectively; P = 0.201). There were also no significant hemispheric differences in the firing rates of these neurons during T1 or during T2 with respect to baseline between the two hemispheres (P = 0.42 and 0.89 for T1 and T2, respectively, using independent t-test comparison).
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Results |
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Encoding of Faces
During encoding of faces 25.3% of the neurons responded significantly to faces in the second of stimulus presentation (T1). There was no significant difference in the percentage of responding units in the amygdala (28.3%), hippocampus (24.7%) and entorhinal cortex (24.4%; 2 = 0.26, d.f. = 2, P = 0.88). However, there were significant differences in the proportions of units responding with increased firing rate (excitatory responses) and decreased firing rate (inhibitory responses) (Fig. 3
, Table 1
). In the amygdala faces evoked only excitatory responses (Fig. 4b
), whereas in the hippocampus and entorhinal cortex, 62.5% and 50% of the responding neurons, respectively, were inhibited by face stimuli (
2 = 13.85; d.f. = 2; P = 0.001; examples in Fig. 4a
). Hippocampal neurons typically responded with a decrease in activity, or even complete silence, that often outlasted stimulus presentation by several hundred milli-seconds (46.7% of inhibited neurons; Fig. 6c
). As for the entorhinal cortex, only in 10% of neurons inhibited by faces did suppression of activity outlast stimulus presentation. The predominance of excitatory responses in the amygdala during encoding (13/46 excitatory and 0 inhibitory) was present only during the first second of stimulus presentation. Later (during T2) there were less neurons responding to faces, and both inhibitory and excitatory responses were observed (Table 1
).
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Recognition of Faces
During recognition, 32.2% of MTL neurons responded to faces. The proportion of neurons responding to faces during recognition was greater in the hippocampus (41.1%) and entorhinal cortex (33.3%) than in the amygdala (11.4%; 2 = 9.8; d.f. = 2; P = 0.0075; Fig. 3
). The proportion of responsive hippocampal neurons was greater during recognition than during encoding (41.1% vs 24.7%;
2 = 5.14, P = 0.023), an increase that can be accounted for by the rise in the number of neurons with inhibitory responses. The percentage of hippocampal neurons with inhibitory responses doubled during recognition (31.5% of all hippocampal neurons) compared to encoding (15.5%, Fig. 3
). Considering only the responding hippocampal units, 76.7% had inhibitory responses. A similar pattern, although less robust, was apparent in the entorhinal cortex (65.2%).
Encoding of Objects
During encoding, 25.3% of the cells responded significantly to object stimuli (during the second of stimulus presentation), the same percentage of cells as during encoding of faces (Fig. 3). Only 8% of the units responded significantly to both faces and objects. Of MTL cells responding to objects, a substantial proportion (33.3%) had decreased firing rate below prestimulus baseline. The difference between encoding of faces and objects was not in the total number of responding cells, but in the distribution of cells with excitatory and inhibitory responses. In the hippocampus and entorhinal cortex the relative prevalence of neurons with inhibitory responses was higher for faces (e.g. in the hippocampus, 62.5% and 27.3% for faces and objects, respectively;
2 = 6.20, d.f. = 1, P = 0.013; Fig. 3
).
Recognition of Objects
During recognition, 35% of the units responded to objects, a proportion not significantly different from that responding to faces (32.2%). As noted for faces, the increase in proportion of units responding during recognition compared to encoding could be accounted for by a two-fold increase in number of neurons with inhibitory responses (8.4% during encoding and 16.4% during retrieval) (Fig. 3). As in encoding, the percentage of cells with inhibitory responses was higher for faces than objects in the hippocampus and entorhinal cortex (e.g. in the hippocampus 76.7% and 43.5% for faces and objects, respectively;
2 = 8.45, d.f. = 1, P = 0.0036), whereas in the amygdala fewer cells responded to faces than objects (11.4% vs 40%;
2 = 6.73, d.f. = 2, P = 0.0094).
We found no significant difference between the left and right side of the brain in the proportion of cells with excitatory, inhibitory and null responses in any of the three regions studied.
Selective Responses
We considered a neuron selective for a particular stimulus category (i.e. faces or objects) if (i) the activity during the first second of stimulus presentation (T1) or the ensuing second (T2) was significantly different from the baseline activity, (ii) the neuron's activity in response to the other category was not significantly different from baseline (in the same direction), and (iii) the response to the preferred category was significantly different from the response to the other stimulus category. During encoding there were altogether 32 MTL neurons (14.2%) that fulfilled these stringent criteria: 12 selective to faces, 18 to objects and two responding to both but with opposite responses (inhibitory to faces, excitatory to objects). All the selective responses to faces in the hippocampus and entorhinal cortex were inhibitory (nine neurons) and in the amygdala were excitatory (five neurons; example Fig. 4b). The responses to objects in the hippocampus and entorhinal cortex were mostly excitatory (14 of 16 neurons), and in the amygdala all inhibitory (although only three neurons responded).
During recognition there were 32 selective units (18%), seven selective for faces, 15 for objects, and 10 responding with opposite signs to these two categories [eight of these had inhibitory responses to faces and excitatory to objects (Fig. 5a), and two responded with the opposite pattern (Fig. 5b
)]. In the hippocampus and entorhinal cortex, 12 neurons responded to faces with inhibition of firing rate and three with excitation, whereas 22 responded to objects with excitation and only one with inhibition. Only two neurons in the amygdala responded selectively during recognition.
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We next examined the relationship of the neuronal responses, excitatory and inhibitory, during presentation of faces to the specific attributes of the faces, i.e. gender and emotional expression. We performed analysis of variance on the discharge rates of all the neurons that responded significantly to faces during T1 or T2 (see Materials and Methods). There were 73 such neurons, 38 with excitatory responses and 35 with inhibitory responses (not all were selective to faces only). Of these 73 neurons, 19 discriminated between facial expressions (Fig. 2) or the gender of faces (Fig. 6b
) or between conjunctions of gender and expression. These neurons were considered discriminative neurons. Of the 38 neurons with excitatory responses 15 (39.5%) were discriminative cells, while of the 35 neurons with inhibitory responses only four (11.4%) were discriminative (Fig. 6a
; see Fig. 6c
for an example of a nondiscriminative cell). Thus the proportion of discriminative cells was higher for neurons with excitatory responses compared to those with inhibitory responses (
2 = 7.44; P = 0.008). Similar proportions were observed for the hippocampal neurons alone (46.7% and 15.8% for the cells with excitatory and inhibitory responses, respectively).
Recognition Performance
Is the neuronal activity during recognition related to the subject's performance? We considered the neuron activity performance selective if (i) the response (during T1 and/or T2) of the neuron during correct performance was different from the response during incorrect performance and (ii) the response of the neuron was significant either during correct retrieval or during incorrect retrieval (or during both if the responses were of opposite sign). During recognition of faces there were 26 (14.7%) performance selective units, most of them (19) with inhibitory responses. The majority of these units responded during correct performance and not during incorrect performance (12 of 19 units). Seven units had the opposite pattern. Only seven performance-selective neurons had excitatory responses, and five of these responded during incorrect performance. No units exhibited opposite sign responses for correct and incorrect performance, i.e. excitatory response for correct responses and inhibitory for incorrect responses or vice versa. Object recognition showed a similar but less striking pattern of performance-related responses. Of 30 performance-selective units, 17 had inhibitory responses (10 during correct performance), and 13 had excitatory responses (only six during correct performance).
Were the unit responses during encoding related to the subsequent performance on the recognition task? For the neuron to be considered performance selective (i.e. performance predictive) during encoding of stimuli, we applied the same criteria mentioned above (see also Materials and Methods section) to the activity of the neuron during encoding based on the subsequent performance on recognition of these stimuli. There were 21 such units for encoding of faces and 21 for encoding of objects. The majority of these units had excitatory responses (for faces, 12 excitatory and 9 inhibitory; and for objects, 13 excitatory, six inhibitory and two inhibitory for correct and excitatory for incorrect performance). There were no significant differences between the number of units responding to items that were subsequently recognized and of those responding to items that were not recognized.
Neuronal Responses in Dominant versus Nondominant MTL
Of the 225 neurons recorded during encoding, 88 were in the dominant hemisphere, 117 in the nondominant hemisphere and 20 in a patient with bilateral hemispheric dominance. Of the 88 dominant MTL neurons 35 (40%) were responsive to faces during either T1 or T2 (24% excitatory and 16% inhibitory), whereas of the 117 nondominant neurons 34 (29%) were responsive to faces (13% excitatory and 16% inhibitory). There was no significant difference between the proportions of neurons responding to faces in the dominant versus non-dominant hemisphere (2 = 2.58; P = 0.14). In the nondominant hemisphere a relatively uniform sampling of the regions was obtained (38 amygdala units, 42 hippocampal units and 37 units from entorhinal cortex), thus enabling a comparison of the distribution of excitatory and inhibitory responses among the regions.
Altogether, 32 cells in the nondominant temporal lobe responded to faces (not all were selective to faces only). In these neurons a pattern of predominantly excitatory responses to faces in the amygdala and inhibitory responses in the hippocampus and entorhinal cortex (recorded during T1 and/or T2) was evident. In the amygdala 12 of the 14 responding cells had excitatory responses and two had inhibitory responses. In the hippocampus only two out of the 12 responding neurons showed excitatory responses and 10 cells showed inhibitory responses. In entorhinal cortex only one of eight responding cells showed excitatory responses and seven had inhibitory responses [overall 2 = 16.74, d.f. = 2, P = 0.0002; for pairwise comparison there are significant differences in the distribution of excitatory and inhibitory responses between the amygdala and hippocampus (
2 = 12.4, P = 0.001) and between the amygdala and entorhinal cortex (
2 = 11.3; P = 0.0015) but not between the hippocampus and entorhinal cortex)].
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Discussion |
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The main finding in this study is the striking prevalence of stimulus-related inhibitory responses in the hippocampus and to a lesser degree in the entorhinal cortex during the recognition memory paradigm. These responses were more prevalent for faces compared to objects and during retrieval compared to encoding. The hippocampus is known to have an extensive inhibitory network, and the pyramidal cells are influenced by inhibitory local interneurons as well as by extrahippocampal inhibitory input [see Buhl et al. (Buhl et al., 1994), and for a review, Freund and Buzaki (Freund and Buzaki, 1996)]. Yet to our knowledge the abundance of inhibitory responses found in our recordings in the human hippocampus has not been observed in cognitive paradigms in the monkey hippocampus. These inhibitory responses reflect either a reduction in excitation or an increase in inhibition of the responding cells. A reduction in excitatory responses has been described in nonhuman primate studies upon repeated stimulus presentation (match suppression), and is thought to represent stimulus recognition (Desimone, 1996
; Suzuki, 1999). However, these responses were diminished compared to the first response, whereas the inhibitory responses observed in the present study involved reduction of firing rate below prestimulus baseline. Often the neurons were virtually shut down for several hundred milliseconds following stimulus presentation (Fig. 6c
). This observation is of particular interest since inhibitory responses have received less attention than excitatory responses in cognitive studies of non-human primates, although such responses have been described in human temporal neocortex during language measures [for a review, see Ojemann et al. (Ojemann et al., 1998
)]. While the abundance of inhibitory responses during the memory task could be unique to the human hippocampus and entorhinal cortex, another plausible explanation for the discrepancy is methodological, namely a sampling bias in many animal extracellular recordings, where the electrode is commonly moved to find cells with increased firing rate using audio monitoring (Miller et al., 1993
). In contrast, for clinical reasons, the microelectrodes in the present study were fixed and could not be moved in search of an optimal excitatory response. It is possible, however, that the prevalence of inhibitory responses is a function of the epileptic brain. Although we have not seen differences in prevalence of inhibitory responses between the seizure focus and other areas or even between neurons in the hemisphere which included the seizure focus compared with the other hemisphere, it is still possible that these patients with intractable seizures have a disturbance of normal inhibitory function (Engel, 1996
) even outside the area of the seizure focus.
Selectivity of Responses
There is evidence that neurons in the human MTL respond selectively to particular stimuli (Heit et al., 1988, 1990
), to stimulus categories (Fried et al., 1997
; Kreiman et al., 2000a
,b
) and to specific stimulus features such as the gender and emotional expression of faces (Fried et al., 1997
). The present study confirms these specific responses with respect to faces and objects. Single unit recordings in the monkey MTL have shown selective responses to stimulus categories and stimulus features. Neurophysiological studies of nonhuman primates have shown selective responses of amygdalar neurons to faces (Rolls, 1981
, 1984
; Leonard et al., 1985
; Nakamura et al., 1992
) and to objects of biological significance [see the review by Ono et al. (Ono et al., 1993
)]. Several animal studies reported coding of stimulus and task variables and their conjunctions by single hippocampal neurons (Cahusac et al., 1989
; Rolls et al., 1989
; Ono et al., 1991
; Eifuku et al., 1995
). Suzuki et al. report that 11% of the neurons in monkey entorhinal cortex show selective responses (Suzuki et al., 1999). What is only rarely addressed in these studies is the issue of selectivity of inhibitory and excitatory responses.
We show that the inhibitory responses observed in the hippocampus and entorhinal cortex show relative specificity to faces. The overwhelming majority of the selective responses to faces during the memory task are inhibitory. Interestingly, the majority of specific responses to objects in this study were excitatory. At the same time, the more selective cells, i.e. those with selective responses to specific features of faces, were predominantly excitatory. These cells could be pyramidal neurons in the hippocampus, which in animal studies have been shown to have highly selective responses [e.g. place cells in rodent hippocampus (O'Keefe et al., 1998)]. Conversely, the cells with inhibitory responses may be hippocampal interneurons (Buhl et al., 1994
; Freund and Buzaki, 1996), or pyramidal cells that are strongly influenced by inhibitory neurons. Support for selective responses of interneurons, albeit with broader tuning than pyramidal cells, has been reported in studies of primate prefrontal cortex (Rao et al., 1999
, 2000
). It is important to point out though, that suggestions about the identity of the cells recorded in our study must be viewed with caution, since distinguishing between pyramidal cells and interneurons, based on extracellular recordings, is difficult. Several criteria, including discharge frequency, spike duration and the autocorrelation function, have been used in attempts to separate pyramidal cells from interneurons in the rodent hippocampus [for a review, see Csicsvari et al. (Csicsvari et al., 1999
)]. In the present study, we have not seen any consistent difference between the cells with inhibitory and excitatory responses in terms of discharge frequency, spike duration or propensity for bursting.
Encoding versus Retrieval
The differential contribution of various MTL structures in encoding versus retrieval has been a major focus of neuroscience research of declarative memory. Based on neuroimaging studies, various suggestions have been made that anterior or posterior MTL regions (Stern et al., 1996; Lepage et al., 1998
; Schacter and Wagner, 1999
) or different MTL structures (Gabrieli et al., 1997
; Aggleton and Brown, 1999; Brown and Aggleton, 2001
) are functionally specialized for the memory processes of encoding and retrieval. There have also been suggestions of a differential role of the hippocampus in episodic memory and of para-hippocampal and perirhinal cortex in recognition memory (Vargha-Khadem et al., 1997
; Aggleton and Brown, 1999; Eldridge et al., 2000
) [for a review, see Brown and Aggleton (Brown and Aggleton 2001
)]. Our study examined recognition memory and did not address episodic memory. The results support the importance of the MTL in both encoding and recognition, while also suggesting differences in the neuronal mechanisms involved in these processes. Similar to our previous findings with word encoding (Cameron et al., 2001
), and in line with reports from fMRI studies (Brewer et al., 1998
; Wagner et al., 1998
), we found that the activity of some MTL neurons during encoding of faces and objects predicted subsequent performance of the subject during retrieval. The majority of these neurons had excitatory responses. During recognition, more neurons with inhibitory response were recruited, especially in the hippocampus and entorhinal cortex, suggesting a more prominent role for inhibition during recognition than during encoding. Overall, we found that the activity of ~15% of MTL neurons during recognition of faces reflected the subject's performance. Most of these neurons had inhibitory responses, more commonly during correct rather than incorrect performance. It is also noteworthy that in a previous study of human MTL neurons which employed a perceptual discrimination rather than a memory task the prevalence of inhibitory responses in the hippocampus was less prominent (Kreiman et al., 2000a
). Yet, in a recent paired associate memory task, we found that the majority (60%) of significant responses of hippocampal neurons to word stimuli were inhibitory (Cameron et al., 2001
).
While the present study corroborates fMRI findings demonstrating MTL activation during encoding and retrieval [see, among others (Gabrieli et al., 1997; Dolan and Fletcher, 1999
; Schacter and Wagner, 1999
)], it also raises the question of how changing patterns of excitatory and inhibitory responses may be translated into hemodynamic responses. In that light, it is perhaps not surprising that early attempts at measuring activation of hippocampus by functional neuroimaging have met with difficulty (Ungerleider, 1995
; Schacter and Wagner, 1999
), and that some studies have suggested the functional importance of decreases in activation (Andreasen et al., 1995
; Buckner and Tulving, 1995
; Nyberg et al., 1996
). Recent studies have also pointed out the complexity of establishing a baseline of MTL activation, raising the possibility that stimulus-related changes during the task may represent less excitation than during the baseline (Eldridge et al., 2000
; Stark and Squire, 2000
, 2001
).
Regional and Hemispheric Differences
In contrast to the sparse excitatory representation of faces in the hippocampus (and to a lesser extent the entorhinal cortex), the amygdala had a robust excitatory code with no inhibitory responses during the first second of face presentation. Moreover, when the category-selective responses are considered for both T1 and T2 all the selective responses to faces were excitatory (and all responses to objects inhibitory). The opposite pattern was observed in the hippocampus (all responses to faces inhibitory and all responses to objects excitatory). However, these results should be considered preliminary, since the number of selective neurons is small (~12% of all 225 recorded neurons during encoding), and this is particularly true for the amygdala where the number of sampled units was relatively small compared to the hippocampus and entorhinal cortex. Comparison of the responding neurons in the nondominant hemisphere where sampling across the three MTL regions was more uniform, confirms the pattern of excitatory responses to faces in amygdala and inhibitory responses in the hippocampus during encoding.
Excitatory coding for faces in the amygdala during encoding may reflect responses to the affective content of the facial expressions, confirming the wealth of evidence that the amygdala functions as a fast conduit for reaction to emotionally charged stimuli (LeDoux, 1998) and a modulator of declarative memory for emotionally arousing events (Cahill and McGaugh, 1990
, 1998
; McGaugh et al., 1996
). The poor response of amygdala units on repeat presentation of faces during recognition lends further support to the observation of rapid habituation to face stimuli in this region (Breiter et al., 1996
).
Despite the presumed specialization of the nondominant hemisphere to processing of faces, we did not observe significant differences in neuronal responses to faces in the dominant versus nondominant temporal lobe. This is not unexpected since responses of single units do not always reflect hemispheric differences. For instance, Ojemannn et al. (Ojemannn et al., 1992) found responses of single units to verbal stimuli in the nondominant hemisphere [reviewed in Ojemann et al. (Ojemann et al., 1998)].
Patterns of Excitation and Inhibition
Our results suggest that it is the distributed pattern of excitation and inhibition that reflects involvement of a region in a task. Such patterns have been observed in the olfactory cortex, where each odor has been shown to elicit a specific and widely distributed pattern of excitatory and inhibitory responses (Tanabe et al., 1975; Haberly and Bower, 1989
). In visual and somatosensory cortex, inhibition may serve to highlight feature-specific excitatory responses and sharpen the distinction between neighboring stimulus patterns. Several studies suggest that GABAA-mediated inhibition plays an important role in spatial selectivity in primary visual and somatosensory cortices and in prefrontal cortex. Application of GABAA receptor antagonists results in (i) reduction of directional selectivity (Murphy and Humphrey, 1999
) and broadening of orientation tuning (Sillito, 1984
; Sato et al., 1996
) in primary visual cortex, (ii) increase in size of receptive fields in somatosensory cortex (Alloway et al., 1989
; Alloway and Burton, 1991
), (iii) loss of spatial tuning in both pyramidal cells and interneurons in the monkey prefrontal cortex [although a minority of units, show establishment of previously absent spatial tuning (Rao et al., 2000
)], and (iv) of particular relevance to our study, changes in the specificity of neuronal responses to specific visual stimuli in monkey inferotemporal cortex (Wang et al., 2000
). Several studies also suggest that inhibition plays an important role in working memory. Disruption of spatial tuning of neurons during mnemonic tasks (Rao et al., 2000
) as well as impairment on actual performance of a delayed response task (Sawaguchi et al., 1988
, 1989
) have been demonstrated in the monkey with application of GABAA receptor antagonist into the dorsal prefrontal cortex. Models of hippocampal function emphasize sparse coding (Marr, 1972
; McNaughton and Morris, 1987
), where a small proportion of the neurons are excited and information is transmitted with relatively few spikes. Such coding serves to minimize interference between stored representations of the environment (Trevis and Rolls, 1994
; Eichenbaum, 1997
), and also has been described for processing of faces in inferotemporal cortex (Young and Yamane, 1992
). Our finding of a relatively small pool of neurons with excitatory responses coding for stimulus features suggests sparse coding of faces in the human hippocampus as well. Moreover, the prevalence of inhibitory responses may make such sparse coding more effective, highlighting the specific excitatory responses and thus reducing the probability of misfiring with resultant spurious encoding or recognition (e.g. mistaking one face for another).
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Acknowledgments |
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